171 77 9MB
English Pages 830 Year 2008
Elsevier Radarweg 29, PO Box 211, 1000 AE Amsterdam, The Netherlands Linacre House, Jordan Hill, Oxford OX2 8DP, UK
First edition 2008 Copyright r 2008 Elsevier B.V. All rights reserved No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (+44) (0) 1865 843830; fax (+44) (0) 1865 853333; email: [email protected]. Alternatively you can submit your request online by visiting the Elsevier web site at http:// www.elsevier.com/locate/permissions, and selecting Obtaining permission to use Elsevier material Notice No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress ISBN: 978-0-444-53019-6 ISSN: 0166-526X
For information on all Elsevier publications visit our website at books.elsevier.com
Printed and bound in Hungary 08 09 10 11 12 10 9 8 7 6 5 4 3 2 1
ADVISORY BOARD Joseph A. Caruso University of Cincinnati, Cincinnati, OH, USA Hendrik Emons Joint Research Centre, Geel, Belgium Gary Hieftje Indiana University, Bloomington, IN, USA Kiyokatsu Jinno Toyohashi University of Technology, Toyohashi, Japan Uwe Karst University of Mu¨nster, Mu¨nster, Germany Gyo¨rgy Marko-Varga AstraZeneca, Lund, Sweden Janusz Pawliszyn University of Waterloo, Waterloo, Ont., Canada Susan Richardson US Environmental Protection Agency, Athens, GA, USA
Wilson & Wilson’s
COMPREHENSIVE ANALYTICAL CHEMISTRY
Edited by ´ D. BARCELO Research Professor Department of Environmental Chemistry IIQAB-CSIC Jordi Girona 18-26 08034 Barcelona Spain
Wilson & Wilson’s
COMPREHENSIVE ANALYTICAL CHEMISTRY FOOD CONTAMINANTS AND RESIDUE ANALYSIS
VOLUME
51 Edited by ´ YOLANDA PICO Laboratori de Bromatologia i Toxicologia Facultat de Farmacia Universitat de Valencia Av. Vicent Andre´s Estelle´s s/n. 46100 Burjassot Valencia, Spain
Amsterdam Boston Heidelberg London New York Oxford Paris San Diego San Francisco Singapore Sydney Tokyo
CONTRIBUTORS TO VOLUME 51
Wendy C. Andersen US FDA, Animal Drugs Research Center, Denver Fed Ctr, Lakewood, CO 80225, USA Jean-Philippe Antignac LABERCA-Ecole Nationale Ve´te´rinaire de Nantes, Route de Gachet, BP 50707, F-44307 Nantes Cedex 3, France Ioannis S. Arvanitoyannis University of Thessaly, School of Agricultural Sciences, Fytokou Str., 38446 Nea Ionia Magnesias, Volos, Greece Damia` Barcelo´ Department of Environmental Chemistry, IIQAB-CSIC, Jordi Girona 18, 08034 Barcelona, Spain Carlo Brera Istituto Superiore di Sanita`, Centro Nazionale per la Qualita` degli Alimenti e per i Rischi Alimentari, Reparto OGM e Xenobiotici di origine fungina, Viale Regina Elena, 299, 00161 Rome, Italy Sergio Caroli Instituto Superiore di Sanita, Viale Regina Elena, 299, 00151 Rome, Italy Leon Coulier Analytical Research Department, TNO Quality of Life, Utrechtseweg 48, 3700 AJ Zeist, The Netherlands Adrian Covaci Toxicological Centre, Department of Pharmaceutical Sciences, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Belgium and Ecophysiology, Biochemistry and Toxicology Group, Department of Biology, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp, Belgium Frank David Research Institute for Chromatography, Kennedypark 26, B-8500 Kortrijk, Belgium
xiii
xiv
Contributors to Volume 51
Francesca Debegnach Istituto Superiore di Sanita`, Centro Nazionale per la Qualita` degli Alimenti e per i Rischi Alimentari, Reparto OGM e Xenobiotici di origine fungina, Viale Regina Elena, 299, 00161 Rome, Italy Edwin De Pauw Department of Chemistry, Laboratory of Mass Spectrometry, CART (Centre of analysis of residues in trace), University of Liege, Alle´e de la Chimie, 6, Bat B6c, Sart Tilman, B-4000 Liege, Belgium Barbara De Santis Istituto Superiore di Sanita`, Centro Nazionale per la Qualita` degli Alimenti e per i Rischi Alimentari, Reparto OGM e Xenobiotici di origine fungina, Viale Regina Elena, 299, 00161 Rome, Italy Kyle D’Silva Waters Corporation, Atlas Park, Simonsway, Manchester, M22 5PP, UK Gauthier Eppe Department of Chemistry, Laboratory of Mass Spectrometry, CART (Centre of analysis of residues in trace), University of Liege, Alle´e de la Chimie, 6, Bat B6c, Sart Tilman, B-4000 Liege, Belgium Marinel la Farre´ Environmental Chemistry, Spain
IIQAB-CSIC,
Jordi
Girona
18,
08034
Barcelona,
James S. Felton Chemistry, Materials, and Life Sciences Directorate, Lawrence Livermore National Laboratory, University of California, Livermore, California, USA Jean-Franc- ois Focant Department of Chemistry, Laboratory of Mass Spectrometry, CART (Centre of analysis of residues in trace), University of Liege, Alle´e de la Chimie, 6, Bat B6c, Sart Tilman, B-4000 Liege, Belgium Ambrose Furey PROTEOBIO, Mass Spectrometry Centre for Proteomics and Biotoxin Research, Cork Institute of Technology, Bishopstown, Cork, Ireland Javier Garcı´a Ferna´ndez PROTEOBIO, Mass Spectrometry Centre for Proteomics and Biotoxin Research, Cork Institute of Technology, Bishopstown, Cork, Ireland Till Goldmann Nestle´ Research Centre, P.O. Box 44, CH 1000 Lausanne 26, Switzerland
Contributors to Volume 51
xv
Stuart Harrad Division of Environmental Health and Risk Management, Public Health Building, School of Geography, Earth, and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK Geert Houben Analytical Research Department, TNO Quality of Life, Utrechtseweg 48, 3700 AJ Zeist, The Netherlands Janice Huwe Biosciences Research Laboratory, USDA-ARS, P.O. Box 5674, University Station, Fargo, North Dakota 58105, USA Kevin J. James PROTEOBIO, Mass Spectrometry Centre for Proteomics and Biotoxin Research, Cork Institute of Technology, Bishopstown, Cork, Ireland Mark G. Knize Chemistry, Materials, and Life Sciences Directorate, Lawrence Livermore National Laboratory, University of California, Livermore, California, USA Sander Koster Analytical Research Department, TNO Quality of Life, Utrechtseweg 48, 3700 AJ Zeist, The Netherlands Bruno Le Bizec LABERCA-Ecole Nationale Ve´te´rinaire de Nantes, Route de Gachet, BP 50707, F-44307 Nantes Cedex 3, France Winfried Leeman Analytical Research Department, TNO Quality of Life, Utrechtseweg 48, 3700 AJ Zeist, The Netherlands Clinio Locatelli Department of Chemistry ‘‘G. Ciamician’’, University of Bologna, Via F. Selmi 2, I-40126 Bologna, Italy and CIRSA (Centro Interdipartimentale di Ricerca per le Scienze Ambientali), Laboratory of Environmental Analytical Chemistry, University of Bologna, Via S. Alberto 163, I-48100 Ravenna, Italy Guy Maghuin-Rogister Department of Food Sciences, Laboratory of Food Analysis, CART (Centre of analysis of residues in traces), University of Liege, Boulevard de Colonster, 20, Bat B43-bis, Sart Tilman, B-4000 Liege, Belgium Elena Martı´nez Environmental Chemistry, IIQAB-CSIC, Jordi Girona 18, 08034 Barcelona, Spain
xvi
Contributors to Volume 51
Hans J.P. Marvin RIKILT-Institute of Food Safety, P.O. Box 230, 6700 AE Wageningen, The Netherlands Katerina Mastovska USDA, Agricultural Research Service, Eastern Regional Research Center, 600 East Mermaid Lane, Wyndmoor, PA 19038, USA Marina Miraglia Istituto Superiore di Sanita`, Centro Nazionale per la Qualita` degli Alimenti e per i Rischi Alimentari, Reparto OGM e Xenobiotici di origine fungina, Viale Regina Elena, 299, 00161 Rome, Italy Sidney S. Mirvish Eppley Institute for Research in Cancer, University of Nebraska Medical Center, Omaha, NE 68198-6802, USA Bas Muilwijk Analytical Research Department, TNO Quality of Life, Utrechtseweg 48, 3700 AJ Zeist, The Netherlands Michel W.F. Nielen RIKILT-Institute of Food Safety, P.O. Box 230, 6700 AE Wageningen, The Netherlands and Wageningen University, Laboratory of Organic Chemistry, Dreijenplein 8, 6703 HB Wageningen, The Netherlands Daniel O’Driscoll PROTEOBIO, Mass Spectrometry Centre for Proteomics and Biotoxin Research, Cork Institute of Technology, Bishopstown, Cork, Ireland Ruud Peters Analytical Research Department, TNO Quality of Life, Utrechtseweg 48, 3700 AJ Zeist, The Netherlands Yolanda Pico´ Laboratori de Bromatologia i Toxicologia, Facultat de Farmacia, Universitat de Valencia, Av. Vicent Andre´s Estelle´s s/n, 46100 Burjassot, Valencia, Spain Gaud Pinel LABERCA-Ecole Nationale Ve´te´rinaire de Nantes, Route de Gachet, BP 50707, F-44307 Nantes Cedex 3, France Monique Rennen Analytical Research Department, TNO Quality of Life, Utrechtseweg 48, 3700 AJ Zeist, The Netherlands Rinus Rijk Analytical Research Department, TNO Quality of Life, Utrechtseweg 48, 3700 AJ Zeist, The Netherlands
Contributors to Volume 51
xvii
Claude Saegerman Department of Infectious and Parasitic Diseases, Epidemiology and Risk analysis applied to Veterinary Sciences, University of Liege, Boulevard de Colonster, 20, Bat B42, Sart Tilman, B-4000 Liege, Belgium Pat Sandra Department of Organic Chemistry, University of Ghent, Krijgslaan 281-S4bis, B-9000 Ghent, Belgium Anna Sannino Stazione Sperimentale Conserve Alimentari, Food Safety Department, Viale Tanara, 31/A, 43100 Parma, Italy Georges Scholl Department of Chemistry, Laboratory of Mass Spectrometry, CART (Centre of analysis of residues in trace), University of Liege, Alle´e de la Chimie, 6, Bat B6c, Sart Tilman, B-4000 Liege, Belgium Marie-Louise Scippo Department of Food Sciences, Laboratory of Food Analysis, CART (Centre of analysis of residues in traces), University of Liege, Boulevard de Colonster, 20, Bat B43-bis, Sart Tilman, B-4000 Liege, Belgium Catherine Simoneau Community Reference Laboratory for Food Contact Materials, European Commission, DG-Joint Research Centre, Institute for Health and Consumer Protection, Unit Physical and Chemical Exposure, T.P. 260, Ispra Va 21020, Italy Richard H. Stadler Quality Management Department, Nestle´ Product Technology Centre Orbe, CH 1350 Orbe, Switzerland Katsumi Tamakawa Sendai City Institute of Public Health, 2-5-10, Oroshimachi-higashi, Wakabayashi ward, Sendai city, Miyagi prefecture, 984-0002, Japan Sherry B. Turnipseed US FDA, Animal Drugs Research Center, Denver Fed Ctr, Lakewood, CO 80225, USA William D. van Dongen Analytical Research Department, TNO Quality of Life, Utrechtseweg 48, 3700 AJ Zeist, The Netherlands Leo van Stee Analytical Research Department, TNO Quality of Life, Utrechtseweg 48, 3700 AJ Zeist, The Netherlands Gerd Vanhoenacker Research Institute for Chromatography, Kennedypark 26, B-8500 Kortrijk, Belgium
xviii
Contributors to Volume 51
Peter Viberg Technical Analytical Chemistry, Lund University, Getingeva¨gen 60, PO Box 124, SE-22100 Lund, Sweden Stefan Voorspoels European Commission, Joint Research Centre, Institute for Reference Materials and Measurements (IRMM), Retieseweg 111, 2440 Geel, Belgium Esther Zondervan-van den Beuken Analytical Research Department, TNO Quality of Life, Utrechtseweg 48, 3700 AJ Zeist, The Netherlands
VOLUMES IN THE SERIES
Vol. 1A
Vol. 1B Vol. 1C Vol. 2A
Vol. 2B
Vol. 2C
Vol. 2D Vol. 3
Vol. 4
Vol. 5
Vol. 6 Vol. 7 Vol. 8
Vol. 9
Analytical Processes Gas Analysis Inorganic Qualitative Analysis Organic Qualitative Analysis Inorganic Gravimetric Analysis Inorganic Titrimetric Analysis Organic Quantitative Analysis Analytical Chemistry of the Elements Electrochemical Analysis Electrodeposition Potentiometric Titrations Conductometric Titrations High-Frequency Titrations Liquid Chromatography in Columns Gas Chromatography Ion Exchangers Distillation Paper and Thin Layer Chromatography Radiochemical Methods Nuclear Magnetic Resonance and Electron Spin Resonance Methods X-ray Spectrometry Couiometric Analysis Elemental Analysis with Minute Sample Standards and Standardization Separation by Liquid Amalgams Vacuum Fusion Analysis of Gases in Metals Electroanalysis in Molten Salts Instrumentation for Spectroscopy Atomic Absorption and Fluorescence Spectroscopy Diffuse Reflectane Spectroscopy Emission Spectroscopy Analytical Microwave Spectroscopy Analytical Applications of Electron Microscopy Analytical Infrared Spectroscopy Thermal Methods in Analytical Chemistry Substoichiometric Analytical Methods Enzyme Electrodes in Analytical Chemistry Molecular Fluorescence Spectroscopy Photometric Titrations Analytical Applications of Interferometry Ultraviolet Photoelectron and Photoion Spectroscopy Auger Electron Spectroscopy Plasma Excitation in Spectrochemical Analysis
xix
xx
Volumes in the Series
Vol. 10 Vol. 11 Vol. 12
Vol. 13
Vol. 14 Vol. 15 Vol. 16 Vol. 17 Vol. 18 Vol. Vol. Vol. Vol. Vol.
19 20 21 22 23
Vol. Vol. Vol. Vol. Vol. Vol. Vol. Vol. Vol. Vol. Vol.
24 25 26 27 28 29 30 31 32 33 34
Vol. Vol. Vol. Vol. Vol. Vol. Vol. Vol. Vol.
35 36 37 38 39 40 41 42 43
Vol. 44 Vol. 45 Vol. 46
Organic Spot Tests Analysis The History of Analytical Chemistry The Application of Mathematical Statistics in Analytical Chemistry Mass Spectrometry Ion Selective Electrodes Thermal Analysis Part A. Simultaneous Thermoanalytical Examination by Means of the Derivatograph Part B. Biochemical and Clinical Application of Thermometric and Thermal Analysis Part C. Emanation Thermal Analysis and other Radiometric Emanation Methods Part D. Thermophysical Properties of Solids Part E. Pulse Method of Measuring Thermophysical Parameters Analysis of Complex Hydrocarbons Part A. Separation Methods Part B. Group Analysis and Detailed Analysis Ion-Exchangers in Analytical Chemistry Methods of Organic Analysis Chemical Microscopy Thermomicroscopy of Organic Compounds Gas and Liquid Analysers Kinetic Methods in Chemical Analysis Application of Computers in Analytical Chemistry Analytical Visible and Ultra-violet Spectrometry Photometric Methods in Inorganic Trace Analysis New Developments in Conductometric and Oscillometric Analysis Titrimetric Analysis in Organic Solvents Analytical and Biomedical Applications of Ion-Selective Field-Effect Transistors Energy Dispersive X-ray Fluorescence Analysis Preconcentration of Trace Elements Radionuclide X-ray Fluorecence Analysis Voltammetry Analysis of Substances in the Gaseous Phase Chemiluminescence Immunoassay Spectrochemical Trace Analysis for Metals and Metalloids Surfactants in Analytical Chemistry Environmental Analytical Chemistry Elemental Speciation – New Approaches for Trace Element Analysis Discrete Sample Introduction Techniques for Inductively Coupled Plasma Mass Spectrometry Modern Fourier Transform Infrared Spectroscopy Chemical Test Methods of Analysis Sampling and Sample Preparation for Field and Laboratory Countercurrent Chromatography: The Support-Free Liquid Stationary Phase Integrated Analytical Systems Analysis and Fate of Surfactants in the Aquatic Environment Sample Preparation for Trace Element Analysis Non-destructive Microanalysis of Cultural Heritage Materials Chromatographic-Mass Spectrometric Food Analysis for Trace Determination of Pesticide Residues Biosensors and Modern Biospecific Analytical Techniques Analysis and Detection by Capillary Electrophoresis Proteomics and Peptidomics: New Technology Platforms Elucidating Biology
Volumes in the Series
Vol. Vol. Vol. Vol.
47 48 49 50
Modern Instrumental Analysis Passive Sampling Techniques in Environmental Monitoring Electrochemical (Bio) Sensor Analysis Analysis, Fate and Removal of Pharmaceuticals in the Water Cycle
xxi
PREFACE
All consumers have the right to expect and demand good-quality and safe food at affordable prices. This right was recognized by the participants at the United Nations Conference on Food and Agriculture, held in the United States (US) in 1943, which laid the foundation for the creation of Food and Agriculture Organization (FAO). Because of this, food safety and consumer protection are topics of highest priority. In the same way, producing a food supply safe and of good quality is a prerequisite to successful domestic and international food trade, and a key to sustainable development of national agricultural resources. Chemical analysis is a vital component of every quality management system. Determination of organic contaminants in food needs to continually refine and explore new technologies to enhance sensitivity, selectivity, separation, interpretation, and adaptability of methodology. Though a well-established field in many senses, new methods, instruments, and modifications are decisive to analytical chemists and instrumentalists who are challenged with the identification and quantitation of new and already recognized xenobiotics of health concern. This book treats different aspects of the analysis of contaminants and residues in food, and highlights some current concerns facing this field. The content is initiated by an overview on food safety, the objectives and importance of determining contaminants and residues in food, and the problems and challenges associated to these analyses. This is followed by full details of relevant European and United States regulations. Topics, such as conventional chromatographic methods, accommodating clean up, and preparing substances for further instrumental analysis, are encompassed with new analytical techniques that have significantly been developed over the past few years, like solid phase microextraction, liquid chromatography-mass spectrometry, immunoassays, and biosensors. A wide range of toxic contaminants and residues, from pesticides to mycotoxins or dioxins are examined. This book can be a practical resource that offers ideas on how to choose the most effective techniques for determining these compounds. The book contains 22 chapters written by different experts in each field that cover the emerging topics in food contaminants and residue analysis, and it is organized into three sections: the first one covers the regulatory framework including validation and quality assurance of analytical methods, the second treats the latest developments in analytical techniques, and the third provides information about the determination of specific contaminants and residues in food. Logically structured and with numerous examples Food Contaminants and Residue Analysis is a valuable tool for food analysis as a reference and trained xxiii
xxiv
Preface
guide. The book is addressed to serve as a general reference for post-graduate students, as well as a practical reference guide for a wide range of experts: biologists, biochemists, microbiologists, food chemists, toxicologists, chemists, agronomists, hygienists, and everybody who need to use the analytical techniques for evaluating food safety. Each chapter contains enough references to the literature to help as an effective resource for more detailed information. Many people have collaborated in this project, directly or indirectly, and I would like to acknowledge my debts to them. Prof. Damia` Barcelo´ for the trust put in me to develop this work and for his help and support through this time; the people from the editorial staff of Elsevier (Andrew Gent, Joan Annuels, Anne Russum) for their willingness to solve any problem related to the production of the book and their patience; and finally and foremost, the authors (the edition of this book would not have been possible without their cooperation) and the readership (you are the ones who will make the book an integral part of food contaminants and residue research). I hope the book lives up to the expectations. Yolanda Pico´
S ER I E S E D I TO R ’ S P R E F A C E
Food safety has become a key issue in our society, especially now that much of the food we consume comes from other parts of the world. The public in general is increasingly concerned about the quality of the products they consume every day and to meet that need, more information is being made available in the media. Various cases have become headline news, such as the dioxin problem in Belgium, antibiotics in shrimps imported from Asia to Europe, and the high levels of persistent organic pollutants detected in European salmon as compared to the American salmon. These cases have alerted the authorities and the public in general that more efforts are needed on food control. In this respect this volume edited by my old friend and colleague, Yolanda Pico´, is timely and I am delighted I was able to convince her to collate such a book for the Comprehensive Analytical Chemistry series. This is only the second book on the topic of food residues in the series. The first, collated by another old friend and colleague, AR Fernandez Alba, was entitled Pesticide Residues published as Vol. 43 in the series. I am sure that food safety will be the subject of further volumes in the future. This book contains 19 chapters; the first three are devoted to general aspects of food analysis. Chapters 4 to 8 cover sample preparation techniques, chromatographic-mass spectrometric methods, capillary electrophoresis and immunochemical methods. Chapters 9 to 19 report on analytical applications of a broad range of contaminants, including pesticides, antibiotics, growth promoters, mycotoxins, phycotoxins, persistent organic pollutants brominated flame retardants and heterocyclic amines. The content is comprehensive and covers most of the problems encountered in food residue analysis, so will act as a useful reference for those who are new to the field and/or expert food laboratories. The book discusses most aspects of food contaminant and residue analysis and I expect it will become a key reference for food residue specialists. Finally I would like to thank not only the editor for compiling such a worldclass book but also all the authors for their contributions. D. Barcelo´ Department of Environmental Chemistry, IIQAB-CSIC Barcelona, Spain
xxv
CHAPT ER
1 Challenges in Chemical Food Contaminants and Residue Analysis Michel W.F. Nielen and Hans J.P. Marvin
Contents
1. Introduction 2 1.1 The food chain: A global issue 3 1.2 Issues according to the Rapid Alert System for Food and Feed 4 1.3 Issues according to the feed and food industry 6 1.4 The consumer perception 6 2. Emerging Contaminants 7 2.1 Brominated flame retardants 8 2.2 Perfluorinated organic substances 8 2.3 Endocrine disruptors 9 2.4 Metal speciation 10 2.5 Alkaloid biotoxins 10 2.6 Peptide and protein growth promoters 11 2.7 Genetically modified organisms (GMO) 12 2.8 Nanoparticles 13 3. Masked Contaminants 14 4. Unknown Bioactive Contaminants 15 4.1 Bioactivity-directed identification of emerging unknown contaminants 15 4.2 Metabolomics approach to the identification of emerging unknown contaminants 17 4.3 In silico prediction approach to the identification of unknowns 17 5. Emerging Technologies 18 5.1 Omics 18 5.2 Bioassays 19 5.3 (Bio)nanotechnology 20 5.4 Ambient mass spectrometry 20 6. Validation and QA/QC Challenges 22 6.1 Biochemical or biological rapid screening assays 22 6.2 Comprehensive instrumental analysis methods 23
Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00001-9
r 2008 Elsevier B.V. All rights reserved.
1
2
Michel W.F. Nielen and Hans J.P. Marvin
7. Conclusions and Future Trends Acknowledgements References
24 25 25
1. INTRODUCTION Nowadays food is produced and distributed in a global market leading to stringent legislation and regulation for food quality and safety in order to protect consumers and ensure fair trade. Despite these efforts, food safety incidents occasionally occur and originate from both microbial and chemical contamination. Pesticide and veterinary drug residues, endocrine disruptors, food additives and packaging materials, environmental contaminants (including dioxins and heavy metals) and contaminants of natural origin (including mycotoxins and marine toxins) are of particular concern. As a consequence of the introduction of food commodities containing ingredients produced by modern biotechnology and resulting legal requirements of safety and labeling, a strong additional demand for adequate methods of analysis has occurred. Risk analysis provides a framework for regulatory authorities to protect the consumer from potential food safety hazards and is performed in an iterative manner by food safety managers (regulatory authorities), risk assessors (scientists) and stakeholders (i.e., consumers, industry, non-governmental organizations). The assessment of food safety is a scientific exercise performed by scientists and consists of hazard identification, hazard characterization, exposure assessment and risk characterization. An important prerequisite for performing risk assessment adequately is the presence of data generated by reliable and fit-for-purpose analytical methods to estimate the level of exposure and intake of the consumer to contaminants and residues. Hence, the accuracy of risk assessment will benefit from the availability of comprehensive quantitative monitoring and consumption data. However, cost and time considerations of food safety managers (in regulatory institutions and industry) favour the development and implementation of inexpensive and rapid screening methods having a limited scope and providing qualitative or semiquantitative ‘‘on-off’’ data only. Global food production practices and the changing climate showed that new unexpected food safety hazards and risks may appear in the food and feed production chain stressing the need for analytical tools capable of early warning for such emerging risks. Some of these potential food safety hazards and methodologies capable of detecting known and unknown emerging contaminants are discussed and related challenges defined. It is argued that monitoring programmes should anticipate these new conspicuous threats. In this context a key role is proposed for bioactivity-based screening concepts and bioactivity-directed identification tools. The development of both rapid screening methods and comprehensive tools covering as many contaminants as possible including emerging and even unknown contaminants is justified by the different needs from food safety
Challenges in Chemical Food Contaminants and Residue Analysis
3
stakeholders. The rapid screening developments are facing the challenge of multiplex detection in order to extend their scope, the comprehensive methods on the other hand are facing major challenges in generic sample preparation and advanced data evaluation.
1.1 The food chain: A global issue The food chain as schematically represented by Figure 1 is rather complex and many factors worldwide play a role in the final issue of food quality and safety. Raw materials for feed and food production come from all over the world with very different local climate, harvesting and storage conditions, all having an impact on the occurrence of microbiological and chemical contaminants such as mycotoxins, pesticide residues, environmental pollution and packaging migrants. The feed producer will mix different raw materials according to its specifications and add additives such as stabilizers but in some cases also medication. Medicated feed production can cause drug residues in nonmedicated feed produced at the same facility due to carry-over. Next, the feed is transported to the first consumer level, i.e., the farm animals. The increased awareness of animal welfare might put a stronger demand on feed-related riskbenefit issues. At the farm stage again additives, but also pesticides, veterinary drugs or even illegal hormones might be applied, which residues and/or metabolites can again build up in the food chain. The food industry produces food products and/or food ingredients but they also yield a waste stream which is at least partly recycled and used as feed ingredient. Packaging into smaller
Raw material
Retailers
Feed
Farmers +animals
Industry, processing
Figure 1 Simplified representation of the food chain.
Consumers
4
Michel W.F. Nielen and Hans J.P. Marvin
pieces might increase the migration issue of chemicals from the packaging into the food commodity. Following transport the final products come to the retailers where a storage issue might influence the final contamination load. Products being beyond the storage limit date might be recycled and end up in the feed stream again. Finally the consumer buys food that must be stored and prepared for cooking, actions known for their potential introduction of contaminants if hygiene guidelines are not followed. During cooking, food processing contaminants, such as acrylamide, heterocyclic amines and polycyclic hydrocarbons, are introduced but some of the contaminants present might be degraded (or bioactivated) so the real load of dietary intake of contaminants is not so easy to determine. The occurrence of residues from intentionally added chemicals somewhere in the food chain can in theory be avoided, but very much depends on the attitude and behaviour of the actors in the food production chain. Retrospective studies on recent food safety incidents have shown that the human factor (unawareness, fraudulent and illegal actions) plays an important role in the development of food safety incidents [1]. Globalization of food trade, changing climate conditions and agricultural practices, changing food consumption patterns and environmental pollution are all drivers of food safety risks and should be taken into account in systems aimed at identifying emerging food safety hazards and risks. Control of food safety standards, monitoring of contaminants and knowledge about the fate of food contaminants through the entire food chain is needed thus requiring the availability of analysis methods dedicated to the different parts and their actors within the chain.
1.2 Issues according to the Rapid Alert System for Food and Feed The Rapid Alert System for Food and Feed (RASFF) is primarily a tool for exchange of information between food and feed authorities in the European Union (EU) member states in cases where a risk to human health has been identified and measures have been taken, such as withholding, recalling, seizure or rejection of the products concerned. The European Commission (EC) publishes weekly overviews of RASFF alert and information notifications on its website, and the summarizing annual reports provide an overview of the numbers of notifications and the categories of food products and hazards that they pertained to [2]. These annual reports also highlight conspicuous developments within the particular year. Kleter et al. [3] have explored the utility of notifications filed through RASFF to identify emerging trends in food safety issues. To this end RASFF information and alert notifications published in the four-year period of July 2003–June 2007 amounting to a total of 11,403 notifications were divided into categories and analysed. The breakdown per hazard category is given in Figure 2. The major categories included chemical (44%), mycotoxins (29%) and microbiological hazards (17%), which together accounted for the majority of the notifications (90%). Within the chemical hazard category, contaminants in products from seafood (30%) and spices and condiments (15%) were the most commonly reported. The most frequently reported are allergens (e.g., sulfite and
Challenges in Chemical Food Contaminants and Residue Analysis
5
Hazards reported through RASFF July 2003 - June 2007 (12,641 hazards)
Chemical Mycotoxin Microbiological Others, including fraud, biological hazards, labeling, chemical hazards, quality, hygiene, defective packaging and others
Figure 2 Breakdown of food chain hazards according to Kleter et al. [3].
histamine), heavy metals (e.g., cadmium, mercury and lead), veterinary antibiotics (e.g., the nitrofurans; furazolidone and nitrofurazone, as well as chloramphenicol), dyes (e.g., Sudan 1 and 4) and pesticides (e.g., dimethoate, isophenfos-methyl and omethoate). Aflatoxins account for the majority (93%) of mycotoxins and are mainly (84%) found in nuts, of which (54%) have been imported from Iran. Microbial contaminants include moulds, viruses and bacteria. Bacteria species were most frequently reported of which Salmonella and its subspecies were the most numerous (57% of the reports) followed by Listeria monocytogenes (16%). It should be noted that the number of reports in the RASFF not necessarily reflects the extent of a specific food safety problem because the nature of the RASFF system implicitly yields a multiplication of a specific finding. Based on warnings from the EU member states authorities in other countries will check suspicious lots which will give an additional RASFF notification. Secondly, cost and time considerations limit the scope of survey and monitoring programs, hence many potential food safety hazards will not be monitored at all or at best be accidentally picked up. The application of more generic screening methods such as bioassays in routine monitoring programs may circumvent this problem and increase the chance of finding new (re)emerging food safety hazards. In general, EC regulators and legislators require the availability of fit-for-purpose analysis methods having a comprehensive contaminant scope in order to provide the data for risk assessment, the establishment of maximum residue limits and the development and execution of monitoring plans. Harmonization of validated methods and interpretation of results is a prerequisite in order to allow their use in data banks and to avoid internal and external trade disputes.
6
Michel W.F. Nielen and Hans J.P. Marvin
1.3 Issues according to the feed and food industry According to the General Food Law [4], the producers are responsible for the safety of food and feed they produce, storage, transport, selling (or eventually dispose), tracking and tracing. They should not place unsafe food or feed on the market, and should have a full traceability system for rapid withholding and recalling in case of alerts. Last but not least, unsafe situations should be prevented using critical control points hazard analyses (HACCP) and good manufacturing practices. Because of this responsibility and associated demand to maintain their core product integrity the need of the industry for rapid and inexpensive screening methods has never been greater. It is obvious that unloading an incoming ship or truck carrying raw materials cannot wait for the results from a full comprehensive contaminant analysis; a first screening result should be available in minutes, not days. As a compromise a limited number of key expected contaminants will be rapidly tested by, for example, dipstick-like screening assays, and other contaminant parameters will be checked less frequently. Ideally a rapid screening test would allow the detection of all relevant contaminants and still be inexpensive. But reality is far from that, putting a strong demand for international cooperation on the development of rapid multi-detection methods for chemical contaminants in the food chain.
1.4 The consumer perception Generally food consumers prefer high quality and intrinsically safe food for a low price, but they are also aware of food-related health and safety concerns. Following the request of the European Food Safety Authority (EFSA) and the EC DG-SANCO a special Eurobarometer was carried out in 2005 aiming at an assessment of how people in the EU perceive risk focusing particularly on food safety [5]: 42% of the EU citizens thought that their health could be damaged by the food they eat or by other consumer goods. When they were asked to freely associate the food-related problems they mentioned most often food poisoning (16%), immediately followed by chemicals including pesticides and toxic substances (14%) and obesity (13%). However, following a reminder of possible risks they expressed widespread concerns having on top of their ‘‘worry-scale’’ pesticide residues in fruit, vegetables or cereals and residues such as antibiotics or hormones in meat. In the mid-range environmental pollutants like mercury or dioxins were considered. Surprisingly EU citizens are less concerned about their personal factors such as food hygiene and food preparation (including preparation induced chemical risks). Asked about regulatory consumer protection 62% agreed that food safety laws are strict, despite some reservations regarding their enforcement. Concerning information sources consumers, physicians and scientists were trusted most while economic actors such as farmers, manufacturers and retailers are the least trusted. According to the same Eurobarometer consumers when they go for shopping indeed go for high quality (42%) and low pricing (40%). Although being based on almost 25,000 interviews (approximately 1,000 per member state) these data should be considered as an
Challenges in Chemical Food Contaminants and Residue Analysis
7
estimation only. Classical chemical residues and contaminant issues were mentioned but, for example, natural contaminants such as toxins were obviously not considered and/or unknown by the interviewers and the respondents. Moreover consumers might show irrational behaviour in answering questions: they tend to underestimate the safety aspect related to their own lifestyle with respect to food hygiene during storage and cooking and to overestimate the external risk of chemical residues. Recently Verbeke et al. [6] discussed why consumers behave as they do with respect to food safety and risk information. Some irrational and inconsistent behaviours were explained based on the nature of the risk and individual psychological processes. Improvement of traceability and labeling, segmented communication approaches and public involvement in risk management decision making might contribute to restore consumer confidence and reduce the gap between risk perception of consumers and experts. Also the consumer expectations regarding food safety and quality require the availability of fit-for-purpose analysis methods having a comprehensive contaminant scope. Harmonization of methods and interpretation of results is again a prerequisite: consumers tend to trust scientists but they will get much more worried when scientists provide contradictory information!
2. EMERGING CONTAMINANTS An emerging risk is an issue that in the future may pose a risk to human health, to animals or the environment [7]. In Europe, regulation (EC) No 178/2002 includes the responsibility of identification of such emerging risks [4]. The indication of an emerging risk may relate to a significant exposure to a hazard not recognized earlier or to a new/increased exposure to a known hazard. Some current and potential future emerging risk issues are listed in Table 1.
Table 1
Some current and potential future emerging risks in the food chain
Abbreviation
Description
EFSA opinion
BFR PFOS ER Metals
Brominated flame retardants Perfluorinated organic substances Endocrine disruptors Arsenic, cadmium, lead, mercury, methylmercury, organotin Pyrrolizidine and ergot toxins Abuse of peptide and protein growth promoters Gene modification of plants and gene doping of animals Nanoparticles
Yes Requested No Yes
Alkaloids Proteins GMO Nano
Yes No Yes No
8
Michel W.F. Nielen and Hans J.P. Marvin
2.1 Brominated flame retardants Brominated Flame Retardants (BFRs) such as polybrominated diphenylethers (PBDEs) and hexabromocyclododecane isomers (HBCD) are widespread occurring in the environment and belong to the group of persistent organic pollutants (POPs): BFRs show persistence in the environment like their polychlorinated biphenyls (PCBs) and dioxins/dibenzofurans (PCDDs/PCDFs) analogues. BFRs are suspects for various toxic effects, including endocrine disruption which might be enhanced following in vivo hydroxylation. The EFSA has drafted an opinion on PCBs [8] and advice on relevant compounds in the BFR group. It can be expected that BFRs occur in the food chain accompanied by several other POPs in different concentrations (PCBs, PCDD/PCDF, PAH, chlorinated pesticides). The complex mixture thus obtained requires analysis methods having a huge separation and identification power. Comprehensive gas chromatography combined with time-of-flight mass spectrometry (GC GC/TOFMS) is an expensive but comprehensive solution to the analysis of BFRs and related substances in the food chain [9,10]. Contrary to conventional techniques, implementation of a GC GC/TOFMS multi-analyte/multi-class strategy in food safety control seems feasible, provided that an adequate solution is found for the automated data interpretation challenge related to the very large fourdimensional datasets. Apart from that, the development of bioactivity-based screening approaches remains challenging since they can not only provide an additional screening tool, but even disclose the presence of unknown bioactive pollutants. The DR-CALUXs, an aryl hydrocarbon receptor-based transcription activation bioassay, is being used for dioxin screening in several laboratories [11]. Also a surface plasmon resonance (SPR) biosensor assay for measurement of the thyroid disrupting activity of hydroxylated halogenated aromatic pollutants has been described based on binding with specific human transport proteins [12]. A real comprehensive exposure assessment would integrate the data from these entirely different but highly complementary approaches.
2.2 Perfluorinated organic substances Perfluorinated compounds (PFCs) or perfluorinated organic substances (PFOS) are used in a wide variety of industrial applications [13]. As a consequence these compounds show a global distribution in the environment [14]. They have been detected not only in environmental samples and fish but also in human blood and liver, and in several wildlife species [15]. PFOS show persistence in the environment and some of them have been related to different carcinogenic actions, for example, perfluorooctanoic acid has been identified as a potent hepatocarcinogen in rodents [16]. Meanwhile PFOS have been recognized by the EFSA and concentration levels, contamination pathways and toxicological potency should be assessed in the food chain. So far most of the analysis methods are based on liquid chromatography coupled to mass spectrometry or tandem mass spectrometry approaches (LC/MS,
Challenges in Chemical Food Contaminants and Residue Analysis
9
LC/MS/MS) preceded by solid-phase extraction. A key issue is the avoidance of contamination during sampling, storage and analysis: PFOS are everywhere inside the laboratory and its instruments. The specific chemical and physical properties of PFOS hinder the development of rapid screening methods: it is for example unlikely that antibodies can be raised successfully against the PFOS family, no biorecognition-based methods have been reported yet. Still many challenges remain even for the LC/MS approach: the development of simplified sample preparation protocols and harmonization of methods are key issues anyway.
2.3 Endocrine disruptors Many contaminants occurring in the food chain can be considered as endocrine disruptors: certain pesticides, POPs and metabolites thereof, phytoestrogens (present in fruit and vegetables and soy products), hormones like estradiol endogenously present in cow’s milk and eggs, and residues of illegally applied hormones. Several synthetic endocrine disruptors are actually POPs and suspect for carcinogenity; information related to phytoestrogens is rather contradictory in this respect: both protection and promotion of cancers is claimed in literature [17]. The main classes of phytoestrogens are isoflavones, lignans, coumestans and natural stilbenes, and show structural similarities with potent estrogens. Their consumption by healthy adults may be without risk but the problem might be totally different when exposure occurs at critical stages of development, i.e., at foetal and prepubertal children. Soy-milk-based baby-food is especially relevant to check for adverse effects of phytoestrogens [18]. Cow’s milk on the other hand should be checked for both estradiol and phytoestrogens. For an adequate risk assessment it is crucial to know how much phytoestrogens (or endocrine disruptors in general) are added to the ‘‘diet’’ of vulnerable consumers. Apart from endocrine disruptor analyses in the diet a clear insight into the endogenous estrogen background levels is needed. Recently, new data were presented using sensitive gas chromatography high-resolution mass spectrometry (GC/HRMS) down to the 2 ng/L level in plasma samples [19]. It was shown that the endogenous levels in prepubertal children are much lower than previously thought based on less specific immunoassays; as a result the diet-contribution to the total exposure becomes much more critical and relevant. Within the scope of the EU project BioCop (phyto)estrogen levels have been assessed both in soy and cow’s milk products [20]. Several bioactivity-based approaches are feasible for the screening of endocrine disruptors in the food chain. Apart from the SPR biosensor assay based on binding with specific human transport proteins already mentioned [12], robust transcription activation bioassays are available for estrogens [21]. The performance of the latest generation based on recombinant yeast cells fulfilled all validation and ISO 17025 accreditation requirements and the results obtained compared very well with GC/MS data [22]. Also a highly challenging transcriptomics approach is being explored within BioCop [20]. An MCF7 cell line is exposed to sample extracts. Next the messenger RNA (mRNA) is extracted
10
Michel W.F. Nielen and Hans J.P. Marvin
from the cells and the cDNA is hybridized on a microarray carrying 47,000 human transcripts. Up and down regulation of specific transcripts was observed which will allow the design of dedicated microarrays having a limited number of transcripts for endocrine disruptor fingerprinting. A major challenge will be to ensure compatibility of real sample extracts with the cells, overall robustness and validation issues.
2.4 Metal speciation The total content of the classical heavy metals, lead, cadmium and mercury in foodstuffs and animal feeding stuff, is regulated by EU maximum levels. However, for some trace elements their speciation is very important in terms of food and feed safety and information on the total content only does not give adequate information for correct toxicological risk assessment. For example, in the case of arsenic, the inorganic forms are the most toxic while for mercury, methylmercury is the most toxic form. Seafood is the major dietary source for arsenic and mercury in the European population [23]. For speciation analysis of trace elements the use of either LC or GC with inductively coupled plasma MS (GC- and LC/ICPMS) is currently the state-of-the-art [24,25]. These techniques have been known for a couple of decades but their use is not routine yet, probably due to rather expensive instrumentation, the need for skilled personnel and the lack of standardization, thus clearly defining some of the urgent challenges. Another issue is the lack of rapid and simple field sensors for speciation analysis which address at least partly the toxicity of the specific metal forms. In the past, different microbial biosensors were developed and evaluated in aqueous model systems [26,27]. These transcription activation biosensors contain a reporter gene under metal responsive element(s). Once the cell and the responsive element detect a metal/metalloid the responsive element on the DNA will switch on the transcriptional and translational machinery producing firefly luciferase leading to light emission directly responding to the concentration. These metal biosensors determine intrinsically the bioavailable fraction of the metal, giving an estimation of the toxic potential and complementing the chemical methods where total concentration of the metals is determined. The ability of this type of biosensors to work in real food and feed extracts is a major challenge that still needs to be explored. Some people are hesitating to work with such genetically modified bacterial cell biosensors. To overcome these hesitations luminescent cells immobilised onto a fibre dipstick might be applied to metal and metal speciation analysis [28].
2.5 Alkaloid biotoxins The EFSA is very interested in alkaloid biotoxins and has requested scientific opinions for ergot alkaloids (EA) in food, and for tropane and pyrrolizidine alkaloids (TA and PA) in feed; an opinion on EA in feed has been completed showing that there is a lack of data on EA patterns in feed materials and on toxic effects [29]. In particular ergotamine and ergocristine are of concern. PA are
Challenges in Chemical Food Contaminants and Residue Analysis
11
widespread and can be found in many plant genera and therefore also in feed, food and herbs, jacobine and lycopsamine being the most abundant. TA, such as atropine and scopolamine, are mainly found in feed as contaminants from Datura species. Plants producing TA have expanded dramatically in parts of Europe and problems are emerging. Data on the sensitivity of animal species towards the alkaloids are incomplete and do not allow the establishment of tolerance levels for individual alkaloids and mixtures thereof; nevertheless the data available so far indicate that adverse effects may occur in animals. The very limited and often incomplete data on tissue distribution and residual concentrations in edible tissues, milk and eggs do not allow an estimation of carry-over rates to food for human consumption. Data on human exposure and sensitivity towards the alkaloids are very incomplete and do not allow the establishment of tolerance levels for individual alkaloids and mixtures thereof. No harmonized methods are available yet, although different suggestions ranging from ELISA to thin layer chromatography (TLC) and LC/MS/MS can be found in literature [30]. A general issue in the determination of these alkaloids is a lack of reliable analytical standards, (certified) reference materials, proficiency schemes and a lack of harmonized regulation.
2.6 Peptide and protein growth promoters The use of growth promoters in food producing animals has been banned in many countries since 1988 [31]. Thanks to harmonization efforts most of the EU member states are capable of detecting steroids and b-agonists at the required level, although large differences in specific analyte coverage still exist. Hormone criminality is believed to be linked with sports doping and to occur via international networks. As in sports doping it can be predicted that the abuse will shift from classical growth promoters such as steroids and b-agonists to peptides and proteins when the veterinary control of the former becomes more effective. Bovine and porcine somatotropin (bST and pST), the equivalents of human growth hormone, are 22 kDa proteins and commercially available as recombinant preparations. They are important endocrine factors influencing metabolic and somatogenic processes including growth, immune function, reproduction and lactation. Their species specificity implies low toxicity in humans, apart from potential rare allergic reactions. Major concerns are the observed increased levels of insulin-like growth factor (IGF-1) in milk [32], which are connected to the incidence of cancer [33]. Detection via instrumental LC/MS/MS approaches is feasible [34]. Recently a rapid SPR biosensor immunoassay has been proposed to detect somatotropins in illegal preparations [35]. However, routine sampling and analysis of somatotropins and associated proteins in blood, milk and other relevant matrices is still a major challenge due to the complexity of the endogenous regulation (Figure 3), protein binding and the pulsatile secretion by the pituitary gland. As a result the blood levels show a high intra- and interindividual variability. In view of this it is rather unlikely that measurement of a single parameter can provide a validated tool for the enforcement of the ban on somatotropin and
12
Michel W.F. Nielen and Hans J.P. Marvin
Figure 3 Endogenous regulation along the somatotropin (growth hormone) axis.
related growth promoters. A huge challenge is envisaged that an assembly of parameters has to be measured followed by appropriate statistics in order to validate its diagnostic value versus untreated control populations.
2.7 Genetically modified organisms (GMO) Within the framework of safety assessment of food produced by means of modern genetic engineering the comparative analysis of the genetic modified (GM) crop with its unmodified genetic counterpart is an important part [36]. Two approaches are followed to detect intentional or unintentional alteration of the chemical composition of the GMO, i.e., a targeted approach (i.e., investigating defined constituents) and an untargeted approach using profiling technologies to analyse differences in RNA, proteins and metabolites [37]. Targeted analysis of single compounds with focus on important nutrients and critical toxicants has been successfully applied to demonstrate the safety of GM foods. Some criticisms have been expressed on the targeted approach as being biased and focused on known compounds and expected results [38]. This may become increasingly a problem in the second generation of GM crops where the introduction of completely new biosynthetic pathways or modifications in key enzymes in the primary or secondary structure may result in unexpected changes. Non-targeted approaches using profiling technologies based on DNA (e.g., microarray methods), proteins (two-dimensional gel electrophoresis followed by MSand/ or metabolites (using e.g., nuclear magnetic resonance (NMR), GC/MS and LC/ MS) are nowadays explored for their potential within the food safety assessment of GM food crops.
Challenges in Chemical Food Contaminants and Residue Analysis
13
In the EU the release of GMO and GMO-derived ingredients into the environment, and the marketing of GMO-derived food and animal feed is regulated within various specific directives and regulations. The EU regulations 1829/2003 and 1830/2003 concern the premarket safety assessment and the traceability and labeling of food and feed products derived from authorized GMOs establish that food or feed materials containing GMO-derived ingredients above the set threshold of 0.9% must be labeled as such. Implementation and enforcement of this regulation is generally performed by PCR-based methods using GMO-specific DNA probes. These methods must meet a number of agreed quality requirements. On the other hand, the presence of unauthorized GMO is not allowed at all in food and feed. In these cases, qualitative methods, such as DNA microarray methods may in the near future become very useful since these methods allow the detection of many different GMOs and GMO elements in one analysis, albeit their quantitative performance is limited [39]. Major challenges in GMO detection are quantitative aspects, validation and harmonization. Knowledge about the measurement uncertainty at the level of 0.9% is crucial already, and once a minimum required performance level (MRPL) has been assigned to the ban on unauthorized GMO that challenge will become immense.
2.8 Nanoparticles Application of nanoparticles — particles with one or more dimensions at the nanoscale — in food, medicine and agricultural products is booming and many nanobased products are already on the market [40]. Inherent to their size and surface-to-volume ratio nanoparticles often show a high chemical reactivity. The quantum-size and Coulomb-charging effects of nanoparticles may yield particles with exceptionally electric conductivity or resistance, high capacity for storing or transferring heat or changed solubility properties. Within food technology nanoparticles are used in food conservation, dietary supplements, food additives, packaging materials, functional foods and intelligent food. Some typical examples of application in the food area can be found: bakeries in Western Australia have incorporated nanocapsules containing omega-3 fatty acids in bread, the capsules will open only in the acidic environment of the stomach; the company NutraLeaset utilizes micelles with a diameter of 30 nm to deliver lycopenes, beta-carotene, lutein, phytosterols, CoQ10 and omega-3 fatty acids; Unilever is developing low fat ice creams by decreasing the size of the emulsion particles and The Oilfresh Corporation marketed a new nanoceramic product that prevents the oxidation and agglomeration of fats in deep fryers. It is envisaged that within agricultural practices nanoparticles can be used for precision farming, meaning that autonomous nanosensors are applied for realtime monitoring and early warning of plant health issues, and for controlled release of pesticides and herbicides encapsulated in nanomicelles. Some of these developments already come into reality are: Syngenta is using nanoemulsions in its pesticide products and also marketing the microencapsulated product Gutbusters that releases its content in the alkaline environment of the insect stomach; and a growth-promoting product PrimoMaxxs is used to strengthen
14
Michel W.F. Nielen and Hans J.P. Marvin
the physical structure of turfgrass. The unique properties of nanoparticles make them attractive in the applications mentioned previously but also impose new unforeseen risks, hence making an evaluation of the appropriateness of the current risk assessment protocols and methods necessary. The appropriateness of risk assessment methodologies currently in place to deal with the new properties of the nanoparticles is being addressed by different authorities. Current methods for the identification of nanoparticle hazards are probably adequate but the methods for characterization of the hazard (i.e., establishment of toxicological dose-response relationships) and subsequent exposure assessment need to be adapted. Improvement of current assessment methodology should consider the following aspects: (i) physical parameters such as particle size, size distribution, surface charge, (ii) agglomeration and disagglomeration properties in different environments, (iii) impurities within, and adsorbed species onto the surface and (iv) biological processes involving nanoparticles, including translocation, cellular uptake and toxicological mechanisms. The analytical challenge for the required monitoring of nanoparticles in the food chain is immense. A vast array of analytical techniques is typically used for the characterization of the physical properties of manufactured nanoparticles: the mean size and its distribution is measured by techniques like photon correlation spectroscopy (PCS), laser diffractometry (LD), light scattering (LS), differential mobility analysis, TOFMS and microscopy, while electrophoresis is typically used to determine the particle charge density [41,42]. The crystalline structure of a nanosuspension can be assessed by differential scanning calorimetry (DSC) [41], polarized optical microscopy and scanning electron microscopy [43]. Electron spectroscopy for chemical analysis (ESCA), X-ray photoelectron spectroscopy (XPS), secondary ions mass spectroscopy (SIMS) and matrix assisted laser desorption ionization MALDI TOFMS are used for surface structure and chemical composition analysis of nanoparticles [42]. It should be stressed that so far the key issue of isolation and sample preparation of nanoparticles from food or feed samples has been hardly addressed. Definitely it will be very difficult to maintain the integrity of the nanoparticle during sample preparation and the subsequent analysis. Apart from that, many of the characterization tools employed and cited previously will not be easily implemented within a routine food control environment.
3. MASKED CONTAMINANTS A masked contaminant is defined as a contaminant present in such a form that it will escape from rapid screening or instrumental analysis and remain undetected. A contaminant might be conjugated with carbohydrates, sulfates, amino acids, fatty acids or bound to proteins or nucleic acids in the sample of interest. Rapid screening tests such as immuno or receptor assays are based on molecular recognition and will fail recognition when the binding sites of the molecule become less accessible due to modification or steric hindrance elsewhere in the molecule. Chromatographic and mass spectrometric methods
Challenges in Chemical Food Contaminants and Residue Analysis
15
will fail as well due to retention time shifts and changes in m/z. A typical example is the occurrence of glycosylated Fusarium mycotoxins in wheat and maize, as recently shown for deoxynivalenol (DON) and zearalenone by Berthiller et al. [44,45]. In addition to that it was shown that the ratio between free and glycosylated mycotoxins can change during fermentation processes, for example, in beer breweries [46]. It can be assumed that all biotoxins are vulnerable to some degree of conjugation and escape at least partly from detection, unless appropriate modifications to sample preparation schemes are being implemented. Risk assessments and intake data of biotoxins should be reconsidered taking this phenomenon into account, but first of all appropriate analytical methods should become available. Another example is residues of the nitrofuran antibiotics, the use of which has been prohibited within the EU because of their potentially harmful effects on human health. Former analysis of the parent drugs turned out to be completely inappropriate since they do not persist in edible tissues due to rapid metabolization. The nitrofuran metabolites on the other hand form persisting protein-bound residues which will remain undetected. Conneely et al. [47] described a method for the determination of the total content of nitrofuran metabolites in tissues incorporating an acidic hydrolysis combined with a nitrobenzaldehyde derivatization step. The method was validated for porcine liver at the 5-ng/g level. Subsequent application to poultry had a global impact: high percentages of non-compliant samples were detected and an MRPL was assessed by the EC for harmonization of residue control in importing and exporting countries.
4. UNKNOWN BIOACTIVE CONTAMINANTS Unknown bioactive contaminants might emerge in the food chain due to climate changes, illegal production methods such as the application of designer steroids and b-agonists in cattle fattening or even because of an act of terrorism. Irrespective of the origin, they will remain undetected and escape from control as long as contaminant monitoring is restricted to a defined list of target substances. At least three different approaches can be distinguished for the detection and mass spectrometric identification of unknown contaminants, a bioactivitydirected, a metabolomics-like and an in silico prediction approach.
4.1 Bioactivity-directed identification of emerging unknown contaminants Ideally, the sample should be extracted and purified in such a way to maintain all relevant contaminant classes of interest, the first challenge being clearly in the field of generic sample preparation development. The sample extract is analysed for bioactivity using a suitable assay (whole cell-, receptor-, immuno-, microbiological inhibition assay, etc.). When the sample has been screened suspect in one of these assays and the cause cannot be identified using the
16
Michel W.F. Nielen and Hans J.P. Marvin
Sample pretreatment and clean-up
Gradient Liquid Chromatography
Optional on-line (Q)TOF MS(/MS) Flow split Bioactivity screening Bioassay plate
Collection plate
Identification off-line UPLC-(Q)TOFMS(/MS) GC-TOFMS
Figure 4 Generic set-up for bioactivity-directed identification of emerging unknown contaminants.
prescribed confirmatory analysis method targeted for the presence of known contaminants, then possibly an emerging unknown contaminant is present in the sample. Next the unknown can be identified using the generic experimental setup shown in Figure 4. In short, the suspect sample is fractionated by gradient LC and narrow fractions are collected in duplicate using a parallel 96-well plate setup. One plate is re-analysed for bioactivity using the original bioassay yielding a bioactivity chromatogram or ‘‘biogram’’. The duplicate well number(s) of the suspect positions in the biogram are subjected to full-scan LC/TOFMS or GC/TOFMS techniques in order to perform chemical identification of the bioactive unknown, preferably using accurate mass measurement and isotope fitting which allows elemental composition assessment of the molecular ion and its collision-induced dissociation fragments. This approach has been demonstrated for cell-, immuno- and SPR biosensor assays and applied successfully to the identification of b-agonists in feed, hormones in urine and antibiotics in chicken muscle [48–50]. A key issue in this approach is the biocompatibility between the LC fraction and the subsequent bioactivity measurement. In this respect we have good experience with wells filled with a mixture of 2 mL dimethylsulfoxide (DMSO) and 50 mL water as a keeper solvent prior to the fractionation. The
Challenges in Chemical Food Contaminants and Residue Analysis
17
water–acetonitrile eluate from the LC gradient yields a large number of filled wells which are simply evaporated overnight in a fume hood, leaving the substances of interest in a tiny volume of water/DMSO. Of course, an LC fractionation is also directly compatible with atmospheric pressure ionization MS. That option requires only one well plate for fraction collection and bioactivity assessment and the suspect well number is then simply correlated with the retention time in the parallel MS system [51].
4.2 Metabolomics approach to the identification of emerging unknown contaminants Another sophisticated means of identification of unknown contaminants is based on a metabolomics-like approach. Again the sample should be extracted and purified in such a way to maintain all relevant contaminant classes of interest. Next the sample, still being a highly complex mixture, is analysed by a highresolution chromatographic technique such as ultra performance liquid chromatography (UPLC), GC or even comprehensive GC GC, combined with a sensitive full-scan MS technique such as TOF, ion trap or FT Orbitrap. The data from the sample replicates are aligned in the retention time domain and compared with the data from a set of reference sample replicates. Finally uni- or multi-variate statistics are applied in order to assess the significant differences between the suspect sample and the regular reference situation. By using appropriate data analysis software contaminants could be retrieved automatically from an oily preparation, drinking water and grass samples [52]. Successful application of this approach requires the availability of a clean, stable and highly reproducible chromatography system, including reproducibility in solvent and column impurities. Moreover, the reference situation is crucial, requiring a more or less reproducible sample matrix background. For homogeneous samples such as drinking water this can be relatively easily achieved but an adequate reference for inherently inhomogeneous samples having a fluctuating composition such as feed will be very difficult to obtain. Last but not least, intelligent data analysis software is required which can automatically correct for small changes in retention time and/or mass accuracy and is capable of keeping the underlying raw data accessible for retrospective analysis, reprocessing and evaluation in its original software format. Note that a GC GC/TOFMS analysis creates a challenging four-dimensional dataset. Ignoring all these factors will yield many irrelevant data from system impurities, bulk composition changes, etc., and probably not identify the unknown emerging contaminant.
4.3 In silico prediction approach to the identification of unknowns Starting from a chemical core structure of a specific contaminant or contaminant class and having knowledge about reactivity at specific atom positions in that core structure, one can predict in silico the chemical structure of unknown contaminants, metabolites and emerging risks. On the basis of such a structure
18
Michel W.F. Nielen and Hans J.P. Marvin
physicochemical parameters such as solubility, polarity, acidity can be estimated as well, thus providing a basis for the prediction of chromatographic and mass spectrometric behaviour of the unknown. Finally, GC- or LC/MS techniques can be used to perform a targeted search on the presence of the predicted unknown in samples of interest. Recently we demonstrated the feasibility of this approach by a UPLC/TOFMS search for in silico predicted metabolites and designer modifications of glucocorticosteroids in urine [53]. Even the potential modifications can be automated: we modified a commercially available software package for metabolite finding in such a way that all kinds of chemical modifications were automatically searched for in the TOFMS dataset yielding a listing of both known compounds already present in a user library and unexpected options caused by a combination of different reactions relative to the core structure, all supported by elemental compositions thanks to the accurate mass measurement.
5. EMERGING TECHNOLOGIES 5.1 Omics Genomics, proteomics and metabolomics (‘‘omics’’) are extremely valuable tools in studying biological processes, in bio- and disease marker discovery, in drug discovery, in nutrition and toxicology. Generally, cells, plants or animals are exposed and divided into a treated and an untreated group. Following the experiment both groups are analysed at the mRNA, the protein or the metabolite level using DNA microarrays, 2D-gel electrophoresis plus MALDI/TOFMS or LC/MS, NMR plus GC- or LC/MS, respectively. Next the differential regulation of thousands of targets is assessed using appropriate statistics. Usually both experimental groups are well-defined and identical, except for the treatment, and the dose of exposure is relatively high as compared to levels normally encountered in food contaminant and residue analysis. On the other hand, biomarkers thus obtained might be used for the development of dedicated screening assays based on PCR, tailored DNA microarrays, receptor or immunoassays. Assuming that such screening assays will be developed at least two scenarios can be distinguished: (i) exposure of a standard cell system or organism to the food sample extract of interest followed by isolation of mRNA, proteins or metabolites from the cells and analysis using the developed dedicated screening assay and (ii) isolation of mRNA, proteins or metabolites directly from biofluids in the food sample, usually restricted to farm animals and crops. A major challenge would be to obtain, purify and maintain the integrity of a representative isolate. But most important of all will be the validation of the biomarker targets versus their natural background variability in food, feed and biofluid matrices: real-life is quite different from standard cells or organisms! The on-going European project on new technologies to screen multiple chemical contaminants in food, acronym BioCop, has taken this challenge and is studying both transcriptomics and proteomics for chemical food contaminant analysis [20]. An MCF-7 standard cell line is used and exposed with food sample extracts for
Challenges in Chemical Food Contaminants and Residue Analysis
19
phytoestrogen and mycotoxin analysis, next the extracted mRNA from the cells is analysed by tailored DNA microarrays. In the proteomics topic of BioCop a multiplex SPR biosensor immunoassay is being developed to analyse protein biomarkers in blood of bovines for the screening of steroid abuse in cattle fattening.
5.2 Bioassays The acceptance and application of whole-cell bioassays in routine chemical food contaminant analysis is progressing slowly but steadily. Typical examples are the DR-CALUXs bioassay and hormone reporter gene bioassay. The principle of such assays is illustrated in Figure 5: Genetically modified cells are exposed to the sample extract containing the contaminant(s). The cells are modified in such a way that they express the receptor protein of interest, in this example the aryl hydrocarbon (Ah) receptor which binds to dioxins and PCBs. Upon binding the receptor–ligand complex travels into the cell nucleus and binds onto the modified DNA at specific responsive elements which act as a switch for the activation of a gene encoding for the production of a marker protein such as luciferase or green fluorescent protein (GFP); as a result the cells will generate light upon exposure, even at trace levels [54]. Cell assays can be performed in parallel in 96-well plates and require hardly any reagents. Only the suspect samples will require confirmatory analysis using expensive instrumental analysis methods such as GC/HRMS in the case of dioxins. A key issue in the application to food and feed samples is the stability of the cells. In general, mammalian cells seem to be more vulnerable to cell toxicity caused by matrix components and require a more stringent sample clean-up in contaminant and residue analysis. Yeast cells on the other hand are inherently more robust, allowing application to
Figure 5 Schematic representation of the mechanism of the DR-CALUXs. Reproduced and kindly provided by T.F.H. Bovee [54].
20
Michel W.F. Nielen and Hans J.P. Marvin
residue analysis of estrogens in feed and urine samples following a simple solidphase extraction step [54].
5.3 (Bio)nanotechnology The nanosciences intend to deliver radical new products and processes at nanoscale dimensions by manipulation of surfaces and macromolecular assemblies. In 2005, Bruce et al. [55] reviewed the role of nanotechnology in food analysis but no real-life application of (bio)nanotechnology in chemical food contaminant analysis was presented. Since then the situation is not so much different. However, it should be noted that any SPR biosensor instrument already used in chemical food contaminant analysis is actually an example of bionanotechnology since the biointeraction is measured within a distance of 150 nanometre of the functionalized surface and the flow cells of the microfluidic system are typically in the order of some tens of nanolitres. For example, by applying SPR, Farre´ et al. [56] showed part-per-trillion sensitivity for the pesticide atrazine in natural water samples and Haasnoot et al. [57] showed the SPR determination of sulfonamide antibiotics in broiler serum and plasma as a prediction tool for residue levels in edible tissues. Another option is the use of localized surface plasmons (LSPs) sustained by functionalized silver or gold nanoparticles: a highly specific, label-less immunosensor has been constructed for the residue analysis of the anabolic steroid stanozolol down to the nanomolar range [58]. The nanoscale format of SPR can also be coupled successfully to nanoLC/TOFMS as demonstrated for the residue analysis of the antibiotic enrofloxacin in chicken muscle [59]. Gold nanoparticles can also be applied to enhance the performance of immunochromatographic strip tests (‘‘dipsticks’’) as shown by Tanaka et al. [60]. A special application of nanoparticles in the detection of chemical food contaminants will be the use of quantum dots (QDs). QDs are semiconducting crystals of a few nanometres and have unique photophysical properties such as size-tunable luminescence spectra, high quantum yields, broad absorption and narrow emission wavelengths. As a result they will be increasingly used as fluorescent labels in, for example, immunoassays [61], also in chemical food contaminant and residue analysis. Apart from detection, nanomaterials might be used in sample preparation as well. Zhao et al. [62] used carbon nanotubes as a solid-phase extraction adsorbent for the GC/MS/MS analysis of barbiturate drug residues in pork at sub-ppb levels.
5.4 Ambient mass spectrometry In 2004 a novel ambient ionization technology, called Desorption ElectroSpray Ionization (DESI), was proposed by the Cooks group at Purdue University [63,64]. For the first time, surfaces can be probed and analysed by MS under real native ambient conditions, without any sample preparation or matrix addition. The typical lay-out of a DESI source is shown in Figure 6. In short, a pneumatically assisted electrospray is used to produce charged microdroplets
Challenges in Chemical Food Contaminants and Residue Analysis
21
Solvent HV N2
electrospray desorbed ions
et inl of S M
Sample
moving sample stage in air
Figure 6 Schematic view of a DESI source.
and gas-phase solvent ions that are directed onto the sample at a surface. The ionization process closely resembles conventional ESI-MS; however, the sample is not present in the solvent nor ionized during the electrospray process, and is therefore less vulnerable to ionization suppression caused by the presence of salts and other interfering matrix components. Instead, ionization of the sample molecules takes place at or above the surface as a result of proton transfer, electron transfer, or ion transfer by gas-phase ions [65]. Reagents can be added to the electrospray solvent in order to tune the selectivity and the sensitivity of the DESI process [66]. That versatility is a great advantage over the direct analysis in real time (DART) ionization alternative in which helium or nitrogen is used as a reaction gas [67]. Depending on the capabilities of the MS, targeted (selected ion mode), untargeted (full-scan mode) or accurate mass analysis is possible, yielding for example, new biomarkers from differential metabolomics with the aid of principal component analysis (PCA) [68]. The ion transfer line to the atmospheric inlet of the MS can be extended and integrated with the electrospray nozzle, thus creating a probe for in situ sensing of any native or cut surface. Widely variable substrates such as paper, metal, Teflon, human skin, animal organs such as pancreas, liver and brain, plant parts such as stems, seeds, flowers and roots, glass, leather, bricks, polymers (Nylon, latex, PDMS) and silica gel have been sampled successfully. Measurements take on average 3 s but high-throughput analysis (3 samples/s) with a moving belt has also been described [69]. Automated chemical imaging of surfaces is possible. Depending on the dimensions of the electrospray tip and the distance to the surface, spot sizes will vary from 2 2 mm down to 50 50 mm. In terms of analytes, the technique is more versatile than standard ESI-MS, as also highly non-polar molecules such as carotenoids, steroids, terpenes and even volatiles can be analysed. The sensitivity of the technique lies in the low picogram or high
22
Michel W.F. Nielen and Hans J.P. Marvin
femtogram range. DESI-MS is also believed to be quantitative but we have some reservations in that respect. So far, the applicability of DESI technology has been demonstrated in forensics (detection of explosives, of drug residues on banknotes, Ecstasy), pharmaceutical [69–71], plant sciences (in vivo analysis of plant alkaloids) [72], and clinical analysis, diagnosis of cancerous tissue [73] and metabolomics [68]. The option of direct surface analysis of plant alkaloids, pesticide residues and natural toxins will be very attractive for chemical food contaminant analysis. For complex, mixtures the combination of TLC and DESI can be considered, as recently demonstrated for alkaloid dietary supplements [74].
6. VALIDATION AND QA/QC CHALLENGES The validation requirements for contaminants and residue analysis in the food chain are laid down in different international regulations. Some contaminant plus sample matrix groups are using the concept of normalized and harmonized reference methods, in other situations the requirements are limited to method validation and data interpretation issues. In any case, the number of available certified reference materials and interlaboratory studies is far too low, mainly due to financial limitations and other priorities. Two issues are particularly challenging: (i) the validation of biochemical or biological rapid screening methods and (ii) the validation of generic comprehensive instrumental methods.
6.1 Biochemical or biological rapid screening assays Validations for classical instrumental chemical analysis methods are relatively straightforward, but the introduction of (multiplex) biochemical or biological rapid screening assays requires a new fit-for-purpose approach. Typically the data output is generating qualitative or semi-quantitative results, while the scope of bioactive analytes covered might be rather diverse in terms of physicochemical parameters. As a pragmatic solution we applied the following validation procedure to the validation of a whole-cell estrogen bioassay: first, five different bioactive estrogen representatives were selected ranging from polar to apolar chemistries assuming that both known and unknown estrogens would have physicochemical characteristics within that range. Then, representative sample matrices, in this case calf urine and three different types of feed matrix, and acceptable spiking levels were defined based on current legislation and/or expected sensitivity of the bioassay for that particular compound. For each sample matrix both unspiked and samples spiked with the representative individual estrogen were analysed. By doing so the unspiked samples were always screened compliant while the spiked samples were always screened suspect non-compliant at the levels chosen, allowing validation as a qualitative screening method and assessment of CCa and CCb values according to 2002/657/EC; even ISO 17025 accreditations could be obtained [75,76]. Moreover,
23
Challenges in Chemical Food Contaminants and Residue Analysis
chem + 1 ng/ml 17bE2 urine + 1 ng/ml 17bE2 blank chem blank urine
1000
response units
800
600 400 200
CCα
0 -200
July 2003
# control samples
May 2005
Figure 7 Long-term performance of a validated estrogen bioassay for blank and estradiolcontaining control samples [22].
as shown in Figure 7 routine operation of the validated bioassay showed that the non-compliant control sample was always screened above the CCa decision limit and declared non-compliant while the compliant blank was only screened two times false non-compliant over a two-year period, despite the inherent signal variability of such a bioassay [22]. In other words, even a biological assay can provide consistent results as an on/off screening tool in residue and contaminant control.
6.2 Comprehensive instrumental analysis methods Thanks to the introduction of highly sensitive ion trap and TOF mass analysers in GC/MS and LC/MS full-scan positive and negative ion data of the residues and contaminants in a particular sample of interest can be easily obtained, provided that the analytes are effectively extracted and survived the clean-up step, the injection, chromatographic separation and ionization. Then the sky is the limit and hundreds of residues and contaminants can be searched for. QA/ QC considerations will require the co-analysis of control samples, and then particularly the preparation of a non-compliant control sample having a known concentration of all analytes of interest will be a huge task. The co-analysis of such a control sample will be crucial for the assessment of false compliant results, especially because in the end automated raw data processing and evaluation will be the only option to handle the screening for hundreds of residues and contaminants. It should be noted that state-of-the-art raw data processing and evaluation software will function quite well in academic standards but most often fail in real samples at residue or contaminant level.
24
Michel W.F. Nielen and Hans J.P. Marvin
Considering validation of the total analysis including data processing it might be questioned whether the immense efforts of a full validation for all these hundreds of analytes in all sample matrices of interest is really required. In analogy with Section 6.1 a set of a limited number of representatives might be chosen for an initial in-house validation covering a range of physicochemical analyte characteristics and/or contaminant (sub)groups. Ideally, the choice of these representatives should be validated by performing at least a within-day replicate analysis experiment of blanks and control samples containing all analytes of interest. Additional contaminants of interest might be added to the control sample during routine operation thus providing a continuous extension of the scope of the method.
7. CONCLUSIONS AND FUTURE TRENDS The current use of routine monitoring systems for a limited number of chemical food contaminants and residues in food industry and food control laboratories does not mean in any way that the challenges we are facing are less, they simply evolved under the influence of globalization, new food technologies, climate change, etc. Not surprisingly different stakeholders have different wishes for improvements in chemical food contaminant and residue analysis: in industry priority will be at the implementation of rapid and inexpensive methods having a scope for those substances which are of paramount importance to their specific core product integrity. Recognized challenges are further increase of speed and reduction of costs, and extension of the scope. Despite their primary responsibility for food safety as laid down in the General Food Law, it cannot be reasonably expected from the food industry that they take care of any emerging known or unknown risk, which might pop up somewhere in the food chain. On the other hand, some of the emerging issues raised in this chapter will cause a problem sooner or later, requiring the availability of analysis methods having a comprehensive scope in order to provide an early warning to the food safety authorities and generate the data for risk assessment. We believe that bioactivity-based screening methods and full-scan accurate mass spectrometric identification methods are highly complementary technologies and both essential in this respect. It is recognized that still major efforts should be put to generic sample preparation and automated data processing and evaluation before such comprehensive tools can be routinely applied in a real-life environment. Current EU monitoring plans are restricted to a limited list of target contaminants and residues in a limited number of samples. Also current validation requirements are typically developed for target analysis. The advocated more comprehensive scope of analysis does not fit easily into such policies. It is recommended that at least a part of the associated efforts and resources is moved towards the actual application of comprehensive methods for known and unknown emerging food contaminants.
Challenges in Chemical Food Contaminants and Residue Analysis
25
ACKNOWLEDGEMENTS Partners in EU-framework projects SAFEFOODS, BioCop (www.biocop.org) and CONffIDENCE (www.confidence.org), and colleagues at RIKILT-Institute of Food Safety are acknowledged for their stimulating contributions.
REFERENCES 1 T.J. Hagenaars, A.R.W. Elbers, G. Kleter, F. Kreft, S.P.J. van Leeuwen, C. Waalwijk, L.A.P. Hoogenboom and H.J.P. Marvin, Pro-active approaches to the identification of emerging risks in the food chain: Retrospective case studies, Report ASG06-I01112, Wageningen University and Research Center, Animal Sciences Group, Lelystad, 2006. Available at http://www.kennisonline.wur.nl/NR/ rdonlyres/3C5C7A63-EE9C-4423-81B1-3DB98492CFB2/26020/PRJ11eindrapportASGfinal.pdf 2 European Commission, The Rapid Alert System for Food and Feed Annual Report 2005, Office for Official Publications of the European Communities, Luxembourg, 2006. Available at http:// europa.eu.int/comm/food/food/rapidalert/index_en.htm 3 G.A. Kleter, A. Prandini, L. Filippi and H.J.P. Marvin, Food Chem. Toxicol. (2008) in press. Available online, DOI: 10.1016/j.fct.2007.12.022. 4 Regulation (EC) No 178/2002 of the European Parliament and the Council of 28 January 2002, Off. J. Eur. Communities, L31 (2002) 1. 5 European Commission, Special Eurobarometer 238, Office for Official Publications of the European Communities, Luxembourg, 2006. 6 W. Verbeke, L.J. Frewer, J. Scholderer and H.F. De Brabander, Anal. Chim. Acta, 586 (2007) 2. 7 EFSA Opinion of the Scientific Committee on a Request from EFSA Related to the Early Identification of Emerging Risks, The EFSA Journal, 375 (2006) 1. 8 EFSA Opinion of the Scientific Panel on Contaminants in the Food Chain on a request from the Commission related to the presence of non dioxin-like polychlorinated biphenyls (PCB) in feed and food, The EFSA Journal, 284 (2005) 1. 9 J. Dallu¨ge, J. Beens and U.A.Th. Brinkman, J. Chromatogr. A, 1000 (2003) 69. 10 A. Covaci, S. Voorspoels, L. Ramos, H. Neels and R. Blust, J. Chromatogr. A, 1153 (2007) 145. 11 T.F.H. Bovee, L.A.P. Hoogenboom, A.R.M. Hamers, W.A. Traag, T. Zuidema, J.M.M.J.G. Aarts, A. Brouwer and H.A. Kuiper, Food Addit. Contam., 15 (1998) 863. 12 G.R. Marchesini, E. Meulenberg, W. Haasnoot, M. Mizuguchi and H. Irth, Anal. Chem., 78 (2006) 1107. 13 H.F. Schro¨der, J. Chromatogr. A, 1020 (2003) 131. 14 M. Villagrasa, M. Lo´pez de Alda and D. Barcelo´, Anal. Bioanal. Chem., 386 (2006) 953. 15 M.M. Schultz, F.B. Douglas and A.F. Jennifer, Environ. Eng. Sci., 20 (2003) 487. 16 I.G. Shabalina, T. Panaretakis, A. Bergstrand and J.W. DePierre, Carcinogen, 20 (1999) 2237. 17 H. Tsuda, A. Naito, C.K. Kim, K. Fukamachi, H. Nomoto and M.A. Moore, Japan J. Clin. Oncol., 33 (2003) 259. 18 J.-P. Antignac, R. Cariou, B. Le Bizec and F. Andre, Food Control, 87 (2004) 275. 19 F. Courant, J.-P. Antignac, D. Maume, F. Monteau, A.-M. Andersson, N. Skakkebaek, F. Andre and B. Le Bizec, Anal. Chim. Acta, 586 (2007) 105. 20 European Commission 6th Framework Program, project New technologies to screen multiple chemical contaminants in food, acronym BioCop. Available at www.biocop.org 21 T.F.H. Bovee, J.R. Helsdingen, I.M.C.M. Rietjens, J. Keijer and L.A.P. Hoogenboom, JSBMB, 91 (2004) 99. 22 M.W.F. Nielen, T.F.H. Bovee, H.H. Heskamp, J.J.P. Lasaroms, M.J. Groot and L.A.P. Hoogenboom, Food Addit. Contam., 23 (2006) 1123. 23 European Commission, SCOOP report Assessment of the dietary exposure to arsenic, cadmium, lead and mercury of the population of the EU member states, Directorate-General Health and Consumer Protection, 2004. 24 R. Cornelis, J. Caruso, H. Crews and K. Heumann, Handbook of Elemental Speciation: Techniques and Methodology, Wiley, Chichester, UK, 2003.
26
25 26 27 28 29 30 31 32 33 34 35 36
37
38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54
Michel W.F. Nielen and Hans J.P. Marvin
S.C. Hight and J. Cheng, Anal. Chim. Acta, 567 (2006) 160. M. Virta, J. Lampinen and M. Karp, Anal. Chem., 67 (1995) 667. S. Tauriainen, M. Virta and M. Karp, Water Res., 34 (2000) 2661. A. Ivask, T. Green, B. Polyak, A. Mor, A. Kahru, M. Virta and R. Marks, Biosens. Bioelectron., 22 (2007) 1396. Opinion of the Scientific Panel on Contaminants in the Food Chain on a request from the Commission related to ergot as undesirable substance in animal feed, The EFSA Journal, 225 (2005) 1. K.A. Than, V. Stevens, A. Knill, R. Gallagher, K.L. Gaul, J.A. Edgar and S.M. Colegate, Anim. Feed Sci. Technol., 121 (2005) 5. Council Directive 96/22/EC, Off. J. Eur. Communities, L125 (1996) 3. A. Daxenberger, B.H. Breier and H. Sauerwein, Analyst, 123 (1998) 2429. I. Rogers, P. Emmett, D. Gunnell, D. Dunger and J. Holly, Public Health Nutr., 9 (2006) 359. G. Pinel, R. Buon, F. Aviat, C. Larre, G. Andre-Fontaine, F. Andre and B. Le Bizec, Anal. Chim. Acta, 529 (2005) 41. T.H.J. Heutmekers, M.G.E.G. Bremer, W. Haasnoot and M.W.F. Nielen, Anal. Chim. Acta, 586 (2007) 239. A. Ko¨nig, A. Cockburn, R.W.R. Crevel, E. Debruyne, R. Grafstroem, U. Hammerling, I. Kimber, I. Knudsen, H.A. Kuiper, A.A.C.M. Peijnenburg, A.H. Penninks, M. Poulsen, M. Schauzu and J.M. Wal, Toxicology, 42 (2004) 1047. F. Cellini, A. Chesson, I. Colquhoun, A. Constable, H.V. Davies, K.H. Engel, A.M.R. Gatehouse, S. Ka¨renlampi, E.J. Kok, J.-J. Leguay, S. Lehesranta, H.P.J.M. Noteborn, J. Pedersen and M. Smith, Food Chem. Toxicol., 42 (2004) 1089. E. Millstone, E. Brunner and S. Mayer, Nature, 401 (1999) 525. M. Miraglia, K.G. Berdal, C. Brera, P. Corbisier, A. Holst-Jensen, E.J. Kok, H.J.P. Marvin, H. Schimmel, J. Rentsch, J.P.P.F. van Rie and J. Zagon, Food Chem. Toxicol., 42 (2004) 1157. Woodraw Wilson International Center for Scholars, The Nanotechnology Consumer products Inventory, 2006. Available at www.nanotechproject.org/consumerproducts R.H. Muller, C. Jacobs and O. Kayser, Adv. Drug Deliv. Rev., 47 (2001) 3. K.W. Powers, S.C. Brown, V.B. Krishna, S.C. Wasdo, B.M. Moudgil and S.M. Roberts, Toxicol. Sci., 90 (2006) 296. M. Avella, J.J. De Vlieger, M.E. Errico, S. Fischer, P. Vacca and M.G. Volpe, Food Chem., 93 (2005) 467. F. Berthiller, C. Dall’Asta, R. Schuhmacher, M. Lemmens, G. Adam and R. Krska, J. Agric. Food Chem., 53 (2005) 3421. F. Berthiller, U. Werner, M. Sulyok, R. Krska, M.-T. Hauser and R. Schuhmacher, Food Addit. Contam., 23 (2006) 1194. J. Hajslova, K. Lancova, M. Kostelanska, M. Zachariasova and J. Poustka, Presented at the XIIth Int. IUPAC Symposium on Mycotoxins and Phycotoxins, Istanbul, May 21–25, 2007. A. Conneely, A. Nugent, M. O’Keeffe, P.P.J. Mulder, J.A. van Rhijn, L. Kovacsics, A. Fodor, R.J. McCracken and D.G. Kennedy, Anal. Chim. Acta, 483 (2003) 91. M.W.F. Nielen, C.T. Elliott, S.A. Boyd, D. Courtheyn, M.L. Essers, H.H. Hooijerink, E.O. van Bennekom and R.E.M. Fuchs, Rapid Commun. Mass Spectrom., 17 (2003) 1633. M.W.F. Nielen, T.F.H. Bovee, P. Rutgers, A.R.M. Hamers, J.A. van Rhijn and L.A.P. Hoogenboom, Anal. Chem., 78 (2006) 424. G.R. Marchesini, W. Haasnoot, P. Delahaut, H. Gercek and M.W.F. Nielen, Anal. Chim. Acta, 586 (2007) 259. M.W.F. Nielen, E.O. van Bennekom, H.H. Heskamp, J.A. van Rhijn, T.F.H. Bovee and L.A.P. Hoogenboom, Anal. Chem., 76 (2004) 6600. A. Lommen, G. van der Weg, M.C. van Engelen, G. Bor, L.A.P. Hoogenboom and M.W.F. Nielen, Anal. Chim. Acta, 584 (2007) 43. M.C. van Engelen, M.E. Touber, C. Georgakopoulos and M.W.F. Nielen, Presented at the 25th Manfred Donike Workshop on Doping Analysis, Cologne, 2007. T.F.H. Bovee, Thesis: Development, validation and routine application of the in vitro REA and DR-CALUX reporter gene bioassays for the screening of estrogenic compounds and dioxins in food and feed, Wageningen University, Wageningen, The Netherlands, 2006, p. 13.
Challenges in Chemical Food Contaminants and Residue Analysis
27
55 I.J. Bruce, T. Sen and A. del Campo, Key for tomorrow: Nanotechnology in food analysis, In: A. van Amerongen, D. Barug, M. Lauwaars, (Eds.), Rapid Methods for Biological and Chemical Contaminants in Food and Feed, Wageningen Academic Publishers, The Netherlands, 2005, ISBN 90-7699-8531. 56 M. Farre´, E. Martı´nez, J. Ramo´n, A. Navarro, J. Radjenovic, E. Mauriz, L. Lechuga, M.P. Marco and D. Barcelo´, Anal. Bioanal. Chem., 388 (2007) 207. 57 W. Haasnoot, M. Bienenmann-Ploum, U. Lamminma¨ki, M. Swanenburg and H. van Rhijn, Anal. Chim. Acta, 552 (2005) 87. 58 M.P. Kreuzer, R. Quidant, G. Badenes and M.P. Marco, Biosens. Bioelectron., 21 (2006) 1345. 59 G.R. Marchesini, J. Buijs, W. Haasnoot, H. Hooijerink, O. Jansson and M.W.F. Nielen, Anal. Chem. 80 (2008) 1159. 60 R. Tanaka, T. Yuhi, N. Nagatani, T. Endo, K. Kerman, Y. Takamura and E. Tamiya, Anal. Bioanal. Chem., 385 (2006) 1414. 61 Z. Zhelev, R. Bakalova, H. Ohba, R. Jose, Y. Imai and Y. Baba, Anal. Chem., 78 (2006) 21. 62 H. Zhao, L. Wang, Y. Qiu, Z. Zhou, W. Zhong and X. Li, Anal. Chim. Acta, 586 (2007) 399. 63 Z. Taka´ts, J.M. Wiseman, B. Gologan and R.G. Cooks, Science, 306 (2004) 471. 64 R.G. Cooks, Z. Ouyang, Z. Takats and J.M. Wiseman, Science, 311 (2006) 1566. 65 Z. Taka´ts, J.M. Wiseman and R.G. Cooks, J. Mass Spectrom., 40 (2005) 1261. 66 I. Cotte-Rodriguez, Z. Takats, N. Talaty, H. Chen and R.G. Cooks, Anal. Chem., 77 (2005) 6755. 67 R.B. Cody, J.A. Laramee and H.D. Durst, Anal. Chem., 77 (2005) 2297–2302. 68 H. Chen, Z. Pan, N. Talaty, D. Raftery and R.G. Cooks, Rapid Commun. Mass Spectrom., 20 (2006) 1577. 69 H. Chen, N. Talaty, Z. Takats and R.G. Cooks, Anal. Chem., 77 (2005) 6915. 70 L.A. Leuthold, J.-F. Mandscheff, M. Fathi, C. Giroud, M. Augsburger, E. Varesio and G. Hopfgartner, Rapid Commun. Mass Spectrom., 20 (2006) 103. 71 T.J. Kauppila, J.M. Wiseman, R.A. Ketola, T. Kotiaho, R.G. Cooks and R. Kostiainen, Rapid Commun. Mass Spectrom., 20 (2006) 387. 72 N. Talaty, Z. Takats and R.G. Cooks, Analyst, 130 (2005) 1624. 73 J.M. Wiseman, S.M. Puolitaival, Z. Taka´ts, R.G. Cooks and R.M. Caprioli, Angew. Chem. Int. Ed., 44 (2005) 7094. 74 G.J. Van Berkel, B.A. Tomkins and V. Kertesz, Anal. Chem., 79 (2007) 2778. 75 T.F.H. Bovee, H.H. Heskamp, A.R.M. Hamers, L.A.P. Hoogenboom and M.W.F. Nielen, Anal. Chim. Acta, 529 (2005) 57. 76 T.F.H. Bovee, G. Bor, H.H. Heskamp, L.A.P. Hoogenboom and M.W.F. Nielen, Food Addit. Contam., 23 (2006) 556.
CHAPT ER
2 International Regulations on Food Contaminants and Residues Ioannis S. Arvanitoyannis
Contents
1. Introduction to EU and USA Legislation 2. Topics/Categories Covered under EU Legislation 2.1 Food safety 2.2 Food quality 2.3 Water quality 3. Topics/Categories Covered under USA Legislation 3.1 Food safety 3.2 Technological aspects 3.3 Food quality 3.4 Water protection and management References
29 31 31 51 60 63 63 65 68 71 73
1. INTRODUCTION TO EU AND USA LEGISLATION Over the past 15 years a series of food safety crises (Bovine Spongiform Encephalopathy (BSE), dioxins, high pesticide and antibiotic content in several foods, high nitrates content, presence of coliforms in drinking water, usage of Sudan Red 1 and formation of acrylamide among others) occurred within the frame of European Union (EU) thus resulting in great losses of human lives and capital. These crises made EU citizens more alert but also increased considerably the EU legislative task in an attempt to undertake preventive instead of corrective measures. One of the top priority areas was dealing with the safety and hygiene directives. In practical terms, the requirements on primary producers amount, in the main, to fairly basic hygiene procedures. Primary producers must ensure that hazards are acceptably controlled and respect other existing legislation. Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00002-0
r 2008 Elsevier B.V. All rights reserved.
29
30
Ioannis S. Arvanitoyannis
Primary producers will not be required to apply Hazard Analysis and Critical Control Point (HACCP)-based procedures. Primary producers will have to be registered with Competent Authorities, although existing forms of registration may be used for this purpose. Stakeholders are being consulted on the form the controls will take to ensure they are practicable and can be addressed in Good Practice Guides to be initiated by industry with support from other stakeholders. For most people in the EU access to potable and clean water in quite abundant quantities is taken for granted. Most people do not realise, however, that all human activities put a burden on water quality and quantity. All polluted water, whether polluted by households, industry or agriculture, returns back, one way or another, to the environment and may cause damage to human health or the environment (http://www.food.gov.uk/science/surveillance). In August 199, Food Quality Protection Act was signed in US — a comprehensive overhaul of laws that regulate pesticides in food. The new law establishes a single, strong health-based standard by using the best science available, and, for the first time, provides Americans with the ‘‘right-to-know’’ about health risks from pesticides. In August 1996, it was signed into law the Safe Water Drinking Act of 1996, strengthening protections to ensure that American families have clean, safe tap water to drink. On 2 December 1997, the Food and Drugs Administration (FDA) approved irradiation of meat products for controlling disease-causing microorganisms. Disease causing microorganisms that can be controlled by irradiation include the Escherichia coli O157:H7 and Salmonella species (http://www.hhs.gov/news/press/2000pres/20000316a.html). The Food Safety and Inspection Service (FSIS) regulates all raw beef, pork, lamb, chicken and turkey, as well as processed meat and poultry products, including hams, sausage, soups, stews, pizzas and frozen dinners (any product that contains 2 percent or more cooked poultry or 3 percent or more raw meat). Under the Federal Meat Inspection Act, the Poultry Products Inspection Act and the Egg Products Inspection Act, FSIS inspects all meat, poultry and eggs prepared for distribution in commerce, including imported products. FSIS develops and improves analytical procedures for detecting microbiological and chemical adulterants and infectious and toxic agents in meat and poultry products (http://www.usda.gov/news/pubs/97arp/arp4.htm). With 27.4 million pounds of ready-to-eat poultry products recalled due to fears of Listeria. Since January 2000, all federally inspected meat and poultry slaughtering and processing plants operate under the HACCP system to ensure meat safety. Schumer’s legislation will give the United State Department of Agriculture (USDA) the authority needed to establish and enforce microbiological standards. These standards will include specific pathogens like Listeria, Salmonella, E. coli and others identified as threats (http://schumer.senate.gov/SchumerWebsite/pressroom/ press_releases/PR01257.html). Food contamination refers to the presence in food of harmful chemicals and microorganisms that can cause consumer illness. This chapter addresses the chemical contamination of foods, as opposed to microbiological contamination, which can be found under food-borne illness (http://en.wikipedia.org/wiki/ Food_contaminants). Contaminants are substances that have not been
International Regulations on Food Contaminants and Residues
31
intentionally added to food. These substances may be present in food as a result of the various stages of its production, packaging, transport or holding. They also might result from environmental contamination. Since contamination generally has a negative impact on the quality of food and may imply a risk to human health, the EU has taken measures to minimize contaminants in foodstuffs. Community measures have been taken for the following contaminants: mycotoxins (aflatoxins, ochratoxin A, fusarium-toxins, patulin), metals (cadmium, lead, mercury, inorganic tin), dioxins and polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAH), 3-mono-chloropropane-1, 2-diol (3-MCPD) and nitrates (http://ec.europa.eu/food/food/chemicalsafety/contaminants/index_en.htm). During their lifetime animals may be treated with medicines for prevention or cure of diseases. In food producing animals such as cattle, pigs, poultry and fish this may lead to residues of the substances used for the treatment in the food products derived from these animals (e.g. meat, milk, eggs). The residues should however not be harmful to the consumer. To guarantee a high level of consumer protection, Community legislation requires that the toxicity of potential residues is evaluated before the use of a medicinal substance in food producing animals is authorized. If considered necessary, maximum residue limits (MRLs) are established and in some cases the use of the relevant substance is prohibited (http://ec.europa.eu/food/food/chemicalsafety/residues/index_en.htm).
2. TOPICS/CATEGORIES COVERED UNDER EU LEGISLATION 2.1 Food safety The EU integrated approach to food safety aims to assure a high level of food safety, animal health, animal welfare and plant health within the EU through coherent farm-to-table measures and adequate monitoring, while ensuring the effective functioning of the internal market (http://europa.eu.int/comm/food/ intro_en.htm). Recent trends in global food production, processing, distribution and preparation are creating an increasing demand for food safety research in order to ensure a safer global food supply (http://www.who.int/foodsafety/en/). The implementation of this approach involves the development of legislative and other actions in order to (a) assure effective control systems and evaluate compliance with EU standards in the food safety and quality, animal health, animal welfare, animal nutrition and plant health sectors within the EU and in third countries in relation to their exports to the EU, (b) manage international relations with third countries and international organizations concerning food safety, animal health, animal welfare, animal nutrition and plant health and (c) manage relations with the European Food Safety Authority (EFSA) and ensure science-based risk management (http://europa.eu.int/comm/food/intro_en.htm).
2.1.1 HACCP Regulation (EC) No 178/2002 (entry into force 1/1/2005) has three main functions (a) Provides the basis for the assurance of a high level of protection of human
32
Ioannis S. Arvanitoyannis
health and consumers’ interest in relation to food, taking into account the diversity in the supply of food, including traditional products, while ensuring the effective functioning of the internal market. It establishes common principles and responsibilities, the means to provide a strong science base, efficient organizational arrangements and procedures to underpin decision-making in matters of food and feed safety. (b) Lays down the general principles governing food and feed at Community and national level. It established the EFSA. (c) It shall apply to all stages of production, processing and distribution of food and feed. It shall not apply to primary production for private domestic use or to the domestic preparation, handling or storage of food for private domestic consumption. The food law shall aim at the prevention of (a) fraudulent or deceptive practices, (b) the adulteration of food and (c) any other practices which may mislead the consumer. Regulation (EC) No 852/2004 (entry into force 1/1/2006) lays down general rules for food business operators on the hygiene of foodstuffs, taking particular account of the following principles: (a) primary responsibility for food safety rests with the food business operator, (b) it is necessary to ensure food safety throughout the food chain, starting with primary production, (c) it is important, for food that cannot be stored safely at ambient temperatures, particularly frozen food, to maintain the cold chain, (d) general implementation of procedures based on the HACCP principles, together with the application of good hygiene practice, should reinforce food business operators’ responsibility, (e) guides to good practice are a valuable instrument to aid food with food hygiene rules and with the application of the HACCP principles, (f) it is necessary to establish microbiological criteria and temperature control requirements based on a scientific risk assessment and (g) it is necessary to ensure that imported foods are of at least the same hygiene standard as food produced in the Community, or are of an equivalent standard. Another Regulation (EC) No 853/2004 (entry into force 1/6/2006) has no application in relation to (a) primary production for private domestic use, (b) the domestic preparation, handling or storage of food for private domestic consumption, (c) the direct supply, by the producer, of small quantities of primary products to the final consumer or to local retail establishments directly supplying to the final consumer, (d) the direct supply, by the producer, of small quantities of meat from poultry and lagomorphs slaughtered on the farm to the final consumer or to local retail establishments directly supplying such meat to the final consumer as fresh meat and (e) hunters who supply small quantities of wild game or wild game meat directly to the final consumer or to local retail establishments directly supplying the final consumer. According to Regulation (EC) No 854/2004 (entry into force 1/1/2006) audits of good hygiene practices shall verify that food business operators apply procedures continuously and properly concerning at least (a) checks on foodchain information, (b) the design and maintenance of premises and equipment, (c) pre-operational, operational and post-operational hygiene, (d) personal hygiene, (e) training in hygiene and in work procedures, (f) pest control, (g) water quality, (h) temperature control and (i) controls on food entering and leaving the establishment and any accompanying documentation.
International Regulations on Food Contaminants and Residues
33
Regulation (EC) No 882/2004 (entry into force 1/1/2006) lays down general rules for the performance of official controls to verify compliance with rules aiming at (a) preventing, eliminating or reducing to acceptable levels risks to humans and animals, either directly or through the environment and (b) guaranteeing fair practices in feed and food trade and protecting consumer interests, including feed and food labeling and other forms of consumer information. A summary of the EU Regulations related to HACCP is given in Table 1.
2.1.2 Pesticide contamination The pesticides have been regulated by three rather old Directives (76/895/EEC, 86/362/EEC, 90/642/EEC), which appeared over a period of 13 years between 1977 and 1990. Directive 76/895/EEC (entry into force 1/1/1977) concerned products intended either for human or, in exceptional cases, animal consumption. For the purposes of this Directive the term ‘‘pesticide residues’’ comprises the residual traces of pesticides, as well as any of the toxic breakdown or metabolized products listed, present in or on the products to which the Directive applies. Member States may not prohibit or impede the putting on the market within their territories of the products referred, on the ground that they contain pesticide residues if the quantity of these residues does not exceed the established MRLs. When a Member State considers that a MRL might endanger the health of humans or of animals other than harmful organisms, that Member State may temporarily reduce that level in its own territory. In that case it shall immediately notify the other Member States and the Commission of the measures taken with a statement of the reasons thereof. The Directive 86/362/EEC (entry into force 7/8/1986) applies to the following crops: wheat, rye, barley, oats, maize, paddy rice, buckwheat, millet, grain sorghum, triticale and other cereals. The MRLs of pesticide residues exceeds 0.1 mg/kg and concerns bromomethane, carbon disulphide, carbon tetrachloride, hydrogen cyanide, cyanides expressed as hydrogen cyanide, hydrogen phosphide, phosphides expressed as hydrogen phosphide. The Directive claims that Member States (a) shall ensure that the products referred do not, from the time they are put into circulation, present a danger to human health as a result of the presence of pesticide residues, (b) may not prohibit or impede the putting into circulation within their territories of the products referred, on the ground that they contain pesticide residues, if the quantity of such residues does not exceed the MRLs, (c) shall prescribe that the products referred, may not contain, from the time they are put into circulation, levels of residues of pesticides greater than those specified and (d) shall take all necessary measures to ensure, at least by check sampling, compliance with the MRLs. There is no application to the products intended for (i) export to third countries, (ii) the manufacture of products other than foodstuffs and (iii) sowing. The Directive 90/642/EEC (entry into force 14/12/1990) also applies to products intended for export to third countries. However, the maximum pesticide residue levels shall not apply in the case of products treated before
Regulation (EC) No 853/2004 (entry into force 1/6/2006) Specific hygiene rules for food of animal origin
Regulation (EC) No 852/2004 (entry into force 1/1/2006) Hygiene of foodstuffs
General principles, principles of transparency,
Regulation (EC) No 178/2002 (entry into force 1/1/2005) General principles and requirements of food law, establishment of the European Food Safety Authority and report of procedures in matters of food safety
of plant origin and processed products of animal origin.
Not applicable to food containing both products
origin for food business operators.
Specific rules on the hygiene of food of animal
Requirements of imports and exports.
hygiene practice.
Food business operators’ obligations. National and Community guides for good
general obligations of food trade, general requirements of food law. Need for independence, transparency, confidentiality and communication of the EFSA. Rapid alert system, crisis management and emergencies.
Main points
Title
Table 1 Regulations (main points and comments) related to HACCP Comments
34 Ioannis S. Arvanitoyannis
general obligations, competent authorities, sampling and analysis, crisis management, official controls on the introduction on food and feed of third countries and financing of official controls. Reference laboratories.
Official controls of Member States relatively
establishments, general principles of official controls and actions in the case of noncompliance. Procedures concerning imports or products of animal origin and fishery products.
Official controls in relation to community
Source: Adapted from [1] with permission from Blackwell Publishing.
Regulation (EC) No 882/2004 (entry into force 1/1/2006) Official controls performed to ensure the verification of compliance with feed and food law, animal health and animal welfare rules
Regulation (EC) No 854/2004 (entry into force 1/1/2006) Specific rules for the organization of official controls on products of animal origin intended for human consumption Repeals Directive EU 70/373/EEC 85/591/EEC 89/397/EEC 93/99/EEC 95/53/EC Decisions 93/383/EEC from 1/1/2006 98/728/EC from 1/1/2006 1999/313/EC from 1/1/2006
International Regulations on Food Contaminants and Residues
35
36
Ioannis S. Arvanitoyannis
export where it can be satisfactorily proved that (a) the third world country of destination requires that particular treatment in order to prevent the introduction of harmful organisms into its territory or (b) the treatment is necessary in order to protect the products against harmful organisms during the transport to the third world country of destination and storage there. The Directive shall not apply to the products referred, where it can be established by appropriate evidence that they are intended for (a) the manufacture of products other than foodstuffs and animal feed or (b) sowing or planting. The products or the parts of them shall not contain, from the time they are put into circulation, pesticide residue levels higher than those specified. In the case of dried products for which maximum levels are not fixed, the maximum level applicable shall be that laid down in the list, taking into account the residue concentration caused by the drying process. Member States shall ensure, at least by checking samples, compliance with the MRLs. The competent authority or authorities of the Member States shall draw up forward programs laying down the nature and frequency of the inspections to be carried out. All the Directives related to pesticide contamination are given in Table 2.
2.1.3 Radioactive contamination Regulation (EC) No 3954/87 (entry into force 2/1/1988) laid down the procedure for determining the maximum permitted levels of radioactive contamination of foodstuffs and of feedingstuffs that may be placed on the market following a nuclear accident or any other case of radiological emergency which is likely to lead to or has led to significant radioactive contamination of foodstuffs and feedingstuffs. In the event of the Commission receiving official information on accidents or on any other case of radiological emergency, substantiating that the maximum permissible levels are likely to be reached or have been reached, it will immediately adopt, if the circumstances so require, a Regulation rendering applicable those maximum permissible levels. In Regulation (EC) No 2219/89 (entry into force 25/7/1989) the conditions for exporting foodstuffs and feedingstuffs after a nuclear accident or any other radiological situation likely to lead to significant radioactive contamination of foodstuffs and feedstuffs are laid down. Foodstuffs and feedingstuffs in which the level of radioactive contamination exceeds the relevant maximum permitted levels may not be exported. The Member States shall carry out checks to ensure that the maximum permitted levels are observed. Regulation (EC) No 737/90 (entry into force 1/4/1990) applies to milk and dairy products for which the maximum permitted level of radioactivity is 370 Bq/kg The accumulated maximum radioactive level in terms of Cs-134 and Cs-137 shall be 370 Bq/kg for milk and milk products and 600 Bq/kg for all other products concerned. The titles, main points and comments of the EU Regulations about radioactive contamination are summarized in Table 3.
Directive 86/362/EEC (entry into force 7/8/ 1986) Setting of maximum residue levels of pesticides in cereals products exported to third world countries, not for edible or drinkable products and for those intended for sowing or planting. Products that contain pesticide residues that exceed the maximum
Not applicable to
Amendments — Directive 86/363/EEC (entry into force 7/8/1986), 88/298/EEC (entry into force 20/5/1988), 93/57/EEC (entry into force 8/7/1993), 94/29/EEC (entry into force 23/7/ 1994), 95/39/EC (entry into force 11/9/1995), 96/33/ EC (entry into force 18/6/1996), 97/41/EC (entry into force 1/8/1997), 97/71/EC (entry into force 18/12/ 1997), 98/82/EC (entry into force 1/11/1998), 1999/ 65/EC (entry into force 8/7/1999), 1999/71/EC (entry into force 1/8/1999), 2000/24/EC (entry into force
Amendments — Directive 80/428/EEC (entry into force 11/9/1980), 81/36/EEC (entry into force 26/2/1981), 82/528/EEC (entry into force 4/8/1982), 88/298/EEC (entry into force 20/5/ 1988), 89/186/EEC (entry into force 10/3/1989), 93/ 58/EEC (entry into force 12/7/1993), 96/32/EC (entry into force 18/6/1996), 97/41/EC (entry into force 1/8/ 1997), 1999/65/EC (entry into force 8/7/1999), 2000/ 24/EC (entry into force 4/5/2000), 2000/57/EC (entry into force 19/10/2000), 2002/66/EC (entry into force 9/8/2002), 2002/71/EC (entry into force 29/8/2002), 2002/79/EC (entry into force 4/11/2002), 2003/60/EC (entry into force 14/7/2003) Regulation (EEC) No 3768/85 (entry into force 1/1/ 1986) and No 807/2003 (entry into force 5/6/2003) Replacement, correction and amendment of articles.
Applicable to products
Directive 76/895/EEC (entry into force 1/1/ 1977) Setting of maximum residue levels of pesticides in fruit and vegetables intended for human and animal nutrition. Not applicable to products exported to third countries. Formal sampling to inspect whether the maximum residue levels are kept.
Comments
Main points
Title
Table 2 Directives (main points and comments) focused on pesticide contamination
International Regulations on Food Contaminants and Residues
37
Directive 90/642/EEC (entry into force 14/12/ 1990) Setting of maximum residue levels of pesticides in certain products of plant origin including fruit and vegetables
Title
Table 2 (Continued )
and vegetables containing the MRLs and of list containing residues of pesticides and their maximum levels. Commission should be annualy informed for the MRLs.
Amendments — Directive 93/58/EEC (entry into force 12/7/1993), 94/30/EC (entry into force 23/7/1994), 95/38/EC (entry into force 11/9/1995), 95/61EC (entry into force 18/6/ 1996), 97/41/EC (entry into force 1/8/1997), 97/71/ EC (entry into force 7/1/1998), 98/82/EC (entry into force 1/11/1998), 1999/65/EC (entry into force 8/7/ 1999), 1999/71/EC (entry into force 1/8/1999), 2000/ 24/EC (entry into force 4/5/2000), 2000/42/EC (entry
4/5/2000), 2000/42/EC (entry into force 1/7/2000), 2000/48/EC (entry into force 23/8/2000), 2000/58/EC (entry into force 19/10/2000), 2000/81/EC (entry into force 11/1/2001), 2001/39/EC (entry into force 21/6/ 2001), 2001/48/EC (entry into force 4/7/2001), 2001/ 57/EC (entry into force 21/8/2001), 2002/76/EC (entry into force 27/9/2002), 2002/79/EC (entry into force 4/11/2002), 2002/97/EC (entry into force 7/1/ 2003), 2003/60/EC (entry into force 14/7/2003), 2003/ 62/EC (entry into force 22/6/2003) Regulation (EC) No 807/2003 (entry into force 5/6/ 2003) Filling, amendment and replacement of articles.
levels are prohibited from circulation. Sampling to inspect whether the maximum residue levels are kept.
Register of list of fruits
Comments
Main points
38 Ioannis S. Arvanitoyannis
Source: Adapted from [1] with permission from Blackwell Publishing.
pesticide residues that exceed the maximum levels are prohibited from circulation.
Products that contain
into force 1/7/2000), 2000/48/EC (entry into force 23/ 8/2000), 2000/57/EC (entry into force 19/10/2000), 2000/58/EC (entry into force 19/10/2000), 2000/81/ EC (entry into force 11/1/2001), 2001/35/EC (entry into force 19/5/2001), 2001/39/EC (entry into force 21/6/2001), 2001/48/EC (entry into force 4/7/2001), 2001/57/EC (entry into force 21/8/2001), 2002/5/EC (entry into force 6/2/2002), 2002/23/EC (entry into force 27/3/2003), 2002/42/EC (entry into force 11/6/ 2002), 2002/66/EC (entry into force 9/8/2002), 2002/ 71/EC (entry into force 29/8/2002), 2002/76/EC (entry into force 27/9/2002), 2002/79/EC (entry into force 4/11/2002), 2002/97/EC (entry into force 7/1/ 2003), 2002/100/EC (entry into force 27/1/2003), 2003/60/EC (entry into force 14/7/2003), 2003/62/EC (entry into force 22/6/2003), 2003/69/EC (entry into force 22/7/2003) Regulation (EC) No 806/2003 (entry into force 5/6/ 2003) Amendment of the Directive relatively with the MRLs.
International Regulations on Food Contaminants and Residues
39
40
Table 3
Ioannis S. Arvanitoyannis
Regulations (main points and comments) dealing with radioactive contamination
Title
Main points
Comments
Regulation (EC) No 3954/87 Maximum permitted levels Amendment Regulation (EC) (entry into force 2/1/ of radioactive No 2218/89 1988) contamination of Replacement of Determination of maximum foodstuffs and feedstuffs the Annex (entry permitted levels of in case of nuclear accident. into force 25/7/ radioactive contamination Duration of each regulation exceeds up to 1989) of foodstuffs and three months. feedstuffs following a Any foodstuff or feedstuff nuclear accident or any that exceeds the other case of radiological maximum permitted emergency levels is banned from the market disposal. Regulation (EC) No 2219/89 Conditions for exporting foodstuffs and feedstuffs (entry into force 25/7/ after a nuclear accident. 1989) Any foodstuff or feedstuff Special conditions for exporting foodstuffs and that exceeds the feedstuffs following a maximum permitted nuclear accident or any levels is banned for other case of radiological export. emergency Regulation (EC) No 737/90 (entry into force 1/4/ 1990) Conditions governing imports of agricultural products originating in third countries following the accident at the Chernobyl nuclear power station
Amendment Regulation (EC) originating from third No 616/2000 countries. Replacement of Determination of articles (entry maximum accumulated into force 24/3/ radioactivity of Cs134 and 2000) Cs137. Control measures in case of non-compliance. Application for products
Source: Adapted from [1] with permission from Blackwell Publishing.
2.1.4 Residues of veterinary medicinal products According to Directive 96/22/EC (entry into force 23/5/1996) Member States shall prohibit (a) the placing on the market of stilvenes, stilbene derivatives, their salts and esters and thyrostatic substances for administering to animals of all species and (b) the placing on the market of beta-agonists for administering to animals, the flesh and products of which are intended for human consumption. They shall, also, prohibit (i) the administering to a farm or aquaculture animal of
International Regulations on Food Contaminants and Residues
41
substances having a thyrostatic, androgenic or gestagenic action and of betaagonists, (ii) the holding of animals on a farm, the placing on the market or slaughter for human consumption of farm animals or of aquaculture animals that contain the substances referred or in which the presence of such substances has been established, (iii) the placing on the market for human consumption of aquaculture animals to which substances have been administrated and of processed products derived from such animals, (iv) the placing on the market of specific animals and (v) the processing of specific kinds of meat. Member States may authorize (1) the administering to farm animals, for therapeutic purposes, of oestradiol 17a, testosterone and progesterone and derivatives, (2) the administering, for therapeutic purposes, of authorized veterinary medicinal products containing (i) allyl trenbolone, administered orally, or beta-agonists to equidae and pets, (ii) beta-agonists, in the form of an injection to induce tocolysis in cows when calving. The official checks are carried out by the competent national authorities without prior notice. Member States shall also prohibit the importation from third countries (a) farm or aquaculture animals to which products or substances referred have been administered by any means whatsoever or to which substances or products referred have been administered, unless those substances or products were administered in compliance with the provisions and requirements laid down and the withdrawal periods allowed in international recommendations have been observed and (b) meat or products obtained from animals the importation of which is prohibited. In agreement with Directive 96/23/EC (entry into force 23/5/1996) substances having anabolic effect and unauthorized substances are (1) stilbenes, stilbene derivatives, and their salts and esters, (2) antithyroid agents, (3) steroids, (4) resorcylic acid lactones, including zeranol and beta-agonists. Moreover, veterinary drugs and contaminants such as (A) antibacterial substances, including sulfonamides, quinolones, (B) other veterinary drugs (anthelmintics, anticoccidials, carbamates and pyrethroids, sedatives, non-steroidal antiinflammatory drugs, other pharmacologically active substances) and (C) other substances and environmental contaminants (organochlorine compounds, including PCBs, organophosphorus compounds, chemical elements, mycotoxins, dyes). The plan used to carry out the required inspections shall (a) provide for detection of groups of residues or substances according to type of animal, (b) specify in particular the measures for detection of the presence of the substances referred in the animals, in the drinking water of the animals and in all places where the animals are bred or kept and residues of the aforementioned substances in live animals, their excrement and body fluids and in animal tissues and products such as meat, milk, eggs and honey and (c) comply with the sampling rules and levels. Member States may have official random checks conducted (i) during the manufacture of the substances and during their handling, storage, transport, distribution and sale or acquisition, (ii) at any point in the animal feedingstuffs production and distribution chain and (iii) throughout the production chain of animals and raw materials of animal origin covered by this Directive. Where illegal treatment is established, the competent authority must ensure that the livestock is immediately placed under
42
Ioannis S. Arvanitoyannis
official control. Where there is evidence of residues of authorized substances or products of a level exceeding the maximum limit for residues, the competent authority shall carry out an investigation in the farm of origin or departure, as applicable, to determine why the above limit was exceeded. In the event of repeated infringements of MRLs when animals are placed on the market by a farmer or products are placed on the market by a farmer or a processing establishment, intensified checks on the animals and products from the farm and/or establishment in question must be carried out by the competent authorities for a period of at least six months, products or carcases being impounded pending the results of analysis of the samples. Some representative points and comments of the Directives regarding residues of veterinary medical products are given in Table 4.
2.1.5 Contaminants A rather recent Regulation (EC) No 466/2001 (entry into force 5/4/2002) covers several foods both of plant and animal origin (1) fresh spinach, preserved-deep frozen or frozen spinach, fresh lettuce regarding the level of nitrates, (2) roundnuts, nuts, dried fruit, cereals, milk regarding the level of aflatoxins, (3) milk, infant fomulae, meat of bovine animals, sheep, pig and poultry, edible offal of cattle, sheep, pig and poultry, muscle meat of fish, muscle meat of wedge sole, crustaceans, bivalve molluscs, cephalopods, cereals, vegetables, fruit, berries, fats and oils, fruit juices, wines, horsemeat, liver and kidney of cattle, sheep, pig and poultry, rice, soybeans regarding the amount of heavy metals (lead, cadmium, mercury). Member States may, where justified, authorize for a transitional period the placing on the market of fresh lettuces and fresh spinach, grown and intended for consumption in their territory, with nitrate levels higher than those set as maximum levels. Member States shall communicate to the Commission by June 30 of each year, the results of their monitoring and report on the measures taken and the progress made with regard to the application and improvement of codes of good agricultural practice to reduce nitrate levels in lettuce and spinach. This information shall also contain the data on which their codes of good agricultural practice are based. The Regulation (EC) No 466/2001 has been replaced by the Regulation (EC) No 1881/2006. The latter regulation contains the community measures for the following contaminants: mycotoxins (aflatoxins, ochratoxin A, fusarium-toxins and patulin), metals (cadmium, lead, mercury and inorganic tin), dioxins and PCBs, PAHs, 3-MCPD and nitrates. The summary of this Regulation is given in Table 5.
2.1.6 Biological safety Regulation (EC) No 999/2001 (entry into force 1/7/2001) has no application to (a) cosmetic or medicinal products or medical devices, or to their starting materials or intermediate products, (b) products which are not intended for use in human food, animal feed or fertilisers, or to their starting materials or intermediate products, (c) products of animal origin intended for exhibition, teaching, scientific research, special studies or analysis and (d) live animals used in or
International Regulations on Food Contaminants and Residues
Table 4 Title
43
Directives (main points and comments) for residues of veterinary medical products Main points
Comments
The placing on the market Directive 96/22/EC (entry and the administering to into force 23/5/1996) The prohibition on the use farm animals of substances in stockfarming of certain having a thyrostatic action substances having a or substances having an hormonal or thyrostatic oestrogenic, androgenic or action and of beta-agonists gestagenic action and of stilbenes and beta-agonists are prohibited. A certain number of these substances may be used for therapeutic purposes provided their use is controlled.
Repeals Directive EU 81/602/EEC from 1/7/1997 Directive EU 88/146/EEC from 1/7/1997 Directive EU 88/299/EEC from 1/7/1997
The monitoring substances Directive 96/23/EC (entry are divided into two into force 23/5/1996) groups: substances having Measures to monitor certain anabolic effect and substances and residues unauthorized substances thereof in live animals and on the one hand, and animal products veterinary drugs and contaminants on the other. Determination of the official control measures and of those taken in the event of infringement.
Repeals Directive EU 85/358/EEC from 1/7/1997 Directive EU 86/469/EEC from 1/7/1997 Directive EU 89/197/EEC from 1/7/1997 Directive EU 91/664/EEC from 1/7/1997
Source: Adapted from [1] with permission from Blackwell Publishing.
intended for research. Each Member State shall carry out an annual program for monitoring BSE and scrapie. Member States shall inform the Commission of the emergence of a Transmissible Spongiform Encephalopathy (TSE) other than BSE. All official investigations and laboratory examinations shall be recorded. The purpose of Regulation (EC) No 2160/2003 (entry into force 12/12/2003) is to ensure that proper and effective measures are taken to detect and to control Salmonella and other zoonotic agents at all relevant stages of production, processing and distribution, particularly at the level of primary production, including in feed, in order to reduce their prevalence and the risk they pose to public health. This Regulation shall cover (a) the adoption of targets for the reduction of the prevalence of specified zoonoses in animal populations,
44
Table 5
Ioannis S. Arvanitoyannis
Regulation (main points and comments) related to contaminants
Title
Main points
Comments
Regulation (EC) No 466/2001 (entry into force 5/4/2002) Setting maximum levels for certain contaminants in foodstuffs
Setting of maximum
Amendments Regulation (EC) No 1881/2006 (entry into force 10/1/2007) Replacement of the Annex
levels for certain contaminants in foodstuffs.
Source: Adapted from [1] with permission from Blackwell Publishing.
(b) the approval of specific control programs established by Member States and food and feed business operators, (c) the adoption of specific rules concerning certain control methods applied in the reduction of the prevalence of zoonoses and zoonotic agents and (d) the adoption of rules concerning intra-Community trade and imports from third countries of certain animals and products thereof. Some points of the EU legislation focused on biological safety are stated in Table 6.
2.1.7 Packaging Packaging per se and the food-packaging interactions were considered an issue of crucial importance because several problems, ranging from poisoning to death, occurred over the years. Most of these problems were either due to usage of inappropriate packaging materials or migration (of monomers, oligomers, catalysts, colorants etc.). A great number of Directives (more than ten) were published to fill this gap on packaging issues. Directive 75/106/EEC (entry into force 19/6/1976) relates to prepackages containing the liquid products measured by volume for the purpose of sale in individual quantities of between 5 mL and 10 L inclusive. This Directive shall not apply to prepackages containing the products which are vatted, bottled and labeled in volumes not exceeding 0.25 L and are intended for professional use and which are intended either for consumption on board aircraft, ships and trains or for sale in duty-free shops. The prepackages may be marked with the EEC mark. The actual contents of prepackages may be measured directly by means of weighing instruments or volumetric instruments or, in the case of liquids, indirectly, by weighing the prepacked product and measuring its density. Irrespective of the method used, the error made in measuring the actual contents of a prepackage shall not exceed one-fifth of the tolerable negative error for the nominal quantity in the prepackage. The procedure for measuring the actual contents of a prepackage may be the subject of domestic regulations in each Member State. The checking of prepackages shall be carried out by sampling and shall be in two parts a check covering the actual contents of each prepackage in the sample and another check on the average of the actual contents of the prepackages in the sample. A batch of prepackages shall be considered
International Regulations on Food Contaminants and Residues
Table 6
45
Regulations (main points) with regard to biological safety
Title
Main points
Regulation (EC) No 999/2001 (entry into force 1/7/2001) Rules for the prevention, control and eradication of certain TSEs.
Rules for the prevention, control and
Regulation (EC) No 2160/2003 (entry into force 12/12/2003) The control of Salmonella and other specified food-borne zoonotic agents.
Measures to detect and to control
eradication of TSEs in animals. Application to the production and
placing on the market of live animals and products of animal origin and in certain specific cases to exports thereof. Member States shall carry out an annual program for monitoring BSE and scrapie. Salmonella and other zoonotic agents. Application to production, processing
and distribution. Designation of a competent authority
for each Member State and arrangement of responsibilities. Source: Adapted from [1] with permission from Blackwell Publishing.
acceptable if the results of both these checks satisfy the acceptance criteria. For each of these checks, there are two sampling plans one for non-destructive testing, i.e., testing which does not involve opening the package and the other for destructive testing, i.e., testing which involves opening or destroying the package. Directive 76/211/EEC (entry into force 23/1/1976) relates to prepackages containing products relating to the making-up by volume of certain prepackaged liquids, and intended for sale in constant unit nominal quantities which are equal to values predetermined by the packer, expressed in units of weight or volume, not less than 5 g or 5 mL and not more than 10 kg or 10 L. A prepackage within the meaning of this Directive is the combination of a product and the individual package in which it is prepacked. A product is prepacked when it is placed in a package of whatever nature without the purchaser being present and the quantity of product contained in the package has a predetermined value and cannot be altered without the package either being opened or undergoing a perceptible modification. All prepackages must bear an indication of the weight or volume of the product, known as ‘‘nominal weight’’ or ‘‘nominal volume’’, which they are required to contain. Prepackages containing liquid products shall be marked with their nominal volume and prepackages containing other products shall be marked with their nominal weight, except in the case of trade practice or national regulations which provide otherwise and which are identical in all Member States, or in the case of contrary Community rules. If trade practice
46
Ioannis S. Arvanitoyannis
or national regulations are not the same in all Member States for a category of products or for a type of prepackage, those prepackages must at least show the metrological information corresponding to the trade practice or national regulations prevailing in the country of destination. In Directive 78/142/EEC (entry into force 1/2/1978), the presence of vinyl chloride monomer in, and possible migration from, materials and articles prepared with vinyl chloride polymers or copolymers, hereinafter called ‘‘materials and articles’’, which in their finished state are intended to come into contact with foodstuffs, or which are in contact with foodstuffs and are intended for that purpose is analysed. Materials and articles must not pass on to foodstuffs which are in or have been brought into contact with such materials and articles with any vinyl chloride detectable by the method which complies with the criteria laid down in this Directive. Maximum vinyl chloride monomer level in materials and articles laid down 1 mg/kg in the final product. Criteria applicable to the method of determining the level of vinyl chloride in materials and articles and of determining vinyl chloride released by materials and articles (1) the level of vinyl chloride in materials and articles and the level of vinyl chloride released by materials and articles to foodstuffs are determined by means of gas-phase chromatography using the ‘‘headspace’’ method, (2) for the purposes of determining vinyl chloride released by materials and articles to foodstuffs, the detection limit shall be 0.701 mg/kg and (3) vinyl chloride released by materials and articles to foodstuffs is in principle determined in the foodstuffs. When the determination in certain foodstuffs is shown to be impossible for technical reasons, Member States may permit determination by simulants for these particular foodstuffs. According to Directive 80/232/EEC (entry into force 17/3/1980) the products shall be divided into three groups (a) products sold by weight or by volume, (b) products sold by weight or by volume and put up in the rigid containers and (c) products put up in aerosol form. Food products in which the Directive shall apply are butter, margarine, emulsified or non-animal and vegetable fats (low fat spreads), fresh cheeses except ‘‘petits suisses’’ and other cheeses put up in the same way, table and cooking salt, impalpable sugars, red or brown sugars, candy sugars, cereal products (excluding foods for infants), dried vegetables, dried fruits, ground or unground roasted coffee, chicory and coffee substitutes, frozen products (fruit and vegetables and pre-cooked potatoes for chips, fish fillets and portions, breaded or not breaded, fish fingers). In Directive 82/711/EEC (entry into force 4/11/1982) reference is made to plastic materials and articles, that is to say to materials and articles and parts thereof (A) consisting exclusively of plastics or (B) composed of two or more layers of materials, each consisting exclusively of plastics, which are bound together by adhesives or by any other means, which, in the finished product state, are intended to come into contact or are brought into contact with foodstuffs and are intended for that purpose. For the purposes of this Directive, plastics shall mean the organic macromolecular compounds obtained by polymerization, polycondensation, polyaddition or any other similar process from molecules with a lower molecular weight or by chemical alteration of
International Regulations on Food Contaminants and Residues
47
natural macromolecules. Silicones and other similar macromolecular compounds shall also be regarded as plastics. Other substances or matter may be added to such macromolecular compounds. However, the following shall not be regarded as plastics: (i) varnished or unvarnished regenerated cellulose film, (ii) elastomers and natural and synthetic rubber, (iii) paper and paperboard, whether modified or not by the addition of plastics, (iv) surface coatings obtained from paraffin waxes, including synthetic paraffin waxes, and/or micro-crystalline waxes and mixtures of the waxes listed in the first indent with each other and/or with plastics. The tests are to be carried out using all the simulants mentioned below, taking a fresh sample of the plastic material or article for each simulant: distilled water or water of equivalent quality, 3% acetic acid (w/v) in aqueous solution, 15% ethanol (v/v) in aqueous solution, rectified olive oil, if for technical reasons connected with the method of analysis it is necessary to use different simulants, olive oil must be replaced by a mixture of synthetic triglycerides or by sunflower oil. Directive 93/10/EEC (entry into force /1/1994) claimed that it shall apply to regenerated cellulose film which either (a) constitutes a finished product in itself or (b) forms part of a finished product containing other materials, and which is intended to come into contact with foodstuffs or which, by virtue of its purpose, does come into such contact. This Directive does not apply to (a) regenerated cellulose film which, on the side intended to come into contact with foodstuffs or which, by virtue of its purpose does come into such contact, has a coating exceeding 50 mg/dm2, (b) synthetic casings of regenerated cellulose. Printed surfaces of regenerated cellulose film shall not come into contact with the foodstuffs. Member States shall (i) permit, as from 1/1/1994, the trade in and use of regenerated cellulose film which is intended to come into contact with foodstuffs complying with this Directive, (ii) prohibit, as from 1/1/1994, the trade in and use of regenerated cellulose film which is intended to come into contact with foodstuffs not complying with this Directive and (iii) prohibit, as from 1/1/1995, the trade in and use of regenerated cellulose film which is intended to come into contact with foodstuffs. The aim of Directive 94/62/EC (entry into force 31/12/1994) was to harmonize national measures concerning the management of packaging and packaging waste in order, on the one hand, to prevent any impact thereof on the environment of all Member States as well as of third countries or to reduce such impact, thus providing a high level of environmental protection, and, on the other hand, to ensure the functioning of the internal market and to avoid obstacles to trade and distortion and restriction of competition within the Community. To this end this Directive lays down measures aimed, as a first priority, at preventing the production of packaging waste and, as additional fundamental principles, at reusing packaging, at recycling and other forms of recovering packaging waste and, hence, at reducing the final disposal of such waste. This Directive covers all packaging placed on the market in the Community and all packaging waste, whether it is used or released at industrial, commercial, office, shop, service, household or any other level, regardless of the material used. This Directive shall apply without prejudice to existing quality
48
Ioannis S. Arvanitoyannis
requirements for packaging such as those regarding safety, the protection of health and the hygiene of the packed products or to existing transport requirements. For the purposes of this Directive packaging, shall mean all products made of any materials of any nature to be used for the containment, protection, handling, delivery and presentation of goods, from raw materials to processed goods, from the producer to the user or the consumer. Packaging consists only of (a) sales packaging or primary packaging, (b) grouped packaging or secondary packaging and (c) transport packaging or tertiary packaging. Member States shall take the necessary measures to attain the following targets covering the whole of their territory: (a) no later than five years from the date by which this Directive must be implemented in national law, between 50% as a minimum and 65% as a maximum by weight of the packaging waste will be recovered, (b) within this general target, and with the same time limit, between 25% as a minimum and 45% as a maximum by weight of the totality of packaging materials contained in packaging waste will be recycled with a minimum of 15% by weight for each packaging material and (c) no later than 10 years from the date by which this Directive must be implemented in national law, a percentage of packaging waste will be recovered and recycled. The Commission shall promote, in particular, the preparation of European standards relating to (i) criteria and methodologies for life-cycle analysis of packaging, (ii) the methods for measuring and verifying the presence of heavy metals and other dangerous substances in the packaging and their release into the environment from packaging and packaging waste, (iii) criteria for a minimum content of recycled material in packaging for appropriate types of packaging, (iv) criteria for recycling methods, (v) criteria for composting methods and produced compost and (vi) criteria for the marking of packaging. Member States shall ensure that the sum of concentration levels of lead, cadmium, mercury and hexavalent chromium present in packaging or packaging components shall not exceed the following: (A) 600 ppm by weight two years after the date 30/6/1996, (B) 250 ppm by weight three years after the date 30/6/1996 and (C) 100 ppm by weight five years after the date 30/6/1996. Information for users of packaging Member States shall take measures, within two years of the date referred to this Directive, to ensure that users of packaging, including in particular consumers, obtain the necessary information about (i) the return, collection and recovery systems available to them, (ii) their role in contributing to reuse, recovery and recycling of packaging and packaging waste, (iii) the meaning of markings on packaging existing on the market and (iv) the appropriate elements of the management plans for packaging and packaging waste. Directive 97/23/EC (entry into force 29/7/1997) applies to the design, manufacture and conformity assessment of pressure equipment and assemblies with a maximum allowable pressure greater than 0.5 bar. Member States shall not, on grounds of the hazards due to pressure, prohibit, restrict or impede the placing on the market or putting into service under the conditions specified by the manufacturer of pressure equipment or assemblies which comply with this Directive and bear the CE marking indicating that they have undergone conformity assessment. Pressure equipment and assemblies the conformity of
International Regulations on Food Contaminants and Residues
49
which has been assessed by a user inspectorate shall not bear the CE marking. The pressure equipment and assemblies referred to may be used only in establishments operated by the group of which the inspectorate is part. The group shall apply a common safety policy as regards the technical specifications for the design, manufacture, inspection, maintenance and use of pressure equipment and assemblies. The user inspectorates shall act exclusively for the group of which they are part. The CE marking shall be affixed in a visible, easily legible and indelible fashion to each item of pressure equipment which is complete or is in a state permitting final assessment. It is not necessary for the CE marking to be affixed to each individual item of pressure equipment making up an assembly. Individual items of pressure equipment already bearing the CE marking when incorporated into the assembly shall continue to bear that marking. Where the pressure equipment or assembly is subject to other Directives covering other aspects which provide for the affixing of the CE marking, the latter shall indicate that the pressure equipment or assembly in question is also presumed to conform to the provisions of this Directive. Pressure equipment must be designed, manufactured and checked, and if applicable equipped and installed, in such a way as to ensure its safety when put into service in accordance with the manufacturer’s instructions, or in reasonably foreseeable conditions. In choosing the most appropriate solutions, the manufacturer must apply the principles set out below in the following order: (i) eliminate or reduce hazards as far as is reasonably practicable, (ii) apply appropriate protection measures against hazards which cannot be eliminated and (iii) where appropriate, inform users of residual hazards and indicate whether it is necessary to take appropriate special measures to reduce the risks at the time of installation and/or use. Where the potential for misuse is known or can be clearly foreseen, the pressure equipment must be designed to prevent danger from such misuse or, if that is not possible, adequate warning be given that the pressure equipment must not be used in that way. The method of operation specified for pressure equipment must be such as to preclude any reasonably foreseeable risk in operation of the equipment. Particular attention must be paid, where appropriate, to (a) closures and openings, (b) dangerous discharge of pressure relief blow-off, (c) devices to prevent physical access while pressure or a vacuum exists, (d) surface temperature taking into consideration the intended use and (e) decomposition of unstable fluids. The manufacturer must ensure the competent execution of the provisions set out at the design stage by applying the appropriate techniques and relevant procedures, especially with a view to the aspects set out below. Preparation of the component parts (e.g., forming and chamfering) must not give rise to defects or cracks or changes in the mechanical characteristics likely to be detrimental to the safety of the pressure equipment. Permanent joints and adjacent zones must be free of any surface or internal defects detrimental to the safety of the equipment. The properties of permanent joints must meet the minimum properties specified for the materials to be joined unless other relevant property values are specifically taken into account in the design calculations. Where there is a risk that the manufacturing process will change the material properties to an extent which would impair the safety of the
50
Ioannis S. Arvanitoyannis
pressure equipment, suitable heat treatment must be applied at the appropriate stage of manufacture. Suitable procedures must be established and maintained for identifying the material making up the components of the equipment which contribute to pressure resistance by suitable means from receipt, through production, up to the final test of the manufactured pressure equipment. Directive 2002/16/EC (entry into force 15/3/2002) is applicable to materials and articles which, in the finished product state, are intended to come into contact or are brought into contact with foodstuffs and are intended for that purpose and which are manufactured with or contain one or more of the following substances: (a) 2,2-bis(4-hydroxyphenyl)propane bis(2,3-epoxypropyl) ether (hereinafter BADGE) and some of its derivatives, (b) bis(hydroxyphenyl)methane bis(2,3-epoxypropyl)ethers (hereinafter BFDGE) and some of their derivatives and (c) other novolac glycidyl ethers (hereinafter NOGE) and some of their derivatives. For the purposes of this Directive, materials and articles are (i) materials and articles made of any type of plastics, (ii) materials and articles covered by surface coatings and (iii) adhesives. This Directive shall not apply to containers or storage tanks having a capacity greater than 10,000 L or to pipelines belonging to or connected with them, covered by special coatings called ‘‘heavy-duty coatings’’. The sum of the migration levels of the following substances: (a) BADGE, (b) BADGE H2O, (c) BADGE HCl, (d) BADGE 2HCl, (e) BADGE H2O HCl shall not exceed the following limits: (i) 1 mg/kg in foodstuffs or in food simulants (analytical tolerance excluded) or (ii) 1 mg/6 dm2 in accordance with this Directive. According to proposal of Regulations COM(2003)0689 and COD(2003)0272, the target of this Regulation is to ensure the effective functioning of the internal market in relation to materials and articles intended to come into contact with foodstuffs, while providing the basis for securing a high level of protection of human health and the interests of consumers. This Regulation shall apply to materials and articles, including active and intelligent food contact materials and articles, which in their finished state (a) are intended to be brought into contact with food or (b) are already brought into contact with food and are intended for that purpose or (c) can reasonably be expected to be brought into contact with foods or to transfer their constituents to food. This Regulation shall not apply to (a) materials and articles which were manufactured and placed on the market before 1/1/1980 and which are supplied as antiques, (b) covering or coating products, such as the products covering cheese rinds, prepared meat products or fruits, which form part of food and may be consumed together with this food and (c) fixed public or private water supply equipment. Active food contact materials and articles means materials and articles that are intended to extend the shelf-life or to maintain or improve the condition of packaged food. They are designed to deliberately incorporate components that would release or absorb substances into or from the packaged food or the environment surrounding the food. Intelligent food contact materials and articles means materials and articles which monitor the condition of packaged food or the environment surrounding the food. Materials and articles shall be manufactured in compliance with good
International Regulations on Food Contaminants and Residues
51
manufacturing practice so that, under normal or foreseeable conditions of use, they do not transfer their constituents to food in quantities which could (i) endanger human health or (ii) bring about an unacceptable change in the composition of the food or a deterioration in the organoleptic characteristics thereof. For the groups of materials and articles and where appropriate, combinations of those materials and articles, specific measures may be adopted in accordance with the Directive. Those specific measures may include (a) a list of the substances and the use of which is authorized to the exclusion of all others, (b) purity standards for substances, (c) special conditions of use for substances and/or the materials and articles in which they are used, (d) specific limits on the migration of certain constituents or groups of constituents into or onto food, taking due account of other possible sources of exposure to those constituents, (e) an overall limit on the migration of constituents into or onto food, (f) provisions aimed at protecting human health against hazards arising from oral contact with materials and articles, (g) other rules to ensure compliance with this Directive, (h) basic rules for checking compliance with this Directive, (i) rules concerning the collection of samples and the methods of analysis to check compliance with this Directive, (j) additional provisions for ensuring traceability of materials and articles and (k) provisions requiring that the Commission establishes and maintains a publicly available Community Register (‘‘Register’’) of authorized substances, materials or articles. The applicant may, in accordance with the procedure laid down in this Directive, apply for a modification of the existing authorization. The application shall be accompanied by the following: (a) a reference to the original application, (b) a technical dossier containing the new information according to the guidelines, (c) a new complete summary of the technical dossier in a standardised form. The traceability of the materials and articles shall be established at all stages of manufacture, processing and distribution. Business operators shall have in place systems and procedures to allow the identification of the businesses from which and to which the materials or articles and, where appropriate, substances or products used in their manufacture have been supplied. That information shall be made available to the competent authorities on demand. The materials and articles, which are placed on the market in the Community, shall be adequately labeled or identified to facilitate their traceability through relevant documentation or information. List of groups of materials and articles which may be covered by specific measures are active and intelligent materials and articles, adhesives, ceramics, cork, elastomers and rubbers, glass, ion-exchange resins, metals and alloys, paper and board, plastics, printing inks, regenerated cellulose, textiles, varnishes and coatings, waxes and wood. All the EU Directives/Regulations dealing with packaging are given in Table 7.
2.2 Food quality The aim is to provide advice for schemes of best practice and help consumers by promoting best practice amongst assurance schemes. It covers relevant legislation, advice on the setting and delivery of production standards and
Amendments — Directive EU 78/89/EEC (entry into force 1/1/80) 79/1005/EEC (entry into force 1/1/1981) 85/10/EEC (entry into force 20/12/1985) 88/316/EEC (entry into force 30/6/1988) 89/676/EEC (entry into force 1/7/1990) Replacement and repeal of specific parts of articles and annexes. Amendment Directive EU 78/891/EEC (entry into force 29/9/1978) Replacements relatively the technical progress in the annexes.
Application to packages containing liquid products, measured by volume and intended for sale in unit quantities varying between 5 mL and 10 L. All prepackages must bear an indication of the volume of the liquid which they are required to contain.
Application to prepackages containing products, except liquids, intended for sale in constant unit nominal quantities. All prepackages must bear an indication of the weight or volume of the product.
Materials and articles which are intended to come into contact with foodstuffs can transfer vinyl chloride monomer to these articles in quantities liable to endanger human health. The Directive specifies that such materials and articles must not contain vinyl chloride monomer in a quantity exceeding 1 mg/kg of finished product and must not pass on to foodstuffs more than 0.01 mg/kg of vinyl chloride monomer.
Directive 75/106/EEC (entry into force 19/6/1976) Approximation of the laws of the Member States relating to the making-up by volume of certain prepackaged liquids
Directive 76/211/EEC (entry into force 23/1/1976) Approximation of the laws of the Member States relating to the making-up by weight or by volume of certain prepackaged products
Directive 78/142/EEC (entry into force 1/2/1978) Approximation of the laws of the Member States relating to materials and articles which contain vinyl chloride monomer and are intended to come into contact with foodstuffs
Comments
Main points
Title
Table 7 Directives (main points and comments) dealing with packaging
52 Ioannis S. Arvanitoyannis
This Directive shall apply to products put up in prepackages. It shall not apply to prepackaged products intended solely for professional use. The products referred to in Directive shall be divided into three groups.
Relating to testing migration of constituents of plastic materials and articles intended to come into contact with foodstuffs. Migration tests may be carried out using simulants. Verification of compliance of migration into foodstuffs shall be carried out under the most extreme conditions of time and temperature foreseeable in actual use.
This Directive shall apply to regenerated cellulose film. This Directive does not apply to regenerated cellulose film which, on the side intended to come into contact with foodstuffs or which, by virtue of its purpose does come into such contact, has a coating exceeding 50 mg/dm2 and synthetic casings of regenerated cellulose. Printed surfaces of regenerated cellulose film shall not come into contact with the foodstuffs.
This Directive aims to harmonize national measures concerning the management of packaging and packaging waste in order to prevent any impact thereof on the
Directive 82/711/EEC (entry into force 4/11/1982) Laying down the basic rules necessary for testing migration of the constituents of plastic materials and articles intended to come into contact with foodstuffs
Directive 93/10/EEC (entry into force 1/1/1994) Relating to materials and articles made of regenerated cellulose film intended to come into contact with foodstuffs
Directive 94/62/EC (entry into force 31/12/1994)
Directive 80/232/EEC (entry into force 17/3/1980) Approximation of the laws of the Member States relating to the ranges of nominal quantities and nominal capacities permitted for certain prepackaged products
Repeal Directive EU 85/339/EEC from 30/6/1996
Repeal Directive EU 83/229/EEC from 1/1/94 Amendments Directive EU 93/111/EEC (entry into force 17/12/1993) Replacement of a part of an article. Directive EU 2004/14/EC (entry into force 24/3/2004) Addition and replacement in articles.
Amendments Directive EU 93/8/EEC (entry into force 22/3/93) 97/48/EC (entry into force 1/9/ 97) Lists of simulants which are used in testing migration. Replacement of the annexes.
International Regulations on Food Contaminants and Residues
53
Comments Amendments Directive EU 97/129/EC (entry into force 12/3/1997) Identification system for packaging materials. Directive EU 97/138/EC (entry into force 12/3/1997) Formats relating to the database system. Directive EU 1999/42/EC (entry into force 3/2/1999) Measures relating to packaging and packaging waste. Directive EU 1999/177/EC (entry into force 28/2/1999) Conditions for a derogation for plastic crates and plastic pallets in relation to the heavy metal concentration levels. Directive EU 1999/823/EC (entry into force 12/12/1999) Confirming the measures notified by the Netherlands on packaging and packaging waste. Directive EU 2001/171/EC (entry into force 1/3/2001) Establishing the conditions for a derogation for glass packaging in relation to the heavy metal concentration levels.
Main points environment, to ensure the functioning of the internal market and to avoid obstacles to trade. This Directive covers all packaging placed on the market in the Community and all packaging waste, whether it is used or released at industrial, commercial, office, shop, service, household or any other level, regardless of the material used. Labeling of packaging. Concentration levels of heavy metals present in packaging.
Title
Packaging and packaging waste
Table 7 (Continued )
54 Ioannis S. Arvanitoyannis
Repeal Directive EU 2001/61/EC
Repeals Decision EU 80/590/EC Decision EU 89/109/EC
Materials and articles containing certain substances may transfer significant levels of these substances to foodstuffs (migration), particularly when used as additives, and thus represent a potential risk to human health. It shall apply to plastic materials and articles, materials and articles covered by surface coatings and adhesives.
Authorization of the placing on the market of two types of packaging which act ‘‘intelligently’’ in contact with foodstuffs. A positive list of authorized substances may be established. Authorization of the marketing of new plastics by authorizing the use of new substances in their manufacture.
Proposal of Regulation COM(2003)0689 COD(2003)0272 Materials and articles intended to come into contact with food
Source: Adapted from [1] with permission from Blackwell Publishing.
Directive 2002/16/EC (entry into force 15/3/2002) Use of certain epoxy derivatives in materials and articles intended to come into contact with foodstuffs
Repeal Article 22 of Directive EU 76/ 767/EEC from 29/11/1999.
This Directive applies to equipment and assemblies subject to a maximum allowable pressure PS exceeding 0.5 bar. The assessment procedures depend on the risk inherent in the pressure equipment.
Directive 97/23/EC (entry into force 29/7/1997) Approximation of the laws of the Member States concerning pressure equipment
Directive EU 2001/524/EC (entry into force 18/7/2001) Publication of references for standards EN 13428:2000, EN 13429:2000, EN 13430:2000, EN 13431:2000 and EN 13432:2000.
International Regulations on Food Contaminants and Residues
55
56
Ioannis S. Arvanitoyannis
transparency for consumers. Food safety is the prime condition for food quality and an absolute, non-negotiable must. This is also true of compliance with legally established standards for the environment and animal welfare since they relate to the protection of natural resources and requirements of an ethical nature, in addition to the characteristics of the products (http://europa.eu.int/comm/ agriculture/foodqual/index_en.htm). Food Quality covers food marketing, consumer research, sensory science and nutrition, as well as food research and development and quality assurance. It is aimed at food industry professionals and researchers aiming to match consumer preferences and food quality (http:// www.elsevier.com/wps/find/journaldescription.cws_home/405859/description# description). Legislation in the food safety field started in the 1960s, grew more intense in the 1990s with the advent of the single market. The 1992 and 1999 common agricultural policy reforms emphasised agri-environmental measures and aid for extensification, and also in 1992 there was the introduction of European quality labels. Community legislation cannot and should not take over entirely from that of the Member States and attempt to cover all aspects of quality; rather, it should seek to work in tandem on pursuing a policy to foster quality (http://europa.eu.int/comm/agriculture/foodqual/index_en.htm).
2.2.1 Labeling, general provisions Directive 90/496/EEC (entry into force 1/10/1990) concerns nutrition labeling of foodstuffs to be delivered as such to the ultimate consumer, it shall also apply to foodstuffs intended for supply to restaurants, hospitals, canteens and other similar mass caterers. This Directive shall not apply to natural mineral waters or other waters intended for human consumption and diet integrators/food supplements. Where nutrition labeling is provided, the information to be given shall consist of either group 1 or group 2 in the following order Group 1: (a) energy value, (b) the amounts of protein, carbohydrate and fat. Group 2: (a) energy value, (b) the amounts of protein, carbohydrate, sugars, fat, saturates, fibre and sodium. Directive 2000/13/EC (entry into force 26/5/2000) concerns the labeling of foodstuffs to be delivered as such to the ultimate consumer and certain aspects relating to the presentation and advertising thereof. The following particulars alone shall be compulsory on the labeling of foodstuffs: (1) the name under which the product is sold, (2) the list of ingredients, (3) the quantity of certain ingredients or categories of ingredients, (4) in the case of prepackaged foodstuffs, the net quantity, (5) the date of minimum durability or, in the case of foodstuffs which, from the microbiological point of view, are highly perishable, the ‘‘use by’’ date, (6) any special storage conditions or conditions of use, (7) the name or business name and address of the manufacturer or packager, or of a seller established within the Community, (8) particulars of the place of origin or provenance where failure to give such particulars might mislead the consumer to a material degree as to the true origin or provenance of the foodstuff, (9) instructions for use when it would be impossible to make appropriate use of the foodstuff in the absence of such instructions and (10) with respect to beverages containing more than 1.2% by volume of alcohol, the actual alcoholic
International Regulations on Food Contaminants and Residues
57
strength by volume. A summary of the Directives related to labeling is given in Table 8.
2.2.2 Labeling Regulation (EEC) No 1576/89 (entry into force 15/6/1989) lays down the general rules on the definition, description and presentation of spirit drinks. For the purposes of this Regulation spirit drink shall mean an alcoholic liquid intended for human consumption, having particular organoleptic qualities and a minimum alcoholic strength of 15 vol.% and produced either directly by the Table 8
Directives (main points and comments) related to labeling; general provisions
Title
Main points
Comments
Directive 90/496/EEC (entry into force 1/10/1990) Approximation of the laws of the Member States relating to food supplements
Nutrition labeling of
Amendment Directive EU 2003/ 120/EC (entry into force 26/10/1990) Addition of an article.
Directive 2000/13/EC (entry into force 26/ 5/2000) Approximation of the laws of the Member States relating to the labeling, presentation and advertising of foodstuffs
Application to pre-
foodstuffs for the ultimate consumer and for mass caterers. Not applicable to natural mineral waters or any other waters intended for human consumption or to diet integrators/food supplements. Nutrition labeling is not compulsory. The declared energy value and amount of nutrients shall be given in figures using specific units of measurement. packed foodstuffs with final receiver the consumer and mass caterers. No application to products which are exported from the Community. Obligatory recordation of specific elements.
Source: Adapted from [1] with permission from Blackwell Publishing.
Directive EU
79/112/EEC Amendments Directive EU 2001/
101/EC (entry into force 14/12/2001) Addition of an Annex. Directive EU 2003/ 89/EC (entry into force 24/11/2004) Replacement of an article.
58
Ioannis S. Arvanitoyannis
distillation, with or without added flavourings, of natural fermented products, and/or by the maceration of vegetable substances and/or the addition of flavourings, sugars or other sweetening products and/or other agricultural products to ethyl alcohol of agricultural origin and/or to distillate of agricultural origin and/or to spirit as defined in this Regulation or by the mixture of a spirit drink with one or more other spirit drinks, ethyl alcohol of agricultural origin, distillate of agricultural origin or spirit, one or more alcoholic drinks, one or more drinks. Categories of spirit drink and their alcoholic strength are (a) rum (37.5%), (b) whisky/whiskey (40%), (c) grain spirit (35%), (d) wine spirit (37.5%), (e) Brandy or Weinbrand (36%), (f) grape marc spirit or grape marc (37.5%), (g) fruit marc spirit (37.5%), (h) raisin spirit or raisin brandy (37.5%), (i) fruit spirits (37.5%), (j) cider spirit, cider brandy or perry spirit (37.5%), (k) gentian spirit (37.5%), (l) fruit spirit drinks (25%), (m) Juniper-flavoured spirit drinks (25%), (n) caraway-flavoured spirit drinks (30%), (o) aniseed-flavoured spirit drinks (25%), (p) bitter-tasting spirit drinks or bitter, (q) vodka, (r) liqueur, (s) egg liqueur/advocaat/avocat/Advokat and (t) liqueur with egg. Regulation (EEC) No 1601/91 (entry into force 17/6/1991) lays down the general rules on the definition, description and presentation of aromatized wines, aromatized wine-based drinks and aromatized wine-product cocktails. Aromatized wine shall mean a drink (i) obtained from wines with the exception of retsina table wine and possibly with added grape must, grape must in fermentation and/or fresh grape must with fermentation arrested by the addition of alcohol, as defined by Community legislation, (ii) which has been flavoured with the aid of natural flavouring substances and/or natural flavourings preparations or aromatic herbs and/or spices and/or flavouring foodstuffs, (iii) which has generally been sweetened and has possibly been coloured with caramel and (iv) which has a minimum actual alcoholic strength by 14.5 vol.% or more and a maximum actual alcoholic strength by less than 22 vol.% and a minimum total alcoholic strength by 17.5 vol.% or more, however, for those products which bear the description ‘‘dry’’ or ‘‘extra dry’’, the minimum total alcoholic strength shall be set at 16 vol.% and 15 vol.%, respectively. Regulation (EEC) No 2081/92 (entry into force 24/7/1993) lays down rules on the protection of designations of origin and geographical indications of agricultural products intended for human consumption. For the purposes of this Regulation (a) designation of origin means the name of a region, a specific place or, in exceptional cases, a country, used to describe an agricultural product or a foodstuff originating in that region, specific place or country and the quality or characteristics of which are essentially or exclusively due to a particular geographical environment with its inherent natural and human factors, and the production, processing and preparation of which take place in the defined geographical area, (b) geographical indication means the name of a region, a specific place or, in exceptional cases, a country, used to describe an agricultural product or a foodstuff originating in that region, specific place or country and which possesses a specific quality, reputation or other characteristics attributable to that geographical origin and the production and/or processing and/or preparation of which take place in the defined geographical area.
International Regulations on Food Contaminants and Residues
59
Furthermore, another Regulation (EEC) No 2200/96 (entry into force 1/1/ 1997) claims that it shall apply to fresh fruits, which are apple, apricot, avocado, grapes, lemon, kiwifruit, tangerine, cherry, melon, water melon, orange, pear, strawberry, nectarine, peach and plum, and vegetables, which are artichoke, bean, carrot, celery, garlic, onion, spinach, chicory, lettuce, pepper, cabbage, cauliflower, vegetable marrow, leek, pea, eggplant, cucumber, tomato and endive. The Regulation (EC) No 2815/98 (entry into force 31/10/2001) concerning marketing standards for olive oil claims that the designation of origin shall relate to a geographical area and may mention only (a) a geographical area whose name has been registered as a protected designation of origin or protected geographical indication and/or (b) for the purposes of this Regulation: a Member State, the European Community, a third country. The designation of origin, where this indicates the European Community or a Member State shall correspond to the geographical area in which the ‘‘extra virgin olive oil’’ or ‘‘virgin olive oil’’ was obtained. However, in the case of blends of ‘‘extra virgin olive oils’’ or ‘‘virgin olive oils’’ in which more than 75% originates in the same Member State or in the Community, the main origin may be designated provided that it is followed by the indication ‘‘selection of (extra) virgin olive oils more than 75% of which was obtained in y (designation of origin)’’. An extra virgin or virgin olive oil shall be deemed to have been obtained in a geographical area for the purposes of this paragraph only if that oil has been extracted from olives in a mill located within that area. Regulation (EC) No 1439/99 (entry into force 14/9/1999) should apply to wine that is sold in the Community. Categories of wine in which the Regulation is set are (a) table wine, (b) table wine with geographical indication, (c) wine produced in specific areas and (d) imported wine. According to Regulation (EC) No 1760/2000 (entry into force 14/8/2000) each Member State shall establish a system for the identification and registration of bovine animals. The system for the identification and registration of bovine animals shall comprise the following elements: (a) ear tags to identify animals individually, (b) computerised databases, (c) animal passports and (d) individual registers kept on each holding. With the exception of transporters, each keeper of animals shall keep an up-to-date register and once the computerized database is fully operational, report to the competent authority all movements to and from the holding and all births and deaths of animals on the holding, along with the dates of these events, within a period fixed by the Member State of between three and seven days of the event occurring. In Regulation (EC) No 1321/2002 (entry into force 1/8/2002), the said producers shall subsequently be inspected regularly. They shall keep current records, for a minimum of six months following dispatch, of the number of birds by type of poultry system showing also the number of birds sold and the names and addresses of the purchasers and quantities and source of feed supply. The definitions given are applicable to the poultry cuts. The sample sizes should be at least as follows: (i) chicken breast: half of the breast, (ii) chicken breast fillet: half of the boned breast without skin and (iii) turkey breast, turkey breast fillet and boned leg meat: portions of about 100 g.
60
Ioannis S. Arvanitoyannis
According to Regulation (EC) No 318/2003 (entry into force 25/2/2003) checks are to be carried out in the packing centres on graded eggs ready for dispatch and not to eggs leaving the packing centres. In order to ensure proper land management and to prevent a build-up of harmful diseases, the open-air runs for laying hens may need to be rotated. Birds should be given even access to the whole paddock area and, where rotation on extensive free range system with at least 10 m2 per hen is practised, each bird should be ensured at all times at least 2.5 m2. The titles, main points and comments of the EU Regulations about labeling are summarized in Table 9.
2.3 Water quality 2.3.1 Directives for water quality The Directive 75/440/EEC claims that surface water shall be assumed to conform to the relevant parameters if samples of this water taken at regular intervals at the same sampling point and used in the abstraction of drinking water, show that it complies with the parametric values for the water quality in question, in the case of 95% of the samples for parameters conforming to those specified and 90% of the samples in all other cases, and if in the case of the 5 or 10% of the samples which do not comply (a) the water does not deviate from the parametric values in question by more than 50%, except for temperature, pH, dissolved oxygen and microbiological parameters, (b) there can be no resultant danger to public health and (c) consecutive water samples taken at statistically suitable intervals do not deviate from the relevant parametric values. The definition of the standard methods of treatment for transforming surface water of categories A1, A2 and A3 into drinking water includes Category A1 (simple physical treatment and disinfection, e.g., rapid filtration and disinfection), Category A2 (normal physical treatment, chemical treatment and disinfection, e.g., pre-chlorination, coagulation, flocculation, decantation, filtration, disinfection) and Category A3 (intensive physical and chemical treatment, extended treatment and disinfection, e.g., chlorination to break-point, coagulation, flocculation, decantation, filtration, adsorption, disinfection). With regard to Directive 79/923/EEC Member States (a) shall within a two year period following the notification of this Directive, designate shellfish waters, (b) may subsequently make additional designations, (c) may revise the designation of certain waters owing in particular to factors unforeseen at the time of designation and (d) shall establish programs in order to reduce pollution and to ensure that designated waters conform to the values set by the Member States, within six years following designation. Where the competent authority records that the quality of designated waters is appreciably higher than that which would result from the application of the values set, the frequency of the sampling may be reduced. According to Directive 98/83/EC, Member States may exempt from the provisions of this Directive the water intended exclusively for those purposes for which the competent authorities are satisfied that the quality of the water has no influence, either directly or indirectly, on the health of the consumers
Table 9 Regulations (main points and comments) for labeling Title
Main points
Comments
Regulation (EEC) No 1576/89 (entry into force 15/6/1989) General rules on the definition, description and presentation of spirit drinks
The minimum alcoholic strength by volume below which a product may not be marketed in the territory of the EU is laid down. Addition of specific substances to the products.
Amendments Regulation (EEC) No 3280/92 (entry into force 16/11/1992) Addition to an article. Regulation (EEC) No 3378/94 (entry into force 1/1/1995) Addition of articles.
Regulation (EEC) No 1601/91 (entry into force 17/6/1991) Laying down general rules on the definition, description and presentation of aromatized wine, aromatized winebased drinks and aromatized wineproduct cocktails.
Three categories of drinks according to their wine content, their alcoholic strength, and whether they contain added alcohol.
Amendments Regulation (EEC) No 3279/92 (entry into force 16/11/1992) Regulation (EC) No 3378/94 (entry into force 1/1/1995) Regulation (EC) No 2061/96 (entry into force 3/11/1996) Addition and replacement of articles.
Regulation (EEC) No 2081/92 (entry into force 24/7/1993) Protection of geographical indications and designations of origin for agricultural products and foodstuffs
No application to wine products or to spirit drinks. Names that have become generic may not be registered. To be eligible to use a protection of designation of origin (PDO) or a protection of geographical indications (PGI) an agricultural product or foodstuff must comply with a specification.
Amendments Regulation (EC) No 535/97 (entry into force 15/4/1997) Regulation (EC) No 1068/97 (entry into force 28/6/1997) Regulation (EC) No 2796/2000 (entry into force 10/1/2001) Completion of articles.
Regulation (EEC) No 2200/96 (entry into force 1/1/1997) Labeling of fresh fruits and vegetables.
Marketing standard for fresh fruits and vegetable. Laying down a list of fresh fruits and vegetable.
62
Ioannis S. Arvanitoyannis
Table 9 (Continued ) Title
Main points
Regulation (EC) No 2815/98 (entry into force 31/10/2001) Marketing standards for olive oil.
The designation of origin shall relate to a geographical area. The ‘‘extra virgin olive oil’’ and ‘‘virgin olive oil’’ which shall be packaged in an establishment approved for that purpose. Labeling is compulsory and it contains information about the origin of wine. Categories of wine and rules for the marketing standards.
Regulation (EC) No 1439/99 (entry into force 14/9/1999) Marketing standards for wine
Comments
Regulation (EC) No 1760/2000 (entry into force 14/8/2000) Establishment of a system for the identification and registration of bovine animals and regarding the labeling of beef and beef products
Every Member State must set up a cattle identification and registration system. Compulsory labeling of beef and beef products.
Repeal Regulation (EC) No 820/97 Amendment Regulation (EC) No 1825/2000 Addition for traceability, labeling and controls of bovine animals and their products (entry into force 1/9/2000)
Regulation (EC) No 1321/2002 (entry into force 1/8/2002) Marketing standards for poultry meat
Mark of designation of origin for fresh and frozen poultry meat only in the case of imports from countries out of the Community. Inspections for designation of origin in the packaging plants.
Repeal Regulation (EC) No 1906/90
Regulation (EC) No 318/2003 (entry into force 25/2/2003) Certain marketing standards for eggs.
Obligatory sign of designation of origin on eggs packaging originated from a third country. Inspections in the plants of packaging.
Source: Adapted from [1] with permission from Blackwell Publishing.
International Regulations on Food Contaminants and Residues
63
concerned and water intended for human consumption from an individual supply providing less than 10 m3 a day as an average or serving fewer than 50 persons, unless the water is supplied as part of a commercial or public activity. All the Directives related to water quality are given in Table 10.
3. TOPICS/CATEGORIES COVERED UNDER USA LEGISLATION 3.1 Food safety Regulating food safety in the United States is complex. This complexity is due largely to the historical division of food safety responsibility amongst different federal agencies and to evolving public attitudes towards the safety of food and concern about the changing nature of food-borne illnesses (http://www.national aglawcenter.org/readindrooms/foodsafety). A food business is defined as being any undertaking regarding food, whether carried out for profit or not, carrying out one or more of the following operations: preparation, processing, manufacturing, packaging, storage, transportation/distribution, handling, offering for sale or supplying a consumer (http://www.eastherts.gov.uk/Buisiness%20Guide% 20to% 20Law%20and%20Practise/Legislation.htm). The Food Safety Act 1990 and regulations specify certain safety standards for the processing and sale of food. It is an offence for anyone to process or sell food, which is harmful to health. The regulations also place an obligation on businesses to ensure that their activities are carried out in a hygienic way. Running a food business means that you have a particular responsibility to protect the health of your customers (http://www.torridge.gov.uk/index.cfm?articleid ¼ 3967).
3.1.1 Food safety legislation In Consumer Product Safety Act (1972) the term ‘‘consumer product’’ means any article or component part thereof, produced or distributed (i) for sale to a consumer for use in or around a permanent or temporary household or residence, a school, in recreation, or otherwise, or (ii) for the personal use, consumption or enjoyment of a consumer in or around a permanent or temporary household or residence, a school, in recreation, or otherwise; but such term does not include (a) any article which is not customarily produced or distributed for sale to, or use or consumption by, or enjoyment of, a consumer, (b) tobacco and tobacco products, (c) motor vehicles or motor vehicle equipment and (d) pesticides. Following Food Quality Protection Act (1996) key issues revolved around: the roles of state, local and tribal governments in pesticide regulation and federal law enforcement; the cost of scientific tests required by the U.S. Environmental Protection Agency (EPA) to support pesticide registration and re-registration, and delays in processing applications for new or amended registrations, especially for minor uses; and long delays in re-registration of older pesticides and the need for fees to support the effort. A lesser issue involved state authority to require training of persons who regularly apply non-restricted pesticides in
64
Ioannis S. Arvanitoyannis
Table 10
Directives (main points and comments) focused on water quality
Title
Main points
Comments
Directive 75/440/ EEC (entry into force16/6/1977) The quality required of surface water intended for the abstraction of drinking water
Demands required for the quality of surface water intended for the abstraction of drinking water. Not applicable to subterranean and subsaline water. Variations in the case of floods or other natural disasters are accepted.
Amendments Directive EU 79/869/EEC Methods of measurement, sampling frequency and parameter analysis. Amendment, repeal and replacement of articles (entry into force 9/10/ 1981) Directive EU 91/692/EEC Standardization of reports concerning the application of specific directives for the environment Articles replacement (entry into force 1/1/ 1993)
Directive 79/923/ EEC (entry into force 5/11/1981) Quality required of shellfish waters
Applicable to coastal and brackish waters in order to support shellfish life. Criteria for minimum demanded quality of shellfish waters. Two year period for Member States to designate shellfish waters. Decline in case of exceptional weather or geographical conditions.
Amendment Directive EU 91/692/EEC Standardization of reports concerning the application of specific directives for the environment (entry into force 1/1/1993)
Directive 98/83/EC (entry into force 25/12/1998) Quality of water intended for human consumption
Application for human health protection from potential contamination. Not applicable to natural, mineral waters and waters that are medicinal products. Demands for limited material migration in plants of drinking water.
Source: Adapted from [1] with permission from Blackwell Publishing.
Repeal of Directive EU 80/778/EEC
International Regulations on Food Contaminants and Residues
65
urban and suburban areas. Canceling a pesticide registration, when it is found to cause ‘‘unreasonable adverse effects’’, can be a prolonged process, lasting 4–8 years or more. Another Public Health Security and Bioterrorism Preparedness and Response Act (2002) claims that the Secretary of Agriculture shall by regulation establish and maintain a list of each biological agent and each toxin that the Secretary determines has the potential to pose a severe threat to animal or plant health, or to animal or plant products. In determining whether to include an agent or toxin on the list under this subparagraph, the Secretary shall (1) consider (i) the effect of exposure to the agent or toxin on animal or plant health, and on the production and marketability of animal or plant products, (ii) the pathogenicity of the agent or the toxicity of the toxin and the methods by which the agent or toxin is transferred to animals or plants, (iii) the availability and effectiveness of pharmacotherapies and prophylaxis to treat and prevent any illness caused by the agent or toxin and (iv) any other criteria that the Secretary considers appropriate to protect animal or plant health or animal or plant products and (2) consult with appropriate Federal departments and agencies and with scientific experts representing appropriate professional groups. In Food Safety Act (2002) ‘‘food’’ means food or drink for human consumption, and includes (a) any substance or thing that is manufactured, sold or represented for use as food or drink for human consumption, (b) any substance or thing that is manufactured, sold or represented for use as an additive, ingredient or processing aid in a substance or thing referred to in (a) and (c) any agricultural or aquatic product that is grown, raised, cultivated, harvested or kept for the purpose of producing food or drink for human consumption. An operator is responsible for ensuring that the food in his or her food establishment is safe for human consumption. An inspector who believes on reasonable grounds that food (a) does not meet a prescribed standard for that food or (b) is contaminated or otherwise unfit for human consumption, may (c) seize the food or have it seized and (d) detain it, or have it detained, for examination or inspection that the inspector considers necessary to determine whether that standard has been met or whether the food is contaminated or unfit for human consumption. Some points of the US legislation focused on biological safety are stated in Table 11.
3.2 Technological aspects Factory-made foods have made chemical additives a significant part of our diet. Most people may not be able to pronounce the names of many of these chemicals, but they still want to know what the chemicals do and which ones are safe and which are poorly tested or possibly dangerous. The listing in http://www. cspinet.org/reports/chemcuisine.htm provides the information about most common additives. Over the years, however, improvements have been made in increasing the efficiency and ensuring the safety of all additives. Today food and colour additives are more strictly regulated that at any other time in history. The basis of modern food law is the Federal Food, Drug and Cosmetic Act of 1938,
66
Table 11
Ioannis S. Arvanitoyannis
US legislation (title, main points) focused on food safety
Title
Main points
Consumer Product Safety Act (1972)
Definitions (consumer product, manufacturer etc.) Consumer product safety standards Commission responsibility — petition for consumer product safety rule Product certification and labeling Financial penalties
Food Quality Protection Act (1996)
Food Safety Act (2002)
Definitions (food, food establishment etc.) Licenses for designated food establishments Seizure and destruction of food
Comments Amendments 1976 (Consumer Product Safety Commission Improvement Act) 1978 (Consumer Product Safety Authorization Act) 1981 (Consumer Product Safety Amendments) 1983 (Lead Contamination Control Act) 1988 (Anti-drug Abuse Act) 1990 (Consumer Product Safety Improvement Act) 1994 (Child Safety Protection Act)
It related to pesticide uses The new law will facilitate registrations and reregistrations of pesticides for special (so-called ‘‘minor’’) uses and authorize collection of maintenance fees of support pesticide reregistration.
Regulation of certain Public Health biological agents and toxins Security and Food safety and security Bioterrorism Preparedness and strategy Notices to States regarding Response Act (2002) imported food Source: Adapted from [2] with permission from Blackwell Publishing.
which gives the Food and Drug Administration (FDA) authority over food and food ingredients and defines requirements for truthful labeling of ingredients (http://www.cfsan.fda.gov/Blrd/foodaddi.html). Another technological aspect is food irradiation. Food irradiation is one means of food preservation that may
International Regulations on Food Contaminants and Residues
67
not be familiar to many, but it has been in development since the early decades of the twentieth century. If properly applied, irradiation can be an effective way to treat a variety of problems in our food supply, such as insect infestation of grains, sprouting of potatoes, rapid ripening of fruits and bacterial growth (http://www. fcs.uga.edu/pubs/current/FDNS-E-3.html).
3.2.1 Technological aspects legislation Following Toxic Substances Control Act (TSCA, 1976) the term ‘‘chemical substance’’ means any organic or inorganic substance of a particular molecular identity, including (i) any combination of such substances occurring in whole or in part as a result of a chemical reaction or occurring in nature and (ii) any element or uncombined radical. Such term does not include (a) any mixture, (b) any pesticide when manufactured, processed, or distributed in commerce for use as a pesticide, (c) tobacco or any tobacco product, (d) any source material, special nuclear material, or by-product material, (e) any food, food additive, drug, cosmetic, or device when manufactured, processed, or distributed in commerce for use as a food, food additive, drug, cosmetic, or device. In US Regulatory Requirements for Irradiating Foods (1986), Congress explicitly defined a source of radiation as a food additive. In a report accompanying the legislation, Congress explicitly stated ‘‘Sources of radiation (including radioactive isotopes, particle accelerators, and X-ray machines) intended for use in processing food are included in the term ‘food additive’ as defined in this legislation’’. In early work on food irradiation, sources of sufficiently high energies to induce radioactivity in foods were sometimes used. As research continued, sources whose energies are too low to induce detectable radioactivity were adopted by the international community. Therefore, this issue is of no concern when currently approved sources of radiation are used, but must be addressed if other sources are being considered. Toxicological safety of typical food additives has traditionally been assessed by feeding large amounts of purified substances to laboratory animals and applying a safety factor to the highest dose of a tested substance that causes no toxic effects in any species. Food irradiation (1999) is a technology for controlling spoilage and eliminating food-borne pathogens, such as Salmonella. The result is similar to conventional pasteurization and is often called ‘‘cold pasteurization’’ or ‘‘irradiation pasteurization’’. Like pasteurization, irradiation kills bacteria and other pathogens that could otherwise result in spoilage or food poisoning. The fundamental difference between the two methods is the source of the energy they rely on to destroy the microbes. While conventional pasteurization relies on heat, irradiation relies on the energy of ionizing radiation. The FDA emphasizes that no preservation method is a substitute for safe food handling procedures. The food irradiation process uses three types of ionizing radiation sources (i) cobalt60 gamma sources, (ii) electron beam generators and (iii) X-ray generators. Food Additives Guide (2005) makes clear that food additives are an important component of our food supply. They mean that we can enjoy a wide variety of foods throughout the year. They also have an important role in ensuring that our food lasts longer and is easier to use. There are good reasons for the use of food
68
Ioannis S. Arvanitoyannis
additives. They can be used to improve the quality or stability of a food. For example (a) sorbitol — humectant (420) — may be added to mix dried fruit to maintain the moisture level and softness of the fruit preserve food when this is the most practical way of extending its storage life, (b) sulphur dioxide — preservative (220) — is added to some meat products such as sausage meat to prevent the bugs that cause food poisoning from growing and improve the taste or appearance of a processed food and (c) lecithin — emulsifier (322) — may be added to margarine to help maintain texture. Additives are used in processed foods in relatively small quantities. Many substances used as additives also occur naturally, such as vitamin C or ascorbic acid (300) in fruit and lecithin (322) in eggs or soy beans. Federal Food, Drug and Cosmetic Act (2005) states that the Director of the Center shall (a) conduct postmarket risk assessment of drugs approved under this Act and of biological products licensed under the Public Health Service Act, (b) conduct and improve postmarket surveillance of approved drugs and licensed biological products using postmarket surveillance programs and activities riskbenefit analyses, adverse event reports, the scientific literature, any clinical or observational studies and any other resources that the Director of the Center determines appropriate, (c) determine whether a study is required under this subsection and consult with the sponsors of drugs and biological products to ensure that such studies are completed by the date, and according to the terms, specified by the Director of the Center, (d) contract, or require the sponsor of an application or the holder of an approved application or license to contract, with the holders of domestic and international surveillance databases to conduct epidemiologic and other observational studies, (e) determine, based on postmarket surveillance programs and activities, risk-benefit analyses, adverse event reports, the scientific literature, and any clinical or observational studies and any other resources that the Director of the Center determines appropriate, whether a drug or biological product may present an unreasonable risk to the health of patients or the general public, and take corrective action if such an unreasonable risk may exist, (f) make information about the safety and effectiveness of approved drugs and licensed biological products available to the public and healthcare providers in a timely manner and (g) conduct other activities as the Director of the Center determines appropriate to ensure the safety and effectiveness of all drugs approved under this section and all biological products licensed under the Public Health Service Act. Some representative points and comments of the U.S. legislation about technological aspects are given in Table 12.
3.3 Food quality The goal of the labeling requirement is to increase consumption of domestic commodities and improve the market for U.S. producers. United States Department of Agriculture (USDA) officials appear to have consulted only with opponents of mandatory country of origin labeling before developing cost burden estimates associated with the implementation of the labeling requirements contained in the farm bill (http://enzi.senate.gov/usdaco.htm). The new
Amendments 1997 (Federal Register, 62) 1999 (Federal Register, 64)
Legal requirements Safety issues (radiological, toxicological,
microbiological, nutritional adequacy)
studies
Publication of progress reports and completed
and research
Duties of the center for postmarket drug evaluation
Intolerance and food additives
functional or class names
Use of food additives Food additives are listed according to their
spoilage and eliminating food-borne pathogens, such as salmonella. FDA approved irradiation for the control of pathogenic microorganisms in red meats.
Food irradiation is a technology for controlling
to ionizing radiation.
Food irradiation is the process of exposing food
Labeling and packaging of irradiating foods
Source: Adapted from [2] with permission from Blackwell Publishing.
Federal Food, Drug and Cosmetic Act (2005)
Food Additives Guide (2005)
Food Irradiation (1999)
US Regulatory Requirements for Irradiating Foods (1986)
their intentions to mass-produce a new chemical substance. TSCA also regulates polychlorinated biphenyls, or PCBs.
Amendment In 1986, TSCA was amended to incorporate the Asbestos Hazard Emergency Response Act to address matters relating to asbestos products in public schools and other buildings.
It establishes the EPA’s toxic substances program. Under TSCA, manufacturers must notify EPA of
Toxic Substances Control Act (TSCA) (1976)
Comments
Main points
US legislation (main points, comments) with regard to technological aspects
Title
Table 12
International Regulations on Food Contaminants and Residues
69
70
Ioannis S. Arvanitoyannis
US rules require that the FDA conducts inspections to ensure that food manufacturers are complying with practices to reduce or eliminate cross-contact of a food with any major food allergens that are not intentional ingredients of the food (http://www.foodnavigator-usa.com/news/ng.asp?n ¼ 58569-food-labeling-must). Most mandatory labeling legislation around the world has either not yet been fully implemented, or has been implemented in combination with informal moratoria on genetically engineered (GE) foods — the result being that few, if any, GE foods actually carry a label yet. GE food labels are only mandated if the food has any known nutritional difference or food safety risk (including increased toxicity or likelihood of causing allergies; http://www. geo-pie.cornell.edu/issues/intllabeling.html).
3.3.1 Labeling and packaging legislation Fair Packaging and Labeling Act (1967) specifies that packages and their labels should enable consumers to obtain accurate information as to the quantity of the contents and should facilitate value comparisons. Therefore, it is hereby declared to be the policy of the Congress to assist consumers and manufacturers in reaching these goals in the marketing of consumer goods. The separate label statement of net quantity of contents appearing upon or affixed to any package (i) if on a package labeled in terms of weight, shall be expressed in pounds, with any remainder in terms of ounces or common or decimal fractions of the pound; or in the case of liquid measure, in the largest whole unit (quarts, quarts and pints, or pints, as appropriate) with any remainder in terms of fluid ounces or common or decimal fractions of the pint or quart, (ii) if on a random package, may be expressed in terms of pounds and decimal fractions of the pound carried out to not more than three decimal places and is not required to, but may, include a statement in terms of the SI metric system carried out to not more than three decimal places, (iii) if on a package labeled in terms of linear measure, shall be expressed in terms of the largest whole unit (yards, yards and feet, or feet, as appropriate) with any remainder in terms of inches or common or decimal fractions of the foot or yard and (iv) if on a package labeled in terms of measure of area, shall be expressed in terms of the largest whole square unit (square yards, square yards and square feet, or square feet, as appropriate) with any remainder in terms of square inches or common or decimal fractions of the square foot or square yard. The term ‘‘label’’ means any written, printed, or graphic matter affixed to any consumer commodity or affixed to or appearing upon a package containing any consumer commodity. Biotech Food Labeling illustrates three observations made in the theory section of this report. First, to establish successful mandatory labeling requirements, the government must provide or arrange for standards, testing, certification and enforcement. Second, labeling of complex, unclear information will not reduce information and search costs. Third, labeling is not the best policy tool for redressing externalities (even theoretical externalities). Labeling requirements are established by USDA for meat and poultry and by FDA for all other food products. Both agencies require labeling of a biotech food if the food’s composition differs significantly from that of its conventional counterpart. Most
International Regulations on Food Contaminants and Residues
71
biotech foods on the market have been found to be essentially equivalent to their conventional counterparts, hence, most biotech foods are unlabeled. As an alternative to segregation, processors could choose to reformulate their products to use ingredients from crops that are exclusively non-biotech, thus minimizing the risk of inadvertently using a biotech variety. For example, corn emulsifiers could be replaced with rice emulsifiers. The cost of any of these options varies greatly depending on the flexibility of the production and marketing systems, the tolerance level for biotech content, the volume of biotech and non-biotech commodities and products processed by the system, and the likelihood of achieving economies of scale. Following Biotech Labeling Guidance (2001) in comments submitted to the FDA, the National Food Processors Association has commended FDA for its draft guidance on voluntary labeling for foods that have or have not been derived through biotechnology. Consumers will benefit only if voluntary biotechnology labeling conforms to standards assuring the information is truthful and not misleading. In this regard, the FDA has provided appropriate and much needed guidance to the food industry through its authority under the misbranding provisions of the Federal Food, Drug and Cosmetics Act. According to Food Labeling (2004) GE food is becoming the rule, rather than the exception, on American grocery-store shelves. By some estimates, two-thirds or more of processed foods now contain ingredients derived from GE corn and soy crops. Unlike the old botanical roulette involved in combining plants to see what traits emerge in their hybrids, genetic engineering is precise. Single traits of one species are spliced into another. The titles and main points of the US legislation about labeling and packaging are summarized in Table 13.
3.4 Water protection and management The Water Act regulates the legal status of water and water estate, the methods and conditions of water management (water use, water protection, regulation of watercourses and other water bodies and protection from adverse effects of water), the method of organizing and performing water management tasks and functions, basic conditions for carrying out of water management activities; powers and duties of Government administration and other Government bodies, local authorities and other legal subjects and other issues of importance to water management (http://en.gmo.hr/index.php/zakonska_regulativa/ hrvatski_zakoni). The Clean Water Act (CWA, 1972) formerly known as the Federal Water Pollution Control Act, intended to restore and maintain the chemical, physical and biological integrity of the Nation’s waters. To accomplish that objective, the act aimed to attain a level of water quality that ‘‘provides for the protection and propagation of fish, shellfish, and wildlife, and provides for recreation in and on the water’’ by 1983 and to eliminate the discharge of pollutants into navigable waters by 1985. The CWA has five main elements (1) a system of minimum national effluent standards for each industry, (2) water quality standards, (3) a discharge permit program that translates these standards into enforceable limits,
72
Ioannis S. Arvanitoyannis
Table 13
US legislation (title, main points, comments) dealing with labeling and packaging
Title
Main points
Comments
Fair Packaging and Labeling Act (1967)
Unfair and deceptive packaging
Amendments 1992 (The quantity disclosure on labels of consumer commodities be expressed in both the metric system and the customary inch/pound system of measurement)
Biotech Food Labeling (1999)
The biotech labeling example
and labeling: scope of prohibition Requirements of labeling, placement, form and contents of Statement of Quantity, Supplemental Statement of Quantity Annual reports to Congress
illustrates three observations Labeling requirements are
established by USDA for meat and poultry and by FDA for all other food products. Biotech Labeling Guidance (2001)
Labeling of biotechnology food
Labeling Food (2004)
Genetically engineered food is
products Words using in labeling
becoming the rule The new label, reflecting the
definition that organic farmers themselves pushed for will certify that organic food, in addition to being grown without pesticides, contains no genetically engineered ingredients. Source: Adapted from [2].
(4) provisions for special problems such as toxic chemicals and oil spills and (5) a revolving construction loan program (formerly a grant program) for publicly owned treatment works (POTWs). According to Safe Drinking Water Act (SDWA, 1974) the term ‘‘primary drinking water regulation’’ means a regulation which (a) applies to public water systems, (b) specifies contaminants which, in the judgment of the Administrator, may have any adverse effect on the health of persons, (c) specifies for each such contaminant either a maximum contaminant level, if, in the judgment of the Administrator, it is economically and technologically feasible to ascertain the level of such contaminant in water in public water systems or if, in the judgment
International Regulations on Food Contaminants and Residues
Table 14
73
US Acts (main points and comments) related to water protection and management
Title
Main points
Comments
Clean Water Act (CWA) (1972)
The CWA was established to restore and maintain the chemical, physical and biological integrity of the nation’s waters. The CWA sets goals to eliminate discharges of pollutants into navigable water, protect fish and wildlife, and prohibit the discharge of toxic pollutants in quantities that could adversely affect the environment.
Amendment The CWA was reauthorized in 1987.
Safe Drinking Water Act (SDWA) (1974)
It seeks to protect sources of the nation’s drinking water and to protect public health to the maximum extent possible, using proper water treatment techniques. SDWA establishes national primary drinking water standards based upon maximum contaminant levels, and establishes state management programs to enforce the standards.
Amendment 1996 (Amendments to the SDWA)
Source: Adapted from [2].
of the Administrator, it is not economically or technologically feasible to so ascertain the level of such contaminant, each treatment technique known to the Administrator which leads to a reduction in the level of such contaminant sufficient to satisfy the requirements of this section and (d) contains criteria and procedures to assure a supply of drinking water which dependably complies with such maximum contaminant levels, including accepted methods for quality control and testing procedures to insure compliance with such levels and to insure proper operation and maintenance of the system, and requirements as to the minimum quality of water which may be taken into the system and siting for new facilities for public water systems. The main points and comments of CWA and SDWA are given in Table 14.
REFERENCES Scientific sources 1 I.S. Arvanitoyannis, S. Choreftaki and P. Tserkezou, Int. J. Food Sci. Technol., 40 (2005) 1021. 2 I.S. Arvanitoyannis, P. Tserkezou and T. Varzakas, Int. J. Food Sci. Technol., 41 (2006) 130.
74
Ioannis S. Arvanitoyannis
EU LEGISLATION Regulation (EC) No 178/2002 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 2002&nu_doc ¼ 178). Regulation (EC) No.852/2004 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 2004&nu_doc ¼ 852). Regulation (EC) No 853/2004 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 2004&nu_doc ¼ 853). Regulation (EC) No 854/2004 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 2004&nu_doc ¼ 854). Regulation (EC) No 882/2004 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 2004&nu_doc ¼ 882). EU 76/895/EEC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 78&nu_doc ¼ 895). EU 86/362/EEC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 86&nu_doc ¼ 362). EU 90/642/EEC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 90&nu_doc ¼ 642). Regulation (EC) No 3954/87 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 87&nu_doc ¼ 3954). Regulation (EC) No 2219/89 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 89&nu_doc ¼ 2219). Regulation (EC) No 737/90 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 90&nu_doc ¼ 737). EU 96/22/EC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 96&nu_doc ¼ 22). EU 96/23/EC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 96&nu_doc ¼ 23). Regulation (EC) No 466/2001 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 2001&nu_doc ¼ 466). Regulation (EC) No 999/2001 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 2001&nu_doc ¼ 999). Regulation (EC) No 2160/2003 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 2003&nu_doc ¼ 2160). EU 75/106/EEC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 75&nu_doc ¼ 106). EU 76/211/EEC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 76&nu_doc ¼ 211). EU 78/142/EEC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 78&nu_doc ¼ 142). EU 80/232/EEC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 80&nu_doc ¼ 232). EU 82/711/EEC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 82&nu_doc ¼ 711). EU 93/10/EEC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 93&nu_doc ¼ 10). EU 94/62/EC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 94&nu_doc ¼ 62). EU 97/23/EC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 97&nu_doc ¼ 23). EU 2002/16/EC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 2002&nu_doc ¼ 16). Proposal of Regulation COM(2003)0689 COD(2003)0272 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod!DocNumber&1g ¼ en&type_doc ¼ RegulationCOM&an_ doc ¼ 2003&nu_doc ¼ 0689).
International Regulations on Food Contaminants and Residues
75
EU 90/496/EEC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 90&nu_doc ¼ 496). EU 2000/13/EC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 2000&nu_doc ¼ 13). Regulation (EEC) No 1576/89 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 89&nu_doc ¼ 1576). Regulation (EEC) No 1601/91 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 91&nu_doc ¼ 1601). Regulation (EEC) No 2081/92 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 92&nu_doc ¼ 2081). Regulation (EEC) No 2200/96 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 96&nu_doc ¼ 2200). Regulation (EC) No 2815/98 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 98&nu_doc ¼ 2815). Regulation (EC) No 1439/99 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 99&nu_doc ¼ 1439). Regulation (EC) No 1760/2000 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 2000&nu_doc ¼ 1760). Regulation (EC) No 1321/2002 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 2002&nu_doc ¼ 1321). Regulation (EC) No 318/2003 (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus! prod!DocNumber&1g ¼ en&type_doc ¼ Regulation&an_doc ¼ 2003&nu_doc ¼ 318). EU 75/440/EEC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 75&nu_doc ¼ 440). EU 79/923/EEC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 79&nu_doc ¼ 923). EU 98/83/EC (http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexplus!prod! DocNumber&1g ¼ en&type_doc ¼ Directive&an_doc ¼ 98&nu_doc ¼ 83).
e-addresses http://www.ohioline.osu.edu/hyg_fact/5000/5058.html http://www.ncseonline.org/NLE/CRSreports/Pesticides/pest-8.cfm http://frwebgate.access.gpo.gov/cgi-bin/getdoc.cgi?dbname ¼ 109_cong_bills&docid ¼ f:s930:s.txt.pdf http://www.ars.usda.gov/is/timeline/leg.htm?pf ¼ 1S http://www.sice.oas.org/int_prop/nat_leg/Usa/plrt37V.asp http://www.foodstandards.gov.au/mediareleasespublications/factsheets/factsheets1999/ foodadditives.cfm http://www.whitehouse.gov/omb/legislative/sap/107-1/S1731-s.html http://vm.cfsan.fda.gov/Bdms/prodguid.html http://www.epa.gov/radiation/sources/food_irrad.htm http://www.epa.gov/r5water/cwa.htm http://www.epa.gov/history/topics/fqpa/02.htm http://www.wetlands.com/regs/tlpge02a.htm http://www.thecampaign.org/alert-house.php http://www.food-irradiation.com/Pauli1.htm http://pirg.org/ge/GE.asp?id2 ¼ 4778&id3 ¼ ge& http://www.eastherts.gov.uk/Buisiness%20Guide%20to%20Law%20and%20Practise/ Legislation.htm http://www.nationalaglawcenter.org/readindrooms/foodsafety/ http://www.torridge.gov.uk/index.cfm?articleid ¼ 3967 http://www.cspinet.org/reports/chemcuisine.htm
76
Ioannis S. Arvanitoyannis
http://www.cfsan.fda.gov/Blrd/foodaddi.html http://www.fcs.uga.edu/pubs/current/FDNS-E-3.html http://www.mindfully.org/GE/GE4/GE-Legislation-Rep-Kucinich11jun02.htm http://enzi.senate.gov/usdaco.htm http://www.foodnavigator-usa.com/news/ng.asp?n ¼ 58569-food-labeling-must http://www.geo-pie.cornell.edu/issues/intllabeling.html http://www.onderzoekinformatie.nl/en/oi/nod/onderzoek/OND1305164/ http://www.usda.gov/news/pubs/97arp/arp4.htm http://www.i-sis.org.uk/subst.php http://www.mja.com.au/public/issues/172_04_210200/huppleed/leeder.html http://www.the-scientist.com/news/20020206/04 http://www.twnside.org.sg/title2/service169.htm http://www.elsevier.com/wps/find/journaldescription.cws_home/405859/ description#description http://www.food.gov.uk/multimedia/pdfs/foodassureguidance.pdf http://www.fao.org/trade/docs/LDC_foodqual_en.htm http://www.blackwellpublishing.com/journal.asp?ref1471-5732 http://www.mannlib.cornell.edu/collections/policies/food.html http://www.fst.vt.edu/undergraduate.courses.html http://www.washingtonwatchdog.org/documents/usc/index.html http://europa.eu.int/comm/food/intro_en.htm
CHAPT ER
3 Guidelines on Quality Implementation for Analytical Methods Sergio Caroli
Contents
1. Introduction 2. The Role of Quality 2.1 General aspects 2.2 Key aspects of a quality system based on the accreditation criteria 2.3 Key aspects of a quality system based on the Principles of Good Laboratory Practice 3. Conclusions References
77 78 78 79 84 86 87
1. INTRODUCTION The concept that no laboratory can survive in the long term without having a fitfor-purpose quality system in place is nowadays widely accepted by the international scientific community. Experimental information must be, in fact, supported by documented evidence to be valid, credible and comparable. To date, quality systems can be traced back basically to two distinct, yet complementary, approaches, i.e., those adopting the criteria for accreditation, mostly those worked out by the International Standardisation Organisation (ISO), and those based on compliance with the Principles of Good Laboratory Practice (GLP), in particular as developed by the Organisation for Economic Co-operation and Development (OECD) [1–3]. The rationale behind the latter has roots in the need for assessing the integrity of experimental studies, while the former aims at evaluating the competence of a laboratory to perform measurements. In other words, in a GLP system the validity of a completed study is challenged. In so doing, necessarily all the phases of the study are reconstructed and the laboratory performance and Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00003-2
r 2008 Elsevier B.V. All rights reserved.
77
78
Sergio Caroli
facilities are checked. On the other hand, in the case of a quality system based on accreditation, the target is to gain confidence in the ability of the laboratory to generate defendable experimental data. In more detail, a GLP system aims at providing the decision maker with reliable experimental information on new chemical substances so as to allow for a sound assessment of the benefit-to-risk ratio well before chemicals are produced and marketed. The cornerstone of this policy is the implementation of the OECD GLP Principles whenever non-clinical safety studies on new chemicals are undertaken by test facilities. Such Principles can be found in the Decision of the Council concerning the Mutual Acceptance of Data (MAD) in the Assessment of Chemicals [C(81)30(Final)], the Council Decision-Recommendation on Compliance with Principles of GLP [C(89)87(Final)] and the Council. Decision concerning the Adherence of Non-member Countries to the Council Acts related to the MAD in the Assessment of Chemicals [C(97)114(Final)]. Needless to say, the GLP quality system is compulsory resorted to whenever there is, e.g., a registration obligation for the commercialization of a new substance. In turn, an accreditation-oriented quality system is governed by the ISO/IEC Standard 17025 and has to cover the administrative and technical issues specified in the Standard, including internal audits, job descriptions and responsibilities, procedures for equipment/instrument maintenance and calibration, document control, handling of reagents, chemicals and reference materials, sample delivery and storage, validation of test methods, traceability and uncertainty of the test results, training of personnel, client complaints and corrective and preventive actions. Several of these issues are also required for compliance with the OECD GLP Principles either with a different emphasis or with additional requirements. Although the two systems have been designed to meet largely different needs, it is hoped that they can more and more support each other to minimize redundancy and to provide the end user with experimental information as trustworthy as possible.
2. THE ROLE OF QUALITY 2.1 General aspects The food safety policy fits in a wide context that originates at world level and at EU level. At world level the standards for food safety are established in the Codex Alimentarius. The standards for fighting animal diseases are established in the world organization for animal health (OIE). In the white paper on food safety the EU Commission (DG SANCO) outlined a completely new framework for the organization and supervision of food safety. With this new legislation the Commission wants to promote the health of European consumers by establishing food safety provisions that are among the best and most stringent in the world. The white paper comprises an action plan of 84 points. Its objectives can be summarized as follows: (1) (2)
The setting up of a European Food Safety Authority (EFSA). The realization of a coherent European food safety legislation.
Guidelines on Quality Implementation for Analytical Methods
(3) (4) (5) (6)
79
An improved and more coherent organization of the control on the food chain. Permanent dialogue with, and information for the consumer. An international dimension: insist on an implementation of the European food policy at world level. The Food and Veterinary Office (FVO) is responsible at the EU Commission level for supervising the proper application of the EU standards and regulations.
Important decisions are often taken on the basis of experimental data. Hence, it is crucial that such data be comparable, reliable and valid. No laboratory can in fact be run without a fit-for-purpose quality system in place. Quality has been defined by ISO as ‘‘The totality of features and characteristics of a product or service that bear on its ability to satisfy stated or implied needs’’. To date, quality systems are basically inspired either by the GLP Principles or by the accreditation criteria. Laboratory work may be of two different types: (i) the outcome of the investigation are exact figures, to which precision and reproducibility are expected to be attached and (ii) the outcome of the investigation is, in a general sense, complex information which should be credible, reliable and comparable. In the former case, what matters more are the experimental measurements. In this context quality is assessed in terms of precision and reproducibility of the numerical data obtained. The ability of the laboratory to generate such data is thus of primary importance. Quality systems based on accreditation criteria are ideal in this respect. In the latter case, the focus is on the overall study as such. Third parties should be enabled to reconstruct the whole course of the study and to check its integrity so that confidence can be gained in the way the study results have been obtained. Under such circumstances, quality systems based on the GLP Principles apply. Which approach is to be preferred depends only on the scope and goals of the activities performed in the laboratory, although it should not be overlooked that accreditation is basically voluntary, whereas the GLP system is prescribed by law for those Test Facilities (TFs) undertaking non-clinical safety studies. There is still some confusion surrounding the terms of accreditation and certification. As this may well be misleading, consensus has been reached on the following definitions: accreditation is a means used to identify competent testing laboratories, whereas certification is the official approval granted by a given authority.
2.2 Key aspects of a quality system based on the accreditation criteria IUPAC has a long tradition of activities related to quality assurance of analytical measurement results. The formation of the IUPAC/ISO/AOAC Working Party for Harmonization of Quality Assurance (WPHQA) Schemes in 1978 was an important milestone. At that time, efforts were focused on harmonizing requirements related to method validation studies (or laboratory collaborative studies), which had been conducted by a number of organizations around
80
Sergio Caroli
the world. Today, after almost 30 years, that working party is the IUPAC Interdivisional WPHQA, which is part of the Analytical Chemistry Division (ACD). As set forth by the IUPAC, ‘‘The international scientific community recognizes that a laboratory must take appropriate measures to ensure that it is capable of providing data of the required quality. Such measures include: (i) internal quality control procedures; (ii) participation in proficiency testing schemes; (iii) validated methods of analysis; (iv) accreditation to an international standard’’ [4]. Accreditation-based quality systems are governed by the international Standard ISO/IEC 17025 [5]. This standard exploits the extensive experience gained in implementing the ISO/IEC Guide 25 and EN 45001 norms and replaces them both. The ISO/IEC Standard sets forth the requirements a laboratory has to meet to be recognized as competent to carry out tests and/or calibrations, including sampling. The pillars of an accreditation system are listed in Table 1. Method validation is central to the accreditation process as reliability and comparability of data are crucial to perform experimental meaningful tests and to achieve credible results which can be profitably used by the client, i.e., the end user. It should be noted that the overall validation process covers all of the pivotal phases of an experimental measurement and not only the mere quantification step, as illustrated in Figure 1. In turn, method validation as such should at least cover the parameters given in Table 2. For the different levels of quality assurance in the accreditation system presented in Table 1, guidelines and requirements are well described in detail by several regulatory bodies and standardization agencies. Relevant guidelines are given in Table 3. Eurachem guides are published on quality in the laboratory in general [5], method validation [6] and proficiency test [7]. A guideline on proficiency test from the joint Eurachem-Eurolab-EA group is also available [8]. At the European level, there is also the CEN, which is working through different technical committees and working groups on standardization of analytical methods for all sectors [9]. At the international level, IUPAC, ISO and AOAC International are distinguished. All three bodies develop validation and standardization frameworks for analytical chemistry. AOAC International introduced the ‘‘AOAC Peer Verified Methods Program’’ [10]. IUPAC, ISO and the AOAC International Table 1
Key aspects of a laboratory compliant with an accreditation system
Service to the client Policy for complaints Control of non-conformities Quality manual Management of records Internal audits Measurement traceability
Motivation of personnel Laboratory setting Validation of methods Equipment Management reviews Test and calibration items Report of results
Guidelines on Quality Implementation for Analytical Methods
81
Hardware validation
Software validation/qualification
Method validation
System suitability
VALIDATION
Figure 1 Major steps of the validation process.
Table 2
Parameters to be ascertained to validate an analytical method
Applicability Selectivity Calibration and linearity Trueness Accuracy Precision Recovery Range
Limit of detection Limit of quantification Sensitivity Ruggedness Robustness Fitness for purpose Matrix variation Measurement uncertainty
together developed different harmonized guidelines and protocols [11–17], in addition to a number of ISO standards [11,12]. The US FDA, USP and ICH developed guidelines specifically for pharmaceutical and biotechnological methods [18–20]. The international Codex Alimentarius Commission within the United Nations FAO/WHO Food Standards Program has a Codex Committee on Methods of Analysis and Sampling (CCMAS). CCMAS works out criteria for evaluating the acceptability of methods of analysis as well as guidelines on single-laboratory and inter-laboratory validation of methods [21,22]. For single-laboratory validation, CCMAS defends the harmonized IUPAC guidelines [23]. On the international level, also ILAC provides guidelines on proficiency test [5] and on accreditation [24,25] (Table 3). The use of standardized methods of analysis in analytical chemistry is one of the most traditional ways of achieving comparability of measurement results.
82
Sergio Caroli
Table 3 Overview of European and international regulatory bodies and their guidelines and standards on different aspects of analytical quality (Adapted from [26]) Body
Guidance on
Reference
Eurachem - A focus for analytical chemistry in Europe Cooperation of International Traceability in Chemistry (CITAC) European Commission for Accreditation (EA) European Committee for Standardization (CE) International Union of Pure and Applied Chemistry (IUPAC) International Standardization Organization (ISO) Association of Official Analytical Chemists (AOAC) US Food and Drug Administration (FDA) US Pharmacopeia (USP) International conference on harmonization (ICH) Food and Agriculture Organization/ World Health Organization (FAO/ WHO) Codex Commission on Methods of Analysis and Sampling (CCMAS) International Laboratory Accreditation Cooperation (ILAC)
Method validation
[5,6,7,8]
Proficiency test Quality assurance Accreditation Standardization
[9]
Method Validation Standardization Internal quality control Proficiency test Accreditation Method Validation
[10,11,12,27]
Method Validation
[21,22]
Proficiency testing Accreditation
[24,25]
[18,19,20]
Source: Adapted with permission from Ref. [10].
Especially in food analysis, agrochemicals, organic analysis and other analytical areas where unstable samples and/or measurands are analyzed, the use of standardized methods is often prescribed by legislation. Two IUPAC internationally harmonized protocols have for many years served as a basis for validation and adoption of standardized analytical methods (procedures). The first is the IUPAC ‘‘Protocol for the Design, Conduct, and Interpretation of Collaborative Studies’’ [26], and the second is the ‘‘Harmonized Protocols for the Adoption of Standardized Analytical Methods and for the Presentation of their Performance Characteristics’’ [28]. These Principles of collaborative studies for method validation are still widely applied by the AOAC International, as well as by the ISO. However, the world is changing rapidly and with the fast development of analytical instrumentation and the availability
Guidelines on Quality Implementation for Analytical Methods
83
of new analytical techniques and procedures the prescription of methods to be used is sometimes a limiting factor. Responding to the situation, the WPHQA has opened the door for single-laboratory method validation, also known as in-house method validation. The Principles presented in the IUPAC ‘‘Harmonized Guidelines for Single Laboratory Validation of Methods of Analysis’’ [29] and in the proceedings of the Joint AOAC Int./FAO/IAEA/ IUPAC International Workshop on the Principles and Practices of Method Validation, have been accepted as official guidelines by the CODEX Alimentarius Commission. Established internal quality-control practices and regular laboratory participation in proficiency testing constitute another very important pillar of quality assurance in analytical chemistry. Again, the contributions of the WPHQA have been indispensable. Two IUPAC internationally harmonized documents, namely the ‘‘International Harmonized Protocol for the Proficiency Testing of (Chemical) Analytical Laboratories’’ [30] and the ‘‘Harmonized Guidelines for Internal Quality Control in Analytical Chemistry Laboratories’’ [31] still provide the basic rules, which have received wide international acceptance and utilization. Assessment of laboratory performance based on a z-score evaluation introduced in the IUPAC proficiency testing protocol became the most frequently used approach in evaluation of laboratory performance. The protocol has been updated and a revised version titled ‘‘The International Harmonized Protocol for the Proficiency Testing (PT) of Analytical Chemistry Laboratories’’ was published in 2006 [32]. To supplement this so-called classical PT approach, the WPHQA recently initiated a separate project on the Selection and Use of Proficiency Testing Schemes for Limited Number of Participants (Chemical Analytical Laboratories) [32]. In case of a small number of participants, some limitations on statistical applications may appear and this project is aimed at elaborating some additional approaches for evaluation of participants’ results and their reporting. However, neither of the above described external quality assurance schemes replaces the internal laboratory quality control. The ISO/IEC 17025 standard, which serves as a basis for laboratory accreditation, is very general and brief in its Clause 5.9 titled ‘‘Assuring the Quality of Test and Calibration Results’’ [33]. It urges laboratories and accreditation bodies to use separate guidance, specifically prepared for their field of application. One of the most important parameters defining the quality of analytical measurement results is comparability. Comparability of measurement results is based on metrological traceability, which allows results to be compared independently of the time, place, analyst and procedure used. Two facets of this description are of concern. The first is the metrological traceability of chemical measurement results. It is a term often used and cited, but without a firm agreement within the measurement/scientific community regarding associated concepts, their understanding and requirements. Comparability of measurement is the ultimate goal of quality assurance and is a prerequisite for quality assurance implementation.
84
Sergio Caroli
The second regards the claim that the traceability chain in chemistry has been broken. This claim is often related to destructive analysis, where the sample and measurand are converted into the physical and chemical form suitable for the selected measurement technique/instrument. Such conversions (digestions, extractions, etc.) may result in the loss of measurand, incomplete conversion into the required chemical/physical form, or even contamination, and are very much dependent on the procedure used.
2.3 Key aspects of a quality system based on the Principles of Good Laboratory Practice In the early 1960s, the US Food and Drug Administration (FDA) became aware that some studies on the safety of new chemicals performed by TFs for regulatory purposes were basically unreliable. Evidence was in fact provided of major adverse effects of such substances which had not been reported at the time when the authorization for production and commerce was granted. In the early 1970s, the US Congress undertook the re-assessment of studies submitted by some TFs to Regulatory Authorities (RAs) and suspected to be fraudulent. Under such conditions thousands and thousands of safety studies on industrial chemicals, pesticides, herbicides, drugs, cosmetics and food and feed additives were
Figure 2 Article published by The Washington Post in 1974 on the falsification of experimental data.
Guidelines on Quality Implementation for Analytical Methods
85
conducted for years (about 35–40% of all toxicological studies authorized in the USA in that period). As an example, an article published by The Washington Post in 1997 is shown in Figure 2. Senator Edward Kennedy declared at the US Congress of January 20, 1976, that ‘‘y unreliable, undocumented and fraudulent research is the most frightening menace to the health and safety of people. That research be wrong because of technical problems or because of the lack of competence or even due to criminal negligence is less important than the very fact that it is wrong y’’. The GLP Principles were conceived to harmonize the conduct of non-clinical safety studies and to minimize the risk of fraud. Since the early years, this matter became a priority for the OECD which set up the GLP Principles in order to promote and manage the mutual acceptance of non-clinical safety studies in the Table 4
The OECD series on the GLP Principles and compliance monitoring OECD Principles of Good Laboratory Practice
No. 1 No. 2 No. 3 No. 4 No. 5 No. 6 No. 7 No. 8 No. 9 No. 10 No. 11 No. 12 No. 13 No. 14 No. 15
Principles of Good Laboratory Practice and Compliance Monitoring (as revised in 1995) Revised Guides for Compliance Monitoring Procedures for Good Laboratory Practice (1995) Revised Guidance for the Conduct of Laboratory Inspections and Study Audits (1995) Quality Assurance and GLP (as revised in 1999) Compliance of Laboratory Suppliers with GLP Principles (as revised in 1999) The Application of the GLP Principles to Field Studies (as revised in 1999) The Application of the GLP Principles to Short Term Studies (as revised in 1999) The Role and Responsibilities of the Study Director in GLP Studies (as revised in 1999) Guidance for the Preparation of GLP Inspection Reports (1995) The Application of the Principles of GLP to Computerized Systems (1995) The Role and Responsibilities of the Sponsor in the Application of the Principles of GLP (1999) Requesting and Carrying Out Inspections and Study Audits in Another Country (2000) The Application of the OECD Principles of GLP to the Organization and Management of Multi-Site Studies (2002) The Application of the OECD GLP Principles to in vitro Studies (2004) Establishment and Control of Archives That Operate in Compliance with the Principles of Good Laboratory Practice (2007)
86
Table 5
Sergio Caroli
Key aspects of a Test Facility compliant with a GLP system
Director of the Test Facility Study Director Quality Assurance Unit Operative Procedures Archivist Sponsor Test and reference items
Study plan Final report Standard Test Site (if applicable) Principal Investigator (if applicable)
Member Countries. According to OECD, the Principles of GLP are a quality system concerned with the organizational process and the conditions under which safety studies are planned, conducted, controlled, recorded, reported and archived. In practice, they form a body of reciprocally dependent documented items that make the falsification of a study more time-consuming and expensive than its actual correct performance. GLP embodies a set of Principles that provides a framework within which laboratory studies can be reliably carried out. These studies are undertaken to generate data by which the hazards and risks to users, consumers and third parties, including the environment, can be assessed for pharmaceuticals, agrochemicals, cosmetics, food and feed additives and contaminants, novel foods and biocides. GLP helps assure regulatory authorities that the data submitted are a true reflection of the results obtained during the study and can therefore be relied upon when making risk/safety assessments. As a part of the permanent activities of its Environment, Health and Safety Programme, the OECD also prepares and publishes Test Guidelines for Chemical Substances to be used when performing GLP studies and thus enhance their reliability. The Series on the GLP Principles and compliance monitoring consists at present of 15 monographs, as detailed in Table 4, whereas Table 5 details the pillars of a GLP system [34,35]. These guides form the core of the legal provisions of the European Union in the field of GLP [36,37].
3. CONCLUSIONS The two quality systems have been conceived to meet quite different needs. In other words, the accreditation criteria are designed to manage activities in a laboratory where routine quantitative measurements (such as analytical determinations) are carried out, whereas the GLP Principles are intended to guarantee the integrity of data generated in non-clinical safety studies. Their respective fundamental characteristics are summarized in Table 6. From this standpoint, it is worth mentioning that, e.g., the GLP system prescribes that the Director of the TF, the person responsible of the Quality Assurance Unit, the Study Director and the Archivist be all independent of each other to fully
Guidelines on Quality Implementation for Analytical Methods
Table 6
87
Key elements of the accreditation and GLP system
Accreditation quality system
GLP quality system
Overlapping aspects
Management of complaints Uncertainty of measurements Proficiency testing Preventive actions Service to the client Sampling
Master schedule Study director Archivist Quality assurance unit Study plan Test article Reports
Management Motivation Training Reference materials Equipment and maintenance Method validation Chain of custody Quality control Procedures Corrective action Audits Sample reception
guarantee the fair conduct of the study, while in the case of the accreditation system the first two functions can coincide and the third one does not exist. On the other hand, in the accreditation system, it is imperative to have a quality manual, which in turn is not formally requested in the GLP system, although in the latter the Standard Operating Procedures play basically the same role. Moreover, a study plan, compulsory in the GLP system, is not needed in the accreditation one, not to speak of the fact that management of complaints and participation in proficiency testing is compulsory in the latter, but not necessary in the former. As regards validation of methods, the GLP system requires that validated methods are in place, but does not impose that such methods are set up according to the GLP Principles, any other fit-for-purpose quality system being acceptable to this end. All this provides clear evidence of the profound diversity in the approaches and goals of the two systems, although some common aspects are present. In this regard, in recent years, the OECD has established a dialogue group to verify where the two systems can actually interact, thus minimizing useless duplication of efforts. In conclusion, the selection of the quality system to be adopted should be carefully made on the basis of the prevailing activities carried out in the laboratory. Quality is inescapable, but it has a cost: a wrong decision can only lead to failure.
REFERENCES 1 Ph. Quevauviller, E.A. Maier and B. Griepink (Eds.), Quality Assurance for Environmental Analysis, Elsevier, Amsterdam, The Netherlands, 1995, xx–649. 2 J.P. Seiler, Good Laboratory Practice. The Why and the How, Springer, Berlin, Germany, 2001, x–395. 3 Ph. Quevauviller (Ed.), Quality Assurance in Environmental Monitoring. Sampling and Sample Pretreatment, VCH Weinheim, New York, NY, USA, 1995, xv–306.
88
Sergio Caroli
4 IUPAC Technical Report, Pure Appl. Chem., 74(5) (2002) 835–855. 5 CITAC/Eurachem Guide: Guide to Quality in Analytical Chemistry – An Aid to Accreditation, 2002. Available at http://www.Eurachem.bam.de 6 Eurachem Guide: The fitness for purpose of analytical methods. A laboratory guide to method validation and related topics, LGC, Teddington, Middlesex, UK, 1998. Available at http://www. Eurachem.bam.de 7 Eurachem Guide: Selection, use and interpretation of PT schemes by laboratories, 2000. Available at http://www.Eurachem.bam.de 8 Eurachem/Eurolab/EA Guide EA-03/04: Use of proficiency testing as a tool for accreditation in testing, August 2001 – rev. 01, 18pp. 9 CEN, European Committee for Normalisation, 2004. Available at http://www.cenorm.be/cenorm/ index.htm 10 AOAC International, Method Validation Programs (OMA/PVM Department), including Appendix D: Guidelines for collaborative study procedures to validate characteristics of a method of analysis, 2000. Available at http://www.aoac.org/vmeth/devmethno.htm 11 M. Thompson, S. Ellison and R. Wood, Pure Appl. Chem., 74 (2002) 835. 12 M. Thompson and R. Wood, Pure Appl. Chem., 67 (1995) 649. 13 W. Horwitz, Pure Appl. Chem., 67 (1995) 331. 14 M. Thompson and R. Wood, Pure Appl. Chem., 65 (1993) 2123. 15 L.A. Currie, Pure Appl. Chem., 67 (1995) 1699. 16 L.A. Currie and G. Svehla, Pure Appl. Chem., 66 (1994) 595. 17 W.D. Pocklington, Pure Appl. Chem., 62 (1990) 149. 18 ICH-Q2A, Guideline for Industry: Text on Validation of Analytical Procedures, 1995. Available at http://www.fda.gov/cder/guidance/index.htm 19 ICH-Q2B, Guidance for Industry: Validation of Analytical Procedures: Methodology, 1996. Available at http://www.fda.gov/cder/guidance/index.htm 20 FDA/CDER/CVM, Guidance for Industry – Bioanalytical Method Validation, 2001, 22pp. Available at http://www.fda.gov/cder/guidance/index.htm 21 CX/MAS 01/4, Codex Alimentarius Commission, Codex Committee on Methods of Analysis and Sampling, Criteria for evaluating acceptable methods of analysis for Codex purposes, Agenda Item 4a of the 23rd Session, Budapest, Hungary, 26 February–2 March 2001. 22 CX/MAS 02/12, Codex Alimentarius Commission, Codex Committee on Methods of Analysis and Sampling (FAO/WHO), Validation of methods through the use of results from proficiency testing schemes, Agenda Item 8c on the 24th Session, Budapest, Hungary, 18–22 November 2002. 23 W. Horowitz, Pure Appl. Chem., 60 (1988) 855. 24 ILAC-G13, Guidelines for the requirements for the competence of providers of proficiency testing schemes, ILAC Technical Accreditation Issues Committee, 2000, 23pp. Available at http://www. ilac.org/ 25 ILAC-G18, The scope of accreditation and consideration of methods and criteria for the assessment of the scope in testing, ILAC Technical Accreditation Issues Committee, 2002. Available at http:// www.ilac.org/www 26 I. Tavernier, M. De Loose and E. van Bockstaele, Trends Anal. Chem., 23 (2004) 535. 27 ISO/IEC 17025, General Requirements for the Competence of Testing and Calibration Laboratories. 28 M. Thompson, S.R.L. Ellison and R. Wood, Pure Appl. Chem., 74 (2002) 838. 29 A. Fajgelj and A. Ambrus (Eds.), Principles and Practices of Method Validation. The Royal Society of Chemistry, Special Publication No. 256, Cambridge, 2000, ISBN 0-85404-783-2. 30 M. Thompson and R. Wood, Pure Appl. Chem., 67 (1995) 649. 31 M. Thompson, S.R.L. Ellison and R. Wood, Pure Appl. Chem., 78 (2006) 145. 32 www.iupac.org/projects/2005/2005-019-2-500.html 33 ISO/IEC 17025 International Standard: General Requirements for the Competence of Testing and Calibration Laboratories, International Organization for Standardization, Geneva, 2005, ICS 03. 120.20.
Guidelines on Quality Implementation for Analytical Methods
89
34 OECD Series on Principles of Good Laboratory Practice and Compliance Monitoring, Number 1, OECD Principles on Good Laboratory Practice (as revised in 1997), ENV/MC/CHEM (98)17. 35 S. Caroli (Ed.), The New Principles of Good Laboratory Practice: Priorities, Problems, Perspectives, Ann. Ist. Super. Sanita`, 2002, Vol. 38, 110pp. 36 Directive 2004/9/EC of the European Parliament and Council, 11 February 2004, Off. J. EU, L50 (2004) 28–43. 37 Directive 2004/10/EC of the European Parliament and Council, 11 February 2004, Off. J. EU, L50 (2004) 44–59.
CHAPT ER
4 Immunochemical and Receptor Technologies: The Role of Immunoassay, Immunoaffinity Chromatography, Immunosensors and Molecularly Imprinted Polymeric Sensors ´ Marinel la Farre´, Elena Martı´nez and Damia` Barcelo
Contents
1. 2. 3. 4.
Introduction Definitions and Concepts Immunoassay Formats Immunoassay Development 4.1 Hapten synthesis 4.2 Antibody production 4.3 Assay development and assay optimization 4.4 Validation 5. Immunochemical Technologies 5.1 Radioimmunoassays (RIAs) 5.2 Enzyme-based immunoassays (EIAs) 5.3 Fluorescence polarization immunoassay (FPIA) 5.4 Chemiluminescent magnetic immunoassay (CMIA) 5.5 Flow-injection immunoassay (FIIA) 5.6 Immunoaffinity chromatography 5.7 Immunosensors 6. Biomimics: Molecularly Imprinted Polymers (MIPs) 6.1 MIPs in preparation/preconcentration and separative applications 6.2 Development and application of MIP-based sensors 7. Commercial Instrumentation and Future Perspectives References
Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00004-4
92 93 95 96 96 99 100 101 101 102 102 105 106 107 107 107 113 118 120 122 125
r 2008 Elsevier B.V. All rights reserved.
91
92
Marinel la Farre´ et al.
1. INTRODUCTION The food industry faces an unprecedented level of scrutiny. Consumers are not only concerned with the safety and quality of food products but also with the way in which they are produced. At the same time, the food industry has developed new ways of assuring appropriate standards for its products and their methods of production, developing systems such as Total Quality Management (TQM) and Hazard Analysis and Critical Control Point (HACCP) to identify and manage key steps in production. On the other hand, the adulteration of food has progressed from being a simple means of fraud to a highly sophisticated and lucrative business. The problem is further compounded by the lack of clear international definitions for enforcement purposes. Adulteration of food has ramifications within society and cannot be ignored since interference with foodstuffs may potentially lead to the production of food that is harmful to health. For all these reasons food safety authorities force a major control. Nowadays quality control analysis is an essential tool in food industry, and due to these reasons a significant number of rapid analytical techniques have arisen during the past decade. One of the most successful groups of these rapid techniques are immunoassays. Immunoassays are based on the binding properties of antibodies (Abs) with antigens (Ags). An antibody is an immunoglobulin (Figure 1) used by the immune system to identify and neutralize foreign objects. An antibody contains two sites called paratopes that bind antigens. These structures can be thought of as similar to locks and are specific for just one particular part of the antigen called an epitope, which can be thought of as similar to a key.
Antigen binding site
Antigen binding site
Variable Constant
Light chain
Heavy chain
Figure 1 Antibody scheme.
Immunochemical and Receptor Technologies
93
The Ab–Ag interaction is reversible, as determined by the law of mass action, and is based on electrostatic forces, hydrogen bonding, hydrophobic and Van der Waals forces. The binding properties of an antibody to an antigen have been used for the development of a wide variety of analytical techniques applicable in clinical chemistry, endocrinology, food analysis and environmental control. This chapter summarizes the most representative immunochemical technologies applied to food analysis.
2. DEFINITIONS AND CONCEPTS Immunoassays are applied for the measurement of both single and multiple analytes [1]. Chemical pesticides, polychlorinated biphenyls (PCBs) and antibiotics are typical examples of contaminants, which can be rapidly and efficiently determined by antibody-based methods. Antibodies enable not only a rapid detection of analyte in water, body fluids, soil or food extracts, but they can also be exploited in sample preparation prior to analyte detection. Because antibody affinity and specificity determine primarily the analytical capability of the immunochemical method, the properties of the antibodies represent an important innovative factor in developing an analytical system. Highly sensitive detection of toxic analytes can be performed by enzyme immunoassays, immunosensors and related techniques, whereas immunoaffinity chromatography and flow-injection immunoassay (FIIA) systems enable the concentration and clean up of the analytes in question. The manner of chemical binding of the hapten to a protein determines the character of the antibody specificity. Various types of hapten derivatives conjugated to proteins have been used for antibody development. Different types of Abs are involved in immunoassays: polyclonal, monoclonal and recombinant. Polyclonal Abs are obtained from the serum of animals immunized with a particular Ag. The Ab pool obtained from serum is the result of many B-cell clones, each secreting one specific Ab. Antiserum refers to a pool of serum containing all of the Ab fraction plus other serum proteins. Whereas, monoclonal antibodies are produced following the fusion of myeloma cells with Ab-secreting B-cells (Figure 2). The resultant continuous cell line (hybridoma) produces large quantities of the homogeneous, well-defined, single-epitope Ab. The availability of large quantities of continuously produced Ab allows greater standardization and quality control of the Ab reagent. Therefore, monoclonal antibodies are more precisely characterized, legally protected and have greater acceptance by regulatory agencies. Preparation of recombinant antibody fragments with novel binding properties was a primary goal of gene technologies. Their major asset lies in the possibility to focus mutagenesis on that part of gene that determines the structure and affinity of antibody binding site. Large phage libraries expressing antibody fragments on the surface of individual phage particles were used for preparation of recombinant antibodies. The systems enable separation of individual phage
94
Marinel la Farre´ et al.
Immunization Tissue culture
Antibody-forming
Tumor cell
Fusion
Hybridoma Hybridoma screening for antibody Antibody-producing hybridoma cloned
Monoclonal antibodies isolated for cultivation
Figure 2 Monoclonal antibodies production scheme.
particles and subsequent selection of phage antibodies from a large number of expressed phage particles. Immunoassays offer a number of advantages in food contaminants analysis over the conventional methods, such as liquid- or gas chromatography-based methods, because immunoassays can provide fast, simple and cost effective detection, with sensitivity in most cases comparable or better to conventional techniques. In addition, the possible automation and the versatility in the applications of immunochemical techniques have also made these techniques more popular in recent years. Main advantages of these methods are: Reduced time of analysis Low detection limits High throughput of samples
Immunochemical and Receptor Technologies
95
Cost effectiveness for large numbers of samples Adaptability to field use Small volumes of sample and solvents are required. Another relevant advantage is the cost effectivity of immunochemical approaches. In general, the major costs involved in food contaminants analysis are related to instruments (including maintenance), skilled personnel, solvents, reagents and time (for both sample pre-treatment and analysis). On the contrary, the instrumentation required by immunochemical approaches is economical in comparison to classical instrumental method, and involved manipulation are easy and rapid, requiring none or minimal quantities of solvent as well as little amount of sample. All these factors reverberate in more than 10 times lower cost of analysis using immunoassays than using classical instrumental analysis. On the other hand, a series of limitations should be also pointed out.
Immunoreagent preparation Lack of implementation Lack of immunoreagent stability Cross-reactivity Matrix effects.
The lengthy development time that can be required for immunoreagent preparation and the lack or limited response in front of some contaminants is sometimes an important limitation of immunochemical techniques, e.g., almost no immunological response can be obtained in front of per-fluorinated compounds and no antibodies against these contaminants can be obtained. The lack of stability (especially thermal, and in front of extreme pH ranges) is a limitation for the use of immunochemical analysis in some cases. Cross-reactivity is the lack of specificity of an immunoassay in front of an analyte when the immunoassay can react with other structurally related compounds, this is a characteristic that directly depends on the antibody. However, when the object of the analysis is screening a group of related substances, this fact can be an advantage.
3. IMMUNOASSAY FORMATS Immunoassays may be carried out according to different formats. Figure 3 shows the most widely used. Competitive assays are the most common and can be performed in different ways, such as the analyte and the tracer competing for a limited number of binding sites (direct), or the analyte and the immobilized ligand (antigen) competing for a limited number of binding sites (indirect). Non-competitive immunoassays are also performed in sandwich-type immunoassays, in which the analyte is recognized by two different antibodies.
96
Marinel la Farre´ et al.
Figure 3 Enzyme-linked immunosorbent assay formats.
4. IMMUNOASSAY DEVELOPMENT The main steps for immunoassay development are: 1. 2. 3. 4.
Hapten synthesis Antibody production Assay optimization and characterization Validation.
4.1 Hapten synthesis Small molecules, such as most food contaminants, with molecular weights lower than 5,000–10,000 do not elicit immune responses. In those cases, the molecules are named haptens because it is necessary to attach them to a large carrier protein in order to stimulate the immune response. Sometimes, the hapten is used as detector, then it is attached to an enzyme. In both cases, as immunogen, or as detector, the attachment to the protein is through a covalent bond, and a linker or spacer arm is often used to enable greater antibody recognition. Antibody specificity is directed to sites on the hapten that are distal to the point of linker attachment [2,3]. A good displacement of hapten by the spacer arm generally produce antibodies with high titer, but sometimes fails to provide the required sensitivity in an immunoassay. A wide variety of proteins are available for the synthesis of immunogens or antigens including bovine serum albumin (BSA), and human serum albumin, ovalbumin, conalbumin, thyroglobulin, keyhole limpet hemocyanin (KLH) or horseshoe crab hemocyanin, and the synthetic polypeptides poly-l-lysine
Immunochemical and Receptor Technologies
97
and polyglutamic acid. Among them, KLH is often the first choice as an immunogen carrier protein because it is large (approximately 106 kDa), highly immunogenic and easy to conjugate because their high abundance of functional available groups. Thyroglobulin has been increasingly used as an immunogenic carrier protein owing to its high water solubility. Another frequently used protein in immunoassay is BSA, specially as a coating antigen carrier. Advantages of BSA include its wide availability in pure form, low cost, stability, relatively resistant to denaturation and is suitability for some conjugation procedures that involve organic solvents. BSA has a molecular weight of 64,000 Da. A spacer arm is preferable with an alkyl chain of three to six carbons. The use of bulky functionalities, such as aromatic rings, conjugated double bonds in spacer arms should be avoided to minimize the recognition of this region by the antibodies [3]. Propionic, succinic and caproic acid are the most commonly used spacer arms for contaminant immunoassay development. The selection of conjugation method is dependent on the functional group on the hapten (e.g., carboxylic acid, amine, aldehyde). A hapten with a carboxylic acid group can conjugate with a primary amino group of a protein using the carbodiimide, activated N-hydroxysuccinimide (NHS) ester or mixed anhydride methods. Haptens with free amino groups can be coupled to proteins using glutaraldehyde condensation or diazotization. Haptens that have been designed to contain spacers may be linked directly to the protein with methods such as the mixed anhydride, whereas haptens lacking a spacer should be coupled using methods that insert a linker between the hapten and the protein such as with glutaraldehyde. Typical procedures are:
Anhydride mixed method Carbodiimide method NHS method Carboxylic methods Hydroxyl groups.
Methods for linking hapten carboxyl groups to amine groups of antigenic proteins include activation by carbodiimides, isobutyl chloroformate or carbonyldiimidazole. In the widely used carbodiimide method, the carbodiimide activates the carboxylic acid to speed up its reaction with the amine. Acidic conditions catalyze the formation of the active O-acylurea intermediate while the protein is more reactive at higher pH, when the lysine amino groups are unprotonated. Therefore, as a compromise, a pH near 6 is used. The choice of the carbodiimide is dependent on the reaction conditions. For example, dicyclohexylcarbodiimide (DCC) is used in nonaqueous media with nonpolar, water insoluble haptens where the carrier protein, in aqueous solution, is added to the activated hapten in a two-step reaction. For more water-soluble haptens, water-soluble derivatives of DCC such as 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide or 1-cyclohexyl-3-(2-morpholino ethyl) carbodiimide
98
Marinel la Farre´ et al.
metho-p-toluenesulfonate (CMC or Morpho CDI) are used in one-step reactions. However, the 1-ethyl-3-(3-dimethylaminopropyl)-3-ethylcarbodiimide react directly with the protein, and some antibodies are generated against the resulting highly immunogenic protein–urea complex. Formation of these antibodies is not a drawback as long as a different coupling chemistry is used to prepare the plate coating antigens. Activated NHS esters of carboxylic acids are prepared by reacting the acid with NHS in the presence of DCC. NHS esters are stable when kept under anhydrous and slightly acidic conditions, and they react rapidly with amino groups to form an amide in high yield. Like the carbodiimide method, the mixed anhydride method [4] results in an amide complex. The acid-containing hapten is dissolved in a dry, inert, dipolar, aprotic solvent such as p-dioxane, and isobutyl chloroformate is added with an amine catalyst. The activated mixed anhydride is chemically stable and can be isolated and characterized. The aqueous protein solution is added to the activated acid and the pH is maintained at around 8.5. A low temperature (around 101C) is necessary during the reaction to minimize side reactions. Amine groups in haptens, carrier proteins or both can be modified for conjugation through homo- or heterobifunctional crosslinkers such as succinic anhydride, succinyl chloride, or glutaraldehyde. Glutaraldehyde condensation has been used widely to produce protein–protein and hapten–protein conjugates. The glutaraldehyde reagent should not have undergone polymerization. Aromatic amine-containing haptens are converted to diazonium salts with ice-cold nitrous acid. Diazonium salts can then react with a protein in alkali through electrophilic attack of the diazonium salt at histidine, tyrosine and (or) tryptophan residues of the carrier protein. Other reactions can also be used to couple haptens to proteins, e.g., the periodate oxidation is suitable for compounds possessing vicinal hydroxyl groups such as some sugars. The conjugates characterization is based on the determination of the haptens density, which is important for both immunization and assay performance. The degree of conjugation can be determined by established methods, such as characteristic ultraviolet (UV) or visible absorbance spectrum that distinguishes the hapten from the carrier protein or by the use of a radio labeled hapten. If the hapten has a similar lmax to the protein, the extent of incorporation can still be estimated when the concentration of the protein, and the spectral characteristics of the hapten and protein are known. The difference in absorbance between the conjugate and the starting protein is proportional to the amount of hapten conjugated [5]. Hapten density can also be determined indirectly by measuring the difference in free amino groups between conjugated and unconjugated protein using trinitrobenzenesulfonic acid [6]. These methods can be used as a rough estimation because the process of conjugation usually alters the apparent number of amine or sulfhydryl groups on the protein. On the other hand, matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) has been applied to estimate the number of
Immunochemical and Receptor Technologies
99
covalently bound haptens [7]. Although these methods offer an accurate approach, large proteins cannot be analyzed. Hapten density, and also the common positions where haptens are bound, can also be estimated by cyanogen bromide or enzymatic cleavage of the protein and either MALDI-MS or separation of the components by reversed-phase ion-pair chromatography and electrospray or electrospray time-of-flight (TOF) analysis. The optimum hapten ratio may depend on the study objectives, the nature of the antigen, immunization protocol, etc. A general rule of thumb is to target high hapten ratios for immunogens and low hapten ratios for coating antigens or enzyme tracers. For immunogens, a high hapten ratio implies greater exposure of the immune system to the hapten; for coating antigens or enzyme tracers, a lower hapten density implies fewer haptens to compete with the analyte in the assay. Optimum hapten density is often determined empirically with checkerboard titration procedures. Such procedures are very rapid and are normally adequate to optimize enzyme-linked immunosorbent assays (ELISAs) without knowing the exact hapten density. However, for the development of new immunosensor devices the determination of exact hapten densities may become increasingly important.
4.2 Antibody production Any vertebrate can be used as a source of antibodies. However, the most used animals for antibody production are rabbits, goats and sheep for polyclonal antibodies, and mice for monoclonal antibodies. For example rabbits are easy to care for and produce a moderate amount of serum often with high antibody titers. Goats or sheep also produce high-quality antiserum in larger amounts. Monoclonal antibodies are obtained from a mouse cell line. These antibodies are produced by fusing single antibody-forming cells to tumor cells grown in culture. The resulting cell is called a hybridoma. Each hybridoma produces relatively large quantities of identical antibody molecules. By allowing the hybridoma to multiply in culture, it is possible to produce a population of cells, each of which produces identical antibody molecules. Although it is attractive to have a permanent supply of antibody with constant specificity and affinity, these cell lines may contain an unstable chromosome complement and their immortality depends upon proper storage and maintenance. The advantages, disadvantages and production of monoclonal antibodies have been discussed in several book chapters and reviews [8,9]. Antibody engineering and production of recombinant antibodies is a very promising field both for research and application [10,11]. Basic synthetic ways for preparation of the hapten derivatives (hapten design) were explored primarily in steroids more than 30 years ago [12]. Hapten immunochemistry thus represents a consistent area for the development and preparation of conventional antibodies. As new impulses for progress are largely depleted, further experimental strategies have been sought outside the classical immunochemistry area. In the past decade, molecular biology has generated fundamental changes in antibody production.
100
Marinel la Farre´ et al.
The discovery of polymerase chain reaction (PCR) simplified the cloning of monoclonal antibody genes from mouse monoclonal cell lines. These functional recombinant antibody fragments could be expressed in bacteria for use [13]. To take advantage of recombinant technology, efficient, large-scale screening techniques must be used. Immunization procedures and schedules vary depending on the laboratory [14]. Usually an initial series of injections is followed by booster injections some weeks later. Animals are generally bled 7–14 days after each booster injection to determine the characteristics of the serum. Serum is collected or pooled following numerous booster injections and (or) the animal may be exsanguinated. For long-term storage, antibodies are best stored frozen either in solution or as a lyophilized powder. Antibodies can be kept in solution containing 0.1% sodium azide (to prevent growth of microorganisms) in a refrigerator for up to a year. Solutions can also go through freeze–thaw cycles several times without too much loss of activity. Although antibodies are relatively hardy proteins, the concentration should be kept above 1 mg/mL during storage, solutions should be frozen quickly in liquid nitrogen before placing in a standard freezer and for long-term storage antibodies are lyophilized and stored in containers sealed under dry nitrogen.
4.3 Assay development and assay optimization The different steps and procedures to develop and optimize one of these assays are linked to the type of immunoassay, such as immunoreagent immobilization in case of immunosensor development, these steps will be reviewed in later sections focused on the different techniques. However, in immunoassay development, there are always two general steps that can be summarized as Determination of optimal immunoreagent concentrations and Determination of optimum general assay conditions of pH, solvents, ionic strength and cross-reactivity. The first stage is the determination of the optimum coating antigen/hapten– enzyme conjugate and anti-analyte antiserum concentrations. This stage involves, in most cases, the development of an ELISA, using a checkerboard titration. In the 96-well plate, the coating antigen concentration is varied by row and the antibody concentration is varied by column so that each well has a different combination of antigen and antibody concentrations. The concentrations that yield a reasonable signal and at which the system is not saturated can be estimated by plotting the resulting absorbance values versus reagent concentration. Using the optimum reagent concentrations, the assay is tested for inhibition by the target analyte. If a useable IC50 is obtained, then further optimization is conducted. This second stage of optimization includes determining the optimum assay temperature and incubation times and the effect of potential interferences (e.g., solvent, salt, pH and cross-reactivity).
Immunochemical and Receptor Technologies
101
The percentage of cross-reaction produced by the structurally close-related compounds is of high importance because they may cross-react with the antibody, yielding inaccurate results.
4.4 Validation Initial validation involves an evaluation of the sensitivity and specificity of the immunoassay, whereas later validation includes comparison with a reference method (in general based on chromatography) with a known accuracy using an identical sample set. When comparing two methods, it is important to be aware of the strengths and weaknesses of each one. Validation should also include testing the effects of sample matrices. Matrix effects are determined by running calibration curves in various dilutions of matrix and comparing the results with those obtained for corresponding calibrations curve run in buffer. Overlapping curves indicate no effect of matrix. Parallel curves are an indication that matrix interference is binding the antibody in the same manner as the analyte. Nonparallel curves are indicative of nonspecific matrix interferences. A second test for matrix effects is to analyze a sample before and after a known amount of analyte has been added (test of additivity). If the values for the ‘before’ and ‘after’ samples are not additive a matrix effect is presumed. If matrix effects are present, then adjustment of the immunoassay method, such as running the calibration curve in the matrix or further sample preparation, is necessary. The final steps in validation involve testing a limited number of samples containing incurred residues to determine if the method provides reliable data.
5. IMMUNOCHEMICAL TECHNOLOGIES Table 1 summarizes the most representative immunochemical technologies applied to food analysis.
Table 1
General scheme of immunochemical techniques related to food control analysis
Basic immunoassays – Fluorescent immunoassays – Chemiluminescence immunoassays (CIA) – Radioimmunoassays (RIA) – Enzyme-lynked immunosorbent assays (ELISAs) – Fluorescence polarization immunoassay (FPIA) Immunoaffinity chromatography Flow injection immunoassays Immunosensors
102
Marinel la Farre´ et al.
5.1 Radioimmunoassays (RIAs) The development of practical immunoassays began in the 1960s with the application of radioimmunoassays (RIAs). RIAs utilize radioactive isotopes as a label, and the amount of radioactivity measured is indicative of the amount of analyte present. RIAs are still used today, particularly for detection of very low quantities of analytes. However, due to the inherent complications of handling and disposing of radioactive materials, RIAs are less often used in the laboratory than other types of immunoassays, such as enzyme-based immunoassays (EIAs).
5.2 Enzyme-based immunoassays (EIAs) Whereas RIAs use radioactivity to measure the concentration of analyte, EIAs typically use a change in color, emission of light, or other signal. Specific equipment is required to quantify the amount of enzyme present by measuring the signal change that occurs. EIAs offer numerous advantages over other immunotechniques because their signal is amplified by forming a great amount of product molecules, and they are widely used for food purposes, especially those based on heterogeneous conditions, such as ELISAs. The main enzymes used are horseradish peroxidase (HRP), alkaline phosphatase and b-galactosidase. Due to the selectivity and sensitivity, as well the simplicity of performing ELISAs, a wide number of assays for food contaminants have been reported in the literature, including low-weight analytes, such as phenols [15] and pesticides [16]. Table 2 summarizes some examples of ELISAs for food contaminants analysis. After the development of a new immunoassay, an important stage is the optimization for its application to real samples. These studies are based in setting the ideal conditions for real work, the evaluation of matrix effects and the establishment of the stages of sample pretreatment that could be necessary. It is also necessary to establish the selectivity of the assay for real samples under real working conditions, and the percentage of recovery. Finally, the validation can be carried out comparing the results of the EIA analysis of natural samples with those obtained by well-established methods, such as chromatographic approaches. Following the previous described scheme, a high number of works have been published showing the optimization and validation of new immunoassays for food analysis applications. Garce´s-Garcı´a et al. [17] developed and evaluated four plate immunoassays for routine determination of pesticide residues (diazinon, fenthion, malathion and chlorpyrifos) in extra virgin olive oil. A good correlation was found between the proposed immunoassays with the reference chromatographic (GC–MS) method. Nunes et al. [18] described a direct application of an ELISA for carbaryl determination in fruit and vegetables, with a limit of detection from 0.13 to 6.05 mg/L. A good correlation was found in comparison with a liquid chromatography postcolumn reaction fluorescence detection method. Shen and Jian [19] performed an study on screening, determination and confirmation of chloramphenicol (CAP) in 10 kinds of matrices, including seafood, meat and honey by
Immunochemical and Receptor Technologies
Table 2
103
Summary of ELISAs applied to food analysis
Class
Name
Matrix
Reference
Herbicide
Bensulfuron-methyl Chlorpropham Chlorsulfuron Cyclohexanediones Dichlobenil Dichlorprop methyl ester Fluometuron Hexazinone Isoproturon Metsulfuron-methyl Propanil Triazines Trifluralin
Water Food
[20] [21] [22] [23,24] [25] [26] [27] [28] [29] [30] [31] [32] [33]
Acetamiprid Allethrin Azidirachtin Azinphos methyl Azinphos methyl Carbofuran Chlorpyrifos DDT Esfenvalerate Fenitrothion Flucythrinate Imidacloprid Organophosphates Oxamyl Permethryn Pymetrozine Pyretroids Spinosad
Food, water
Food, water, sediments
[34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46,47] [48] [49] [50] [51] [52]
Benalaxyl Captan Chlorothalonil Imazalil Myclobutanil Procymidone Tebuconazole Thiabendazole Thiram
Food, Food, Food, Food Food, Food Food Food Food
[53] [54] [55,56] [57] [58] [59] [60] [61] [62]
Gentamicin Kanamycin
Milk Milk
Insecticide
Fungicide
Antibiotics
Soil Water Water Water Water Food Food
Food Water Water Food Water Food, soil Water Food, water Food, water Food Water Plants
water water water water
[63] [64]
104
Marinel la Farre´ et al.
Table 2 (Continued ) Class
Name
Matrix
Reference
Neomycin Oxytetracycline Streptomycin Tetracycline Tylosin
Milk Pork meat Milk Water Water
[64] [65] [66] [67] [68]
Microorganisms
Escherichia coli Toxoplasma gondii Listeria monocytogenes
Food Pork Milk, ice-creams
[69] [70] [71]
Mycotoxins
Fumonisin Citrin
Food Grains
[72] [73]
ELISA, high-performance liquid chromatography with UV detector (HPLC–UV) and gas chromatography in combination with electronic capture detector (GC– ECD) and MS detector using electronic ionization and negative ion chemical ionization modes with selected-ion monitoring acquisition (GC–MS–EI–SIM and GC-MS–NCI–SIM). A number of immunoassays have been developed for detection of antibiotics and coccidiostats in milk. Watanabe et al. [74] developed a monoclonal ELISA for the detection of monesin in chicken plasma and cattle milk, with a limit of detection of 1 ng/mL and relative standard deviations between 2.1–6.3% intraassay and 5.9–12.9% inter-assay. At present different commercial kits are available in the market. Matthews and Haverly [51] evaluated three commercial kits in tube format for the determination of methyl-chlorpyrifos, methyl-pirimifos and fenitrothion in samples of grain. They realized linearity assays, and reproducibility, matrix effects studies and they determined the cross reactivity of related compounds, and they compared the performance of these commercial immunoassays with those from GC. In this work, the ELISA for Methyl-Chlorpyrifos was the most sensitive. Some of these immunoassays have been developed for food quality evaluation, for example, a Performance Tested MethodSM multiple laboratory validations for the detection of peanut protein in four different food matrixes were conducted under the auspices of the AOAC Research Institute [75]. In this blind study, three commercially available ELISA test kits were validated: Neogen Veratoxs for Peanut, R-Biopharm RIDASCREENs FAST Peanut and Tepnel BioKits for Peanut Assay. The food matrixes used were breakfast cereal, cookies, ice cream and milk chocolate spiked at 0 and 5 ppm peanut. All three commercial test kits successfully identified spiked and peanut-free samples. The validation study required 60 analyses on test samples at the target level 5 mg peanut/g food and 60 analyses at a peanut-free level, which was designed to ensure that the lower 95% confidence limit for the sensitivity and specificity would not be o90%. The probability that a test sample contains an allergen given a prevalence rate of
Immunochemical and Receptor Technologies
105
5% and a positive test result using a single test kit analysis with 95% sensitivity and 95% specificity, which was demonstrated for these test kits, would be 50%. When two test kits are run simultaneously on all samples, the probability becomes 95%. It is therefore recommended that all field samples be analyzed with at least two of the validated kits. During recent years a high number of assays have been developed using the dipstick format [26,27,76,77]. Cho et al. [78] developed a direct competitive ELISA for fenthion in microtiter plate and dipstick format. The microtiter plate ELISA showed an IC50 value of 1.2 mg/L with a detection limit of 0.1 mg/L. The antibodies showed negligible cross-reactivity with other organophosphorus pesticides. The use of the dipstick format using a support membrane allowed the quick visual detection of fenthion in concentrations W10 mg/L. The IC50 value of the dipstick format using reflectance detection was 15 mg/L with a detection limit of 0.5 mg/L. The recoveries of fenthion from spiked vegetable samples using the two formats without any prior enrichment or cleanup steps were 87–116%. Sharma et al. [79] have evaluated the suitability and sensitivity of two in vitro lateral-flow assays for detecting Clostridium botulinum neurotoxins (BoNTs) in several foods. The two lateral-flow assays, one developed by the Naval Medical Research Center (Silver Spring, MD) and the other by Alexeter Technologies (Gaithersburg, MD), were based on the immuno-detection of BoNT types A, B and E. The assays were found to be rapid and easy to perform with minimum requirements for laboratory equipment or skills. They can readily detect 10 ng/mL of BoNT types A and B and 20 ng/mL of BoNT type E. Compared to other in vitro detection methods, these assays are less sensitive, and the assessment of a result is strictly qualitative. The assays successfully detected BoNT types A, B and E in a wide variety of foods, suggesting their potential usefulness as a preliminary screening system for triaging food samples. Sometimes these assays present the advantage of avoiding any sample pretreatment; however, in some cases sophisticated extraction procedures can be also necessary in order to extract residues from complex matrices. This is the case of the extraction of pesticide residues in food samples presented by Lopez-Avila et al. [80] who performed a fluid solid extraction and ELISA procedure. General recoveries were around 70% except for carbaryl with a recovery percentage of 49.4%. Urruty et al. [81] applied a method based on solid-phase microextraction (SPME) followed by and immunoassay based on magnetic particles for the determination of procymidone residues in wine. The linear range of this assay was from 2 to 100 mg/L in fortified samples. The recoveries by ELISA and using the official method by GC were 109 and 103%, respectively.
5.3 Fluorescence polarization immunoassay (FPIA) Fluorescence polarization immunoassay (FPIA) is a type of homogeneous competitive fluorescence immunoassay. With competitive binding, antigens from the specimen and antigen-fluorescein (AgF) labeled reagent competes for binding sites on the antibody. As an homogeneous immunoassay, the reaction is carried
106
Marinel la Farre´ et al.
out in a single reaction solution, and the bound Ab–AgF complex does not require a wash step to separate it from ‘free’ labeled AgF. This immunoasay is utilized to provide accurate and sensitive measurement of small toxicology analytes such as therapeutic drugs, and some hormones. FPIA utilizes three key concepts to measure specific analytes in a homogeneous format Fluorescence: Fluorescein is a fluorescent label. It absorbs light energy at 490 nm and releases this energy at a higher wavelength (520 nm) as fluorescent light. Rotation of molecules in solution: Larger molecules rotate more slowly in solution than do smaller molecules. This principle can be used to distinguish between the smaller antigen-fluorescein molecule, AgF, which rotates rapidly, and the larger Ab–AgF complexes, which rotate slowly in solution. Polarized light: Fluorescence polarization technology distinguishes AgF label from antibody bound-antigen-fluorescein (Ab–AgF) by their different fluorescence polarization properties when exposed to polarized light. Polarized light describes light waves that are only present in a single plane of space. When polarized light is absorbed by the smaller AgF molecule the AgF has the ability to rotate its position in solution rapidly before the light is emitted as fluorescence. The emitted light will be released in a different plane of space in which it was absorbed and is therefore called unpolarized light. With the larger sized Ab–AgF complex, the same absorbed polarized light is released as polarized fluorescence because the much larger Ab–AgF complex does not rotate as rapidly in solution. The light is released in the same plane of space as the absorbed light energy, and the detector can measure it. A FPIA method based on a monoclonal antibody for the detection of parathionmethyl was developed and optimized by Kolosova et al. [82], with a linear range from 25 to 10,000 mg/L. The detection limit was 15 mg/L. Recovery in vegetable, fruit and soil samples averaged between 85 and 110%. The method developed showed a high specificity and reproducibility (coefficient of variation ranged from 1.5 to 9.1% for inter-assay and from 1.8 to 14.1% for intra-assay). The same authors developed another FPIA also based on monoclonal antibodies for the determination of ochratoxin A (OTA) [83]. This assay was highly specific and the cross-reactivity with other mycotoxins (zearalenone, aflatoxins, patulin and T-2 toxin) was negligible (o0.1%). However, when the assay was used in naturally contaminated barley samples in comparison with an indirect competitive ELISA some disagreement was observed between the results.
5.4 Chemiluminescent magnetic immunoassay (CMIA) Chemiluminescent compounds can also be used to label analytes. A chemiluminescent label produces light when combined with a trigger reagent. A chemiluminescent magnetic immunoassay (CMIA) for atrazine analysis was developed and evaluated by Fischer-Durand et al. [84], and this study demonstrates the feasibility of pesticide determination using CMIA, although the sensitivity of current CMIA format does not reach the required levels.
Immunochemical and Receptor Technologies
107
5.5 Flow-injection immunoassay (FIIA) FIIA, is based on the introduction of the sample into a carrier stream, which enters the reaction chamber where the immunoreaction takes place. In general in FIIA, the antibodies are immobilized to form an affinity column and analyte is pumped over the column. The loading of the antibodies with analyte is followed by pumping over the column enzyme tracers that compete with the analyte for the limited binding sites of the antibodies. Generally, the indirect format produces a result inversely proportional to the analyte concentration. FIIA can be used with electrochemical, spectrophotometric, fluorimetric and chemiluminescence detection methods. Conventional UV visible spectrophotometry is also suitable for the FIIA detection of bioligand interactions. FIIA has been used for the detection of diuron and atrazine in water. This method was developed as a cost-effective screen for determining compliance with the European drinking water directive. FIIA has been successfully used for the detection of pesticides (e.g., triazines [85,86]). At present, FIIA is integrated into different immunosensors.
5.6 Immunoaffinity chromatography This technique uses the binding properties between Ab–Ag for the selective extraction of an analyte from complex food and environmental matrices. The technique is especially useful for polar organic analytes. Immunoaffinity sorbents are used for pre-concentration of closely related compounds, that are later eluted, separated and analyzed; an example of application is the detection of isoproturon in water samples, allowing determination of 0.1 mg/L [87], or of bisphenol A [88]. The main limitations of these procedures are the effects of the matrix on immunoreagents, the small volume admitted by the immunosorbents and the desorbtion step that is sometimes difficult. Recent applications in food analysis have been focused on aflatoxins and ocratoxine. Prado et al. [89] performed the analysis of OTA in beers by immunoaffinity column and HPLC using a fluorescence detector. Recoveries of OTA from beer samples spiked at levels from 8.0 to 800 pg/mL ranged from 81.2 to 95.0%, with coefficient of variation between 0.1 and 11.0%. Detection limit and quantification limit were 2.0 and 8.0 pg/mL, respectively.
5.7 Immunosensors Immunosensors are a specific case of biosensors, and they constitute the most advanced technologies based on the binding properties of antibodies. In this context, nanotechnology, miniaturization, multi-sensor array development and, especially, biotechnology arise as fast-growing areas that will have a marked influence on the development of new immuno-sensing strategies in the near future. A biosensor is defined by IUPAC as a self-contained integrated device that is capable of providing specific quantitative or semi-quantitative analytical
108
Marinel la Farre´ et al.
information using a biological recognition element (biochemical receptor), which is retained in direct spatial contact with a transduction element. In the special case of immunosensors, the biochemical receptor is an antibody. This type of device combines the principles of solid-phase immunoassay with physicochemical transduction elements (electrochemical, optical, piezoelectric, evanescent wave and surface plasmon resonance (SPR)). In this section most relevant transduction principles coupled to immuno-affinity properties used in food analysis applications will be summarized.
5.7.1 Electrochemical transduction Small molecular weight organic residues in food (such as pesticides or their metabolites) have few distinguishing optical or electrochemical characteristics, the detection of stoichiometric binding of these compounds to antibodies is typically accomplished using competitive binding assay formats. The main limitation of these techniques is the electrochemical detection of the immunoreaction because it is necessary to use enzymes that will generate electrochemical active compounds. Electrochemical immunosensors have been widely used for food analysis in amperometric, potentiometric and conductimetric configurations. Some examples of new developments are the disposable screen-printed electrodes for the detection of polycyclic aromatic hydrocarbons (PAHs) [90] and the use of recombinant single-chain antibody fragments [91] for atrazine determinations. Alarcon et al. [92] described a direct, competitive electrochemical ELISA development for the quantitative determination of OTA in wine using polyclonal antibodies. The assay is carried out on carbon-based screen-printed electrodes. Recently, a novel electrochemical immunosensing strategy for the detection of sulfonamide antibiotics in milk based on magnetic beads has been presented by Zacco et al. [93]. Among the different strategies for immobilizing the class-specific anti-sulfonamide antibody to the magnetic beads — such as those based on the use of Protein A or carboxylate modified magnetic beads, the best strategy was the covalent bonding on tosyl-activated magnetic beads. The immunological reaction for the detection of sulfonamide antibiotics performed on the magnetic bead is based on a direct competitive assay using a tracer with HRP for the enzymatic labeling. After the immunochemical reactions, the modified magnetic beads can be easily captured by a magneto sensor made of graphite–epoxy composite (m-GEC), which is also used as the transducer for the electrochemical immunosensing. The electrochemical detection is thus achieved through a suitable substrate for the enzyme HRP and an electrochemical mediator.
5.7.2 Acoustic transduction These transducers have also been applied in immunosensors for food or water analysis [94]. The resonant frequency of an oscillating piezoelectric crystal can be affected by a change in mass at the crystal surface. Piezoelectric immunosensors are able to measure a small change in mass. Novelty contribution is the use of
Immunochemical and Receptor Technologies
109
magneto elastic transduction, an example is a mass-sensitive magneto elastic immunosensor for detection of Escherichia coli [95]. However, most of the past publications have been based on immunosensors using quartz crystal microbalance (QCM) for the detection of trace amounts of chemical compounds, such as dioxins [96]. Other examples of application are focused on the determination of pathogens such as the work presented by Liu et al. [97], in this work the detection of E. coli O157:H7 was accomplished using a QCM immunosensor with nanoparticle amplification. The quartz crystal is a highly precise and stable oscillator. It has been used widely in electric circuits as a frequency standard clock in computers, communication systems and frequency measurement systems. The quartz crystal is the crucial component of the QCM because it registers and reports the mass deposited on its electrodes quantitatively: the mass changes its oscillation frequency. It is also used for immunosensor techniques, for film thickness metres and for chemical sensors. A variety of surface-based detection principles are employed for immunosensors based on QCM. Preparation and characterization of such layers for useful deposition of detector molecules require sophisticated surface science input. Furthermore, commercialization for use in the food analysis, medical diagnostics and environmental monitoring fields necessitates stability and reliability of the bio-interface. Therefore, antibody immobilization method and its stabilization are very important to prepare the bio-functional interface of QCM immunosensors [98,99]. These methods are classified into three main categories Immobilization of the antibody on the crystal precoated with a suitable material Immobilization via entrapment in polymer membranes Immobilization via glutaraldehyde cross-linking. The prerequisites for the active surface of a QCM immunosensor include that it be chemically active of or toward the immobilized antibody or antigen. Furthermore, the coatings achieved using the immobilization method must be as uniform and thin as possible. These features are particularly important in QCM immunosensors because high sensitivity can only be achieved using active, thin and rigid layers. Additionally, leakage of the immobilized materials must not occur to any extent during the immunosensor use. Although many immobilization methods have been tried with QCM immunosensors, no one ideal method exists that gives high immobilization yield and good stability. Furthermore, the complexity and diversity of antibody or antigen that is useful for different purposes render it difficult to devise one optimum method. Therefore, it is necessary to find a suitable immobilization method for an antibody or antigen for a particular application. The development of QCM immunosensors for food analysis is in an initial phase of development, but it is one of the most promising fields. Up to now most of the applications have been centred in the analysis of pathogenic microorganisms [100].
110
Marinel la Farre´ et al.
5.7.3 Optical transduction Many optical devices have been developed. On the basis of solid-phase fluoroimmunoassays combined with an optical transducer chip chemically modified with an analyte derivative for the measurement of different pesticides in water control analysis [101,102], even for multidetection measuring pollutants at low nanogram per litre levels in single few-minutes analysis [103]. Different optical immunosensors have been constructed for the control of bacterial growth [104]. A variety of devices have been developed for bacterial detection, using a range of transduction elements. Seo et al. [105], described an immunosensor for Salmonella typhimurium detection in chicken carcass wash fluid, using a flowthrough cell that comprised two channels, one with immobilized anti-Salmonella antibodies through a silane-derivatized surface, and a reference channel with immobilized human IgG. An integrated optic interferometer allowed the specific measurement of Salmonella by comparing the phase shift generated by the refractive index variation with the reference channel. Although the assay time was 10 min, 12-h pre-incubation time is needed in order to allow a cultural growth level detectable by the sensor. DeMarco et al. [106] developed a portable polystyrene fibre optic device for E. coli O157:H7 and staphylococcal enterotoxin B analysis in 20 min. This rapid and sensitive device is now commercially available from Research International. The basic principle of optical waveguide lightmode spectroscopy (OWLS) technique is that the light polarized of He–Ne laser is coupled by diffraction grating into the wave-guide layer, if the incoupling condition is fulfilled. This incoupling resonance phenomenon occurs at the precise angle of incidence. This angle depends on the refractive index of the medium covering the surface of the wave-guide. In the wave-guide layer, the light is guided by total internal reflection to its ends where it is detected by photodiodes. By varying the angle of incidence of the light the mode spectrum can be obtained and the effective refractive index can be calculated for both the electric and the magnetic mode. OWLS is a label-free technique for investigating surface adsorptions, binding and adhesions processes as occurs in an immuno-reaction. This technique has been applied to food analysis such as the detection of Aflatoxin and Ochratoxin in wine using both competitive and indirect immunoassays. The sensitive detection range of the competitive detection method was between 0.5 and 10 ng/mL in both cases [107]. Several approaches are based on the principle of total internal reflection fluorescence (TIRF). This principle is based on incident plane waves that generate an evanescent wave, which excites molecules near a sensor surface, with a local distribution proportional to the evanescent electric field intensity. After a characteristic excited-state lifetime, these molecules emit fluorescent radiation with a local distribution in the surface similar to the excitation distribution. The light of the fluorescent evanescent wave is coupled back as a plane wave in the same way as the primary process, when a plane wave generates an evanescent wave. A recent work reports a sandwich immunoassay coupled to TIRF for the determination of Campylobacter and Shigella bacteria with limits of detection of
Immunochemical and Receptor Technologies
111
4.9 104 cfu/mL for Shigella dysenteriae, and lower than 9.7 102 cfu/mL for Campylobacter jejuni [108]. Recently, a TIRF-based biosensor for progesterone in bovine milk was developed and tested by measuring the progesterone level in daily milk samples. The assay has been designed as a binding-inhibition test with a progesterone derivative covalently immobilized on the sensor surface and a monoclonal antiprogesterone antibody as biological recognition element [109,110]. SPR is an optical electronic technique in which an evanescent electromagnetic field generated at the surface of a metal conductor is excited by light of a certain wavelength at a certain angle. Interest in the development of SPR-based immunosensors for detection and monitoring of low-molecular-weight analytes in food and environmental fields has been rapidly increasing over the past 10 years. By combining the advantages of the specific antigen–antibody immunoreaction and the high sensitivity and reliability of SPR signal transduction, SPR immunoassays offer exceptional sensitivity, specificity, speed and multianalyte detection in complex analytical matrices, such as food. Advances in the technology of antibody production and the signal transduction provide a promising scope for SPR immunosensors to lead in the next generation biosensors. SPR is associated with the evanescent electromagnetic field generated on the surface of a thin metal film when excited by an incident beam of light of appropriate wavelength at a particular angle, and it is explained as a charge density oscillation occurring at the interface between two media of oppositely charged dielectric constants. As the evanescent field generated under total internal reflection conditions is strongest at the interface and diminishes exponentially with increasing the distance of penetration from the interface, SPR promotes the detection of only surface-confined molecular interactions occurring on the transducer surface. There are two kinds of configuration used for excitation of surface plasmons: Kretchmann [111] and Otto [112]. Most of the SPR instruments use Kretchmann configuration working at attenuated total reflectance for excitation of surface plasmons. In general, an SPR immunosensor consisted of several important components: a light source, a detector, a transduction surface (usually gold-film), a prism, the bio-molecule (antibody or antigen) and a flow system. Figure 4 shows a simple scheme of the principle and operation of SPR immunoassay technique. The transduction surface is usually a thin gold-film (50–100 nm) on a glass slide optically coupled to a glass prism through a refractive index matching oil. In addition to gold, various metals can be used including silver, copper and aluminium. However, gold is highly preferred due to its chemical stability and free electron behaviour. Plane polarized light is directed through a glass prism to the gold/solution dielectric interface over a wide range of incident angles and the intensity of the resulting reflected light is measured against the incident light angle with a detector. At certain incident light wavelength and angles, a minimum in the reflectivity is observed at which the light waves are coupled to the oscillation of surface plasmons at the gold/solution interface. The angle at which the minimum reflectivity occurs is denoted as an SPR angle. This critical angle is very sensitive to the dielectric properties of
112
Marinel la Farre´ et al.
Flow Channel
Optical detection unit Reflected light I (initial)
Polarized light
Reflected light II (after binding)
Prism
Sensor chip with gold film
Intensity
Signal resonance II I
II I Angle
Time
Figure 4 SPR scheme based on total internal reflection (Kretschmann configuration).
the medium adjacent to the transducer surface apart from its dependence on the wavelength and polarization state of the incident light. In particular, the resonance condition is extremely sensitive to the refractive index of the sample in contact (around 200 nm) with the metal surface, because the optical electric fields are localized within 250 nm from the gold surface. The resonance conditions are influenced by the bio-molecules immobilized on the gold layer. Thus, adsorption of bio-molecules (antigen or antibody) on the metallic film, any followed conformational changes of the adsorbed bio-molecules (or subsequent modification) and molecular interactions with relevant substances can be accurately detected. When a surface immobilized antibody binds with an analyte, the change in the interfacial refractive index can be detected as a shift in the resonance angle. These changes are monitored over time and converted into a sensorgram, from which the kinetics and affinity constants of the interaction can be determined. The resonance angle shift can provide information on the amount of bound analyte, the affinity of analyte for the antibody and the association (or dissociation) kinetics between the antibody and analyte. Microfluidic systems are important in bringing antibody or antigen solutions over the gold surface. Since the SPR signal is highly sensitive to the structure, configuration and reactivity of the surface-immobilized species, a slight change in any of these properties will be transformed into an SPR signal in real-time. Thus, the use of a uniform, well-regulated microfluidic component is necessary
Immunochemical and Receptor Technologies
113
in studying the bio-molecular association/dissociation reactions with precise kinetic information and/or configuration changes. SPR offers the following advantages compared to other transduction techniques for application as a high throughput tool in food analysis: SPR does not require labeling of the reagents. SPR analyzers are capable of producing continuous real time responses to biomolecular interactions occurring at the interface. This will lead to rapid evaluation of the analytical systems. Sensor surface can be regenerated for repeated multiple use. The SPR instrumentation is feasible for miniaturization and multispot detecting, which is highly useful in the fabrication of portable sensors. By combining the advantages of the specificity of the biorecognition reactions, the SPR immunosensor could be developed for detecting any analyte with error-free measurements. In addition to these advantages, the main limitations should also be mentioned: Specificity: A high cross-reactivity with interfering substances can be produced, if density and the compact degree of the monolayer immobilizing the sensing element is not the optimal one. The percentage of cross-reactivity of this type of immunoassay is also directly linked to the specificity of immunoreagents involved. Interferences: The SPR sensors are sensitive to any effect that produces a variation in the refractive index, fluctuations of temperature, or different composition of the samples. In the detection of various small-molecular organic compounds related to food quality, SPR immunosensors based on the indirect competitive immunoreaction principle were predominantly applied. Some examples of immunosensors reported for food analysis are summarized in Table 3. Different applications have been published for aflatoxins control [113,114], and pesticides residues in water and food [115,116]. Some applications of SPR immunosensors have been developed for the food quality control, such as the casein content in milk products [117], for food adulteration control [118], for the detection of genetically modified organisms (GMO) [119] and for the detection of pathogens in food and water [120–123], for example, a prototype SPR analyzer developed by Homola et al. [124] showed good stability and high sensitivity in the determination of the microbe, Staphylococcal enterotoxin B. Some examples of immunosensors reported for food analysis are summarized in Table 3.
6. BIOMIMICS: MOLECULARLY IMPRINTED POLYMERS (MIPS) Due to the frequently poor stability (thermal, pH) and short life times of biological components, synthetic molecules with high affinity properties, similar
Type and basis
Mycotoxins Aflatoxins Aflatoxins Deoxynivalenol Fumonisin B1 Ochratoxin A
Pesticides
Direct immunoassay and fluorometric detection Indirect assay and SPR Indirect assay and SPR Direct assay and SPR detection Inhibition assay and SPR detection
Inhibition assay and SPR detection Inhibition assay and surface refractive index change detection Flow-through amperometric immunosensor based on peroxidase chip and enzyme channeling system Competitive immunoassays and fluorescence detection
Triazines Triazines
Triazines
Indirect assay and TIR-fluorescence detection Competitive immunoreaction and potentiometric detection
Isoproturon Simazine
Pesticides and herbicides Atrazine Inhibition assay and electrochemical detection Atrazine Inhibition assay and optical detection Atrazine Indirect assay and TIR-fluorescence detection Atrazine Indirect assay and SPR Carbaril Indirect assay and SPR Chlorsulfuron Competitive assay and amperometric detection
Analyte
Table 3 Examples of immunosensors for food contaminants analysis
1 ng/L
Aqueous solution
Aqueous solution Food Grain Aqueous solution Liquid food samples
2.5 mg/L 15 mg/mL 5 ng/mL
0.01 mg/L
[130] [131]
0.16 mg/L 15 mg/mL
Aqueous solution
[129] [34]
0.01–0.14 mg/L 3 ng/mL
[134] [60,61] [129] [135] [136]
[133]
[132]
[125] [126] [127] [63] [62] [128]
Reference
0.03 mg/L 1–10 mg/L 0.06–0.2 mg/L 20 ng/L 1.38 mg/L 0.01 ng/mL
Sensitivity
Water Water Water Water Water Aqueous solution water Water Meat extract, milk, tomatoes, cucumbers, potatoes Water Water
Matrix
114 Marinel la Farre´ et al.
Shellfish Shellfish Food and drinking water Food Food Aqueous suspension
Indirect inhibition assay and SPR detection Sandwich assay format and Biosensor arrays
Indirect inhibition assay and SPR Indirect inhibition assay and SPR Recombinant antibodies
QCM SPR Anti E. coli covalently immobilized to Biodyne membrane and amperometric detection
Enterotoxin B Botulinum toxoid A
Domoic acid Domoic acid Cyanobacter hepatotoxins microcystins E. coli enterotoxin E. coli enterotoxin E. coli O157:H7
Food Tomatoes, sweet corn, green beans, mushrooms and tuna
Biosensor arrays
Tomatoes, sweet corn, green beans, mushrooms and tuna
Enterotoxin B
Food borne microorganisms and bacterial toxins Staphylococcal Sandwich assay format
35 pM 70 pM 100 cells/mL
Tomato juice (buffered) 20 Whole tomatoes 50 Mushrooms 100 Sweet corn 50 Sweet corn juice 50 Green beans 250 Green bean juice 100 Tuna 500 0.5–150 ng/L 2–3.3 mg/L
Whole tomatoes 0.1 ng/ml Mushrooms 0.5 ng/ml Sweet corn 0.5 ng/ml Green beans 0.5 ng/ml Tuna 0.5 ng/ml
Tomato juice (buffered) 0.1 ng/ml
[142] [143] [144]
[139] [140] [141]
[71] [138]
[137]
Immunochemical and Receptor Technologies
115
Staphylococcal enterotoxin A Staphylococcal enterotoxin B Staphylococcal enterotoxin B Clostridium botulinum toxins A, B, E and F C. jejuni
S. typhimurium
Milk Food Food
Food
Sandwich assay and SPR
Automated fibre optic
Paramagnetic bead-based electrochemiluminescence
Array Biosensor; Sandwich immunoassay
[151]
[150]
50 pg/ml for serotype A [152] to 50–100 pg/ml for serotypes B, E and F Yogurt 1880 [153] Milk 469 Ground turkey sausage 469 Ground turkey ham 3750
0.5 ng/mL
[64]
[149]
1.106 cfu/mL
Aqueous suspension
10 ng/g
[148]
1.104 cfu/mL
Chicken carcass wash fluid
Food
[146] [147]
[145]
Reference
1 ng/ml
3-30 cfu/mL
Sensitivity
Milk, mushrooms Food
Beef
Matrix
Anti-Salmonella antibody covalently bound to sensor surface refractive index change detection Anti-Salmonella antibody adsorbed to gold electrode QCR detection Sandwich assay and evanescent wave detection
Anti E. coli immobilized in a fibre optic and fluorescence detection SPR sensor chip-MALDI-TOF detection Array biosensor
E. coli O157:H7
Enterotoxin B Pathogens (Campylobacter jejuni) and mycotoxins Salmonella typhimurium
Type and basis
Analyte
Table 3 (Continued )
116 Marinel la Farre´ et al.
Sulphamethazine Sulphamethazine Sulphamethazine Sulphamethazine
Ciprofloxacine Enterofloxacine Penicillin and its derivatives Sulphadiazine
Antibiotics Chloramphenicol Chloramphenicol
Inhibition assay based on indirect immobilization of sulphamethazine to a sensor chip and SPR detection Inhibition assay and SPR detection Inhibition assay and SPR detection Inhibition assay and SPR detection Inhibition assay based on indirect immobilization of Sulphamethazine to a sensor chip and SPR detection
Inhibition assay and SPR detection Label-free detection, quartz crystal microbalance measurement Inhibition assay and SPR detection Inhibition assay and SPR detection SPR, direct inhibition assay [154] [154] [156] [157]
[158] [159] [160] [161]
1.5 mg/Kg 1.5 mg/Kg 2 mg/Kg 0.02 mg/mL
1 mg/L 1.7 mg/Kg 1 mg/Kg 0.5 mg/Kg
Milk Milk Milk Pig bile
Milk Milk Milk Milk
[154] [155]
1 ng/mL 5 106 M
Milk
Immunochemical and Receptor Technologies
117
118
Marinel la Farre´ et al.
to biological ones, are being introduced. One of the most promising groups of biomimetic materials are molecularly imprinted polymers (MIPs). MIPs are a class of highly cross-linked polymer-based molecular recognition elements engineered to bind a single target compound or a class of structurally related compounds with high selectivity. By engineering both the binding site and the polymer backbone a wide range of optimized separation phases can be produced. Selectivity is introduced during MIP synthesis in which a template molecule, designed to mimic the analyte, guides the formation of specific cavities or imprints that are sterically and chemically complementary to the desired target analyte(s). Non-covalent imprinting, in particular, has a great range of applications because of the theoretical lack of restrictions on size, shape or chemical character of the imprinted molecule. The possibility of tailor-made, highly selective receptors at low cost, with good mechanical, thermal and chemical properties makes these polymers appear ideal chemoreceptors. There are great hopes for development of a new generation of chemical sensors using these novel synthetic materials as recognition elements [128,162]. The selected ligand or print molecule is first allowed to establish bond formations with polymerizable functionalities, and the resulting complexes or adducts are subsequently copolymerized with cross-linkers into a rigid polymer. Following the extraction of the print molecule, specific recognition sites are left in the polymer, where the spatial arrangement of the complementary functional entities of the polymer network together with the shape image corresponding to the imprinted molecule. Molecular imprinted polymers can be prepared by self-assembly, where the prearrangement between the ligand and the functional monomers is formed by non-covalent bond, or metal coordination interactions; or by a preorganized approach, where the aggregates in solution prior to polymerization are maintained by reversible covalent bonds. By use of a high percentage of crosslinker, polymers of substantial rigidity and complete insolubility are obtained. MIPs allow for selective extraction of low levels of target compounds in the presence of a mixture of potentially interfering matrix components. Compared to biological receptors, MIP polymer recognition systems have the advantage of superior chemical and mechanical stability being compatible with most solvents, pressures and pH conditions. The materials can be engineered for an almost unlimited variety of small molecules, such as drugs, natural products, pharmaceuticals, peptides and other types of molecules. The main characteristics of these materials is their resistant, mechanical stress, high temperatures and pressures, resistant against treatment with acid, base, or metal ions, stability in a wide range of solvents, and can be used repeatedly.
6.1 MIPs in preparation/preconcentration and separative applications MIPs are recognition elements that have been successfully applied in analytical chemistry as an alternative to immunoaffinity systems. They have been applied in affinity chromatography, binding assays and sensor developments.
Immunochemical and Receptor Technologies
119
The past decade is characterized by the transition of molecular imprinting techniques from a predominantly theoretical research to practical analytical applications. The first application of MIPs was as stationary phases in affinity chromatography, in particular for the enantio separation of racemic mixtures of chiral compounds, and much of the early work on MIPs was devoted to this aspect. Capillary electrochromatography (CEC) is a hybrid separation method that couples the high separation efficiency of capillary zone electrophoresis (CZE) with liquid chromatography, and uses an electric field rather than hydraulic pressure to propel the mobile phase through a packed bed. Since there is no back pressure it is possible to use small diameter packing and thereby achieve very high efficiencies. CEC might be one of the more promising chromatographic techniques to be used in combination with MIPs, in particular for chiral separations. MIP-based CEC profits from the inherent separation power of this method; compared with MIP-based HPLC, appreciable more resolution can be achieved. One of the most studied areas of application was preparation/preconcentration techniques. Sellergren in 1994 [163] published one of the first relevant works on MIP-based solid-phase extraction (SPE), since then a new window was open, and intensive labor of development have been carried out on molecularly imprinted solid-phase extraction (MISPE). The potential advantages of this technique compared to conventional SPE sorbents are the specificity, batch reproducibility, can be regenerated and cost-effective synthesis. Due to these reasons, during previous years the potential of MIPs application for SPE materials has been thoroughly investigated culminating in the commercial availability of MIP-based SPE cartridges by companies, such as ELIPSA (Germany) [164] and MIP Technologies (Sweden) [165]. However, some limitations of these new SPE materials have also been reported [166] such as diminution of recovery percentage after repetitive regenerations. For food analysis some relevant contributions have been done using MISPE in different areas, such as the analysis of flavones in wine [167,168], or in food toxicant analysis. Main applications in food toxicants analysis have been carried out in three specific areas: Residues of pharmaceutical compounds (antibiotics, b-agonists) Microbial pathogens and mycotoxins Residues of pesticides. The class selective MIP SPE-b-agonists has shown to be a valuable tool in screening and quantitative determination of b-agonists in muscle tissue from several kinds of animals [169]. The extraction of mycotoxins demonstrates the versatility of MIPs even for more complex natural compounds such as deoxynivalenol and zearelenone [148], or OTA [138]. A high sensitivity (0.05–0.2 mg/L) method was developed for the analysis of chlorotriazine in environmental samples by Ferrer and Barcelo´ [170].
120
Table 4
Marinel la Farre´ et al.
Applications of MIPs for SPE and packing column materials for food analysis
Analyte
Analysis format
Functional monomer
Reference
(+)-Catechin 4-Nitrophenol Chloramfenicol Chloro triazines Clembuterol
MIP-based SPE MIP-based SPE MIP-based SPE MIP-based SPE MIP-packed HPLC column MIP-based SPE Polymeric microcapsules MIP-based SPE MIP-based SPE MIP-based SPE MIP-based SPE MIP-packed HPLC column MIP-based SPE MIP-based SPE MIP-based SPE On-line MIP-based SPE RAM-MIP-SPE MIP-based SPE
EDMA 4-VP NS
[171] [172] [173] [174] [175]
Flavonoids Listeria monocytogenes Micotoxins Microsystin-LR Ochratoxin A Ochratoxin A Penicillin V, Penicillin G, Oxacillin Propazine Simazine b-blockers Sulfamethazine Triazines Triazines
MAA
4-VP+EDMA [176] Poly(allilamine) [177]
PAM EDMA MAA+4-VP
MAA MAA+EDMA
[154] [178] [179] [180] [181] [182] [183] [184] [185] [186] [187]
Note: 4-VP, 4-vinylpyridine; EDMA, ethylene glycol dimethacrylate; MAA, methacrylic acid; PAM, N-phenylacrylamide; DEAEM, diethylamino ethyl methacrylate.
The synthesis, evaluation and comparison of different MIPs based on the use of preformed silica beads, to be used as selective HPLC stationary phases able to recognize and separate several phenylurea herbicides at low concentration levels directly from vegetable sample extracts without any previous clean-up step, have been reported by Tamayo and Martin-Esteban [143]. A clembuterol-selective MISPE cartridge has been released by MIP Technologies, for detection of trace concentrations of this illegal growth promoter in meat products. Recently, membranes become increasingly attractive materials for efficient affinity separations [188]. Some examples of reported applications of MIPs for SPE and packing column materials are shown in Table 4.
6.2 Development and application of MIP-based sensors During the past decade the number of application of MIP-based sensors has increased drastically.
Immunochemical and Receptor Technologies
121
The high selectivity and affinity properties of MIP for target analytes make them ideal recognition elements in sensors development [63]. Capacitive [189], conductimetric [190], field effect [191], amperometric [192] and voltammetric [193] electrochemical transduction systems have been used. On the basis of conductimetric transduction by Piletsky et al. [190] sensors for herbicide analysis have been developed with a linear range of 0.01–0.50 mg/L for atrazine, without interference of simazine. Chloroaromatic acids were determined by Lahav et al. [191] using a TiO2 sol-gel system, and using a voltammetric transduction Pizzariello et al. [193] developed a sensor for clembuterol analysis. MIP-based sensors coupled to piezoelectric transducers are one of the most promising areas. Different devices have been developed for their use in food industry, such as a supported-piezoelectric detection based on MIP for the quantification of caffeine content in coffee and tea samples [194], the detection of sorbitol [195], antibiotics in milk [174], and the detection of toxicant compound such as PAHs [196]. Another optical transducers reported is a chemiluminescent sensor for clembuterol determination [197]. Applications of MIP-based sensors for contaminant analysis are summarized in Table 5. In spite of the development in this field, MIPs still have a series of limitations: Unless the print-material is inexpensive, their preparation is very costly There is a lack of robustness and sensitivity, due to inefficient removal of the print molecules during MIP preparation Several times there is a lack of reproducibility General MIP preparation procedures are adequate at the laboratory level, and now these preparation procedures need to be developed for scaling up to commercial production. Table 5
Examples of MIP-based sensors for food toxicant analysis
Analyte
Functional monomer
Transduction
Reference
o-Xilene 2,4-Dichlorophenoxyacetic-acid
NS 4-VP
[198] [199]
Atrazine
MAA+EDMA
QCM Electrochemical detection using screen printed electrodes Amperometric detection Conductimetric sensor
Trichloroacetic acid 4-VP+EDMA and haloacetic acids Domoic acid 2-(Diethylamino) ethyl methacrylate Ochratoxin A Polypyrrole film Sulphamethazine MAA Caffeine MAA+EDMA Note: PQC, piezoelectric quartz.
[200] [201]
SPR-QCM
[202]
SPR (SPREETA) Voltammetric BAW
[203] [204] [140]
122
Marinel la Farre´ et al.
However, new polymeric strategies have been proposed in order to overcome these limitations. For example, Jodlbauer et al. [138] reported the development of an OTA-selective MIP material, specifically designed to recognize and bind OTA under polar protic conditions, using as a functional monomer Q-MMA, auxiliary monomer tBu-MAA and the OTA-mimicking template. Recently, Maier et al. [180] reported the application of this material for the investigation of OTA in red wines using a two-dimensional SPE clean-up protocol on C18-silica and a target-selective MIP. The combined protocol afforded extracts suitable for sensitive OTA quantification by HPLC-fluorescence detection. In this study, problems inherent to MIP-based SPE have been addressed including the reproducible preparation of MIP materials with consistent molecular recognition characteristics, the potential for repeated use of MIP, unfavourable polymer swelling in application-relevant solvents, potential sample contamination by template bleeding and slow analyte binding kinetics.
7. COMMERCIAL INSTRUMENTATION AND FUTURE PERSPECTIVES The majority of reported biosensor research has been directed towards the development of devices for clinical markets; however, driven by the need for better methods for food surveillance, research into this technology is also expanding to encompass food applications. Table 6 shows some examples of commercial biosensor instrumentation available for toxic compounds and pathogens analysis in food. A number of instruments for food analysis are already commercially available. However, the commercial success of biosensors is limited to a small number of applications, where the market size justified more research, validation and development investment. These commercial devices are focused on few applications, such as the determination of saccharides (YSI), or the detection of bacterial toxins or pathogens (Research International). The future commercial status and general acceptance of this technology will depend on the performance characteristics, sample throughput, associated costs, validation and acceptance by regulatory authorities. A variety of laboratory prototype biosensors have been reported which measure a fairly broad spectrum of food contaminants and residues. Immunoassays traditionally have been used as a single-analyte method, which has often been considered a limitation of the technology. However, several approaches are possible to overcome this limitation. An approach is to use a compact disk (CD)-based microarray system [139]. A microdot system was developed that utilized inkjet technology to print microdots on a CD. The CD was the solid phase for the immunoassay, and laser optics were used to detect the near-infrared fluorescent label. The advantage of the CD system is the ability both to conduct assays and to record and/or read data from the same CD. Since the surface of a single CD can hold thousands of dots, thousands of analyses can be made on a single sample simultaneously. Such high-density analyses could lead to environmental tasters where arrays of immunosensors are placed on Chips [205] or high-density plates. Because the CD
Direct measurement of molecular locking and DNA-hybridization
Generic sensor for studding binding interactions with low molecular weight molecules Hormones, vitamins, mycotoxins, antibiotics, low weight molecules
ANDREA
Autolab SPR SPRIT
Generic sensor for studding binding interactions with low molecular weight molecules Staphylococcal enterotoxin B, Bacillus anthracis, Yersinia pesti, micotoxins, spores Generic sensor for studding binding interactions with low molecular weight molecules
MORITEX, SPR-670M
SPREETAt
RAPTORt
Generic sensor for studding binding interactions with low molecular weight molecules
IBIS
Generic sensor for studding binding interactions with low molecular weight molecules
Staphylococcal enterotoxin B, Escherichia coli O157:H7, spores
Analyte 2000t
BIAcore (1000, 2000, 3000, Q, A100, Flexchip) FasTraQ is a biosensor
Analyte
Commercial devices
Name
Table 6
Miniaturized SPR affinity based biosensor
Portable fluoroimmuno biosensor
SPR affinity based biosensor
SPR affinity based biosensor
SPR affinity based biosensor
SPR affinity based biosensor
4-Channel, single wavelength fluorometer optimized for performing evanescent-wave fluoroimmunoassays The measurement of antibody– antigen reactions is done by a new technique on the basis of ellipsometry. Ellipsometry is an optical method, which simply measures the state of polarization of light that is reflected from a substrate. SPR affinity based biosensor
Description
Research International, 18706 142bd Ave, N.E., Woodinville, WA, 98072, USA (www.resrchintl.com) Texas Instruments Inc., 12500 TI Boulevard, Dallas, TX, 75243-4136, USA. (www.ti.com)
QUANTECH LTD, 815 Northwest Parkway, Suite 100, Eagan, MN, 55121, USA (http://www.quantechltd.com/) Windsor Scientific Limited, 264 Argyll Avenue, Slough Trading Estate, Slough, Berkshire SL1 4HE, United Kingdom. (www.windsor-ltd.co.uk) Moritex Inc., Japan (www.moritex.co.jp)
BIAcore AB, Rapsgatan 7, Uppsala, Sweden (www.biacore.com)
Windsor scientific (http://www.ecochemie.nl/)
DRE — Dr. Riss Ellipsometerbau GmbH, Feldstr. 14 D-23909, Ratzeburg, Germany (www.dre.de)
Research International, 18706 142bd Ave, N.E., Woodinville, WA, 98072, USA (www.resrchintl.com)
Company
Immunochemical and Receptor Technologies
123
124
Marinel la Farre´ et al.
format has the potential for high-density analyses, there will be the opportunity for easily generating multiple replicates of the same sample, including more calibration standards, thus improving data quality. The development of class-selective antibodies is another approach to multianalyte analysis. The analyst may design haptens that will generate antibodies that recognize an epitope common to several compounds. Examples of classselective immunoassays that have been developed are mercapturates [206], glucuronides [207], pyrethroids [208], organophosphate insecticides [209] and benzoylphenylurea insecticides [210]. Rather than have one antibody that can detect a class, a third approach is to analyse a sample using multiple immunoassays, each with a known crossreactivity spectrum, and determine the concentration of the analytes and confidence limits mathematically [211]. A drawback to using class-selective assays or assays with known cross-reactivity is that for a given antibody, the sensitivity for each analyte vary, and the sensitivity for some analytes may not be sufficient, hence selection of well-characterized antibodies will be a critical step. Some of the other important keys in the future of immunoassays and immunosensors development are to allow more stability of biological components, more robustness assays, more repeatability between different batches of production when disposable elements are involved, and the integration of new technologies coupled to biosensors, such as the PCR. On the other hand, there are at least two other developments that are expected to have significant impact, the laboratory on a chip (LOC) [212] and nanotechnology [213]. The concept of LOC entails miniaturization of all the essential components of analytical instrumentation (e.g., sample preparation, components, reaction with appropriate reagents and detection) by micro fabrication on a chip. Some of the components in LOC technology have already been released on the market (GeneChips from Affimatrix). Nanotechnology refers to the exploitation of processes to generate and utilize structures, components and devices with a size range from 0.1 nm (atomic and molecular scale) to 100 nm or larger in some cases, by control at atomic, molecular and macromolecular levels. It has been suggested that nanoscale sensors and ultra miniaturized sensors could lead to the next generation of biotechnology-based industries. There are several companies manufacturing SPR instruments for studying bio-molecular interactions [214,215]. Each company produces different SPR systems equipped with a variety of options usable for specific applications. Some of these companies are Biacore, SENSIA, Windsor scientific, Quantech, Texas, NTT and Moritex (formerly, Nippon Laser and Electronics). SPR instruments from Biacore have been widely used by the sensor researchers around the world. Finally, among the variety of biomimetic recognition schemes utilizing supramolecular approaches MIPs have proven their potential as synthetic receptors in numerous applications, and their advantages compared to biochemical recognition systems include thermal stability, storage endurance and lower costs. In particular, the areas of, food and beverage analysis require analytical tools capable of discriminating chemicals with high molecular specificity. Furthermore, food and process safety control issues favour the application of on-line in situ
Immunochemical and Receptor Technologies
125
analytical methods with high molecular selectivity. While biorecognition schemes frequently suffer from degrading bioactivity and long-term stability when applied in real-world sample environments, MIPs serving as synthetic antibodies have successfully been applied as stationary phase separation matrix, and biomimetic recognition layer in chemical sensor systems. Current research demonstrates the progression of MIP chemistry and the potential of these materials to solving a wide variety of food analytical problems. The combination of MIPs with a range of transducers to produce on line and real time sensors is expected, and their potential has been demonstrated, but limitations described previously should be addressed. The majority of applications of MIPs are directed to low molecular weight, organic soluble analytes of interest in the pharmaceutical industry (e.g., chiral drug separation), but new applications have been developed in environment and food industry. Several new approaches to MIP production (e.g., surface imprinting) are expected to allow MIPs to be prepared in aqueous media. Other new approaches in development are Magnetic MIPs and Cathalytic MIPs (also referred to as enzyme mimics or plastizyme).
REFERENCES 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
C.A. Spinks, Trends Food Sci. Technol., 11 (2000) 210. J.H. Skerritt and N. Lee, ACS Symposium Series Book, 1996, p. 621. B.D. Hammock and R.O. Mumma, ACS Symposium Series Book, 1980, p. 136. B.F. Erlanger, F. Borek, S.M. Beiser and S. Lieberman, J. Biol. Chem., 234 (1959) 1090. M.H. Goodrow, R.O. Harrison and B.D. Hammock, J. Agric. Food Chem., 38 (1990) 990. A.F.S.A. Habeeb, Anal. Biochem., 14 (1966) 328. I. Wengatz, R.D. Schmid, S. Kreissig, C. Wittmann, B. Hock, A. Ingendoh and F. Hellenkamp, Anal. Lett., 25 (1992) 1983. A.M. Campbell, Monoclonal antibody and immunosensor technology: The production and application of rodent and human monoclonal antibodies, Elsevier, Amsterdam, 1991. J.W. Goding, Monoclonal antibodies: Principles and practice. Production and application of monoclonal antibodies in cell biology, biochemistry and immunology, Academic Press, London, 1996. B. Hock, Acta Hydrochim. Hydrobiol., 29 (2002) 375. K. Krame and B. Hock, Anal. Bioanal. Chem., 377 (2003) 417. M. Franek, J. Steroid Biochem., 28 (1987) 95. A. Pluckthun and A. Skerra, Methods Enzymol., 178 (1989) 497. E. Harlow and D. Lane, Antibodies: A laboratory manual, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY, 1988. R. Galve, F. Camps, F. Sanchez-Baeza and M.-P. Marco, Anal. Chem., 72 (2000) 2237. L. Bruun, C. Koch, M.H. Jakobsen and J. Aamand, Anal. Chim. Acta, 423 (2000) 205. M. Garce´s-Garcı´a, E.M. Brun, R. Puchades and A. Maquieira, Anal. Chim. Acta, 556 (2006) 347. G.S. Nunes, M.-P. Marco, M. Farre and D. Barcelo, Anal. Chim. Acta, 387 (1999) 245. H.Y. Shen and H.L. Jiang, Anal. Chim. Acta, 535 (2005) 33. J.K. Lee, K.C. Ahn, O.S. Park, Y.K. Ko and D.-W. Kim, J. Agric. Food Chem., 50, 1791 (2002) 209. S. Sadakane, T. Sakai, A. Hayashi and H. Ohkawa, J. Pestic. Sci., 23 (1998) 410. E.V. Yazynina, A.V. Zherdev, S.A. Eremin, V.A. Popova and B.B. Dzantiev, Appl. Biochem. Microbiol., 38 (2002) 225. S.R. Webb and J.C. Hall, J. Agric. Food Chem., 48 (2000) 1210. S.R. Webb and J.C. Hall, J. AOAC Int., 84 (2001) 143.
126
Marinel la Farre´ et al.
25 L. Bruun, C. Koch, B. Pedersen, M.H. Jakobsen and J. Aamand, J. Immunol. Methods, 240 (2000) 133. 26 A. Navas-Diaz, F. Garcia-Sanchez, J. Lovillo and J.A. Gonzalez-Garcia, Anal. Chim. Acta, 321 (1996) 219. 27 M.W. Shankle, D.R. Shaw and M. Boyette, Weed Technol., 15 (2001) 669. 28 R.J. Bushway and B.S. Ferguson, BCPC Symp. Proc., 65 (1996) 317. 29 S. Ben-Rejeb, N. Fischer-Durand, A. Martel, F. Le Goffic, J.F. Lawrence, J.M. Yeung and M.A. Abbott, Int. J. Environ. Anal. Chem., 69 (1998) 13. 30 E. Simon, D. Knopp, P.B. Carrasco and R. Niessner, Food Agric. Immunol., 10 (1998) 105. 31 A.I. Krasnova, S.A. Eremin, M. Natangelo, S. Tavazzi and E. Benfenati, Anal. Lett., 34 (2001) 2285. 32 J. Leszczynska, J. Maslowska and A. Owczarek, Pol. J. Food Nutr. Sci., 7 (1998) 733. 33 G. Hegedus, I. Belai and A. Szekacs, Anal. Chim. Acta, 421 (2000) 121. 34 M.F. Yulaev, R.A. Sitdikov, N.M. Dmitrieva, E.V. Yazynina, V. Zherdev and B.B. Dzantiev, Sens. Actuator. B, 75 (2001) 129. 35 S. Pullen and B. Hock, Anal. Lett., 28 (1995) 765. 36 K. Hemalatha, N.B.K. Venugopal and B.S. Rao, J. AOAC Int., 84 (2001) 1001. 37 W.T. Jones, D. Harvey, S.D. Jones, G.B. Ryan, H. Wynberg, W. Ten Hoeve and P.H.S. Reynolds, Food Agric. Immunol., 7 (1995) 9. 38 J.V. Mercader and A. Montoya, J. Agric. Food Chem., 47 (1999) 1285. 39 M.J. Moreno, A. Abad, R. Pelegri, M.J. Martinez, A. Saez, M. Gamon and A. Montoya, J. Agric. Food Chem., 49 (2001) 1713. 40 J.J. Manclus, J. Primo and A. Montoya, J. Agric. Food Chem., 44 (1996) 4052. 41 B. Mickova, L. Karasova, L. Fukal, I. Hochel, P. Rauch, P. Gregor, J. Hajslova, F. Fini, S. Girotti, A. Abad, J.J. Manclus, J.V. Mercader and A. Montoya, Czech J. Food Sci., 18 (2000) 266. 42 G. Shan, D.W. Stoutamire, I. Wengatz, S.J. Gee and B.D. Hammock, J. Agric. Food Chem., 47 (1999) 2145. 43 E. Watanabe, Y. Kanzaki, H. Tokumoto, R. Hoshino, H. Kubo and H. Nakazawa, J. Agric. Food Chem., 50 (2002) 53. 44 M. Nakata, A. Fukushima and H. Ohkawa, Pestic. Manage. Sci., 57 (2001) 269. 45 K. Li and Q.X. Li, J. Agric. Food Chem., 48 (2000) 3378. 46 M.J.C. Alcocer, P.P. Dillon, B.M. Manning, C. Doyen, H.A. Lee, S.J. Daly, R. O’Kennedy and M.R.A. Morgan, J. Agric. Food Chem., 48 (2000) 2228. 47 M.J. Kim, J.Y. Shim, Y.T. Lee and H.-S. Lee, Int. J. Food Sci. Technol., 41 (2006) 927–932. 48 S. Miyake, K. Morimune, Y. Yamaguchi, K. Ohde, M. Kawata, S. Takewaki and Y. Yuasa, Int. J. Food Sci. Technol., 25 (2000) 10. 49 S. Oepkemeier, S. Schreiber, D. Breuer, G. Key and W. Kleibohmer, Anal. Chim. Acta, 393 (1999) 103. 50 P. Wyss, M. Bolsinger and C. Pfister, Anal. Lett., 29 (1996) 2363. 51 W.A. Matthews and M. Haverly, Food Agric. Immunol., 7 (1995) 153. 52 D.L. Young, C.A. Mihaliak, S.D. West, K.A. Hanselman, R.A. Collins, A.M. Phillips and C.K. Robb, J. Agric. Food Chem., 48 (2000) 5146. 53 G. Giraudi, I. Rosso, C. Baggiani, C. Giovannoli, A. Vanni and G. Grassi, Anal. Chim. Acta, 392 (1999) 85. 54 J.A. Itak, M.Y. Selisker, D.P. Herzog, J.R. Fleeker, E.R. Bogus and R.O. Mumma, J. AOAC Int., 77 (1994) 86. 55 T.S. Lawruk, A.M. Gueco, S.W. Jourdan, A.M. Scutellaro, J.R. Fleeker, D.P. Herzog and F.M. Rubio, J. Agric. Food Chem., 43 (1995) 1413. 56 C. Jahn and W. Schwack, J. Agric. Food Chem., 49 (2001) 1233. 57 E. Watanabe, S. Watanabe, S. Ito, M. Hayashi, T. Watanabe, Y. Yuasa and H. Nakazawa, J. Agric. Food Chem., 48 (2000) 5124. 58 A. Szekacs, A. Cairoli, H.M. Le and S. Pagani, Acta Phytopathol. Entomol. Hung., 31 (1996) 293. 59 A.R. Fernandez-Alba, A. Valverde, A. Agueera, M. Contreras and D. Rodriguez, Anal. Chim. Acta, 311 (1995) 371. 60 C. Danks, M.Q. Chaudhry, L. Parker, I. Barker and J.N. Banks, Food Agric. Immunol., 13 (2001) 151.
Immunochemical and Receptor Technologies
127
61 A. Abad, J.J. Manclus, M.J. Moreno and A. Montoya, J. AOAC Int., 84 (2001) 156. 62 A.L. Queffelec, F. Boisde, J.P. Larue, J.P. Haelters, B. Corbel, D. Thouvenot and P. Nodet, J. Agric. Food Chem., 49 (2001) 1675. 63 E.M.G. Loomans, J. van Wiltenburg, M. Koets and A. van Amerongen, J. Agric. Food Chem., 51 (2003) 587. 64 L. Rasooly and A. Rasooly, Int. J. Food Microbiol., 49 (1999) 119. 65 K. De Wasch, L. Okerman, S. Croubels, H. De Brabander, J. Van Hoof and P. De Backer, Analyst, 123 (1998) 2737. 66 J.V. Samsonova, M.L. Bashkurov, N.L. Ivanova, M.Y. Rubtsova and A.M. Egorov, Food Agric. Immunol., 16 (2005) 47. 67 K. Kumar, A. Thompson, A.K. Singh, Y. Chander and S.C. Gupta, J. Environ. Qual., 33 (2004) 250. 68 C. Situ and C.T. Elliot, Anal. Chim. Acta, 33 (2005) 89. 69 A.G. Gehring, D.M. Albin, P.L. Irwin, S.A. Reed and S.I. Tu, J. Microbiol. Met., 67 (2006) 527. 70 D.E. Hill, S. Chirukandoth, J.P. Dubey and J.K. Lunney, Vet. Parasitol., 141 (2006) 9. 71 M. Blazkova, L. Karamonova, M. Greifova, L. Fukal, I. Hoza, P. Rauch and G. Wyatt, Eur. Food Res. Technol., 223 (2006) 821. 72 S. Wang, Y. Quan, N. Lee and I.R. Kennedy, J. Agric. Food Chem., 54 (2006) 2491. 73 B.J. Xu, X.J.L. Gu and C.K. Sung, Food Control, 17 (2006) 271. 74 H. Watanabe, A. Satake, M. Matsumoto, Y. Kido, A. Tsuji, K. Ito and M. Maeda, Analyst, 123 (1998) 2573. 75 D.L. Park, S. Coates, V.-A. Brewer, E.A.E. Garber, M. Abouzied, K. Johnson, B. Ritter and D. McKenzie, J. AOAC Int., 88 (2005) 156. 76 M.J. Kim, J.Y. Shim, Y.T. Lee and H.S. Lee, Int. J. Food Sci. Technol., 41 (2006) 927. 77 J.Z. Su-Ping He, W. Liu, A.X. Deng, T.G. Nan, B.M. Wang, Z.X. Zhai and Z.H. Li, Food Agric. Immunol., 17 (2006) 173. 78 Y.A. Cho, Y.J. Kim, B.D. Hammock, Y.T. Lee and H.S. Lee, J. Agric. Food Chem., 51 (2003) 7854. 79 S.K. Sharma, B.S. Eblen, R.L. Bull, D.H. Burr and R.C. Whiting, Appl. Environ. Microbiol., 71 (2005) 3935. 80 V. Lopez-Avila, R. Young and W.F. Beckert, Anal. Chem., 66 (1994) 1097. 81 L. Urruty, M. Montuty, M. Braci, J. Fournier and J.M. Dournell, J. Agric. Food Chem., 45 (1997) 1519. 82 A.Y. Kolosova, J.H. Park, S.A. Eremin, S.J. Kang and D.H. Chung, J. Agric. Food Chem., 51 (2003) 1107. 83 W.B. Shim, A.Y. Kolosova, Y.J. Kim, Z.Y. Yang, S.J. Park, S.A. Eremin, I.S. Lee and D.H. Chung, Int. J. Food Sci. Technol., 39 (2004) 829. 84 N. Fischer-Durand, A. Vessieres, J.M. Heldt, F. le Bideau and G. Jaouen, J. Organometal. Chem., 668 (2003) 59. 85 M. Wortberg, C. Middendorf, A. Katerkamp, T. Rump, J. Krause and K. Cammann, Anal. Chim. Acta, 289 (1994) 177. 86 P.M. Kramer, A. Franke and C. Standfuss-Gabisch, Anal. Chim. Acta, 399 (1999) 89. 87 I. Ferrer, V. Pichon, M.C. Hennion and D. Barcelo, J. Chromatogr. A, 777 (1997) 98. 88 M.P. Zhao, Y.Z. Li, Z.Q. Guo, X.X. Zhang and W.B. Chang, J. Chromatogr., 783 (2003) 401. 89 G. Prado, M.S. Oliveira and E. Carvalho, Cieˆnc. Tecnol. Aliment., 23 (2003) 58. 90 K.A. Fahnrich, M. Pravda and G.G. Guilbault, Biosens. Bioelectron., 18 (2003) 73. 91 K. Grennan, G. Strachan, A.J. Porter, A.J. Killard and M.R. Smyth, Anal. Chim. Acta, 500 (2003) 287. 92 S.H. Alarcon, L. Micheli, G. Palleschi and D. Compagnone, Anal. Lett., 37 (2004) 1545. 93 E. Zacco, J. Adrian, R. Galve, M.-P. Marco, S. Alegret and M.I. Pividori, Biosens. Bioelectron., 22 (2007) 2184. 94 G.G. Guilbault, Biosens. Bioelectron., 7 (1992) 411. 95 C. Ruan, K. Zeng, O.K. Varghese and C.A. Grimes, Anal. Chem., 75 (2003) 6494. 96 S. Kurosawa, Meat Sci. Technol., 14 (2003) 1882. 97 F. Liu, X.L. Su and Y. Li, Paper number 067119, 2006, ASAE Annual Meeting. 98 S. Kurosawa, M. Nakamura, J.W. Park, H. Aizawa, K. Yamada and M. Hirata, Biosens. Bioelectron., 20 (2004) 1134.
128
Marinel la Farre´ et al.
99 J.W. Park, S. Kurosawa, H. Aizawa, S. Wakida, S. Yamada and K. Ishihara, Sens. Actuator. B, 91 (2003) 158. 100 F. Liu, X.-L. Su and Y. Li, 2006, ASAE Annual Meeting. 101 E. Mallat, C. Barzen, A. Klotz, A. Brecha, G. Gauglitz and D. Barcelo´, Environ. Sci. Technol., 33 (1999) 965. 102 S. Rodriguez-Mozaz, S. Reder, M. Lopez de Alda, G. Gauglitz and D. Barcelo´, Biosens. Bioelectron., 19 (2004) 633. 103 J. Tschmelak, G. Proll, J. Riedt, J. Kaiser, P. Kraemmer, L. Ba´rzaga, J.S. Wilkinson, P. Hua, J.P. Hole, R. Nudd, M. Jackson, R. Abukneshaf, D. Barcelo´, S. Rodriguez-Mozaz, M.-J. Lo´pez de Alda, F. Sacher, J. Stienh, J. Slobodny´k, P. Oswald, H. Kozmenko, E. Korenkov, L. Tothov, Z. Krascsenits and G. Gauglitz, Biosens. Bioelectron., 20 (2005) 1499. 104 H. Chuang, P. Macuch and M.-B. Tabacco, Anal. Chem., 73 (2001) 462. 105 K.H. Seo, R.E. Brackett, N.F. Hartmann and D.P. Capbell, J. Food Protect., 62 (1999) 431. 106 D.R. DeMarco, E.W. Saaski, D.A. McCrae and D.V. Lim, J. Food Protect., 62 (1999) 711. 107 N. Adanyi, I.A. Levkovets, S. Rodriguez-Gil, A. Ronald d, M. Varadi and I. Szendro, Biosens. Bioelectron., 22 (2007) 797. 108 K.E. Sapsford, A. Rasooly, C.R. Taitt and F.S. Ligler, Anal. Chem., 76 (2004) 433. 109 J. Tschmelak, N. Kappel and G. Gauglitz, Anal. Bioanal. Chem., 382 (2005) 1895. 110 N.D. Kappel, F. Proll and G. Gauglitz, Biosen. Bioelectron., 22 (2007) 2295. 111 E. Kretchmann, Z. Phys., 241 (1971) 313. 112 A. Otto, Z. Phys., 216 (1968) 398. 113 S.J. Daly, G.J. Keating, P.P. Dillon, B.M. Manning, R.O. Kennedy, H.A. Lee and M.R.A. Morgan, J. Agric. Food Chem., 48 (2000) 5097. 114 L. Dunne, S. Daly, A. Baxter, S. Haughey and R.O. Kennedy, Spectrosc. Lett., 38 (2005) 229. 115 E. Mauriz, A. Calle, A. Abad, A. Montoya, A. Hildebrandt, D. Barcelo and L.M. Lechuga, Biosens. Bioelectron., 21 (2006) 2129. 116 M. Farre´, E. Martı´nez, J. Ramo´n, A. Navarro, J. Radjenovic, E. Matriz, L. Lechuga, M.-P. Marco and D. Barcelo´, Anal. Bioanal. Chem., 388 (2007) 207. 117 S. Muller-Renaud, D. Dupond and P. Dulieur, J. Agric. Food Chem., 52 (2004) 659. 118 W. Haasnoot, K. Olieman, G. Cazemier and R. Verheijen, J. Agric. Food Chem., 49 (2001) 5201. 119 G. Ferriotto, M. Borgatti, C. Mischiati, N. Bianchi and R. Gambari, J. Agric. Food Chem., 50 (2002) 955. 120 E. Kaclikova, T. Kuchta, H. Kay and D. Gray, J. Immunol. Met., 46 (2001) 63. 121 J. Haines and P.D. Patel, BIAJ, 2 (1995) 31. 122 B.K. Oh, W. Lee, Y.K. Kim, W.H. Lee and J.W. Choi, J. Biotechnol., 111 (2004) 1. 123 B.K. Oh, Y.K. Kim, Y.M. Bae, W.H. Lee and J.W. Choi, J. Microbiol. Biotechnol., 12 (2002) 780. 124 J. Homola, J. Dostalek, S. Chen, A. Rasooly, S. Jiang and S.S. Yee, Int. J. Food Microbiol., 75 (2002) 61. 125 R.J.M. Fernandez, M. Stiene, R. Kast, M.D. Luque de Castro and U. Bilitewski, Biosens. Bioelectron., 13 (1998) 1107. 126 P. Skladal, Biosens. Bioelectron., 14 (1999) 257. 127 E. Mallat, C. Barzen, R. Abuknesha, G. Gauglitz and D. Barcelo´, Anal. Chim. Acta, 426 (2001) 209. 128 B.B. Dzantiev, E.V. Yazynena, A.V. Zherdev, Y.V. Plekhanova, A.N. Reshetilov, S.-C. Chang and C.J. MxNeil, Sens. Actuator. B, 98 (2004) 254. 129 K. Haupt and K. Mosbach, Chem. Rev., 100 (2000) 2495. 130 R.D. Harris, B.J. Luff, J.S. Wilkinson, J. Piehler, A. Brecht, G. Gauglitz and R.A. Abuknesha, Biosens. Bioelectron., 14 (1999) 377. 131 F.F. Bier, R. Jockers and R.D. Schmid, Analyst, 119 (1994) 437. 132 J. Zeravik, T. Ruzgas and M. Franek, Biosen. Biolelectron., 18 (2003) 1321. 133 J. Tschmelak, G. Proll, J. Ried, J. Kaiser, P. Kraemmer, I. Barzaga, J.S. Wilkinson, P. Hua, J.P. Hole, R. Nudd, M. Jackson, R. Abuknesha, D. Barcelo, S. Rodriguez-Mozaz, M.J. de Alda, F. Sacher, J. Stien, J. Slobodnik, P. Oswald, H. Kozmenko, E. Korenkova, L. Tothova, Z. Krascsenits and G. Gauglitz, Biosen. Bioelectron., 20 (2004) 1509. 134 M.A. Carlson, C.B. Bargeron, R.C. Benson, A.B. Fraser, T.E. Phillips, J.T. Velky, J.D. Groopman, P.T. Strickland and H.W. Ko, Biosens. Bioelectron., 14 (2000) 841.
Immunochemical and Receptor Technologies
135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178
129
W. Mullett, E.P.C. Lai and J.M. Yeung, Anal. Chem., 258 (1998) 161. S. Hauck, C. Kosslinger, S. Drost and H. Wolf, Lebensmittelchemie, 52 (1998) 158. E. Kim, C. Sapsford, C.R. Taitt, N. Loo and F.S. Ligler, Appl. Environ. Microbiol., 71 (2005) 5590. J. Jodlbauer, N.M. Maier and W. Lindner, J. Chromatogr. A, 945 (2002) 45. H. Kido, A. Maquieira and B.D. Hammock, Anal. Chim. Acta, 411 (2000) 1. C. Liang, H. Peng, X. Bao, L. Nie and S. Yao, Analyst, 124 (1999) 1781. J. McElhiney and L. Lawton, Toxicol. Appl. Pharm., 203 (2005) 219. B.D. Spangles, E.A. Wilkinson, J.T. Murphy and B.J. Tyler, Anal. Chim. Acta, 12 (2001) 149. F.G. Tamayo and A. Martin-Esteban, J. Chromatogr. A, 1098 (2005) 116. I. Abdel-Hamid, D. Ivnitski, P. Atanasov and E. Wilkins, Biosens. Bioelectron., 14 (1999) 309. M.A. Carlson, C.B. Bargeron, R.C. Benson, A.B. Fraser, T.E. Phillips, J.T. Velky, J.D. Groopman, P.T. Strickland and H.W. Ko, Biosens. Bioelectron., 14 (2000) 841. D. Nedelkov, A. Rasooly and R.W. Nelson, Int. J. Food Microbiol., 60 (2000) 1. K.E. Sapsford, M.N. Ngundi, M.H. Moore, M.E. Lassman, L.C. Shiver-Lake, C.R. Taitt and F.S. Ligler, Sens. Actuator. B, 113 (2006) 588. R. Weiss, M. Freundenschuss, R. Krska and B. Mizaikoff, Food Add. Contam., 20 (2003) 386. I.S. Park and N. Kim, Biosens. Bioelectron., 13 (1998) 1091. J. Homola, J. Dosta´lek, S. Chen, A. Rasooly, S. Jiang and S.S. Yee, Int. J. Food Microbiol., 75 (2002) 61. K.D. King, G.P. Anderson, K.E. Bullock, M.J. Regina, E.W. Saaski and F.S. Ligler, Biosens. Bioelectron., 14 (1999) 163. V.R. Rivera, F.J. Gamez, W.K. Keener, J.A. White and M.A. Poli, Anal. Biochem., 353 (2006) 248. K.E. Sapsford, M.M. Ngundi, M.H. Moore, M.E. Lassman, C. Shriver-Lake, C.R. Taitt and F.S. Ligler, Sens. Actuator. B, 113 (2006) 599. R. Krska, E. Welzig, F. Berthiller, A. Molinelli and B. Mizaikoff, Food Add. Contam., 22 (2005) 345. N. Ada´nyi, M. Varadi, N. Kim and I. Szendro¨, Cur. Appl. Phys., 6 (2006) 279. G. Cacciatore, M. Petz, S. Rachid, R. Hakenbeck and A.A. Bergwerff, Anal. Chim. Acta, 520 (2004) 105. C.T. Elliot, G.A. Baxter, S.R.H. Crooks and W.J. McCaughey, Food Agric. Immunol., 11 (1999) 19. L. Wahlstrom. In: Proceedings of the 25th International Dairy Congress, Aarhus, September 1998. Volume 2, Dairy Science and Technology, Danish National Committee of the IDF, Aarhus, 1999, p. 344. V. Gaudin and M.L. Pavy, J. AOAC Int., 82 (1999) 1316. M. Stanker (Ed.), Immunoassys for residue analysis, food safety, American Chemical Society, Washington, DC, 1996 M.R.S. Fuh, L.W. Burgess and G.D. Christian, Anal. Chem., 60 (1988) 433. K. Haupt, Analyst, 126 (2001) 747. B. Sellergren, Anal. Chem., 66 (1994) 1578. Elipsa.de, Available at http://www.elipsa.de. MIP Technologies, Available at http://www.miptechnologies.se. G. Theodoridis and P. Manesiotis, J. Chromatogr. A, 948 (2002) 163. R. Weiss, A. Molinelli, M. Jakusch and B. Mizaikoff, Bioseparation, 10 (2001) 379. A. Molinelli, R. Weiss and B. Mizaikoff, J. Agric. Food Chem., 50 (2002) 1804. P.R. Kootstra, et al., Anal. Chim. Acta, 529 (2005) 75. I. Ferrer and D. Barcelo´, Trends Anal. Chem., 18 (1999) 180. E. Blahova´, J. Lehotay and I. Skacˇa´ni, J. Liq. Chromatogr. Rel. Technol., 27 (2004) 2715. N. Masque, R.M. Marce, F. Borull, P.A.G. Cormack and D.C. Sherrington, Anal. Chem., 72 (2000) 4122. M. Matsui, M. Okada, T. Tsuruoka and T. Takeuchi, Anal. Commun., 34 (1997) 85. I. Ferrer, A. Tolokan, V. Horvath, B. Sellergren, G. Horvai and D. Barcelo´, Anal. Chem., 72 (2000) 3934. V. Crescenzi, G. Masci, M. Fonsi and G. Casati, American Chemical Society meeting, held in Boston, USA, August, 1998. R. Weiss, A. Molinelli, M. Jakusch and B. Mizaikoff, Bioseparation, 6 (2002) 379. J. Whitcombe, J. Alexander, C. Alexander and E.E. Vulfson, Anal. Chem., 8 (1997) 140. I. Chianella, S.A. Piletsky, I.E. Tothill and A.P. Turner, Biosens. Bioelectron., 18 (2003) 119.
130
Marinel la Farre´ et al.
179 S.N. Zhou, E.P.C. Lai and J.D. Miller, Anal. Bioanal. Chem., 378 (2004) 1903. 180 N.M. Maier, G. Buttinger, S. Welhartizki, E. Gavioli and W. Lindner, J. Chromatogr. B, 804 (2004) 103. 181 K. Skudar, O. Bru¨ggemann, A. Wittlesberger and O. Ramstro¨m, Anal. Commun., 36 (1999) 327. 182 C. Cacho, E. Turiel, A. Martin-Esteban, D. Ayala and C. Perez-Conde, J. Chromatogr. A, 1114 (2006) 255. 183 K. Haupt, A. Dzgoev and K. Masbach, Anal. Chem., 70 (1998) 628. 184 P.D. Martin, G.R. Jones, F. Stringer and I.D. Wilson, Analyst, 128 (2003) 345. 185 A.G.V. De Prada, P. Martı´nez-Ruiz, A.J. Reviejo and J.M. Pingarro´n, Anal. Chim. Acta, 539 (2005) 125. 186 R. Koeber, C. Fleischer, F. Lanza, K.S. Boos, B. Sellergren and D. Barcelo´, Anal. Chem., 73 (2001) 2437. 187 F. Chapuis, V. Pichon, F. Lanza, S. Sellergren and M.C. Hennion, J. Chromatogr. A, 30 (2003) 23. 188 T.A. Sergeyava, H. Matuschewski, S.A. Piletsky, J. Bendig and U. Schedle, J. Chromatogr. A, 907 (2001) 89. 189 T.L. Panasyuk, V.M. Mirsky, S.A. Piletsky and O.S. Wolfbeis, Anal. Chem., 71 (2001) 720. 190 S.A. Piletsky, E.V. Piletskaya, A.V. Elgersma, K. Yano and I. Karube, Biosens. Bioelectron., 10 (1995) 959. 191 M. Lahav, A.B. Kharitonov, O. Katz, T. Kunitake and I. Willner, Anal. Chem., 73 (1994) 1578. 192 D. Kritz and K. Mosbach Chen, Anal. Chim. Acta, 300 (1995) 71. 193 A. Pizzariello, M. Stredansky, S. Stredanska and S. Miertus, Sens. Actuator. B, 76 (2001) 286.4. 194 M. Zougagh, A. Rios and M. Valcarcel, Anal. Chim. Acta, 539 (2005) 117. 195 L. Feng, Y. Liu, Y. Tan and J. Hu, Biosens. Bioelectron., 19 (2004) 1513. 196 F.L. Dickert, M. Tortshanoff, W.E. Bulst and G. Ficherauer, Anal. Chem., 71 (1999) 4559. 197 H. Zhou, Z. Zhang, D. He, Y. Hu, Y. Huang and D. Chen, Anal. Chim. Acta, 523 (2004) 237. 198 F.L. Dickert and O. Hayden, Trends Anal. Chem., 18 (1999) 192. 199 S. Kro¨ger, A.P. Turner, K. Mosbach and K. Haupt, Anal. Chem., 71 (1999) 3698. 200 R. Shoji, T. Takeuchi and I. Kubo, Anal. Chem., 75 (2003) 4882. 201 R. Suedee, T. Srichana, C. Sangpagai, C. Tunthana and P. Vanichapichat, Anal. Chim. Acta, 504 (2004) 89. 202 M. Lotierzo, O.Y.F. Henry, S. Piletsky, I. Tothill, D. Cullen, M. Kania, B. Hock and A.P.F. Turner, Biosen. Bioelectron., 20 (2004) 75. 203 J.C.C. Yu and E.P.C. Lai, React. Func. Pol., 63 (2005) 171. 204 A. Guzma´n-Va´zquez de Prada, P. Martı´nez-Ruiz, A.J. Reviejo and J.M. Pingarro´n, Anal. Chim. Acta, 539 (2005) 125. 205 K.E. Sapsford, P.T. Charles, C.H.J. Patterson and F.S. Ligler, Anal. Chem., 74 (2002) 1061. 206 C. Lohse, L.L. Jaeger, N. Staimer, J.R. Sanborn, A.D. Jones, J. Lango, S.J. Gee and B.D. Hammock, J. Agri. Food Chem., 48 (2000) 5913. 207 N. Staimer, S.J. Gee and B.D. Hammock, Anal. Chim. Acta, 444 (2001) 27. 208 T. Watanabe, G. Shan, D.W. Stoutamire, S.J. Gee and B.D. Hammock, Anal. Chim. Acta, 444 (2001) 119. 209 J.C. Johnson, J.M. Van Emon, D.R. Pullman and K.R. Keeper, J. Agric. Food Chem., 46 (1998) 3116. 210 S. Wang, R.D. Allan, J.H. Skerritt and I.R. Kennedy, J. Agric. Food Chem., 46 (1998) 3330. 211 M. Wortberg, G. Jones, S.B. Kreissig, D.M. Rocke, S.J. Gee and B.D. Hammock, Anal. Chim. Acta, 319 (1996) 291. 212 D. Figeys and D. Pinto, Anal. Chem., 72 (2000) 330. 213 J.M. Laval, P.E. Mazeran and D. Thomas, Analyst, 125 (2000) 29. 214 E. Zubritsky, Anal. Chem., 72 (2000) 289A. 215 C.L. Baird and D.G. Myszka, J. Mol. Recog., 14 (2001) 261.
CHAPT ER
5 Advanced Sample Preparation Techniques for the Analysis of Food Contaminants and Residues Pat Sandra, Frank David and Gerd Vanhoenacker
Contents
1. Introduction 2. Sample Preparation Methods for VOCs 2.1 Static headspace (SHS) 2.2 Dynamic headspace (DHS) 2.3 Solid phase microextraction (SPME) 2.4 Headspace sorptive extraction (HSSE) 2.5 Selected applications 3. Sample Preparation Methods for SVOCs and NVOCs 3.1 Solid samples 3.2 Liquid samples 4. Fractionation and Clean-Up 4.1 Chemical methods 4.2 Chromatographic methods 4.3 Gel permeation chromatography 4.4 On-line techniques 4.5 Selected applications 5. Evaporation 6. Derivatization 7. Conclusion References
131 133 134 134 135 136 136 138 140 148 162 163 163 164 165 167 170 170 171 172
1. INTRODUCTION In the analysis of contaminants and residues in food samples, enrichment is of vital importance because samples are too dilute (e.g., beverages) or too complex (e.g., meat) for direct analysis and need to undergo a chain of specific treatments to make them compatible with the analytical techniques. While the dictum ‘‘the Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00005-6
r 2008 Elsevier B.V. All rights reserved.
131
132
Pat Sandra et al.
best sample preparation is no sample preparation’’ is also true for food analysis, for the determination of traces of contaminants and residues, direct analysis is only applicable in some exceptional cases, e.g., the direct analysis of polycyclic aromatic hydrocarbons (PAHs) in drinking water by liquid chromatography (LC) with fluorescence detection and the determination of haloforms in drinking water with capillary gas chromatography with electron capture detection (CGCECD). Extraction, fractionation/clean-up, concentration and/or derivatization steps preceding the analysis, mostly by chromatographic techniques, are mandatory. A typical flow diagram for the determination of contaminants and residues in foodstuffs is shown in Figure 1. Sampling and sample preparation remain among the more time-consuming, error-prone and contamination-prone aspects of the flow diagram. Obtaining a representative sample and proper storage of the sample are important parts of any analysis. Both are often overlooked by analytical chemists, who regard them as self-evident secondary problems, with the chromatographic analysis being of primary interest. However, errors or faults in the sampling protocol cannot be corrected at any point in the analysis. For the analytical data to be meaningful, a plan for acquiring samples and storing samples should be implemented and, if possible, validated by statistical techniques. A discussion on sampling is beyond the scope of this chapter. On the other hand, problems of storage mostly occur in the analytical laboratory and are the responsibility of the analyst. Processes that occur in the sample between the time of sample collection and analysis such as adsorption on the container walls, vaporization loss, photoreactions, and microbial action, can invalidate the data. Samples should be properly stored in the dark in brown glass vials or containers and maintained at 41C or lower. Especially for liquid samples adsorption on the glass wall should be controlled and, if needed, suppressed by adding a polar modifier like methanol, e.g., in beverages with no or low alcohol content.
Sampling
Sample preparation
Chromatographic analysis Data Handling
Collection Storage Extraction Fractionation/Clean-up Concentration Derivatisation Separation Identification Quantification
Reporting
Figure 1 Flow diagram for the analysis of contaminants and residues.
Advanced Sample Preparation Techniques
133
In recent years, great efforts have been made to develop sample preparation techniques that guarantee high recovery and reproducibility and that moreover are faster, cheaper, greener and easier to automate than older methods. A recent trend is also the development of multi-residue methods (MRMs) for a great variety of matrices such as the QuEChERS method [1,2] and sorptive extraction [3,4]. In this chapter the currently used sample preparation methods for chromatographic analysis of contaminants and residues in foodstuff are reviewed and the new methods are discussed in depth and illustrated with examples from the laboratories of the authors. The subdivision of the chapter is, in first instance, based on the target compounds to be determined which can be divided into three main classes: (1) volatile organic compounds (VOCs) that can be analysed via headspace techniques eventually after derivatization, (2) semivolatile compounds (SVOCs) that are GC amenable (thermally stable) like polychlorobiphenyls (PCBs), PAHs, most of the pesticides, etc. that require an extraction step and finally (3) non-volatile or thermally labile compounds (NVOCs) the analysis of which should be performed by LC after extraction. Also the different matrixes from which the target solutes are enriched should be taken into account and differentiated. In general, matrixes can be divided based on the absence or presence of fatty material. Non-fatty foodstuffs include non-alcoholic beverages, alcoholic beverages (ethanol content from 3% to 50% ethanol), fruits and vegetables and herbs, while the fatty food includes milk, vegetable oils and diary products. It has to be noted that in recent years the sample preparation strategies have changed drastically. On the one hand, analysts are confronted with the continuous decrease of legislative limits for food contaminants and residues accompanied with higher requirements for more precise and accurate results and, on the other hand, the performance of analytical tools in terms of qualitative and quantitative analysis, has increased tremendously. Mass spectrometers are a must in trace analysis and because of their ‘‘recognition’’ features they have partly taken over the ‘‘selectivity’’ of classical sample preparation methods. Notwithstanding this, quantification is still challenging and both in target and multi-residue methods, isotope dilution and the method of standard addition provide the most accurate results by compensating for matrix effects (sample characteristic) and ion suppression in mass spectrometry (MS) (sample preparation characteristic). The cleaner the extract, the better are the quantitative data, stressing the importance of sample preparation. Several sample preparation techniques will only be covered briefly in this chapter. For more details, refer to Refs. [5,6] and two recent special issues of J. Chromatogr. A [7,8] including a review on Sample Preparation Techniques for the Determination of Trace Residues and Contaminants in Foods by Ridgway et al. [9].
2. SAMPLE PREPARATION METHODS FOR VOCS VOCs in liquid and solid food samples are best analyzed by headspace techniques. Injecting only the vapour phase gives clean chromatograms and the
134
Pat Sandra et al.
analytical system is not contaminated by non-volatile compounds generally present in liquid extracts. Different approaches are available for headspace sampling and the selection is most often dictated by the sensitivity required. One of the main problems in headspace analysis is quantification as the concentration of the analytes in the vapour phase is matrix dependent. The methods of standard addition and, if possible, of isotope dilution guarantee the most precise and accurate results. Headspace sampling is intensively used for the analysis of off-flavors in foods and beverages but can also be applied to investigate residues from packaging materials [10], benzene in bottled sparkling water, chloropropanols in soy-derived products [11], furan in food products [12], etc.
2.1 Static headspace (SHS) In SHS, an aliquot of a solid or liquid sample is placed in a vial and the sealed vial is heated at a given temperature for a defined amount of time. Heating is required to increase the concentration of the target compounds in the vapour phase. A portion of the headspace is then injected into a GC instrument via a loop or a gastight syringe. Precise replication of the headspace sampling conditions is mandatory to obtain reproducible results.
2.2 Dynamic headspace (DHS) The difference between SHS and DHS analysis mainly lies in the sensitivity that can be reached. In the static mode, part of ‘‘one equilibrium’’ is injected whereas in the dynamic mode the equilibrium concentration is continuously removed and trapped resulting in exhaustive extraction and thus high sensitivity for the analysis of volatiles. For liquid samples, DHS sampling is mostly carried out by purge-and-trap analysis. An inert gas is bubbled through the liquid sample and the purgeable organics are moved from the aqueous to the vapor phase. The volatile compounds are then trapped (solid phase extraction, SPE) on an adsorbent such as Tenax or active charcoal. The trap containing the adsorbent is built in a desorption chamber equipped with a powerful heating mechanism which when activated, permits desorption (gas phase extraction) of the trapped compounds. This technique has the distinct merit of providing a clean sample, free from its often complex matrix. A purge-and-trap device can easily be mounted on a GC equipped with a flame ionization detector (FID), flame photometric detector (FPD) or MS. This technique is most appropriate for mg/L (ppb) level analysis of low molecular weight, slightly water-soluble volatile organics with a boiling point below 2001C. A variation of purge-and-trap is closed-loop stripping (CLS) analysis [13] which is a combination of gas phase extraction with SPE in a closed system. CLS allows ng/L (ppt) analysis of contaminants in drinking water. A recently introduced DHS sampling method is in-tube extraction (ITEX; CTC Analytics, Zwingen, Switzerland) [14]. The enrichment of volatiles can be fully automated as the ITEX device can be mounted on a CTC Combipal sampler. The principle of ITEX is illustrated in Figure 2.
Advanced Sample Preparation Techniques
135
Figure 2 Principle and operation of in-tube extraction (ITEX).
The sample is heated and agitated in a sealed vial until equilibrium is achieved. A special syringe equipped with a trap containing an adsorbent (Tenax, Carbosieve, etc.) is pierced through the vial septum and the syringe pumps the headspace through the adsorbent, e.g., 10 times 1 mL. The trap is then flashheated and desorbed in the GC injector. Afterwards, the hot ITEX trap is cleaned with inert flush gas before the next sampling. The comparison SHS and ITEX will be presented in Section 2.5.1 for the determination of diacetyl, responsible for the cardboard flavour, in beer.
2.3 Solid phase microextraction (SPME) SPME is intensively applied in headspace analysis. A number of books are reviewing the fundamental aspects and the applications of SPME [3,15]. On polymers such as polydimethylsiloxane (PDMS) and polyacrylate a partitioning mechanism applies while on divinylbenzenestyrene copolymers or mixtures of Carboxen (CAR) and PDMS, adsorption controls the enrichment. In headspace SPME, two mechanisms apply, firstly the partitioning of analytes between the sample matrix and the headspace, and secondly the partitioning between the headspace and the fibre coating. SPME is thus not an exhaustive extraction technique but an equilibrium technique. Maximum sensitivity is obtained at equilibrium, although commonly non-equilibrium conditions are used. This requires optimization of temperature, time and agitation for each application.
136
Pat Sandra et al.
Gandini and Riguzzi applied HS-SPME for the analysis of methyl isothiocyanate, an illegal antifermentative agent, in wine [16]. Page and Lacroix applied HS-SPME to the analysis of fruit juices, soft and fruit drinks, and milk for the determination of volatiles ranging from vinyl chloride to hexachlorobenzene [17]. Recent applications include the determination of furan in baby food [18] and formaldehyde in fish [19].
2.4 Headspace sorptive extraction (HSSE) A new approach for sorptive enrichment of analytes from the headspace of aqueous or solid samples, referred to as headspace sorptive extraction has recently been developed [20,21]. The technique implies the sorption of volatile compounds into a large amount of PDMS (ca. 50 mg) placed on a glass rod support. The PDMS-coated glass bar is then thermally desorbed on-line with capillary GC-MS. Using a large amount of sorptive phase, highly volatile as well as SVOCs can be efficiently enriched and compared to SPME a significant increase in sensitivity is achieved. Bicchi et al. [22] compared the performance of HSSE, through the determination of the recoveries and relative abundances of 16 components in coffee headspace, with SHS and HS-SPME applying the fibres PDMS 100 mm, Carbowax/divinylbenzene 65 mm (CW/DVB), Carboxen/PDMS 75 mm (CAR/ PDMS), polyacrylate 85 mm, PDMS/divinylbenzene 65 mm (PDMS/DVB) and Carboxen/divinylbenzene/PDMS 30 mm (CAR/PDMS/DVB). In all cases, HSSE gave higher recoveries, which is entirely due to the high amount of extracting phase applied.
2.5 Selected applications 2.5.1 In-tube headspace extraction for the determination of the diacetyl offflavor in beer In the quality control of beer, several VOCs are monitored. These compounds include C3–C5 alcohols, C2–C5 esters, dimethyl sulfide and 1,2-diketones (diacetyl, 2,3-pentanedione). These compounds are present at different concentration levels ranging from tens of ppm (alcohols) to ppb level (diacetyl). Beer samples are normally analyzed by SHS in combination with GC. In order to cover all solutes and concentration levels, often several runs are needed per sample. Alternatively, the analysis is performed using effluent splitting to three detectors: FID for alcohols and esters, selective sulfur detection (FPD, PFPD) for dimethyl sulfide (DMS) and ECD for diketones. The three detectors allow sufficient sensitivity and selectivity, but this set-up is rather complicated and problems with splitters and thus robustness are encountered. With mass spectroscopic detection, all solutes can be detected using the simultaneous scan and selected ion-monitoring (SIM) acquisition of state-of-the-art MS systems. However, for some solutes, the sensitivity of mass spectroscopic detection is at the limit, especially in combination with SHS.
137
Advanced Sample Preparation Techniques
The total ion chromatograms obtained for a beer sample using classical SHS sampling and ITEX sampling are compared in Figure 3A and 3B, respectively. Both chromatograms represent the datafiles obtained in scan acquisition mode. Ethanol, the most abundant peak, elutes at 6 min. The peak at 4 min corresponds to the air peak (MS scan from m/e 29). It is clear that more peaks are detected using the ITEX sampling. The following solutes could be identified using the mass spectra: 1-propanol (peak 1), ethyl acetate (peak 2), 2-methyl-1-propanol Abundance 800000
A
400000 0 800000
2
B DMS
5
6
9
3
10
1
400000
8
4
7
0 2
4
6
8
10 12 Time (min)
14
16
18
Abundance 500 C 250
0 500
Diacetyl
D 250
0 12
13
14
Time (min)
Figure 3 Total ion chromatograms for beer by SHS (A) and ITEX (B) sampling, and SIM chromatograms at m/z 86 for diacetyl by SHS (C) and HSSE (D). Belgian lager beer (10 mL) was placed in a 20-mL headspace vial and the samples were analysed as such. The SHS conditions were as follows: sample conditioning at 801C for 15 min, 2.5 mL headspace; the ITEX conditions were sample conditioning at 801C for 15 min, 10 extraction strokes of 1 mL at 50 mL/s and desorption at 2501C with 1 mL headspace at 50 mL/s. The analyses were performed on an Agilent 6890 GC — 5975 MSD combination equipped with a 20-m L 0.18-mm ID 1 mm df DB-VRX column. The carrier gas was helium at 200 kPa constant pressure. Injection was split at 1/25. The oven was programmed from 401C, 5 min, at 101C/min to 2501C, 10 min. The MSD transfer line was set at 2501C. The MS was operated in the scan/SIM mode with 50 ms dwell times.
138
Pat Sandra et al.
(peak 3), ethyl propanoate (peak 4), 3-methyl-1-butanol (peak 5), 2-methyl-1butanol (peak 6), 2-methyl propyl acetate (peak 7), ethyl butyrate (peak 8), 3-methyl butyl acetate (peak 9) and 2-methyl butyl acetate (peak 10). Also DMS could be detected at 7.7 min (Figure 3B). Using an extracted ion chromatogram (EIC), the peak can be quantified without problem in the beer sample. The signal-to-noise, measured on ion m/z 62 was 70. The concentration of DMS in this sample was 8 ppb. In the chromatogram obtained by SHS, DMS was difficult to detect (Figure 3A). Only in an extracted ion trace, a small peak with signal-to-noise of 5 could be detected, but no library search confirmation was obtained. The sensitivity was thus increased by a factor of more than 10 for this compound using ITEX sampling. The EICs for ion m/z 86, typical for diacetyl, obtained by GC-MS in SIM mode are compared in Figure 3C and 3D. At 13.1 min, diacetyl can be detected in the chromatogram obtained by SHS only as a trace (S/N ¼ 8 in Figure 3C). Using ITEX, the peak can be detected more easily (Figure 3D) and confirmation of the identity through the relative ratios of target and qualifier ions is possible. The S/N value obtained by ITEX was 44 or 6 times higher than with SHS. The concentration of diacetyl was in the order of 10 ppb.
2.5.2 Comparison of SHS and HSSE in the analysis of fragrances The selection of an HS technique strongly depends on the sensitivity required which is linked to the instrumentation, and especially to the detectors available in the laboratory. In our experience [22], of the recently introduced HS techniques, ITEX, SPME and HSSE, the latter is the most sensitive technique and enrichment factors compared to SHS are increased drastically. This is illustrated with the analysis of some fragrances in a lotion. In Figure 4A, the total ion chromatogram using classical SHS sampling is shown. The internal standards, added at the same concentration level, are detected at 10.3 and 23.1 min, respectively. The response for the first internal standard is higher in comparison to the second internal standard, corresponding to their relative volatility. In this chromatogram, linalool (peak 1) and hexyl cinnamaldehyde (peak 6) are easily detected. Other solutes are only detected as traces and confirmation of their presence by mass spectral comparison with a library spectrum is difficult. The chromatogram obtained by HSSE sampling on PDMS is shown in Figure 4B. Excellent enrichment is obtained considering that the abundances in both chromatograms differ by a factor 10. The structures of all solutes could be elucidated through the MS spectra and some important compounds are citronellol (peak 2), alpha isomethyl ionone (peak 3), lilial (peak 4) and amyl cinnamaldehyde (peak 5).
3. SAMPLE PREPARATION METHODS FOR SVOCS AND NVOCS Food matrixes encompass a broad range of physical types and the selection of a sample preparation method is, in first instance, dictated by the sample structure, e.g., powders, vegetables, fruits, meat and fatty or non-fatty beverages (e.g., milk and yoghurt versus soft drinks and wines). With the exception of food samples directly soluble in an organic solvent, e.g., vegetable oils, all samples analysed for
139
Advanced Sample Preparation Techniques
Abundance
400000
B IS1
300000
200000 6 1
IS2
3
100000 2
4
5
0 8 Abundance
10
12
14
16 18 Time (min)
IS 1
1
20
22
24
6
A 400000 5 IS2
300000 2 200000 3
4
100000
0 8
10
12
14
16 18 Time (min)
20
22
24
Figure 4 Headspace sampling of fragrances by SHS (A) and HSSE (B). A sample of 100 mg was placed in a 20-mL headspace vial. Two internal standards (1,4-dibromobenzene and 4,4u-dibromobiphenyl) were added at the 10 ppm level. The SHS conditions were sample conditioning at 801C for 15 min, HS needle at 901C and injection of 1 mL at 350 mL/s with a 1/10 split ratio. For HSSE, the sample was conditioned at 801C for 15 min with a 10 mm 0.5 mm df PDMS Twister (Gerstel, Mulheim a/D Ruhr, Germany). The Twister was desorbed at 2501C during 10 min in the splitless mode and the released solutes were cryo-focussed at 1001C. The PTV injector was heated from 1001C at 6001C/min to 2501C and the split ratio was 1/10. The analyses were performed on an Agilent 6890 GC — 5975 MSD combination equipped with a 30-m L 0.25-mm ID 0.25 mm df HP-5MS (Agilent Technologies). The carrier gas was helium at 168 kPa constant pressure. Injection was at 2501C with a 1/10 split. The oven was programmed from 501C, 1 min, at 81C/min to 2701C. The MSD transfer line was at 2501C. The MS was operated in the scan mode between 40 and 350 amu.
140
Pat Sandra et al.
NVOCs or SVOCs require a solvent extraction step to enrich/isolate the target solutes from the matrix. Extraction is commonly followed by a clean-up or fractionation step to selectively remove interferences that disturb the chromatographic analysis. However in recent years, the selective nature of mass spectrometers and especially of MS-MS techniques, is more and more exploited to eliminate or reduce these steps. However, care should be taken because these interferences can have a pronounced effect on the MS ionization efficiencies and isotope dilution should be applied. Because both solid and liquid samples require enrichment in an organic solvent, it seems logical to discuss first the sample preparation techniques for solid and semi-solid samples and later those for liquid samples.
3.1 Solid samples Before extraction, solid samples require some extra steps such as grinding, sieving and drying. Extraction is then performed as such or after mixing with a solid matrix (see matrix solid phase dispersion).
3.1.1 Shake flask extraction, Soxhlet and ultrasonic extraction The extraction of solid samples is most commonly done using traditional liquid– solid extraction methods such as shake flask extraction, classical Soxhlet extraction (introduced in 1870!) and its more modern forms Soxtec and Soxtherm. Soxhlet extraction is still considered as a rugged method because it has very few variables that can adversely affect extraction recovery. The modern forms allow equivalent extraction efficiency in about 2 h. It is not the aim to detail all these methods but rather to concentrate on ultrasonic extraction (UE). UE uses mechanical energy in the form of shearing action that is produced by a low-frequency sound wave. The sample is immersed in an ultrasonic bath with a solvent and subjected to ultrasonic radiation for 15–60 min. UE often provides very good results for solid food samples. Advantages over other techniques are simplicity, speed, productivity and low cost. The selection of the solvent is of utmost importance and heating can be applied if needed although self-heating is already generated by the sonication process. Its application will be illustrated and its performance compared to microwave assisted solvent extraction (MASE) and accelerated solvent extraction (ASE) for the analysis of PCBs in food samples (Section 3.2.6).
3.1.2 Supercritical fluid extraction (SFE) The excellent properties offered by a supercritical fluid namely tuneable solvating power (selectivity), high diffusivity and low viscosity have resulted in analytical usage for many years. Despite early promise, the utility of supercritical fluids for extraction was dormant for many years until the mid1980s when analytical-scale SFE instrumentation became commercially available. SFE was received with high expectations by the analytical community, but in recent years enthusiasm has declined as the disadvantages have become clearer. The most important disadvantage is definitely the complexity of the extraction
Advanced Sample Preparation Techniques
141
procedure which is strongly matrix dependent and needs careful optimization. A procedure developed for one particular matrix does not automatically work for another matrix. Chuang et al. [23] applied SFE for the analysis of pesticides in baby food but they could not obtain quantitative recoveries for all monitored pesticides. SFE is therefore not really accepted for routine work and remains a research tool. The determination of PAHs in vegetable oils by SFE was recently described by Lage and Cortizio [24]. In Section 3.2.5, the determination of pesticides by supported liquid-SFE will be presented.
3.1.3 Pressurized liquid and accelerated solvent extraction (PLE, ASE) PLE encloses a number of extraction techniques that use solvents at elevated temperatures and pressures. Best known is ASE that originates from SFE and uses organic solvents at high temperature and high pressure to leach out the organics from solid matrixes. Compared to extractions at or near room temperature and at atmospheric pressure, ASE delivers enhanced performance by the increased solubility, the improved mass transfer and the disruption of surface adsorption by the conditions applied. Dionex Corp. introduced in 1995 a fully automated sequential extraction system that was very soon after its introduction recommended by the US Environmental Protection Agency (EPA) for the extraction of solid waste [25]. Typical conditions for an ASE extraction are: temperature 1001C, pressure 2,000 psi, extraction time 5 min equilibration and 5 min static extraction with a solvent composed of dichloromethane and acetone in ratio 1:1. The speed of the extraction process is greatly increased compared to conventional liquid– solid methods and virtually all organics can be extracted. Disadvantages of ASE are the lack of selectivity which means that further clean-up is needed and that the sample is too dilute for direct analysis and further concentration is required. Recent developments to circumvent these shortcomings are the combination of ASE with SPE and the application of large volume injection. The application of PLE for food (and biological) sample analysis has been reviewed by Carabias-Martinez et al. [26]. Recent applications include the determination of ochratoxin in bread [27] and bisphenol A diglycidyl ether in canned food [28]. Another variant of PLE is extraction at high temperatures and pressures with water. Super-heated water extraction (SHWE) including many applications was recently reviewed by Smith [29]. Although SHWE is by far the most ‘‘green’’ extraction technique, main disadvantages of SHWE over ASE are that the solutes are obtained in dilute aqueous medium and further extraction with an organic solvent is required. A large number of matrix compounds are extracted as well, so that further clean-up is needed and last but not least that the thermal stability of the target solutes under SHWE conditions should be carefully evaluated.
3.1.4 Microwave assisted solvent extraction (MASE) MASE utilises electromagnetic radiation to desorb organics from their solid matrices. MASE typically operates at 2.45 GHz. The use of a microwave oven for sample preparation originates from inorganic or elemental analysis. In this case the electromagnetic radiation is used to destroy inorganic and organic matter using a
142
Pat Sandra et al.
combination of strong acids and peroxides. The first application of microwaves for the extraction of organics from solid material appeared in 1986 [30]. In recent years, different systems have become commercially available and they are based on extraction in a closed high pressure vessel with microwave absorbing solvents, extraction with a non-microwave absorbing solvent in an open vessel and/or extraction with a non-microwave absorbing solvent in a closed vessel applying a Weflon stir bar that heats the solvent. The performance of MASE has been compared to other recently introduced techniques like ASE and SFE and similar recoveries were obtained for soil and sediment samples [31]. For food analysis, the same disadvantages mentioned for ASE apply namely lack of selectivity and the dilution effect. Moreover, care should be taken with solutes that are thermolabile or can rearrange under the influence of electromagnetic radiation. The performance of MASE has also been evaluated for the Belgian dioxin crisis (Section 3.1.6).
3.1.5 Matrix solid phase dispersion (MSPD) MSPD first reported by Barker et al. [32] is a powerful technique for disrupting and extraction of solid, semi-solid and viscous samples. A small amount of sample is homogenized with bulk-bonded silica sorbent (typical ratio 1:4) with a glass pestle in a glass mortar. The shearing forces disrupt the structures of the matrix and disperse the sample over the surface of the sorbent. The homogeneous blend of sorbent and sample is then packed in a syringe-type cartridge (like an SPE cartridge) followed by elution of targets and interfering compounds (or vice versa) by consecutive washings with appropriate solvents. For non-fatty matrices, a simultaneous clean-up often occurs during the MSPD process which allows direct analysis of the extracts [33] while further clean-up is required for MSPD extracts of fatty matrices. An elegant way to remove fat traces was described by Ferrer et al. [34]. Olives and the acetonitrile extract of olive oil were homogenized with aminopropyl silica and the obtained powder was loaded on a Florisil SPE cartridge. Elution with acetonitrile gave a nearly fat free extract. This method is compared to the conventional procedure of size exclusion clean-up. The practical and theoretical aspects of MSPD are described in Ref. [35]. A recent review by Barker [36] contains numerous applications illustrating that the method has found wide application in the analysis of contaminants and pesticide residues from animal tissues, fruits, vegetables and other matrices.
3.1.6 Selected applications 3.1.6.1 The determination of PCBs in foodstuffs. In the European Community, 1999 will be remembered as the year of the Belgian dioxin crisis. The dioxins (mainly polychlorinated dibenzofurans or PCDFs) originated from the presence of used transformer oil in animal feed and many thousands of food samples had to be analysed for PCBs. During the crisis, the sample preparation technique applied at the Research Institute for Chromatography, Kortrijk, Belgium, was continuously updated and a high-throughput method based on UE was developed. The implementation of the method had to be accompanied with validation studies and the analysis of certified samples.
Advanced Sample Preparation Techniques
143
The analytical scheme of the official method Beltest I 014 for the analysis of PCBs in food consists of different steps: sample drying, extraction, clean-up and CGC analysis. Sample drying can be performed by freeze-drying or chemically by the addition of sodium sulphate. In the second step, the lipophilic contaminants are extracted from the matrix using an apolar solvent. The extract contains the lipids, PCBs, PCDDs, PCDFs and other apolar solutes such as organochloro-pesticides (OCPs), PAHs and mineral oil. Different extraction techniques may be applied namely Soxhlet extraction (or the automated versions Soxtec or Soxtherm), UE, ASE, MASE and SFE. All these techniques perform equally well for the extraction of fat and PCBs as will be illustrated further. It is obvious that especially in a crisis situation the selection should be based on sample throughput and cost. Next the PCBs are fractionated from the (co-extracted) fat matrix. For this fractionation, column chromatography on acidic silica gel and aluminium oxide is advised although other techniques such as gel permeation chromatography (GPC) and SPE may be applied if validated. Both sample extraction and clean-up require a concentration step. Finally, the cleaned extract is analysed by CGC-ECD and positive samples are confirmed by capillary gas chromatography with mass selective detection (CGC-MS). UE and clean-up by a dispersive solid phase extraction (DSPE) technique nowadays also applied in the QuEChERS method, was performed as follows. Samples were homogenised using a blender. From fat samples (chicken or pork fat) 1 g sample was weighed in a 20-mL headspace vial. From eggs, 3 g egg yolk was taken. For animal feed samples or other meat products, a sample size corresponding to 200–500 mg fat was taken. To the sample, 2 g anhydrous sodium sulphate and 10 mL petroleum ether were added. Tetrachloronaphthalene or octachloronaphthalene may be added as internal standard to the sample at this stage although external standardization can also be applied. The headspace vial is closed and placed in an ultrasonic bath at 301C for 30 min. In this step, the fat and PCBs are transferred from the matrix in the petroleum ether phase. The sodium sulphate adsorbs the water present in the sample. After extraction, the sample is allowed to settle. An aliquot (typically 5 mL) is transferred to a test tube and another aliquot (2 mL) is used to determine gravimetrically the fat content of the extract. To the test tube, 2 g of acidic silica gel (44% sulphuric acid) is added and the tube is placed in an ultrasonic bath for 30 min. This technique is nowadays called DSPE. In column chromatography and in SPE, the analytes are eluted through a bed and the fat is retained. In DSPE, the fat matrix is allowed to bind on the adsorbent that is mixed with the sample, while the solutes of interest stay in solution. For the fractionation of fat from PCBs, this method works very efficiently. After settlement of the adsorbent or centrifugation, an aliquot of the clear solution is transferred to an autosampler vial. The final volume is not important, since the concentrations are calculated to the initial 10 mL solvent and the sample or fat weight. The whole sample preparation takes approximately one hour and several samples can be prepared in parallel. One technician can handle more than 50 samples per day.
144
Pat Sandra et al.
The extracts are analysed by CGC-ECD and/or CGC-MS. For MS detection, SIM mode is performed on two ions per congener group. The limit of detection (S/NW3) of the micro-ECD and the MS were 0.2 and 0.5 pg, respectively. Figure 5 shows the RTL-CGC-ECD profiles of Aroclor 1260, egg, pork fat and mink fat recorded with a time interval of nearly one month. PCB congeners 153, 138 and 180 are the pre-dominant congeners. The chromatogram of the mink fat extract is interesting. The minks were fed with contaminated eggs and although the same PCB profile (mainly Arochlor 1260) is present, some differences are noted in the relative abundances of the PCB congeners. This can be explained by a different metabolism between the animal species. In the mink sample, the PCB concentration measured as the sum of the seven congeners was as high as 25 ppm (25 mg/kg fat). This concentration was fatal for most minks. Some 4,000 samples, including animal feed, eggs, chicken fat, pork fat, pork meat, meat products (ham, sausages), etc. were analysed using this methodology. From a practical point of view, the splitless liner was replaced after 100 analyses and the column after 1,000 injections. On the column selected and with the
Hz 2000
PCB 153
PCB 138
PCB 180
A
1000 0 6000 4000 2000 0
B
6000 4000 2000 0
C
15000 10000 5000 0
D
20
22
24
26 Time (min)
28
30
32
Figure 5 Retention time locked CGC-ECD analyses of Aroclor 1260 (A), egg extract (B), pork fat extract (C), mink fat extract (D). Analyses were performed on a HP 6890 GC (Agilent) equipped with split/splitless inlet and micro-ECD detection. Separations were carried out on a 30-m L 0.25-mm ID 0.25 mm df HP-5MS column (Agilent). Injection of 1 mL was done in the splitless mode at 2501C. The carrier gas was hydrogen at an initial head pressure of 71 kPa hydrogen. The pressure was adjusted via the RTL software to obtain a retention time of 26.999 min for p,pu-DDT. The oven was programmed from 701C (2 min) to 1501C at 251C/min, to 2001C at 31C/min and to 3001C (2 min) at 81C/min. Nitrogen at 40 mL/min was used as detector make-up gas. The detector was set at 3201C. Reprinted from Ref [52] with permission from Elsevier.
145
Advanced Sample Preparation Techniques
chromatographic conditions applied the PCB congeners 28 and 31 are not separated but this was not critical as both congeners were not relevant for this PCB pollution. The performance of UE was compared with ASE and MASE. The extraction efficiency of the three methods was evaluated with three egg samples contaminated at different levels (low, medium and high). For ASE, a Dionex ASE 200 system (Dionex Corp., Sunnyvale, CA, USA) was used. A 1-g sample was extracted at 1001C and 1,500 psi using petroleum ether as solvent. The extraction time was 5 min oven heat-up time, 5 min static extraction and 3 cycles with 60% of the extraction cell volume (22 mL). The extract was then concentrated to 10 mL. For MASE, an ETHOS SEL system (Milestone, Analis, Gent, Belgium) was applied. A 1-g sample was extracted after 20 min at 951C. The extraction solvent was n-hexane (10 mL in extraction thimble, 10 mL outside thimble) using a Weflon stir bar to absorb the microwave energy in combination with the nonmicrowave absorbing solvent. After extraction, the extract was filtered and concentrated to 10 mL to obtain the same final concentration factor as the UE and ASE. Clean-up and analysis was done in the same way for the three extracts of the three samples. The results based on duplicate analysis are summarized in Table 1. For the sample with the lowest concentration (egg 1) the relative standard deviation (RSD) on the PCB sums obtained by the three techniques is 12%; for the two other samples the RSDs are less than 6%. For the individual values, some small differences are noted but in general these differences are within 10% of the average values. These results clearly demonstrate that there is no statistically significant difference between the three techniques and that equally good results are obtained. The ultrasonic method exhibits by far the highest throughput and is extremely cheap compared to ASE and MASE. The repeatability of the method (n ¼ 6) was evaluated by the analysis of a contaminated egg and fat sample (Table 2). These samples were distributed in a round robin test for Belgian laboratories during the crisis. The RSDs are all below 10% for the congeners PCB 118, 153, 138 and 180 and below 5% for the sum of the congeners. The linearity and method sensitivity were determined by spiking a blank pork fat sample at 6 levels with the individual PCB congeners. The spike levels were 5, 10, 25, 50, 100 and 200 ppb (ng/g fat) per congener. The recovery was determined versus an external standard and the linearity was measured by plotting the Table 1
Comparison of UE, ASE and MASE for PCB enrichment
PCB
118 153 138 180 Sum
Egg 1 (ppb)
Egg 2 (ppb)
Egg 3 (ppb)
UE
MASE
ASE
UE
MASE
ASE
UE
MASE
ASE
170 263 240 111 783
68 309 320 166 863
147 210 234 93 682
556 1,142 1,019 696 3,412
410 1,051 1,120 552 3,133
550 1,184 1,105 686 3,525
945 1,811 2,031 1,015 5,803
1,023 2,032 2,323 1,166 6,544
922 2,042 2,128 1,259 6,349
146
Table 2
Pat Sandra et al.
Repeatability for a contaminated egg and fat sample (1999 Belgian dioxin crisis)
PCB
118 153 138 180 Sum
Egg sample
Fat sample
Concentration (ppb)
RSD (%)
Concentration (ppb)
RSD (%)
141 333 342 165 982
7 2 4 5 2
20 274 318 165 776
4 6 3 4 4
Table 3
Figures of merit for the fast PCB method
CB
Mean % recovery
Linearity
S/N at 5 ppb
28 52 101 118 153 138 180
110 88 91 105 101 104 105
0.9999 0.9903 0.9991 0.9996 0.9994 0.9991 0.9998
9 8 12 12 13 11 18
absolute peak areas versus the spiked concentration. The signal-to-noise ratio was also measured at the lowest spiked concentration. The results are summarised in Table 3. All recoveries are within 88–110% for the individual congeners. The linearity is better than 0.995 except for PCB 52 for which an interfering peak was observed in the CGC-ECD trace. The signal-to-noise ratio was better than eight for all congeners at the 5 ppb level. Lastly, the reproducibility and accuracy of the ultrasonic method was evaluated with the determination of the PCB content in two certified reference materials of the European Community namely the cod liver oil sample CRM 349 and the mackerel oil sample CRM 350 (IRMM, Geel, Belgium). The analyses of these reference materials were performed by four laboratories to which the method was transferred and having the same CGC-ECD and CGC-MS instrumentation. The results are summarised in Table 4 for cod liver oil and in Table 5 for mackerel oil. Most values are within 88% and 110% of the certified samples. The values outside these ranges are noted in italic. For all laboratories and for both techniques, the sum values were always between these limits. The relatively long analysis times (see Figure 7) prompted us to evaluate fast high resolution capillary GC for PCB analysis [37]. This reduced the chromatographic analysis time to less than 8 min. Later, extracts were directly introduced in a mass spectrometer operated in the negative chemical ionization mode. This reduced the analysis time to less than 2 min [38].
147
Advanced Sample Preparation Techniques
Table 4 PCB
28 52 101 118 153 180 Sum
Table 5 PCB
28 52 101 118 153 180 Sum
Accuracy and reproducibility test for the cod liver oil sample Certified Concentration (ppb)
68 149 370 454 938 280 2,259
Lab 1
Lab 2
Lab 3
Lab 4
ECD
MS
ECD
MS
ECD
MS
ECD
MS
61 126 333 390 975 252 2,137
65 165 394 467 989 295 2,375
73 141 385 421 886 283 2,189
64 164 404 448 1,010 312 2,402
104 144 296 479 790 270 2,083
68 199 437 508 1,030 326 2,568
75 159 356 397 810 288 2,085
70 148 373 458 1,016 273 2,338
Accuracy and reproducibility test for the mackerel oil sample Certified Concentration (ppb)
22.5 62 164 142 317 73 778.5
Lab 1
Lab 2
Lab 3
Lab 4
ECD
MS
ECD
MS
ECD
MS
ECD
MS
25 75 152 163 337 73 825
24 72 181 152 345 79 853
21 56 175 117 319 75 763
21 56 175 117 319 75 739
21 65 152 138 287 76 739
19 71 143 125 350 83 791
19 54 150 131 290 70 714
16 63 172 134 316 60 761
3.1.6.2 The determination of nitrofuran metabolites in scrimp and poultry. Nitrofuran antibiotics have been widely used as food additives for treatment of Gram positive and Gram negative bacteria in poultry and fish. The parent compounds and metabolites are suspect carcinogens and they have been banned around the world. The Rapid Alert System for Food and Feed Annual report 2005 [39] shows that these compounds and metabolites continue to be detected in food samples thus remaining today a major concern in food safety. The nitrofuran antibacterial drugs furazolidone, furaltadone, nitrofurazone and nitrofurantoin have been found to metabolize rapidly and the metabolites bind to muscle tissue. The determination of metabolites and not the parent compounds is required in samples of animal origin. The structures of the parent compounds, the metabolites and the derivatives are shown in Figure 6. The European Union set a minimum required performance level (MRPL) at 1 mg/kg for each metabolite [40]. Such levels can easily be determined using stateof-the-art MS systems (ion trap, triple quad and high resolution TOF) if an appropriate sample preparation technique is applied. Sample preparation should include a homogenization step, the release of the metabolites from the proteins, transformation into derivatives to facilitate chromatographic elution and UV
148
Pat Sandra et al.
N
O2N
N
O
N
O
O
N
H2N
N
O
O
H2N
NH
NO2 2
SEM
N
NBA-SEM
NH
O H2N
N
Nitrofurantoin
2
NH
O
NO2 N N
O
O
O N
NH O
O N
N NH
NH2 O
Nitrofluranzone
O
O
NBA-AMOZ
NH
NH2
O
N O
AMOZ
O
O2N
N N
O
O Furaltadone O2N
NO2
N O
NH
O
AHD
NBA-AHD NO2
O
N
N O
Furazolidone
O
H2N
N
O
N N
O AOZ
O
O NBA-AOZ
Figure 6 Structures of the nitrofuran antibiotics, metabolites and formed derivatives.
(the metabolites are not UV absorbing) or MS detection and transfer to an organic phase for analysis. Fortunately, the labelled standards NBA-d5AMOZ (used to quantify NBA-AMOZ) and NBA-d4AOZ (used to quantify the other metabolites) are commercially available simplifying drastically their determination. A typical sample preparation protocol is as follows. One gram of homogenized tissue (e.g., poultry and shrimps) is mixed with 5 mL of a 0.2-M hydrochloric acid and 50 mL of a 2-nitrobenzaldehyde (2-NBA) solution (100 mM in methanol) and incubated 16 h at 371C. The mild acidic conditions release the metabolites via the imine bond from the tissue and the formed amino groups react with 2-NBA to form an aromatic imine bond. The acidic medium is neutralized with 500 mL of a 0.3-M Na3PO4 solution in water and the pH is adjusted to 7 with a 2-M NaOH solution. The sample is twice extracted and centrifuged with 4 mL ethyl acetate and the combined extracts are evaporated to near dryness and reconstituted in 500 mL of initial LC mobile phase. Reversed phase LC-MS (ITD, QqQ or HR-TOF) with electrospray ionization in the positive mode is applied. A typical LC-QqQ analysis is shown in Figure 7. A fish sample (genus Tilapia) was spiked with 0.5 ng/g of the four metabolites and extracted as described [41].
3.2 Liquid samples Extraction of liquid samples (aqueous food samples or extracts obtained from the extraction of solids — see Section 2) is based on partitioning into an immiscible extracting phase which can be a liquid like in liquid–liquid extraction (LLE) or a solid like in SPE.
Advanced Sample Preparation Techniques
149
Abundance
NBAAMOZ
NBAAOZ
1000 NBASEM
0
5
10 Time (min)
NBAAHD
15
Figure 7 LC-QqQ analysis of nitrofurans of a fish extract spiked at the 0.5-ng/g (ppb) level. The sample was analyzed on a reversed phase column with a mobile phase gradient from 20% acetonitrile/80% formic in water to 99% acetonitrile in 10 min with electrospray ionization in the positive mode. Reprinted from Ref. [41] with permission from Agilent Technologies.
3.2.1 Liquid–Liquid extraction The most commonly used enrichment method for aqueous samples is LLE. LLE may be carried out manually by shaking the water sample with an organic solvent in a separation funnel or automatically, using a continuous liquid–liquid extractor. Depending on the extraction conditions used, extracts can contain intermediate to low polarity components (universal extraction for neutral solutes) or acid and base compounds (selective extraction) by adjusting the pH. LLE is very time-consuming and often uses toxic solvents. The volume of the extract is usually too large for direct injection and in order to obtain sufficient sensitivity, an additional evaporation–concentration step is necessary. Particular care needs to be taken in both the solvent extraction and concentration procedures to avoid contamination of the sample. Moreover, solvent impurities will be concentrated as well often masking the target solutes. For a number of applications automated micro LLE in the vial of an injection autosampler can offer a simple and robust alternative. By using highly sensitive and selective detectors, eventually in combination with large volume injection, sub-ppb sensitivities can be reached. Micro LLE has been used for the analysis of trihalomethanes in drinking water [42].
3.2.2 Supported liquid–liquid extraction SLLE uses a diatomaceous earth material placed in a cartridge to adsorb the aqueous phase by hydrophilic interactions. An efficient LLE occurs when a water immiscible solvent is applied. The high surface area at the interface between the organic and aqueous phase increases efficiency while eliminating the possibility
150
Pat Sandra et al.
of emulsion formation (e.g., in extracting milk). The analytes are then eluted as the solvent passes through the adsorbent. Selective extraction for acids and bases can be obtained by adjusting the pH of the aqueous solution. Two examples of SLLE, one applying a liquid and one a supercritical fluid are described. SLLE was experienced to be an excellent method for the determination of chloramphenicol (CAP) in different matrices. No additional clean-up was required. Moreover emulsion formation that was observed for several matrices was completely suppressed. The procedures for honey and shrimps are detailed. A 5-g sample of honey was diluted to 20 mL with water and an appropriate amount of the internal standard d5-chloramphenicol (CAP-d5) was added. The solution was loaded on an ISOLUTE HM-N cartridge from (IST Hengoed, UK, Part-nr. 800-1300-FM) and allowed to stand for 5 min. Elution was performed with 50 mL ethyl acetate. The eluate was collected and the solvent was evaporated under a nitrogen stream at 401C. The residue was redissolved in 1 mL water/methanol (9:1, v/v) and placed in an ultrasonic bath for 1 min. The solution was filtered by a syringe filter before injection. For shrimps, a portion of at least 10 g of frozen shrimps was defrosted and mixed. To 10 g of the mixed shrimps, 30 mL of water and the internal standard was added. After centrifugation for 10 min at 2,000 rpm, a 20-mL portion of the supernatant was loaded on the ISOLUTE HM-N cartridge and allowed to stand for 5 min. After this, the same elution and concentration procedures as described for honey were applied. Both a single quad and an ion trap MS have been used for CAP determinations and a comparison is given in Ref. [43]. Figure 8A shows the analysis of a standard mixture containing 2.5 ppb CAP and 5 ppb CAP-d5. By applying a fragmentor voltage of 160 V, a fragment ion corresponding to [M-HCOCl] is detected at m/z 257 and 262 for CAP and CAP-d5, respectively which are monitored for confirmation purposes. The extraction procedure was evaluated for repeatability and linearity. For repeatability, blank honey was spiked with 1 ppb CAP and 1 ppb CAP-d5. The extraction procedure was carried out six times and the recovery was calculated. The recovery for CAP varied from 85.3% to 94.9% and the mean recovery was 90.6%. The RSD on the recovery taking the internal standard (IS) into account was 3.4%. A calibration curve was constructed with blank honey samples spiked with 0.1, 0.2, 0.5, 1.0 and 2.0 ppb CAP. The samples contained 1 ppb of the IS. The correlation coefficient was 0.9997. The limit of detection (LOD) for the quadrupole was found to be 0.5 ppb corresponding to 50 pg on-column. Taking the sample preparation into account, CAP can be detected in honey samples containing 0.1 ppb. Figure 8B shows the analysis of a CAP polluted honey sample at a concentration of 0.6 ppb. The matrix of honey is rather complex and lower LODs can be obtained by MS-MS techniques (ITD in Ref. [43] and QQQ in Ref. [44]). The same method was applied to the analysis of shrimps. The sample matrix showed less interference compared to honey samples. An example of an analysis of shrimps is shown in Figure 8C. Due to the reduced matrix effect, the LOD with the quadrupole instrument was lowered to ca. 0.05 ppb in the sample. A concentration of 0.35 ppb was recovered in the shrimp sample. Extraction recovery was 85%.
Abundance 7000 321 m/z 4000
CAP (2.5 ppb)
A
323 m/z 257 m/z
1000 14000
326 m/z CAP-d5 (5 ppb)
8000
328 m/z
2000
262 m/z 4
14000
5
Time (min)
EIC 257, 321, 323 m/z (CAP)
Honey B
2000
15000
EIC 262, 326, 328 m/z (CAP-d5)
0 4 14000
5
Time (min)
6
EIC 257, 321, 323 m/z (CAP)
7 Shrimp C
2000 15000
EIC 262, 326, 328 m/z (CAP-d5)
0 4
5 Time (min)
6
7
Figure 8 LC-MS analysis of 2.5 ppb CAP and 5 ppb internal standard (A), of CAP in a honey (B) and a shrimp (C) sample. The column was an Eclipse XDB C18, 150-mm L 4.6-mm ID, 5 mm dp (Agilent) operated at a flow of 0.9 mL/min with the following gradient between 10 mM ammonium acetate in water (solvent A) and methanol/acetonitrile 1/9 (solvent B): 0–1 min 30% B, 1–8 min 30–70% B, 8–8.5 min 70–100% B, 8.5–12 min 100% B and post time 4 min at 30% B. Column temperature was 301C and the injection volume 100 mL. MS settings were: negative ESI, drying gas temperature 3401C and flow-rate 11 L/min, nebulizer pressure 50 psig, Vcap 3,500 V, MSD acquisition on between 3 and 7.5 min, fragmentor 160 V, SIM ions 257, 321, 323 m/z for CAP and ions 262, 326, 328 m/z for CAP-d5.
152
Pat Sandra et al.
Table 6 Quantification data for pesticides spiked in orange juice and determined by SFE-CGC-MS Pesticide
Measured concentration (ppb)
RSD (%)
Spiked concentration (ppb)
Recovery (%)
Thionazin Methyl parathion Fenthion Methidation Pyrazophos Phosalone Vinclozolin Procymidone
17 107
3.5 2.9
20 101
85 103
92 44 28 429 273 130
4.1 3.6 4.8 3.3 3.7 4.1
103 51 30 505 303 130
89 86 93 85 90 100
Liquids can also be enriched by SFE after mixing them with a solid support such as Chromosorb W (60–80 mesh). The method was applied to the determination of pesticide residues in orange juices. A 2-g amount of Chromosorb W was placed in a 7-mL SFE thimble and 2 mL of orange juice was added on top of the adsorbent followed by another 0.5 g Chromosorb W. SFE was performed at a flow rate of 1 mL/min pure CO2 with a density of 0.75 g/mL and at a temperature of 501C for 5 min of static and 30 min of dynamic operation. The extracted solutes were collected on a trap packed with octadecylsilica and the trap was then rinsed with 1 mL chloroform. The extract was analysed by capillary GC-MS operated in the scan mode. The selectivity of SFE was fully exploited, i.e., the pesticides are soluble in neat CO2 at the selected density while unwanted polar and high molecular mass solutes like triglycerides were retained on the Chromosorb W or octadecyl-modified silica support (ODS) adsorbents. Some data are summarized in Table 6 giving the measured concentration (mean value of 3 experiments), the RSD%, the amount spiked in the sample and the recovery. Recoveries ranged between 85% and 103% with precisions lower than 5% for the total analytical procedure. Working in the SIM mode, determinations at the low ppb level are possible. The total analysis time was 1 h and both the sample preparation and analysis were fully automated [45].
3.2.3 Solid phase extraction This extraction procedure is more and more applied, being much faster, cheaper, and more versatile than most classical techniques. Moreover, SPE procedures are easily automated using robotics, or can be coupled on-line with chromatographic techniques. The principle of retention (enrichment) is analogous to LC and is suitable for low, intermediate and high polarity solutes. Commonly, SPE media are based on normal phase, reversed phase or ion exchange chromatography. Giving an overview of the different SPE sorbents and their applications is not within the scope of this chapter. Hundreds of SPE cartridges are commercially available and the catalogues of the manufacturers describe their features and
Advanced Sample Preparation Techniques
153
applications. The principles and practice of SPE have been described in books by Thurman and Mills [46], Fritz [47] and Simpson [48]. Present designs of SPE devices are the syringe-type cartridge, the Empore disks and the Empore disk cartridges. The syringe cartridge is the most common arrangement and cartridges ranging in mass of sorbent from 50 mg to 10 g are commercially available. Solvent flow through is typically done using a commercially available vacuum manifold. Permeability is no problem because sorbents are mostly based on irregular particles with a particle diameter between 30 and 60 mm. In the Empore disk format, 5–10 mm particles are intertwined with fine threads of Teflon giving a disk with a thickness of ca. 0.5 mm and a diameter in the range 47–70 mm. Manifolds are also commercially available for multiple sample extraction using Empore disks. The SPE disk allows rapid flow rates of sample and of solvents. One litre of water can be passed through an Empore disk in ca. 10 min whereas with the syringe cartridge the same volume of water can take more than 1 h. Both approaches need a relatively large volume of desorbing liquid and further concentration is required. In the disk cartridge format, a disk of 10 mm diameter is placed in a cartridge between two polyethylene frits. Only small volumes of solvent are needed for solid phase stripping eliminating the need for an additional evaporation step hereby considerably reducing the risk of losses and contamination. The principle of SPE is illustrated with the determination of triazines in drinking water applying large volume injection capillary GC-MS. For the enrichment of triazines from water a 10-mm/6 mL ODS Empore disk cartridge was chosen. This means that enrichment is based on the reversed phase mechanism. For capillary GC, the operation can be divided in six steps namely wetting and stripping the sorbent, conditioning the sorbent, loading the sample, rinsing the sorbent to elute extraneous material, drying of the sorbent and finally elution of the analytes of interest. The disk was first rinsed with 0.5 mL of methanol (wetting and stripping), followed by 1 mL distilled water (conditioning). Twenty-five milliliter water spiked at the 1 ppb level with eleven triazines was passed through the cartridge at a flow of 50 mL/min (loading). Five milliliter distilled water was then passed through the cartridge to elute polar extraneous solutes (rinsing). After drying under vacuum for 10 min (drying), desorption was performed directly in a 2-mL autosampler vial with 0.5 mL ethyl acetate. Forty microliter of the extract was directly injected, this means without further concentration, into the capillary GC system equipped with a programmed temperature vaporizing (PTV) injector operated in the solvent vent mode. The detection limits set by the European Community (0.1 ppb) could easily be reached with scan MS while ion-monitoring allowed determinations down to the ppt or ng/L level. Several approaches allow the tuning of the selectivity of the SPE process. pH control is important to suppress ionization as illustrated for the analysis of veterinary drug residues in shrimps by Li et al. [49]. For ionic solutes the ion exchange mechanism can be utilized. Chlormequat (chlorocholine chloride) belongs to the family of quaternary ammonium salt pesticides. Chlormequat was extensively used for the control and management of terrestrial and aquatic
154
Pat Sandra et al.
vegetation since the mid-1950s but its use has been restricted because of its toxicity to man. Nevertheless, in the late 1990s concentrations as high as 7 ppm were measured in pears. Because of the zero tolerance for pesticides in baby food, often containing pears, a robust and reliable analytical method down to the ppb level is needed. In the procedure presently used in our laboratory, chopped and homogenized pears are mixed with methanol containing the internal standard d4-chlormequat. The mixture is filtered and an aliquot is extracted by SPE on a strong cationic exchanger (BondElut SCX, Varian, CA, USA). After rinsing with a mixture of MeOH-H2O (1:1), chlormequat and the internal standard are eluted with MeOH-H2O (0.2 M NH4OAC) (4:6). Analysis is performed by LC/MS-MS on a cyanopropyl column with electrospray MS in the positive mode. Monitored ions are m/z 122 and daughters m/z 58:60. Other selective SPE methods include the use of restricted access media (RAM), immunosorbents and molecularly imprinted polymers (MIP). These sorbents have mainly been applied for biological and environmental samples and food applications to date are rather limited. Pharmaceuticals in milk were determined by Souverain et al. [50] using RAM SPE and SPE with an immunosorbent was applied by Pichon et al. [51] for the determination of phenylurea pesticides in fruit juices. DSPE in which the solid material added to the liquid sample is more and more applied. The main reason is the high-throughput possibilities DSPE offers. As outlined in Section 3.1.6, DSPE was intensively used in 1999 in our laboratory for the Belgian dioxin crisis [52,53]. Similar procedures are also used in the QuEChERS multi-residue method [1]. In recent years, regulatory agencies emphasize more and more the need for development and use of analytical methods able to determine in food products as many residues as possible out of the whole pattern of insecticides, fungicides and other compounds applied in agricultural practice. At present, single residue methods, i.e., the determination of one pesticide, e.g., chlormequat, or selective residue methods (MRMs), i.e., the determination of a relatively small number of chemically related compounds, e.g., N-methylcarbamate insecticides, are intensively applied for pesticide residue determinations in large number of samples whose pesticide treatment history is known. The use of single residue methods and sMRMs will definitely continue but the development and utilization of MRMs, i.e., the determination of as many pesticides as possible with preferably a single sample preparation method and one GC and one LC method both hyphenated to MS, recognizes a momentum. In the past, a variety of capillary GC-MS-based MRMs have been developed. For example, working group 4 of the Technical Committee (TC 275) of the European Committee for Standardization (CEN) provides information on five MRMs for non-fatty foods (EN 1528:1996) [54]. All methods require extraction with organic solvents such as acetone [55–57], acetonitrile [58] and ethyl acetate [59] and with the exception of Ref. [59] they all require partitioning in a solvent mixture and further clean-up by column chromatography or GPC is advised. The multi-residue capillary GC-MS method that was applied in our laboratory until the application of stir bar sorptive extraction (SBSE – see Section 3.2.5) was a
Advanced Sample Preparation Techniques
155
method used by the laboratories of the Dutch Inspectorate for Health Protection [59]. This method is similar to the Luke method [55] but the extraction procedures have been miniaturized to reduce solvent consumption. Other MRMs for the GC determination of residues in fruit and vegetables include the procedures described by Stan et al. [60,61] for 385 pesticides using extraction of the samples with acetone followed by salting-out and a multi-bed clean-up and the procedure described by Fillion et al. [62] for 251 pesticide and degradation products. The sample preparation of the later method comprises extraction with acetonitrile, a salting-out step, clean-up by SPE on octadecyl and on carbon/aminopropyl silica and a concentration step. An MRM for animal tissues was recently described by Pang et al. [63] using gel permeation chromatographic clean-up followed by GC-MS and LC-tandem MS. The procedure on clean-up will be described in Section 4.4. Today, the QuEChERS method is by far the best developed MRM for a wide variety of pesticides in several common non-fatty and, since recently, fatty food matrices. The QuEChERS process, as initially developed for fruit and vegetables, is outlined in the flow diagram in Figure 9 [1]. DSPE is a key aspect of the method and the type of adsorbents, as well as the pH and polarity of the solvent, can be adjusted for differing matrices and difficult analytes.
Homogenization in Dry Ice 10 g Sample
10 mL Acetonitrile
Add 4 g MgSO4 + 1 g NaCl
Add IS solution
Dispersive SPE PSAm + MgSO4
(Add 0.1% HAc and Analyte Protectants)
CGC-MS or LC-MS
Figure 9 Flow diagram of the QuEChERS procedure.
156
Pat Sandra et al.
In step 1, a 10-g sample obtained by homogenization in a powerful chopping device using dry ice is vigorously shaken with 10 mL acetonitrile for 1 min. Salts are added in step 2 to induce the phase separation. MgSO4 reduces the water phase while NaCl controls the ionic strength of the extracting solvent. After shaking for 1 min, an internal standard solution is added (step 3). Step 4 is DSPE and typically 50 mg adsorbent is added to a 1-mL aliquot of the acetonitrile phase. The sample is centrifuged, and acetic acid and GC protectors (sorbitol, gulonolactone and ethyl glycerol) are added before injection. For LC analysis, GC protectors are not needed. In recent years, several modifications of the QuEChERS method have been made for specific applications and matrices. Different extraction solvents can be applied and DSPE, commonly performed with PSAm (primary secondary amine) which mainly removes sugars and fatty acids, can be complemented with graphitized carbon black (remove pigments and sterols) and/or octadecylsilica (remove lipids). An important note is that ‘‘QuEChERS-kits’’ have been assembled commercially by Sigma Aldrich/Supelco (Bellefonte, Pennsylvania), Restek (Bellefonte, Pennsylvania) and United Chemical Technologies (Bristol, Pennsylvania). The QuEChERS technique has proven successful for the determination of pesticides in a variety of fruit and vegetables, e.g., [64–66] and also recently in fatty matrices such as olive oil [67], and milk and eggs [68]. The technique was also used to analyse acrylamide in various food matrices [69] and ivermectin in salmon and antioxidants in pet food [70]. In the European Community (EU), QuEChERS round robin tests have been conducted with over 100 laboratories participating. These tests showed that the method can be transferred among laboratories with success [71]. In the US, the QuEChERS method has been adopted First Action as AOAC International Official Method 2007.01. The QuEChERS method is an excellent method to determine pesticides at the maximum residue limits (MRLs) set by regulatory authorities for human consumption. However, for very low MRLs such as set by the European baby food directive (10 ng/g), the method is inadequate. In a recent article, Lehotay et al. [72] described the analysis of a mixture of vegetables and fruit spiked with 36 organophosphorus and organochlorine pesticides at the 10-ng/g level. With the original QuEChERS method only 12 of the 36 pesticides could be determined at the 5-ng/g level. A new technique called Solvent in silicone tube extraction (SISTEx) was introduced. This is a combination of sorptive extraction and solvent collection and similar in its operation as membrane-assisted extraction. The number of elucidated pesticides increased to 24 with a 44-fold improvement in detection threshold.
3.2.4 Solid phase microextraction The literature on application of SPME in food analysis is overwhelming. The reader is referred to the many application notes of Supelco, the producer of the SPME devices. A review by Wardencki et al. [73] describes several applications of SPME in food analysis. However, most applications use headspace SPME (e.g., the off-flavours geosmin and methylisoborneol in drinking water, the cork
Advanced Sample Preparation Techniques
157
flavour caused by trichloroanisol in wine, off-flavours in rancid oils and fats, caffeine in decaffeinated coffee and the sunstruck flavour in beer) and direct immersion SPME of water samples. The application of the latter technique to complex liquid food samples can be difficult because of protein, sugar, etc., adsorption limiting the lifetime of the fibres. This could be solved by incorporating the fibre inside a hollow cellulose membrane but this technique requires much longer extraction times [74]. SPME liquid desorption in combination with LC is another alternative, also applicable for the analysis of thermolabile pesticides. SPME-LC for the analysis of pesticides has been reviewed by Aulakh et al. [75]. SPME-LC was applied by Blasco et al. [76] to determine post-harvest fungicides in fruits.
3.2.5 Stir bar sorptive extraction In SBSE a glass-lined magnetic bar is covered with a thick layer of PDMS [77,78]. Through magnetic stirring of the bar in the sample solution the components are enriched in the PDMS phase. The typical manipulations in SBSE are (1) the stir bar is introduced in the liquid and stirred for a given time at a selected stirring speed and temperature, (2) removed with tweezers, (3) rinsed with distilled water to remove matrix compounds such as sugars, proteins, etc., (4) dried on lint-free tissue and finally (5) introduced in desorber tubes for thermal extraction (for capillary GC analysis) or in a mini vial for liquid desorption (for LC analysis). Advantages of this technique are ease-of-use, high sensitivity, high accuracy of analysis and reduced risks of contamination compared with other sample preparation techniques. Like all sorptive extraction methods SBSE is an equilibrium technique. Enrichment factors at equilibrium can be predicted from the log P values [79,80]. In practice, it is not necessary to work at this point and extractions are commonly performed for a much shorter defined period of time. Stir bars have been commercialized under the name TWISTER and are, together with the analytical tools, available from Gerstel (Mu¨lheim a/d Ruhr, Germany). SBSE has been applied for quality control, and trace (ppb) and ultra-trace (ppt) analysis of water samples, beverages, diary products, biological fluids, etc. A recent review by F. David and P. Sandra describes the applications of SBSE for environmental analysis, food analysis, and biomedical and life science applications [81]. The performance of SBSE in combination with liquid extraction and LC-MS analysis has been compared to SPME for the determination of organophosporus insecticides in honey [82] and to SPE for fungicide residues in grapes [83]. Two typical examples are discussed, namely elucidation of endocrine disrupting chemicals (EDCs) in cheap red wines and the analysis of benzoic acid in yoghurt. In a cheap red wine sample some EDCs were detected by SBSE-CGC-MS. The question was from where did these EDCs originate? The red wine sample was closed by a plastic stopper and 10 mg of the stopper was directly analysed by thermal desorption-CGC-MS analysis (Figure 10). The main peak is diisobutylphthalate (DiBP) (peak 5). The other compounds are the nonylphenols (peak group 4), benzoic acid (peak 2) and the typical wine components ethyl
158
Pat Sandra et al.
Abundance 2 1 5
2x107 3 1x10
4
7
10
15 Time (min)
20
Figure 10 TD-CGC-MS analysis of 50 mg of a plastic stopper. A 10-mg sample of the stopper was thermally desorbed at 2501C and the released volatiles were analysed by capillary GC-MS on a 30-m L 0.25-mm ID 0.25 mm df HP5-MS. The MS was operated in the scan mode and ion m/z 149 was selected.
Abundance BA 3000000
2000000
1000000
6
8
10
12
14
16
18
20
Time (min)
Figure 11 SBSE analysis of a yoghurt sample on the presence of benzoic acid. Extraction time was 60 min at 1,400 rpm and analysis was performed by capillary GC-MS on a 30-m L 0.25-mm ID 0.25 mm df HP-FFAP (Agilent) column.
octanoate (peak 1) and ethyl decanoate (peak 3) that were adsorbed on the stopper. A yoghurt sample, claimed to be free of preservatives, was diluted 1:3 with distilled water and acidified to pH 2 with 1N hydrochloric acid. SBSE extraction was performed followed by CGC-MS analysis (Figure 11). The concentration of benzoic acid in the yoghurt sample was 28 ppm. Because of a log K(o/w) for benzoic acid of 1.87 maximum recovery is 40% at equilibrium. For quantification, the standard addition method was applied. The limit of quantification (LOQ)
Advanced Sample Preparation Techniques
159
(at signal-to-noise level S/N10) was 8 ppb in the scan mode and 0.5 ppb in the ion-monitoring mode.
3.2.6 Selected applications 3.2.6.1 Multi-residue screening of pesticides in vegetables, fruit and baby food applying SBSE. An MRM has been described based on SBSE followed by capillary GC-MS using retention-locked conditions [4]. The method provides detection from the mg/kg (ppm) to the sub mg/kg (ppb) level hereby complying with the MRL set by regulatory organizations for pesticides in different matrices. A schematic overview of the original method is presented in Figure 12. Approximately 15 g of a vegetable, fruit or baby food sample is accurately weighed in a 100-mL flask and 30 mL of methanol is added. The mixture is homogenized using an Ultra Turrax mixer for 5 min and the flask is placed in an ultrasonic bath for 15 min. A fraction (approximately 10 mL) of the blend is placed in a closed 20-mL vial and centrifuged for 5 min at 5,000 rpm. One milliliter of the supernatant methanol phase is put in a 20-mL headspace vial and 10 mL of water is added. A stir bar 10 mm long coated with a 0.5 mm PDMS layer is added and the mixture is stirred for 60 min at 1,000 rpm. After sampling, the stir bar is taken out with tweezers, dipped in distilled water, placed on lint-free tissue to remove residual droplets and finally put in a liner of a thermal desorption system. For quantification, 5 mL of appropriate pesticide standard solutions in methanol are added to the sample before Ultra Turrax mixing and ultrasonic treatment. Analysis is performed by retention time locked (RTL) GC-MS using automatic RTL screener software in combination with the Agilent RTL pesticide library. Modifications can be done according to specific needs in different steps of the procedure. For example, sample extraction can be done with acetonitrile or after pH adjustment for acidic or basic pesticides; new developments in GC and MS 15 g Sample + 30 mL MeOH
Ultraturrax + Ultrason (15 min)
1 mL Extract + 10 mL Water
SBSE (60 min)
TD-RTL-CGC-MS
Figure 12 Flow diagram of the multiresidue SBSE method for pesticides in fruit and vegetables.
160
Pat Sandra et al.
software, i.e., the deconvolution reporting software (DRS) can be implemented in the procedure, etc. Figure 13A shows the recorded total ion chromatogram of the SBSE-TDcapillary GC-MS analysis of a lettuce sample. The main peaks (1–3) correspond to Abundance
1
3
2
A
-4
100x10
-4
80x10
-4
60x10
-4
40x10
-4
20x10
7
11
15
19 Time (min)
23
27
31
35
Abundance -4
500x10
B
1. Vinclozolin (175 ppb) 2. Toclofos-methyl (17 ppb) 3. Procymidone (249 ppb)
2 Reproducibility (n=6) Vinclozolin: RSD = 5.4 % Toclofos-methyl: RSD = 8.8 % Procymidone: RSD = 4.6 %
-4
400x10
-4
300x10
1 3
-4
200x10
-4
100x10
7
11
15
19 23 Time (min)
27
31
35
Figure 13 Total ion chromatogram of the SBSE extract of a lettuce sample (A) and EIC (B) using the RTL and MS libraries. Splitless thermal desorption was performed by heating the tube from 401C to 2801C (5 min) at a rate of 601C/min. The analytes were cryo-focused in a PTV at –1501C with liquid nitrogen prior to injection. An empty baffled liner was used in the PTV injector. For splitless injection (2 min) the PTV was ramped from –1501C to 2801C (2 min) at a rate of 6001C/min. Capillary GC analysis was done on a 30-m L 250-mm I.D., 0.25 mm df HP-5MS column (Agilent Technologies). The oven was programmed from 701C (2 min) at 251C/min to 1501C, at 31C/min to 2001C and finally at 81C/min to 3001C. This is the temperature program required for the RTL screener option (Agilent Technologies). Helium was used as carrier gas. The head pressure was calculated, using the RTL software, so that p,pu-DDT was eluting at a constant retention time of 26.98 min. An Agilent 5973 MSD was used in the scan mode (m/z 40–500). Reprinted from Ref. [4] with permission from Elsevier.
Advanced Sample Preparation Techniques
161
C16–C18 fatty acids. Detection and identification of trace levels of pesticides in this complex profile can be very time-consuming and laborious. The presence of pesticides is elucidated automatically via the RTL screener software in combination with the RTL-MS library for pesticides and endocrine disruptors selecting four qualifier ions for positive identification (presently with the DRS software the full spectrum is taken into account). Toclofos-methyl, vinclozolin and procymidone were detected by the RTL in the lettuce sample. The EIC at m/z 212, 265 and 283 for vinclozolin, tolclofos-methyl and procymidone, respectively, is shown in Figure 13B. These pesticides have thus positively been identified in the lettuce sample and only now can MRM quantification be performed. There are different ways to quantify accurately positive findings. Conventional methods in food analysis are single calibration with a standard the concentration of which is close to the estimated concentration and prepared in a blank matrix to compensate for matrix effects, internal standard addition of D- or C13-labelled pesticides and standard addition at five or six concentration levels. The first method requires a blank sample to compensate for matrix effects but as strange as this may look such samples are not readily available. The second approach cannot be applied in an MRM because labelled standards of only a few pesticides are commercially available. The last method is by far the easiest to use in a routine environment. However, this method is time-consuming and thus costly. Precise quantification in fact is only needed when the detected quantity is expected to exceed the maximum allowable level. MRL in foodstuffs, with the exception of baby food, are relatively high and with semi-quantitative methods elucidation of negative, i.e., far below the MRL, and positive samples, i.e., concentration around the MRL values, can easily be made. Only accurate quantification is needed for positive samples. For the lettuce sample, quantification was made by standard addition at six levels and the correlation coefficients were all higher than 0.99. Vinclozolin, tolclofos-methyl and procymidone were quantified at 175, 17 and 249 mg/kg, respectively. These are mean-values of six complete analyses (n ¼ 6) and the RSDs were 5.4%, 8.8% and 4.6%, respectively. The residue levels are far below the MRL of the European Community, i.e., 5 mg/kg for vinclozolin and procymidone and, 0.5 mg/kg for tolclofos-methyl in lettuce and in fact accurate quantitation was not required because the lettuce sample could be considered negative taking the abundances of the MS-trace into account. MRLs in baby food become more and more stringent and ultra-trace level analysis (mg/kg and sub mg/kg) is required. Baby food is a more complex matrix because, besides vegetables or fruits, small quantities of meat and thus fat are also present. This affects the efficiency of the pre-extraction in methanol and the SBSE recovery. Standard addition calibration is the only valid alternative for baby food. As illustration, the analysis of a baby food containing vegetables, complete rice and chicken using SBSE-TD-GC-MS is presented. Preliminary screening was performed with the MSD in the scan mode, hereby elucidating the presence of small traces of piperonyl butoxide. For accurate quantitation, the MSD was used in the SIM mode at m/z 176. Six sub-samples of the baby food
162
Pat Sandra et al.
Abundance 120
Non-spiked 1
100 80 60 Spiked 2 ppb
40 20
7
11
15
19 Time (min)
23
27
31
35
Figure 14 SBSE extract of baby food contaminated with piperonyl butoxide (for conditions, see Figure 13). Reprinted from Ref. [4] with permission from Elsevier.
sample were spiked with a piperonyl butoxide standard in methanol at concentrations of 0, 2, 5, 10, 20 and 50 mg/kg. Figure 14 shows the selected ion chromatogram at m/z 176 of the unspiked sample (A) and of the sample spiked at 2 mg/kg piperonyl butoxide (B). The correlation coefficient of the standard addition curve was R2W0.99 and the concentration in the sample was calculated at 1.1 mg/kg.
3.2.6.2 Determination of iprodione in white wines using SBSE-liquid desorptionLC/MS. The pesticide iprodione partially decomposes to 3,5-dichlorophenyl hydantoin during GC analysis. LC-MS is therefore the method of choice [84]. For its determination in wine samples, SBSE was combined with liquid desorption followed by LC-atmospheric pressure chemical ionization mass spectroscopy. Undiluted wine (10 mL) was poured into a headspace vial of 20 mL and a twister containing 25 mg PDMS was stirred in the sample for 40 min at a speed of 1,400 rpm. The stir bar was extracted with 1 mL acetonitrile in an ultrasonic bath for 15 min. Five microliter of the extract was injected for LC-MS analysis. Figure 15 shows the analysis for an Italian sparkling wine. The calculated concentration of iprodione via standard addition was 98 mg/L (RSD 4.6% triplicate analysis).
4. FRACTIONATION AND CLEAN-UP Solvent distribution and LC (or its derivative SPE) are commonly applied to further fractionate or clean-up a solvent extract.
Advanced Sample Preparation Techniques
163
Abundance Iprodione (98 ppb) 200000
100000
0
0.5
1
1.5 Time (min)
2
2.5
Figure 15 LC–MS analysis of the liquid extract of SBSE of a wine sample. LC–APCI–MS analyses were carried out on a benchtop HP1100 Series LC–MSD instrument (Agilent Technologies, Waldbronn). A Phenomenex Luna C 18 column, 250-m L 4.6-mm I.D., 5 mm particle size was used. The mobile phase consisted of water (solvent A) and 10% tetrahydrofuran in methanol (solvent B). A gradient from 70% B at 0 min to 80% B at 20 min was applied. The flow-rate was 1 mL/min and the analyses were performed at 221C. APCI was carried out in the negative mode at a mass range between m/z 200–350. The fragmentor voltage was set to 70 V. The nitrogen drying gas was at 3501C with a flow-rate of 5 L/min. The nebulizer pressure was 60 psig. The capillary voltage was 4,000 V and the corona current was 25 mA. Analyses in the SIM mode for iprodione were carried out at m/z 242.9, 245.0 and 246.8.
4.1 Chemical methods In solvent distribution the principle of ‘‘like likes like’’ is applied and the partitioning is based on polarity or selective interactions. As an example, the separation of apolar/medium polar and polar compounds can be performed by distribution in a hexane–methanol/water (95:5) mixture. Acidic compounds such as phenols can be extracted with 6% NaHCO3 while alkaline compounds can be recovered with 5% HCl. Alcoholic contaminants can be fractionated via an isocyanate reaction while solutes with an aldehyde or ketone function can be fractionated with a Schiff base like phenylhydrazine. The chemical methods are more and more replaced by chromatographic methods.
4.2 Chromatographic methods The different modes of LC are used to further fractionate or clean-up samples after solvent extraction. The separation mechanism can be based on polarity (normal phase LC), on hydrophobicity (reversed phase LC), on the ionic character of the solutes (ion exchange LC), on their shape (graphitized carbon elution) or on their size (size exclusion or GPC). Low pressure LC, better known as column chromatography, high pressure LC or SPE are all used depending on the aim of the clean-up and the complexity of the sample. Column chromatography is somewhat old-fashioned and large amounts of (toxic) solvents have to be used to elute the solutes of interest. Moreover, concentration is very time-consuming and
164
Pat Sandra et al.
Fat
GPC on Biobeads SX-3 (to remove fat)
Alumina (to remove apolar compounds)
Graphitized Carbon (to remove the PCBs)
Analysis CGC-High Resoltion MS
Figure 16 Flow diagram for the fractionation and clean-up of dioxins and furans from fat samples.
prone to artifacts. HPLC is the method of choice when the fractionation is critical and high resolution is needed in this step. SPE is the best method for highthroughput analysis using minimum amounts of solvents. Frequently employed adsorbents are silica gel, alumina, Florisil and graphitized carbon. A scheme for the clean-up of dioxins (PCDDs) and furans (PCDFs) from fats is shown in Figure 16. Presently, automated sample preparation systems are available for the enrichment of PCDDs/PCDFs and PCBs in a single step. Automated and on-line systems will be presented in Section 4.4. A technique with excellent features for the fractionation of contaminants and pesticide residues from fatty food samples is size exclusion chromatography (SEC) or GPC.
4.3 Gel permeation chromatography For fatty food matrices, the main problem is the co-extraction of fats. The amount of fat extracted strongly depends on the nature of the target solutes and the solvent to be selected to efficiently extract them. For example, the determination of PCBs in meat requires extraction with an apolar solvent like cyclohexane that will solubilize the fat completely while extraction of phenylurea pesticides can be performed with acetonitrile, only partly solubilizing the fat. When the fat content is relatively low, but still disturbing chromatographic analysis, clean-up by SPE on octadecylsilica can be applied. Lipid traces are strongly retained on ODS and do not elute even with pure methanol. For high lipid concentrations and/or when the polarity of the target solutes is the same as of the lipids (phthalates in edible oils), GPC is an excellent technique. In GPC, compounds are separated according to the molecular volume (E molecular mass). Larger molecules cannot
Advanced Sample Preparation Techniques
165
enter the pores of the GPC packing material (polystyrenedivinylbenzene) and elute before smaller molecules that can enter the small pores. Already in the 1980s, low pressure GPC was used for the fractionation of pesticides from lipid matrices [85,86]. Classical GPC separations are performed on 40-cm L 25-mm ID low pressure columns packed with Biobeads SX-3 and operated at 5 mL/min. A similar set-up was recently used by Pang et al. [63] in a validation study on 660 pesticide residues in animal tissues. In this method, 10 g animal samples were mixed with 20 g sodium sulphate and extracted with 35 mL cyclohexane/ethyl acetate (1:1) twice by blender homogenization, centrifugation and filtration. After evaporation, the extract was injected on a S-X3 GPC column (40-cm L 25-mm ID) with cyclohexane/ethyl acetate (1:1) as mobile phase at 5 mL/min. The 22–40 min fraction was collected for subsequent analysis by GC-MS and LC-tandem MS. GPC can be miniaturized and solvent consumption largely reduced by using HPLC equipment and high-pressure GPC columns. Automated GPC clean-up can be performed using a system consisting of an isocratic HPLC pump, an autosampler allowing the injection of 500 mL fat extract, a temperature controlled column oven, a variable UV or RI detector and a fraction collector. In our laboratory, GPC is performed on small bore columns (e.g., 300-mm L 7.5-mm ID) packed with PL-Gel with 5 mm particles having 5 nm pore size and operated at 1-mL/min dichloromethane. The 5-nm pore size is important since it gives the highest resolution and the largest elution window for compounds in the 100–1,000 Da mass range. The resolution power is further increased by using two columns in series (60-cm L). Solvent consumption is approximately 5–10 times lower in comparison to the classical GPC method. The method is illustrated with the analysis of palm oil spiked at the 10-mg/kg level with some PAHs. A 50-mg sample of the palm oil was diluted with 1 mL dichloromethane and 500 mL was injected on a 60-cm L 7.5-mm ID PL-Gel column. Figure 17A shows the GPC chromatogram of the spiked palm oil superimposed by the EPA GPC evaluation mixture consisting of corn oil (peak 1), diethylhexylphthalate (DEHP) (peak 2), methoxychlor (peak 3), perylene (peak 4) and sulphur (peak 5). The fraction eluting between 18 and 21 min (3 mL) was evaporated with 100 mL isooctane as keeper and 1 mL was analysed by GC-MS on a 30-m L 0.25-mm ID 0.25 mm df HP-5MS. Figure 17B shows the chromatograms obtained by single ionmonitoring for some high molecular mass PAHs and ppb level determinations are possible.
4.4 On-line techniques The urgency to increase the capacity of analytical laboratories and to reduce manual labour has resulted in the construction of sample preparation stations for high-throughput analysis. Automated sample preparation is often accompanied with more reliable and rugged data compared to manual sample preparation methods. Well known is the ‘‘dioxin street’’ in which ASE, a ‘‘Power-Prep’’ workstation (Fluid Management Systems, Waltham, MA, USA), a solvent evaporation unit and a GC-HRMS are implemented. In the automated prep
166
Pat Sandra et al.
Absorbance
1
2
3
4
5
A
1200
800 EPA te st sample Palm oil sample 400
0 8 Abundance 1000
12
16 Time (min) B(b+k)F
PYR
Spike level: 10 ppb in oil
20
CHRYS
BaP
B(a)A
FTH B 500
0 16
18
20
22 Time (min)
24
26
28
Figure 17 GPC chromatogram of the EPA standard (dashed line) and a palm oil sample spiked with PAHs (A) and GC-MS analysis of the collected fraction (B). A sample of 1 mL was analysed on a 30-m L 0.25-mm ID 0.25 mm df HP-5MS using single ion-monitoring for some high molecular mass PAHs.
station system, a multi-step SPE procedure based on well-established sets of adsorbents such as acidic, basic and neutral silica, basic alumina, Florisil and graphitised carbon black are combined depending on the target analytes. Nowadays, laboratories performing dioxin analysis of fatty food samples must also produce PCB data and the use of a single sample preparation step for PCDFs/PCDDs and PCBs has been described [87–89].
Advanced Sample Preparation Techniques
167
Fully automated on-line LC-GC systems for fractionation and clean-up have been described [90]. The systems can be based on large volume injection via a cool on-column injector or a PTV injector. The first system allows the enrichment of both volatiles and semi-volatiles, while the second is restricted to the analysis of semi-volatiles. De Paoli et al. [91] constructed an on-line GPC-normal phase LC-GC-FPD system for the determination of organophosphorus pesticides in fruit. Hyotylainen et al. [92] described an on-line microporous membrane LLEGC-MS system for the determination of pesticides in red wines. Jongenotter and Janssen [93] applied on-line GPC-GC-FPD for the determination of organophosphorus pesticides in edible oil. A similar system using MS as detection was used by Liu et al. [94] for measuring multi-residual pesticides in agricultural products. Pesticides were extracted from homogenised food samples with acetonitrile and decontaminated via DSPE with PSAm as sorbent. The on-line LC-PTV-GC-NPD system used in our laboratory for the determination of pesticides in essential oils [95] is presented in Section 4.5.
4.5 Selected applications 4.5.1 Analysis of pesticides in orange oil by on-line LC-GC The principle of LC-PTV-GC-NPD is illustrated with the determination of ethion and chlorpyriphos in orange oil used to prepare soft drinks. The essential oil is fractionated by normal phase LC, resulting in a separation according to polarity and the fraction containing the pesticides and leaving the LC detector is directed via a capillary tube with well-defined dimensions, in a T-shaped flow cell. The cell is equipped with a septumless sampling head through which a syringe needle can be introduced. The sampler is completely computer controlled. To transfer a selected LC fraction, the transfer start and stop times, measured on the LC chromatogram, are introduced in the controller software. The time delay between the LC detector and the flow cell is automatically calculated from the connecting tubing dimensions and the LC flow rate. At the time the LC fraction of interest passes through the flow cell, the syringe needle penetrates the septumless head and samples the LC fraction at a speed equal to the LC flow rate. Volumes up to 2 mL can be collected in the syringe. After collection, the needle is withdrawn from the flow cell and a large volume injection is made using the PTV in the solvent vent mode. Depending on the fraction volume and solvent type, the sample introduction parameters (inlet temperature, vent flow, vent time, injection speed, etc.) are calculated by the PTV calculator program. The LC profile for the orange essential is shown in Figure 18A. The apolar mono- and sesquiterpenes elute first, followed by the terpenoids and after 16 min the flavanoids also elute. These last compounds especially give unwanted interferences in direct GC analysis because they have similar molecular weights as the pesticides. Using the same conditions, ethion and chlorpyriphos standards eluted at 4.6–4.7 min. The fraction eluting from 4.4 to 4.9 min (volume ¼ 0.5 mL) was automatically transferred to the GC inlet. The LC-GC interface was programmed to take the sample at a 1,000 mL/min sampling speed (the same as the LC flow rate). The complete fraction of 500 mL was injected in the PTV inlet
168
Pat Sandra et al.
Absorbance
NPLC-UV Orange oil A
800 600 400 200 0 0
5
10
pA 700
Time (min)
15
20
25
GC-NPD analysis of NPLC fraction
B
chlorpyriphos 500
ethion 300
0
10
Time (min)
20
30
Figure 18 On-line NPLC-CGC-NPD for the characterization of chlorpyriphos and ethion in orange oil, (A) NPLC analysis, (B) capillary GC-NPD analysis. HPLC parameters used: column 250-mm L 4.6-mm ID 10 mm dp Lichrospher 100 DIOL, injection volume 20 mL, mobile phase in a gradient from 100% hexane for 10 min, to 40% isopropanol at 20 min (2 min hold) at a flow rate of 1 mL/min and UV detection at 220 nm. Capillary GC-NPD analysis was performed on a 30-m L 0.25-mm ID 0.25 mm df HP-5MS column and the oven was programmed from 701C (2 min) to 1501C at 251C/min and then to 2801C at 81C/min (10 min). The detector was set at 3201C with 3 mL/min hydrogen, 80 mL/min air and 30 mL/min helium make-up flow.
at 250 mL/min. This injection speed corresponds to the injection speed calculated by the PTV software program. Figure 18B shows the resulting GC-NPD chromatogram and both ethion and chlorpyriphos are detected. The chromatograms are very clean and no interferences are present. This demonstrates the excellent selectivity of the LC-GC combination. The concentrations of ethion and chlorpyriphos were calculated by external standard analysis and are 1.9 ppm for chlorpyriphos and 0.8 ppm for ethion.
4.5.2 Determination of phthalates in milk and edible oils by off-line GPC-GC [96] Approximately 5 g of milk samples or milk powders dissolved in water (1g/10 mL) are extracted on a shaking machine for 30 min with 20 mL of a 1:1 cyclohexane/acetone mixture in a 40-mL vial. After completion, the vials are
Advanced Sample Preparation Techniques
169
centrifuged and the supernatant is transferred to a pre-weighed vial. The solvent is evaporated under nitrogen and the fat content is measured. The residue is dissolved in dichloromethane and the internal standard (d4-DEHP) is added. The amounts of solvent and internal standard are adjusted to give approximately 50 mg fat and 100 ng internal standard per mL dichloromethane. The solution is then homogenised in a vortex agitator. For the determination of phthalates in edible oils and fat, the oil or fat sample can be diluted directly in dichloromethane to a concentration of 50 mg fat per mL. For GPC separation of the dichloromethane solution, 500 mL is injected onto a column combination consisting of 5-cm L 7.5-mm ID PL-Gel pre-column and two 30 cm 7.5-mm ID 5 mm PL-Gel 5 nm columns. The mobile phase is dichloromethane at 1 mL/min flow rate. UV detection at 220 nm is used to monitor the effluent. Phthalates typically elute in a window between 20 and 23 min (3 mL fraction). This fraction is automatically collected and dichloromethane is evaporated under a nitrogen stream and the residue is redissolved in 100 mL isooctane. A 1-mL sample of the extract was analysed by capillary GC-MS. The limit of quantification for milk samples with 3% fat content is 1 ng/g for DiBP and dibutylphthalate (DBP) and 3 ng/g for DEHP. The recovery of the GPC clean-up method was tested by spiking an olive oil sample at a 500 ppb level with dimethylphthalate (DMP), diethylphthalate (DEP), DiBP, DBP, butylbenzylphthalate (BBzP) and DEHP, and at a 5-ppm level with diisononylphthalate (DiNP) and diisodecylphthalate (DiDP). The olive oil was tested before and no phthalates were detected at concentrations above 50 ppb (500 ppb for DiNP and DiDP). The results from the non-spiked oil were therefore considered as the ‘‘procedure blanks’’. d4-DEHP (internal standard) was added to the dichloromethane solution. The sample was analysed in triplicate. The linearity was tested by spiking an olive oil sample at 8 levels (100, 250, 500, 1,000, 2,500, 5,000 and 7,500 ng/g fat) ( 10 for mixed isomers). The mean recovery, standard deviation (RSD%) and linearity (correlation coefficient r2) are listed in Table 7. In general, good recoveries (W80%) are obtained, except for butylbenzylphthalate where the recovery is lower. This is due to a slightly different behaviour of this compound in sample clean-up (GPC). The correlation coefficients are better than 0.99 for all phthalates, except for DiNP (0.98). This correlation shows that the method can be used in the concentration range from 100 to 7,500 ppb for the single isomer phthalates and from 1 to 75 ppm for the mixed isomer phthalates. The major problem in phthalate analysis is the contamination problem, resulting in false positive results or over-estimated concentrations. The risk of contamination is present in the whole analytical scheme, including sampling, Table 7
Validation data for the determination of phthalates in olive oil
Recovery (%) RSD (%) Linearity (r2)
DMP
DEP
DiBP
DBP
BBzP
DEHP
DiNP
DiDP
103 15.7 0.996
134 15.7 0.995
104 9.5 0.999
138 11.8 0.996
69 16.0 0.995
127 12.1 0.998
85 11.6 0.984
81 10.6 0.990
170
Pat Sandra et al.
sample preparation and chromatographic analysis. Due to the fact that phthalates are widely used, they are present in air, in water and organic solvents, in plastics and adsorbed on glass or other materials. Running continuous blanks is the only solution to this problem.
5. EVAPORATION Liquid extraction or desorption techniques often needs solvent evaporation to concentrate the target solutes. Solvent evaporation can only be applied for concentrating semi-volatiles and even then care must be taken or solutes of interest will be lost. Moreover contamination can occur and impurities in the extracting solvent are enriched hence the need for ultra-pure solvents. Most common approaches for solvent evaporation are gas blow-down, rotary evaporation, Kuderna-Danish evaporative concentration, automated evaporative concentration [97], and TurboVap concentration (Zymark Corporation, Hopkinton, MA, USA). The loss of solutes can partly be overcome by adding a keeper, i.e., a small amount of an organic solvent of the same polarity as the extracting solvent but with a higher boiling point, e.g., isooctane in n-hexane or cyclohexane.
6. DERIVATIZATION For single residue and selective residue determinations, derivatization can be useful to improve the chromatographic analysis as well as the extraction yield and to decrease detection. A typical example is the analysis of amitrol [98]. Derivatization with hexylchloroformate introduces hydrophobicity in amitrol and the derivative can be extracted by SPE on octadecyl silica, analysed by reversed phase LC and, moreover, the derivative shows better ionization in MS compared to the original molecule. Another example of derivatization in LC was presented in Section 3.1.6.2 for the analysis of nitrofurans. Derivatization in GC is most often applied to ‘‘cap’’ the polar groups by substituting the active proton so that volatility increases and irreversible or reversible adsorption into the column is avoided. However, derivatization is more and more applied in sorptive extraction techniques to increase the recoveries. For example, chlorophenols are derivatized into the acyl compounds by adding a base like potassium carbonate to the solution followed by acetic acid anhydride. The acyl derivatives possess higher affinities for the extraction phase in headspace and direct emerging SPME and SBSE. Figure 19 shows the analysis of a water sample spiked at the 10-ng/L level (10 ppt) with monochlorophenols (ion m/z 128), dichlorophenols (ion m/z 164), trichlorophenols (ion m/z 196), tetrachlorophenols (ion m/z 232) and pentachlorophenol (ion m/z 266). Extraction was performed by emerging SBSE using a 10 mm 0.5 mm df PDMS stir bar on a 10-mL sample after addition of 0.5 g K2CO3 and 0.5 mL acetic acid anhydride. Extraction conditions were 45 min stirring speed at 1,000 rpm and room temperature. The derivatives were
171
Advanced Sample Preparation Techniques
CP
Abundance
PCP
DCP
4000
TCP 3000 TeCP 2000
1000
10
12
14
16 18 Time (min)
20
22
24
Figure 19 SBSE analysis of chlorophenols in drinking water after in-situ acylation. The derivatives were thermally desorbed in the splitless mode and analyzed on a 30-m L 0.25mm ID, 0.25 mm df HP5-MS column using MS detection in the ion-monitoring mode (for other conditions, see Figure 13). Reprinted from Ref [81] with permission from Elsevier.
thermally desorbed in the splitless mode and analyzed on a 30-m L 0.25-mm ID, 0.25 mm df HP5-MS column using MS detection in the ion-monitoring mode. SBSE was also applied for the determination of pyrimethanil, chlorothalonil, vinclozolin and chlorfenvinphos in honey samples [81]. Sample preparation was only dilution of 1 g honey with water. Campillo et al. applied a similar derivatization method for the headspace SPME analysis of chlorophenols in honey samples [99]. Numerous derivatization reactions can be applied and for more information we refer to the book by Blau and Hacket [100]. It is important to note that nowadays, derivatization can be fully automated and often placed on-line with the chromatographic analysis.
7. CONCLUSION Notwithstanding the tremendous power of state-of-the-art analytical instrumentation, and especially the recent progress made in MS, sample preparation is still a key step to ensure the validity of the measurements. Increasing demand for high-throughput (faster and simpler) determinations of contaminants and residues has seen the introduction of many new sample preparation techniques. Much has been published on sample preparation in recent literature and a considerable database of applications has evolved. The methods used in routine laboratories are often the ones dictated by regulatory organizations and implementation of new developments can be a slow process because of validation and robustness issues. In the era of green
172
Pat Sandra et al.
chemistry, an argument to speed up the application of recent methods is the drastically reduced solvent consumption making them environmentally friendly. An extremely important aspect is quantification. The degree of accuracy and precision will always remain a function of the number of targets to be determined. Single residue methods and sMRMs provide more accurate results than MRMs. For single residue methods and sMRMs, often labelled standards are available that can be added to the sample before or during the sample preparation steps. Examples are the determination of chlormequat in fruit and vegetables, of CAP in honey, of dioxins in milk, of nitrofurans in fish. In MRMs compromises have to be made but this does not automatically mean that the obtained data are less important. In the first instance, a semi-quantitative idea is obtained allowing one to decide whether or not precise quantification is needed. When the concentration is far below the MRL value further work in this respect is a waste of time. The main advantage of MRM is that a broad range of contaminants and residues is screened and when positive elucidation, both in terms of nature and close to the MRL level, is obtained accurate quantification can be made by standard addition.
REFERENCES 1 M. Anastassiades, S.J. Lehotay, D. Stajnbaher and F.J. Schenck, J AOAC Int., 86 (2003) 412. 2 www.quechers.com 3 J. Pawliszyn (Ed.), Applications of Solid Phase Microextraction, RSC Chromatography Monographs, Hertfordshire, 1999. 4 P. Sandra, B. Tienpont and F. David, J. Chromatogr. A, 1000 (2003) 299. 5 A. Handley (Ed.), Extraction Methods in Organic Analysis, Scheffield Academic Press, Scheffield, 1999. 6 S. Mitra (Ed.), Sample Preparation Techniques in Analytical Chemistry, Wiley, New Jersey, 2003. 7 L. Ramos and R. M. Smith (Eds.), Advances in Sample Preparation Part I, J. Chromatogr. A., 1152 (2007) 1. 8 L. Ramos and R. M. Smith (Eds.), Advances in Sample Preparation Part II, J. Chromatogr. A., 1153 (2007) 1. 9 K. Ridgway, S.P.D. Lalljie and R.M. Smith, J. Chromatogr. A, 1153 (2007) 36. 10 W.J. Reid, In: B. Begrie (Ed.), Taints and Off-flavours in Food, Woodhead Publishing, Cambridge, 2003, p. 31. 11 C. Crews, G. Lebrun and P.A. Brereton, Food Addit. Contam., 19 (2002) 343. 12 A. Becalski, D. Forsyth, V. Casey, B.P.Y. Lau, K. Pepper and S. Seaman, Food Addit. Contam., 22 (2005) 535. 13 K. Grob and F. Zurcher, J. Chromatogr., 117 (1976) 285. 14 www.ctc.ch/gc_products/combi_specifications_itex.htm 15 J. Pawliszyn, Solid Phase Microextraction. Theory and Principles, Wiley, New York, 1997. 16 N. Gandini and R. Riguzzi, J. Agric. Food. Chem., 45 (1997) 3092. 17 B.D. Page and G. Lacroix, J. Chromatogr., 648 (1993) 199. 18 F. Bianchi, M. Careri, A. Mangia and M. Musci, J. Chromatogr. A, 1102 (2006) 268. 19 F. Bianchi, M. Careri, M. Musci and A. Mangia, Food Chem., 100 (2007) 1049. 20 B. Tienpont, F. David, C. Bicchi and P. Sandra, J. Microcolumn Sep., 12 (2000) 577. 21 C. Bicchi, C. Cordero, E. Liberto and P. Sandra, J. Chromatogr. A, 1094 (2005) 11. 22 C. Bicchi, C. Iori, P. Rubiolo and P. Sandra, J. Agric. Food Chem., 50 (2002) 449. 23 J.C. Chuang, K. Hart, J.S. Chang, L.E. Boman, J.M. Van Emon and A.W. Reed, Anal. Chim. Acta, 463 (2002) 189.
Advanced Sample Preparation Techniques
173
24 M.A. Lage Yusty and J.L. Cortizo Davina, Food Control, 16 (2005) 59. 25 Method 3545, USEPA SW-846, 3rd ed., Update III, 1995, Washington, DC. 26 R. Carabias-Martinez, E. Rodriguez-Conzalo, P. Revilla-Ruie and J. Hernandez-Mendez, J. Chromatogr. A, 1089 (2005) 1. 27 L. Gonzalez Osnaya, J.M. Soriano del Castillo, J.C. Molto Cortes and J.M. Vinuesa, J. Chromatogr. A, 1113 (2006) 32. 28 O. Pardo, V. Yusa, N. Leon and A. Pastor, J. Chromatogr. A, 1107 (2006) 70. 29 R.M. Smith, Anal. Bioanal. Chem., 385 (2006) 419. 30 K. Ganzler, A. Salgo and Valko, J. Chromatogr., 371 (1986) 2999. 31 J. Dean, Extraction Methods for Environmental Analysis, Wiley, Chichester, 1998. 32 S.A. Barker, A.R. Long and C.R. Short, J. Chromatogr., 475 (1989) 353. 33 H.S. Dorea and F.M. Lanc- as, J. Microcolumn Sep., 11 (1999) 437. 34 C. Ferrer, M.J. Gomez, J.F. Garcia-Reyes, I. Ferrer, E.M. Thurman and A.R. Fernandez-Alba, J. Chromatogr. A, 1069 (2005) 183. 35 S.A. Barker, J. Chromatogr. A, 885 (2000) 115. 36 S.A. Barker, J. Biochem. Biophys. Methods, 70 (2007) 151. 37 P. Sandra and F. David, J. Chromatogr. Sci., 40 (2002) 248. 38 P. Sandra, F. David and B. Tienpont, Chromatographia, 60 (2004) S299. 39 RASFF Annual Report 2005, p. 29. Available at ec.europe.eu/food/food/rapidalert/index. en.htm. 40 EU Decision 2003/181/EC amending decision 2002/657/EC. 41 F. Liang, P. Hu and P. Li, Agilent Technologies Application Note 5989-5808EN, 2006. 42 I. Temmerman, F. David, P. Sandra and R. Soniassy, Hewlett Packard Application Note 228-135, 1991. 43 G. Vanhoenacker, F. David and P. Sandra, Agilent Technologies Appication Note 5988-9920EN, 2003. 44 K. Vivekanandan, M.G. Swany, S. Prasad and R. Mukherjee, Rapid Commun. Mass Spectrom., 19 (2005) 3025. 45 P. Sandra, F. David, E. Baltussen and T. De Smaele, In: A. Handley (Ed.), Extraction Methods in Organic Analysis, Scheffield Academic Press, Scheffield, 1999, p. 300. 46 E.M. Thurman and M.S. Mills, Solid-Phase Extraction: Principles and Practice, Wiley, Sommerset, USA, 1998. 47 J.S. Fritz, Analytical Solid-Phase Extraction, Wiley, Weinheim, Germany, 1999. 48 N.J.K. Simpson (Ed.), Solid-Phase Extraction: Principles, Techniques and Applications, Marcel Dekker, New York, 2000. 49 H. Li, P.J. KIjak, S.B. Turnipseed and W. Cui, J. Chromatogr. B, 836 (2006) 22. 50 S. Souverain, S. Rudaz and J.-L. Veuthey, J. Chromatogr. B, 801 (2004) 141. 51 V. Pichon, A.I. Kransova and M.C. Hennion, Chromatographia, 60 (2004) S221. 52 P. Sandra, F. David and T. Sandra, In: C.W. Gehrke, R.L. Wixom and E. Bayer (Eds.), Chromatography. A Century of Discovery 1900–2000, Elsevier, Amsterdam, 2001, p. 488. 53 P. Sandra and F. David, In: H.J. Issaq (Ed.), A Century of Separation Science, Marcel Dekker, New York, 2002, p. 643. 54 C. Schenzler and H.P. Their, Food Addit. Contam., 18 (2001) 875. 55 M.A. Luke, J.E. Froberg, G.M. Doose and H.T. Masumoto, J. AOAC, 64 (1981) 1187. 56 G. Becker. In: Deutsche Forschungsgemeinschaft (Ed.), Manual of Pesticide Residue Analysis, VCH, Weinheim, Germany, 1992, Vol. 2, p. 313. 57 W. Specht. In: Deutsche Forschungsgemeinschaft (Ed.), Manual of pesticide residue analysis. VCH, Weinheim, Germany, 1992, Vol. 2, p. 317. 58 Official Methods of Analysis of AOAC International. In: P. Cunniff (Ed.), 16th ed., AOAC, Arlington, 1995, Vol 1, p. 1. 59 Analytical Methods for Pesticide Residues in Foodstuffs. In: P. van Zoonen (Ed.), General Inspectorate for Health Protection, RIVM, Bilthoven, The Netherlands, 1996, Part 1. 60 H.J. Stan and M. Linkergagner, J. Chromatogr. A, 750 (1996) 369. 61 H.J. Stan, J. Chromatogr. A, 89 (2000) 347.
174
Pat Sandra et al.
62 J. Fillion, F. Sauve´ and J. Selwyn, J. AOAC Int., 83 (2000) 698. 63 G.-F. Pang, Y.-Z. Cao, J.-J. Zhang, C.-L. Fan, Y.-M. Liu, X.-M. Li, G.-Q. Jia, Z.-Y. Li, Y.Q. Shi, Y.P. Wu and T.T. Guo, J. Chromatogr. A, 1125 (2006) 1. 64 F.J. Schenck and J.E. Hobbs, Bull. Environ. Contam. Toxicol., 73 (2004) 24. 65 www.flworkshop.com/2003/schenck.pdf 66 N. Looser, D. Kostelac, E. Scherbaum, M. Anastassiades and H. Zipper, J. Verb. Lebensmittel., 1 (2006) 135. 67 S.C. Cunha, S.J. Lehotay, K. Mastovska, J.O. Fernandes and M.B.P.P. Oliveira, J. Sep. Sci., 30 (2007) 620. 68 S.J. Lehotay, K. Mastovska and S.J. Yun, J. AOAC Int., 88 (2005) 630. 69 K. Mastovska and S.J. Lehotay, J. Agric. Food Chem., 54 (2006) 7001. 70 www.flworkshop.com/2004/schenck25.pdf 71 M. Anastassiades, E. Scherbaum and D. Bertsch, Validation of a simple and rapid multiresidue method (QuEChERS) and its implementation in routine pesticide analysis, MGPR Symposium, Aix en Provence, France, May, 2003. 72 M. Janska, S.J. Lehotay, K. Mastovska, J. Hajslova, T. Alon and A. Amirav, J. Sep. Sci., 29 (2006) 66. 73 W. Wardencki, M. Micheluc and J. Curylo, Int. J. Food Sci. Technol., 39 (2004) 703. 74 Z.Y. Zhang, J. Poerschmann and J. Pawliszyn, Anal. Commun., 33 (1996) 219. 75 J.S. Aulakh, A.K. Malik, V. Kaur and P. Schmitt-Kopplin, Crit. Rev. Anal. Chem., 35 (2005) 71. 76 C. Blasco, G. Font, J. Manes and Y. Pico, Anal. Chem., 75 (2003) 3274. 77 E. Baltussen, P. Sandra, F. David and C.A. Cramers, J. Microcolumn Sep., 11 (1999) 737. 78 E. Baltussen, C.A. Cramers and P. Sandra, Anal. Bioanal. Chem., 373 (2002) 3. 79 A. Tredoux, H. Lauer, T. Heideman and P. Sandra, J. High Resolut. Chromatogr., 23 (2000) 644. 80 W.M. Meylan and P.H. Howard, J. Pharm. Sci., 84 (1995) 83. 81 F. David and P. Sandra, J. Chromatogr. A, 1152 (2007) 65. 82 C. Blasco, M. Fernandez, Y. Pico and G. Font, J. Chromatogr. A, 1030 (2004) 77. 83 A. Juan-Garcia, J. Manes, G. Font and Y. Pico, J. Chromatogr. A, 1050 (2004) 119. 84 P. Sandra, B. Tienpont, J. Vercammen, A. Tredoux, T. Sandra and F. David, J. Chromatogr. A, 928 (2001) 117. 85 W. Specht and M. Tilkes, Frezenius Z. Anal. Chem., 301 (1980) 300. 86 H.-P. Thier and H. Zeumer, Manual of Pesticide Residue Analysis, Vol. 1, VCH, Weinheim, 1987, p. 75. 87 C. Picard, J.-F. Focant and E. De Pauw, Anal. Bioanal. Chem., 372 (2002) 373. 88 J.-F. Focant, C. Picard and E. De Pauw, Talanta, 63 (2004) 1101. 89 K. Holscher, A. Maulshagen, H. Shirkhan, G. Lieck and P.A. Behnisch, Organohalogen Compounds, 66 (2004) 117. 90 K. Grob, On-Line Coupled LC-GC, Hu¨thig Verlag, Heidelberg, 1990. 91 M. De Paoli, M.T. Barbina, R. Mondini, A. Pezoni, A. Valentino and K. Grob, J. Chromatogr., 626 (1992). 92 T. Hyotylainen, K. Luthje, M. Rautiainen and M.-L. Riekkola, J. Chromatogr. A, 1056 (2004) 267. 93 B. Jongenotter and H.-G. Janssen, LC-GC Europe, 15 (2002) 338. 94 L.-B. Liu, Y. Hashi, Y.-P. Qin, H.-X. Zhou and J.-M. Lin, J. Chromatogr. B, 845 (2007) 61. 95 F. David, P. Sandra, D. Bremer, R. Bremer, F. Rogis and and A. Hoffmann, Labor Praxis, 21 (1997) 33. 96 F. David, P. Sandra, B. Tienpont, F. Vanwalleghem and M. Ikonomou, Analytical methods review. In: C.A. Staples (Ed.), Phthalate Esters. The Handbook of Environmental Chemistry Vol. 3, Anthropogenic Compounds, Springer Verlag, Weinheim, 2003, Part Q, p. 9. 97 E.A. Ibrahim, I.H. Suffet and A.D. Sakla, Anal. Chem., 59 (1987) 2091. 98 www.lcgceurope.com/lcgceurope/data/articlestandard//lcgceurope/442002/36589/article.pdf 99 N. Campillo, R. Penalver and M. Hernandez-Cordoba, J. Chromatogr. A, 112 (2006) 31. 100 K. Blau and J. Hacket (Eds.), Handbook of Derivatives for Chromatography, Wiley, Chichester, 1994.
CHAPT ER
6 Recent Developments in Chromatographic Techniques Katerina Mastovska
Contents
1. Introduction 2. Fast Chromatographic Separation 2.1 Fast gas chromatography 2.2 Fast liquid chromatography 3. Two-Dimensional Chromatographic Separation 3.1 Comprehensive two-dimensional gas chromatography 4. Overcoming Adverse Matrix Effects 4.1 Approaches to overcome matrix effects in gas chromatography 4.2 Approaches to overcome matrix effects in liquid chromatography-mass spectrometry 5. Future Trends References
175 176 178 184 188 189 191 192 194 196 197
1. INTRODUCTION Chromatographic techniques play a significant role in the determination of analytes in complex matrices, separating individual sample components before their detection [1]. In the analysis of contaminants and chemical residues in food, gas chromatography (GC) and liquid chromatography (LC) are two main chromatographic methods employed in practice. Other chromatographic techniques, such as thin-layer chromatography (TLC) [2], supercritical fluid chromatography (SFC) [3], or capillary electrochromatography (CEC) [4], may be suited for some special applications but did not find a wider use in routine analysis of food contaminants and residues. GC is a suitable technique for thermally stable compounds that can be readily volatilized. This includes mainly halogenated contaminants, such as polychlorinated dibenzo-p-dioxins — PCDDs, polychlorinated dibenzofurans — PCDFs,
Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00006-8
r 2008 Elsevier B.V. All rights reserved.
175
176
Katerina Mastovska
polychlorobiphenyls — PCBs, polybrominated diphenylethers (PBDEs), semivolatile pesticides, polycyclic aromatic hydrocarbons (PAHs), or phthalates. A group of LC-amenable contaminants and residues comprises polar, thermally labile and/or larger molecules that cannot be easily volatilized, such as the majority of veterinary drug residues, mycotoxins and other toxins, polar pesticides or large PAHs. As compared to LC, GC generally provides more separation efficiency. Also, GC has been traditionally combined with more selective detectors for contaminant and residue analysis. In particular, the well-established conjunction of GC with mass spectrometric (MS) detection and availability of relatively affordable benchtop GC-MS instruments made GC a number one choice for multicomponent contaminant and residue analysis, even though the polar analytes had to be derivatized before the GC step. In recent years, the situation has dramatically changed thanks to the advances in LC-MS, which brought this powerful technique to routine laboratories and opened the door to direct, selective and sensitive analysis of polar compounds. For instance, LC-MS is gradually replacing immunochemical and microbial methods in the analysis of veterinary drugs [5]. Also, LC-MS is competing with GC-MS for the status of a reference technique in the multiclass, multiresidue analysis of pesticides [6,7]. In fact, many pesticide residues are not directly amenable for GC and their permanently increasing number reflects a trend in pesticide product development, i.e., transition from the use of persistent and less polar compounds to more readily degradable, more (sometimes very) polar, low volatile and/or thermolabile pesticides. Determination of these ‘‘modern’’ pesticides and their metabolites was rather difficult in the past [8]. GC- and LC-MS(-MS) provides several advantages over the use of other GC or LC detectors, which mainly include simultaneous quantitation and structural identification of detected analytes, detection of a wide range of compounds independent of their elemental composition or structure, and possibility to spectrometrically resolve co-eluting peaks. All these features can substantially contribute to the increased sample throughput in the analysis of multiple chemical residues or contaminants, with the latter trait being extremely important in fast chromatographic separations. Thus, the increasing availability, affordability, and performance of GC-MS and LC-MS instruments have led to a growing interest in fast GC and LC separations in recent years. Also, fast separation and detection play an important role in two-dimensional (2D) separations, particularly in comprehensive 2D chromatography. This chapter discusses recent developments in fast and 2D chromatographic techniques and their application in the GC and LC analysis of contaminants and chemical residues in foods. Furthermore, it also reviews current and some novel approaches to overcome matrix effects that may adversely affect quantitative GC and LC-MS analysis of trace components in food matrices.
2. FAST CHROMATOGRAPHIC SEPARATION Faster chromatographic separation reduces the analysis time, which can translate in a significantly increased sample throughput, providing that the entire
Recent Developments in Chromatographic Techniques
177
laboratory operation, including sample preparation and data analysis, is streamlined to keep up with the fast GC or LC determinative step. The GC or LC separation time, given as the retention time tR of the last analyte, can be described by L tR ¼ t0 ðk þ 1Þ ¼ ðk þ 1Þ (1) u¯ where t0 is the time required for the elution of an unretained component, k the solute retention (or capacity) factor, L the column length, and u¯ the average linear velocity of the mobile phase. Therefore, the separation time is decreased by reducing L, decreasing k, and/or increasing u¯. In practice, an increase in separation speed is not for free and some sacrifice must be made in chromatographic resolution (Rs) and/or sample capacity (Qs) in most cases. An existing method can firstly be speeded by minimizing Rs (of important peaks) to a value that is just sufficient for our application, employing for instance shorter columns, higher than optimum mobile phase flow rates, faster temperature programming in GC or steeper mobile phase gradients in LC. A reduction of L decreases the number of theoretical plates N (a measure of separation efficiency) in a directly proportional relationship (L ¼ H N, where H is the plate height) but the impact on Rs is less severe because it is proportional to OL. Thus, practically all fast GC and LC methods utilize shorter columns in combination with other approaches. In GC-MS and LC-MS, Rs is not necessarily the limiting factor in speed because MS has the ability to distinguish between analytes that have some differences in their MS spectra. Thus, except for certain applications, such as chiral separations or congener-specific analysis of dioxins and PCBs, MS can resolve co-eluting peaks spectrometrically. As indicated in Figure 1, MS adds another adjustable degree of control in selectivity (and sensitivity), which allows compensation for a potentially worse GC or LC performance in faster separations [9]. If the gain in speed at the minimum acceptable Rs is not sufficient, the analysis time can be
compensation
Selectivity
Selectivity
(Resolution)
GC or LC
Speed MS
Sensitivity
Sensitivity (Sample Capacity)
compensation
Figure 1 The combination of GC or LC with MS for optimization of speed. The sensitivity and selectivity of each approach can be used to compensate for losses in the other to provide a faster analysis of potentially the same quality. Modified with permission from Ref. [9].
178
Katerina Mastovska
further reduced by shifting the optimum mobile phase velocity (u¯opt) to higher values. Fast GC and LC approaches that can maintain Rs while speeding the analysis are discussed below in greater detail, including the major instrumentation requirements for their practical use. General requirements for instrumentation in fast GC and LC involve the ability to provide and handle the speed. As the speed increases, the peaks become narrower, which poses greater demands on the used instrumentation. Extracolumn contributions to band broadening (in the injector, connections, or detector) may become of critical importance in limiting the potentially available column performance. Also, the detector must be able to record the narrower peaks with an acceptable precision, providing reproducible quantitation and identification characteristics.
2.1 Fast gas chromatography Table 1 lists possible approaches to fast GC derived from the GC theory [9–14] and includes practical considerations associated with their application [10], indicating mainly specific instrument requirements and sacrifices made in Rs and/or Qs. In terms of the speed, modern, commercially available GC instruments offer sample introduction, pressure control, temperature programming, and data acquisition rates sufficient for fast GC with typical separation times of 1–10 min and peak widths (full-width at half-maximum, FWHM) of 0.2–1 s [15]. For very fast and ultra-fast GC (separation times in the range of less than 1 or 0.1 min, respectively), specially designed or exceptional instrumentation is mostly needed (mainly for sample introduction and pressure regulation), thus the application of these approaches in practice is currently very limited [10]. As mentioned earlier, the easiest way to speed an existing method involves minimizing Rs to the extent that is still acceptable for a given purpose. In GC, this can be achieved by employing for instance higher than optimum carrier gas velocities, faster temperature programming rates and/or shorter capillary columns. These simple approaches are often combined with other fast GC techniques to provide an additional gain in speed. Fast temperature programming can be accomplished with conventional GC ovens [16,17], by resistive heating [17–23], or less intensively studied microwave GC ovens [24,25]. Modern oven-based GC instruments provide maximum temperature programming rates of 1–21C/s, but these maximum declared rates for a given instrument are reached only at relatively low temperatures. As the temperature increases, heat losses from the oven to the surrounding air also increase, which may lead to larger time lags between the actual and set column temperatures and less reproducible heating at faster temperature programming rates, resulting in longer analysis times vs. the expected ones and decreased precision of tR measurements [17,26]. In resistive heating, electrical current is employed to heat a conductive material (a metal) that encases the analytical column, thus the thermal mass of the heater is minimized and the heat-up and cool-down rates can be very fast and precise. Commercial systems are available, in which a fused silica capillary
Recent Developments in Chromatographic Techniques
179
Table 1 Possible approaches to faster GC separation and practical considerations associated with their application (see the chapter text for the symbol definitions) Possible approaches to faster GC separation
Practical considerations
(A) kL, reduced column length
Decreased resolution (Rs p OL)
(B) kk, decreased retention factor
Decreased resolution (Rs p k/(k+1); less significant for k W 3) For isothermal analysis only (restricted to analytes with a narrow boiling-point range) Special instrumentation required for temperature rates W 1–21C/s Higher elution temperatures (potential greater thermal breakdown of susceptible analytes) Limited by stationary phase availability (difficult for a wide range of analytes) Special instrumentation required for a coupled-column operation Reduced sample capacity (Qs p df) and ruggedness Increased sample capacity (Qs p d3c ) and ruggedness
(1) Higher isothermal temperature
(2) Faster temperature programming
(3) Altered stationary phase (of a single column or coupled columns) to improve selectivity (4) Thinner film of the stationary phase (5) Larger diameter capillary column (for fixed column length) (C) mu¯, increased carrier gas velocity (1) u¯ W u¯opt, higher than optimum carrier gas velocity (2)mu¯opt, increased optimum carrier gas velocity (a) Hydrogen as a carrier gas
(b) Vacuum outlet operation (low-pressure GC)
(c) Smaller diameter capillary column (for fixed resolution)
Decreased resolution (H W Hmin, Rs p 1/OH) Instrumentation limited (GC pressure limit, MS pumping capacity and sensitivity) Constant resolution (H ¼ Hmin, Rs ¼ constant) Safety concerns Potential inertness problems Reduced GC inlet pressure requirements Source of vacuum required for operation (inherent to MS) Restriction capillary or special injection technique required for sample introduction into the column kept at subambient pressures Reduced sample capacity (Qs p d3c ) and ruggedness Increased GC inlet pressure requirements
Source: Reprinted with permission from the publisher Elsevier from Ref. [10].
180
Katerina Mastovska
column is coiled together with a heating wire or inserted into a resistively heated metal tube, achieving temperature programming rates up to 201C/s [17–23]. A practical drawback of these systems is the difficulty in accessing the column to perform routine maintenance. Besides much faster temperature programming rates, the resistive heating technique provides very good tR repeatability and rapid cooling down, which results in higher sample throughput, even if the same temperature programming rate is applied in an oven-based GC as demonstrated in rapid pesticide multiresidue analysis in various food crops [17–19]. Another possible approach to faster GC is to optimize selectivity (ability to distinguish between compounds) with respect to the utilization of time. In GC, the use of one type of stationary phase over another may increase the separation speed only to a small degree. However, a sequential combination of two different GC columns (2D GC) may provide improved or equivalent separation selectivity in a shorter amount of time. Among 2D GC approaches, pressure-tunable (flow modulation) GC-GC developed by Sacks et al. [27–29] is predominantly aimed at analysis time reduction. In this technique (commercially available as stop-flow GC [30]) the carrier gas pressure is programmed at the junction of two, serially coupled columns with different stationary phase chemistries. An increase in the junction point pressure reduces the flow in the first column and accelerates the flow in the second column, resulting in increased residence time in the first column and decreased residence time in the second column. This increases the influence of the stationary phase chemistry of the first column and decreases the influence of the second column (a reduction in the junction point pressure has the opposite effect). Thus, pressure-tunable GC-GC can alter retention patterns by programming the column ensemble selectivity, which can be used to improve the quality of the separation with respect to the utilization of time. A drawback of this approach involves a tedious method development including optimization of pressure programming and selection of suitable columns, especially if complex compound mixtures have to be separated. The GC analysis can be speeded without sacrificing Rs by increasing the diffusivity of the solute in the mobile phase (using hydrogen as a carrier gas or operating the column at lower pressures) or using narrower columns. In addition to the increased u¯opt, a reduction of column inner diameter (dc) of a thin-film capillary column also results in a proportionally decreased H, thus a higher efficiency per L. Therefore to maintain Rs while increasing the analysis speed, the use of a narrower column must be accompanied by a proper reduction in L (L to dc ratio should be kept constant [12]). A significant disadvantage of this approach involves substantial sacrifice in Qs, which is proportional to d3c. Moreover, a thinner film of the stationary phase (df) is often used in combination with narrower columns (to keep the phase ratio constant), resulting in a further decrease in Qs (directly proportional to df). With respect to dc, capillary columns can be divided into several groups [9]: (i) megabores (dcX0.5 mm; commercially available 0.53 mm); (ii) wide bores (0.3pdco0.5 mm; 0.32 and 0.45 mm); (iii) narrow bores (0.2pdco0.3 mm; 0.20, 0.25, and 0.28 mm); (iv) microbores (0.1pdco0.2 mm; 0.10, 0.15, and 0.18 mm); and (v) sub-microbores (dco0.1 mm; various dc commercially available). Table 2
Recent Developments in Chromatographic Techniques
181
Table 2 Relative speed, Qs and column head pressure (p) calculated for different dc at the same separation efficiency (L/dc ¼ 100,000) and phase ratio (dc/df ¼ 1,000) using He carrier gas at speed-optimized flow rate (SOF) and 1001C column temperature (see the chapter text for the symbol definitions) dc (mm)
L (m)
SOF (mL/min)
t0 (min)
Relative speed
Relative Qs
p (psi)
0.53 0.32 0.25 0.20 0.10 0.05
53 32 25 20 10 5
4.24 2.56 2.0 1.6 0.8 0.4
2.72 1.25 0.89 0.67 0.30 0.15
1 2.18 3.05 4.06 8.97 8.5
100 22 10.5 5.4 0.67 0.084
6.7 14.9 21.3 28.9 68.7 150.2
Source: Modified with permission from Ref. [12].
compares relative speeds that can be achieved for columns of different dc at the same separation efficiency and phase ratio. This table also demonstrates the sacrifice in Qs (hence sensitivity) that has to be made for an increase in speed using microbore or sub-microbore columns. For instance, as compared to a standard 0.25 mm i.d. column, 3- and 6-fold gains in speed are obtained at the cost of 16- and 125-fold lower Qs in the cases of 0.10 and 0.05 mm i.d. columns, respectively. In this respect, short megabore columns may offer a viable alternative to microbore columns in fast analysis of trace components, especially when combined with MS to compensate for decreased separation efficiency.
2.1.1 Fast gas chromatography with short microbore columns The use of short microbore columns represents an attractive approach to fast GC but several practical aspects have to be considered, especially in routine analysis of trace components in complex matrices, such as in food samples. Important concerns associated with application of columns with a smaller dc include pressure requirements necessary for their operation, injection difficulties, analyte detectability, and method ruggedness [12,31–33]. Table 2 shows increasing pressure requirements necessary for operation of columns of a smaller dc. Most common GC instruments allow maximum column head pressure of 100 psi (690 kPa), some provide 150 psi. Thus, the calculated head pressure value for a 0.05-mm i.d., 5 m long capillary column (at 1001C, He as a carrier gas) is at the limit of the commercially available GC instruments at this time. The use of H2 instead of He can lower the pressure requirements. For instance, if H2 was used instead of He at the same flow, the column head pressure for a 0.05-mm i.d. column in Table 2 would drop from 150 to 102 psi. However, the operation of the sub-microbore columns is restricted to low flow rates and temperatures even if H2 is employed as a carrier gas. Thus currently, the use of microbore columns (dcX0.1) seems to represent a practical limit for common GC instrumentation.
182
Katerina Mastovska
Injection is a crucial step in fast GC because the introduced sample vapor plug has to be sufficiently narrow to minimize the input band width. Split injection is generally favored over non-splitting injection techniques because of its speed, which is however achieved at the expense of reduced sensitivity, especially in the case of very high split ratios. In splitless injection, only the column flow is utilized for sample transfer from the injector liner to the column, thus effective refocusing of the initial band is required. In columns with a smaller dc, refocusing becomes more difficult because the length of the flooded zone increases with decreasing dc. Therefore, cryofocusing or coupling with a short retention gap of a larger dc (also suitable for on-column injection in fast GC) are often necessary to prevent severe discriminations and peak distortions in this case [33]. A programmed temperature vaporizing (PTV) injection in solvent vent mode can eliminate the problems caused by column flooding, however other practical limitations associated with the use of microbore columns remain. In addition to instrumental requirements, analyte detectability and method ruggedness are two important concerns in real-world analysis using columns with a smaller dc. Microbore columns produce sharper, thus taller peaks, but this effect usually does not fully compensate for the lower sample amount injected. Moreover, the peak-sharpening effect does not improve detectability (signal to noise ratio, S/N) in applications, in which matrix interferences are the limiting source of noise. Also, the repeated injections of matrix extracts deteriorate the performance of microbore columns faster as compared to the columns with a larger dc, resulting in a more frequent need for column maintenance [26]. In many respects, the use of 0.15 mm i.d. columns seems to be a reasonable compromise between speed and other issues in real-world analysis of sample extracts, such as in the analysis of pesticide residues in food samples [31]. Various applications of microbore columns in the analysis of food contaminants and chemical residues (such as pesticides, PCBs, or PAHs) have been reported in the literature [9,14], often combining microbore columns with a high-speed time-offlight (TOF) MS instrument that provides fast data acquisition rates (up to 500 spectra/s is currently available with a commercial instrumentation) for adequate recording of narrow peaks. A unique application of short, (sub-)microbore columns involves their use in the comprehensive GC GC technique, where they serve as second dimension columns for very fast separations of modulated peaks eluting from the first dimension (see the discussion on GC GC later in this chapter).
2.1.2 Fast gas chromatography with short megabore columns As discussed earlier, short megabore columns provide several benefits as compared to microbore columns, including higher Qs, improved ruggedness and less instrumentation problems associated with their use [26,34]. However, they have to be combined with a highly selective detection technique, such as MS, to compensate for decreased separation efficiency in fast GC applications. When connected to MS as a source of vacuum, short megabore columns can be operated at lower pressures along the entire column length. Lower column pressures lead to higher diffusivity of the solute in the gas phase, which shifts
Recent Developments in Chromatographic Techniques
183
u¯opt to a higher value, resulting in faster GC separation as compared to the use of the same column operated at atmospheric outlet pressure conditions [35]. A practical problem associated with the direct connection of a short megabore column to MS involves extension of sub-ambient conditions to the injector unless precautions are made. Special injection techniques for sub-atmospheric pressure conditions have been tested with varying degrees of success [36,37], but the simplest way to solve this injection problem is to employ a short, narrow restriction capillary connected to the front of the wider analytical column [37,38]. In this manner, the analytical column is kept under low-pressure conditions, but the inlet remains at usual GC inlet pressures, thus the same injection methods can be used as in conventional GC. An additional benefit is that the restriction column also serves as a retention gap (or guard column) in the analysis of relatively dirty samples [39]. As for the analysis of food contaminants and residues, low-pressure (LP) GC-MS has been successfully applied mainly in the analysis of pesticide residues in various produce matrices using single quadrupole [26,39], TOF [40], triple quadrupole [41], or ion trap [42–44] MS instruments. As mentioned earlier, the use of megabore columns in LP-GC-MS provides increased Qs and improved ruggedness. However, the sensitivity of conventional MS instruments at higher flow rates in LP-GC-MS may be a limiting factor in the attainable speed in practice [39]. Conventional MS instruments work optimally at 1–2 mL/min effluent flows and, even if the MS pumping capacity is not exceeded, sensitivity can be significantly reduced at higher flow rates. This is not true for the supersonic molecular beam (SMB) GC-MS technique (developed by Amirav et al. [45–49]), which is well suited for the use of high flows because SMB-MS requires high gas flow rates for its operation (up to 240 mL/min is possible with the prototype instrument). The high column flows in SMB-MS enable very fast analyses, especially when combined with a short megabore column. They also facilitate very fast sample introduction using splitless injection without a need for cryofocusing (as compared to a microbore column operated at low flow rates), thus eliminating cool-down times. The use of a megabore column results in wider peaks that can be recorded using a conventional quadrupole MS even for ultrafast run times. In addition to an increase in speed, the fast flow rates and other unique features of GC-SMB-MS also enable analysis of thermally labile and lowvolatility analytes, such as carbamate pesticides [46] or large PAHs [48], thereby extending the scope of GC-MS to compounds currently done only by LC. In GC-SMB-MS, organic molecules pass through a small opening (about 0.1 mm i.d.) placed between the GC outlet and the MS, form an SMB by coexpansion with a carrier gas into vacuum and are vibrationally supercooled in the process. As a result, an enhanced molecular ion occurs practically for all molecules, increasing the MS detection selectivity in electron ionization (EI). SMBMS still provides typical EI fragmentation patterns, thus enabling conventional MS library searching, but with a higher confidence in correct compound identification due to the presence of a prominent molecular ion [49]. The potential and beneficial features of GC-SMB-MS have been demonstrated in numerous applications; however, the lack of commercial availability is
184
Katerina Mastovska
currently a severe limitation in the applicability of this fast GC-MS approach in practice.
2.2 Fast liquid chromatography Basic approaches to fast LC are very similar to fast GC approaches presented in Table 1. Of course, differences exist due to a simple fact: LC employs liquid not gaseous mobile phases. Apart from different physico-chemical properties of the mobile phase, LC is much more versatile technique than GC because both stationary and mobile phase affect the separation. A myriad of stationary and mobile phase combinations can be used, enabling selectivity optimization for enhanced separation and/or increased speed. Similarly to GC, an existing method can be speeded up by employing higher than optimum mobile phase flows and/or shorter columns. Faster temperature programming in GC can be compared to faster (steeper) mobile phase gradients in LC, resulting in faster analyte elution as the mobile phase strength increases more rapidly. Also, fast isocratic runs can be used for analytes of relatively narrow polarity range. The benefit of isocratic elution is the elimination of column reequilibration to the initial mobile phase conditions, which greatly improves the throughput. A fast isocratic run in LC is an analogy to a fast isothermal analysis in GC, which also provides high-throughput due to the elimination of cool-down times, but is restricted to analytes with a narrow boiling point range. High sample throughput represents an ultimate goal in many applications. Pharmaceutical industry currently drives the development and utilization of highspeed, high-throughput LC and LC-MS approaches, especially in the area of drug discovery and development [50]. Even if very short columns and ballistic gradients are used, a lot of time can be wasted during column cleaning and reequilibration, injection of the next sample, etc. Thus to fully utilize the detector time, several columns can be operated in parallel, with only the chromatographic window of interest from each LC separation being transferred into the detector (usually MS) [51]. The simplest approach involves the use of an alternating twocolumn (dual-column switching) system that separates analytes on one column using a gradient provided by a binary pump, whereas the second column is being re-equilibrated for the next run with a simple isocratic pump [52]. More complex techniques, such as staggered injections [53] or multiplexing [54], require more sophisticated instrumentation to minimize the detector downtime, resulting in significantly increased sample throughput mainly in single-analyte applications. As in GC, fast LC approaches that do not necessarily sacrifice separation efficiency for speed are attractive in practice, especially in multicomponent analysis. The use of LC-MS(-MS) may allow compromises in Rs, but a certain degree of separation is beneficial for creating different analyte windows (e.g., for single-run analysis of compounds ionized in positive and negative modes) and/or for separation from matrix components that can affect analyte ionization (as discussed later in this chapter in the section dealing with matrix effects). As discussed earlier, the LC analysis can be speeded up without sacrificing Rs if the optimum mobile phase velocity (u¯opt) is shifted to higher values by improving
Recent Developments in Chromatographic Techniques
185
mass transfer. In practice, this can be accomplished by employing columns with small particle sizes (dpo 2 mm), monolithic columns, and/or mobile phases at elevated temperatures.
2.2.1 Fast liquid chromatography using small particle sizes According to the chromatographic theory, as dp decreases, the separation efficiency increases because N is inversely proportional to dp, and so is u¯opt. Thus, columns with smaller dp can provide an increase in speed due to higher u¯opt. Although this theory has been well-known for decades, the practical application of this approach has been difficult for several reasons. The operation of small dp columns at high flow rates creates high backpressures (often exceeding 10,000 psi), requiring special instrumentation that enables injection of samples and reproducible mobile phase pumping at these pressures. Moreover, the entire LC system must have very low extra-column volumes to preserve the separation efficiency. Another challenge involves the design and development of sub-2 mm particles and their packing into reproducible and rugged columns [55]. Also, the samples must be well filtered to prevent clogging of the frits holding the particles in the column. Recently, two manufacturers introduced columns with smaller particles (1.7 and 1.8 mm) together with compatible LC systems, providing adequate pressure limits, injection systems, low extra-column volumes, as well as fast MS detection for narrow peaks. One manufacturer termed the technology as ultra performance liquid chromatography (UPLC) [56], whereas the other describes the columns as suitable for rapid resolution LC. The UPLC term and technology is spreading throughout the scientific community, which can be demonstrated by a number of studies evaluating this approach in various applications, including mainly those in the pharmaceutical and bioanalytical fields, but also in multiresidue analysis of pesticides [57,58], veterinary drugs [59] or heterocyclic amines [60] in various food matrices. Figure 2 compares high-performance liquid chromatography (HPLC)- and UPLC-MS/MS multiresidue analyses of 17 selected pesticides in a baby-food sample. Very recently, ‘‘fused-core’’ technology has been introduced, which produces 2.7 mm particles with a 0.5-mm porous shell fused to a solid core [61]. The porous shell decreases the diffusional mass transfer path as compared to totally porous particles. Thus, similar resolving power might be achieved as with sub2 mm totally porous particles at comparable or even higher speeds without high backpressures. Another, more explored alternative is the use of monolithic columns.
2.2.2 Fast liquid chromatography using monolithic columns Monolithic columns consist of one piece of an organic polymer or silica with flowthrough pores [62,63]. In this continuous phase of porous material, the size of flow-through channels and the depth of the pores that are accessible only by diffusional mass transfer may be optimized independently, enabling simultaneous maximization of column permeability and mass transfer. For example, recently
186
Katerina Mastovska
Figure 2 Comparison of (i) HPLC-MS/MS and (ii) UPLC-MS/MS analysis of 17 pesticides in a potato-based baby food matrix. Insets show expanded peaks for terbufos sulfone (0.01 mg/kg), demonstrating the peak width differences. Reprinted with permission from Ref. [57].
reported silica monoliths with permeability similar to that of a column packed with 5 mm particles were able to attain separating power of columns packed with 2–2.5 mm particles [64]. As a result, monolithic columns can offer highly efficient separations with low resistance to hydraulic flow, thus operation at high flow rates without high backpressures. Figure 3 compares monolithic columns to
Recent Developments in Chromatographic Techniques
187
Figure 3 Comparison of (a) highly permeable and less-efficient packed columns with large particles, (b) less-permeable and highly efficient packed columns with small particles, and (c) highly permeable and highly efficient monolithic columns. Reprinted with permission from Ref. [63].
columns packed with large and small particles, demonstrating the differences in column permeability and efficiency. Monolithic columns have been used mainly for fast separations of large molecules, such as proteins or peptides, which significantly benefit from improved mass transfer because their diffusion coefficients are several orders of magnitude smaller than the diffusion coefficient of smaller molecules [63]. Although monolithic columns are commercially available, the current selection of stationary phases is rather limited. However, this situation may change in the future due to the increasing trend towards faster LC separations.
2.2.3 Fast high-temperature liquid chromatography The application of elevated temperatures in high-temperature LC (HTLC) decreases viscosity of the mobile phase and increases analyte diffusivity, which leads to lower backpressures and increased mass transfer, respectively [65]. As a result, LC columns can be operated at higher flow rates, reducing the analysis time without making significant sacrifices in the separation efficiency. Moreover, elevated temperatures can be employed in the combination with small particle size columns, thus providing an additional gain in speed or separation efficiency, while keeping the backpressure within reasonable limits. Also, temperature programming of the column can change separation selectivity, which may improve analyte separation or serve as an alternative to solvent gradient. Another attractive aspect involves the use of superheated water (at 100–200 1C) as a potential replacement for medium-polarity mobile phases (such as acetonitrile–water mixtures) in reversed-phase LC [66,67]. This would reduce solvent and waste costs and simplify system operation. Under high-temperature conditions, water behaves as a moderate polarity solvent because its dielectric constant decreases from about 80 to about 35 over the range 25–2001C [68], while it retains an appreciable density (W 0.85 g/mL), cohesive energy, and hydrogen bonding potential [69]. Until recently, the application of HTLC was rather difficult in practice due to instrument and column limitations. Instrumentation for HTLC is now available, which allows operation at temperatures up to 2001C with mobile phase
188
Katerina Mastovska
preheating to eliminate thermal mismatch [70]. The thermal mismatch occurs when the cool mobile phase enters the heated column and warms up faster along the walls, leading to band broadening due to the faster flow of the mobile phase along the column wall than in the centre [71]. Another practical concern involves the stability of the stationary phase at the elevated temperatures. Conventional, reversed-phase LC columns with silicabased stationary phases are stable at temperatures up to 901C (50–601C limit is more common). Stationary phases with higher temperature stability are based mainly on zirconium oxide, although graphitized carbon or rigid polystyrene– divinylbenzene phases can also tolerate elevated temperatures [70]. With the recent advancements in column technology and instrumentation, HTLC may soon become a practical tool, especially in the combination with narrower columns and/or columns with small particle sizes and in applications that can tolerate higher temperature with respect to the analyte stability.
3. TWO-DIMENSIONAL CHROMATOGRAPHIC SEPARATION 2D GC or LC separations involve the use of two coupled columns of different selectivity (or capacity) to provide improved separation for sections (heartcuts) of one-dimensional (1D) chromatogram or for the whole first dimension separation (in comprehensive 2D chromatography) [1]. In standard heart-cutting techniques, only a single or a few small fractions of the first dimension effluent are transferred to the second column for further separation to enhance resolution of compounds eluting in specific region(s). In GC, heart-cutting is employed (using somewhat complex instrumentation) mainly for detailed characterization of petroleum products or flavors and fragrances [72]. It can be also utilized in congener-specific analysis of PCBs [73]. In standard 2D LC, the two columns are usually coupled using a low-dead volume switching valve (or a series of valves in advanced systems) that manages the mobile flow direction, including transfer of sample components between the columns. The basic requirement involves compatibility of the mobile phase flow and strength with the transfer to the second column. Thus, the mobile phase eluting from the first column should have a lower flow rate, should be weak in respect to the secondary column separation mechanism, and should be miscible with the mobile phase for the second column. As a result, only a limited number of stationary phases of different selectivity are compatible. Examples of compatible columns include ion-exchange with reversed-phase or size-exclusion with normal, reversed-phase, and/or ion-exchange. In a sense, clean-up procedures, such as solid-phase extraction (SPE), size-exclusion or turbulent flow chromatography, coupled on-line to LC can also be considered 2D separations, introducing a fraction containing analytes to the analytical column and diverting the removed matrix components to the waste. Using special interfaces enabling large volume injections of LC effluents, LC can be coupled to GC [74]. In LC-GC, the role of LC is to perform selective cleanup, concentration and/or fractionation of the sample, whereas GC serves as a
Recent Developments in Chromatographic Techniques
189
determinative step. Recently, the applicability of comprehensive LC GC has been evaluated, showing a great potential of this technique for characterization of certain complex samples, such as edible oils and fats [75]. As opposed to the heart-cutting techniques, comprehensive 2D chromatography requires each component or fraction eluting from the first column to be subjected to a second separation system using different, ideally independent separation mechanism (orthogonal selectivity). As a result, the peak capacity of comprehensive 2D chromatography is significantly increased and can be estimated by multiplying the peak capacity of the first and second dimension separations [76]. The introduction and commercialization of comprehensive 2D GC (GC GC) are probably the most exciting recent developments in GC. As for comprehensive 2D LC (LC LC), this technique is still more or less at the stage of exploration, but its potentials have been already demonstrated in a number of complex separations, including mainly those in the area of proteomics and metabolomics [77,78].
3.1 Comprehensive two-dimensional gas chromatography Comprehensive 2D GC, GC GC, employs two columns of different selectivity coupled by a special interface or modulator that can sample or collect the effluent from the first column and introduce it periodically (about every 3–6 s) to the second column [79–85]. In terms of column dimensions, the first column is usually a conventional GC capillary column (typically 15–30 m 0.25 mm i.d.), whereas short (sub-)microbore columns are used as the second dimension columns (0.5–2 m 0.1 mm i.d. or even 0.05 mm i.d.) to provide very fast separations (in a few seconds) with minimum broadening of the very narrow bands generated by the modulator. To create an orthogonal-selectivity system in GC, the first column should have a non-polar stationary phase (typically 100% dimethylpolysiloxane or 5% phenyl/ 95% dimethylpolysiloxane), which provides separation based solely on volatility (boiling point) of the analytes. As a result, each small fraction eluting from the first column will contain analytes of very similar volatilities. The runs in the second dimension are very fast, thus performed almost isothermally. Therefore, there is practically no contribution of boiling-point-based separation in the second column, with the analyte retention being based on specific interactions with the stationary phase, such as hydrogen bonding, p–p interaction, steric effects, etc. Typical stationary phases for the second dimension include W35% phenyl/o65% dimethylpolysiloxane or polyethyleneglycol (Carbowax). It should be noted that, in certain specific applications, non-orthogonal systems (such as polar nonpolar or polar polar columns) may provide some benefits [86], but the orthogonal column combination described above (non-polar polar columns) is generally preferred in practice, especially for group-type analysis or classification purposes. Various GC GC modulators have been developed, mainly based on cryogenic focusing. A current, prevalently used commercial system employs a nonmoving quad-jet dual stage thermal modulator [87] consisting of two sets of dual
190
Katerina Mastovska
(A)
Stage 1 cold
(B)
Stage 2 cold
Stage 2
I
hot
tI hot
cold tI
II
tII
tIII
tIV tI
tII
tIII
tIV
tII cold
cold Stage 1
cold
hot
III tIII cold
tI
hot
tII
tIII
tIV tI
tII
tIII
tIV
IV tIV
modulation period
next modulation period
cold
second column
Figure 4 Illustration of (A) the GC GC modulation process using a non-moving quad-jet dual stage thermal modulator located at the junction of the first and second column and (B) the modulation period, including hot and cold pulse durations. A single modulation period consists of four distinct steps: (I) a fraction of solutes eluting from the first column is trapped using a cold pulse produced by the first trapping zone (stage 1) of the modulator; (II) a hot pulse then releases the trapped solutes to the second trapping zone (stage 2) that is cold at that moment; (III) stage 2 continues to retain the solutes while stage 1 cools again; and (IV) stage 2 releases the solutes with a hot pulse to the rest of the secondary column. The duration of each step are symbolized by tI–tIV. Reprinted with permission from Ref. [96].
(‘‘cold’’ and ‘‘hot’’) jets that create two trapping zones (stages) at the beginning of the second column. Cold and hot jets supply in pulses N2 (cooled by liquid N2) and heated air, respectively. Figure 4 shows four distinct steps that take place during a single modulation period using the quad-jet dual-stage thermal modulator. The modulation period must be short enough to preserve the 1D separation. In this respect, it is recommended to take at least three samples (slices) across a peak eluting from the first column [88]. The peaks eluting from the second column are very narrow (typical basewidths of 100–200 ms), thus require the use of fast detectors with small internal volumes, such as flame ionization detectors (50–200 Hz data acquisition frequency), micro electron capture detector (50 Hz), high-speed TOF MS (up to 500 spectra/s) or quadrupole MS with a limited scan range [89]. High-speed TOF MS is probably the most popular detector, providing full MS spectra information and enough data points for adequate characterization of the narrow secondary peaks. Figure 5 illustrates the process involved in generation and visualization of a GC GC chromatogram. The outcome of a GC GC run is a series of fast secondary chromatograms, which are usually stacked side-by-side to form a 2D plot (array) with the first dimension representing the retention time on the first column and the second dimension, the retention time on the second column. After this transformation, it is possible to visualize the chromatograms using contour
Recent Developments in Chromatographic Techniques
191
Figure 5 Generation and visualization of a comprehensive GC GC chromatogram. Reprinted with permission from Ref. [83].
plots, where the peaks are displayed as spots on a plane using colors, shading, and/or contours to indicate the signal intensity [83]. The peak intensity can be used as the third dimension in 3D plots, which generally have less practical value but provide attractive figures in data presentations. Numerous applications of GC GC (mainly GC GC-TOF MS) have been reported in the literature. The applications pertinent to the analysis of contaminants and chemical residues in food include mainly the analysis of pesticide residues [90,91], PCBs [92–94], PCDDs and PCDFs [94–96], or PBDEs [97]. In addition to the improved selectivity (increased analyte–analyte and analyte–matrix separation), GC GC also provides improved sensitivity due to the focusing effect in the modulator. As a result, analyte detectability can be improved significantly.
4. OVERCOMING ADVERSE MATRIX EFFECTS In general, matrix effects are all adverse phenomena caused by unavoidable presence of co-extracted matrix components, leading to inaccurate quantitation,
192
Katerina Mastovska
decreased method ruggedness, low analyte detectability and/or even reporting of false positive or negative results [98]. The most obvious matrix effects are coelutions of matrix components with analytes that affect analyte detection. Those effects can be overcome by improved selectivity of detection (e.g., using MS or MS-MS), separation (e.g., using 2D chromatography), and/or sample preparation. There are, however, matrix effects that are more difficult to manage because the culprit cannot be easily eliminated. These effects include mainly matrix-induced response enhancement in GC and signal suppression or enhancement in LC-MS with atmospheric pressure ionization (API) techniques.
4.1 Approaches to overcome matrix effects in gas chromatography Matrix-induced response enhancement, first described by Erney et al. [99], is a matrix effect well-known mainly in the GC analysis of pesticide residues in food, negatively impacting quantitation accuracy of certain susceptible analytes [98]. When a real sample is injected, the matrix components tend to block active sites (mainly free silanol groups) in the GC inlet and column, thus reducing losses of susceptible analytes caused by adsorption or degradation on these active sites. This phenomenon results in higher analyte signals in matrix-containing vs. matrixfree solutions, thus precluding the convenient use of calibration standards in solvent only, which would lead to overestimations of the calculated concentrations in the analysed samples. In theory, elimination of active sites or matrix components would overcome the matrix-induced enhancement effect; however, absolute and permanent GC system deactivation or thorough sample clean-up are virtually impossible in practice [100]. Careful optimization of injection and separation parameters (such as the injection technique, temperature, and volume; liner size and design; solvent expansion volume; column flow rate; and/or column dimensions) can lower the number of active sites (due to a decreased surface area) or shorten the analyte interactions with them. This results in a reduction but rarely complete elimination of the effect. For instance, application of a pressure pulse or temperature programming during the injection (to reduce residence time or thermal degradation in the injection port) may serve as examples of this effort [101–104]. Since an effective elimination of the sources of the matrix-induced response enhancement is not likely in practice, the analysts often try (or are required) to compensate for the effect using alternative calibration methods. The current compensation approaches include the use of matrix-matched standards, standard addition method, and isotopically labelled internal standards (not feasible in multianalyte analysis due to their unavailability and/or prohibitive price). All of these techniques require extra labour and costs; moreover, they may still lead to quantitation inaccuracies because the extent of the effect depends on analyte concentration and matrix composition [105] (problems in the case of standard addition and matrix-matching, respectively). Matrix-matched standardization is thus far the most widely used approach in spite of its imperfections including a rather time-consuming and laborious
Recent Developments in Chromatographic Techniques
193
preparation of matrix-matched standards and need for an appropriate blank material (ideally the same as the analysed samples). The matrix-matching procedure becomes especially onerous when different commodity types are to be analysed in one batch of samples, which is often the case in routine pesticide residue analysis. Recently, a concept of ‘‘analyte protectants’’ has been introduced in the GC analysis of pesticide residues [106,107], but can be applied to other analytes as well. Analyte protectants are compounds that strongly interact with active sites in the GC system, thus decreasing degradation and/or adsorption of co-injected analytes. The concept idea is to add suitable analyte protectants to sample extracts as well as matrix-free (solvent) standards to induce an even response enhancement in both instances, resulting in effective equalization of the matrixinduced response enhancement effect. A mixture of 3-ethoxy-1,2-propanediol, gulonic acid g-lactone, and sorbitol was found to be the most effective for the volatility range of GC-amenable pesticides [107] as demonstrated in Figure 6, which compares peak shapes and intensities of three selected pesticides obtained in solvent standards and matrix extracts with and without the addition of the above mixture of analyte protectants. In addition to the compensation for matrix-induced response enhancement, the application of analyte protectants can also significantly reduce another matrix effect called matrix-induced response diminishment [26,108]. This effect is caused by gradual accumulation of non-volatile matrix components in the GC system, resulting in formation of new active sites and gradual decrease in analyte responses. The use of analyte protectants provides GC system deactivation in each injection, resulting in improved ruggedness and a less frequent need for the GC system maintenance [107]. Another way how to overcome gradual build-up of non-volatile matrix components is to remove them from the system after each analysis. This can be accomplished using a special injection technique called direct sample introduction (DSI) [109]. In DSI, a liquid (or solid) sample is placed in a disposable microvial. After this step, the microvial is introduced into the injection port using a manual probe or more recently using an autosampler. In the automated version, called DMI (difficult matrix injection) or recently introduced Linex (automated liner exchanger), the liquid sample (up to about 20–30 mL) is injected into the microvial placed in a liner, which is then inserted into the inlet [110–114]. After solvent evaporation, the inlet is rapidly heated and analytes transferred to the column for a GC separation. When the GC run is completed, the liner with the microvial is removed from the system together with non-volatile matrix components, which remain in the disposable microvial. In comparison with other injection techniques, DMI incorporates greater glass surface area in the inlet, which needs to be deactivated. Also, the activity of the inlet may vary greatly throughout the GC sequence because a new (different) liner and microvial are introduced into the system each time. In this respect, the use of analyte protectants was demonstrated to offer more convenient and effective solution than standard silanization of glass surfaces, thus another benefit in addition to the compensation for matrix-induced response enhancement [113].
194
Katerina Mastovska
A) without analyte protectants
B) with analyte protectants
1.12x
a) Lindane Cl Cl
Injection in: matrix solvent
Cl
Cl
Cl Cl
b) Phosalone S
Cl N O
S
3.98x
P O O
O
c) o-Phenylphenol 2.16x OH
10.6x
Figure 6 Comparison of peak shapes and intensities of three selected pesticides (with different susceptibility to the matrix-induced enhancement effect) obtained by injection in matrix (fruit extract) and solvent (acetonitrile) solutions (A) without and (B) with the addition of analyte protectants (ethylglycerol, gulonolactone, and sorbitol). The numbers demonstrate signal (peak height) enhancement factors (signal in matrix vs. solvent) obtained without the use of analyte protectants and improvement in o-phenylphenol signal intensity in matrix with the use of analyte protectants. Reprinted with permission from Ref. [107].
4.2 Approaches to overcome matrix effects in liquid chromatographymass spectrometry In LC-API-MS, the co-eluting matrix components can suppress or enhance analyte ionization, leading to lower or higher signals in the presence of matrix [98,115,116]. The exact mechanism of matrix suppression/enhancement is not known, but the matrix components are assumed to interfere in the spraying, ionization, and evaporation processes, including droplet formation, competition for the droplet surface and proton transfer, or ion-pair formation [117–119].
Recent Developments in Chromatographic Techniques
195
The signal suppression effect is observed mainly in electrospray ionization (ESI), whereas the enhancement effect is more likely to occur when atmospheric pressure chemical ionization (APCI) is employed [120]. For analytes that provide acceptable signals in different ionization modes, a change from ESI to APCI or from positive to negative-ion mode (and vice versa) may provide a feasible approach to elimination or reduction of the matrix effects [121]. Also, the optimization of mobile phase composition may be helpful in certain applications [122]. In general, the matrix effects in LC-API-MS can be eliminated if the co-eluting matrix components are removed from the sample extract or separated from analytes in the chromatographic run. In practice, improved sample preparation (more selective extraction and/or clean up) or LC separation can be a solution to the suppression/enhancement effect in the analysis of a smaller number of analytes, but the elimination is more difficult in multicomponent analysis, such as in the analysis of pesticide residues. Another possibility is to reduce the concentration of co-eluting matrix components by diluting the sample and/or injecting a smaller sample volume [122–124], which reduces the matrix effects, but also decreases analyte detectability. Similarly, reduced suppression was observed in nano-ESI [125] or with post-column splitting to reduce the LC flow rate in ESI [126]. As in GC, compensation approaches, such as the use of matrix-matched standards, standard addition method, or isotopically labelled internal standards,
Figure 7 An example of echo and sample peaks obtained for the same analyte (a pesticide, propoxur) using the echo peak technique, involving two subsequent injections of a sample extract and solvent standard with the same propoxur concentration. Reprinted with permission from Ref. [120].
196
Katerina Mastovska
are often employed in practice with similar practical drawbacks and limitations as described earlier. As mentioned earlier, isotopically labelled internal standards are very effective, but their application is limited due to their unavailability or high price. An interesting alternative to the labelled internal standards is so-called echo peak technique [127], which has been evaluated in the analysis of pesticide residues [120,128] and antibiotics [129]. The echo peak technique involves injections of the sample and standard solution within a short time period using a relatively simple instrumentation [120,127–129]. As a result, the analyte peak from the sample elutes in a very close proximity to the analyte peak from the standard solution, which forms an echo peak (Figure 7). It is expected that these two closely eluting peaks are affected by the co-eluting matrix components (usually larger peaks) to the same extent. This approach can be quite effective, but 100% compensation may not be achieved for all analytes/matrices. Still, it represents an attractive method in routine pesticide or veterinary drug screening, because it offers some additional benefits, such as direct comparison of analyte concentrations in the sample with critical standard concentrations (e.g., with lowest calibration levels or maximum residue limits) and a quality control measure present in each LC run to check for retention time shifts, sensitivity or other LC-MS instrument problems.
5. FUTURE TRENDS Current trends towards high-speed, high-throughput analysis are likely to continue spearheading the development in both GC and LC, especially in the combination with MS detection. Very fast separations also play a pivotal role in comprehensive 2D chromatography. GC GC has already made the transition from research to routine laboratories. And, it is only a matter of time when LC LC and LC GC become techniques of choice in applications that can benefit from their separation power. Current, commercially available instrumentation reflects the trend towards increased speed, providing faster data acquisition rates in MS, low dead volumes, new column technologies, rapid and precise temperature and pressure programming in GC or fast mobile phase gradients and column heating in LC. This trend will continue for both hardware and software components. In particular, fast and reliable automated data processing is highly desirable in routine practice because it is currently one of the limiting factors in the implementation of fast and 2D chromatography. Furthermore, routine laboratories will start fully benefiting from fast chromatography if the sample preparation becomes also faster. In this respect, techniques and instrumentation that offer more rugged, sensitive, and selective analysis have a better chance of being implemented because they can tolerate dirtier, minimally processed samples. The obvious trend towards minimum sample preparation leads to higher chances of more pronounced matrix effects that need to be managed properly. In this respect, techniques, such as echo peak in LC-MS or analyte protectants with DSI/DMI in GC-MS, may provide convenient and quite
Recent Developments in Chromatographic Techniques
197
effective alternatives to the current approaches, such as matrix-matched standardization.
REFERENCES 1 2 3 4 5 6 7 8
9 10
11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39
C.F. Poole, The Essence of Chromatography, Elsevier, Amsterdam, The Netherlands, 2003. J. Sherma, J. Chromatogr. A, 880 (2000) 129. C. Turne, J.W. King and L. Mathiasson, J. Chromatogr. A, 936 (2001) 215. A.M. Enlund, G. Hagman, R. Isaksson and D. Westerlund, Trends Anal. Chem., 21 (2002) 412. A.A.M. Stolker and U.A. Th. Brinkman, J. Chromatogr. A, 1067 (2005) 15. L. Alder, K. Greulich, G. Kempe and B. Vieth, Mass Spectrom. Rev., 25 (2006) 838. C. Soler and Y. Pico´, Trends Anal. Chem., 26 (2007) 103. K. Mastovska, Food & nutritional analysis: (q) pesticide residues. In: P. Worsfold, A. Townshend and C. Poole (Eds.), Encyclopedia of Analytical Science, 2nd ed., Elsevier, Oxford, UK, 2005, Vol. 3, pp. 251–260. K. Mastovska and S.J. Lehotay, J. Chromatogr. A, 1000 (2003) 153. K. Mastovska, Instrumental aspects and application of (ultra)fast gas chromatography-mass spectrometry, In: W. Niessen (Ed.), Encyclopedia of Mass Spectrometry, Volume 8: Hyphenated Methods. Elsevier Oxford, UK, 2006, pp. 73–83. C.A. Cramers, H.-G. Janssen, M.M. van Deursen and P.A. Leclercq, J. Chromatogr. A, 856 (1999) 315. M.S. Klee and L.M. Blumberg, J. Chromatogr. Sci., 40 (2002) 234. P. Korytar, H.-G. Janssen, E. Matisova and U.A. Th. Brinkman, Trends Anal. Chem., 21 (2002) 558. E. Matisova and M. Domotorova, J. Chromatogr. A, 1000 (2003) 199. M.M. van Deursen, J. Beens, H.-G. Janssen, P.A. Leclercq and C.A. Cramers, J. Chromatogr. A, 878 (2000) 205. X. Song and H.M. McNair, J. Chromatogr. Sci., 40 (2002) 321. K. Mastovska, J. Hajslova, M. Godula, J. Krivankova and V. Kocourek, J. Chromatogr. A, 907 (2001) 235. K. Patel, R.J. Fussell, D.M. Goodall and B.J. Keely, J. Sep. Sci., 29 (2006) 90. K. Patel, R.J. Fussell, R. Macarthur, D.M. Goodall and B.J. Keely, J. Chromatogr. A, 1046 (2004) 225. S.J. MacDonald, G.B. Jarvis and D.B. Wheeler, Int. Environ. Technol., 8 (1998) 30. M.M. van Deursen, H.G. Janssen, J. Beens and C.A. Cramers, J. High Resolut. Chromatogr., 22 (1999) 509. H.M. McNair and G.L. Reed, J. Microcol. Sep., 12 (2000) 351. J. Dallu¨ge, R.J.J. Vreuls, D.J. van Iperen, M. van Rijn and U.A. Th. Brinkman, J. Sep. Sci., 25 (2002) 608. S. Gaisford, Am. Lab., 34 (2002) 10. J. Bao, N. Nazem, L.T. Taylor, J. Crnko and K. Kyle, J. Chromatogr. Sci., 44 (2006) 108. K. Mastovska, J. Hajslova and S.J. Lehotay, J. Chromatogr. A, 1054 (2004) 335. M. Akard and R.D. Sacks, Anal. Chem., 66 (1994) 3036. T. Veriotti, M. McGuigan and R.D. Sacks, Anal. Chem., 73 (2001) 279. T. Veriotti and R.D. Sacks, Anal. Chem., 73 (2001) 3045. R.E. Wittrig, F.L. Dorman, C.M. English and R.D. Sacks, J. Chromatogr. A, 1027 (2004) 75. M. Domotorova, M. Kirchner, E. Matisova and J. de Zeeuw, J. Sep. Sci., 29 (2006) 1051. M. Kirchner, E. Matisova, R. Otrekal, A. Hercegova A and J. de Zeeuw, J. Chromatogr. A, 1084 (2005) 63. M. Kirchner, E. Matisova, M. Domotorova and J. de Zeeuw, J. Chromatogr. A, 1055 (2004) 159. A. Amirav, N. Tzanani, S.B. Wainhaus and S. Dagan, Eur. J. Mass Spectrom., 4 (1998) 7. P.A. Leclercq and C.A. Cramers, J. High Resolut. Chromatogr. Chromatogr. Commun., 10 (1987) 269. M.E. Hail and R.A. Yost, Anal. Chem., 61 (1989) 2402. M. van Deursen, H.-G. Janssen, J. Beens, P. Lipman, R. Reinierkens, G. Rutten and C.A. Cramers, J. Microcol. Sep., 12 (2000) 613. J. de Zeeuw, J. Peene, H.-G. Janssen and X. Lou, J. High Resolut. Chromatogr., 23 (2000) 677. K. Mastovska, S.J. Lehotay and J. Hajslova, J. Chromatogr. A, 926 (2001) 299.
198
Katerina Mastovska
40 J.W. Cochran, J. Chromatogr. Sci., 40 (2002) 254. 41 S. Walorczyk and B. Gnusowski, J. Chromatogr. A, 1128 (2006) 236. 42 M.J. Gonza´lez-Rodrı´guez, A. Garrido-Frenich, F.J. Arrebola and J.L. Martı´nez-Vidal, Rapid Commun. Mass Spectrom., 16 (2002) 1216. 43 F.J. Arrebola, J.L. Martı´nez Vidal, M.J. Gonza´lez-Rodrı´guez, A. Garrido-Frenich and N. Sa´nchez Morito, J. Chromatogr. A, 1005 (2003) 131. 44 A. Garrido-Frenich, F.J. Arrebola, M.J. Gonza´lez-Rodrı´guez, J.L. Martı´nez-Vidal and N.M. Diez, Anal. Bioanal. Chem., 377 (2003) 1038. 45 S. Dagan and A. Amirav, Int. J. Mass Spectrom. Ion Process., 133 (1994) 187. 46 S. Dagan and A. Amirav, J. Am. Soc. Mass Spectrom., 7 (1996) 737. 47 A. Amirav, A. Gordin and N. Tzanani, Rapid Commun. Mass Spectrom., 15 (2001) 811. 48 A.B. Fialkov, A. Gordin and A. Amirav, J. Chromatogr. A, 991 (2003) 217. 49 M. Kochman, A. Gordin, P. Goldshlag, S.J. Lehotay and A. Amirav, J. Chromatogr. A, 974 (2002) 185. 50 W.M.A. Niessen, J. Chromatogr. A, 1000 (2003) 413. 51 D.A. Volme and L. Sleno, Multiplexed and parallel LC-MS, In: W. Niessen (Ed.), Encyclopedia of Mass Spectrometry, Volume 8: Hyphenated Methods. Elsevier, Oxford, UK, 2006, pp. 241–249 52 R. Oertel, K. Richter, J. Fauler and W. Kirch, J. Chromatogr. A, 948 (2002) 187. 53 L. Yang, N. Wu and P.J. Rudewicz, J. Chromatogr. A, 926 (2001) 43. 54 Y. Deng, J.T. Wu, T.L. Loyd, C.L. Chi, T.V. Olah and S.E. Unger, Rapid Commun. Mass Spectrom., 16 (2002) 1116. 55 J.J. Kirkland and J.J. DeStefano, J. Chromatogr. A, 1126 (2006) 50. 56 M.E. Swartz, J. Liq. Chromatogr., 28 (2005) 1253. 57 C.C. Leandro, P. Hancock, R.J. Fussell and B.J. Keely, J. Chromatogr. A, 1103 (2006) 94. 58 T. Kovalczuk, M. Jech, J. Poustka and J. Hajslova, Anal. Chim. Acta, 577 (2006) 8. 59 X. Cui, B. Shao, R. Zhao, Y. Yang, J. Hu and X. Tu, Rapid Commun. Mass Spectrom., 20 (2006) 2355. 60 E. Barcelo´-Barrachina, E. Moyano, M.T. Galceran, J.L. Lliberia, B. Bago´ and M.A. Cortes, J. Chromatogr. A, 1125 (2006) 195. 61 J.J. Kirkland, T.J. Langlois and J.J. DeStefano, New ‘‘fused-core’’ particles for very fast HPLC separations, Proceedings of Pittcon 2007, February 25–March 2, 2007, Chicago, IL USA. 62 N. Tanaka, H. Kobayashi, K. Nakanishi, H. Minakuchi and N. Ishizuka, Anal. Chem., 73 (2001) 420A. 63 F. Svec and C.G. Huber, Anal. Chem., 78 (2006) 2101. 64 T. Hara, H. Kobayashi, T. Ikegami, K. Nakanishi and N. Tanaka, Anal. Chem., 78 (2006) 7632. 65 T. Greibrokk and T. Andersen, J. Chromatogr. A, 1000 (2003) 743. 66 S.M. Fields, C.Q. Ye, D.D. Zhang, B.R. Branch, X.J. Zhang and N. Okafo, J. Chromatogr. A, 913 (2001) 197. 67 J.W. Coym and J.G. Dorsey, J. Chromatogr. A, 1035 (2004) 23. 68 Y. Yang, M. Belghazi, A. Lagadec, D.J. Miller and S.B. Hawthorne, J. Chromatogr. A, 810 (1998) 149. 69 T.M. Pawlowski and C.F. Poole, Anal. Commun., 36 (1999) 71. 70 S.J. Marin, B.A. Jones, W.D. Felix and J. Clark, J. Chromatogr. A, 1030 (2004) 255. 71 M. Mao and P. Carr, Anal. Chem., 73 (2001) 4478. 72 G. Schomburg, J. Chromatogr. A, 703 (1995) 309. 73 J.C. Duinker, D.E. Schulz and G. Petrick, Anal. Chem., 60 (1988) 478. 74 T. Hyo¨tyla¨inen and M.L. Riekkola, J. Chromatogr. A, 1000 (2003) 357. 75 H.-G. Janssen, W. Boers, H. Steenbergen, R. Horsten and E. Flo¨ter, J. Chromatogr. A, 1000 (2003) 385. 76 A.W. Moore and J.W. Jorgenson, Anal. Chem., 67 (1995) 3456. 77 H.J. Issaq, K.C. Chan, G.M. Janini, T.P. Conrads and T.D. Veenstra, J. Chromatogr. B, 817 (2005) 35. 78 D.R. Stoll, J.D. Cohen and P.W. Carr, J. Chromatogr. A, 1122 (2006) 123. 79 J.B. Phillips and J. Beens, J. Chromatogr. A, 856 (1999) 331. 80 W. Bertsch, J. High Resolut. Chromatogr., 23 (2000) 167. 81 R.C.Y. Ong and P.J. Marriott, J. Chromatogr. Sci., 40 (2002) 276. 82 P.J. Marriott and R. Shellie, Trends Anal. Chem., 21 (2002) 573. 83 J. Dallu¨ge, J. Beens and U.A. Th. Brinkman, J. Chromatogr. A, 1000 (2003) 69.
Recent Developments in Chromatographic Techniques
199
84 M. Adahchour, J. Beens, R.J.J. Vreuls and U.A. Th. Brinkman, Trends Anal. Chem. 25 (2006) 438–454, 540–553, 726–741, 821–840. 85 J. Harynuk and P.J. Marriot, Comprehensive two-dimensional gas chromatography-mass spectrometry, In: W. Niessen (Ed.), Encyclopedia of Mass Spectrometry, Volume 8: Hyphenated Methods. Elsevier, Oxford, UK, 2006, pp. 83–92. 86 M. Adahchour, J. Beens, R.J.J. Vreuls, A.M. Batenburg and U.A. Th. Brinkman, J. Chromatogr. A, 1054 (2004) 47. 87 E.B. Ledford, C.A. Billesbach and J.R. Termaat, Transverse thermal modulation, U.S. Patent No. 6,547,852 B2; April 15, 2003. 88 R.E. Murphy, M.R. Schure and J.P. Foley, Anal. Chem., 70 (1998) 1585. 89 M. Adahchour, M. Brandt, H.-U. Baier, R.J.J. Vreuls, A.M. Batenburg and U.A. Th. Brinkman, J. Chromatogr. A, 1067 (2005) 245. 90 J. Dallu¨ge, M. van Rijn, J. Beens, R.J.J. Vreuls and U.A. Th. Brinkman, J. Chromatogr. A, 965 (2002) 207. 91 J. Zrostlikova, J. Hajslova and T. Cajka, J. Chromatogr. A, 1019 (2003) 173. 92 M. Harju, C. Danielsson and P. Haglund, J. Chromatogr. A, 1019 (2003) 111. 93 J.-F. Focant, A. Sjo¨din and D.G. Patterson, J. Chromatogr. A, 1040 (2004) 227. 94 J.-F. Focant, G. Eppe, M.L. Scippo, A.C. Massart, C. Pirard, G. Maghuin-Rogister and E. de Pauw, J. Chromatogr. A, 1086 (2005) 45. 95 J.-F. Focant, E.J. Reiner, K. MacPherson, T. Kolic, A. Sjo¨din, D.G. Patterson, S.L. Reese, F.L. Dorman and J. Cochran, Talanta, 63 (2004) 1231. 96 E. Hoh, K. Mastovska and S.J. Lehotay, J. Chromatogr. A, 1145 (2007) 210. 97 P. Koryta´r, A. Covaci, P.E.G. Leonards, J. de Boer and U.A. Th. Brinkman, J. Chromatogr. A, 1100 (2005) 200. 98 J. Hajslova and J. Zrostlikova, J. Chromatogr. A, 1000 (2003) 181. 99 D.R. Erney, A.M. Gillespie, D.M. Gilvydis and C.F. Poole, J. Chromatogr. A, 638 (1993) 57. 100 F.J. Schenck and S.J. Lehotay, J. Chromatogr. A, 868 (2000) 51. 101 P.L. Wylie and K. Uchiyama, J. AOAC Int., 79 (1996) 571. 102 M. Godula, J. Hajslova and K. Alterova, J. High Resolut. Chromatogr., 22 (1999) 395. 103 M. Godula, J. Hajslova, K. Mastovska and J. Krivankova, J. Sep. Sci., 24 (2001) 355. 104 J. Zrostlikova, J. Hajslova, M. Godula and K. Mastovska, J. Chromatogr. A, 937 (2001) 73. 105 J. Hajslova, K. Holadova, V. Kocourek, J. Poustka, M. Godula, P. Cuhra and M. Kempny, J. Chromatogr. A, 800 (1998) 283. 106 M. Anastassiades, K. Mastovska and S.J. Lehotay, J. Chromatogr. A, 1015 (2003) 163. 107 K. Mastovska, S.J. Lehotay and M. Anastassiades, Anal. Chem., 77 (2005) 8129. ´ . Ambrus (Eds.), Principles 108 E. Soboleva, N. Rathor, A. Mageto and A. Ambrus, In: A. Fajgelj and A and Practices of Method Validation, Royal Society of Chemistry, Cambridge, 2000, pp. 138–156. 109 A. Amirav and S. Dagan, Eur. J. Mass Spectrom., 3 (1997) 105. 110 S. de Koning, G. Lach, M. Linkerha¨gner, R. Lo¨scher, R.H. Tablack and U.A. Th. Brinkman, J. Chromatogr. A, 1008 (2003) 247. 111 K. Patel, R.J. Fussell, D.M. Goodall and B.J. Keely, Analyst, 128 (2003) 1228. 112 K. Patel, R.J. Fussell, D.M. Goodall and B.J. Keely, Food Addit. Contam., 21 (2004) 658. 113 T. Cajka, K. Mastovska, S.J. Lehotay and J. Hajslova, J. Sep. Sci., 28 (2005) 1048. 114 S.C. Cunha, S.J. Lehotay, K. Mastovska, J.O. Fernandes and M.B.P.P. Oliveira, J. Sep. Sci., 30 (2007) 620. 115 J.-P. Antignac, K. de Wasch, F. Monteau, H. de Brabander, F. Andre and B. Le Bizec, Anal. Chim. Acta, 529 (2005) 129. 116 W.M.A. Niessen, P. Manini and R. Andreoli, Mass Spectrom. Rev., 25 (2006) 881. 117 M.G. Ikonomou, A.T. Blades and P. Kebarle, Anal. Chem., 62 (1990) 957. 118 P. Kebarle and L. Tang, Anal. Chem., 65 (1993) 972A. 119 R.C. King, R. Bonfiglio, C. Fernandez-Metzler, C. Miller-Stein and T. Olah, J. Am. Soc. Mass Spectrom., 11 (2000) 942. 120 L. Alder, S. Lu¨deritz, K. Lindtner and H.-J. Stan, J. Chromatogr. A, 1058 (2004) 67. 121 B.K. Matuszewski, M.L. Constanzer and C.M. Chavez-Eng, Anal. Chem., 75 (2003) 3019.
200
Katerina Mastovska
B.K. Choi, D.M. Hercules and A.I. Gusev, Fresenius J. Anal. Chem., 369 (2001) 370. B.K. Choi, D.M. Hercules and A.I. Gusev, J. Chromatogr. A, 907 (2001) 337. R. Dams, M.A. Huestis, W.E. Lambert and C.M. Murphy, J. Am. Soc. Mass Spectrom., 14 (2003) 1290. E. Gangl, M. Annan, N. Spooner and P. Vouros, Anal. Chem., 73 (2001) 5635. A. Kloepfer, J.B. Quintana and T. Reemtsma, J. Chromatogr. A, 1067 (2005) 153. C.R. Powley, F.Q. Bramble, L. Jin and J.J. Stry, Application of quantitative LC/MS and LC/MS/ MS to the determination of pesticide residues in agriculture, Proceedings of the 3rd European Pesticide Residue Workshop, July 3–5, 2000, York, UK. 128 J. Zrostlikova, J. Hajslova, J. Poustka and P. Begany, J. Chromatogr. A, 973 (2002) 13. 129 K. Mastovska and A.R. Lightfield, Use of the echo peak technique to compensate for matrix effects in the LC-MS/MS analysis of beta-lactam antibiotics, Proceedings of the 55th ASMS Conference on Mass Spectrometry, June 3–7, 2007, Indianapolis, IN, USA.
122 123 124 125 126 127
CHAPT ER
7 New Approaches in Mass Spectrometry Yolanda Pico´
Contents
1. Introduction 201 2. High Resolution and Accurate Mass Analysers 204 2.1 Time-of-flight mass spectrometry 205 3. Tandem Mass Spectrometry 211 3.1 Triple quadrupole mass analysers 211 3.2 Ion-trap mass spectrometers 212 3.3 Linear ion trap 213 4. High Resolution Mass Spectrometers in Tandem 219 4.1 Quadrupole time-of-flight mass spectrometer 219 4.2 Fourier transform ion cyclotron resonance and orbitrap mass analysers 222 5. Conclusions and Future Trends 227 References 228
1. INTRODUCTION Nowadays, mass spectrometry (MS) is the most used technique to determine food contaminants [1–3]. Normally, this technique is combined with a separation one, such as gas chromatography (GC) [2,4,5], liquid chromatography (LC) [6–8] or capillary electrophoresis (CE) [9,10], because of the high number of organic pollutants and their low concentrations in food samples. Among the different MS techniques and their combinations with chromatographic separation, GC-MS is the routine, preferred analytical method for determining food contaminants and residues since the end of the 1970s. A large number of publications have resulted from research on food applications of GC-MS [4]. This technique is frequently used to study the behaviour of contaminants and residues as well as to monitor their presence in food. GC-MS is currently a mature Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00007-X
r 2008 Elsevier B.V. All rights reserved.
201
202
Yolanda Pico´
technique applied in the analysis of a significant number of pollutants [2,4,11,12]. The compounds most commonly analysed include alkanes, polycyclic aromatic hydrocarbons (PAHs), pesticides, polychlorinated biphenyls (PCBs), polychlorinated dibenzo-p-dioxins and furans (PCDD/Fs), as well as other endocrinedisrupting chemicals such as phthalates and short ethoxy alkylphenol etoxylates [5,13–18]. GC-MS is also the technique of choice for the analysis of emerging pollutants, such as polybrominated diphenyl ethers (PBDEs) or polychlorinated alkanes [17]. However, the development of LC-MS in the past 20 years has made the detection of many harmful compounds possible. The primary advantage LC-MS has over GC-MS is that it is capable of analysing a much wider range of components. Compounds that are thermally labile, exhibit high polarity or have a high molecular mass may all be analysed using LC-MS, even proteins may be routinely analysed. Several recently published comprehensive papers summarized the current state-of-the-art in LC-MS analysis of specific classes of contaminants (e.g., veterinary drug residues, banned growth promoters, perfluorinated compounds, and pesticides and their degradation/transformation products and food packaging migrating materials) [6,19–27]. These two approaches can be considered the established ones. There are more emerging techniques, such as CE-MS or ambient MS, which are very promising, helping to improve MS features for the analysis of food contaminants, even though they are not well ascertained yet in the field of food contaminants and residues analysis [28–30]. The introduction of novel methods and expanding applications to diverse areas highlight truly impressive progress in MS. Table 1 summarizes the current state-of-the-art in MS for food contaminants and residue analysis and the expected improvements. These developments are illustrated here by two seemingly different areas of research: innovative ionization methods and mass analysers. Some emerging technologies in the field of the ionization sources have shown great potentials to further enhance the capabilities of high throughput analysis by MS, including CE-MS and ambient MS [31,32]. The recent development on CE-MS has been produced in the field of micro- and nano-electrospray ionization (ESI) ion sources, which have radically improved the CE/ESI-MS sensitivity level. In such devices the need of make-up flow is eliminated because the sample is sprayed into the MS either directly from the tip of the separation capillary or from a tapered micro- or nanoemitter butted to the CE column. In both cases, the achieved flow rates are situated in the range of nanolitre per minute . The effects of the use of this kind of micro/nanosprayers, which include higher analyte concentration, reduced spraying potential and closer positioning of the sprayer to the orifice of the mass spectrometer, render a substantially improved mass transfer into MS, better ionization and desolvation of the generated droplets and therefore, superior sensitivity [33]. Because of the rather low sensitivity provided by the sheath flow CE-MS, for applications where limited amount of material is available, sheathless on-line CE/ESI-MS is a reliable alternative, even if the tedious optimization procedures make it often a non-user-friendly approach. The lack of commercial
New Approaches in Mass Spectrometry
203
Table 1 Summary of the improvements of mass spectrometry in food contaminants and residues GC-MS
LC-MS
CE-MS
Current state-of-the-art in mass spectrometry The dominant Well-established Well-established interfacing ionization ionization system is the sources: EI sources: EI sheath interface and CI and CI
Variety of mass Variety of mass Variety of mass analysers MS, analysers MS, analysers MS, MS2 (quadrupole, MS2 (quadrupole, MS2 (sector, ion trap, sector) ion trap, triple triple quadrupole, quadrupole) ion trap, time-of-flight)
Routine technique Routine technique No real applications
MS
Method for the analysis of solids are still under development (DART) MALDI is the well-developed techniques always combined with time-of-flight and not appropriate for small molecules Not appropriate for food contaminants and residues which are small molecules
Expected improvements in mass spectrometry New interfacing New mass New interfacing New mass systems system (sheathless analysers analysers (triple (desorption interface, liquid (time-of-flight, quadrupole, electrospray junction interfaces, linear traps, time-of-flight, ionization) etc.) quadrupole etc.) time-of-flight, orbitrap, etc.) First applications Already a reality Already a reality The available of commercial approaches devices require improvements Note: EI, electron ionization; CI, chemical ionization; DART, direct analysis in real time; MALDI, matrix assisted laser desorption.
204
Yolanda Pico´
sheathless interfaces or completely standardized procedures for smooth and fast in-house production, along with the deficit in methodological protocols for running different analytes, stimulated continuously the creativity of the CE-MS scientific community. So far, a remarkable number of sheathless setups were conceived and their potential for various applications tested [34]. These combinations are still little applicable to food contaminants and residue analysis because the sensitivity is not optimum yet and will not be covered in this chapter [9,10]. Recently introduced ambient MS represents a new family of ionization techniques that create ions under ambient conditions without vacuum constraints, including desorption electrospray ionization (DESI) [31] and direct analysis in real time (DART) [35], which have already been detailed in Chapter 1. In DESI experiments, a spray of charged solvent droplets hits the surface of the sample and ionizes the sample molecules (small molecules and large biomolecules) [35]. In DART experiments, a plasma of excited-state atoms and ions from nitrogen/ helium desorb/ionize small molecules from the surface of the sample. These techniques can be used to rapidly obtain mass spectra of compounds without any sample preparation [35]. Some encouraging results on analysis of food with ambient MS have recently been reported in the literature [36]. These techniques are very promising and further developments in this area will establish the use of ambient MS for high-throughput analysis, accurate mass measurement and other aspects of structural characterization of food contaminants and residues. This chapter is, thus, aimed at discussing the progress of MS analysers in food contaminants and residue analysis and reporting the recent applications for the trace analysis of selected contaminants. Two emerging trends in the mass analysers design are valuable to get better quality and quantity of structural information: High-resolution (HR) mass spectrometers, which calculate elemental composition and nominal mass, because they can determine exact mass of analytes. They are a tool to identify unknown substances in the samples. These spectrometers are represented by time-of-flight (TOF). Tandem mass spectrometry (MS/MS), which allow the mass spectrometer to analyse an ion and obtain its mass spectrometer again. The mass spectrometers capable of carrying out MS/MS are QqQ, ion trap, quadrupole time-of-flight (QqTOF) and linear ion trap (LIT).
2. HIGH RESOLUTION AND ACCURATE MASS ANALYSERS High resolution and accurate mass mainly include four types of instrumentation — double-focusing magnetic-sector (resolving power of 10,000–40,000 full width at half maximum (fwhm) with 2–5 ppm accuracy), TOF (resolving power of 10,000–20,000 fwhm and an accuracy of 2–5 ppm at m/z 1,000), the LITOrbitrap (resolving power of 60,000–100,000 fwhm) and Fourier transform ion cyclotron resonance (FTICR) MS systems (W100,000 fwhm and 0.5–2 ppm). Although all four instruments work readily with GC or LC systems, the magnetic-sector instruments were developed initially to operate with GC-MS.
New Approaches in Mass Spectrometry
205
High resolution and accurate GC-MS with a magnetic sector instrument is already a well-developed technique to determine some organic contaminants such as PCBs, PBBs and PCDD/Fs, as described in detail in Chapters 14 and 15 of this book and hence is not discussed in this Chapter. The more recent highaccuracy TOF systems have been applied indistinctly to LC-MS or GC-MS. The QqTOF, FTICR-MS and LIT-Orbitrap systems are currently considered research tools in LC-MS and are also susceptible to carry out MS/MS. These instruments and their applications are described in next section [37].
2.1 Time-of-flight mass spectrometry The current trend in the trace analysis of food contaminants and residues is to use TOF-MS systems because they are easier and less expensive to operate compared with the other high resolution and high accuracy mass spectrometers [5,37–41]. Recent advances have reduced instrument costs and have made analysis less complicated, more accurate and more quantitative [15]. At present, several commercial benchtop instruments are available with high resolution and accurate mass that are suitable for food analysis coupled either with GC or LC [5,41]. TOF-MS offers the advantage of a comprehensive mass analysis in a broad dynamic range, because TOF-MS is a non-scanning technique, all ions included in the mass range are virtually recorded at the same time and are represented at the same point on the chromatographic peak profile. Constant ion ratio across the GC or LC peak is thus ensured. High-quality mass spectra are produced and deconvoluted if more than one compound is present at the time mass spectra are recorded, as is the case when two compounds chromatographically co-elute. Other TOF-MS advantages are high sensitivity, speed and ease of use, simple experimental design (no tuning) and that it can achieve resolving powers (m/Dm) of Z3,500, and exact parts per million mass measurements. Those spectrometers are the best available instruments for routine HRMS, not as accurate as a sector, but much easier to handle [5,37–41]. TOF-MS analysers provide high specificity due to both high mass accuracy and mass resolution. This technique can generate high specificity without limiting the number of simultaneously observed target compounds. Both the accurate mass of each scan and the higher mass resolving power provide a greater degree of reduction in chemical noise, thereby enhancing selectivity. The advantage of a TOF-MS analyser for screening is its ability to examine a data file for a theoretically unlimited number of food contaminants [41]. TOF-MS combined with LC is used in food contaminants and residue analysis because, in contrast to conventional triple quadrupole (QqQ) instruments working in selected reaction monitoring (SRM), it offers several benefits such as: A large number of targets can be screened at the same time without loss of sensitivity [42–44]. Unknown peaks can be identified based on accurate mass and isotopic profile evaluation [45–47]. Data can be reprocessed a posteriori for additional compounds, which had not yet been investigated [41].
206
Yolanda Pico´
The LC-TOF-MS approach enables screening for several hundreds of compounds with high sensitivity within one run. The selectivity is based on the accurate mass measurements with mass traces defined within 0.005 Da over a dynamic range of about three orders of magnitude [48–50]. It is also important to remark the feasibility of LC-TOF-MS/MS and elemental database searching as spectral library [51]. Figure 1 illustrates an example of the LC-TOF-MS application to identify an unknown chlorinated compound. In a grapefruit extract and a pear extract, a doubly chlorinated species was detected with m/z 311 at a retention of 18.2 min. Figure 1(a) shows the total ion chromatogram (TIC) of the grapefruit extract (accurate mass spectrum as insert) and Figure 1(b) shows the accurate mass spectrum of this doubly chlorinated species in the pear extract. The accurate m/z of the main peak was 311.0712 with an A+2 isotope signal at m/z 313.0681, which has a relative intensity consistent with the presence of two chlorine atoms. Although all available databases (e.g., The Merck Index, ChemIndex and e-catalogues) were used, no match with the candidate elemental compositions was obtained. The authors, based on previous experience, indicate that the most likely elemental composition was C15H17N2OCl2. This elemental composition was rather similar to that of imazalil (a common post-harvest fungicide); there was only a difference of a methylene group (CH2) that reasonably attributes to a methyl group substitution. The combination of GC with TOF-MS technique resulted in the introduction of two types of spectrometers differing in their basic characteristics: Instruments using HR analysers characteristic with only moderate acquisition speed. Unit-resolution instruments that feature a high acquisition speed (HSTOF). The potential application of these approaches is obviously complementary. Recently GC-TOF-MS, employing both detectors, has been demonstrated as a powerful and highly effective analytical tool in various fields, and the analysis of food contaminants is one of them [5]. Due to the availability of spectral information even at very low levels for a particular compound (high mass analyser efficiency), this technique can be used not only for quantification/confirmation of target analytes but also for identification of non-target sample components even in very complex mixtures [12,13,16,17,25,52–54]. The moderate acquisition rates of the HRTOF instruments predetermine their use as the detector for conventional and fast GC; the HSTOF instruments are suitable for detection of very narrow chromatographic peaks generated by very fast and ultra-fast GC or GC GC. HSTOF-MS instruments provide only a unit mass resolution, whereas HRTOF analysers offer resolution as high as 7,000 fwhm and even more. The advantage of high resolution is the possibility of partially or completely resolving matrix components yielding ions with the same nominal mass as that of the target analyte, hence, significantly reducing background interferences and, consequently, improving the analyte identification. The utility of high speed is the possibility to couple a selective detector with GC GC improving the capabilities of the technique.
207
New Approaches in Mass Spectrometry
tive
Figure 1 Identification of an unknown chlorinated specie: (a) total ion chromatogram and (b) accurate mass spectrum (m/z 311); a case study of a methyl derivative of imazalil. Reproduced from Ref. [47] with permission from Wiley.
208
Yolanda Pico´
TOF-MS combined with conventional GC is applied in food contaminants and residue analysis. The HRTOF-MS instruments achieve mass accuracy as low as 5 ppm. Under these conditions, the determination of elemental composition is possible; also the specificity for the identification of unknowns is enhanced. This detector has been widely applied to the determination of pesticide residues, acrylamine and environmental contaminants, such as PCBs and PBDEs [12,13,16,17,25,52–54]. The high mass resolution and monitoring of the exact mass of target analytes, can reduce significantly the chemical noise originating from various sources (e.g., matrix coextractants, column filled) resulting in an improved limit of quantification (LOQs) [2,12]. Figure 2 shows negative ion chemical ionization (NICI) chromatograms obtained by HRTOF-MS examination of purified fish (perch) extract and standard of PBDEs [17]. This study demonstrated that operating the instrument in the NICI mode provides not only more sensitive detection (20–100fold) compared with electron ionization (EI) but also results in increased selectivity. Although the low m/z bromine ions used for identification/ quantification of target analytes may not seem specific enough (compared with high molecular ions produced by the EI), their selectivity is relatively high since only a limited number of GC-amenable compounds, potentially present in food samples, are prone to yield ions capable of efficient electron capture in NICI [17]. Moreover, thanks to the availability of full spectral information, other analytes (particularly, the case of major PCB congeners) occurring in this sample could be determined without any instrumental modification, simply by retrieval of stored data. To obtain comparable LOQs by quadrupole operated in selected ion monitoring (SIM) mode (ions m/z 79 and 81 monitored only), as those achieved by HRTOF-MS, a 10 times higher sample equivalent had to be introduced into the system. In other words, HRTOF-MS was more sensitive by one order of magnitude in the analysis of PBDEs. However, in this field, GC GC coupled with HSTOF-MS has been proved in the past few years to be a powerful technique for achieving unsurpassed separation and has been therefore applied to any challenging separation needs for unravelling complex mixtures, for which, conventional GC showed its limitation. In particular, the determination of PCBs, PBBs and PCDD/Fs is taking great advantage in using this technique. In this context, TOF-MS offers several important features over conventional MS detectors to be combined with GC GC: Full mass spectral information is available across the chromatogram, with detectability fully comparable with conventional MS detectors. The absence of spectral skew and constant ion ratios across the peak allows application of the software algorithm of peak finding and spectral deconvolution, enabling the applications in non-target analysis. Being the fastest MS detector, TOF can be used in GC GC without any compromise.
6.47
100
CB 180
New Approaches in Mass Spectrometry
209
m/z 393.803 Mass window: 0.02 Da (A)
% 6.75 6.03
6.71
6.42 6.07
7.03
7.23
0 5.73
6.47
m/z 359.842 Mass window: 0.02 Da
CB 180
CB 153
Rel. abundance
100
5.96
(B)
6.41
%
6.22 5.98 5.68
6.72 5.82
6.03
6.75
BDE 49
% 5.89 6.06 6.12
6.38 6.32
6.69
(C)
BDE 99
BDE 28 5.63
m/z 80.916 7.26 Mass window: 0.02 Da BDE 100
6.56
100
BDE 47
0
7.48 6.90
7.62
7.13
0 5.60
5.80
6.00
6.20
6.40
6.60
6.80
7.00
7.20
7.40
Time (min)
Figure 2 GC-TOF-MS chromatograms of selected PCBs and PBDEs in diluted fish extract (0.32 mg of original matrix equivalent injected) in NICI mode. Ions extracted by a mass window of 0.02 Da. (A) Chromatogram of ion m/z 393.803 corresponding to heptachlorobiphenyls, (B) Chromatogram of ion m/z 359.842 corresponding to hexachlorobiphenyls and (C) Chromatogram of ion m/z 80.916 corresponding to PBDEs. Reproduced from Ref. [17] with permission from Wiley.
As an interesting example, Focant et al. [55] developed and tested a comprehensive gas chromatography-isotope dilution-time-of-flight mass spectrometry (GC GC-ID-TOF-MS) method for the measurement of selected PCDD/Fs and PCBs in foodstuffs (fish, pork and milk samples). The set of compounds consisted of seven 2,3,7,8-substituted PCDDs, ten 2,3,7,8-substituted PCDFs, four non-ortho-PCBs, eight mono-ortho-PCBs and six indicator PCBs (Aroclor 1260), from a total of 35 compounds. GC GC-ID-TOF-MS results were compared to the confirmatory reference gas chromatography isotope dilution highresolution mass spectrometry (GC-ID-HRMS) method, to the alternative screening gas chromatography isotope dilution quadrupole ion storage tandem mass spectrometry (GC-ID-QIST-MS/MS) method, and to the DR-CALUXs
210
Yolanda Pico´
bioassay screening method. This comparison indicates the good performance of GC GC-ID-TOF-MS. Hoh et al. [56] presented a remarkable study focused on an extensive optimization of GC GC-TOF-MS conditions for analysis of PCDD/Fs by evaluating primary GC oven temperature programs, carrier gas flow rate, GC GC conditions and MS conditions to maximize sensitivity and selectivity in the detection and separation of the 17 PCDD/Fs, in the presence of potentially interfering PCBs. Figure 3 shows how to preserve the separation, HxCDF II eluted immediately after HxCDF I in the 1D arrangement, and HxCDD II eluted just after HxCDD I. These two congener pairs (HxCDF I and II, HxCDD I and II) have identical mass spectra, so they must be chromatographically separated for the congener-specific analysis. The 1D separations were preserved in r4 s modulation periods, as shown in Figure 3A and B, but they co-eluted at the 5 s modulation period, as shown in Figure 3C. The separation gained from the 2D column can be seen in the 2D-axis (on the lower left) in Figure 3D. The resolution (RS) was not much different among the modulation periods, and the separation of the pair was achieved in all the modulation periods, even in the longest modulation period of 4 s (see Figure 3D).
Figure 3 GC GC contour maps of HxCDD I and HxCDD II (m/z 390) obtained from different modulation periods: (A) 1 s; (B) 4 s; (C) 5 s and (D) GC GC surface map for 6.7 pg injection of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) (m/z 322) and 58 pg of CB126 (m/z 254) with 4 s modulation period. Reproduced from Ref. [56] with permission.
New Approaches in Mass Spectrometry
211
3. TANDEM MASS SPECTROMETRY It has been widely recognized that MS/MS (or MS2) offers very good sensitivity and selectivity in trace analysis of food contaminants. These mass analysers are already used routinely combined with LC in many food safety fields, where LC-MS2 techniques, such as QqQs and ion traps (ITDs), are in common use. More recent approaches in LC-MS2 are LITs, new-generation QqQs and hybrid instruments, quadrupole time-of-flight (QqTOF) and Q-linear traps (Qq-LITs), which are gaining widespread acceptance in several application areas. These instruments offer advantages such as high scanning speeds, accurate mass measurement (QqTOF) and increased sensitivity (LITs and new-generation QqQs).
3.1 Triple quadrupole mass analysers QqQ mass analysers have become the most widely used analytical tool in food analysis. A number of analytical methods, using LC-MS (QqQ) have been developed for the analysis of different classes of priority and emerging contaminants in food samples. LC-MS2 (QqQ) has mostly been applied for the determination of target analytes, using the SRM and achieving LODs of typically nanogram per kilogram (ng/kg) (e.g., in the analysis of growth promoters, the use of QqQ in LC-MS2 has substantially increased the selectivity and the sensitivity of the determination, therefore allowing detection of low, but nevertheless toxicologically relevant, concentrations in the sub-ng/kg range). Their application to food contaminants analysis has allowed the determination of a great number of compounds, especially polar ones that were previously difficult or even impossible to analyse. LC-QqQ-MS/MS is an already well-established technique that presents many applications in food safety. The reader is referred to the chapters on particular contaminants (pesticides, veterinary drugs residues, myco and phycotoxins, growth promoters or food contact materials), where a number of interesting applications are described. Hence, it is not discussed in this chapter. Recent combination of QqQ with GC is still quite a new approach within the field of MS. These instruments have been successfully applied mainly to the analysis of pesticides and PCBs [57]. Unquestionably, MS/MS gives a much higher degree of certainty in analyte identification than any single-stage MS technique, because isobaric interferences are avoided and multiple-component spectra can be resolved. Thanks to this, the confirmation of target analytes can be achieved with a higher level of confidence. Among the different mass analysers that can perform MS/MS, QqQ mass spectrometers have recently been proposed for the determination of pesticide residues in crops [58–60]. A remarkable advantage of the QqQs, in comparison with previously used ion traps, is the possibility of operating in SRM, which is a faster scan mode than product ion scan available on the ion traps. Modern quadrupole instruments are capable of sufficiently fast scan rates for fast-GC-MS. Although considered as one of the most powerful techniques, there are not many references in the literature to the use of gas chromatography/QqQ-MS/MS in the analysis of pesticide residues. Garrido Frenich et al. [58] studied the potential of
212
Yolanda Pico´
GC with QqQ MS/MS for the multi-residue analysis of pesticides in vegetables, validated the method on cucumbers, then expanded the scope of the method, and validated on strawberries [59]. Okihashi et al. [60] dealt with the simultaneous analysis of 260 pesticide residues in agricultural products. Two MS/MS transitions were selected for each analyte using the intensity ratio obtained from them as a confirmatory parameter. The sensitivity of this method was lower than with most of the selective GC detectors, such as flame photometric or single MS. The selectivity of QqQ gives a very clean chromatogram, making compound identification and confirmation easy. Other examples are the determination of xenoestrogens (pesticides, PCBs and polybrominated diphenyl ethers) in human breast tissues [61], organochlorine and organophosphorous pesticides in animal liver [62] and meat samples [63]. Also, low-pressure gas chromatography/triple quadrupole tandem mass spectrometry (LP-GC-MS/MS) conditions were developed for 78 pesticides but validation data were generated for only 12 pesticides in tomato [64]. In the field of PCBs, GC GC-QqQ-MS/MS is presented by Bucheli and Brandli [15] as a robust, selective and sensitive method for the accurate quantification of enantiomeric fractions of atropisomeric PCBs in several foods. GC GC-MS/MS proved to be superior to coupling technique with less dimensions to quantify atropisomeric PCBs, almost irrespective of their origin and cleanup quality. However, modern QqQ are not fast enough and can only be combined with GC GC in very specific situations.
3.2 Ion-trap mass spectrometers The conventional 3D ion-trap (Paul trap) mass spectrometer has only three electrodes, one ring electrode between two hyperbolic endcap electrodes, which form a three-dimensional trap. The oscillating potential difference established between the ring endcap electrodes forms a substantial quadrupolar field. The ions can be stored for milliseconds or longer in an ITD. Raising the DC potential will isolate ions of a particular m/z by ejecting all of the other ions from the trap. A subsequent increase of the rf potential will eject the stored ions from the trap and send them to the detector. ITD can simultaneously store positive and negative ions for extended periods of time. The principal advantage of ion trap is its ability to perform multiple stages of MS, which increase the amount of information obtainable from a molecule. This characteristic facilitates the identification of unknown compounds making ITD an ideal tool to study fragmentation processes and pathways, increasing, at the same time, sensitivity and selectivity. The fragmentation of isolated ions in an ion trap depends on the frequency of the resonance excitation voltage, the magnitude rf and the duration and trapping rf voltage during resonance excitation. Those features make ITD an attractive option to perform different studies. In fact, the ITD is already a well-established MS technique that can be combined with both LC and GC [65–74]. There are a number of publications using this detector for almost all the possible food contaminants and residues. However, it should be mentioned in this Chapter because it is a very recognized instrument and their ability as confirmation technique makes it almost indispensable in several types of applications.
New Approaches in Mass Spectrometry
213
The drawbacks of ITD are its inability to trap product ions below m/z 50 and the fragment ions with masses in the lower third of the mass range will not be detected, this drawback is relevant for acrylamide. The reported differences between the product ion mass spectra obtained by this instrument and those obtained by the most conventional and routine QqQ. When fragmentation on an ITD and the QqQ is compared, two factors are to be considered: (i) the amount of energy that can be deposited in an ion — the relative amount of energy that can be deposited within a molecule is greater for a QqQ (uses Ar as collision gas) than for an ITD (uses He), and (ii) the time that the ion is stored on the ITD or the time that the ion spends in the collision cell for the QqQ .The formation of rearrangement product ions versus cleavage product ions is favoured in the ITD. Another drawback is that the ion trap requires clean extracts and more than periodical cleaning of the system. An interesting and recent example of the applicability of gas chromatography coupled with ion trap MS/MS (CG-MS-MS) for the analysis of PCDD/Fs and dioxin-like PCBs in samples containing low levels of these compounds illustrates very well this problem [75]. Vegetable oils were selected for this study because European Union (EU) legislation has established a very low value of maximum concentration levels for them: 0.75 pg WHO-TEQ/g for dioxins and furans and 1.50 pg WHO-TEQ/g for the sum of PCDD/Fs and dioxine-like PCBs (dl-PCBs). The importance of the clean-up when using ion-trap instruments is directly related to the normal operation of this analyser that introduces into the trap a number of ions of m/z range regardless of whether they are from the target compounds or the interfering ions. The decrease of the number of precursor ions produces a reduction of the product ions and, as a consequence, of the signal-to-noise ratio. Therefore, an inadequate clean-up decisively affects the quality of the final results and false negatives may be obtained. The presence of lipid components in the oil extracts due to an insufficient clean-up drastically affected the sensitivity of the ion trap. This problem was only observed in the analysis of the mono-ortho PCB fraction because the polarity of the solvents used (n-hexane:dichloromethane 98:2 (v/v) and dichloromethane:Hexane 50:50 (v:v)) for eluting these compounds from the alumina and carbon adsorbent column favoured the presence of small amounts of lipids. As a result, the chromatograms obtained were characterized by the presence of deformed peaks and elevated signal-to-noise ratios, as can be seen in Figure 4a where the chromatogram of an oil sample is given. In contrast, in Figure 4b nice chromatograms with well-defined peaks were obtained using an additional clean-up step, using a 2-g acid silica (44% sulfuric acid) column and eluting the target compounds with 5 mL of n-hexane. So, GC-MS/MS can be considered a suitable technique for the analysis of PCDD/Fs and dl-PCBs in vegetable oils, but an exhaustive clean-up process of the extracts is required.
3.3 Linear ion trap The LIT mass spectrometer, a recent addition to the MS family, has increased ion capacity, improved ion trapping efficiency and faster cycle times compared
Figure 4 GC-MS/MS chromatograms of mono-ortho PCBs fraction for a vegetable oil sample with: (a) problems in the clean-up process and (b) suitable clean-up process. Reproduced from Ref. [75] with permission.
214 Yolanda Pico´
New Approaches in Mass Spectrometry
215
to the previous one. LIT use a set of quadrupole rods to confine ions radially and a static electrical potential on end electrodes to confine the ions axially. The linear form of the trap can be used as a selective mass filter or as an actual trap by creating a potential well for the ions along the axis of the electrodes. Advantages of the linear trap design are increased ion storage capacity, faster scan times, and simplicity of construction. Recently, LITs have been combined with quadrupole, TOF and FTICR-MS. LITs can be used either as ionaccumulation devices or as commercially available, stand-alone mass spectrometers with MSn capabilities. The combination of QqQ MS with LIT technology in the form of an instrument of configuration Qq-LIT (like a QqQ but the third quadrupole is substituted by the LIT), using axial ejection, is particularly interesting because this instrument retains the classical QqQ scan functions such as SRM, product ion (PI), neutral loss (NL) and precursor ion (PC), while also providing access to sensitive ion-trap experiments. For small molecules, quantitative and qualitative analysis can be performed using the same instrument. Several studies such as determination of Ochratoxin A in wine and beer [76], avermectin residues in food [77] and fluoroquinolones in animal tissues [78], have already been developed using linear ion-trap MS. All these studies showed the good performance characteristics of this system that is replacing the popular QqQ. In this way, Garcia-Reyes et al. [42] presented a new approach based on LC-TOF-MS and LC-MS/MS analysis for the comprehensive screening of target pesticides. The proposed approach consists of three steps. First, samples are analysed by LC-TOF-MS and the proposed method provides the screening and preliminary identification of the species by retention time and m/z mass window, followed by subsequent identification (if positive results) by LC-TOF-MS accurate mass analysis (second step). Final confirmation and reliable quantitation is accomplished in the final step by LC-MS/MS analysis with two SRM transitions. This scenario, proposed for target pesticides, is complemented with the ability of LC-TOF-MS for the analyses of both non-target and unknown pesticides and the possibility of recording a data file as a history of each individual sample. The identification criteria, quantitation capabilities, and effectiveness of the proposed comprehensive screening method have been evaluated with various spiked food extracts and also in real samples obtaining satisfactory results. The potential of the proposed approach was tested with a large number of pesticides (i.e., 100). The optimization of MS parameters (declustering potential (DP), entrance potential (EP), collision cell entrance potential (CEP) for precursor ions, collision energy and collision cell exit potential (CXP) for product ions) was performed by flow injection analysis (FIA) for each compound. Table 2 shows the values of the parameters optimized and the SRM transitions used for the confirmation and quantification of the selected pesticides by LC-LIT-MS. For confirmation of the studied pesticides, two SRM transitions were used, and for quantification, the most intense SRM transition was selected.
Cyromazine Butoxycarboxin Carbendazim Thiabendazole Oxamyl Aldicarbsulfone Nitempyram Methomyl Chloridazon Thiametoxam Methiocarbsulfoxide Metamitron Cambendazole Imidacloprid Oxfendazole Dimethoate Acetamiprid Cymoxanil Albendazole Butocarboxin Methiocarbsulfone Thiacloprid Imazalil
Pesticide
6.2 9.7 8.8 8.8 9.7 10.2 8.8 11.5 15.0 11.5 11.2 13.8 9.8 15.3 12.5 16.3 16.01 18.1 17.3 18.4 17.6 18.2 16.8
tR (min)
167.0/85.1 223.1/106.2 192.4/160.2 202.0/131.2 220.1/72.2 223.2/148.1 271.2/99.1 163.3/106.1 222.0/92.0 292.2/211.2 242.2/185.2 203.1/175.3 303.1/217.3 256.3/209.2 316.2/159.1 230.1/199.2 223.2/126.2 199.1/128.2 266.2/234.1 213.2/75.0 258.2/122.1 253.2/126.1 297.1/159.1
SRM1
Identification
167.0/108.1 223.1/63.0 192.4/132.1 202.0/175.2 220.1/90.1 223.2/86.0 271.2/225.1 163.3/88.1 222.0/77.0 292.2/132.1 242.2/170.2 203.1/104.1 303.1/261.2 256.3/175.1 316.2/191.1 230.1/125.1 223.2/56.1 199.1/111.0 266.2/191.2 213.2/156.0 258.2/201.1 253.2/99.0 297.1/109.2
SRM2
5 8 5 8 8 5 5 5 5 5 5 5 5 5 5 5 5 8 5 5 10 5 5
Dwell time (ms)
37 35 52 59 37 45 51 20 60 41 42 42 66 56 63 38 50 32 64 77 44 52 20
DP
5 6 5 5 6 4 4 5 3 3 5 4 7 5 4 2.6 5 4 6 6 5 5 5
EP
14.90 16.47 15.61 15.88 16.39 16.48 17.82 14.80 16.44 18.41 17.01 15.91 18.71 17.40 19.08 16.67 16.48 15.80 17.68 16.20 17.46 17.32 18.55
CEP
(24, 28) (10, 16) (24, 42) (35, 42) (11, 21) (12, 20) (14, 20) (14, 14) (47, 38) (18, 24) (16, 32) (27, 23) (38, 22) (24, 26) (41, 26) (27, 14) (27.5, 31) (12, 23) (26, 46) (18, 12) (24, 11) (27.5, 56) (28, 26)
(2, 2) (1, 1) (3, 2) (2, 2) (1, 1) (3, 2) (3, 1) (1.8, 1.8) (1, 1) (3, 2) (3, 3) (1, 2) (3, 4) (2.5, 2) (2, 2) (2.2, 2.9) (2, 2) (3, 2) (2, 4) (1, 3) (2, 3) (2, 2) (2, 2.5)
Collision energy CXP (SRM1, (SRM1, SRM2) SRM2)
MS parameters
Table 2 LC-MS/MS method: SRM transitions and values of MS parameters optimized for SRM operation mode using a hybrid triple quadrupole linear ion trap system (QTRAP)
216 Yolanda Pico´
Mebendazole Aldicarb Oxadixyl Simazine Fluroxypyr Monuron Lenacil Pyrimethanil Spiroxamine Ethoxyquin Prometryn Fenbendazole Carbofuran Chlorotoluron Bendiocarb SpinosynA Fluometuron Atrazine Miconazole Metalaxyl Isoproturon Difenoxuron Diuron Monolinuron Ethiofencarb SpinosynD Metobromuron Dimethomorph Flazasulfuron
17.9 19.2 19.2 19.9 33.3 19.6 19.8 21.9 18.8 21.5 21.29 20.5 21.6 21.6 21.7 19.5 22.06 22.3 20.0 22.3 22.3 22.0 22.5 22.9 22.8 20.2 23.5 23.5 23.2
296.2/264.3 213.2/89.1 279.2/219.2 202.1/132.2 255.0/237.2 199.2/72.2 235.2/153.3 200.3/67.0 298.0/144.3 218.3/174.3 242.3/158.2 300.0/268.2 222.3/165.3 213.2/72.0 224.2/109.1 732.7/142.2 233.2/72.1 216.1/174.1 415.1/159.1 280.2/220.2 207.2/72.1 287.1/123.2 233.1/72.1 215.1/148.3 226.2/107.1 746.5/142.2 259.0/170.1 388.2/301.2 408.0/182.3
296.2/105.3 213.2/116.2 279.2/102.1 202.1/124.2 255.0/209.0 199.2/126.1 235.2/136.3 200.3/77.1 298.0/100.0 218.3/160.3 242.3/200.2 300.0/159.3 222.3/123.2 213.2/140.1 224.2/167.3 732.7/189.3 233.2/160.2 216.1/104.1 415.1/227.2 280.2/192.3 207.2/165.2 287.1/72.1 233.1/160.2 215.1/126.1 226.2/164.2 746.5/189.2 259.0/148.2 388.2/165.2 408.0/226.8
5 5 8 5 10 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 8 5 5 5
52 30 54 50 40 26 33 45 43 69 18 55 40 54 31 20 41 47 40 50 56 48 41 40 28 20 39 65 32
8 5 4 5 3 5 5 5 8 7 5 4 5 5 5 5 5 4 6 4 7 5 5 5 5 5 5 5 5
18.52 16.20 18.04 15.89 17.37 15.80 16.81 15.84 18.57 16.34 17.01 18.63 16.45 16.20 16.48 30.74 16.76 16.28 21.85 18.04 16.03 18.27 16.76 16.25 16.56 31.13 17.48 21.01 21.65
(26, (22, (13, (23, (13, (32, (25, (55, (29, (40, (22, (25, (16, (39, (10, (40, (34, (20, (40, (21, (33, (35, (34, (18, (21, (46, (26, (28, (30,
45) 15.8) 12) 25) 24) 34) 43) 58) 43) 44) 33) 46) 20) 32) 26) 42) 35) 40) 26) 22) 18) 23) 35) 22) 8) 40) 21) 40) 30)
(3, 2) (2, 2) (2, 2) (1.7, 1.79) (4, 2) (2, 2) (2, 2) (1, 1) (2, 1) (2, 2) (3, 3) (2, 2) (2, 2) (1, 2) (1, 4) (2, 2) (2, 2) (2.5, 2) (2, 2) (2, 3) (2, 7) (1, 2) (2, 2) (2, 2) (1.8, 2) (2, 2) (3, 3) (2.7, 2.3) (3, 4)
New Approaches in Mass Spectrometry
217
24.0 24.7 24.7 24.9 25.2 24.7 25.1 25.4 25.3 25.1 25.9 25.1 25.68 26.1 26.3 29.0 27.8 27.1
tR (min)
Identification
376.1/308.1 230.2/188.2 292.2/70.1 226.2/121.2 230.2/174.3 291.0/72.1 376.0/159.2 249.1/160.0 302.9/145.2 304.2/217.2 293.1/204.1 404.0/372.0 208.1/109.2 308.2/70.0 311.1/141.0 330.0/245.0 346.2/278.2 331.0/127.2
SRM1
Source: Reproduced from Ref. [42] with permission
Prochloraz Propazine Cyproconazole Methiocarb Terbuthylazine Chloroxuron Bromuconazole Linuron Methidathion Fenamiphos Chlorbromuron Azoxystrobin Promecarb Tebuconazole Diflubenzuron Iprodione Triflumizol Malathion
Pesticide
Table 2 (Continued )
376.1/266.1 230.2/146.2 292.2/125.1 226.2/169.2 230.2/146.1 291.0/218.1 376.0/70.0 249.1/182.2 302.9/84.9 304.2/234.2 293.1/182.2 404.0/344.0 208.1/151.3 308.2/125.2 311.1/158.2 330.0/101.0 346.2/73.1 331.0/285.2
SRM2
5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
Dwell time (ms)
40 48 63 20 48 62 47 50 20 63 48 40 32 48 40 50 30 43
DP
5 5 5 5 5 5 5 5 5 5 5 5 5 4 5 5 5 5
EP
20.76 16.67 18.41 16.56 16.67 18.38 20.76 17.20 18.71 18.74 18.43 21.54 16.05 18.86 18.94 19.47 19.92 19.50
CEP
(16, (31, (49, (24, (23, (40, (28, (22, (13, (26, (24, (20, (20, (40, (40, (15, (12, (16,
21) 21) 43) 13) 31) 34) 44) 19) 22) 20) 20) 33) 14) 49) 20) 32) 22) 12)
(3.2, 3) (2, 3) (1, 2) (2, 2) (3, 2) (3, 2) (2, 1) (3, 3) (1.3, 1.8) (2, 3) (3, 3) (3, 3) (3, 3) (1, 2) (1.5, 1.8) (4, 2) (3, 2) (2, 3)
Collision energy CXP (SRM1, (SRM1, SRM2) SRM2)
MS parameters
218 Yolanda Pico´
New Approaches in Mass Spectrometry
219
4. HIGH RESOLUTION MASS SPECTROMETERS IN TANDEM 4.1 Quadrupole time-of-flight mass spectrometer The quadrupole time-of-flight (QqTOF) mass spectrometer has been developed and introduced with the analysis of biopolymers, especially proteins, in mind. Nevertheless, it is also a useful instrument for the determination of small molecules. The QqTOF mass spectrometer consists of an MS1 and collision region adapted from a QqQ instrument and a reflectron-type orthogonal acceleration TOF analyser for MS2. It can basically be seen as a QqQ system with the last quadrupole replaced by a TOF analyser. In recent years, QqTOF instruments for environmental analysis have been accepted more significantly and the number of screening, quantitative and confirmatory methods reported in the literature is steadily increasing. Recent publications include application of LC-QqTOF-MS for: Screening, confirmation and quantitative analysis of target environmental contaminants (e.g., Sudan azo-dyes [25], pesticides and metabolites [79–81]). Screening and elucidation of unknown contaminants present in food [43,82]. Characterization of degradation products of selected contaminants [79,83]. The application of a hybrid QqTOF-MS technique to food contaminants analysis attains an unequivocal confirmation of the contaminants detected. The elimination of false positives and avoiding interpretation ambiguities are possible because of its unique characteristic of generating full-scan product-ion spectra with exact masses. The main fields of application are identification of unknowns and elucidation of structures proposed for transformation products, where the amount of information obtained allows secure identification of the identity of compounds. The advantages of this mass analyser are High resolution (5,000 fwhm), high sensitivity (fmol-amol), impressive mass accuracy, simplicity of calibration and high speed in MS/MS analysis with parallel scanning of MS1 and MS2. QqTOF delivers simple exact mass measurement of precursor and product ions with maximum sensitivity to yield the highest confidence in structural elucidation and databank search results. Compared to the QqQ instruments, QqTOF-MS/MS has the unique capability of determining accurate mass on the fragment ions generated in the collision cell, this ability is particularly important in the structural elucidation of unknowns. For example, the analysis of a pear sample, conventionally treated and taken from a supermarket, yielded the ultra high-performance liquid chromatography UPLC-QqTOF-MS chromatograms depicted in Figure 5, which illustrates the TIC, the extracted ion chromatograms (XICs) of the peaks that could be of interest, the mass spectra of these peaks and the tentative structure. Full-scan data acquisition ranging from m/z 100–500 pointed forward the presence of several small peaks at
220
Yolanda Pico´
Figure 5 (A) Total ion chromatograp (TIC) obtained from the UPLC-TOF-MS analysis of the studied pear extract, (B) extracted ion chromatogram (XIC) of m/z 149, (C) XIC of m/z 202, (D) XIC of m/z 192, (E) XIC of m/z 218 and (F) XIC of m/z 297. The mass spectrum corresponding to each peak is shown as an insert with the most probable structure. Reproduced from Ref. [84] with permission.
221
New Approaches in Mass Spectrometry
the beginning of the chromatogram and a series of main peaks between 3.5 and 6.4 min (Figure 5A). The mass spectra of all the signals visible in the chromatogram were analysed. Tentative identification has been carried out searching those chemically coherent elemental compositions in the Google website or in the ‘‘Merck Index Data Base’’. The peaks that have not been labelled in Figure 5A were identified as different phthalate esters (data not shown), which are extensively used as plasticizers in a variety of materials. On the others, three main peaks (number 2, 6 and 7) present the common mass spectra shown as an insert in Figure 5B, the ions at m/z 149.0209 and 177.0522 correspond with the protonated molecules of N,Nu-dimethylthioxamide and N,Nu-tetramethyldithioxamide. Both chemicals are used as rubber and latex additives and as components of the polymers used in electronic devices like polymer light-emitting diodes. This identification together with the fact that the three peaks eluted at similar time intervals indicated that they come from a plastic contamination. The hypothesis was confirmed later because methanol chromatograms started to show the same mass spectrum after a few injections of the same vial. The main drawbacks of the QqTOF according to these studies are the low dynamic range (response was never found linear for more than two orders of magnitude) and high detection limits compared with those obtained by the QqQ. Table 3 lists the key parameter: LOQs, for a group of selected pesticides which were the same for all the tested matrices [79]. These limits were calculated according to the guidelines of the European Commission for residue analytical methods for post-registration control and monitoring as the lowest analyte concentration that provides acceptable recoveries (W70%) and precision (o20%). QqQ working in SRM reaches, at least, 10-fold higher sensitivity for the majority of the compounds compared to the ITD and QqTOF. It is best suited to attain Table 3
LOQs obtained in fruit after PLE by the three instruments
Compound
Acrinathrin Bupirimate Buprofezin l-cyhalothrin Cyproconazole Fluvalinate Hexaflumuron Kresosim methyl Propanil Pyrifenox Pyriproxyfen Tebufenpyrad
LOQs (mg/kg) QqQ
ITD
QqToF
0.01 0.0001 0.0001 0.01 0.002 0.001 0.01 0.0005 0.001 0.0005 0.002 0.0005
0.01 0.005 0.01 0.4 0.01 0.2 0.02 0.01 0.02 0.01 0.02 0.01
0.02 0.01 0.05 0.3 0.05 0.4 0.04 0.05 0.07 0.03 0.05 0.05
Source: Reproduced from Ref. [79] with permission
222
Yolanda Pico´
LOQs well-below the strict MRLs regulated for these pesticides, which range from 0.01–5 mg/kg in the different selected fruits. However, it should be noted that for ITD, LOQs are higher than MRLs only for l-cyhalothrin in all matrices, apart from stawberry, and for fluvalinate in strawberry and cherry. For QqTOF, LOQs are higher than MRLs only for four pesticides, which are buprofezin in all matrices except orange, l-cyhalothrin in all matrices except strawberry, cyproconazole in orange, strawberry and cherry, and fluvalinate in strawberry and cherry. The main advantage attributed to this instrument is the unambiguous identification obtained by accurate MS/MS, as illustrated in Figure 6 for carbendazim and ethoxyquin.
4.2 Fourier transform ion cyclotron resonance and orbitrap mass analysers An orbitrap mass analyser is the most recent addition to the set of tools that can be applied to identification, characterization and quantitation of compounds in complex systems. With its ability to deliver low-ppm mass accuracy and extremely high resolution, all within a time scale compatible with nano-LC separations, the orbitrap has become an instrument of choice for many proteomic applications since its commercial introduction in 2005 [85,86]. However, its application to determine food contaminants residues is still rare [24]. Orbitrap is an unconventional ion trap because there is neither radio frequency (RF) nor a magnet to hold ions inside. Instead, moving ions are trapped in an electrostatic field [87,88]. The electrostatic attraction towards the central electrode is compensated by a centrifugal force that arises from the initial tangential velocity of ions: very much like a satellite on orbit. The electrostatic field that the ions experience inside the orbitrap forces them to move in complex spiral patterns. The axial component of these oscillations is independent of initial energy, angles and positions, and can be detected as an image current on the two halves of an electrode encapsulating the orbitrap. A Fourier transform is employed to obtain oscillation frequencies for ions with different masses, resulting in an accurate reading of their m/z. Such measurements achieve very high resolution matching that of FTICR instruments, and surpassing, by an order of magnitude, the resolution presently obtainable with TOF-MS. The orbitrap functions very efficiently as a high-resolving accurate mass detector. Although it may be possible to fragment ions in the orbitrap, it is more practical and faster to manipulate them in another mass analyser to which the orbitrap can be linked as a detector. Several ideas have been tried out to create a powerful hybrid system. Ultimately, it was determined that a LIT is an ideal partner for the orbitrap — it is exquisitely sensitive, very fast and capable of multiple levels of fragmentation commonly referred to as MSn. Often it is advantageous not to stop at MS2. The LTQ-Orbitraps is the only commercially available system featuring the orbitrap mass analyser. It consists of three main parts (Figure 7). The first section after the source is a LIT capable of detecting MS and MSn spectra at very high
Figure 6 Accurate product ion mass spectrum and proposed fragmentation of (A) carbendazim and (B) ethoxyquin. Proposed fragmentations are shown as an insert. Reproduced from Ref. [84] with permission.
New Approaches in Mass Spectrometry
223
Yolanda Pico´
API ion source
Linear ion Trap
C-Trap
Differential pumping
Orbitrap
Differential pumping
224
Figure 7 Schematic diagram of the LTQ-Orbitrap mass spectrometer.
sensitivity but relatively low resolution and mass accuracy. Ions accumulated in the LIT can be transferred into an RF-only quandrupole called C-trap due to its letter ‘C’ shape. The C-trap accumulates and stores the ions. This additional storage improves the analytical capabilities of the instrument. Also, higher energy collision fragmentations can be done in the C-trap, which is of considerable interest. The last part of the system is the orbitrap itself. It is filled by a pulse of ions accumulated in the C-trap. So in fact, this hybrid contains two complete mass analysers capable of detecting ions and recording spectra: the LIT and the orbitrap. Depending on the requirements for the analysis, the two analysers can be used independently or in concert. Although its application to determine food contaminants and residues is still rare, its wider acceptability is expected. LIT and LTQ-Orbitrap mass analysers were compared for determination of stanozolol and its analogues or metabolites 17-epistanozolol, 3-OH-stanozolol, 4-OH-stanozolol, 17-epi-16-OH-stanozolol, 16-OH-stanozolol, and the synthetic analogues 4-dehydrostanozolol, 17-ketostanozolol and methyl-3-OH-stanozolol [89]. Their structural elucidation by MS/MS provides information that can be utilized to identify further unknown metabolites or artificially modified analogues of stanozolol, such as the recent discoveries of synthetic growth promoters on the basis of the so-called designer steroids. Nielen et al. [90] compared LC coupled with orbitrap with different accurate mass alternatives such as TOF-MS or FTICR. In this study, mass resolution and accuracy are discussed for LC-MS screening and confirmation of targeted analytes and for the identification of unknowns using the anabolic steroid stanozolol and the designed b-agonist ‘‘Clenbuterol-R’’ as model substances. LC/QqTOF-MS/MS of stanozolol provides a full accurate mass spectrum of product ions. The ion at m/z 81.0494 confirms the C4H5N2 elemental composition of the pyrazole ring substructure (mass error +4.7 mDa or +58 ppm). However, the higher mass product ions obtained do not confirm stanozolol. The origin of strange accurate masses in the QqTOF-MS/MS analysis of stanozolol soon became apparent: as can be seen in Figure 8b, most of the product ions of stanozolol are
New Approaches in Mass Spectrometry
225
Figure 8 Characteristic details of (a) the QTOF-MS/MS and (b) LTQMS2/FTICR product ion mass spectra of stanozolol representing one example of the doublet product ions. Reproduced from Ref. [90] with permission.
actually doublets of distinct product ions having only minor exact mass differences. In FTICR and in FT Orbitrap MS these doublets are easily resolved but they will overlap at least partially at 5,000 fwhm mass resolution for m/z 161, as shown by the QqTOF-MS data in Figure 8a. As a result, an artificial single product ion is obtained showing an accurate but wrong average mass value upon mass measurement. This will be a typical result for bench-top (Q)TOF-MS
226
Yolanda Pico´
instruments; only high-end QqTOF-MS systems providing more than 13,000 resolution (fwhm) at m/z 160 would have resolved these doublets as well. The width of the signal at m/z 161 in Figure 2a might have been a trigger for being an artificial composite from a doublet. It should be noted, however, that such information is not always available since current TOF-MS instruments often show automatic centroiding and mass measurement routines in which detailed information about the peak shape is lost. As an example, a raw isolate of Clenbuterol-R was injected into an LTQMSn/FT Orbitrap MS system operated at a mass resolution of 100,000–200,000 fwhm and the accurate mass product ions thus obtained were compared with the QqTOF-MS/MS data at a mass resolution of 5,000 fwhm. Data shown in Table 4 pointed out that the QqTOF-MS/MS product ions are confirmed by the high resolution and higher mass accuracy data from the LTQMSn/FT Orbitrap MS system. Contrary to stanozolol, no doublet product ions showed up at higher mass resolution. A remarkable difference is the presence of the low intensity m/z Table 4 Comparison of accurate mass MSn and MS/MS data of the designed b-agonist Clenbuterol-R Product Elemental ion (m/z) composition
LTQMSn/FT LTQMSn/FT LC/QTOFMS/ Orbitrap MS Orbitrap MS MS measured measured mass error (ppm)
LC/ QTOFMS/MS mass error (ppm)
471 415 397 385 384 378 350 348 322 304 293 203 195 190 168 167 151 132 94 86
471.1721 415.1092 397.0976 385.0739 384.0665 378.1132 350.1049 n.d. 322.0503 304.0402 293.0241 203.0131 195.0910 189.9814 168.0441 167.0362 151.0175 132.0675 n.d. n.d.
+0.4 +1.0 n.d. +5.1 +6.8 +6.5 2.5 +6.8 +3.0 +3.3 +4.1 +2.8 +6.8 +6.9 +26.3 +12.8 6.1 +3.0 5.6 +12.5
C25H29N4OCl2 C21H21N4OCl2 C21H19N4Cl2 C20H17N3OCl2 C20H16N3OCl2 C19H22N3OCl2 C20H17N3OCl C20H15N3OCl C15H14N3OCl2 C15H12N3Cl2 C14H11N2OCl2 C8H9N2Cl2 C13H11N2 C7H6NOCl2 C8H9N2Cl C8H8N2Cl C8H6NCl C8H8N2 C6H8N C5H12N
Source: Reproduced from Ref. [90] with permission. Note: n.d.: not detected.
+1.7 +1.2 1.3 1.1 +0.0 0.6 1.6 n.d. 1.7 0.3 0.7 3.1 3.5 3.7 1.7 5.1 5.5 5.3 n.d. n.d.
471.1715 415.1091 n.d. 385.0763 384.0691 378.1159 350.1046 348.0922 322.0518 304.0413 293.0255 203.0143 195.0930 189.9834 168.0493 167.0392 151.0174 132.0686 94.0646 86.0975
New Approaches in Mass Spectrometry
227
397.0976 product ion in the LTQMS2/FT Orbitrap MS spectrum of m/z 471, becoming slightly more abundant in the LTQMS3/FT Orbitrap MS spectrum of m/z 471-415. The apparent loss of water from m/z 415 can be explained by rearrangement only since Clenbuterol-R does not have a hydroxyl but an ether group. The second discrepancy between the QqTOF-MS/MS and the LTQMSn/FT Orbitrap MS results is the product ion at m/z 348. This ion was suggested to be originated from m/z 384 by the neutral loss of HCl. However, contrary to the radical cation at m/z 385.0739, the product ion m/z 384 was hardly formed in LTQMS3/FT Orbitrap MS. The most abundant MS3 product ions are m/z 322.0508, 304.0402, 203.0131 and 195.0910. Note that LTQMS4/FT Orbitrap MS experiments of m/z 471-415-322 confirmed that m/z 304.0402 is not formed by the loss of water from m/z 322.0508 but obviously directly from m/z 415 following rearrangement.
5. CONCLUSIONS AND FUTURE TRENDS MS, combined with chromatography or not, is really needed in a routine food laboratory carrying out monitoring of contaminants and residues. Both GC-MS and LC-MS are indispensable tools to determine food contaminants and residues. Nowadays, LC-MS has become a priority without substituting GC-MS. They are not competitive but complementary techniques. A laboratory for food contaminants and residue analysis requires, at least, both types of instruments because each one has its own field of work. However, advances in MS are not so fundamental for GC-MS because the classical quadrupole with electron impact is still an appropriate technique for many determinations. Advances in GC-MS technology have led to dramatic improvements in sample throughput and sensitivity analytical performance. GC-MS produces a very consistent ionization that makes possible very large electronic libraries of verified standards for sample matching and confirmation of identity. The use of bench-top instruments with QqQ or ITD will certainly continue and increase in future years because of their relative ease of operation, selectivity, unequivocal identification capability and detection limits down to parts per trillion (ppt). GC-MS instruments used for food contaminants and residue analysis range from simple EI quadrupoles to GC GC-TOF-MS instruments that can decrease the detection limits, which will probably become routine in the near future. The new generation of fast-scanning TOF-MSs capable of working at high scan rates (500 scan/s) offers the ideal detection technique to couple with GC GC. This coupling will provide a powerful technique for the qualitative and the quantitative analysis of complex food samples, although software programs for automated handling and processing of the tremendous quantity of data generated by these systems will be required. True computer-assisted chemical analysis by GC GC, with mass spectral detection, appears plausible in the near future. Nowadays, there is a clear trend to increase the number of liquid chromatography applications in food contaminants and residue analysis, both in specific/individual and in multi-residue methods, especially after the
228
Yolanda Pico´
introduction into the market of robust, easily operated LC-MS instruments that provide a new way of analysing contaminants more sensitively and efficiently. This trend is closely bound to the evolution of modern LC-MS instruments and the improvements in the quality of their performance. MS research is focused mainly on expanding the implementation of mass analysers instead of on ionization sources, as it was 10 years ago. The sensitivity and specificity of pesticide analysis in food matrices have advanced by combining different designs of analysers in order to enlarge versatility and to increase application of MS2 (QqQ, ITD, LIT, QqTOF). In this situation, there is still a question over which instrument should be selected. The answer seems a bit complex, but exact mass seems required more and more in food laboratories. Over the past few years, there has been substantial progress in technologies employing the orthogonal acceleration TOF-MS for improved performance. TOF analysers represent a complementary approach to the routine QqQ for target as well as non-target analysis of a wide range of (semi)volatile organic compounds present in food. TOF and Qq-TOF instruments provide sufficiently accurate mass to carry out unequivocal confirmation of target compounds and investigate unknown contaminants. In this respect, and to clarify it, it is rather easy with a TOF to look for a comprehensive list of metabolites of a known pesticide in a complex sample but it is certainly much more difficult to investigate a real unknown compound. TOF instrumentation still needs to increase the availability of searchable databases of elements. The use of other types of high resolution and accurate mass instruments (e.g., Orbitrap and FT-ICR) is still rare because of their high cost that makes them unaffordable to most food laboratories. In that way, several works proposed an analytical strategy for the monitoring of food contaminants and residues consisted of a comprehensive approach to tackle this analytical problem. Target analysis of contaminants by LC-MS/MS provided accurate quantitative results for a group of selected compounds. Besides, LC-TOF-MS offers unique capabilities for identifying both non-target and unknown compounds, providing a dynamic methodology able to increase the scope of the monitoring program in a fast and simple way, with the inclusion of new compounds [42]. That means, at least, two LC-MS systems will be required for a comprehensive analysis.
REFERENCES 1 2 3 4 5 6 7
F.L. Brancia, Exp. Rev. Prot., 3 (2006) 143. F.J. Santos and M.T. Galceran, J. Chromatogr. A, 1000 (2003) 125. D.A. Volmer and L. Sleno, Spectroscopy, 20 (2005) 90. S.J. Lehotay and J. Hajslova, Trends Anal. Chem., 21 (2002) 686. T. Cajka and J. Hajslova, LC GC Eur., 20 (2007) 25. C. Soler and Y. Pico, Trends Anal. Chem., 26 (2007) 103. O. Nunez, E. Moyano and M.T. Galceran, Trends Anal. Chem., 24 (2005) 683.
New Approaches in Mass Spectrometry
8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
229
M. Kuster, M.L. de Alda and D. Barcelo, Mass Spectrom. Rev., 25 (2006) 900. A. Juan-Garcia, G. Font and Y. Pico, J. Sep. Sci., 28 (2005) 793. G. Font, M. Ferna´ndez, M.J. Ruiz and Y. Pico, Electrophoresis, (2008). H.U. Melchert and E. Pabel, J. Chromatogr. A, 1056 (2004) 195. K. Patel, R.J. Fussell, D.M. Goodall and B.J. Keely, Analyst, 128 (2003) 1228. M.R.R. Agustin, H.M. Park, S.M. Hong, J.C. Ryu and K.B. Lee, J. Chromatogr. A, 1085 (2005) 278. F.E. Ahmed, Trends Anal. Chem., 22 (2003) 170. T.D. Bucheli and R.C. Brandli, J. Chromatogr. A, 1110 (2006) 156. T. Cajka and J. Hajslova, J. Chromatogr. A, 1058 (2004) 251. T. Cajka, J. Hajslova, R. Kazda and J. Poustka, J. Sep. Sci., 28 (2005) 601. J.L.M. Vidal, F.J.A. Liebanas, M.J.G. Rodriguez, A.G. Frenich and J.L.F. Moreno, Rapid Commun. Mass Spectrom., 20 (2006) 365. Y. Pico, C. Blasco and G. Font, Mass Spectrom. Rev., 23 (2004) 45. Y. Pico, G. Font, M.J. Ruiz and M. Fernandez, Mass Spectrom. Rev., 25 (2006) 917. A.A.M. Stolker and U.A.T. Brinkman, J. Chromatogr. A, 1067 (2005) 15. V. Andreu and Y. Pico, Curr. Anal. Chem., 1 (2005) 241. M.S. Diaz-Cruz and D. Barcelo, Trends Anal. Chem., 26 (2007) 637. D. Barcelo and M. Petrovic, Trends Anal. Chem., 26 (2007) 2. F. Calbiani, M. Careri, L. Elviri, A. Mangia and I. Zagnoni, J. Chromatogr. A, 1058 (2004) 127. X.Y. Cui, X.W. Gao, X.G. Chu, W. Yong, Y. Ling, M.L. Yang, X.Q. Li, D.N. Wang, Y.Y. Fang and J.A. Zweigenbaum, Anal. Lett., 40 (2007) 1117. P. Pais and M.G. Knize, J. Chromatogr. B Analyt. Technol. Biomed. Life Sci., 747 (2000) 139. J. Ohnesorge, C. Neususs and H. Watzig, Electrophoresis, 26 (2005) 3973. P. Schmitt-Kopplin and M. Englmann, Electrophoresis, 26 (2005) 1209. I. Cotte-Rodriguez, C.C. Mulligan and G. Cooks, Anal. Chem., 79 (2007) 7069. R.B. Dixon, M.S. Bereman, D.C. Muddiman and A.M. Hawkridge, J. Am. Soc. Mass Spectrom., 18 (2007) 1844. A.D. Zamfir, J. Chromatogr. A, 1159 (2007) 2. C.C. Liu, J.F. Alary, P. Vollmerhaus and M. Kadkhodayan, Electrophoresis, 26 (2005) 1366. J.C.M. Waterval, P. Bestebreurtje, H. Lingeman, C. Versluis, A.J.R. Heck, A. Bult and W.J.M. Underberg, Electrophoresis, 22 (2001) 2701. A. Keil, N. Talaty, C. Janfelt, R.J. Noll, L. Gao, Z. Ouyang and R.G. Cooks, Anal. Chem., 79 (2007) 7734. H.W. Chen, J. Zheng, X. Zhang, M.B. Luo, Z.C. Wang and X.L. Qiao, J. Mass Spectrom., 42 (2007) 1045. E.M. Thurman, I. Ferrer and J.A. Zweigenbaum, Anal. Chem., 78 (2006) 6702. I. Ferrer and E.M. Thurman, Trends Anal. Chem., 22 (2003) 750. I. Ferrer, J.F. Garcia-Reyes and A. Fernandez-Alba, Trends Anal. Chem., 24 (2005) 671. S. Lacorte and A.R. Fernandez-Alba, Mass Spectrom. Rev., 25 (2006) 866. J.F. Garcia-Reyes, M.D. Hernando, A. Molina-Diaz and A.R. Fernandez-Alba, Trends. Anal. Chem., 26 (2007) 828. J.F. Garcia-Reyes, M.D. Hernando, C. Ferrer, A. Molina-Diaz and A.R. Fernandez-Alba, Anal. Chem., 79 (2007) 7308. A. Gentili, M. Sergi, D. Perret, S. Marchese, R. Curini and S. Lisandrin, Rapid Commun. Mass Spectrom., 20 (2006) 1845. B. Gilbert-Lopez, J.F. Garcia-Reyes, P. Omega-Barrales, A. Molina-Diaz and A.R. Fernandez-Alba, Rapid Commun. Mass Spectrom., 21 (2007) 2059. E.M. Thurman, I. Ferrer and A.R. Fernandez-Alba, J. Chromatogr. A, 1067 (2005) 127. J.F. Garcia-Reyes, A. Molina-Diaz and A.R. Fernandez-Alba, Anal. Chem., 79 (2007) 307. J.F. Garcia-Reyes, I. Ferrer, E.M. Thurman, A. Molina-Diaz and A.R. Fernandez-Alba, Rapid Commun. Mass Spectrom., 19 (2005) 2780. E.M. Thurman, I. Ferrer, J.A. Zweigenbaum, J.F. Garcia-Reyes, M. Woodman and A.R. FernandezAlba, J. Chromatogr. A, 1082 (2005) 71. J. Wang and D. Leung, Rapid Commun. Mass Spectrom., 21 (2007) 3213.
230
50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90
Yolanda Pico´
Z.P. Wu, Lc Gc North America (2007), p. 45. E.M. Thurman, I. Ferrer, O. Malato and A.R. Fernandez-Alba, Food Addit. Contam., 23 (2006) 1169. E. Barcelo-Barrachina, E. Moyano and M.T. Galceran, J. Chromatogr. A, 1054 (2004) 409. L. Dunovska, T. Cajka, J. Hajslova and K. Holadova, Anal. Chim. Acta, 578 (2006) 234. C.C. Leandro, P. Hancock, R.J. Fussell and B.J. Keely, J. Chromatogr. A, 1166 (2007) 152. J.F. Focant, G. Eppe, M.L. Scippo, A.C. Massart, C. Pirard, G. Maghuin-Rogister and E. De Pauw, J. Chromatogr. A, 1086 (2005) 45. E. Hoh, K. Mastovska and S.J. Lehotay, J. Chromatogr. A, 1145 (2007) 210. P.P. Bolanos, A.G. Frenich and J.L.M. Vidal, J. Chromatogr. A, 1167 (2007) 9. J.L.M. Vidal, F.J.A. Liebanas, M.J.G. Rodriguez, A.G. Frenich and J.L.F. Moreno, Rapid Commun. Mass Spectrom., 20 (2006) 365. P.P. Bolanos, J.L.F. Moreno, D.D. Shtereva, A.G. Frenich and J.L.M. Vidal, Rapid Commun. Mass Spectrom., 21 (2007) 2282. M. Okihashi, S. Takatori, Y. Kitagawa and Y. Tanaka, J. AOAC Int., 90 (2007) 1165. F. Hernandez, T. Portoles, E. Pitarch, F.J. Lopez, J. Beltran and C. Vazquez, Anal. Chem., 77 (2005) 7662. A.G. Frenich, P.P. Bolanos and J.L.M. Vidal, J. Chromatogr. A, 1153 (2007) 194. A. Garrido Frenich, J.L. Martinez Vidal, A.D. Cruz Sicilia, M.J. Gonzalez Rodriguez and P. Plaza Bolanos, Anal. Chim. Acta, 558 (2006) 42. S. Walorczyk and B. Gnusowski, J. Chromatogr. A, 1128 (2006) 236. G. Sagratini, J. Manes, D. Giardina, P. Damiani and Y. Pico, J. Chromatogr. A, 1147 (2007) 135. C. Soler, J. Manes and Y. Pico, J. Chromatogr. A, 1109 (2006) 228. B. Gomara, L. Herrero, L.R. Bordajandi and M.J. Gonzalez, Rapid Commun. Mass Spectrom., 20 (2006) 69. C. Blasco, G. Font and Y. Pico, J. Chromatogr. A, 1098 (2005) 37. C. Soler, J. Manes and Y. Pico, J. Chromatogr. A, 1088 (2005) 224. C. Medana, P. Calza, C. Baiocchi and E. Pelizzetti, Curr. Org. Chem., 9 (2005) 859. C. Soler, J. Manes and Y. Pico, J. Chromatogr. A, 1067 (2005) 115. C. Blasco, G. Font and Y. Pico, J. Chromatogr. A, 1043 (2004) 231. P. Rovellini, Rivista Italiana Delle Sostanze Grasse, 82 (2005) 299. H.U. Melchert and E. Pabel, J. Chromatogr. A, 1056 (2004) 195. J. Malavia, M. Abalos, F.J. Santos, E. Abad, J. Rivera and M.T. Galceran, J. Chromatogr. A, 1149 (2007) 321. A. Bacaloni, C. Cavaliere, A. Faberi, E. Pastorini, R. Samperi and A. Lagana, J. Agric. Food Chem., 53 (2005) 5518. M.D. Hernando, J.M. Suarez-Barcena, M.J.M. Bueno, J.F. Garcia-Reyes and A.R. Fernandez-Alba, J. Chromatogr. A, 1155 (2007) 62. M. Lolo, S. Pedreira, B.I. Vazquez, C.M. Franco, A. Cepeda and C.A. Fente, Anal. Bioanal. Chem., 387 (2007) 1933. C. Soler, K.J. James and Y. Pico, J. Chromatogr. A, 1157 (2007) 73. C. Soler, B. Hamilton, A. Furey, K.J. James, J. Manes and Y. Pico, Anal. Chem., 79 (2007) 1492. J.M. Halket, D. Waterman, A.M. Przyborowska, R. K .P. Patel, P.D. Fraser and P.M. Bramley, J. Exp. Bot., 56 (2005) 219. J.F. Van Bocxlaer, S.R.V. Casteele, C.J. Van Poucke and C.H. Van Peteghem, Anal. Chim. Acta, 529 (2005) 65. Y. Pico, M. Farre´, C. Soler and D. Barcelo, Anal. Chem., 79 (2007) 9350. Y. Pico, M. Farre´, C. Soler and D. Barcelo, J. Chromatogr. A, 1176 (2007) 123. M. Scigelova and A. Makarov, Proteomics, 6 (Suppl. 2) (2006) 16. G.D. Chen, B.N. Pramanik, Y.H. Liu and U.A. Mirza, J. Mass Spectrom., 42 (2007) 279. Q.Z. Hu, R.J. Noll, H.Y. Li, A. Makarov, M. Hardman and R.G. Cooks, J. Mass Spectrom., 40 (2005) 430. M. Hardman and A.A. Makarov, Anal. Chem., 75 (2003) 1699. M. Thevis, A.A. Makarov, S. Horning and W. Schanzer, Rapid Commun. Mass Spectrom., 19 (2005) 3369. M.W.F. Nielen, M.C. van Engelen, R. Zuiderent and R. Ramaker, Anal. Chim. Acta, 586 (2007) 122.
CHAPT ER
8 Capillary-Based Separation Techniques Peter Viberg
Contents
1. 2. 3. 4.
Introduction Miniaturization and the Capillary Format Capillary Liquid Chromatography Capillary Electroseparations 4.1 Instrumentation 4.2 Electroosmotic flow and Joule heating 4.3 Band broadening 4.4 Capillary electrophoresis 4.5 Capillary chromatographic electroseparation techniques 5. Detection Techniques in Capillary-Based Separations 6. Automation and On-Line/In-Capillary Coupled Solid-Phase Extraction in Capillary Electrophoresis 7. Applications in Determination of Food Contaminants Using Capillary Electrophoresis References
231 232 233 235 235 236 239 239 241 250 251 252 253
1. INTRODUCTION The rapid advances in analytical chemistry place great demands on the development of new efficient separation techniques. Frequently, numerous samples, which are provided in very small volumes, need to be analysed rapidly, and the samples often consist of analytes at low concentration in complex mixtures of matrix constituents. One way to tackle these needs is to use highly efficient miniaturized separation techniques, and such techniques have been developed during past decades. This chapter will focus on describing different capillary-based separation techniques. Capillary-based separation techniques comprise several different modes of separation that have gained in popularity due to different miniaturization Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00008-1
r 2008 Elsevier B.V. All rights reserved.
231
232
Peter Viberg
advantages. The capillary-based separation techniques are associated with low solvent and sample consumption, short analysis time, and sometimes high detection sensitivity. Furthermore, separations obtained using capillary-based separation techniques often show excellent separation efficiencies. These characteristics make them suitable for analysis of small sample amounts, small sample volumes, trace analysis, and high sample throughput analysis. Several capillary-based separation techniques will be described in this chapter, including capillary liquid chromatography (CLC), capillary electrophoresis (CE), capillary electrochromatography (CEC), and capillary electrokinetic chromatography (EKC). Theoretical aspects and separation mechanisms will be discussed together with instrumentation descriptions and different modes of sample treatment. Automation and on-line coupling will also be discussed and practical tips will be included in the text. The different capillary-based techniques will be compared with each other as well as with other traditional separation techniques. The performance of the capillary-based techniques is very beneficial in the field of determination of food contaminants, and different applications within this field will be mentioned.
2. MINIATURIZATION AND THE CAPILLARY FORMAT The trend in analytical chemistry over several decades has been to decrease the dimensions of the analytical equipment. For example, the development of miniaturized liquid chromatography (LC) techniques has evolved from traditional analytical-sized systems, over micro-bore LC, to capillary-based systems (Table 1). It is evident that as the column diameters decrease from analyticalsized columns to capillary columns, the surface-to-volume ratio is dramatically increasing. As a consequence, a potential risk with miniaturized columns is that the surface of the column has undesired effects on the separation. For example, analytes may adsorb to or interact with the capillary wall resulting in spreading and tailing of the analyte zone with resulting less-efficient separations. On the other hand, in electroseparation systems, the large surface-to-volume ratio associated with capillaries is beneficial as it allows for efficient transfer of Joule heat [1] from the capillary (Joule heat appears from the electrical resistance of the Table 1
a
Different column dimensions used for LC
LC type
Internal diameter (mm)
Column volumea (mL)
Surface-to-volume ratio (mm1)
Analytical Microbore Capillary (larger bore) Capillary (smaller bore)
4,600 1,000 100 10
16,600 790 7.9 0.079
0.87 4 40 400
Calculated per metre column.
Capillary-Based Separation Techniques
233
background electrolyte when a high voltage is applied over the capillary). Furthermore, the large surface-to-volume ratios in combination with the small column dimensions make open-tubular columns practical. Open-tubular columns have some benefits that will be discussed later. The very low volumes of the separation capillaries require that the dead volumes in the system are kept as small as possible. Connecting tubes must be kept as short as possible and have small internal diameters, or they may result in severe band broadening. Great care must also be taken towards using tubeconnectors that introduce as small dead volumes as possible. ‘‘Zero-dead volume’’ connectors are commercially available, but great care must be taken when cutting the capillaries or tubes to get smooth and flat ends, or else significant dead volumes will be introduced. A 100-mm transfer tube (7.85 mL per meter tube) may add little to the dead volume for an HPLC column with an internal diameter of 4.6 mm, but with a capillary column with a 50-mm internal diameter the dead volume from the tube would be devastating and the analytes risk to spend as long time in the tube as in the columns, with resulting band broadening caused by longitudinal diffusion of the analytes. A great benefit with capillary columns is that they, as a result of their flexibility, often can be connected directly to the valves and detectors without any additional tubes connecting them (providing that the column is not too short). With UV-VIS absorption detection, on-column detection is preferred as it does not add to the dead volume. The small volumes of the capillary columns (Table 1) also results in a low consumption of mobile phases and buffers, which can considerably reduce the costs for the analysis and make it more environmentally friendly. For example, a capillary column with a 100-mm internal diameter consumes considerably less than 1% of the solvent consumed by an analytical-sized column with a diameter of 4.6 mm. When capillary-based separation techniques are discussed, the term capillary usually refers to a capillary made of fused silica coated with polyimide, in which the analytes are separated. Such fused silica capillaries are strong, long-lasting, and robust over wide ranges of buffers and solvents. The polyimide coating protects the capillary from breaking and makes it easy to handle. The capillaries are relatively cheap and readily available in several dimensions. The most widely used separation capillaries have internal diameters ranging from 10 to 200 mm, but several other dimensions exist. In addition to this, capillaries with crosssections other than circular are commercially available, for example, squared capillaries. Fused silica is an ideal material for electroseparations as it provides sufficient electrical insulation, and because it is transparent to UV-VIS light, which enables on-column detection.
3. CAPILLARY LIQUID CHROMATOGRAPHY CLC is a miniaturized version of traditional HPLC, and a CLC system is, therefore, similar to an ordinary HPLC system (Figure 1). The preparation of packed capillary columns with high separation efficiencies have gradually
234
Peter Viberg
INJECTOR SPLITTER
COLUMN
PUMP DETECTOR Mobile phase reservoirs
Waste
Figure 1 Schematic diagram of an example of a typical instrumentation used for LC separations. The splitter can be either included in the pump or it can be externally fitted. In the case of isocratic LC, the waste flow from the splitter may be recirculated back to the mobile phase reservoir and thus reused. The detector may be of on-column or post column type. If a mass spectrometer is used as detector, there will not be a flow from the detector to waste. Injection of sample may be performed either from an external syringe, or from an internal injection device.
developed from columns with internal diameters of several hundreds of micrometer [2,3] down to diameters well below 100 mm [4–6]. The separation in LC is based on partitioning of the analytes between a stationary phase and a mobile phase. Reversed phase chromatography is the most common, but also normal phase and ion-exchange chromatography are frequently performed. The stationary phase is often immobilized on 3–10 mm silica-based particles, but monolithic phases are also commonly used. The very small volumes of the capillary columns (Table 1), require much lower volumetric flow rates of the mobile phase, than analytical-sized equipments do. Typical volumetric flow rates for capillary columns are found in the range from a few mL min1 down to nL min1. Such low flow rates require either special pumps, or that a larger flow is split before entering the separation column. In isocratic LC, splitting may be performed using a fixed splitter. However with gradient LC, due to the changes in the viscosity of the mobile phase over the gradient, a dynamic splitter should be used to maintain a constant volumetric flow rate. Commercial pumps with flow-meters and automatically adjusted splitters are available for such purposes. The small volumes of the capillary columns (and the corresponding small volume of the stationary phase) require small injection volumes of much less than 1 mL to avoid stationary phase over-loading and to avoid peak broadening. Commercial loop injectors are available for sample injections down to tens of nanoliter, but for injection of smaller volumes, timed injections are required. However, larger injection volumes can be tolerated if the analytes are dissolved in a solvent with very low elution strength, in which case the analytes will be stacked on the top of the
Capillary-Based Separation Techniques
235
column and the volume will be of less importance. However, there is a risk of over-loading the stationary phase during stacking. A lot of effort has been put into the development of both improved solid phase particles, and of new solid phases for LC. Different types of columns and stationary phases are discussed below under ‘‘CEC with immobilised stationary phases’’.
4. CAPILLARY ELECTROSEPARATIONS Capillary electroseparation techniques include both chromatographic and electrophoretic separations, as well as combinations of the two modes [7,8]. Therefore, analytes can be separated by capillary electroseparation techniques on the basis of either their charge-to-size ratios, or their chromatographic properties.
4.1 Instrumentation The instrumentation normally used for capillary electroseparations is illustrated in Figure 2. The instrumentation includes a capillary (that may contain a stationary phase) in which the separations take place, and a high voltage supply that is used to produce an electroosmotic flow (EOF) through the capillary, and to electrophoretically separate charged analytes. A detector and a means of injecting High Voltage −
+
Capillary
Electrode EOF
Po
Outlet vial
Pi
Inlet vial
Figure 2 Schematic diagram of a typical instrumentation used for capillary electroseparations. The ends of an electrolyte-filled capillary are submerged in electrolytecontaining vials and a high voltage potential is applied over the vials via electrodes. One or both vials can be pressurised (P0 and Pi) to facilitate injections or modifications to the flow velocity during the separation. On-column absorbance detection usually takes place on the outlet region of the capillary. In case of on-line ESI-MS detection, the outlet end of the capillary terminates at the interface of the mass spectrometer instead of in the outlet vial.
236
Peter Viberg
the sample are other important parts of the system. Small and precise volumes can be injected, for example, by applying pressure to the inlet vial for welldefined times (Equation (1) can be used to calculate the injection volume for open-tubular capillaries applied in, for example, CE), or by electrokinetic pumping (where the EOF is used to pump sample into the capillary). During separation, the inlet end of the capillary is submerged in an electrolyte-containing vial, while the outlet end of the capillary terminates in either an electrolytecontaining vial or at the interface to a mass spectrometer. Vinj ¼
DPpd4 t 128ZL
(1)
where Vinj is the injection volume, DP the pressure difference over the capillary, d the internal diameter of the capillary, t the injection time, Z the viscosity of the electrolyte, and L the length of the capillary.
4.2 Electroosmotic flow and Joule heating During capillary electroseparations, a high voltage potential is applied over both ends of the separation capillary. This potential results in electrophoretic transport of electrolyte through the capillary, an EOF [1], as illustrated in Figure 3. In an High Voltage
Electric Double layer
Figure 3 Schematic diagram of an electrolyte-filled fused silica capillary with a high voltage applied over the ends. An electric double layer of cations is formed close to the negatively charged capillary wall (inset), and as a result, a flow (EOF) is created through the capillary. The obtained flat flow velocity profile is illustrated by the arrows. For clarity, anions in the electrolyte are not drawn.
Capillary-Based Separation Techniques
237
electrolyte-filled capillary, the negative silanol groups of the fused silica (present above approximately pH 2) will attract cations from the electrolyte resulting in a decreasing concentration gradient of cations from the capillary wall towards the centre of the capillary. Due to ion-pairing between the cations from the electrolyte and the negative charges on the capillary wall, the cations closest to the capillary wall will form a fixed layer known as the Stern layer. The ions just outside of the Stern layer ions will form a diffuse layer, and together these two layers form the electric double layer. In the electric field created in the capillary by the high voltage applied over the capillary, cations in the diffuse layer will move towards the cathode, dragging the bulk liquid along, which results in a flow with a characteristic flat flow velocity profile. The flat flow velocity profile is believed to exist as long as the distance between the charged surfaces (or the diameter of an open-tubular separation capillary) is at least 10 times larger than the width of the electrical double layer [1,7]. This is the case in most practical open-tubular capillary electroseparation capillaries, but may not be the case in the passages between the stationary phase particles in a packed particle column. A flat flow velocity profile is beneficial for separation purposes as it does not add to band broadening [1]. Figure 4 illustrates the difference between the velocity profiles of the EOF and a hydrodynamically pumped flow. A hydrodynamically pumped flow has the highest velocity in the centre of the channel and the flow decreases towards the walls of the channel. Therefore, analytes present at different distances from the channel wall will move at different rates resulting in the spreading of the sample zone. The magnitude of the EOF can be altered by changing the viscosity and permittivity of the electrolyte, being for example, a function of the amount of organic modifiers and the ionic strength [9,10]. Furthermore, the magnitude of the EOF shows a strong dependence with the pH in the electrolyte, as the number of charges of the silanol groups on the capillary wall will change with pH. At a pH below 2, the capillary wall will not be negatively charged and consequently there will be no EOF. The charges on the capillary wall can also be affected by using different coatings adsorbed or bound to the capillary wall [11–15]. The coatings can be, for example, polymers or surfactants, and the aim is often to yield a capillary that produces an EOF that is independent of the pH. By using cationic polymers the capillary wall can be coated with positive charges instead of negative charges and the direction of the EOF can be reversed [16]. The volumetric flow velocity of the electrolyte through the capillary can also be changed by applying pressure to either the inlet or the outlet end of the capillary [17]. Modifications to the volumetric flow velocity can be made, for example, in order to obtain a high enough flow rate to support electrospray ionization (ESI) mass spectrometric (MS) detection (ESI requires a minimum flow rate to result in a stable and quantitative MS detection). To obtain a stable and reproducible EOF, the capillary should be washed with sodium hydroxide solution prior to use, in order to free the negative charges on the capillary wall, followed by careful washing with water and finally running electrolyte.
238
Peter Viberg
Hydrodynamic flow velocity profile (pressure driven)
Flow velocity profile (electrokinetically driven)
Figure 4 Top: Flow velocity profile for a hydrodynamically driven flow that is driven by a pressure gradient over the capillary. Lower: Flow velocity profile for EOF, which is driven by a voltage difference over the capillary.
The electrical current resulting from the high voltage applied over the capillary, in combination with the electrical resistance of the electrolyte, produces heat during an electroseparation. This Joule heating [1,10] is disadvantageous as it results in a heat gradient from the centre of the capillary to its walls, with a corresponding change in viscosity, which disturbs the flat flow velocity profile. Thus, if the Joule heating is not kept low it may lead to band broadening and loss in separation efficiency. If the Joule heating is too strong it may even result in bubble formation or even boiling in the capillary which will destroy the separation and likely result in a current break-down. However, the high surface-to-volume ratio of the capillary allows for efficient heat-transfer from the capillary which enables favourably high voltages to be used, compared to, for example, traditional gel-electrophoresis. The Joule heat can be further controlled by decreasing the current through the capillary by, for example, using
Capillary-Based Separation Techniques
239
low ionic strengths of the background electrolyte. Normally, acceptable buffering capacities are obtained with electrolytes with ionic strengths around or below 50 mmol L1.
4.3 Band broadening CE has gained a high interest partly because of its capacity for very high efficiency separations in short times. The small diameter capillaries allow for high field strength to be used, with resulting rapid separations, without being disturbed by Joule heating. Furthermore, the open-tubular column employed eliminates the multiple path term in the van Deemter equation, and the lack of stationary phase eliminates mass transfer associated band broadening. Because of this and the flat flow velocity profile in CE, the main reason for band broadening in CE is longitudinal diffusion of the analytes, which is why CE often yields extra high separation efficiencies with macromolecules that have very slow diffusion rates (minimising band broadening from longitudinal diffusion in the capillary). Also CEC and EKC benefit from flat flow velocity profiles, but the use of stationary phases in CEC and in CLC, and pseudostationary phases in EKC, will add to the band broadening. Band broadening is partly the result of limitations in mass transfer with these chromatographic techniques. The limitations in mass transfer results in some analytes being swept away by the mobile phase (or the background electrolyte) before they have time to equilibrate with the stationary (or pseudostationary) phase, while other analytes still remain in the stationary (or pseudostationary) phase. By reducing the particle diameters in packed columns the distances between the particles will be reduced, which results in improved mass transfer. However, particularly with CLC, the pressure drops with small particles add practical lower limits around 3 mm particles or slightly below. With pseudostationary phases in CEC and EKC systems however, no pressure drops occur and very efficient separations can be obtained with, for example, nanoparticles or micelles that have very small interparticle distances in the background electrolyte. Several other effects also affect the band broadening in capillary separations, for example, the monodispersity of the stationary phase particles. Also Eddy diffusion and the porosity of stationary or pseudostationary phases will affect band broadening.
4.4 Capillary electrophoresis Electrophoresis was first described as a separation technique by Tiselius in the first part of the twentieth century [18–20]. The first step towards miniaturization of electrophoretic separation was taken by Hjerte´n in the 1960s, when he described electrophoresis in narrow bore tubes [21]. CE in its modern form occurred in the early 1980s [22–24]. CE, as other electrophoretic separation techniques, is based on different mobilities of analytes with differences in their charge-to-size ratios, in an electrical field. Therefore only charged analytes, and
240
Peter Viberg
not neutrals, can be separated in CE. An ion in an electrical field has a mobility expressed by Equation (2). q (2) mep ¼ 6pZR where mep is the electrophoretic mobility of the ion, q the charge of the ion, Z the viscosity of the electrolyte, and R the ion radius. Thus, according to Equation (2), the larger the size of the ion the smaller the electrophoretic mobility, and the higher the charge, the larger the electrophoretic mobility. The reasons for this being that a larger analyte ion has a greater friction in the background electrolyte than a smaller and that a higher charge gives the ion a stronger force in the electric field. The relation between electrophoretic velocity, electrophoretic mobility, and electric field strength is given by Equation (3). uep ¼ mep E
(3)
where uep is the electrophoretic velocity of the ion and E the electric field strength. During a CE separation, a charged analyte will have a velocity and a mobility through the capillary that is affected both by the electrophoretic mobility of the ions and the EOF. The apparent mobility of an ion is the sum of the electrophoretic mobility of that ion and the electroosmotic mobility, which can be obtained from experimental data by calculating the velocity for the analyte and that of an uncharged species, respectively and converting these velocities into mobilities. A drawback with CE is its limitations in the analysis of diluted samples. The lack of a stationary phase in CE does not allow for sample stacking, as is commonly employed in chromatographic techniques. Instead, several sample concentration techniques have been developed for CE: Field amplified stacking (FASS) [25–27] is used as an easy and straightforward means to concentrate the analytes in the sample plug in the capillary. FASS relies on a much lower ionic strength in the sample compared to the background electrolyte surrounding the sample in the capillary. A lower ionic strength means a lower electrical conductivity and therefore a higher electrical resistance, resulting in higher field strength in the sample plug compared to in the surrounding background electrolyte. According to Equation (3), an increase in field strength will result in a higher velocity for charged species. In practise, this means that analyte ions will move fast through the sample plug until they reach the interface with the background electrolyte where they will be subjected to a lower field strength resulting in a lower velocity and consequently the analytes will be concentrated, or stacked, in a thinner band. It is therefore often recommended for CE that samples are prepared with a low conductivity, or that samples with high salt concentrations are desalted prior to analysis. In isoelectric focusing (IEF) [28], the separation is based on different isoelectric points (pI) of the analytes. A pH gradient is maintained in the capillary and the analytes will, when a high voltage is applied over the capillary, move in the gradient until they reach the point where their pI equals the pH. There they will be electrically neutral and their movement will be terminated
Capillary-Based Separation Techniques
241
and the analytes will be concentrated. Other efficient concentrating techniques applicable to the capillary format include isotachophoresis [29,30] and sweeping [31]. CE can also be combined with different types of on-line or in-capillary solid phase extractions (SPE) techniques. In addition to these sample concentration techniques different improvements can be made to the detection of diluted samples (see section Detection techniques in capillary-based separations).
4.5 Capillary chromatographic electroseparation techniques In capillary chromatographic electroseparation techniques, the separation is based on partitioning of analytes between two phases that move at differential velocities [1,8]. In that sense, capillary chromatographic electroseparation techniques are similar to other types of chromatographic techniques. However, in contrast to, for example, LC, the flow through the column is generated by electroosmosis [7]. Often one of the phases is a solid stationary phase and the other a liquid mobile phase. The most straightforward example of capillary chromatographic electroseparation techniques being the use of a capillary column packed with stationary phase particles through which a mobile phase is pumped by EOF [23,32], in which case the technique generally is referred to as CEC. Other examples include the use of a moving stationary phase, or a pseudostationary phase. Such techniques are generally referred to as EKC techniques. Because of the stationary phase, neutral analytes can be separated in capillary chromatographic electroseparation techniques, but also charged analytes, which can be separated by combined forces of chromatographic and electrophoretic separation mechanisms. Capillary electrochromatographic separation techniques combine the excellent separation resolution of HPLC with the high-efficiency separations obtained with CE, which make these techniques very advantageous.
4.5.1 CEC with immobilized stationary phases The first successful development of CEC was performed in the 1980s, using 170 mm i.d. capillary columns packed with 10 mm particles [23]. Since then, improved columns have been developed, with smaller internal diameters and smaller stationary phase particles. The capillary columns employed for CEC are often the same as can be used with CLC systems. Because electroosmosis is used to pump the mobile phase in CEC, instead of a pressure difference as in LC, the pressure drop over the column is not as important in CEC as it is in LC, and very small stationary phase particles can be used in the CEC columns. During the past 10 years, several monolithic stationary phases have been developed. A monolith (Figure 5), also known as a continuous bed, has a spongelike structure and it can be made from several different materials, including plastic polymers [33–36] and silica [37]. The monolithic columns often result in lower back pressures compared to packed stationary phases, resulting in more rapid conditioning of the column.
242
Peter Viberg
Figure 5 Scanning electron micrographs of a monolithic packing in a 75-mm inner diameter fused silica capillary. The micrograph is taken at the end of the cut capillary. The inner wall was treated, prior to polymerization of the monolith, with g-(trimethoxysilyl)propyl methacrylate containing the inhibitor DPPH. Reproduced with permission from Ref. [97]. Copyright (1999) Elsevier.
Open-tubular stationary phases for CEC have been prepared by in-situ polymerization of monolithic plastic polymers [38] (Figure 6), and by adsorption of gold nanoparticles to the capillary wall [39]. Open-tubular columns have the benefit of a flat flow velocity profile over its whole crosssection but suffer from lower sample capacities than packed or monolithic columns do.
4.5.2 CEC with pseudostationary phases — electrokinetic chromatography In the mid-1980s, the first attempt of EKC using micelles as a pseudostationary phase in micellar EKC (MEKC) was presented [40,41]. Excellent separations of neutral analytes were obtained, as illustrated by Figure 7. The separation in MEKC is based on surfactants that form micelles acting as a pseudostationary phase in the background electrolyte. Several other pseudostationary phases have also been employed, including cyclodextrins [42,43], proteins [44], liposomes [45], microemulsions [46–48], polymeric micelles [49], and polymeric microparticles and nanoparticles [50–52]. In order to function efficiently, the pseudostationary phases must form stable solutions or suspensions and they must have properties that allow them to interact with the analytes. The interactions can be based on, for example, reversed phase mechanisms, as in Ref. [41] (Figure 7). Figure 8 illustrates that excellent chromatographic resolution can be obtained with microemulsion EKC (MEEKC) [46]. In MEEKC, an organic solvent that is
Capillary-Based Separation Techniques
243
Figure 6 Scanning electron micrographs of three molecularly imprinted monolithic polymer coatings on the wall of a 50-mm open-tubular capillary column used for CEC. The three coatings were synthesized using different solvents, or porogens, but with otherwise identical prepolymerization mixtures and conditions: A, toluene; B, dichloromethane; C, acetonitrile. The white bars indicate a 5-mm distance. Reprinted with permission from [38]. Copyright (2002) American Chemical Society.
244
Peter Viberg
4 6 5 2
14 12 1315
7
8
3
0.001 a.u 1
0
5
11
16
9 10
10
15
20
Time, min
Figure 7 MEKC separations using SDS-micelles as pseudostationary phase. (1) water, (2) acetylacetone, (3) phenol, (4) o-cresol, (5) m-cresol, (6) p-cresol, (7) o-chlorophenol, (8) m-chlorophenol, (9) p-chlorophenol, (10) 2,6-xylenol, (11) 2,3-xylenol, (12) 2,5-xylenol, (13) 3,4-xylenol, (14) 3,5-xylenol, (15) 2,4-xylenol, (16) p-ethylphenol. Please see Ref. [41] for further details. Reprinted with permission from [41]. Copyright (1983) American Chemical Society.
incorporated in micelles is added to the background electrolyte. Other binding or interaction mechanisms can also be used with EKC. The use of chiral cyclodextrins is an efficient means of obtaining enantiomeric separations through host–guest complexations, because of differences in interaction properties between the L and D form of analytes [43]. Figure 9 illustrates separations of optical isomers obtained through the use of cyclodextrins as pseudostationary phase in EKC. Molecularly imprinted polymeric microparticles suspended in background electrolyte have also been used in enantiomer separations [50], as illustrated by Figure 10. Molecular imprints are cavities created in polymers that have a predetermined selectivity towards special analytes that is based on, for example, size, charge, or hydrogen bonds [33,53]. The use of polymeric nanoparticles as pseudostationary phases is of growing interest [54]. A nanoparticle-based CEC technique combined with ESI-MS detection, termed ‘‘continuous full filling (CFF)’’ was reported in 2002 [51]. This CFF technique involves the use of stable suspensions of nanoparticles (approximately 50–400 nm in diameter) in a background electrolyte. In CFF experiments, the sample solution is injected into a capillary that is filled with a nanoparticle suspension, and the separation is performed with nanoparticle suspension as running electrolyte, resulting in a continuous flow of nanoparticles through the capillary throughout the analysis. Therefore, an orthogonal ESI source was used to separate the analytes from the nanoparticles and thereby to
Capillary-Based Separation Techniques
245
mAU A 40
5
30
4 2
20
3
1
10
67
0 0
2.5
5
mAU B
30
7.5
10
12.5
15 min
10
12.5
15 min
3
20
5 6+7
2
10
1 4
0
0
2.5
5
7.5
Figure 8 Comparison of microemulsion EKC and MEKC. Capillary: 50 mm inner diameter, 48.5 cm long (40 cm to detector). Voltage, 20 kV; detection, 215 nm. (A) Microemulsion EKC: 0.8% 5-chloropentane, 3.3% SDS, 6.6% n-butanol, and 89.3% 10 mM sodium tetraborate pH 9.2. (B) MEKC: 100 mM SDS in 10 mM sodium tetraborate pH 9.2. The peaks are: 1, caffeine; 2, terbutaline; 3, tropic acid; 4, cinnamic acid; 5, pindolol; 6, hydrocortisone; and 7, prednisolon. Reproduced with permission from Ref. [47]. Copyright (2003) Elsevier.
246
Peter Viberg
7 8
1
5 6
2 3
9 10
4
0
1
2
3
4
5
6
0
1
2
3
4
5
6
migration time (min)
Figure 9 Electropherograms obtained from EKC separations of optical isomers with cyclodextrins as pseudostationary phase. Left: norephedrine and ephedrine. Right: norepinephrine, epinephrine, and isoproterenol. 1, ()norephedrine; 2, (+)norephedrine; 3, ()ephedrine; 4, (+)ephedrine; 5, ()norepinephrine; 6, (+)norepinephrine; 7, (–)epinephrine; 8, (+)epinephrine; 9, ()isoproterenol; and 10, (+)isoproterenol. Further information can be found in Ref. [42]. Reproduced with permission from Ref. [42]. Copyright (1989) Elsevier.
Figure 10 Electrochromatogram of an enantiomer separation of propranolol, obtained by CEC using molecularly imprinted microparticles as pseudostationary phase. The microparticles were suspended in the electrolyte to 5 mg mL1 and were introduced by applying 50 mbar for 4 s, which corresponds to 11.8 cm of the capillary length. The capillary was of 100 mm i.d., 35 cm total length, and 26.5 cm effective length. Sample (25 mmol L1) was injected electrokinetically at 5 kV for 4 s. The separation was performed by applying 15 kV (429 V cm1) at 5 bar overpressure. Obtained from Ref. [50] — Reproduced by permission of The Royal Society of Chemistry.
Capillary-Based Separation Techniques
247
hinder the nanoparticles from entering and contaminating the mass spectrometer (Figure 11). Thus, MS detection is enjoyed with its high sensitivity, and other benefits, without the detection being disturbed by the nanoparticles. While the first report on CFF-CEC [51] demonstrated the proof-of-principle for the technique with ion exchange chromatographic separations, later studies focused on reversed phase separations [52,55,56]. Reversed phase separations were made possible through the use of charged nanoparticles having a hydrophobic core and a hydrophilic surface, thus enabling stable nanoparticle suspensions to be made in background electrolytes with low concentrations of organic modifiers. Separations of neutral phthalate esters were performed that resulted in very high separation efficiencies with up to over one million theoretical plates per meter column [57]. The high separation efficiencies are partly believed to be the result of high concentrations of small nanoparticles in the suspensions with resulting small distances between the nanoparticles and therefore efficient mass transfer. The interparticle distances in the study were approximately 0.7 mm [58].
Nanoparticle Analyte ions Electrospray Plume
Entrance to mass spectrometer
Flow direction in capillary
End of capillary
Flow of nebulizer gas
Flow of sheath liquid
Figure 11 Schematic illustration of the orthogonal electrospray interface during continuous full filling CEC-MS analysis. Positive ions are pulled out of the electrospray plume and accelerated in the electrical field directed towards the inlet to the mass spectrometer. Analyte ions enter the mass spectrometer where they are analysed, while the much more massive nanoparticles go to waste. Reprinted with permission from Ref. [51]. Copyright (2002) American Chemical Society.
248
Peter Viberg
4.5.3 Limitations with stationary and pseudostationary phases In all analyses involving stationary phases, there is a risk of contamination of the stationary phase. The contamination may occur either from the analytes themselves, or from molecules present in the sample matrix. Contamination is particularly a risk during analysis of samples present in complex matrices. Such contamination of the stationary phase can result in changed retention behaviour of the analytes and an increased noise during the detection. Furthermore, there is also the risk that the column is clogged or even destroyed as a result of adsorbing contaminants. Quantification of particularly low abundant analytes may be impossible or erroneous if analytes from previous runs are remaining and eluting from the column. If, for example, biological samples, such as blood plasma or urine are to be analysed, a sample pre-treatment step may be necessary to avoid severe memory effects or even destroying the column. Contamination problems can be overcome through the use of a pseudostationary phase instead of an immobilised stationary phase. The pseudostationary phase is constantly replaced throughout the analysis, thus regenerating the column during each analysis, allowing each sample to be injected on a new and fresh pseudostationary phase. With pseudostationary phases, possible memory effects will have to be due to either contamination of the capillary walls, or be related to carry-over effects (e.g., via the electrodes and the electrolyte vials). Fortunately, the lack of an immobilized stationary phase combined with the strength of an open-tubular fused silica capillary allows for thorough and rapid rinsing between runs that can remove contaminants from the capillary wall. In addition to this, the use of pseudostationary phases avoids the need for retaining frits that otherwise may add to band broadening [59,60]. Although solving problems with memory effects, the pseudostationary phases may have negative effects on the detection. With absorbance or fluorescent detection, light scattering, fluorescence and absorbance by the pseudostationary phase will add to the background noise, often making the analytes completely undetectable. Mass spectrometry is often a desired detection technique, as it can provide both quantitative and structural information on the analytes. However, also with MS detection, the pseudostationary phase can add noise, and it may also have a suppressing effect on the ionization of the analytes [61]. The mass spectrometer can also be contaminated by the pseudostationary phase, and may not even be compatible with some phases. In one study using MEKC with sodium dodecyl sulphate (SDS), the signal from the ESI-MS detection decreased by 65% during one day of analysis and the ion source had to be cleaned on a daily basis [62]. One way to circumvent detection problems associated with the use of pseudostationary phases, is to use the partial filling technique that was developed in the early 1990s [44]. In partial filling, the pseudostationary phase is injected into the capillary as a small plug (Figure 12). The benefit with the technique is that the analytes will be separated as they are passing the plug of pseudostationary phase, but will be detected before the pseudostationary phase reaches the detector. Thus, detection interferences from the pseudostationary phase will be avoided or minimized. However, the partial
Capillary-Based Separation Techniques
249
A
B
C
D
Figure 12 Schematic diagram illustrating the use of a pseudostationary phase in the partial filling technique. The background electrolyte is illustrated by grey fields. The pseudostationary phase is illustrated by grey dots and the sample is illustrated by black bars. (A) The capillary is filled with background electrolyte. (B) A plug of pseudostationary phase is injected into the capillary. (C) The sample is injected into the capillary. (D) The sample moves faster than the pseudostationary phase and is separated as it passes the plug of pseudostationary phase. When the experimental conditions are optimized, the sample will be eluting from the capillary before the pseudostationary phase.
filling technique has some disadvantages. Time-consuming optimizations that limit the separation may be necessary in order to allow the sample to completely pass the pseudostationary phase prior to reaching the detector, i.e., the sample needs to be moving at a rate considerably faster than the pseudostationary phase, or the plug of pseudostationary phase must be kept very small. The latter may severely limit the retention factors of the analytes and therefore limit the resolution of the separation. Furthermore, the EOF is likely to be different in the plug compared to the surrounding background electrolyte, which will result in pressure differences and induced parabolic flow rate profiles that can result in band broadening and reduced separation efficiency. Partial filling has been used with several different types of pseudostationary phases including proteins [44], micelles [63], and polymeric microparticles and nanoparticles [50,51]. Some of these issues regarding detection interferences with pseudostationary phases and limitations to the partial filling technique are dealt with in the nanoparticle-based CFF-CEC technique [51]. In the CFF-CEC technique, an orthogonal ESI-MS interface (Figure 11) is used to enable efficient detection of the analytes while at the same time excluding the nanoparticles of the pseudostationary phase from entering the mass spectrometer, as was described earlier under CEC with pseudostationary phases — EKC.
250
Peter Viberg
5. DETECTION TECHNIQUES IN CAPILLARY-BASED SEPARATIONS Many different types of detectors exist but the focus in this chapter will be on absorbance, fluorescence, and electrospray MS techniques. Special considerations must often be taken when choosing a detector for a capillary-based separation technique because of the often very low volumetric flow velocities, small column/capillary volumes, and small sample volumes associated with these techniques. Minimizing the dead volumes is necessary to avoid severe band broadening, as was previously discussed. Furthermore, a concentration sensitive detector is often beneficial because of the low volumetric flow rate, with its resulting low analyte mass flow. Because of the light transparent properties of the fused silica capillary (when the polyimide coating is removed by, for example, burning or scratching), optical detection can be performed directly on the column, which does not add any extra dead volumes. However, on-column detection suffers from short optical path-lengths and therefore by poor detection sensitivity. Different solutions to improve the pathlength and the detection sensitivity have been developed [64] and two of them are presented in Figure 13. A bubble cell [65–67] takes advantage of an increased internal diameter over a small portion of the capillary. The use of a bubble cell has proved to increase the detection signal-to-noise, but it does on the other hand induce band broadening. A z-cell [68,69] can increase the optical path-length even further than a bubble cell, but losses in the separation resolution have been observed [68]. Path length
P0 A P
P0
Path length
B
P
Figure 13 Schematic illustrations of (A) a bubble cell and (B) a z-cell. P0 indicates the incoming light and P the outgoing light from the capillary. The path lengths for the light are longer than that for a standard capillary.
Capillary-Based Separation Techniques
251
Electrospray mass spectrometry [70,71] is an attractive detection option for on-line coupling to capillary separation techniques, as it provides high sensitivity and is compatible with the low volumetric flow rates associated with these techniques (normal ESI can typically be used with volumetric flow rates of a few mL min1). However, CLC, CEC, and CE separations using small diameter capillaries are frequently performed in the nL min1 region, and such low flow velocities result in unstable and non-quantitative ESI-MS detection unless a sheath-flow is used. The sheath-flow is pumped coaxially to the outlet of the separation capillary mixing with its effluent at the interface to the mass spectrometer and therefore sheath-flows have the disadvantage of diluting the sample and thereby decreasing the MS signal intensity. The low flow rate version of ESI termed nanoelectrospray (nESI), or microelectrospray (mESI) [72,73] has working ranges suitable for many capillary-based separation techniques, without the need for a sheath-flow. The use of nESI often greatly increases the signal intensities, compared to standard ESI. In nESI the effluent from the separation capillary is electrosprayed from a small diameter capillary (a few micrometer) with thin walls, which results in a very efficient ionization of the analytes. ESI and nESI are often performed in positive-mode, in which the analytes are positively charged by protons. Positive ionization is therefore best performed at low pH, which may be problematic if a high pH mobile phase or electrolyte is required for the separation. In those cases, it may be best if a sheath-flow is used that has a low enough pH to break the buffered effluent from the separation capillary. If open-tubular separation capillaries are used in combination with sheath-flow assisted ESI, the eluent times for the analytes are often decreased as a result of an increased volumetric flow rate caused by the suction-force from the sheath flow. This does not just change the elution times, but it also induces a parabolic flow-profile with a resulting band broadening of the peaks. This effect can be minimized by using a separation capillary with a small internal diameter. When choosing buffer salts for the mobile phase or background electrolyte, it is important to choose salts that are easily evaporated, not to cause contamination of the mass spectrometer or disturbance of the ESI process. Buffer salts of shortchained organic acids and ammonia, for example, ammonium formate and ammonium acetate are commonly used, as well as ammonium carbonate. Together these salts buffer a pH range from approximately 3 to 10, which should be sufficient for most separation situations.
6. AUTOMATION AND ON-LINE/IN-CAPILLARY COUPLED SOLID-PHASE EXTRACTION IN CAPILLARY ELECTROPHORESIS Commercial CE and CEC instruments as well as CLC systems are highly automated and can be operated over a long time without much labour needed. Several sample and electrolyte or mobile phase vials can be loaded and automatically switched between, and pre-separation conditionings and washing steps can be programmed. However, analysis of samples present in for example
252
Peter Viberg
complex matrices may also require a sample pre-treatment step to clean and concentrate the analytes, in addition to the sample separation step. Sample pretreatment techniques are often laborious and can be a bottle-neck in the analysis chain unless they are automated and coupled on-line to the separation system. When analytical methods are designed to be used with automated instruments for the analysis of perhaps hundreds of samples per day, unmonitored by man, it is of great importance that the methods perform reliably with high repeatability and reproducibility. Several different solutions have been proposed and developed for on-line couplings and in-capillary couplings of sample pretreatment to capillary electroseparation systems. SPE is a commonly used sample pre-treatment technique that is employed to remove contaminants from the sample, which may otherwise clog the separation capillary and increase the background noise during detection. In addition to this, SPE is performed to pre-concentrate the analytes to improve the limit-ofdetection. SPE relies on strong interactions between the analytes and a solidphase, and it is a special case of chromatography with very high retention factors. The retention can be based on reversed phase mechanisms, ionic interactions, or other properties of the solid-phase and the analytes. SPE is ideal for in-capillary coupling to CE, as the lack of a stationary phase in CE make cleaning and washing of the extracted sample straightforward with a minimized risk of contaminating the separation capillary. SPE-CE is an important complement to the in-capillary concentration techniques described above under CE, as SPE is a very efficient means to handle complex or contaminated sample matrices. For efficient coupling with CE, miniaturization of the SPE-equipment is important [74,75] and such equipments are often known as solid-phase micro extraction (SPME) or micro-SPE (mSPE). mSPE can be performed on a short bed of packed particles inside the CE capillary [76–80]. Also membranes [81–83] have been used as solid-phase matrices in on-line approaches of SPE-CE. Several other matrices have also been employed for SPE coupled on-line or in-capillary to CE [74,75], such as monolithic phases [84,85].
7. APPLICATIONS IN DETERMINATION OF FOOD CONTAMINANTS USING CAPILLARY ELECTROPHORESIS Determination of contaminants in food is a great challenge as the contaminants often are present in very low concentrations and in complex mixtures and sample matrices. Therefore, the high separation efficiencies that can be obtained with capillary-based separation techniques (as has been discussed in this chapter) is of great value for determination of food contaminants. When complex sample matrices are analysed, and low abundant compounds determined, sample pretreatment and sample clean-up steps may be vital to obtain accurate analysis results. The challenge is often to concentrate the analytes of interest while at the same time getting rid of the sample matrix compounds present at much higher concentrations.
Capillary-Based Separation Techniques
253
CE is a separation technique that has gained great interest and that has been widely used within the field of determination of food contaminants and food analysis [86–88]. Several different application areas have been found, including determination of amino acids, vitamins, organic acids, proteins, different food additives, toxins, antioxidants, phenols, pigments, mutagenic compounds, and pesticides, which is evident from the many reviews written within this field (e.g., Refs. [86–89]). To tackle the complex matrices of foods, different sample clean-up techniques have been employed prior to analysis by CE. For example, different microextraction techniques, including examples of interfacing with CE, have recently been reviewed in Refs. [90–92]. The capillary separation techniques have several benefits, as has been discussed in this chapter, including high separation efficiencies, low LODs, low sample consumptions, possibilities of interfacing with sample pre-treatment techniques, and possibilities for automation of the analyses. These techniques, therefore, are very useful for demanding analyses and well suited for determination of food contaminants. They will likely develop for applications in food analyses and their use will increase in the future. Miniaturized analytical techniques based on the chip format [93–95] have not been discussed in this chapter, but chip analyses have many miniaturization benefits, which make them useful for demanding separations, particularly when high speed and high through-put analyses are needed, and they have gained a great interest in the field of food analysis [96], an interest that is likely to increase.
REFERENCES 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
J.H. Knox, Chromatographia, 26 (1988) 329. F.J. Yang, J. Chromatogr., 236 (1982) 265. T. Takeuchi and D. Ishii, J. Chromatogr., 238 (1982) 409. K. Karlsson and M. Novotny, Anal. Chem., 60 (1988) 1662. R.T. Kennedy and J.W. Jorgenson, Anal. Chem., 61 (1989) 1128. S. Hsieh and J.W. Jorgenson, Anal. Chem., 68 (1996) 1212. J.H. Knox, J. Chromatogr. A, 680 (1994) 3. ˚ . Jo¨nsson and R.M. Smith, Pure Appl. Chem., 76 (2004) 443. M.L. Riekkola, J.A G. Choudhary and C. Horvath, J. Chromatogr. A, 781 (1997) 161. A.S. Rathore, K.J. Reynolds and L.A. Colon, Electrophoresis, 23 (2002) 2918. H. Katayama, Y. Ishihama and N. Asakawa, Anal. Chem., 70 (1998) 2254. P. Sun, A. Landman, G.E. Barker and R.A. Hartwick, J. Chromatogr. A, 685 (1994) 303. F. Steiner and M. Hassel, Electrophoresis, 24 (2003) 399. X.W. Yao, D. Wu and F.E. Regnier, J. Chromatogr., 636 (1993) 21. M. Chiari, M. Cretich, F. Damin, L. Ceriotti and R. Consonni, Electrophoresis, 21 (2000) 909. P. Sun, A. Landman and R.A. Hartwick, J. Microcolumn. Sep., 6 (1994) 403. P. Viberg, S. Nilsson and K. Skog, Anal. Chem., 76 (2004) 4241. A. Tiselius, Biochem. J., 31 (1937) 313. H. Haglund and A. Tiselius, Acta Chem. Scan., 4 (1950) 957. H.G. Kunkel and A. Tiselius, J. Gen. Physiol., 35 (1951) 89. S. Hjerte´n, Chromatogr. Rev., 9 (1967) 122.
254
Peter Viberg
22 J.W. Jorgenson, S.K. DeArman and E.J. Guthrie, In: Vth International Symposium on Column Liquid Chromatography, University of Avignon, Avignon, 1981, p. 38. 23 J.W. Jorgenson and K.D. Lukacs, J. Chromatogr., 218 (1981) 209. 24 J.W. Jorgenson and K.D. Lukacs, Science, 222 (1983) 266. 25 F.E.P. Mikkers, F.M. Everaerts and T. Verheggen, J. Chromatogr., 169 (1979) 11. 26 D.S. Burgi and R.L. Chien, Anal. Chem., 63 (1991) 2042. 27 R.L. Chien and D.S. Burgi, J. Chromatogr., 559 (1991) 141. 28 S. Hjerten and M.D. Zhu, J. Chromatogr., 346 (1985) 265. 29 F.M. Everaerts, M. Geurts, F.E.P. Mikkers and T.P.E.M. Verheggen, J. Chromatogr., 119 (1976) 129. 30 F. Foret, E. Szoki and B.L. Karger, J. Chromatogr., 608 (1992) 3. 31 J.P. Quirino and S. Terabe, Anal. Chem., 70 (1998) 149. 32 J.H. Knox and I.H. Grant, Chromatographia, 24 (1987) 135. 33 L. Schweitz, L.I. Andersson and S. Nilsson, Anal. Chem., 69 (1997) 1179. 34 E.C. Peters, M. Petro, F. Svec and J.M. Fre´chet, Anal. Chem., 70 (1998) 2288. 35 A. Palm and M.V. Novotny, Anal. Chem., 69 (1997) 4499. 36 J.L. Liao, N. Chen, C. Ericson and S. Hjerte´n, Anal. Chem., 68 (1996) 3468. 37 S.M. Fields, Anal. Chem., 68 (1996) 2709. 38 L. Schweitz, Anal. Chem., 74 (2002) 1192. 39 B. Nieman, E. Grushka and O. Lev, Anal. Chem., 73 (2001) 5220. 40 S. Terabe, K. Otsuka and T. Ando, Anal. Chem., 57 (1985) 834. 41 S. Terabe, K. Otsuka, K. Ichikawa, A. Tsuchiya and T. Ando, Anal. Chem., 56 (1984) 111. 42 S. Fanali, J. Chromatogr., 474 (1989) 441. 43 S. Fanali, J. Chromatogr. A, 875 (2000) 89. 44 L. Valtcheva, J. Mohammad, G. Pettersson and S. Hjerte´n, J. Chromatogr., 638 (1993) 263. 45 Y.X. Zhang, R. Zhang, S. Hjerte´n and P. Lundahl, Electrophoresis, 16 (1995) 1519. 46 H. Watarai, Chem. Lett., 35 (1991) 391. 47 S. Pedersen-Bjergaard, C. Gabel-Jensen and S. Honore´ Hansen, J. Chromatogr. A, 897 (2000) 375. 48 S.H. Hansen and Z.A. Sheribah, J. Pharm. Biomed. Anal., 39 (2005) 322. 49 S.A. Rizvi and S.A. Shamsi, Electrophoresis, 24 (2003) 2514. 50 L. Schweitz, P. Spe´gel and S. Nilsson, Analyst, 125 (2000) 1899. 51 P. Viberg, M. Jornten-Karlsson, P. Petersson, P. Spegel and S. Nilsson, Anal. Chem., 74 (2002) 4595. 52 P. Viberg, P. Spe´gel, J. Nilsson, C.T. Reimann, C. Nilsson, M. Jornte´n-Karlsson, P. Petersson and S. Nilsson, In: Micro Total Analysis Systems, Malmoe, Sweden, 2004, p. 168. 53 L. Schweitz, L.I. Andersson and S. Nilsson, J. Chromatogr. A, 792 (1997) 401. 54 E. Guihen and J. Glennon, Anal. Lett., 36 (2003) 3309. 55 C. Nilsson, P. Viberg, P. Spe´gel, M. Jo¨rnte´n-Karlsson, P. Petersson and S. Nilsson, Anal. Chem., 78 (2006) 6088. 56 P. Viberg, P. Spe´gel, J. Nilsson, P. Petersson, M. Jo¨rnte´n-Karlsson and S. Nilsson, Chromatographia, 65 (2007) 291. 57 P. Viberg, P. Spegel, J. Carlstedt, M. Jornten-Karlsson and P. Petersson, J. Chromatogr. A, 1154 (2007) 386. 58 P. Viberg, PhD Thesis: Capillary Electroseparations with Mass Spectrometric Detection-NanoparticleBased Continuous Full Filling and Applications for Complex Sample Matrices, Lund University, Lund, Sweden, 2006. 59 E. Rapp and E. Bayer, J. Chromatogr. A, 887 (2000) 367. 60 B. Behnke, J. Johansson, E. Bayer and S. Nilsson, Electrophoresis, 21 (2000) 3102. 61 W. Lu, G.K. Poon, P.L. Carmichael and R.B. Cole, Anal. Chem., 68 (1996) 668. 62 G.W. Somsen, R. Mol and G.J. de Jong, J. Chromatogr. A, 1000 (2003) 953. 63 W.M. Nelson and C.S. Lee, Anal. Chem., 68 (1996) 3265. 64 G. Hempel, Electrophoresis, 21 (2000) 691. 65 M.J. Cugat, F. Borrull and M. Calull, Analyst, 126 (2001) 1312. 66 Y. Mrestani, S. Claussen and R.H.H. Neubert, Chromatographia, 59 (2004) 759. 67 W.S. Law, J.H. Zhao and S.F.Y. Li, Electrophoresis, 26 (2005) 3486. 68 J.P. Chervet, R.E.J. Van Soest and M. Ursem, J. Chromatogr. A, 543 (1992) 439.
Capillary-Based Separation Techniques
255
69 A. Mainka and K. Bachmann, J. Chromatogr. A, 767 (1997) 241. 70 M. Dole, L.L. Mach, R.L. Hines, R.C. Mobley, L.D. Ferguson and M.B. Alice, J. Chem. Phys., 49 (1968) 2240. 71 J.B. Fenn, M. Mann, C.K. Meng, S.F. Wong and C.M. Whitehouse, Science, 246 (1989) 64. 72 M. Wilm and M. Mann, Anal. Chem., 68 (1996) 1. 73 M.S. Wilm and M. Mann, Int. J. Mass Spectrom. Ion Process, 136 (1994) 167. 74 N.A. Guzman, S.S. Park, D. Schaufelberger, L. Hernandez, X. Paez, P. Rada, A.J. Tomlinson and S. Naylor, J. Chromatogr. B, 697 (1997) 37. 75 N.H. Heegaard, S. Nilsson and N.A. Guzman, J. Chromatogr. B, 715 (1998) 29. 76 A.J. Tomlinson, N.A. Guzman and S. Naylor, J. Capillary Electrophor., 2 (1995) 247. 77 M.A. Strausbauch, J.P. Landers and P.J. Wettstein, Anal. Chem., 68 (1996) 306. 78 M. Petersson, K.-G. Wahlund and S. Nilsson, J. Chromatogr. A, 841 (1999) 249. 79 A. Schellen, B. Ooms, M. van Gils, O. Halmingh, E. van der Vlis, D. van de Lagemaat and E. Verheij, Rapid Commun. Mass Spectrom., 14 (2000) 230. 80 P. Viberg, K.G. Wahlund and K. Skog, J. Chromatogr. A, 1133 (2006) 347. 81 A.J. Tomlinson, L.M. Benson, R.P. Oda, W.D. Braddock, B.L. Riggs, J.A. Katzmann and S. Naylor, J. Capillary Electrophor., 2 (1995) 97. 82 S. Naylor, L.M. Benson and A.J. Tomlinson, J. Chromatogr. A, 735 (1996) 415. 83 J.C. Waterval, G. Hommels, P. Bestebreurtje, C. Versluis, A.J. Heck, A. Bult, H. Lingeman and W.J. Underberg, Electrophoresis, 22 (2001) 2709. 84 D. Schaller, E.F. Hilder and P.R. Haddad, Anal. Chim. Acta, 556 (2006) 104. 85 J.P. Hutchinson, M. Macka, N. Avdalovic and P.R. Haddad, J. Chromatogr. A, 1106 (2006) 43. 86 A. Juan-Garcia, G. Font and Y. Pico, J. Sep. Sci., (2005) 793. 87 A. Cifuentes, Electrophoresis, 27 (2006) 283. 88 R.A. Frazier and A. Papadopoulou, Electrophoresis, 24 (2003) 4095. 89 J. Hernandez-Borges, S. Frias-Garcia, A. Cifuentes and M.A. Rodriguez-Delgado, J. Sep. Sci., 27 (2004) 947. 90 D.A. Lambropoulou and T.A. Albanis, J. Biochem. Biophys. Methods, 70 (2007) 195. 91 Y. Pico, M. Fernandez, M.J. Ruiz and G. Font, J. Biochem. Biophys. Methods, 70 (2007) 117. 92 J. Hernandez-Borges, A. Cifuentes, F.J. Garcia-Montelongo and M.A. Rodriguez-Delgado, Electrophoresis, 26 (2005) 980. 93 J.D. Harrison, A. Manz, Z. Fan, H. Lu¨di and M.H. Widmer, Anal. Chem., 64 (1992) 1926. 94 A. Manz, N. Graber and H. Widmer, Sens. Actuators B, (1990) 244. 95 A. Manz, J. Harrison, E.M. Verpoorte, J.C. Fettinger, A. Paulus, H. Lu¨di and M.H. Widmer, J. Chromatogr., 593 (1992) 253. 96 A. Escarpa, M.C. Gonzalez, A.G. Crevillen and A.J. Blasco, Electrophoresis, 28 (2007) 1002. 97 I. Gusev, X. Huang and C. Horvath, J. Chromatogr. A, 855 (1999) 273.
CHAPT ER
9 Pesticide Residues Anna Sannino
Contents
1. 2. 3. 4. 5.
Introduction Physical and Chemical Properties Health Effects Analytical Methods Instrumental Determination 5.1 Gas chromatography 5.2 Liquid chromatography 6. LC-MS-MS Applications 6.1 Chlormequat 6.2 Pesticides of new generation 7. Conclusions and Future Trends References
257 258 259 272 278 279 289 295 295 296 301 302
1. INTRODUCTION The term ‘‘pesticide’’ covers a wide range of substances that belong to many completely different chemical groups. The Food and Agriculture Organization (FAO) of the United Nations has defined a pesticide as a substance or a mixture of substances intended to prevent, destroy or control any pest [1]. Also included in the FAO definition are chemicals intended for use as plant growth regulators, defoliants or desiccants, even though they are neither normally employed as pest control agents nor usually effective as such. Pesticides include a great variety of chemicals used widely in agriculture since significant economic damage can occur when insects, nematodes, fungi and other macro- and microorganisms affect food and commodity crops [2]. Large scale use of pesticides began after World War II, when the agriculture production of food
Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00009-3
r 2008 Elsevier B.V. All rights reserved.
257
258
Anna Sannino
accelerated. Currently, more than 800 active substances are formulated in pesticide products [3]. This chapter aims to describe the issues surrounding pesticide residues in food and in particular the issues associated with the analysis of pesticide residues. The state of art of the individual steps (extraction, clean-up, identification, quantitation) of methods for pesticide analysis in food is critically reviewed with emphasis laid on emerging techniques which have gained popularity. The first part of this chapter outlines some of the different types of pesticides, which can be classified by chemical structure, target pest or mode of activity. A brief introduction summarizes the properties of pesticides and the regulations that highlight its importance to meet the official requirements on analytical performance.
2. PHYSICAL AND CHEMICAL PROPERTIES Pesticides may be classified in according to the target on which they act. Examples are herbicides, which are used for weed control, insecticides that destroy insects, fungicides that control fungi, etc. They can also be grouped according to their known, or assumed, biochemical mode of action (e.g., insect growth regulators, acetylcholinesterase inhibitors). According to their chemical nature, the pesticides can be divided into two chemical groups: inorganic and organic compounds. Most pesticides used today are organic compounds. A small number are either extracted or derived directly from plants. Examples include products such as pyrethrum, rotenone and nicotine. Synthetic pesticides cover a very wide range of chemical structural types. Their use to control pests and diseases has become widespread in the 20th century. Pesticides commercially available today are characterized by such a variety of chemical structure and functional groups to make their chemical classification quite complex. The major chemical groups of the most classical categories of pesticides are given below: (i)
(ii)
(iii)
Organochlorines (OCs) are a commonly used term referring to a group of hydrocarbons with one or more chlorine atoms which include the cyclodienes, DDT and related compounds, lindane, and hexachlorocyclohexanes and toxaphene. However, their chemical stability and fat solubility were shown to give environmental hazards leading to an ability to accumulate in humans and animals. Therefore, DDT and other chemically stable OCs have been taken out of agricultural use in most countries. Organophosphorates (OPs) integrated by esters of phosphoric, phosphonic, phorothionic or related acids. They are commonly used as insecticides in a variety of crops. Some of the more common examples in this group are dichlorvos, malathion, diazinon, and phosmet. Carbamates (e.g., carbaryl and propoxur) formed by salts and esters of carbamic acid. They form an important group of insecticides. Chemicals
Pesticide Residues
(iv) (v) (vi)
259
which are structurally related to these carbamates have also been developed as fungicides, herbicides and molluscicides. Pyrethroids (e.g., D-phenothrin) which mimic the structure and action of naturally occurring pyrethrins are very widely used as insecticides. 1,3,5-triazines (e.g., atrazine and simazine) which are an important chemical class of herbicides. Substituted ureas, which comprise a large number of groups as phenylureas and sulfonylureas that are herbicides and benzoylureas that have insecticide activity.
These compounds represent the most classical chemical categories of pesticides. For the past several decades, approximately 80% of the insecticide market has been taken up by organophosphorates, carbamates and pyrethroids. However, other types of compounds are taking an increasing portion of the market. The use of pesticides has changed through the years, going from more persistent (e.g., organochlorine) to more polar, readily degradable pesticides, such as N-methyl carbamates (NMCs). Moreover, synthetic nicotinoids and neonicotinoids (related to the natural compound nicotine as the pyrethroids are related to the pyrethrum) are gaining increasing importance. Table 1 shows the chemical structure of representative compounds of the principal pesticide groups used in agriculture. Recently, a new group of pesticides has been developed for plant protection at low doses, with a reversible mode of action, less persistence, systemic action and adequate potency against crop pests. Agrochemicals belonging to carboxamide, quinazolin, phenoxypyrazol, strobilurin, pyrimidine, triazol, neonicotinoid, carbamate, morpholine classes are representative of the newly introduced molecules.
3. HEALTH EFFECTS On the negative side of the application of pesticides in agricultural praxis, many pesticides are harmful to the environment and are known or suspected to be toxic to human. Their adverse effects on human health may include acute neurologic toxicity, chronic neuro-development impairment, possibly dysfunction of the immune, reproductive and endocrine systems or cancer and many others. Toxicity studies aim to characterize the nature and extent of toxic effects caused by the pesticide and to find no adverse effects in the test animals (no observed adverse effect level, NOEL). The acceptable level of long-term dietary exposure, referred to as the acceptable daily intake (ADI) for humans may be calculated by using a safety factor (usually 100) from the NOEL (ADI ¼ NOEL/100). The most common route of exposure to pesticides is by ingestion of treated food commodities containing residues. Most pesticide residues occur in food as a result of the direct application of a pesticide to a crop or farm animal or the postharvest treatments of food commodities. Residues also occur in meat, milk and eggs from the consumption by farm animals of feed from treated crops. Residues can also occur in food from environmental contamination and spray drift. In
Organophosphorus
DDT
Insecticides Organochlorines
Malathion
Heptenophos
Endofulfan
Dieldrin
Typical pesticide
Class
Table 1 Chemical structures of major classes of pesticides
O
CH2
CH3
O
O
Cl
Cl
O
C
CH
O
S
S
O
Cl
CH2
C
Cl
O S
Cl
Cl
C
H C
Cl
CH2 O
O
CH3
P
Cl
Cl
Cl
Cl
Cl
CH3
O
Cl
Cl
O
Cl
CH3
Cl
Cl
Chemical structure
P
O
O
O
Cl
CH3
CH3
260 Anna Sannino
Benzoylphenylurea
Carbamate
Teflubenzuron
Benfuracarb
Aldicarb
Carbaryl
CH3
H
H3C
H
H3C
N C
C
O
O
F
F
CH2
N
O
O
N
O
O
C
C
H
N
O
S
C
C
CH3
CH2
CH
N
H
N
O
CH3
CH
CH2
CH3
CH3
CH3
F
S
H3C N
O
O
Cl
Cl
C
F
O
CH3
CH3 Pesticide Residues
261
Neonicotinoid
Pyrethroids
Class
Table 1 (Continued )
Imidachloprid
Cypermethrin
Permethrin
Diflubenzuron
Typical pesticide
Cl
Cl
Cl
Cl
N
H3C
HC
C
H3C
Cl C HC
F
F
O
C
CH3
O
O
HC
O
H
N
O
N
C
C
CH3
H
N
O
H2C
C
Chemical structure
N
N
N
NO2
C
CH2
H
O
O
Cl
262 Anna Sannino
Azadirachtin
Botanical
Pyrethrin
Abamectin
Macrocyclic lactone
H3C
O
H3C
O
C
H3C
C CH3
CH3
CH3
O
H
C
C
O
O
O
O
O
O
O CH3
H
H2C
H
O
H
C O H
O
C
C
CH3 CH2
OH
H
CH3
O
CH3
CH
O OH H3C O
H
H
CH3
CH3
H3C
H
O
(Z )-(S)-alcohol (1R)-trans-acid H
H3C
CH
H
O O
C C CH3
C
pyrethrin [
O
H3C
O
H
avermectin B1a (major component)
HO
CH3
O
H HO
OH
O
H
H
H
O
O
OH
H
O
CH3
H
O
Cl
H
CH2
CH3
C H CH3
H
Pesticide Residues
263
Fenpyroximate
Pyrazole
Captan
Ziram
Fungicides Phthalimide
Dithiocarbamate
Tebufenpyrad
Typical pesticide
Class
Table 1 (Continued )
H3C
H3C
H3C
H3C
N
C
CH3
N
C S
S
O
N
O
CH3
C
Zn
Cl
S
CH3
N
H O
S
S C
Cl
Cl
CH2 N H
O
N
C
Chemical structure
N
Cl
CH3
CH3
C
O
CH2
N
CH3 N CH2
C
CH3
O
O
CH3
C
CH3 CH3
264 Anna Sannino
Imazalil
Cymoxanil
Iprodione
Aliphatic nitrogen
Dicarboximide
Captafol
Thiabendazole
Carbendazim
Imidazole
Benzimidazoles
Cl
CH3
Cl
N
H
Cl
O
N
N
O
C
N
O
N
O
H
CH3
N
N
H
C
N
Cl
H
C
N
C H O
H
C
N
N
O
N
CH2
N
O
N
O
CH2
H
Cl
O
C
Cl
Cl
C
S
O
CH
Cl
S
N
C O
N
CH3
CH
CH2
CH
CH3
CH3
CH2
Pesticide Residues
265
Pyrimidine
Triazole
Class
Table 1 (Continued )
Mepanypirim
Myclobutanil
Tebuconazole
Famoxadone
Typical pesticide
H3C
Cl
Cl
C
C
O
N
N
CH3
N
N
CH2
N
N CH2
C
CH2
O
CH3
C
CH2
Chemical structure
N
O
C
N
N
H
N
CH3
CH3
CH2
CH2 CH3
C
OH CH3
H
N
CH2
N
O
266 Anna Sannino
Fludioxonil
Azoxistrobin
Dimethomorph
2-Phenylphenol
Pyrrole
Strobilurin
Morpholine
Substituted phenol
Nuarimol
Cl
CH3
F
N
O
O
F
OH
C
H
O
N
C
Cl
C
C
O
C CH
O
O
O
CH3
C
HO
N
O
N
N
H
N
C
O
O
CH3 CH3
O
F
N
C
N
Pesticide Residues
267
Atrazine
Herbicides Triazine
Diphenamide
Pendimethalin
Amide
Dinitroanaline
Simazine
Typical pesticide
Class
Table 1 (Continued )
CH3
Cl
Cl
H
N
H
N
CH3
N
N
N
N
C
NO2
N H
CH
CH2 CH2
CH3
CH3
CH3
CH3
CH3
N
O
CH3
CH2
CH3
CH2
NO2
CH
CH2
N
H N
CH3
CH
N
N
H
Chemical structure
CH3
268 Anna Sannino
Linuron
Chlorotoluron
Cl
MCPA
Phenylurea
Cl
2,4-D
CH3
CH3
CH3
C N
N H
O
O
O
N
C
O
CH3 H
N
O
CH3
Cl
H2C
CH3
Phenoxyalcanoic acid
CH2
Cl
Alachlor
Chloroacetanilide
C
CH2
CH2
N
O
Cl
Cl
C
C
Cl
CH3
OH
O
OH
O
CH2
CH2
O CH3
CH3
Pesticide Residues
269
Triazole
Rimsulfuron
Solfonylurea
Amitrol
Amidosulfuron
Typical pesticide
Class
Table 1 (Continued )
O
CH3
N
N
O
CH3
N
O
CH3
H
O
CH3
NH2
N
N
N
N
Chemical structure
H
N
H
N
C
O
C
O
H
N
H
N
O
S
O
O
S
S CH3
N
O
O
CH3
N
CH2 O S O O
CH3
270 Anna Sannino
Carbamates
Ammonium quaternarium
Chlorprofam
Diquat
Mepiquat
Chlormequat
Cl
H3C
Cl
N+
+ N
CH2
H
N
N+
C
CH3 Cl−
Cl−
CH3
N+
CH2
CH3
O
O
CH3
CH3
CH
CH3
Pesticide Residues
271
272
Anna Sannino
addition, transport of residues and sediment may also contaminate drinking water sources [2]. Dietary exposure to a pesticide depends on both the actual residue in or on foods and the food consumption pattern. In determining the health risks associated with chronic intake, it is necessary to determine the quantity of the pesticides likely to be consumed over a prolonged period of time and compare this estimate with the ADI. Monitoring of pesticide residues is therefore crucial for proper assessment of human exposure to pesticides through foods. Maximum residue levels (MRLs or tolerances) of pesticides in foodstuffs and drinking waters have been set by Government agencies and the European Union Commission to guarantee consumer safety and to regulate international trade. In general, the MRLs in foods are in the range 0.01–10 mg/kg, depending on the combination commodity and pesticide, the lowest is characteristic of banned compounds because it is considered that this would be the minimum limit of detection (LOD) achievable [4,5]. Specific rules on the presence of pesticide residues in infant and follow-on formulae, as well as in processed cereal-based baby food and baby foods are set out in Commission Directives [6,7]. These Directives require that baby food contains no detectable levels of pesticide residues, meaning not more than 0.010 mg/kg of pesticide residues. In addition, Directives 2003/13/EC and 2003/14/EC [8,9] prohibit the use of highly toxic pesticides (ADIp0.5 mg/kg body weight per day) in the production of any baby food and establish MRL values between 0.003 and 0.008 mg/kg for these very toxic pesticides. All aspects commented upon earlier have an important impact on method development because all of them are interdependent on the required performance of the analytical methods. Low MRLs have promoted the development of more powerful and sensitive analytical methods to meet the requirements in food.
4. ANALYTICAL METHODS The determination of pesticide residues in foodstuffs is a requirement to support enforcement of legislation, to ensure trading compliance and in the conduct of surveillance programs to monitor residues in regional and national dietary components. As noted earlier, approximately 800 active compounds are currently used in pesticide formulations. In addition, several metabolites, degradation products and ‘‘old’’ persistent pesticides have to be considered by pesticide analysts. Approximately 500 pesticides are regulated by the EU Commission [4,5]. Residue analysis in food is probably one of the most complex fields of analytical chemistry because of the need for the isolation and determination of substances at the picogram and femtogram level. Nevertheless, the analysis of pesticides in food samples is made even more complex by the fact that the concentration of matrix components is often greater than the concentration of the target pesticide. Major progress has been made in the development of analytical methods for pesticide residue since the early days of pesticide residue regulation
Pesticide Residues
273
in the 1950s and 1960s. Colorimetric methods were the best methods available at that time. These methods had high limits of quantitation (LOQ), being approximately 1 mg/kg. Modern methods mostly using gas chromatography (GC) or high-performance liquid chromatography (HPLC) with very sensitive detectors routinely measure residue concentrations at 1–10 mg/kg in food commodities. Before 1960 individual procedures were used for nearly each pesticide. As the number of pesticides increased, the application of a large number of individual methods to determine them became economically impracticable. In addition, the spray history of a given sample was generally unknown; thus, the residue chemist did not know which methods to apply. The physical and chemical properties of pesticides may differ considerably. There are several acidic pesticides; others are neutral or basic. A number of compounds are very volatile, but several do not evaporate at all. Without question, the most efficient approach to pesticide analysis involves the use of multiclass, multiresidue methods (MRMs). MRMs are preferable because many pesticides can be determined in a single analysis, reducing time and costs. The basic units of pesticide residue analysis are: (1) (2) (3) (4)
Sampling Extraction of pesticides from samples Clean-up Identification and quantitative determination of pesticide residue.
The procedure employed for isolation, clean-up and analysis of food samples is dictated by the composition of the food matrix, especially the fat content. Products with fat percent above 2% are considered fatty foods. Foods with fat composition of 2–20% include milk, nuts, wheat, corn, fish, liver, meat from pork, poultry, beef, eggs and avocado. The polarity ranges of the different pesticide families in water are an important consideration in the development of a universal residue analytical method which should have the widest scope possible. A universal extraction method is considered as a procedure in which all pesticide residues are transferred from sample matrix to organic phase [10]. It is important to transfer as much of the pesticide as possible from the matrix into the organic phase and the solvent system should eliminate the major part of the sample matrix from the organic phase; thus, this step can be seen as a raw clean-up procedure. The first developed MRM used a polar water-miscible solvent able to extract all pesticides including their metabolites. This solvent is miscible with the intrinsic food water, which generally enhances the quantitative pesticide extraction. Then, for the partitioning of the pesticides, it is necessary to use a non-polar solvent, which is miscible with the polar solvent and non-miscible with water. By this procedure the pesticides are distributed from aqueous phase into organic phase. The extent of this distribution into the organic phase depends mainly on the solubility of each pesticide in both solvent layers.
274
Anna Sannino
The first notable MRM was developed by Mills in the 1960 [11] when the nonpolar OC pesticides were the main focus for analysis. With this method, OC and other non-polar pesticides were extracted from non-fatty foods with acetonitrile, which was then diluted with water and the pesticides were partitioned into a non-polar solvent (petroleum ether). As a consequence, relatively polar pesticides, such as certain organophosphorus (OP) compounds were partially recovered. Later, new methods were developed to extend the analytical polarity range to cover OCs, OPs and organonitrogen pesticides (ONs) in a single procedure [12,13]. These MRMs used acetone instead of acetonitrile for the initial extraction and still a non-polar solvent (dichloromethane- or dichloromethane– petroleum ether) to remove water from the organic phase in the liquid–liquid partitioning step. Furthermore, sodium chloride was added to the water phase in both methods during the partitioning step. The basis of these extraction techniques is the use of an electrolyte (salting-out effect) for the partitioning of pesticides into organic phase. The Becker method used a NaCl solution, which only partially saturated the water phase with salt. However, in the extraction procedures developed by Luke et al. [13] and Specht and Tills [14], the water phase was saturated with solid NaCl to force more acetone into the organic layer, thus increasing its polarity and enhancing the extraction of the polar pesticides. The Becker method became official in Germany as the DFG-S8, and Specht method became the official DFG-S19 procedure [15]. The Luke method became the official PAM 302 electron ionization (EI) procedure [16], and several years later became AOAC Official Method 985.22 [17]. Taking into consideration the toxic potential of chlorinated solvents, many new developed methods use cyclohexane–ethyl acetate (1 + 1) instead of dichloromethane (or dichloromethane–petroleum ether, 1 + 1) in the liquid– liquid partitioning step whereas others use solid-phase extraction (SPE) to isolate pesticides from diluted acetone extracts [18]. Some authors [19,20] investigated the use of salts to separate water from acetone without using non-polar solvents. However, acetone is too miscible with water to be easily separated without using non-polar solvents. In the case of procedures in which acetonitrile is chosen as extraction solvent, salt alone can be used to form a satisfactory separation from water. Several multiclass MRMs based on salting-out principle with acetonitrile have been developed [21–24]. Anastassiades et al. [25] introduced the quick, easy, cheap, effective, rugged and safe (QuEChERS) method for the analysis of pesticide residues in fruit and vegetables. Lehotay et al. [26] demonstrated its effectiveness for more than 200 pesticides in lettuce and orange matrices. The procedure involves initial single-phase extraction of 15 g sample with 15 mL acetonitrile, followed by liquid–liquid partitioning formed by addition of 6 g anhydrous MgSO4 and 1.5 g NaCl. Removal of residual water and clean-up are performed simultaneously by mixing acetonitrile extract with 1.8 g of anhydrous MgSO4 and 300 mg primary secondary amine (PSAm) sorbent. The results were excellent for a wide range of pesticides, including polar and basic compounds such as methamidophos, acephate, omethoate, imazalil, thiabendazole (TBZ). The pesticides captan, chlorothalonil, dichlofuanid, folpet, tolylfluanid and pymetrozine
Pesticide Residues
275
are well known as being difficult for their determination using existing methods, including QuEChERS. The modification to improve the extraction and stability of the mentioned problematic pesticides has been presented by Lehotay et al. [27]; sample preparation entailed extraction with acetonitrile that contained 1% acetic acid and partitioning with a mixture of MgSO4 and sodium acetate. A third extraction solvent commonly used in MRMs is ethyl acetate (EtAc) [28,29]. EtAc has the advantage of partial immiscibility with water, which makes unnecessary the addition of non-polar solvents to separate water from organic extracts. However, a problem with EtAc is that some of the most polar pesticides are not readily extracted. To increase recoveries of polar compounds, large amounts of NaSO4-to bind the water- or polar co-solvents, such methanol and ethanol, are usually added. Another disadvantage associated with the use of EtAc is the extraction of a large amount of non-polar co-extractive, such lipids and epicuticular wax material, which must be removed before the determination step. With the demand for the faster sample preparation and reduced solvent usage, new techniques based on solvent extraction have been tested. One of these novel techniques that are emerging is pressurized liquid extraction (PLE) also known commercially as accelerated solvent extraction (ASE). The extraction process has three sequential steps. First, the analytes must diffuse from the core of the matrix to the surface. They are then transferred from the surface into the extraction fluid and, finally the analytes are eluted. Bogialli et al. [30] analysed residues of carbamate insecticides in vegetables and fruit using hot water as an effective extractant. PLE can be carried out with conventional solvents such as dichloromethane-hexane [31] or EtAc [32]. This technique requires dry samples — freeze-dried and powdered [31] or previously homogenized with a drying or dispersive agent [32]. PLE is fully automated but requires rather high-cost equipment. After the extraction step, the obtained crude extracts can be injected directly into the chromatographic system, but the majority of the sample preparation methods utilize different clean-up steps. Clean-up is still required to minimize matrix effects, to achieve better ruggedness and to decrease LOQs in pesticide residue analysis. SPE is a simple preparation technique based on the separation by liquid chromatography (LC) where the solubility and functional group interactions of sample, solvent and sorbent are optimized to affect the retention and elution. SPE is used for pesticide analysis for liquid samples, such as juices, wine and honey, and to clean-up organic solvent extracts after analyte isolation by means of liquid extraction [33]. Many MRMs include a clean-up step using adsorption columns, in particular Florisil, aluminium oxide (alumina) and silica gel. Most adsorbent columns provide a good clean-up only when they are eluted with solvent mixtures of low polarity, eluting less polar residues and leaving more polar coextractives in the column. A Sep-Pack cartridge containing 0.900 g Florisil was chosen as the SPE stationary phase by Sannino et al. [34] for the clean-up of processed fruit and vegetables. The eluate is very clean for the determination of 12 pyrethroids by GC-ECD.
276
Anna Sannino
The introduction of various types of co-polymeric sorbents has helped to make SPE a more robust purification technique with a wider application range than the conventional silica-based sorbent. A polymeric sorbent frequently used for the isolation of pesticides from food samples is a hydrophilic-lipophilic balanced (HLB) copolymer of N-vinylpirrolidone and divinylbenzene [35]. A very effective way how to utilize SPE sorbents for removing co-extractants from a matrix, and concurrently reduce manual handling, published by Anastassiades et al. [25] within the development of the QuEChERS method. In this study, the authors used a very simple clean-up approach that they call ‘‘dispersive-SPE.’’ A 1 mL aliquot of the sample extract is added to a vial containing a small amount of PSAm sorbent, and the mixture is mixed in a Vortex mixer for 30 s. PSAm as a weak anion exchanger sorbent is able to remove matrix components, such as organic acids, polar pigments, sugars and some other co-extractives that form hydrogen bonds [36]. With the current trends towards miniaturization of sample preparation, matrix solid-phase dispersion (MSPD), based on the dispersion of the sample on an adsorbent is a new SPE and clean-up technique that was first reported by Barker et al. in 1989 [37]. MSPD, based on dispersion of the sample on an adsorbent, such as Florisil, C18, alumina, silica or diatomaceous earth is a technique that allows the extraction and clean-up in a single step. For solid samples, the mixture is done in a mortar and then transferred to the extraction columns [37], whereas for liquid samples the dispersion of the matrix in the adsorbent is done directly in the extraction columns [38]. The basic concept of the technique is to allow the extraction of pesticides from homogeneously dispersed food samples in a solid support. The sample matrix is placed in a column, and the polar compounds, such as pigments, are held on the support. In this manner, various pesticide residues can be rapidly eluted with organic solvents and the extract can be analysed. MSPD eliminates the traditional processes of extraction and clean-up, reduces time and costs and avoid emulsification. It has been used mainly for the analysis of pesticides in fruit and vegetables but has also been applied to the analysis of liquid samples such as milk and fruit juices. Perret et al. [39] developed a method based on MSPD for the determination of multiclass pesticide residue (omethoate, dimethoate, carbendazim, propoxur, TBZ, carbaryl pirimicarb, azinphos-methyl, metidathion and iprodione) in peach, apple, apricot and pineapple juices. A flow diagram of the method is shown in Figure 1. MSPD is also a sample strategy appropriate to extract pesticide residues in matrices with high fat content. Ferrer et al. [40] proposed a methodology based on MSPD using aminopropyl as sorbent material with a clean-up performed in the elution step with Florisil to extract pesticides from olives and olive oil (the latter with a preliminary liquid–liquid extraction). Solid-phase microextraction (SPME) is a recent developed technique, which avoids organic solvents, and, can be easily automated [41–43]. In combination with GC, SPME is able to extract and to detect volatile residues in an easy and, relatively fast and cheap approach. Because of complications in quantitation, strong dependence on matrix, and certain practical matters, some quality in the results is sacrificed for speed and ease.
Pesticide Residues
277
1g fruit juice mixed with 1g diatomeaceous earth
→ elution with 10 ml ethyl acetate
→ evaporation of solvent
→ residue reconstituted with 500 µL methanol- water (50+50)
→ 50 µL injected into LC/MS-MS
Figure 1 Flow diagram of MSPD procedure employed by Perret et al.
SPME is based on the partition of analytes between the matrix and a silica fibre, coated with a stationary phase, whereas the analytes are retained due to their high affinity for this phase. SPME can be applied to the analysis of liquid matrices, and pesticides can be extracted by direct immersion in aqueous samples or headspace analysis. The other important step in SPME is usually performed by thermal desorption and gas chromatographic analysis, although it can also be achieved by solvent desorption and liquid chromatographic determination. SPME application to pesticide analysis requires, typically, a previous extraction step. Fruit samples have been extracted with high-speed blending with water [44]. A variation on the SPME technique is the use of a stir bar covered with poly(dimethylsiloxane) (PDMS). This technique, called stir-bar sorptive extraction (SBSE) is performed by stirring the sample with a stir bar for a given time. Applications to pesticide analysis in beverages have been recently published [45–47]. Bicchi et al. [47] determined nine pesticides in pear pulp by extraction on PDMS-SBSE followed by recovery through thermodesorption and GC/mass spectrometry (MS) analysis. The levels of pesticides range from 10 to 100 ng/g. The most universally applicable clean-up is gel permeation chromatography (GPC). It was introduced as a clean-up technique for pesticides by Stalling et al. [48]. They found that an automated GPC system removed the lipids from fish extracts and gave good recoveries of non-ionic chloride and polychlorobiphenyls (PCBs). Separation is generally performed by using divinylbenzene-linked polystyrene gels, mostly BIO-Beads SX3 (200–400 mesh, Bio-Rad, USA). GPC has the advantage of being applicable to a wide range of structurally dissimilar compounds, unlike some adsorption techniques that are narrower in scope. It is suitable for OC, OP and nearly all other types of pesticides. The stationary phase is a porous matrix with the pores closely controlled in size. Separation results through differences in the size of the sample molecules. Lipid molecules that are too large to enter the pores are totally excluded and are therefore eluted from the
278
Anna Sannino
column first. Most synthetic pesticides have molecular mass of between 200 and 400, whereas those of most lipids range from 600 to 1,500. This system could clean-up a wider range of sample types, including green plant lipids, animal feed extracts, human adipose tissue and beef tallow. Another valuable feature is that GPC can be carried out in an automatically controlled device. A GPC clean-up of vegetables, fruit and crops for the analysis of organophosphate pesticide residues was introduced by Ault et al. [49]. This GPC system used BIO-Beads SX3 with dichloromethane–cyclohexane (15:85, v/v) as the elution solvent, which is useful for the clean-up of seven carbamates and three related metabolites in fruit and vegetables [50]. The preparation of fatty samples for the determination of pesticides by chromatographic techniques requires the complete removal of the high-molecularmass fat from the sample to maintain the chromatographic system in working order. Most MRMs for the determination of pesticides in fatty matrices involve extraction of fat with an organic solvent, partition of residues in an immiscible solvent and/or clean-up by GPC and/or successive clean-up on a Florisil column [51–53]. Methods for extraction of fat are recommended which are simultaneously applicable for the extraction and determination of fat and the residue analysis in the fat portion. Sannino et al. [54,55] used a GPC procedure for determination of 24 OC pesticides, 9 PCBs and 39 OP compounds in 8 fatty preserved foods of vegetable and animal origin. Samples are extracted with dichloromethane and cleaned up by automated GPC with Bio-Beads SX3 and dichloromethane– cyclohexane (15:85, v/v) as the eluting solvent. A new method using GPC clean-up has been established for quantitative determination of 437 pesticide residues in animal tissue such as beef, mutton, pork, chicken and rabbit [56]. In this method, 10 g animal samples were mixed with 20 g sodium sulfate and extracted with 35 mL of cyclohexane–ethyl acetate (1:1, v/v). An aliquot of extract was injected into a 400 25 mm SX3 GPC column, with cyclohexane–ethyl acetate (1:1, v/v) as mobile phase at a flow rate of 5 mL/min. However, all these mentioned techniques, using large columns and flow rates, need long analysis times and large amounts of solvents. Some pesticides with high molecular mass (e.g., pyrethroids) are not sufficiently separated from wide elution band of co-extractants, which can result in lower recoveries [36]. Considering the entire analytical process, much effort is still required to reduce analysis time and cost. Recently Liu et al. [57] have proposed an online GPC-GC/MS for the analysis of residual pesticides. In this experiment, a semi-micro GPC column was employed. A low flow rate of 0.1 mL/min resulted in a 40-fold reduction in solvent consumption compared to conventional GPC column applications. This system can determine 97 pesticides in 90 min.
5. INSTRUMENTAL DETERMINATION Analytical methodologies employed should be capable of residue measurement at very low levels and must also provide unambiguous evidence to confirm both the identity and the magnitude of any residues detected.
Pesticide Residues
279
Chromatographic methods are most widely used for the analytical separation, identification and quantification of pesticide residues in different matrixes.
5.1 Gas chromatography The introduction of commercially available fused-silica capillary columns was a great step forward with regard to the separation power and enhanced sensitivity. Due to the reduction of peak width, capillary columns attains the separation and determination of a large number of pesticides with similar physico-chemical characteristics. The selection of columns depends upon the nature of the pesticide to be separated. In general, 5% diphenyl, 95% dimethylpolysiloxane stationary phase, normal bore columns with ID (internal diameter) of 0.25 mm (20– 30 m 0.25 mm ID 0.25 mm) were successfully utilized in multiresidual analysis. Owing to its high separation efficiency and the variety of selective and sensitive detection methods that can be used, GC is the preferred method for determination of volatile and thermally stable compounds such as OC and OP pesticides. An ideal selective detector for the analysis of pesticide residues would respond only to the target pesticides, while the co-extracted compounds remain transparent. Pesticides almost always contain heteroatoms and often have several atoms in a single molecule. The most frequently encountered heteroatoms are O, P, S, N, Cl, Br and F. Therefore, most GC methods employ element-selective detectors. Two of these detection methods are nitrogen phosphorus detection (NPD) for N- or P-containing compounds and flame photometric detection (FPD), which is better suited for the detection of P-containing compounds. For the determination of OP compounds the FPD is widely used because of its very good selectivity and good sensitivity. This makes the detector particularly suitable for the determination of OP pesticide residues in various crops without extensive clean-up of the sample [55]. For the determination of OC pesticides, electron capture detection (ECD) has been used for the past 30 years because of the extraordinary sensitivity for organic halogen compounds. Since the retention time is characteristic for each compound in a given chromatographic system, the pesticides can be tentatively identified by comparison of their individual retention times. The detectors mentioned earlier do not provide unequivocal confirmation of identity and are often subjected to matrix interferences. Confirmation of results required the use of a further chromatograph equipped with a different type of column or detector. Moreover, the limiting disadvantage in conventional GC analysis was that only a limited number of compounds could be detected in a single determination. In multiclass, MRMs, several GC injections are often required when these selective detectors are used. When fused capillary columns became feasible to couple to a mass selective detector, the routine confirmation process could be carried out. In the past, mass spectrometry was chosen as the method for confirmation of pesticides initially detected in food by other techniques. Its unique combination of specificity and sensitivity, together with the wide applicability to a diverse range of organic contaminants, makes mass spectrometry (MS) the primary
280
Anna Sannino
detection method for pesticide residue analysis [58]. The MRMs are preferred, not only due to cost benefits but also due to importance of checking a large number of pesticides in one single analysis compared to methods for determination of single analyte. The need for analysing pesticides belonging to different classes requires the use of universal detectors able to determine them at residue levels. MS detection is a good option because it can be employed as a universal detector at full scan and also as a selective detector in the selected ion monitoring (SIM) mode. The most widely used GC/MS technique for pesticide residue analysis is based on single quadrupole instruments and EI. Selectivity of GC-MS can be adjusted by the selection of appropriate molecular and fragment ions (SIM mode) to avoid interferences from co-extracted sample materials. Therefore, the importance of GC with ECD, NPD or FPD detection has decreased in pesticide residue laboratories. A MRM for the quantitative determination of 39 OP compounds including the parent pesticides and their major metabolites in 7 fatty preserved foods of vegetable and animal origin is described by Sannino et al. [55]. OP compounds are quantified by capillary gas chromatography with flame photometric detection (GC/FPD) using OV-1701 and DB5 columns and two temperature programs. Determination of all 39 OP compounds by a single chromatographic run was possible by GC/MS with SIM. Figure 2 shows total ion profiles of meat sauce extract and same sample fortified with all 39 compounds obtained by the SIM program. Co-elution is usually not a problem because each pesticide has its own characteristic ion pattern. Figure 3 illustrates a typical example of how two co-eluting analytes were separated and estimated. With the assistance of a software program the single-ion chromatograms of m/z 221 and 232 (pyrazophos), 160 and 132 (azinphos-ethyl) were extracted and reconstructed from the 36 to 37 peak of Figure 6. Moreover, since most of the monitored ions were above 100, a minimum background and less spectral interferences were observed in the fragmentograms. Simultaneous determination of 24 organochloride pesticides and 9 PCB congeners [54] can be performed by a single chromatographic run following the SIM program of Table 2. Gas chromatographic conditions as capillary column, temperature program and flow rate were the same as those used in method for OP pesticide determination [55]. Then, two injections at two SIM settings were required per sample to cover 24 OC pesticides, 9 PCBs and 39 OP compounds. The main limitation of GC/MS is the relatively low sensitivity obtained for many pesticides in the full scan mode when EI is selected. The introduction of the ion-trap detector (ITD) improved the LODs. Analysis is normally carried out in the full scan mode — thus complete mass range is acquired for all GC peaks. In full scan mode, these instruments are sensitive and confirmation by library search is possible at lower concentrations. But, at trace levels, quantitative analysis is based on chromatograms of ions extracted from mass spectra and that are specific to the substance. Compared to single quad instrument running in SIM, identical pesticides are covered and the sensitivity does not differ significantly. Lehotay and Eller [59] developed a MRM using GC-ITMS for analysis of 46 pesticides in fruit and vegetables. Simultaneous determination of 19 fungicides in processed
Pesticide Residues
281
TIC: MS703.D Abundance (a) 4000
3000
2000
1000
0 Time-->
6.00
8.00
10.00
12.00
14.00
16.00
18.00
20.00
22.00
TIC: MS705.D Abundance (b)
4000
8 3
3000
1
5
2
6
7
36-37 34-35 38 39
28 15-16 19 18 21-22 23 20
10 9
2000
31
12-1314
4
11
30 24-25 26-27 29
32 33
17
1000
0 Time-->
6.00
8.00
10.00
12.00
14.00
16.00
18.00
20.00
22.00
Figure 2 Total ion current chromatograms of (a) unspiked meat sauce and (b) meat sauce spiked with 39 OP compounds at 0.025 mg/kg. Peaks: dichlorvos (1), mevinphos (2), thionazin (3), ethprophos (4), sulfotep (5), phorate (6), dimethoate (7), fonofos (8), diazinon (9), disulfoton (10), formothion (11), methyl-parathion (12), chlorpyrifos-methyl (13), malaoxon (14), paraoxon (15), enchlorfos (16), fenitrothion (17), pyrimifos-methyl (18), malathion (19), fenthion (20), chlorpyrifos-ethyl (21), parathion (22), bromophos (23), chlorfenphos (24), isofenphos (25), mecarbam (26), quinalphos (27), methidathion (28), bromophos-ethyl (29), tetrachlorvinphos (30), ethion (31), carbophenothion (32), EPN (33), phosalone (34), azinphos-methyl (35), pyrazophos (36), azinphos-ethyl (37), dialifos (38), coumaphos (39). Experimental conditions: 30 m 0.25 mm 0.25 mm HP MS-5 column. MS analyser: quadrupole operating in SIM mode. Reproduced from Ref. [55] with permission from AOAC International, Copyright 1995.
fruit and vegetables was carried by Sannino et al. [60]. Quantitative analysis was performed both by GC/ITMS and GC/ECD and the results compared. Figure 4 illustrates a GC/ITMS typical example of how a targeted pesticide was detected in a sample extract. The normalized ion chromatogram of m/z 173 and 175 254 (Figure 4b) was extracted and reconstructed from the total ion profile (Figure 4a).
282
Anna Sannino
Abundance
Ion 132.00 (131.70 to132.30): MS704.D Ion 159.95 (159.65 to160.25): MS704.D Ion 232.05 (231.75 to232.35): MS704.D Ion 221.00 (220.70 to221.30): MS704.D
2400 2200 2000 AZINPHOS-ETHYL
1800 1600 1400 1200 1000 800 600
PYRAZOPHOS
400 200 Time--> 0 22.40 22.50 22.60
22.70 22.80 22.90 23.00 23.10
23.20 23.30 23.40
Figure 3 Extracted single-ion chromatograms of characteristic ions of pyrazophos and azinphos-ethyl from the peaks 36 to 37 in Figure 2. Reproduced from Ref. [55] with permission from AOAC International, Copyright 1995.
With the assistance of computerized graphing and data manipulation, the extracted ion data showed the possible presence of propyzamide. The above positive finding led to further examination of the full mass spectral data at 11.18 min. The exact matching with the NIST library spectrum of propyzamide (Figure 4c and d) provides the conclusive fingerprint of the presence of pesticide in the extract. An additional advantage of IT instruments is the capability of performing tandem mass spectrometry (MS-MS) by means of collision-induced dissociation (CID). The use of MS-MS improves the selectivity of the technique, sometimes with a drastic reduction in the background and without loss of identification capability. It enables analysis of pesticides at trace levels in the presence of many interfering compounds. Dissociation conditions were selected for each pesticide using methods built with the automated method development (AMD) editor. As general criteria,
Pesticide Residues
283
Table 2 SIM data for simultaneous determination of 24 organochloride pesticides and 9 PCB congeners Compound
Acquisition group
Start time (min)
Characteristic masses, m/z (relative abundance, %)a
a-HCH HCB b-HCH g-HCH Trans-chlordene d-HCH PCB 28 Heptachlor PCB 52 Aldrin Heptachlor epox g-Chlordane o,p DDE a-Endosulfan PCB 101 a-Chlordane Dieldrin p,pu DDE o,p DDD Endrin Perthane b-Endosulfan 118 p,pu DDD o,p DDT PCB 153 PCB 105 Endosulfan sulfate p,pu DDT 138 p,pu methoxychlor 156 180
1 2 3 4 5 6 7 8 9 10 11 12 13
8.0 8.9 9.3 9.7 10.1 10.5 11.0 11.9 12.6 13.4 15.0 16.9 17.3
14
18.6
15 16 17
19.1 19.4 19.6
18
19.9
19
20.1
20
20.5
21
21.1
22
21.6
183(100),181(95),219(92) 284(100),282(48),286(40) 181(100),183(85),219(76) 181(100),183(85),219(76) 66(100) 181(100),183(82),219(75) 256(100),258(99),260(20) 272(100),274(82),237(45) 292(100),290(74),294(50) 263(100),265(62),293(32) 353(100),355(82),237(41) 373(100),375(98),377(37) 246(100),248(64),318(32) 239(92),195(100),241(80) 326(100),324(60),328(65) 373(100),375(100),377(69) 277(100),263(76) 318(70),246(100),248((64) 235(100),237(68),165(60) 263(100),265(56),281(34) 223(100),224(15) 237(100),240(37) 326(100),324(65),328(60) 235(100),237(58) 235(100),237(63) 360(100),362(79),358(70) 326(100),324(60),328(68) 272(100),229(64),387(30) 235(100),237(67) 360(100),362(84),358(72) 227(100),228(14) 360(100),362(86),358(75) 394(100),396(98),398(53)
Source: Reproduced from Ref. [54] with permission from AOAC International, Copyright 1996. a An asterisk indicates an ion used in quantitation.
precursor ion dissociation conditions are selected in order to obtain a balance between maximum sensitivity, minimal spectral interferences and enough structural information for an unequivocal identification. So, the base peak on the spectrum is generally selected as the precursor ion with a narrow mass
284
Anna Sannino
Spect 1 BP 173 (453=100%) erbi11.sms
11.198 min. Scan: 672 Chan: 1 Ion: 24999 us RIC: 2871 BC
173
100%
75%
50%
254 145
25%
240
110 214
191
125
226
277
0% 150
200
250
293
306
300 RIC all erbi11.sms
kCounts
323 m/z
6
(a) 5
4
3 S/N: 78 S: 935 N: 12
kCounts
Ions: 173+175+254 all erbi11.sms
1.00
0.75
(b)
0.50
0.25
0.00 10.75
11.00
645
660
11.25 Segment 1 675
11.50
11.75
690
705
minutes Scans
Figure 4 (a) Display of the total ion chromatogram from retention time 10 to 12 min of an apricot sample fortified with 10 ng/g propyzamide. (b) Extracted ion chromatograms of the most characteristic ions of propyzamide (173 + 175 + 254 m/z). (c) Mass spectrum of the eluate at 11.19 min. (d) NIST library spectrum of propyzamide.
isolation window. In the case in which the precursor ion presents a low m/z or can be confused with a matrix ion, a different fragment, with lower abundance, is selected. Ideally, the MS-MS spectrum should be optimized to maximize the signal of the highest mass product ion while obtaining at least two product ions for confirmation purposes. To perform MS-MS [21], each analyte must have its own ion preparation method (IPM), which performs the functions of ionization, isolation and precursor fragmentation. Each analyte must have its own list of
285
Pesticide Residues
Purity = 768 Fit = 911 RFit = 814 Average = 831 Ion Range: 43 - 329 Spect 1 BP 173 (453=100%) erbi11.sms
11.198 min. Scan: 672 Chan: 1 Ion: 24999 us RIC: 2871 BC 173
100%
(c)
75%
50%
254 145
25%
240
110 191
125
214 277 293
0% Match 1 of 25
323
Propyzamide CAS No. 23950-58-5, C12H11Cl2NO, MW 255 173
100%
(d) 75%
50% 255 145 25% 43
75
109
240 192
226
0% Diff 100%
Spect 1 - Match 1 of 25 Normalized
11.198 min. Scan: 672 Chan: 1 Ion: 24999 us RIC: 2871 BC Propyzamide
50%
0%
-50%
-100% 50
100
150
200
250
300
m/z
Figure 4 (Continued)
parameters that will create the desired product spectrum. Table 3 shows examples of IPM parameters for various pesticides. To analyse co-eluting or closely eluting peaks the selected reaction monitoring (SRM) methods were created [61,62]. Unlike full-scan MS, in which one set of conditions can detect all analytes in a GC run, MS-MS with an IT instrument is much like SIM, in which
286
Table 3
Anna Sannino
Examples of IPM parameters for various pesticides
Pesticide
Start time
Precursor ion Storage level Excitation (m/z) (m/z) voltage (V)
Product ion (m/z)
Biphenyl 2-Phenylphenol Tecnazene Diphenylamine Dicloran Quintozene Pirimetanil Metalaxyl Dichlofluanid Triadimefon Fenson Ciprodinyl Penconazole Fipronyl Mepanypirim Buprofezin
4.0 6.3 7.1 7.1 8.0 8.8 8.8 9.2 11.0 11.0 12.6 13.3 13.3 14.2 11.8 16.0
154 169 261 169 176 295 198 206 224 208 268 224 248 367 222 175
122 115 201+203 139+140 148 265 155+129+182 132+162 123 180+144 141 208 192+206+157 332+324+292 193+191+218 117+132
60 70 110 70 70 128 85 88 90 90 95 95 100 130 90 75
70 70 78 74 71 80 93 70 65 75 0.28 98 90 0.8R 2.6R 65
Note: R, resonant mode.
specific conditions are used for targeted analytes within time segments during a GC run. The IT instrument used by Lehotay [22] was capable of employing five different sets of conditions within a single segment. The GC-MS-MS analysis allows for more accurate analysis than GC-MS primarily due to the removal of matrix interference. The typical food matrix contains many compounds that are thousands of times more concentrated than the pesticide residue levels. Even relatively small ion intensities from a co-eluting matrix compound can cause a significant positive interference. Figure 5 shows an example of the advantages of GC-MS-MS over GC-MS in the detection of dichlofuanid at 20 ng/g in an olive extract. Interference from coextracted plant material can also be reduced significantly in comparison with GC-MS. The GC-MS-MS analytical method was able to identify the presence of the low amount of dichlofuanid in the complex extract, whereas the GC-MS method, obtained with the same instrument, is not capable of discriminating between the analyte and matrix signal. In recent years, some interesting applications of GC-MS-ITD in the analysis of pesticide residues in food have been published. Lehotay [22] determined 22 diverse pesticide residues in mixed apple, green bean and carrot extracts by GC-MS-MS using IT chromatography. For most pesticides the LODs in GC-MS-MS were 5–20 times lower than those in GC-MS with the same instrument. Martinez-Vidal et al. [63] developed and validated a selective procedure to determine multiclass pesticide residues in lyophilized agricultural plants by low-pressure GC coupled with MS-MS.
287
Pesticide Residues
Chromatogram Plots Plot 1: d:\sa\sa042.sms Ions: 224+226 all Plot 2: d:\ca\ca226.sms Ion: 123 merged kCounts
Ions: 224+226
Olive oil fortified with dichlofuanid at 0.020 mg/kg
80 70 60 50 40 30 20
GC/MS
10 0 kCounts
3.5
Ion: 123
S/N (P-P): 69
3.0 2.5
GC/MS-MS
2.0 1.5
Precursor ion 224
1.0 0.5 0.0 11.0
11.1
11.2
11.3
11.4
11.5
11.6
minutes
Figure 5 Comparison of GC-MS and GC-MS-MS chromatograms obtained by gas chromatograph/ITMS in the detection of dichlofuanid at 20 ng/g in olive oil extract. See Table 3 for MS-MS conditions.
The number of analytes that can be simultaneously determined in a time segment is limited to 5–6. The use of the triple quadrupole (QqQ) mass spectrometer can solve this technical limitation because this instrument can measure 25–30 analytes at the same time by use of the SRM mode. This scan mode is faster than the production ion scan mode available on an ITD. Within each segment, precursor ions are isolated in the first quadrupole, and then fragmented by collision-induced decomposition in the second quadrupole with the goal of generating spectra at different voltages, and in the third quadrupole the produced ions were separated before detection. The chromatographic separation is not a critical point in the analysis of pesticide residues by GC/QqQ-MS-MS because the analyser is able to monitor a high number of co-eluting compounds: the only limit was due to the shape peak and number of points per peak. Recently, GC-QqQ-MS is becoming a powerful tool for pesticide residue analysis in a variety of complex matrices, due to its inherent advantages: selectivity are notably improved, the sample pre-treatment step can be minimized and
288
Anna Sannino
reliable quantitation and confirmation can be easily achieved at low concentration levels required. In the last few years, several GC-MS-MS methods have been developed for the determination of a large number of multiclass pesticides in food [64–69]. Walorczyk and Gnusowski [67] investigated the feasibility of low-pressure gas chromatography (LP-GC-MS) in conjunction with a QqQ mass spectrometer, as a route towards fast pesticide residue analysis. LP-GC is a chromatography technique that involves the use of a relatively short (10 m) large-diameter column connected with a restriction capillary (0.1–0.25 mm of appropriate length) at the inlet end. Under the optimized conditions the analysis time was reduced to 13.3 min which corresponds to an almost three-fold gain in speed versus the conventional GC (37 min). For evaluation purposes, 78 target pesticides were included in the screening method and 12 target pesticides in the quantitative methods. Martinez Vidal [68] described the validation of a MRM in cucumber matrix, able to analyse 130 multiclass pesticide residues in less than 12 min with a single chromatographic injection. A first identification of the pesticides is based on an MS-MS screening method, which monitors a single transition for each target compound. Potentially positive samples in the screening method were further analysed by the MS-MS confirmation/quantitation method which monitors two or three MS-MS transitions for each compound, also in less 12 min. The calculated LOD and LOQ were typicallyo3.2 and 9.6 mg/kg, respectively. Plaza Bolan˜os et al. [69] developed and validated a method for 151 pesticide residues in a single injection in strawberry samples. The list of target compounds included various classes of pesticides such as OC, OP, carbamates, pyrethroids, triazoles and dicarboximides. The combination of QuEChERS and GC/QqQ/ MS-MS allows the preparation of a batch of 10 samples in about 1 h, and the subsequent chromatographic analysis in less than 3.5 h. Time-of-flight (TOF) instruments have recently gained popularity in quantitative analysis. TOF mass spectrometers (TOF-MS) have advantages over quadrupole MS spectrometers because of their fast acquisition rates and highresolution capabilities. Gas chromatograms have narrow peaks and require a fast-scanning detector. TOF-MS, unlike scanning instruments, have the ability to acquire chromatograms in microseconds, depending on the acceleration potential (L.N. Williamson and M.G. Bartlett). Normally, TOF-MS have been used for accurate mass measurements for empirical formula verification. However, over the past decade, they have been used quantitatively as well. Cajka and Hajslova [70] demonstrated the high-resolution TOF-MS as a powerful tool for reliable detection and accurate quantitation of pesticide residue even at very low concentration levels. With only few exceptions, LOQ for most of pesticides involved in this study were far below 0.01 mg/kg. The combination of large volume-difficult matrix introduction (LV-DMI) with GC/TOF-MS, described by Patel et al. [71] provides the analyst with a simple but rapid alternative GC-MS technique for analysis of 98 pesticides in fruit-based baby foods at 0.010 mg/kg. Samples were extracted with EtAc in the presence of Na2SO4 and NaHCO3, and the crude extracts were analysed directly using LV-DMI/GC-TOF-MS.
Pesticide Residues
289
The instrumentation and basic principle have been described by De Koning et al. [72]. Depending on their volatility, analytes present in the extract, which is held in a microvial inside the injector liner of the GC, are transferred onto column as the temperature of the injector is increased. The non-volatile matrix components are retained in the DMI vial and consequently do not contaminate the chromatographic system.
5.2 Liquid chromatography One of the disadvantages of GC has always been, and in fact still is, the requirement that the compound to be determined has to be thermally stable and should have a sufficient volatility. In GC analysis, these compounds either show sign of thermal decomposition or fail to elute to column. In recent years many new pesticides have been developed that are not very well amenable to GC. Among the analytical approaches, LC is the preferred separation technique for the most polar and thermally labile pesticides. There are some classes of pesticides for which HPLC is superior to GC, such as carbamates, urea herbicides, benzoylurea insecticides and benzimidazole fungicides. HPLC methods for the determination of pesticides could employ reversedphase. As most pesticides are low-polarity compounds, they often are analysed by reversed-phase chromatography with C18 or C8 columns and aqueous mobile phase, followed by UV adsorption, UV diode array, fluorescence or mass spectrometric detection. In the determination of phenylureas, which are used extensively to protect a large number of crops against weeds, LC methods have been used in various matrices. UV detection used in many methods [73,74]) is sensitive enough in most cases but lacks selectivity, especially when trace levels in complex samples need to be assayed. Effective clean-up before LC/UV determination could be sufficient to isolate phenylureas from matrix interferences well enough to allow determination at low levels required by current regulator laws for baby and organic foods (p0.010 mg/kg). Sannino [75] described a method for quantitative determination of nine phenylurea herbicides in potatoes, carrots and mixed vegetables. Samples are extracted with acetone, partitioned with ethyl acetate–cyclohexane (50 + 50, v/v) and cleaned up by GPC with ethyl acetate–cyclohexane (50 + 50, v/v) as eluent. A further purification on Florisil cartridge was necessary to obtain an extract free from interferences when detected by LC with UV at 254 nm. The fluorescence detector has been in use for a number of years on a more or less routine basis. Fluorimetry is much more selective and in many cases much more sensitive than UV absorbance spectrometry. The better selectivity is because two wavelengths, the excitation and the emission wavelength, are involved, and by a careful selection of these two wavelengths a very selective detection is possible. The very high selectivity of fluorimetry is of course also a disadvantage because there are only a rather limited number of compounds that can be detected with good sensitivity. Some classes of compounds show a strong native fluorescence, but there are not many pesticides that show a native fluorescence.
290
Anna Sannino
An example of LC method with fluorescence detector is the determination of TBZ and carbendazim, two compounds that belong to the benzimidazole class. They are systemic fungicides used as either pre-harvest or post-harvest treatment for the control of a wide range of fruit and vegetable pathogens. Carbendazim is the major metabolite and fungitoxic principle of benomyl and thiophanate methyl (TM). Sannino [76] used a reversed-phase liquid chromatographic method for determining carbendazim, TBZ and TM in fruit products (nectars, purees, concentrates and jams). The extraction and clean-up method, based on the procedure developed by Bicchi et al. [77], is schematized in Figure 6. The fungicides were separated and quantified by using an ion-pairing mobile phase with UV and fluorescence detectors in tandem, following the procedure of Gilvydis and Walters [78]. UV and fluorimetric detectors connected in series allowed the simultaneous determination of the non-fluorescent TM and fluorescent carbendazim and TBZ. Figure 7 shows the chromatograms of apricot puree extract and the sample spiked with 0.1 mg/kg of carbendazim and TBZ and 0.01 mg/kg of TBZ. For those compounds which do not possess appreciable native fluorescence, a derivatization technique can be employed. In pesticide residue analysis the main application of derivatization is the determination of NMCs. They comprise an important class of insecticides, widely used for crop protection with some of the most common ones being carbaryl, carbofuran, aldicarb, methomyl and oxamyl. Carbaryl has been included in the final list of compounds to be considered for periodic re-evaluations by the 2001 Joint FAO/WHO Meeting on the Pesticide Residues [79]. NMCs can be determined by UV detector [80]. However, the sensitivity and selectivity offered by UV detection is very poor, because the carbamates present their absorption maximum at about
Non Fatty food
Extraction with HCL/ methanol
Centrifugation- filtration
Aliquot to pH 7.5
Clean-up on a diatomaceous earth column
Analysis by HPLC/ UV/ FL
Figure 6 Scheme for simultaneous determination of benzimidazole fungicides employed by Sannino [76].
Pesticide Residues
291
190 nm. Post-column hydrolysis and derivatization coupled with fluorescence detection has been accepted as a standard protocol by several official organizations (US-FDA, EN 14185-2) [81,82]. The derivatization is specific for primary amines and thus adds a high degree of selectivity to the detection compared to direct UV absorbance detection of the parent compounds. The carbaryl metabolite, 1-naphthol, which is not carbamate, is unaffected by this reaction sequence, but exhibits an equally strong native fluorescence. Thus, on the basis of the pioneering work by Moye et al. [83] which was refined by Krause [84] various sensitive and selective LC methods including post-column derivatization for simultaneously determining NMCs in complex matrices such as vegetables [85,86] and meat [87] as well as water [88] have been proposed. The typical method is as follows: the pesticides are extracted from food with organic solvents, the extract is cleaned up by a method based on liquid–liquid or solid–liquid partition, and is analysed by LC with post-column derivatization. Podhorniak [89] uses an acetone extraction, followed by an aminopropyl SPE. A method is presented for the determination of 24 compounds (13 parent NMC pesticides and their metabolites, and piperonyl butoxide) in selected fruit and vegetables. The Comite´ Europe´en de Normalisation (CEN; European Committee for Standardization) Technical Committee CEN/TC 275 ‘‘Food Analysis-Horizontal Methods’’ has prepared the European Standard EN 14185-2 [82] method for the determination of NMC in fruit and vegetables based on post-column derivatization. The extract is purified on a diatomaceous earth column. A disadvantage of the post-column technique is that special equipment is needed, such as a mixer chamber, a reactor and an extra pump. In addition, coexisting substances having fluorescence from food, especially from citrus fruits, frequently interfere with the determination of the pesticides.
5.2.1 Liquid chromatography-mass spectrometry The number of compounds that cannot be determined by GC because of their poor volatility, high polarity and thermal instability has grown dramatically in the last few years. Agrochemicals belonging to carboxamide, quinazolin, phenoxypyrazol, strobilurin, pyrimidine, triazol, carbamate, neonicotinoid, morpholine classes are representative of the newly introduced molecules. The identification of pesticides in complex samples can be a problem for LC with traditional detection methods such as UV or even diode array detection (DAD), because the latter technique may not be specific enough for spectral differences that are too small. A fluorescence detector can offer a greater selectivity compared to UV detection, but if there are many different compounds to be analysed, this technique will not provide adequate results [90]. Nowadays, liquid chromatography coupled with mass spectrometry (LC/MS) is becoming one of most powerful techniques for the residue analysis of polar, ionic or low volatility pesticides in fruit and vegetables. Compared to traditional detectors electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) sources in combination with MS instruments have increased the sensitivity of LC detection by several orders of magnitude. Single quadrupole
Anna Sannino
1.0
UV (280nm)
-MBC
-TM
volts
0.8
0.6
(b) 0.4 (a) 1.0
1.5
2.0
(a)
2.5
3.0
x10 min UV (305 nm) -TM
4.5
x 10-1 volts
4.0 3.5
(b)
3.0 (a)
2.5 1.0
1.5
2.0
2.5
3.0
x10 min 4.5
Fluorescence
-MBC
(b)
4.0
3.5 -TBZ
x 10-1 volts
292
3.0
(b) 2.5
(a) 1. 0
(c)
1 .5
2. 0 x10 min
2 .5
3. 0
Pesticide Residues
293
was the first mass spectrometer introduced in the market for combination with LC by means of atmospheric pressure ionization (API) sources. Those interfaces have the characteristic of being designed to provide a soft ionization process that lead to a mass spectrum with only few ions (commonly only the molecular ion), without the required specific structure diagnostic ions. The poor fragmentation of molecules is translated in deficient specificity because isobaric interferences (compounds with the same m/z ratio) or multiple component spectra are frequently observed in extracts of complex matrices [91]. Then, in contrast to GC/MS, single quadrupole mass spectrometers are not used in the majority of recent studies dealing with LC/MS. A disadvantage of single quadruple instruments is the high intensity of background signals derived from sample matrix and HPLC solvent clusters. Owing to this chemical noise in real samples, very low LODs cannot be achieved even if the sensitivity of these instruments is high. The chemical background can be reduced significantly if MS-MS in combination with SRM is applied. Reaction-monitoring modes enhance the detection limits in analytical procedures. In a QqQ, Q1 and Q3 quadrupoles are both fixed at a single mass. This technique is applied when the precursor and the product ions are known before analysis. Even if the co-extracted matrix component has the same molecular mass of a pesticide it can be separated in SRM experiments because their fragmentation in the collision cell most often results in different product ions. Therefore, MS-MS offer excellent sensitivity and unsurpassed selectivity. For this reason, QqQ analysers have been the most widely used technique for the determination of pesticides in food until now. In the last 4 years, many LC-MS-MS methods have been developed for multiclass pesticides in fruit and vegetables and water [92–101]. Nowadays, a modern commercial QqQ mass spectrometer is suitable to detect approximately 100 analytes simultaneously with sensitivity sufficient for residue determination at the 0.010 mg/kg level [92]. In the case of sufficiently high concentrations, the simultaneous observations of approximately 200 SRM transitions are feasible. The use of time window programs (periods) is not necessary unless the number of analytes to be analysed within one run is significantly increased, or pesticides with very low response are determined. Because of the high sensitivity achieved by MS-MS, gradient elution on a small reversed-phase column is usually used. However for confirmation purposes at least two transitions must be recorded. Pizzutti et al. [101] developed and validated a method for the analysis of 169 Figure 7 Chromatograms of (a) apricot puree free from carbendazim, TM and TBZ, and (b) apricot puree spiked with 0.1 mg/kg of carbendazim and TM and 0.0010 mg/kg of TBZ obtained by UV (at 280 and 305 nm), and (c) fluorescence detection at excitation/emission wavelengths of 280/310 nm, immediately following carbendazim elution at 305/345 nm. Column: 5 mm Supelcosil LC-18-DB; injection volume, 25 mL; mobile phase; 35% methanol in ion pairing solution. 1 g sodium decanesulfonate dissolved in a mixture of 200 mL of water, 7 mL of phosphoric acid and 10 mL of triethylamine and diluted to 1 L with water); column temperature: 401C and flow rate: 1.5 mL/min. Reproduced from Ref. [76] with permission from Elsevier, Copyright 1995.
294
Anna Sannino
pesticides in soya, without clean-up, by LC-MS-MS using positive and negative ESI. In total, 155 pesticides were analysed in the positive mode and 14 pesticides in the negative mode, each mode in one single chromatographic run. ITDs may also operate in the MS-MS mode, which reduces the background to a level known from MS-MS. When performing MS-MS, quadrupole ion trap (QIT) instruments are generally more difficult to handle than QqQ analysers but they have the advantage of working in product-ion-scan without loss of sensitivity. Moreover, QIT offers the possibility of performing multiple-stage fragmentation (MSn). However, ion collection, fragmentation, and mass analysis of fragments in a step-by-step process in traps require much more time than in QqQ instruments, which do this in parallel. Furthermore, ion traps suffer from a limited dynamic range, a smaller potential to fragment very stable ions and the inefficiency to trap low-mass fragments. Soler et al. [102] compared QIT and QqQ for determining pesticides in orange samples. The results indicated that TQ provides higher precision, better linearity, it is more robust and when the purpose of the analysis is quantitative determination, it is preferable over QIT. However, the LOQs were almost the same for both instruments. All LC-MS instruments can be equipped with at least three types of soft ionization sources, which are ESI, APCI and photoionization. Up to now, applications of photoionization to the determination of pesticides have been rarely published. ESI and APCI are used more often. The ESI coupled with MS-MS is supposed to have a high sensitivity and selectivity for a wider range of pesticides in food. There are several instrumental parameters that have drastic influence on the ionization efficiency. The instrumental optimization includes the adjustment of typical interface parameters such as the ionization voltage in ES, the pressure of the spraying/nebulizing gases, the interface temperature and the clustering potential. The mobile phase is important to obtain a good chromatographic separation, but it also affects the analyte ionization and the sensitivity of the mass spectrometry. Usually, the use of MS-MS does not require any chromatographic separation between analytes, because it is very rare to find molecules that share the same unique transition. However, the simultaneous analysis of a high number of compounds by MS-MS requires at least a sufficient chromatographic separation, in order to reduce the matrix effect. Methanol and/or acetonitrile are usually used as organic modifiers. LC separations are sometimes improved at acidic pH, using acetic acid or formic acid, as such or in combination with ammonium acetate or ammonium formate. The intensity of signal can be increased in the positive ionization (PI) mode; however the presence of H+ ions inhibited the negative ionization. A relatively new and valuable technique in the field of pesticide analysis is the TOF-MS. The accurate mass measurements of the TOF-MS (typical mass error o2 mDa) ensure an equal selectivity as that obtained with the two type of MS-MS. The high degree of selectivity is obtained by removing matrix interferences at the same nominal mass measurement (using the exact mass chromatograms). The main advantage of this type of instrument is the
Pesticide Residues
295
identification of non-target pesticides and unknown peaks in a sample even if analytical standards are not available. Thurman et al. [103] developed an identification scheme using a combination of LC/TOF-MS (accurate mass) to generate elemental composition of ions and LC/MS ITMS (MS-MS) providing complementary structural information, which is useful for the elucidation of unknown organic compounds at trace levels in citrus fruit extracts. This scheme has been applied to identify two post-harvest fungicides (imazalil and prochloraz), the main degradation product of imazalil and a non-previously reported prochloraz degradation product. The high speed and acceptable sensitivity have made TOF an attractive alternative to quadrupole or QqQ. Recently, LC/TOF-MS has been proven to be a sensitive and selective method for the determination and confirmation of pesticide residues in vegetables and fruit [104] obtaining LODs in compliance with established MRLs. Gilbert-Lopez et al. [105] developed a method based on LC/ESI-TOF-MS for the determination of 12 pesticides (MCB, TBZ, imazalil, tridemorph, triadimefon, bitertanol, prochloraz, flutriafol, myclobutanil, iprodione, diphenylamine and procymidone) in fruit-based baby foods. The confirmation of the target pesticides was based on accurate mass measurements of protonated molecules (M + H)+ and fragment ions. LODs were between 0.1 and 10 mg/kg depending on pesticide studied.
6. LC-MS-MS APPLICATIONS 6.1 Chlormequat In agriculture, the quaternary ammonium herbicides chlormequat (CQ) and mepiquat (MQ) are used as plant growth regulators either individually, as mixtures, or together with other pesticides. CQ has especially attracted the attention of enforcement laboratories and regulatory agencies in Europe, reflected by numerous publications and website notifications on violative levels of residues in fresh pears, pear juices for infants, tomatoes and cereals [106]. Before introduction of method based on LC/MS in the late 1990s, the analysis of CQ was difficult owing to its ionic character and to the absence of chromophore groups in its chemical structure. The GC method most frequently applied involved the conversion of CQ into acetylene, which was determined by flame-ionization detection [107]. However, this reaction was not specific, and an extensive clean-up was required. Recently, with wider availability of robust instruments, a number of methods based on LC/MS and LC/MS-MS for the determination of CQ [108,109] or for the determination of CQ and MQ [110,111] have been reported. The CEN Technical Committee CEN/TC 275 ‘‘Food Analysis-Horizontal Methods’’ has prepared the European Standards EN [112] 15054 and EN 15055 [113] for two methods applicable to all kinds of fruit, vegetables and cereal grains. These methods both use stable isotope internal standardization and identical extraction procedure employing MeOH–water and they do not involve any clean-up. The sample is mixed with deuterated internal standards, water and methanol and the
296
Table 4
a
Anna Sannino
Analyte MS-MS transitions established by EN 15055 method
Compound
Precursor
Firsta transition mass (m/z)
Second transition mass (m/z)
Chlormequat d4-Chlormequat Mepiquat d3-Mepiquat
M+H M+H M+H M+H
122-58 126-58 114-98 117-98
124-58 128-58 114-58 117-101
MS-MS transition used for quantitation.
homogenate is centrifuged. An aliquot is analysed by LC-MS using PI mode. The two methods differ in specifying the use of LC/MS or LC-MS-MS for the determination, the amount of internal standard used and their expected LOD. Alder and Startin [114] reported the results of an interlaboratory validation study of these methods conducted on behalf of CEN TC 275/WG 4 by the German Federal Institute for Health Protection of Consumer and Veterinary Medicine (now Federal Institute for Risk Assessment), Berlin. The method has been collaboratively studied on mushrooms, pears, wheat flour, fruit puree and on infant formula. For LC-MS the instrument operated in SIM mode for the ions 122 and 124 (CQ), 126 and 128 (d4-CQ), 114 (MQ) and 117 (d3-MQ). For LC-MS-MS the instrument operated in multiple reaction monitoring. MRM transitions established by the CEN LC/MS-MS method are listed in Table 4. Figure 8 shows LC-MS-MS chromatograms of a pear puree extract and the same sample fortified with CQ at 10 mg/kg obtained with a QqQ instrument. Under the isocratic conditions described in EN 15055 method the analyte elutes at approximately 6 min. The additional selectivity of LC-MS-MS allows measurement at 10 mg/kg or below, as required for infant foods, whereas LC-MS is satisfactory for higher levels.
6.2 Pesticides of new generation Recently, several applications have described the use of MS-MS with both QqQ and IT analysers in multiresidue analysis of pesticide [97,115–117]. Most of the methods achieve satisfactory results even without making use of clean-up treatments. Sannino et al. [117] described a sensitive and selective method for the determination of 24 new pesticide residues (azoxystrobin, trifloxystrobin, kresoxim-methyl, fenazaquin, indoxacarb, fenothiocarb, furathiocarb, benfuracarb, imidachloprid, dimethomorph, fenpyroximate, hexythiazox, tebufenpyrad, tebufenozide, defeconazole, fenbuconazole, flusilazole, paclobutrazol, tebuconazole, tetraconazole, bromuconazole, etofenprox, fenhexamid, pyridaben) in apple puree, concentrated lemon juice and tomato puree. Samples were extracted with acetone and partitioned with cyclohexane/ ethyl acetate (50 + 50, v/v). This method requires only small volumes of solvent per sample, short analysis time and does not use any chlorinated solvents.
Pesticide Residues
297
650 600 550 (a)
500 450
Intensity,
400 350 300 250 122 → 58 200 150 100 50 0
1 1
0
4.7 4.8 4.9 5.0 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 6.0 6.1 6.2 6.3 6.4 6.5 6.6 min
650
5.6
600 550
(b)
500 450
Intensity,
400 350 300 250 200 150 100 50 0
4.7 4.8 4.9 5.0 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 6.0 6.1 6.2 6.3 6.4 6.5 6.6 min
Figure 8 LC/MS-MS chromatograms (m/z 122-58) of pear puree: (a) unfortified and (b) fortified sample with CQ at 10 mg/kg. Injection volume, 20 mL of a 0.333g/mL sample; column Shodex Rspack De 413, 150 4.6 mm; mobile phase: Methanol/water 1 + 1 (v/v) with 50 mmol ammonium acetate and acetic acid 2.5% and flow rate: 0.3 mL/min.
8.13 9.11 7.91 8.60 7.23 9.96 9.62 8.17 7.40 8.26 9.32 8.08 9.11 9.41 8.64 3.04 9.02 6.97 9.58 7.57 8.21 8.72 7.87 8.94
Azoxystrobin Benfuracarb Bromuconazole Difeconazole Dimethomorph Etofenprox Fenazaquin Fenbuconazole Fenhexamide Fenothiocarb Fenpyroximate Flusilazole Furathiocarb Hexythiazox Kresoxim-methyl Imidachloprid Indoxacarb Paclobutrazol Pyridaben Tebuconazole Tebufenozide Tebufenpyrad Tetraconazole Trifloxystrobin
404-372 411-195 378-159 406-251 388-301 359-183 307-161 337-125 302-97 254-72 422-366 316-247 383-195 353-228 314-206 256-209 528-249 294-70 365-309 308-70 297-133 334-117 372-159 409-186
Firsta transition Mass (m/z)
19 13 25 49 26 52 22 27 64 20 50 21 20 15 10 26 15 30 40 27 16 60 27 15
20 32 40 34 26 31 21 40 34 30 23 26 25 23 10 19 23 41 18 47 20 55 37 24
DPb (V) CEc (V)
Source: Reproduced from Ref. [117] with permission from Elsevier, Copyright 2004. a MS-MS transition used for quantitation. b Declustering potential (similar to the cone voltage of other manufacturers). c Collision energy.
Retention time (min)
404-344 411-252 376-159 408-253 390-303 394-177 307-147 337-70 304-97 254-160 422-135 316-165 383-252 353-168 314-116 256-175 528-293 296-70 367-311 310-70 353-139 334-145 374-161 409-206
Second transition mass (m/z)
Analyte MS-MS transitions, retention time and instrument conditions
Compound
Table 5
19 13 25 47 32 9 22 27 62 20 50 21 20 15 10 26 15 35 40 27 46 60 27 15
DPb (V)
30 18 40 32 27 20 26 44 33 13 46 37 23 35 19 22 20 40 18 49 24 45 45 20
CEc (V)
19 13 25
22
10 15
27
307-57
314-267 528-218
308-151
DPb (V)
404-329 411-190 380-161
Third transition mass (m/z)
35
31
9
45
40 17 40
CEc (V)
298 Anna Sannino
Intensity, cps
Intensity, cps
10
9.62
10
0
200
400
5 Time, min
0
500
1000
1500
2000
3000
3500
4000
4975 4500
0
6
8 Time, min
Dimethomorph 5µ/Kg 388 → 301
10
0.00
2.00e4
4.00e4
6.00e4
8.00e4
1.00e5
1.20e5
0
1000
2000
1000
3000
5000
6000
7000
8000
9000
0.0
2000
10
10
2000.0
4000.0
6000.0
4000
8 Time, min
Indoxacarb 4µ/Kg 528 → 249
7.23
8.77
9.02
8 Time, min
→ 206
8000.0
1.0e4
1.3e4 1.2e4
3000
6
6
314
10µ/Kg
Kresoxim-methyl
8.64
4000
5000
2500
256 → 209
Imidachloprid 10µ/Kg
8 Time, min
57
6000
7000
600
3.04
6
307
→
Fenazaquin 4µ/Kg
8700 8000
800
1000
1200
1400
1550
0.0
1.0e4
2.0e4
3.0e4
4.0e4
5.0e4
6.6e4 6.0e4
0
0.0
8 Time, min
500
2000.0
6
1000
1500
2000
2500
373
3000
→
404
3500
Azoxystrobin 2µ/Kg
8.13
4000.0
6000.0
8000.0
1.0e4
1.2e4
1.4e4
8.25
8 Time, min
→ 186
9.11
8 Time, min
6
8 Time, min
Benfuracarb 10µ/Kg 411 → 195
6
Fenothiocarb 4µ/Kg 25 4 → 72
6
4 09
Trifloxystrobin 2µ/Kg
8.94
10
10
10
Figure 9 Typical MRM profiles of a fortified apple puree at 2–10 mg/kg. Injection volume, 40 mL of 1 g/mL sample. HPLC conditions: A 4-mm Synergy Polar-RP column (150 2.0 mm) (Phenomenex, Aschaffenburg, Germany) was operated at a flow rate of 0.250 mL/min. The following elution program was used: at the start 60% solvent A (0.1% aqueous formic acid) and 40% solvent B (acetonitrile); after 0.5 min the percentage of solvent B was linearly increased to 95% in 4.0 min; kept constant for 5.5 min; ramped to original composition in 1 min and then equilibrated for 9.0 min. MS analyser: QqQ operating in MRM mode (Table 5). Reproduced from Ref. [117] with permission from Elsevier Science, Copyright 2004.
Intensity, cps
1.6e4
Pesticide Residues
299
Intensity, cps
Figure 9 (Continued)
Intensity, cps
6
10
10
0
500
1000
1500
2000
2500
Time, min
8
Etofenprox 10µ/Kg 359 → 183
9. 96
6
8
10
10 Time, min
0 8
0
1000
1500
2000
2500
3000
3450
500
6
Fenhexamide 10µ/Kg 302 → 97
7.40
Time, min
500
1000
1500
2000
2500
3000
3300
0.0
1000
1500
2000
2500
3000
3500
4000
4500
0
8 Time, min
Tetraconazole 4µ/Kg 372 → 159
7.87
0.0
5000.0
1.0e4
1.5e4
2.0e4
500
6
Tebuconazole 4µ/Kg 308 → 70
7.57
2000.0
4000.0
6000.0
8000.0
1.0e4
1.2e4
1.4e4
1.6e4
8
9.58
Time, min
8
Pyridaben 8µ/Kg 365 → 309
Time, min
10
10
Bromuconazole 4µ/Kg 378 → 159
7.91
300 Anna Sannino
Pesticide Residues
301
Extracts were analysed by LC-MS-MS without any further clean-up steps. Suitable transitions from precursor to product ions (MRM transitions) were identified for each compound. For confirmation of results a second and, for azoxystrobin, kresoxim-methyl, fenazaquin, benfuracarb, tebuconazole, bromuconazole, a third fragmentation of the selected parent ions can be used. The simultaneous measurement of 55 MRM transitions was carried out (Table 5). Thus, 24 pesticides can be screened in a single injection using only one retention time window (period). Typical chromatograms of individual MRM transitions for 24 pesticides in apple puree extract at concentrations ranging from 2 to 10 mg/kg are shown in Figure 9. Although interferences are not visible in the LC-MS-MS chromatograms, co-eluting matrix components could inhibit or enhance the analyte signal. This phenomenon is referred to as matrix effects (13). The best way to compensate for matrix effects is the use of isotope internal standards, however for most pesticides these compounds are not available. In this study, calibration was performed by external matrix matched standards to eliminate the matrix effect and to obtain a more realistic determination.
7. CONCLUSIONS AND FUTURE TRENDS The area of pesticide analysis is complicated by the large number of possible residues, which are classified in terms of functionality as well as being classified in according to their chemical nature. Nevertheless, the analysis of pesticides in food samples is made even more complex by the fact that the concentration of matrix components is often greater than the concentration of the target pesticide. The MRMs are preferred due to the importance of checking a large number of pesticides in one single analysis. Simplifying complicated and time-consuming sample pre-treatment is still a pending subject. Traditional solvent extraction remains the most widely used method for sample preparation with a tendency to suppress the clean-up procedures of this isolation step. However, with the current trends to reduce solvent usage and manual labour, several alternative extraction approaches have been introduced, for example MSPD, SPME and SBSE. GC coupled with EI-MS and LC with MS-MS using ESI are the most important detection techniques in pesticide residue analysis today. Alder et al. [118] compared the applicability and sensitivity of MS in combination with GC and LC for the determination of 500 high-priority pesticides. This chapter summarizes all typical precursor and product ions appropriate for LC-ESI-MS-MS determination and the sensitivity obtained. The applicability of GC-MS with EI-MS was evaluated for the list of pesticides. Only for one substance class, the OC pesticides, GC-MS achieves better performance. The development, optimization and implementation of recent approaches in LC-MS-MS, including linear traps, and hybrid instruments are expected to improve performance even more in the near future. During the past 6 years, the number of applications of LC-MS-MS to control pesticide residues rapidly increased.
302
Anna Sannino
Moreover, important advances were made in the development and application of GC combined with QqQ mass spectrometer. The detection of pesticides by GC-tandem quadrupole mass spectrometry is now supplanting current GC-MS detection with a single quadrupole, as demonstrated by the many examples of application of GC-MS-MS to the analysis of pesticide residues that can be found in recent literature.
REFERENCES 1 FAO, International Code of Conduct on the Distribution and use of Pesticide, Food and Agriculture Organization of the United Nations, Rome, 2003, p. 6. 2 D. Hamilton and S. Crossley, Introduction. In: D. Hamilton and S. Crossley (Eds.), Pesticide Residues in Food and Drinking Water, Wiley, Chichester, 2004, pp. 1–25. 3 C. Tomlin, The Pesticide Manual, 13th ed., British Crop Protection Council, Surrey, UK & the Royal Society of Chemistry, Cambridge, UK, 2003. 4 Commission Directive 1986/362/ EC, Off. J. Eur. Commun., L221 (1986) 37 and following updates. 5 Commission Directive 1990/642/ EC, Off. J. Eur. Commun., L350 (1990) 71 Union, Brussels, and following updates. 6 Commission Directive 1999/39/ EC, Off. J. Eur. Commun., L124 (1999) 8. 7 Commission Directive 1999/50/ EC, Off. J. Eur. Commun., L139 (1999) 29. 8 Commission Directive 2003/13/ EC, Off. J. Eur. Commun., L41 (2003) 33. 9 Commission Directive 2003/14/ EC, Off. J. Eur. Commun., L41 (2003) 37. 10 H. Steinwandter, Universal extraction and cleanup methods. In: J. Sherma (Ed.), Analytical Methods for Pesticides and Plant Growth Regulators, Academic Press Inc., Harcourt Brace Jovanovich, Publisher, Weinheim, Germany, 1989, pp. 35–73. 11 P.A. Mills, J.H. Onley and R.A. Gaither, J. Assoc. Off. Anal. Chem., 46 (1963) 186. 12 G. Becker, Deut. Lebens. Runds., 67 (1971) 125. 13 M. Luke, J.E. Froberg and H.T. Masumoto, J. Assoc. Off. Anal. Chem., 58 (1975) 1020. 14 W. Specht and M. Tilks, Anal. Chem., 301 (1980) 300. 15 DFG Ru¨ckstandsanalytik von Pflanzenschutzmitteln, VCH, Weinheim, Germany, DFG-S8, DFG-S19, 1982. 16 U.S. Food and Drug Administration Pesticide Analytical Manual, Vol. 1, Multiresidue Methods, 3rd ed., FDA, Washington, 1994. 17 Official Methods of Analysis, 17th ed., AOAC International, Gainthersburg, MD, 2000. 18 K. Nordenmeyer and H.P. Their, Z. Lebensm. Unters. Forsch A, 208 (1999) 259. 19 M. Luke, I. Cassias and S. Yee, Lab Inform. Bull. No. 4178, Office of Regulatory Affairs, U.S. Food and Drug Administration, Rockville, MD, 1999. 20 F.J Schenck, P. Callery, P.M. Gannett, J.R. Daft and S.J. Lehotay, J. AOAC Int., 85 (2002) 1177. 21 R.S. Sheridan and J.R. Meola, J. AOAC Int., 82 (1999) 982. 22 S.J. Lehotay, J. AOAC Int., 83 (2000) 680. 23 S.J. Lehotay, A.R. Lightfield, J.A. Harman-Fetcho and D.A. Donoghue, J. Agric. Food Chem., 49 (2001) 4589. 24 J. Fillion, F. Sauve and J. Selwyn, J. AOAC Int., 83 (2000) 698. 25 M. Anastassiades, S.J. Lehotay, D. Sˇtajnbaher and F.J. Schenck, J. AOAC Int., 86 (2003) 412. 26 S.J. Lehotay, A. De Kok, M. Hiemstra and P. van Bodegraven, J. AOAC Int., 88 (2005) 595. 27 S.J. Lehotay, K. Masˇtovska and A.R. Lightfield, J. AOAC Int., 88 (2005) 615. 28 A.R. Fernandez-Alba, A. Valverde, A. Aguera and M. Contreras, J. Chromatogr., 686 (1993) 263. 29 D.M. Holsteg, D.I. Scharberg, E.R. Tor, L.C. Hart and F.D. Galey, J. AOAC Int., 77 (1994) 1263. 30 S. Bogialli, R. Curini, A. Di Corcia, M. Nazzari and D. Tamburro, J. Agric. Food Chem., 52 (2004) 665. 31 K. Bester, G. Bordin, A. Rodriguez, H. Schimmel, J. Pauwels and G. Van Vyncht, Fresenius J. Anal. Chem., 371 (2001) 550.
Pesticide Residues
32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52
53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73
303
C. Blasco, G. Font and Y. Pico´, J. Chromatogr. A, 1098 (2005) 37. Y. Pico´, G. Font, M.J. Ruiz and M. Fernandez, Mass Spectrom. Rev., 25 (2006) 917. A. Sannino, M. Bandini and L. Bolzoni, J. AOAC Int., 86 (2003) 101. J. Zrostlikova, J. Hajsˇlova, T. Kovalczuk, R. Sˇteˇpan and J. Poustka, J. AOAC Int., 86 (2003) 612. A. Hergegova, M. Do¨mo¨to¨rova and E. Matisova, J. Chromatogr. A, 1153 (2007) 54. S.A. Barker, A.R. Long. and C.R., Short, J. Chromatogr., 475 (1989) 353. B. Albero, C. Sanchez-Brunete and J.L. Tadeo, J. Agric. Food Chem., 51 (2003) 6915. D. Perret, A. Gentili, S. Marchese, M. Sergi and G.D. Ascenzo, J. AOAC Int., 85 (2002) 724. C. Ferrer, M.J. Gomez, J.F. Garcia–Reyes, E. M Thurman and A.R. Fernandez-Alba, J. Chromatogr. A, 1069 (2005) 183. S. Vichi, A.I. Castellote, L. Pizzale, L.S. Conte, S. Bruxaderas and E. Lo`pez–Tamames, J. Chromatogr. A, 983 (2003) 93. C. Blasco, G. Font, J. Man˜es and Y. Pico´, Anal. Chem., 75 (2003) 3606. C.S. Tsoutsi and T.A. Albanis, J. Environ. Anal. Chem., 84 (2004) 3. A.L. Simplicio and L.V. Boas, J. Chromatogr. A, 833 (1999) 35. A. Juan-Garcia, J. Man˜es, G. Font and Y. Pico´, J. Chromatogr. A, 1050 (2004) 119. P. Sandra, B. Tienpont and F. David, J. Chromatogr. A, 1000 (2003) 299. C. Bicchi, C. Cordero, P. Rubiolo and P. Sandra, Eur. Food Res. Technol., 216 (2003) 449. D.L. Stalling, R.C. Tindle and J.L. Johnson, J. AOAC Int., 55 (1972) 32. J.A. Ault, M.C. Schofield, L.D. Johnson and R.H. Waltz, J. Agric. Food Chem., 27 (1979) 825. D. Chaput, J. Assoc. Off. Anal. Chem., 71 (1988) 542. Official Methods of Analysis, Vol. 1, 16th ed., AOAC International, Arlington, VA, 1995, p. 1, Chapter 10. W. Specht, Organochlorine, organophosphorus, nitrogen-containing and other pesticides. In: H.P. Thier and H. Zeumer (Eds.), Deutsche Forschungsgemeinschaft, Manual of Pesticides Residue Analysis, Vol. 1, Cleanup Method 6 and Method 19, VCH, Weinheim, 1987, pp. 75–78 and 383–400. H. Steinwandter, Fresenius J. Anal. Chem., 354 (1996) 259. A. Sannino, P.M. Ambriani, M. Bandini and L. Bolzoni, J. AOAC Int., 79 (1996) 1434. A. Sannino, P.M. Ambriani, M. Bandini and L. Bolzoni, J. AOAC Int., 78 (1995) 1502. G.F. Pang, Y.Z. Cao, J.J. Zhang, C.L. Fan, Y.M. Liu, X.M. Li, G.Q. Jia, Z.Y. Li, Y.Q. Shi, Y.P. Wu and T.T. Guo, J. Chromatogr. A, 1125 (2006) 1. L. Liu, Y. Hashi, Y. Qin, H. Zhou and J. Lin, J. Chromatogr. B, 845 (2007) 61. M. Careri, F. Bianchi and C. Corradini, J. Chromatogr. A, 970 (2002) 3. S.J. Lehotay and K.I. Eller, J. AOAC Int., 78 (1995) 821. A. Sannino, M. Bandini and L. Bolzoni, J. AOAC Int., 82 (1999) 1229. S. Schachterle and C. Feigel, J. Chromatogr. A, 754 (1996) 411. A. Aguera, M. Contreras, J. Crespo and A.R. Fernandez-Alba, Analyst, 127 (2002) 347. J.L. Martinez-Vidal, M.J. Gonzalez-Rodriguez, F.J. Arrebola, A. Garrido-Frenich, F.J. SanchezLopez and N. Mora-Diez, J. AOAC Int., 86 (2003) 856. C. Leandro, R.J. Fussell and B.J.J. Keely, J. Chromatogr. A, 1085 (2005) 207. A. Garrido-Frenich, R. Romero-Gonzalez, J.L. Martinez-Vidal, P. Plaza Bolan˜os, L. CuadrosRodriguez and M.A. Herrera-Abdo, J. Chromatogr. A, 1133 (2006) 315. A. Garrido-Frenich, J.L. Martinez-Vidal, A.D. Cruz Sicilia, M.J.R. Gonzalez-Rodriguez and P. Plaza Bolan˜os, Anal. Chim. Acta, 558 (2006) 42. S. Walorczyk and B. Gnusowski, J. Chromatogr. A, 1128 (2006) 236. J.L. Martinez Vidal, F.J. Arrebola Lie`banas, M.J. Gonzalez Rodriguez, A. Garrido Frenich and J.L. Fernandez Moreno, Rapid Commun. Mass Spectrom., 20 (2006) 365. P. Plaza Bolan˜os, J.L. Fernandez Moreno, D.D. Shtereve, A. Garrido Frenich and J.L. Martinez Vidal, Rapid Commun. Mass Spectrom., 21 (2007) 2282. T. Cajka and J. Hajslova, J. Chromatogr. A, 1058 (2004) 251. K. Patel, R.J. Fussell, D.M. Goodall and B.J. Keelye, Food Addit. Contam., 21(7) (2004) 658. A. De Koning, G. Lach, M. Linkerhagner, R. Loscher, P.H. Tablack and U.A. Brinkman, J. Chromatogr. A, 1008 (2003) 247. A. D’Amato, I. Semeraro and C. Bicchi, J. AOAC Int., 76 (1993) 657.
304
74 75 76 77 78 79 80 81 82
83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107
108 109 110 111
Anna Sannino
A. Lagana`, A. Marino, G. Fago and B.P. Martinez, Analysis, 22 (1994) 63. A. Sannino, J. AOAC Int., 81 (1998) 1048. A. Sannino, Food Chem., 52 (1995) 57. C. Bicchi, F. Belliardo, L. Cantamessa, G. Gasparini, M. Iscardi and E. Sesia, Pestic. Sci., 25 (1989) 355. D. Gilvydis and S.M. Walters, J. AOAC Int., 73 (1990) 753. Report of the thirty-third session of the Codex committee on pesticide residues. In: Proceeding of the Joint FAO/WHO Meeting on Pesticide Residues (JMPR), The Hague, 2001. E.V. Minelli, A. Angioni, M. Melis, F.M. Pirisi and P. Cabras, J. AOAC Int., 80 (1997) 1315. U.S. Food and Drug Administration Pesticide Analytical Manual, Vol. 1, Multiresidue Methods, 3rd ed., FDA, Washington, 1994. EN 14185-2, Non fatty foods: Determination of N-methylcarbamate residues — Part 2: HPLCmethod with clean-up on a diatomaceous earth column, European Committee for Standardization, Brussels, Belgium, 2006. H.A. Moye, S.J. Scherer and P.A. St. John, Anal. Lett., 10 (1977) 1049. R.T. Krause, J. Chromatogr. Sci., 16 (1978) 281. A. Sannino, M. Bandini and L. Bolzoni, Industria Conserve, 67 (1992) 34. A. De Kok and M. Hiemstra, J. AOAC Int., 75 (1992) 1063. M.S. Ali, J. AOAC Int., 72 (1989) 586. M.V. Bassett, S.C. Wendelken, B.V. Pepich and D.J. Munch, J. Chromatogr. Sci., 41 (2003) 100. L.V. Podhorniak, F.J. Schenck, A. Krynitsky and F. Griffith, J. AOAC Int., 87 (2004) 1237. A.R. Fernandez-Alba, Chromatographic Mass Spectrometry Food Analysis for Trace Determination of Pesticide Residues, Vol. XLIII, Elsevier, Amsterdam, 2005, p. 403. Y. Pico´, C. Blasco and G. Font, Mass Spectrom. Rev., 23 (2004) 45. J. Klein and L. Alder, J. AOAC Int., 86 (2003) 1015. K. Granby, J. Hinge Andersen and H.B. Chrinstensen, Anal. Chim. Acta, 520 (2004) 165. A. Garrido Frenich, J.L. Martinez Vidal, T. Lopez, S. Corte´s Aguado and J. Martinez Salvador, J. Chromatogr. A, 1048 (2004) 199. D. Ortelli, P. Edde and C. Corvi, Anal. Chim. Acta, 520 (2004) 33. A. Sannino and M. Bandini, Rapid Commun. Mass Spectrom., 19 (2005) 2729. A. Sannino and M. Bandini, J. AOAC Int., 88 (2005) 1822. F. Hernandez, O.J. Pozo, J.V. Rancho, L. Bijlsma, M. Barreda and E. Pitarch, J. Chromatogr. A, 1109 (2006) 242. M.D. Gil-Garcia, D. Barranco-Martinez, M. Martinez-Galera and P. Parilla-Vasquez, Rapid Commun. Mass Spectrom., 20 (2006) 2395. C.C. Leandro, P. Hancock, R.J. Fussel and B.J. Keely, J. Chromatogr. A, 1144 (2007) 161. I.R. Pizzutti, A. de Kok, R. Zanella, M.B. Adaime, M. Hiemstra, C. Wickert and O.D. Prestes, J. Chromatogr. A, 1142 (2007) 123, 169. C. Soler, J. Manes and Y. Pico`, J. Chromatogr. A, 1067 (2005) 115. E.M. Thurman, I. Ferrer, J.A. Zweigenbaum, J.F. Garcia-Reyes, M. Woodman and A. Rodriguez Fernandez-Alba, J. Chromatogr. A, 1082 (2005) 71. J.F. Garcia-Reyes, C. Ferrer, E.M. Thurman, A.R. Fernandez-Alba and I. Ferrer, J. Agric. Food Chem., 54 (2006) 6493. B. Gilbert- Lopez, J.F. Garcia- Reyes, P. Ortega Barrales, A. Molina-Diaz and A.R. Fernandez-Alba, Rapid Commun. Mass Spectrom., 21 (2007) 2059. S. Riediker, H. Obrist, N. Varga and R.H. Stadler, J. Chromatogr. A, 966 (2002) 15. P.A. Greve and E.A. Hogendoorn, In: Analytical Methods for Pesticide Residues in Foodstuffs, Part II, General Inspectorate for Health Protection, Ministry of Health, Welfare and Sports, Amsterdam, The Netherlands, 1996. R. Castro, E. Moyano and M.T. Galceran, J. AOAC Int., 84 (2001) 1903. M. Careri, L. Elviri, A. Mangia and I. Zagnoni, Rapid Commun. Mass Spectrom., 16 (2002) 1821. R.K. Juhler and M. Vahl, J. AOAC Int., 82 (1999) 331. S. Riediker, H. Obrist, N. Varga and R.H. Stadler, J. Chromatogr. A, 996 (2002) 15.
Pesticide Residues
305
112 EN 15054, Non Fatty Foods: Determination of Chlormequat and Mepiquat — LC/MS Method, European Committee for Standardization, Brussels, Belgium, 2005. 113 EN 15055, Non Fatty Foods: Determination of Chlormequat and Mepiquat — LC/MS/MS Method, European Committee for Standardization, Brussels, Belgium, 2005. 114 L. Alder and J.R. Startin, J. AOAC Int., 88 (2005) 1762. 115 A. Sannino, Rapid Commun. Mass Spectrom., 21 (2007) 2079. 116 C. Soler, J. Manes and Y. Pico´, J. Chromatogr. A, 1048 (2004) 41. 117 A. Sannino, L. Bolzoni and M. Bandini, J. Chromatogr. A, 1036 (2004) 161. 118 L. Alder, K. Greulich, G. Kempe and B. Vieth, Mass Spectrom. Rev., 25 (2006) 838.
CHAPT ER
10 Veterinary Drug Residues Sherri B. Turnipseed and Wendy C. Andersen
Contents
1. Introduction 1.1 Antibiotics 1.2 Anthelmintics and antifungals 1.3 Tranquilizers and anti-inflammatory drugs 2. Physical and Chemical Properties Affecting Analytical Methodology 2.1 Properties of veterinary drugs 2.2 Properties of food matrices 3. Human Health Effects from Veterinary Drug Residues 3.1 Direct effects 3.2 Antibiotic resistance 4. Analytical Methods 4.1 Types of methods 4.2 Summary of analytical methods 4.3 Specific examples of recent methodology 5. Occurrence in Food 6. Future Trends 6.1 Biosensors 6.2 Multi-class methods References
307 308 312 313 313 313 314 315 315 316 317 317 319 319 328 329 329 332 332
1. INTRODUCTION The use of animal drugs in food production has been a standard practice for decades. The high density of animal populations in agricultural facilities can increase the potential for disease outbreak. This results in the need for medications to be given therapeutically to treat existing infections or prophylatically to minimize the impact of an outbreak spreading across an animal population. In addition, veterinary drugs are sometimes provided to food Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00010-X
r 2008 Elsevier B.V. All rights reserved.
307
308
Sherri B. Turnipseed and Wendy C. Andersen
animals at subtherapeutical levels to promote growth efficiency and increase feed conversion. A 1999 study indicated that 60–80% of all animals consumed in the United States had been treated at one point with an approved drug [1]. Therefore, the possibility of drug residues remaining in the edible product and the potential human health problems associated with exposure to these residues is a concern to public safety. The following is a brief description of the types of veterinary drugs that are used in food animals. The structures of many of the representative drugs discussed are shown in Figures 1–3 [2].
1.1 Antibiotics Antibiotics are commonly administered to food animals both therapeutically and subtherapeutically. Several classes of antibiotics are used in livestock veterinary medicine. Sulfonamides are derivatives of sulfanilamide, one of the first drugs discovered to treat Streptococcal infections. Sulfamethazine and sulfadimethoxide are shown as examples of this class of drugs in Figure 1. Although not technically classified as antibiotics, these drugs are bacteriostatic agents that effectively interfere with the synthesis of folic acid in susceptible organisms and are widely used in both humans and food-producing animals to prevent infectious diseases [3]. Penicillin is one example of a b-lactam antibiotic historically used in veterinary medicine. All antibiotics in this class contain a b-lactam ring [4]. Many b-lactams approved as animal drugs are based on the penicillin molecule, including ampicillin, amoxicillin and cloxacillin. Cephapirin and ceftioflur, however, contain a cephalosporin nucleus. These drugs are effective in cattle that are fighting against mastitis as well as respiratory and intestinal infections. They are also administered to swine and allowed to be used in some countries for farm-raised finfish. Aminoglycoside drugs are antibiotics effective against most gram-positive and negative organisms. They are isolated from Streptomyces or Micromonospora species and their mode of action is to interfere with bacterial protein synthesis. These drugs consist of linked amino sugar groups; examples include streptomycin, apramycin, dihydrostreptomycin, gentamicin and neomycin (Figure 1). They are administered both therapeutically and prophylatically to treat cattle, swine and poultry [5]. Aminoglycosides are not absorbed orally and so are usually administered via intramuscular injection. Residues of these drugs tend to concentrate in the kidney as they are generally excreted through the urinary tract. Tetracyclines are broad-spectrum antibiotics that inhibit protein synthesis in bacterial cell walls. They consist of a substituted 2-napthacenecarboxamide molecule. These antibiotics were originally isolated from Streptomyces. The most common tetracyclines with animal health applications are tetracycline, oxytetracycline and chlortetracycline [6]. In the U.S., these drugs have been approved for beef cattle, calves, swine, sheep, chickens and turkeys. Oxytetracycline has been specifically approved for use in dairy cattle and aquacultured catfish, salmon and lobster. This drug has not been approved by the U.S. for shrimp aquaculture, although it is believed to be used widely in shrimp production in other parts of the world.
N
H2N
HO HO
Ceftiofur
N
S
N H
NH2 CH2
O
COOH
S
CH2 O
OH
NH2 H2N O O
O
NH2
N
CH3
CH3
S
H2N
COOH
S
CH3
Neomycin
HO
H2C HO HO
O
N
H
H H
H
OCH3 O
O
N H Benzylpenicillin (Penicillin G) O
O
Figure 1 Structures of antibiotics [2].
H2N
H2N
N
N N H Sulfamethazine
S
O O
CH3
OH
O
OH O OH
H3 C
F
N
O H CH3 COOH
H3C H3CO
HO
HN
O
H3C CH3 CH3 OH N H H OH
Oxytetracycline
O
NH2
O
OH
HO
N
O
NH2
OCH3 N N H Sulfadimethoxine
S
O O
OCH3
O
O
H
O
OCH3
N
O2 N
O
HO
CH3 H O
H
2′ O
H3C
OH
N CH3
OH
CH3
O OH
H N
CH3
O
NH2
Chloramphenicol
OH
H N
CH3
Nitrofurazone
O
COOH
H3C
Monensin
H
CH3
O2N
O
O HO
CH3
CH3 OH
CH3 Erythromycin
CH3
OH H3C O
O
O Sarafloxacin
N
F
CH3
H3C
OH
H3C
Cl Cl
Veterinary Drug Residues
309
310
Sherri B. Turnipseed and Wendy C. Andersen
O
H N N
S
N H
OCH3
Fenbendazole
H
S
N N
Levamisole
H3C
N
CH3
N
CH3
CH3
Malachite Green
OC 3 OCH HO OCH3 O H3C
O
CH3
H
O
O H3C
O
CH3
H
H
CH3
O H
H3C
Ivermectin
O
O
OH
H
H R
O CH3
H OH
Figure 2 Structures of anthelmintics and antifungals [2].
Another class of antibiotics originally isolated from the Streptomyces species is the macrolides [7]. Macrolides are multi-membered lactone rings with one or more sugars attached. These drugs are most effective against gram-positive organisms and some strains of Listeria and Mycoplasma. Erythromycin (Figure 1) and tylosin are the drugs most commonly given to food-producing animals. Oleandomycin, spiramycin, sedamycin and tilmicosin are also used therapeutically to treat bovine respiratory diseases and mastitis and swine dysentery, or used as a feed additive to promote growth efficiency. Macrolides can also be added to the food and water supplies for chickens and turkeys to prevent respiratory disease and enteritis, as well as to promote growth. These drugs are also effective in treating bee colonies for brood disease. Although their chemical
Veterinary Drug Residues
311
N O
N N CH3
F
H N
S
Azaperone
N H3C
Xylazine
CH3 N
H N
CF3
COOH
Flunixin
O
N N
H3C O
Phenylbutazone
Figure 3 Structures of tranquilizers and anti-inflammatory drugs [2].
structure is quite different, the lincosamide antibiotics (lincomycin and pirlimycin) have similar antibacterial activity, clinical applications and cellular mechanisms as the macrolides. Quinolones are pyridone carboxylic acid derivatives that are effective against gram-negative bacteria. Examples of quinolone drugs include oxolinic, nalidixic and piromidic acids. Quinolones have been found to be effective as a prophylactic treatment for aquacultured species; they have also been investigated by the swine and poultry industry. Fluoroquinolones are the fluorinated subclass of the quinolones that also exhibit activity towards gram-positive bacteria [8]. Sarafloxacin, enrofloxacin, difloxacin, ciprofloxacin, norfloxacin and ofloxacin are just some examples of fluoroquinolones. As is discussed later, there are growing concerns with the use of these drugs in foods of animal origin due to the problem of increased antibiotic resistance associated with this subclass of antibiotics. Compounds that retard the development of a parasite in a host cell are known as coccidiostats. A common class of drugs used for this purpose is the ionophores, which include monensin (Figure 1), salinomycin and lasalocid [9]. Other drugs such as amprolium, clopidol, halofuginone, nicarbazin and even the tetracyclines can also be effective coccidiostats. While these drugs are most commonly given to poultry populations, monensin, lasalocid and amprolium can
312
Sherri B. Turnipseed and Wendy C. Andersen
also be administered to cattle to treat coccidiosis. The ionophores may also be used to promote growth in cattle. Another class of drugs used in veterinary medicine is the peptide antibiotics including bacitracin, colistin, virginiamycin and avoparcin. Each of these drugs are actually a mixture of peptides produced by Bacillus and Streptomyces species and may be glycosylated in some positions. They are primarily added to animal feed to enhance growth. There are concerns regarding antibiotic resistance from glycopeptides because of their structural similarity to the human drug vancomycin [10]. Other antibiotic classes that will be discussed in further detail later in the chapter include the nitrofurans and the phenicols such as chloramphenicol and florfenicol. Representative drugs from these classes of antibiotics are also included in Figure 1.
1.2 Anthelmintics and antifungals Anthelmintic (deworming) compounds control parasitic infections. Benzimidazoles are anthelmintics that contain a common 1,2-diaminobenzene nucleus; most of them also have a carbamate functional group. Albendazole and fenbendazole are common drugs in this class. These drugs protect against roundworms and flukes by inhibiting the processes necessary for parasitic mitochondrial production of ATP [11]. The use of fenbendazole (Figure 2) can also increase the rate of weight gain in growing and finishing swine. Avermectins are anthelmintics isolated from Streptomyces avermitilis. Ivermectin, doramectin and eprinomectin are avermectin compounds that may be administered to cattle to combat parasitic infections such as roundworms, lungworms and mites, among others [12]. Approvals have been granted for injectable or oral (bolus) dosage forms for some of these drugs in cattle, but it is common for these drugs to be applied topically. Ivermectin and doramectin are not approved for lactating dairy cattle. Some avermectins, including emamectin, have also been shown to be effective for the treatment of fishfin diseases such as sea lice in farm-raised salmon. Moxidectin is a synthetic milbemycin drug with similar properties to the avermectins; it has been approved for use in dairy cattle. Levamisole (Figure 2) is another anthelmintic that is used for the control of lungworms and gastrointestinal nematodes in cattle, sheep and swine. It can be administered orally, topically, via injection or in a medicated feed. Other compounds such as the tetrahydropyrimidines (i.e., pyrantel or morantel) are administered to swine for the treatment of parasites and are considered broadspectrum anthelmintics in ruminants. Organophosphates (i.e., dichlorvos and coumaphos) can also be considered anthelmintics in food animals, as well as being an effective external pest control. Triphenylmethane dyes are effective fungicides and are used illegally in food production facilities for that purpose. Malachite green, in particular, is added to the water of aquaculture ponds to treat fungal infections. An analogous compound, crystal violet, has also been reported to have been used for aquaculture as well as in chicken feed to prevent fungal growth.
Veterinary Drug Residues
313
1.3 Tranquilizers and anti-inflammatory drugs Drugs administered to food animals to treat acute conditions include tranquilizers and anti-inflammatory drugs (Figure 3). These medicines might be given to animals shortly before they are sent to slaughter, resulting in potentially high levels of residues that may persist in edible tissue. For example, tranquilizers, such as acepromazine, azaperone, chlorpromazine, propionlypromazine and xylazine, have been shown to reduce stress or aggressiveness during transport for certain species of pigs [13]. The b-blocker carazolol has also been used [14]. In the U.S., azaperone is approved for the control of aggressiveness in small pigs. In the European Union (EU), maximum residue limits have been set for carazolol and azaperon; the use of chlorpromazine in food animals is not allowed [13]. The non-steroidal anti-inflammatory drugs (NSAIDs) are effective in reducing inflammation and managing pain. Those used in veterinary medicine include flunixin, phenylbutazone, ketoprofen, aspirin, dipyrone and naproxen. In general, these drugs are only approved for pets and other non-food animals (horses). Although flunixin is approved for some therapeutic applications in cattle, there is concern that the non-approved drugs may also be administered covertly to disguise lame or sick food animals, thus allowing them to pass federal meat inspections. In 1992, a poll of nearly 1500 U.S. veterinarians revealed that over 66% of the veterinarians used dipyrone, aspirin and phenylbutazone to treat food-producing animals [15].
2. PHYSICAL AND CHEMICAL PROPERTIES AFFECTING ANALYTICAL METHODOLOGY 2.1 Properties of veterinary drugs Residue methods must be able to isolate and detect very small amounts (partper-billion or lower) of an analyte in a variety of complex matrices. The physical and chemical properties of the drug(s) of interest as well as the accompanying matrix must be evaluated to determine the optimal procedures for extraction, isolation and detection at residue levels. Specifically, molecular properties that can affect an analytical approach for any given compound include polarity, charge state, size, volatility, thermal stability and the presence or absence of a chromophore. For example, the polarity and/or charge state of an analyte can be a crucial factor in designing an effective extraction and isolation scheme. Traditionally, liquid–liquid extraction with pH adjustment (i.e., back extraction) can be used to transfer the analyte between polar and non-polar solvents, removing matrix impurities such as salts and lipids in the process. The use of reversed-phase, ion-exchange or mixed-mode solid-phase extraction (SPE) cartridges can also achieve similar results. The size of an analyte may be advantageous for sample clean-up with techniques such as gel permeation chromatography. Fedeniuk and Shand have thoroughly reviewed the relationship between the chemical properties of veterinary drugs and strategies needed for their extraction and isolation [16].
314
Sherri B. Turnipseed and Wendy C. Andersen
Further isolation of an analyte is often achieved with chromatographic separation. Volatile, thermally stable compounds can be very effectively separated from the sample matrix and other sample components using gas chromatography (GC). More polar or less thermally stable analytes can also be analysed by GC after derivatization, but are more commonly analysed by reversed-phase liquid chromatographic (LC) methods. The optimal LC stationary phase (e.g., C18, C8 and phenyl) and mobile phase components (buffer, organic modifier) are determined by properties such as the pKa of any ionizable groups and the presence of other functional moieties such as a phenyl ring. The detection of any compound must also take into account the physical and chemical properties of the molecule. For example, there are element-specific detectors for nitrogen- and sulfur-containing compounds for GC. Volatile analytes containing electrophilic functional groups are very selectively detected by GC electron capture detectors (ECD). Traditional LC systems generally utilize ultraviolet (UV), visible or fluorescence detectors that take advantage of unique chromophores present (or added via derivatization) in an analyte. Recently, liquid chromatography-mass spectrometry (LC-MS) has become a predominant methodology for the detection of veterinary drug residues. One decided advantage of MS is its ability to act as a universal detector without the need for a significant chromophore. The physical and chemical properties of the analyte, however, will determine the optimum parameters for an LC-MS method. The most common ionization techniques used are electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI). In general, ESI works well for more polar analytes that are charged in solution, while APCI will ionize, via proton exchange in the gas phase, a larger range of less-polar compounds. Recently, no-discharge APCI has been shown to be very sensitive and selective for certain veterinary drug residues, particularly those that easily form sodium adducts [17].
2.2 Properties of food matrices Because the human diet is so diverse, the type of matrices in which animal drug residues are found is quite varied. The following is a brief description of the food commodities commonly monitored for veterinary drugs. The prevalent use of veterinary drugs in cattle, swine and poultry production has resulted in the need to monitor residues in the tissues of these animals. This includes muscle meat such as various cuts of beef and pork, as well as in poultry products. Initial sample preparation for meat products involves cutting the tissue into small portions and homogenizing the pieces with a homogenizer or similar apparatus. In some cases, residues can bind to the proteins in the muscle and hydrolysis is required to release the residues. Owing to typical animal excretion pathways, it is also quite common to find residues in organ meats such as liver and kidney. These tissues typically have a high fat content, which requires additional fat removal clean-up steps. The residues may also occur as conjugates, i.e., modified with glucoronide or acetyl groups, when present in these organ
Veterinary Drug Residues
315
meats. The use and analysis of veterinary drugs in meat have been reviewed [18,19]. Dairy cows are susceptible to mastitis, a common bacterial infection that is effectively treated with antibiotics. Because milk is a commodity that is consumed in a higher proportion by children, the monitoring for residues in milk is of increased importance. Often the allowed amount of approved residues in milk is lower than that for edible bovine tissues. Sample preparation steps for veterinary drug residue methods for milk often involve defatting and protein precipitation, with acetonitrile or trichloracetic acid, prior to or concurrent with the extraction of residues. Information concerning the incidence of veterinary drug residues in other dairy products, such as dried or condensed milk or different kinds of cheeses, is fairly limited. Recent studies, however, indicate a growing interest in these types of food products [20–22]. Aquaculture, or fish farming, is a rapidly growing industry. Approximately 80% of the fish and shellfish consumed in the U.S. is imported from other countries, amounting to over 2 billion pounds of harvested seafood imported into the U.S. in 2004. A large percentage (approximately 40%) of that imported seafood is produced by aquaculture facilities [23]. The use of antibiotics and antifungal drugs in aquaculture has also increased with the expansion of the industry [24]. Fish raised in these high-density environments may experience higher stress and weakened immune systems requiring drugs to stem disease outbreaks. Methods for residue extraction and isolation in aquatic organisms are similar to those used for other animal tissues. The fat content of fish can vary significantly depending on the species and even the specific environmental growing conditions. Veterinary drug residues can also be found in foods such as eggs and honey produced as animal by-products. The drugs of concern in eggs are similar to those monitored for in poultry tissue, such as coccidiostats. Residue-extraction procedures designed for tissue can be applied to eggs, but additional steps may be required to eliminate sample components that are unique to the egg matrix [25]. Foul brood disease has become a global problem in the apiary industry and many drugs such as tetracyclines, macrolides and phenicols have been used to combat this threat to honey production. The high sugar content of honey complicates residue isolation and clean-up. Additional aqueous wash steps to eliminate the excess sugar, as well as the use of internal standards to compensate for any background interference or signal suppression, are often required [26].
3. HUMAN HEALTH EFFECTS FROM VETERINARY DRUG RESIDUES 3.1 Direct effects The public health significance of veterinary drug residues in foods of animal origin has been a topic of much discussion [1]. Potential human health problems include adverse reactions to the drug residues themselves or the possible development of resistant bacterial populations in the food supply. There are a few
316
Sherri B. Turnipseed and Wendy C. Andersen
limited reports of allergic responses caused by drug residues in foods. For example, incidences of sensitization to aminoglycosides [27] and b-lactams [28,29] have been reported. Some drugs have potentially more serious acute effects. One example is chloramphenicol, a dichloroacetamide derivative of 1-phenyl-2-amino-1-propanol (Figure 1). Chloramphenicol is prescribed for stubborn bacterial infections in both humans and companion animals. It is given cautiously, however, as there have been reports that chloramphenicol can cause aplastic anemia, a fatal bleeding disorder, in susceptible individuals [30]. It is not approved for use in food-producing animals so that unintended exposure, even at residue levels, can be avoided. Monitoring food for residues that may occur as a result of inappropriate use is important because chloramphenicol has been found to be effective in treating infections in food animals. In 2002, residues of chloramphenicol were found with a relatively high frequency in shellfish (shrimp, crab and crayfish) and honey products from certain parts of the world. Florfenicol, an analog of chloramphenicol that does not cause the same potentially dangerous side effects, has been approved for the treatment of bovine respiratory disease and for the control of enteric septicemia in farmed fish. Residues of the nonsteroidal anti-inflammatory drug phenylbutazone (Figure 3) may also be a human health concern as this drug has been shown to induce tumors in some species and exposure to this drug has also been reported to cause aplastic anemia and gastrointestinal bleeding in susceptible people [31]. Other drugs are of concern due to possible carcinogenicity. One example is the nitrofuran compounds, which have been used as antibiotics in the poultry industry as well as for the treatment of cattle and pigs. The structure of nitrofurazone is shown in Figure 1. Residues of these drugs also have been found in farm-raised shrimp and honey. Some data suggest that nitrofurans may be carcinogenic [32]; therefore, these drugs are not approved for use in any food animal. Another example is malachite green, a triphenylmethane dye used to control fungi in aquaculture ponds (Figure 2). Malachite green undergoes a metabolic reduction to the leuco form in fish tissue. Leucomalachite green is lipophilic and can remain in fatty tissue for extended periods of time. Studies have shown that these compounds may be mutagenic and teratogenic [33].
3.2 Antibiotic resistance One of the main issues associated with the use of antibiotics in food animals is the concern of developing antibiotic resistance. Animals fed with subtherapeutic levels of antibiotics may harbor bacterial populations that have evolved to be immune to these drugs. Humans may be exposed to these resistant bacterial populations during the preparation or consumption of food. There is general support for the fact that the use of these drugs can cause resistant bacteria to develop in animals and contaminate the resulting meat products [34–37]. There is evidence that this may translate into increased resistance to these drugs in the human population [37], although this remains an area of debate [34]. Many of these resistant organisms are non-pathogenic and do not cause infection when
Veterinary Drug Residues
317
ingested by humans. The appearance of resistance among pathogenic organisms, such as Salmonella DT-104 and Campylobacter, is of more concern [38–40]. For example, there appears to be a correlation between the use of fluoroquinolone antibiotics in chickens and an increase in resistant Campylobacter infections in humans. As a result, the use of fluoroquinolones, such as enrofloxacin and sarafloxacin, for the treatment of poultry populations is no longer allowed in the U.S. The link between enterococci resistance to glycopeptides and their use in animal feeds has also been investigated [10,37,41]. In the late 1990s, the National Research Council convened a group to evaluate the benefits and risks of using drugs in the food animal industry [1]. This group identified antibiotic resistance as the most serious risk associated with the continued use of drugs in food animals. They recommended that the animal health, medicine, consumer advocate and academic communities work together with the various government agencies to formulate integrated research plans and policy development to address this issue. The group recommended continued reevaluation of the animal drug approval process to expand the number of drugs that are available. The investigation of possible alternatives to the use of drugs in food animals, such as reducing overall animal population density, was also discussed. With the intent of mitigating antibiotic resistance from the treatment of food animals, the U.S. Food and Drugs Administration (FDA) recently posted guidance that outlines how a sponsor of a new animal drug application should evaluate their product for potential effects on non-target bacteria. This FDA guidance suggests that the drug sponsor provide information such as known resistance mechanisms and genetics, occurrence and rate of transfer of resistance determinants and possible resistance selection pressure. These factors, along with the knowledge concerning how the drug, or drug class, is used in human medicine, will be considered as part of the approval process [42].
4. ANALYTICAL METHODS Because of the potential health risk from exposure to some animal drugs and the low levels at which they are found in edible products, monitoring the food supply for these residues is an important analytical challenge. Tolerances or maximum residue levels are established for drugs that are allowed for use in food animals. For these drugs, analytical methods need to be able to accurately determine if a residue is present above these set limits. For some compounds (e.g., chloramphenicol, nitrofurans and malachite green) the health concerns are such that no amount of residue is allowed. In these cases, analytical methods need to be as sensitive and selective as possible to monitor for any residue that might be present.
4.1 Types of methods Several broad types of analytical methods can be described; these include screening, determinative and confirmatory procedures. Screening methods are
318
Sherri B. Turnipseed and Wendy C. Andersen
designed to be rapid, easy to use tests that will give a positive or negative response for a drug at a given concentration level in a matrix. Historically, microbial inhibition tests (MITs) have been used to screen large numbers of samples for antibiotics. All MITs are based on the inhibition of bacterial growth by antibacterial residues present in a biological fluid that results in zones of inhibition on assay plates. MITs are relatively simple to perform and can detect many classes of antibacterial compounds. Selective sensitivity for specific classes of antibacterials can be obtained by changing the culture medium, indicator bacteria or pH. Although these tests are still widely used today, they often lack the specificity and sensitivity required for residue detection at the required levels, may be affected by non-specific inhibitors, do not detect microbiologically inactive metabolites and often have a 20–24 h incubation time. In addition to MITs, new rapid test kits are being used to screen samples for specific drugs. A database of available antibiotic and veterinary drug residue test kits is maintained by the AOAC International [43]. The information integrated in the database includes the analyte, the manufacturer, the kit name, primary matrices and whether or not the kit has undergone performance testing (validation) by the AOAC. Several types of kits are listed, including bacterial receptor cell assay, enzyme-linked immunoassay (ELISA) and modified rapid MITs. Alternative screening methods for veterinary drug residues have also recently been reviewed [44]. Recent advances in analytical technology have led to other types of rapid tests, including biosensors and multi-class MS methods, which will be discussed later in the chapter. Determinative methods are designed to separate, quantify and perhaps provide some qualitative information on the analyte of interest. For many of the drugs used in animal husbandry, the determinative method of choice is LC with UV detection using a variable wavelength or diode array detection system. LC using fluorescence, chemiluminescence, or post-column reaction detectors are also available and have been successfully used to determine drug residues in animal tissue. Volatile compounds can also be measured by GC with flame ionization, ECD or element-specific detectors. The increased availability and reliability of GC-MS and especially LC-MS instruments has led to an increased number of quantitative residue methods that use these technologies. Certain considerations for issues such as matrix effects and variable ionization must be taken into account when developing determinative methods with MS detection. Matrix-based standards may be needed; deuterated internal standards are commonly used and are highly recommended. Quantitative methods must be validated prior to widespread implementation for accuracy, precision, limits of detection and quantification, linearity and ruggedness. Several guidelines have been published outlining the rigorous validation procedures [45–47]. In addition to determining how much of a drug residue is present, confirmation of identity is also required for a complete analytical regulatory package. MS is ideally suited for this qualitative analysis due to its inherent selectivity and sensitivity. Certain criteria, in terms of the number and quality of ions monitored for any given compound, need to be met to definitively determine if a residue has been positively identified. These criteria have been
Veterinary Drug Residues
319
discussed [48–50] and guidelines have been issued by several regulatory bodies [45,51]. MS methods are also advantageous in that it is possible to design a procedure that can simultaneously screen, quantify and confirm multiple drug residues in one sample analysis.
4.2 Summary of analytical methods There have been several other general review articles or texts recently published for the analysis of veterinary drug residues in food of animal origin [18,19,44,52–59]. Table 1 provides an updated list of representative veterinary drug residue methods categorized by drug class. This table is certainly not exhaustive and, in general, only methods published since 2000 are included. This is done primarily for the sake of brevity and is not meant to diminish the importance of earlier-published methods. In fact, many of the more recent methods are based on work done previously and the interested reader should be able to refer to the citations within the given references for a complete history of these analyses. In addition, review articles specific to each class of drugs are listed in Table 1 and should be of help in finding a more complete list of relevant methods.
4.3 Specific examples of recent methodology In the next section, a few specific important examples are examined in more detail. These include methods for the analysis of sulfonamides in milk and dairy products, chloramphenicol in shellfish, nitrofurans in various foods and triphenylmethane dyes in farmed fish and shrimp.
4.3.1 Sulfonamides in dairy products Sulfonamide residues in dairy products have been a regulatory issue for a long time. These drugs effectively treat bovine mastitis and can then be transferred into the cow’s milk. While some of these drugs are approved for such use, appropriate withdrawal times need to be observed to prevent the occurrence of residues in the milk and other dairy products. Several reviews for the analysis of sulfonamide residues in food have been published [3,73]. Many innovations in analytical chemistry have been applied to sulfonamide residue methods. The detection of these drugs is fairly straightforward since the compounds have a strong chromophore of around 270 nm. The primary amine group on these compounds can also be derivatized with fluorescent groups to provide even greater sensitivity and selectivity for LC detection. There have been several examples utilizing unique extraction and isolation techniques for sulfonamide residues in food. Supercritical fluid (CO2) along with in-line adsorption on alumina has been used for the extraction of sulfonamides from chicken tissue [184]. A hot-water matrix solid-phase dispersion method has also been used to extract these drugs from milk and eggs [66]. Roybal et al. illustrated the use of size-exclusion chromatography for the isolation of sulfonamides from shrimp [68]. Van Rhijn et al. isolated these drugs from small quantities of milk after a simple clean-up using only ultrafiltration with molecular weight cutoff
Broad-spectrum Streptomycin, antibiotics, growth gentamicin, efficiency neomycin
For gram-positive organisms and strains of Listeria and Mycoplasma, growth efficiency
Aminoglycosides
Macrolides
Erythromycin, tylosin, oleandomycin, spiramycin, tilmicosin
Milk, bovine, swine and fish tissue, eggs, honey
Milk, bovine, poultry and swine tissue (kidney)
Milk, bovine, poultry and swine tissue, shrimp, fish, eggs, honey
Enteritis, pneumonia, Tetracycline, anaplasmosis, oxytetracycline, growth efficiency chlortetracycline, doxycycline
Poor chromophore, may need ion pair reagents for LC Weak LC-UV, LC-FLD chromophores after derivatization, LC-MS
LC-FLD w/ derivatization; GC-ECD, LC-MS
Chelating LC or ion agents used chromatography in extraction with UV at 270/ and LC mobile 350 nm; LC-FLD of phase metal complexes, LC-MS
May use tungstic or trichloroacetic acid in extraction
Tetracyclines
LC-UV penicillins: 210–230 nm, cephalsosporins: 260–295 nm, LC-MS
Milk, bovine, swine and fish tissue
Colibacillosis, bacterial enteritis, salmonellosis, mastitis
b-Lactams
Penicillin, ampicillin, amoxicillin, cloxacillin, cephapirin, ceftioflur
LC with UV Multi-residue methods (270 nm), liquid available chromatographyfluorimetric detector (LC-FLD) after derivatization, LC-MS
Milk, bovine, swine and poultry tissue, fish, eggs, shrimp, honey
Sulfamethazine, Pneumonia, sulfadimethoxine, other respiratory sulfamerazine, diseases, mastitis, diphtheria, diarrhea sulfathiazole
Sulfonamides
Comments
Detection
Examples of compounds
Typical matrices
Function (used to treat)
Drug class
Table 1 Selected veterinary drug residue methods
[102–109]
[94–99] Reviews: [5,100,101]
[84–92] Reviews: [6,93]
[74–83] Review: [4]
[21,60–72] Review: [73]
References
320 Sherri B. Turnipseed and Wendy C. Andersen
Broad spectrum effective against gram positive, fluoroquinolones are effective for gram-negative species
Infections, bovine respiratory disease
Parasites, growth efficiency
Broad spectrum antibiotics
Growth efficiency
Quinolones
Phenicols
Ionophores and other coccidiostats
Nitrofurans
Peptides
Bacitracin, avoparcin, virginiamycin, colistin
Furazolidone, furaltadone, nitrofurazone, nitrofurantion
Monensin, lasalocid, salinomycin, halofuginone,
Chloramphenicol, florfenicol, thiamphenicol
Oxolinic acid, nalidixic acid, sarafloxacin, enrofloxacin, ciprofloxacin, flumequine
Bovine, swine and poultry tissue, milk,
Poultry and swine tissue, shrimp, honey
Bovine and poultry tissue, eggs
Milk, bovine, poultry, swine and fish tissue, shrimp, eggs
Milk, bovine, poultry, swine and fish tissue, eggs [110–120] Reviews: [8,100]
Ionophores form sodium adducts that are detected by LC-MS
[9,104,133–137]
No tolerance or [25,26,115, maximum 121–132] residue limit (MRL) for chloramphenicol residues
Concerns regarding antibiotic resistance to these drugs
LC-MS, LC-UV, LC with electrochemical detection
Concerns regarding antibiotic resistance to these drugs
[148–151]
LC-MS after Need to hydrolyze [32,138–147] derivatization with bound nitrobenzaldehyde metabolites, no tolerance
LC with visible or fluorescence detection after derivatization, LC-MS
LC-UV, GC-ECD or GC-MS after derivatization, negative ion LC-MS
LC-FLD and/or UV detection, LC-MS
Veterinary Drug Residues
321
Acepromazine, azaperone, chlorpromazine, propionlypromazine, xylazine, carazolol Flunixin, phenylbutazone, ketoprofen
Fungus and parasite infections
Reduce stress and aggression transport aid preanesthetic
Reduce inflammation
Triphenylmethane dyes
Tranquilizers
Antiinflammatory
Malachite green, crystal violet, brilliant green
Ivermectin, eprinomectin, doramectin, moxidectin
Anthelmintics
Avermectins and milbemycins
Milk, bovine tissue (kidney)
Tissue
Fish, shrimp
Milk, bovine, swine and fish tissue
LC-UV, LC-MS
LC-UV, LC-FLD, LC-MS
LC-visible, LC-MS
[13,14, 173–176]
[162–172] Review: [30]
[20,157–161] Review: [12]
5-Hydroxyflunixin [177–183] is flunixin metabolite
Multi-residue methods available
Convert leuco metabolites to chromic form for detection, no tolerance
LC-fluorescence Form sodium after derivatization, adducts that LC-MS are detected by LC-MS
[152–156] Review: [11]
May form sulfone metabolites
LC-UV (290 nm), LC-MS
Bovine and swine tissue, milk
Albendazole, fenbendazole, oxfendazole, thiabendazole
Anthelmintics, growth efficiency
Benzimidazoles
References
Comments
Detection
Typical matrices
Examples of compounds
Function (used to treat)
Drug class
Table 1 (Continued )
322 Sherri B. Turnipseed and Wendy C. Andersen
Veterinary Drug Residues
323
filters [64]. In-tube solid-phase microextraction (SPME) was used to isolate five sulfonamides from milk; low levels (ng/mL) were detected by LC-UV after chromatographic separation on a capillary monolithic LC column [72]. Because maximum or safe levels for these drugs have been established (10 ng/mL in the U.S. and 100 ng/mL according to EU regulations), it has not been necessary to develop methods with lower detection limits. Instead, many of these innovative methods have been able to reduce the sample size needed, down from a 10–20 mL portion to 1 mL or less and still successfully detect and measure the drugs at the required concentrations. The emergence of MS has had an influence in this area of analysis with early methods utilizing GC-MS [185] and many more recent methods taking advantage of the capability of LC-MS [64,66,67,186]. For example, a detection and confirmation LC-MS-MS method for sulfonamides in milk was developed that can detect 14 residues at levels below 10 ng/mL [67]. Another paper describes the analysis of these drugs in processed dairy products such as condensed milk and soft cheeses using LC-MS-MS [21]. An example of the analysis of three sulfonamides in condensed milk using this method is shown in Figure 4. The development of rapid screening tests for sulfonamides has also been of interest for many years. These drugs do not respond very well to traditional microbial inhibition testing, so effective alternative screening methods are important. Early chemical methods for the screening of milk for sulfonamide residues included thin layer chromatography methods [187]. There have also been rapid test kits available for quite some time [43]. The detection of 1.49
100
3.85
7.95E2 SRM ms2 251@-25 3.68E4 SRM ms2 256@-25
4.52
100
Sulfathiazole
100
4.36E2 SRM ms2 250@-25
100
2.79E2 SRM ms2 265@-25 1.09E5 SRM ms2 279@-25
6.38
100
Sulfamethazine
5.20E2 SRM ms2 285@-25
100
1.39E5 SRM ms 2 311@-25
9.02
100 Sulfadimethoxine
1.06E2 SRM ms2 301@-25
100
0
5 Time (min)
10
Figure 4 LC-MS-MS combined ion chromatograms for sulfathiazole, sulfamethazine and sulfadimethoxine in control condensed milk fortified at 5 ng/mL. Reprinted with permission from Ref. [21]. Copyright 2005 by AOAC International.
324
Sherri B. Turnipseed and Wendy C. Andersen
sulfonamides in milk was one of the earliest applications of the use of biosensors in animal drug residue methodology [188] and is still in use today [189].
4.3.2 Chloramphenicol Residues in Seafood and Other Products As mentioned earlier, chloramphenicol residues are of concern because of the drug’s unique capability to produce aplastic anemia in susceptible individuals. A review of the analytical methodology for chloramphenicol is also a good illustration of how the field of veterinary drug residue methodology has changed over the last several years. Initially, methods to detect residues of chloramphenicol or analogous compounds in food used either LC-UV, or GC with (ECD) or MS after derivatization. For example, one of the first methods for chloramphenicol in shrimp involved GC-ECD analysis of a silyl derivative after liquid–liquid extraction and isolation [190]. In an extension of that method, chloramphenicol, florfenicol, florfenicol amine and thiamphenicol were silylated and analysed by GC-ECD after liquid–liquid extraction and isolation from shrimp by a series of SPE columns; the quantification limit for this method was 5 mg/kg [121]. In 2001 and 2002, chloramphenicol residues in food became an urgent problem, specifically in seafood and honey imported to EU countries, Canada and the U.S. from China. More sensitive methods were needed to adequately monitor for these residues. With the advent of widely available LC-MS instrumentation, the detection limits for chloramphenicol were decreased significantly to below 0.5 mg/kg. For this reason, there were many methods published in 2003–2004 describing the analysis of chloramphenicol in these food products using LC-MS [115,122–127,132]. Most of these methods utilized negative ion ESI to monitor the deprotonated molecular ion of chloramphenicol at m/z 321. A triple quadrupole LC-MS-MS instrument was most commonly utilized and the methods were capable of both quantification and confirmation of the residue. A few methods described the use of a single quadrupole or ion trap instrumentation. Regardless of the MS instrumentation used, the chloramphenicol molecule breaks apart into consistent fragment or product ions that can be used for confirmation. In some methods, the chlorine isotope ratio was also used for identification purposes. Internal standards were often used for quantification including meta-chloramphenicol, deuterated chloramphenicol or an analogous compound such as thiamphenicol. The extraction procedure for many of these methods was still fairly extensive with liquid–liquid extraction and SPE isolations. More recently published methods for chloramphenicol residue analysis generally utilize simplified generic or novel extraction methods and have expanded the analysis to additional matrices such as crab, honey, milk and eggs [26,128,131]. LC-MS-MS analysis of chloramphenicol in honey by electrospray with negative ion detection and quantification with meta-chloramphenicol as an internal standard is illustrated in Figure 5 [26]. Biosensor-based assay test kits have expanded the possibility of rapidly screening food matrices for chloramphenicol residues at or below a concentration of 0.07 mg/kg [191].
325
Veterinary Drug Residues
(a) RT: 4.00 - 9.00 SM: 5G
200
2000
100
80 60 40 20 0 40
1000 500
1500
Intensity
Intensity
RT: 6.70
1000 0
RT: 6.70
3000 2000 1000
2000
321 > 176 500 RT: 5.37 0
30 20 10 0
0
1000 500
RT: 5.60
1000
500
500
5
6 7 8 Time (min)
9
321 > 257
RT: 5.65
RT: 5.64
321 > 207
0
0 4
RT: 6.79
1000 500 0
1000
RT: 6.74
0
321 > 194 500
1500 RT: 5.98 RT: 8.15
0
RT: 5.56
RT: 6.80
1000
0 2000
RT: 5.62
200
1500
RT: 6.78
1000
400
RT: 5.58
321 > 152 RT: 7.40
0
RT: 5.44 RT: 5.33 RT: 5.59
600
1000
RT: 6.79
4000
RT: 5.95 RT: 5.61
0
RT: 6.73
0
RT: 4.00 - 9.00 SM: RT: 7.41
4000
0 1500
(c)
Intensity
RT: 4.00 - 9.00 SM: 5G RT: 6.71
(b)
4
5
6 7 8 Time (min)
9
4
5
6 7 8 Time (min)
9
Figure 5 LC-MS-MS ion chromatograms for chloramphenicol of (a) 0.5 ng/g standard, (b) control honey with internal standard meta-chloramphenicol and (c) a chloramphenicolpositive honey sample. Ions monitored are (from top to bottom) m/z 152, 176, 194, 257 and 207. Reprinted with permission from Ref. [26]. Copyright 2006 by AOAC International.
4.3.3 Nitrofuran residues in seafood, poultry and honey Nitrofuran antibiotics are broad-spectrum agents effective against infections common to poultry, swine and aquacultured shrimp. Nitrofurans may also be used to treat honey bees. The most common nitrofurans associated with food production are furazolidone, furaltadone, nitrofurazone and nitrofurantion. The drugs metabolize rapidly so the parent compounds are not detected as residues. The metabolites of these drugs, which correspond to a side chain of the original molecule bound to proteins, do persist in tissue for a significant amount of time. The metabolites generated are 3-amino-2-oxazolidinone, 3-amino-5-morpholinomethyl-2-oxazolidinone, semicarbazide and 1-aminohydantion from furazolidone, furaltadone, nitrofurazone and nitrofurantion, respectively. There are concerns regarding the carcinogenicity and mutagenicity of these metabolites, making monitoring for these compounds both important and a significant analytical challenge [32]. Because of the human health concerns, there are no tolerances or maximum residue limits set for nitrofuran metabolite residues. The EU has established a minimum residue performance level of 1 mg/kg.
326
Sherri B. Turnipseed and Wendy C. Andersen
Methods have been developed for nitrofuran metabolite residues in tissue [139,147], shrimp [140,141], eggs [139] and honey [145]. In general, these methods have several attributes in common. A hydrolysis step, usually incubation with dilute hydrochloric acid, is needed to release the protein-bound metabolites. The molecules are then derivatized with nitrobenzaldehyde. While LC detection by UV is possible at this point, LC-MS is usually utilized to obtain the necessary detection limits as well as residue confirmation. There are some variations in this basic protocol. The clean-up and isolation of the residues after hydrolysis, but before derivatization, can be accomplished with liquid–liquid extraction or with a SPE cartridge, or by using a combination of both. In some methods, the matrix is first washed to remove any unbound residue, so that only compounds covalently attached to proteins are measured in the final extract; other procedures do not incorporate this step. One particular concern is for the residues of semicarbazide. While the metabolism of nitrofurazone is one source of semicarbazide in food, there are other possible explanations for the presence of this residue. Axodicarbonamide is an industrial chemical used as a blowing agent for rubber gaskets on jars (such as baby food) and in some cases as a food additive in flour. This chemical can also thermally degrade to form semicarbazide. It is also possible that semicarbazide could originate from the treatment of nitrogen-rich food with hypochlorite, a procedure that occurs when seaweed products are processed into gelling agents. It was originally thought that any protein-bound semicarbazide would necessarily originate from nitrofurazone exposure and that washing unbound residue prior to hydrolysis could reduce the amount of semicarbazide residues in the matrix from these other sources. However, a more extensive study of this issue is still needed [32]. The quantification of these metabolites can be complicated. In most cases, selective reaction monitoring using a triple quadrupole LC-MS-MS system is used to quantify the residues. Additional ion transitions can be monitored for confirmatory purposes. The fragmentation patterns of these derivatized metabolites have been established [192]. Ion trap and single quadrupole instruments can be used as well, but the results may not be as reliable for quantitative purposes as those obtained with a triple quadrupole procedure [140]. Matrix effects, i.e., ion suppression, can be an issue in obtaining good quantitative LC-MS methods [193]. For these methods, matrix effects can be overcome with matrix-based standards; but more often deuterated internal standards of one or more of the analytes are added to compensate for any ion suppression as well as for lack of recovery through the extraction procedure. The results of a proficiency study for nitrofuran metabolites in shrimp highlight some of the issues with these methods [140].
4.3.4 Triphenylmethane dyes in fish Triphenylmethane dyes are used as inexpensive and effective water bath treatments for fungal and parasite infections in fish. Malachite green is the most commonly used treatment within this class of compounds. The suspected carcinogenicity and teratogenicity of malachite green has rendered its use inappropriate for fish raised for human consumption [33]. Crystal violet (also
Veterinary Drug Residues
327
known as gentian violet) and brilliant green are structurally similar dyes with similar antifungal and toxicity properties [33,194,195]. Regardless of the international restrictions on the use of malachite green, illegal residues are regularly found in fish tissue. Reports of crystal violet abuse have also been noted [196]. The use of these therapeutic dyes in fish has been reviewed [30,195,197]. Methods to detect triphenylmethane dyes and their reduced leuco metabolites in fish tissue often include extraction by mixing the ground fish tissue with an acidic buffer and acetonitrile. This is followed by defatting and sample clean-up and residue isolation with liquid–liquid partition and/or SPE. The cationic triphenylmethane dyes have strong chromophores in the visible region of the spectrum, yet their reduced leuco metabolites are colorless. Since it is the leuco moiety that is found in greatest concentration in tissues, methods must emphasize the detection of this metabolite. Many traditional malachite green analytical methods have taken advantage of the sensitivity offered by LC with detection in the visible region by including a lead oxide, post-LC column reactor to oxidize the leuco residues to their chromic analogs [198–203]. The lead oxide reactor, however, is often difficult to prepare and can lead to rapid depletion and peak broadening resulting in a decrease in method sensitivity for regulatory use. Because all of the triphenylmethane dyes are banned, regulatory action can be taken in many countries if any level of residue is found in fish tissue. Method detection limits therefore drive regulatory action and should be as sensitive as possible. Recent methodology for the detection of malachite green in fish tissues has included several different approaches to meet minimum performance limits (2.0 mg/kg and lower) of international agencies [204]. In the first approach, leucomalachite green residues were oxidized to malachite green using 2,2,7dichloro-5,6-dicyano-1,4-benzoquinone (DDQ) prior to chromatographic analysis, enabling the measurement of the sum of malachite green and leucomalachite green residues by LC with visible detection at 1.0 mg/kg [163,168]. In another approach, residues at the 0.5 mg/kg level were determined using LC separation followed by the visible detection of malachite green at 620 nm and florescence detection of leucomalachite green at 360 nm (265 nm excitation) [171]. Both of these methods are advantageous for screening numerous samples with less expensive instrumentation. Mass spectrometric analysis of malachite green and leucomalachite green residues are divided by those that use an oxidation procedure to detect leucomalachite green as malachite green and those that detect leucomalachite green directly. Malachite green is cationic and more sensitively detected than leucomalachite green by LC-MS. In the former case, DDQ has been used prior to sample analysis with no-discharge LC-MSn to detect the sum of malachite green and leucomalachite green at 0.25 mg/kg [165,168]. This method was used to detect and confirm malachite green residues in store-bought basa fish (Figure 6). The lead oxide reactor has also been used to detect leucomalachite green as low as 0.1 mg/kg [164,166,172]. Several other methods rely on detection of malachite green and leucomalachite green individually using triple quadrupole LC-MS-MS, which is more sensitive for the quantification of leucomalachite green [162,167,170,205]. These methods offer excellent sensitivity with limits of detection
Relative Abundance
328
Sherri B. Turnipseed and Wendy C. Andersen
100
5.11 Area: 256,730,573 SN: 16,141
1.76E7 m/z= 328.5-329.5 ms2 [email protected] [150.00-350.00]
100
5.06 Area: 187,769,285 SN: 15,042
1.16E7 m/z= 313.0-315.0 ms2 [email protected] [150.00-350.00]
100
5.11 Area: 73,898,029 SN: 9,767
4.90E6 m/z= 284.0-286.0 ms2 [email protected] [150.00-350.00]
100
5.05 Area: 83,353,865 SN: 8,411
5.80E6 m/z= 250.5-251.5 ms2 [email protected] [150.00-350.00] 9.48E6 m/z= 207.5-208.5 ms2 [email protected] [150.00-350.00]
5.07 Area: 132,887,237
100
SN: 10,484
0
1
2
3
4
5 6 Time (min)
7
8
9 1.41E7
Relative Abundance
[email protected] [ 150.00-350.00]
329.3
100 80 60
208.2
40 20 0
251.2 193.1
160
200
237.2 241.1
240
270.3
285.2 284.2
280
313.3 314.2
320
m/z
Figure 6 LC-MSn extracted ion chromatograms and product ion spectrum from the malachite green (m/z 329) product ion trace in an extract from retail basa (diluted 1:5). Extracted ion ranges (from top to bottom) are m/z 329, 313–315, 284–286, 251 and 208. Reprinted with permission from Ref. [168]. Copyright 2006 American Chemical Society.
below 0.5 mg/kg. Some of these newer methods have also been applied to the concurrent determination of crystal violet and brilliant green residues [170,206]. Finally, an ELISA test kit based on DDQ oxidation for the detection of malachite green at 0.5 mg/kg in fish tissue has recently been commercialized [207].
5. OCCURRENCE IN FOOD It is not possible to obtain an absolute accounting of the rate of occurrence of violative veterinary drug residues in human food. The violation rate can depend greatly on not only the specific residue and matrix, but also on the number of samples analysed and the type of methodology utilized. Nevertheless, the results from several monitoring programs can be informative in evaluating the overall scope of the issue. In the U.S., one monitoring program for veterinary drug residues in meat products is administered by the Food Safety Inspection Service of the U.S. Department of Agriculture (FSIS/USDA). Tissue from many production classes of cattle, swine, lambs, goats and poultry are tested for a variety of residues. The
Veterinary Drug Residues
329
results from this program are published in the FSIS/USDA Red Book [208]. In 2004, over 3,000 tests were performed for antibiotic residues and 38 violations were recorded. Violative residues of penicillin (6), tilmicosin (3), neomycin (25) and gentamicin (4) were found; many of these occurred in veal products. In addition to these tests, a similar number of tests were performed for sulfonamide residues. Five sulfonamide violations were found in hogs, veal and turkey. Over 1,000 samples were analysed for chloramphenicol in cows, veal and poultry, but no residues were found. The National Milk Drug Residue Database is maintained by the U.S. FDA’s Center for Food Safety and Nutrition in cooperation with state governments in the U.S. This database reports the results from a voluntary industry-reporting program. Samples are obtained from milk pick-up tanks, pasteurized fluid milk and milk products and analysed for drug residues using rapid test kits. In the 2003 report [209], over 4 million samples were analysed. Many of these tests were for b-lactam residues and the most violations, approximately 3,000 (o0.1%), were found for these residues. Sulfonamide residue tests were performed over 66,000 times and 23 positive samples were found. A few non-compliant residues of tetracyclines and aminoglycosides were also detected in a limited number of samples. A Canadian total diet study monitoring veterinary drug residues in fish and seafood was conducted over a period of more than 10 years [210]. This study examined 30 samples of shrimp, marine fish, fresh fish and canned fish. The products were analysed for 39 different drug residues and 9 positive samples were found. The most common violations were for quinolone and nitrofuran metabolite residues in shrimp; leucomalachite green and chloramphenicol residues were also present. The EU conducts an extensive residue-monitoring program; the results from the 2004 program have been posted [211]. This report includes residuemonitoring data from 25 countries (member states). In 2004, approximately 807,000 targeted samples and 64,000 suspect samples were tested. In addition to antibiotics testing, samples were also monitored for hormones and other veterinary drugs. Many types of food matrices were part of this program, including milk, eggs, honey, aquaculture and meat products. Residues of prohibited substances such as chloramphenicol and nitrofurans were found to be violative at a rate of approximately 0.11%. Residues of malachite green were found in aquaculture products from many of the member states. The violation rate for antibiotics was 0.22%. There were a few violative results for other drugs such as tranquilizers and NSAIDs and the incidence of coccidiostat residues in eggs was highlighted as a continuing problem.
6. FUTURE TRENDS 6.1 Biosensors In the past 10 years, biosensor technology increasingly has been relied on for the sensitive and reliable monitoring of veterinary drug residues in food [212–215]. This technique typically relies on contacting the food sample or extract with a
330
Table 2
Sherri B. Turnipseed and Wendy C. Andersen
Biosensor veterinary drug residue methods Sensitivity (limit of detection (LOD))
References
Drug class
Examples of compounds
Matrices
Sulfonamides
Sulfamethazine, sulfadiazine, sulfamethoxazole
Milk, pig bile 1–23 mg/kg and muscle, chicken serum and plasma
[188,189, 217,218]
b-Lactams
Benzylpenicillin, ampicillin, amoxicillin, cephapirin, ceftiofur, etc.
Milk
1.2–100 ng/mL
[219,220]
Aminoglycosides Gentamicin, neomycin, kanamycin, streptomycin, dihydrostreptomycin
Milk powder, milk, honey, pig muscle and kidney
15–70 mg/kg
[221,222]
Macrolides
Tylosin
Honey
2.5 mg/kg
[223]
Quinolones
Enrofloxacin, ciprofloxacin
Milk
2–3 ng/mL
[224]
Phenicols
Chloramphenicol, florfenicol, thiamphenicol, florfenicol amine
Milk, honey, chicken muscle, shrimp
0.02–250 mg/kg
[191,225]
Coccidiostats
Nicarbazin
Eggs, liver
17–19 mg/kg
[226]
Anthelmintics
Ivermectin, levamisole
Milk, liver
0.5–16.2 mg/kg
[227]
residue-specific antibody to form a drug–antibody binding pair. The binding reaction generates a signal that can be detected by various methods, e.g., optical, piezoelectric, etc. The inherent specificity of the binding reaction allows biosensors to offer many advantages over traditional analytical methods. Food matrices require only minimal sample preparation and the analytical signal is typically absent of background interference. As a result, biosensor methods are easy to use, fast and offer excellent sensitivity for high-throughput screening. For veterinary drug residue analysis, most of the literature methods have been developed using optical biosensor instrumentation based on surface plasmon resonance. Methods have been developed for a broad range of the drug classes described previously in foods. A selection of recent methodology is summarized in Table 2. In addition, binding assay test kits are commercially available for sulfonamides, chloramphenicol, streptomycin and others [216].
Ionophores, macrolides
Fluoroquinolones, sulfonamides, tetracyclines, b-lactams Sulfonamides quinolones tetracyclines, dyes
Eggs
Eggs
Quinolones, sulfonamides, tetracyclines, macrolides, benzimidazoles, b-lactams, etc.
Quinolones, sulfonamides, tetracyclines, macrolides, dyes, imidazoles, b-lactams, etc.
Tetracyclines, sulfonamides, 70% methanol extract diluted with LC-MS-MS triple quad, macrolides, quinolones, b-lactams water electrospray
Tetracyclines, sulfonamides, pyrimethamine
Tissue
Fish
Tissue
Milk
Trichloroacetic acid, polymeric SPE
Acetonitrile/hexane extraction, hexane wash
Acetonitrile/methanol (95:5 extract), hexane wash
LC-MS (single quad) electrospray
Ion trap LC-MS electrospray
LC-MS-MS triple quad, electrospray
LC-MS-MS triple quad, electrospray
Macrolides, fluoroquinolones, etc.
Tissue
Acetonitrile extraction, on line polymer SPE
Trichloroacetic acid or acetonitrile LC-MS-MS triple quad, extraction electrospray
b-Lactams, tetracyclines, aminoglycosides, macrolides, quinolones, sulfonamides
Milk
LC-UV/Fluorescence, LC-MS (APCI)
Ion trap LC-MS APCI/no-dischargeAPCI
Ion trap LC-MS electrospray
Ion trap LC-MS electrospray
Detection
Acetonitrile extraction, cation exchange SPE
Trichloroacetic acid extraction, polymeric SPE
Succinate buffer extraction, polymeric SPE
Silica SPE
Extraction
Tissue, Sulfonamides, benzimidazoles, fish, eggs tranquilizers, fluoroquinolones, dyes
Shrimp
Drug classes
Multi-class veterinary drug residue methods
Matrix
Table 3
10
19
35
130
13
44
30
19
[230]
[236]
[235]
[231]
[229]
[234]
[233]
[228]
[232]
[104]
7 29
References
Number of residues
Veterinary Drug Residues
331
332
Sherri B. Turnipseed and Wendy C. Andersen
6.2 Multi-class methods An emerging trend in veterinary drug residue analysis is the development of methods that are capable of monitoring a wide variety of residues, regardless of drug class, in a single sample. Often this involves a generic extraction and cleanup, designed to be as inclusive as possible, combined with the sensitivity and selectivity of LC-MS detection. For example, several methods utilize a polymeric SPE clean-up, such as OASISs, to isolate many of the drug residues from the initial extract [104,228–230]. A hexane wash is sometimes required to remove lipid materials, but in general, extensive liquid–liquid extractions are avoided to maximize throughput. Screening and confirmatory data are collected by MS; some methods also provide quantification of residues [231]. Both ion trap and triple quadrupole MS-MS instruments have been successfully utilized. Several multi-class veterinary drug residues methods have been reported in recent years and these are summarized in Table 3. Multi-class multi-residue LC-MS methods are an effective way to monitor a wide variety of drug classes in a single sample, maximizing laboratory resources and allowing for flexibility in a risk-based regulatory program.
REFERENCES 1 National Research Council, The Use of Drugs in Food Animals: Benefits and Risks, National Academy Press, Washington, DC, 1999. 2 The Merck Index on CD Rom., Version 12:3, Merck & Co., Whitehouse Station, NJ, 2000. 3 C.C. Walker and S.B. Turnipseed, In: S.B. Turnipseed and A.R. Long (Eds.), Analytical Procedures for Drug Residues in Food of Animal Origin: Sulfonamides, Science Technology System, West Sacramento, CA, 1998. 4 W.A. Moats, In: S.B. Turnipseed and A.R. Long (Eds.), Analytical Procedures for Drug Residues in Food of Animal Origin: Beta-Lactams, Science Technology System, West Sacramento, CA, 1998. 5 R. Gehring, S.R. Haskell, M.A. Payne, A.L. Craigmill, A.I. Webb and J.E. Riviere, J. Am. Vet. Med. Assoc., 227 (2005) 63. 6 H. Oka, Y. Ito and H. Matsumoto, J. Chromatogr. A, 882 (2000) 109. 7 S.B. Turnipseed, In: S.B. Turnipseed and A.R. Long (Eds.), Analytical Procedures for Drug Residues in Food of Animal Origin: Macrolides and Lincosamides, Science Technology System, West Sacramento, CA, 1998. 8 J.A. Herna´ndez-Arteseros, J. Barbosa, R. Compan˜o and M.D. Prat, J. Chromatogr. A, 945 (2002) 1. 9 L. Mortier, E. Daeseleire and C. Van Peteghem, Rapid Commun. Mass Spectrom., 19 (2005) 533. 10 N. Woodford, J. Med. Microbiol., 47 (1998) 849. 11 M. Danaher, H. De Ruyck, S.R.H. Crooks, G. Dowling and M. O’Keeffe, J. Chromatogr. B, 845 (2007) 1. 12 M. Danaher, L.C. Howells, S.R.H. Crooks, V. Cerkvenik-Flajs and M. O’Keeffe, J. Chromatogr. B, 844 (2006) 175. 13 Y. Govaert, P. Batjoens, K. Tsilikas, J. Degroodt and S. Srebrnik, Analyst, 123 (1998) 2507. 14 A. Kaufmann and B. Ryser, Rapid Commun. Mass Spectrom., 15 (2001) 1747. 15 M. Kopcha, J.B. Kaneene, M.E. Shea, R. Miller and A.S. Ahl, J. Am. Vet. Med. Assoc., 201 (1992) 1868. 16 R.W. Fedeniuk and P.J. Shand, J. Chromatogr. A, 812 (1998) 3. 17 S.B. Turnipseed, W.C. Andersen, C.M. Karbiwnyk, J.E. Roybal and K.E. Miller, Rapid Commun. Mass Spectrom., 20 (2006) 1231.
Veterinary Drug Residues
333
18 S.B. Turnipseed, In: Y.H. Hui, W.K. Nip, W.R. Rogers and O.A. Young (Eds.), Meat Science and Applications: Drug Residues in Meat, Emerging Issues, Marcel-Dekker, New York, 2001. 19 S.J. Lehotay, K. Mastovska and N. Thiex, In: J.N. Sofos (Ed.), Improving the Safety of Fresh Meat: Detecting Veterinary Drug Residues in Feed and Cattle, Woodhead Publishing, Cambridge, MA, 2005. 20 A. Anastasio, M. Esposito, M. Amorena, P. Catellani, L. Serpe and M.L. Cortesi, J. Agric. Food Chem., 50 (2002) 5241. 21 S.B. Clark, S.B. Turnipseed, M.R. Madson, J.A. Hurlbut, L.R. Kuck and J.N. Sofos, J. AOAC Int., 88 (2005) 736. 22 D.J. Fletouris, N.A. Botsoglou, I.E. Psomas and A.I. Mantis, J. Food Protect., 61 (1998) 1484. 23 B. Koonse, Food Safety Mag., 12 (2006) 22. 24 F.C. Cabello, Environ. Microbiol., 8 (2006) 1137. 25 L. Penney, A. Smith, B. Coates and A. Wijewickreme, J. AOAC Int., 88 (2005) 645. 26 D. Quon, M.C. Carson, C. Nochetto, D.N. Heller and F. Butterworth, J. AOAC Int., 89 (2006) 586. 27 D.G. Tinkelman and S.A. Bock, Ann. Allergy, 53 (1984) 243. 28 H.J. Schwartz and T.H. Sher, Ann. Allergy, 52 (1984) 342. 29 S.F. Sundlof and J. Cooper, In: W.A. Moats and M.B. Medina (Eds.), Veterinary Drug Residues: Human Health Risks Associated with Drug Residues in Animal-Derived Foods, American Chemical Society, Washington, DC, 1996. 30 J.E. Roybal, A.P. Pfenning, S.B. Turnipseed, J.A. Hurlbut and A.R. Long, In: W.A. Moats and W.B. Medina (Eds.), Veterinary Drug Residues: Analysis of Dyes in Foods of Animal Origin, American Chemical Society, Washington, DC, 1996. 31 P. Gowik, K. Kato and S. Uhlig, J. Chromatogr. B, 716 (1998) 221. 32 M.B. De La Calle and E. Anklam, Anal. BioAnal. Chem., 382 (2005) 968. 33 S.J. Culp and F.A. Beland, J. Am. Col. Toxicol., 15 (1996) 219. 34 T.M. Wassenaar, Crit. Rev. Microbiol., 31 (2005) 155. 35 M. Quednau, S. Ahrne, A.C. Petersson and G. Molin, App. Microbiol., 84 (1998) 1163. 36 H.C. Wegener, F.M. Aarestrup, L.B. Jensen, A.M. Hammerum and F. Bager, Emerg. Infect. Dis., 5 (1999) 329. 37 O.E. Heuer, A.M. Hammerum, P. Collignon and H.C. Wegener, Clin. Infect. Dis., 43 (2006) 911. 38 H.P. Endtz, G.J. Ruijs, B. van Klingeren, W.H. Jansen, T. van der Reyden and R.P. Mouton, J. Antimicrob. Chem., 27 (1991) 199. 39 M.K. Glynn, C. Bopp, W. Dewitt, P. Dabney, M. Mokhtar and F.J. Angulo, N. Eng. J. Med., 338 (1998) 1333. 40 K.E. Smith, J.M. Besser, C.W. Hedberg, F.T. Leano, J.B. Bender, J.H. Wicklund, B.P. Johnson, K.A. Moore and M.T. Osterholm, N. Eng. J. Med., 340 (1999) 1525. 41 I. Klare, D. Badstubner, C. Konstabel, G. Bohme, H. Claus and W. Witte, Microb. Drug Resist., 5 (1999) 45. 42 Evaluating the Safety of Antimicrobial New Animal Drugs with Regard to Their Microbiological Effects on Bacteria of Human Health Concern, U.S. Food and Drug Administration, Center for Veterinary Medicine, Guidance for Industry #152, 2003. Available at http://www.fda.gov/cvm/ Guidance/fguide152.DOC 43 Antibiotic and Veterinary Drug Residue Test Kits, 2007. Available at http://www.aoac.org/ testkits/kits-antibiotics.HTM 44 F. Toldra and M. Reig, Trends Food Sci. Tech., 17 (2006) 482. 45 European Union Commission Decision 2002/657/EC of 12 August 2002 Implementing Council Directive 96/23/EC Concerning the Performance of Analytical Methods and the Interpretation of Results, Off. J. Eur. Comm., L221 (2002) 8. 46 AOAC, AOAC Official Methods Program Manual: Appendix D: Guidelines for Collaborative Study Procedures to Validate Characteristics of a Method of Analysis, AOAC International, Gaithersburg, MD, 2002. 47 Validation of Analytical Procedures: Methodology, U.S. Food and Drug Administration, Center for Veterinary Medicine, Guidance for Industry #64, 1999. Available at http://www.fda.gov/ cvm/Guidance/guida64.htm
334
Sherri B. Turnipseed and Wendy C. Andersen
48 F. Andre, K. De Wasch, H. De Brabander, S.R. Impens, L. Stolker, L.A. van Ginkel, R.W. Stephany, R. Schilt, D. Courtheyn, Y. Bonnaire, P. Furst, P. Gowik, G. Kennedy, T. Kuhn, J.P. Moretain and M. Sauer, Trends Anal. Chem., 20 (2001) 435. 49 J.A. Sphon, J. AOAC Int., 61 (1978) 1247. 50 S.E. Stein and D.N. Heller, J. Am. Soc. Mass Spectrom., 17 (2006) 823. 51 Mass Spectrometry for Confirmation of the Identity of Animal Drug Residues, U.S. Food and Drug Administration, Center for Veterinary Medicine, Guidance for Industry #118, 2003. Available at http://www.fda.gov/cvm/guidance/guide118.pdf 52 G. Balizs and A. Hewitt, Anal. Chim. Acta, 492 (2003) 105. 53 A. Gentili, D. Perret and S. Marchese, Trends Anal. Chem., 24 (2005) 704. 54 S.B. Turnipseed, In: Y.H. Hui, B.L. Bruinsma, R. Gorham, W.-K. Nip, P.S. Tong and P. Ventresca (Eds.), Food Plant Sanitation: Analysis of Drug Residues in Food, Marcel Dekker, New York, 2002. 55 D.G. Kennedy, R.J. McCracken, A. Cannavan and S.A. Hewitt, J. Chromatogr. A, 812 (1998) 77. 56 F.J. Schenck and P.S. Callery, J. Chromatogr. A, 812 (1998) 99. 57 A.A.M. Stolker and U.A.T. Brinkman, J. Chromatogr. A, 1067 (2005) 15. 58 H. Oka, H. Nakazawa, K.-I. Harada and J.D. MacNeil (Eds.), Chemical Analysis for Antibiotics Used in Agriculture, AOAC International, Arlington, VA, 1995. 59 S.B. Turnipseed and A.R. Long (Eds.), Analytical Procedures for Drug Residues in Food of Animal Origin, Science Technology System, Sacramento, CA, 1998. 60 G. Stoev and A. Michailova, J. Chromatogr. A, 871 (2000) 37. 61 N. Van Eeckhout, J.C. Perez and C. Van Peteghem, Rapid Commun. Mass Spectrom., 14 (2000) 2331. 62 D.N. Heller, M.A. Ngoh, D. Donoghue, L. Podhorniak, H. Righter and M.H. Thomas, J. Chromatogr. B, 774 (2002) 39. 63 A. Kaufmann, S. Roth, B. Ryser, M. Widmer and D. Guggisberg, J. AOAC Int., 85 (2002) 853. 64 J.A. van Rhijn, J.J.P. Lasaroms, B.J.A. Berendsen and U.A.T. Brinkman, J. Chromatogr. A, 960 (2002) 121. 65 L. Verzegnassi, M.C. Savoy-Perroud and R.H. Stadler, J. Chromatogr. A, 977 (2002) 77. 66 S. Bogialli, R. Curini and A. Di Corcia, J. Agric. Food Chem., 51 (2003) 4225. 67 C. Cavaliere, R. Curini, A. Di Corcia, M. Nazzari and R. Samperi, J. Agric. Food Chem., 51 (2003) 558. 68 J.E. Roybal, A.P. Pfenning, S.B. Turnipseed and S.A. Gonzales, Anal. Chim. Acta, 483 (2003) 147. 69 T.A.M. Msagati and M.M. Nindi, Talanta, 64 (2004) 87. 70 M. Juhel-Gaugain, M.P. Fourmond, B. Delepine, M. Laurentie, B. Roudaut and P. Sanders, Food Addit. Contam., 22 (2005) 221. 71 B. Shao, D. Dong, Y. Wu, J. Hu, J. Meng, X. Tu and S. Xu, Anal. Chim. Acta, 546 (2005) 174. 72 Y. Wen, M. Zhang, Q. Zhao and Y.Q. Feng, J. Agric. Food Chem., 53 (2005) 8468. 73 S. Wang, H.Y. Zhang, L. Wang, Z.J. Duan and I. Kennedy, Food Addit. Contam., 23 (2006) 362. 74 C.Y. Ang, F.F. Liu, J.O. Lay, Jr., W. Luo, K. McKim, T. Gehring and R. Lochmann, J. Agric. Food Chem., 48 (2000) 1673. 75 W. Luo and C.Y. Ang, J. AOAC Int., 83 (2000) 20. 76 F. Bruno, R. Curini, A. Di Corcia, M. Nazzari and R. Samperi, J. Agric. Food Chem., 49 (2001) 3463. 77 S. Riediker and R.H. Stadler, Anal. Chem., 73 (2001) 1614. 78 D.M. Holstege, B. Puschner, G. Whitehead and F.D. Galey, J. Agric. Food Chem., 50 (2002) 406. 79 M. Becker, E. Zittlau and M. Petz, Anal. Chim. Acta, 520 (2004) 19. 80 Y. Ito, T. Goto, H. Oka, H. Matsumoto and K. Takeba, J. Chromatogr. A, 1042 (2004) 107. 81 C.K. Fagerquist, A.R. Lightfield and S.J. Lehotay, Anal. Chem., 77 (2005) 1473. 82 E. Daeseleire, H. De Ruyck and R. Van Renterghem, Rapid Commun. Mass Spectrom., 14 (2000) 1404. 83 R.E. Hornish, P.J. Hamlow and S.A. Brown, J. AOAC Int., 86 (2003) 30. 84 W.A. Moats, J. Agric. Food Chem., 48 (2000) 2244. 85 N. Van Eeckhout, J.C. Perez, J. Claereboudt, R. Vandeputte and C. Van Peteghem, Rapid Commun. Mass Spectrom., 14 (2000) 280. 86 F. Bruno, R. Curini, A.D. Corcia, M. Nazzari and M. Pallagrosi, Rapid Commun. Mass Spectrom., 16 (2002) 1365.
Veterinary Drug Residues
335
87 M. Cherlet, M. Schelkens, S. Croubels and P. De Backer, Anal. Chim. Acta, 492 (2003) 199. 88 H.S. Rupp and C.R. Anderson, J. AOAC Int., 88 (2004) 505. 89 W.C. Andersen, J.E. Roybal, S.A. Gonzales, S.B. Turnipseed, A.P. Pfenning and L.R. Kuck, Anal. Chim. Acta, 529 (2005) 145. 90 G.H. Wan, H. Cui, H.S. Zheng, J. Zhou, L.J. Liu and X.F. Yu, J. Chromatogr. B, 824 (2005) 57. 91 S.P. Khong, Y.A. Hammel and P.A. Guy, Rapid Commun. Mass Spectrom., 19 (2005) 493. 92 B.F. Spisso, A.L. de Oliveira e Jesus, M.A.G. de Araujo, Jr. and M.A. Monteiro, Anal. Chim. Acta, 581 (2007) 108. 93 C.R. Anderson, H.S. Rupp and W.H. Wu, J. Chromatogr. A, 1075 (2005) 23. 94 D.N. Heller, S.B. Clark and H. Righter, J. Mass Spectrom., 35 (2000) 39. 95 A. Kaufmann, P. Butcher and P. Kolbener, Rapid Commun. Mass Spectrom., 17 (2003) 2575. 96 M. van Bruijnsvoort, S.J.M. Ottink, K.M. Jonker and E. de Boer, J. Chromatogr. A, 1058 (2004) 137. 97 S. Bogialli, R. Curini, A. Di Corcia, A. Lagana, M. Mele and M. Nazzari, J. Chromatogr., 1067 (2005) 93. 98 A. Kaufmann and K. Maden, J. AOAC Int., 88 (2005) 1118. 99 D.N. Heller, J.O. Peggins, C.B. Nochetto, M.L. Smith, O.A. Chiesa and K. Moulton, J. Chromatogr. B, 821 (2005) 22. 100 S.I. Kotretsou, Crit. Rev. Food Sci. Nutr., 44 (2004) 173. 101 D.A. Stead, J. Chromatogr. B, 747 (2000) 69. 102 M. Dubois, D. Fluchard, E. Sior and P. Delahaut, J. Chromatogr. B Analyt. Technol. Biomed. Life Sci., 753 (2001) 189. 103 T.S. Thompson, D.K. Noot, J. Calvert and S.F. Pernal, J. Chromatogr. A, 1020 (2003) 241. 104 D.N. Heller and C.B. Nochetto, J. Agric. Food Chem., 52 (2004) 6848. 105 J. Wang, J. Agric. Food Chem., 52 (2004) 171. 106 J. Wang, D. Leung and S.P. Lenz, J. Agric. Food Chem., 54 (2006) 2873. 107 M. Cherlet, S. De Baere, S. Croubels and P. De Backer, Anal. Chim. Acta, 473 (2002) 167. 108 S.B. Clark, J.J. O’Rangers, W.D. Rowe, M.R. Madson, J.A. Hurlbut, J.N. Sofos, B. Fuerst, G. James, S. Griffith and R.S. Readnour, J. AOAC Int., 85 (2002) 1260. 109 D. Lucchetti, L. Fabrizi, A. Esposito, E. Guandalini, M. Di Pasquale and E. Coni, J. Agric. Food Chem., 53 (2005) 9689. 110 L. Johnston, L. Mackay and M. Croft, J. Chromatogr. A, 982 (2002) 97. 111 J.E. Roybal, C.C. Walker, A.P. Pfenning, S.B. Turnipseed, J.M. Storey, S.A. Gonzales and J.A. Hurlbut, J. AOAC Int., 85 (2002) 1293. 112 M.J. Schneider and D. Donoghue, J. Chromatogr. B, 780 (2002) 83. 113 B. Toussaint, G. Bordin, A. Janosi and A.R. Rodriguez, J. Chromatogr. A, 976 (2002) 195. 114 D.J. Donoghue and M.J. Schneider, J. AOAC Int., 86 (2003) 669. 115 S.B. Turnipseed, J.E. Roybal, A.P. Pfenning and P.J. Kijak, Anal. Chim. Acta, 483 (2003) 373. 116 C. Ho, D.W.M. Sin, H.P.O. Tang, L.P.K. Chung and S.M.P. Siu, J. Chromatogr. A, 1061 (2004) 123. 117 M.D. Marazuela and M.C. Moreno-Bondi, J. Chromatogr. A, 1034 (2004) 25. 118 N. Van Hoof, K. De Wasch, L. Okerman, W. Reybroeck, S. Poelmans, H. Noppe and H. De Brabander, Anal. Chim. Acta, 529 (2005) 265. 119 A.C. Huet, C. Charlier, S.A. Tittlemier, G. Singh, S. Benrejeb and P. Delahaut, J. Agric. Food Chem., 54 (2006) 2822. 120 E. Verdon, P. Couedor, B. Roudaut and P. Sanders, J. AOAC Int., 88 (2005) 1179. 121 A.P. Pfenning, J.E. Roybal, H.S. Rupp, S.B. Turnipseed, S.A. Gonzales and J.A. Hurlbut, J. AOAC Int., 83 (2000) 26. 122 W. Hammack, M.C. Carson, B.K. Neuhaus, J.A. Hurlbut, C. Nochetto, J.S. Stuart, K. Youngs, K. Ferbos and D.N. Heller, J. AOAC Int., 86 (2003) 1135. 123 P. Mottier, V. Parisod, E. Gremaud, P.A. Guy and R.H. Stadler, J. Chromatogr. A, 994 (2003) 75. 124 M. Ramos, P. Munoz, A. Aranda, I. Rodriguez, R. Diaz and J. Blanca, J. Chromatogr. B, 791 (2003) 31. 125 M. Takino, T. Daishima and T. Nakahara, J. Chromatogr. A, 1101 (2003) 67. 126 C.L. Wrzesinski and L.S. Crouch, J. AOAC Int., 86 (2003) 515. 127 E. Gikas, P. Kormali, D. Tsipi and A. Tsarbopoulos, J. Agric. Food Chem., 52 (2004) 1025.
336
128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175
Sherri B. Turnipseed and Wendy C. Andersen
H.S. Rupp, J.S. Stuart and J.A. Hurlbut, J. AOAC Int., 88 (2005) 1155. H.Y. Shen and H.L. Jiang, Anal. Chim. Acta, 535 (2005) 33. J.F. Huang, H.J. Zhang and Y.Q. Feng, J. Agric. Food Chem., 54 (2006) 9279. H.T. Ronning, K. Einarsen and T.N. Asp, J. Chromatogr. A, 1118 (2006) 226. J.M. van de Riet, R.A. Potter, M. Christie-Fougere and B.G. Burns, J. AOAC Int., 86 (2003) 510. L. Mortier, E. Daeseleire, A.C. Huet, P. Delahaut and C. Van Peteghem, Rapid Commun. Mass Spectrom., 18 (2004) 1817. L. Mortier, E. Daeseleire and C. Van Peteghem, J. Chromatogr. B, 820 (2005) 261. S. Yakkundi, A. Cannavan, C.T. Elliott, T. Lo¨vgren and D.G. Kennedy, J. Chromatogr. B, 788 (2003) 29. V. Hagren, P. Peippo, M. Tuomola and T. Lo¨vgren, Anal. Chim. Acta, 557 (2006) 164. M. Rokka and K. Peltonen, Food Addit. Contam., 23 (2006) 470. S. Szilagyi and B. de la Calle, Anal. Chim. Acta, 572 (2006) 113. J.K. Finzi, J.L. Donato, M. Sucupira and G. De Nucci, J. Chromatogr. B, 824 (2005) 30. D. Hurtaud-Pessel, E. Verdon, J. Blot and P. Sanders, Food Addit. Contam., 23 (2006) 569. P.S. Chu and M.I. Lopez, J. Agric. Food Chem., 53 (2005) 8934. R.J. McCracken, J.A. van Rhijn and D.G. Kennedy, Br. Poultry Sci., 46 (2005) 287. R.J. McCracken, J.A. van Rhijn and D.G. Kennedy, Food Addit. Contam., 22 (2005) 567. I. Diblikova, K.M. Cooper, D.G. Kennedy and M. Franek, Anal. Chim. Acta, 540 (2005) 285. S.P. Khong, E. Gremaud, J. Richoz, T. Delatour, P.A. Guy, R.H. Stadler and P. Mottier, J. Agric. Food Chem., 52 (2004) 5309. L. Tribalat, O. Paisse, G. Dessalces and M.F. Grenier-Loustalot, Anal. Bioanal. Chem., 386 (2006) 2161. A. Leitner, P. Zollner and W. Lindner, J. Chromatogr. A, 939 (2001) 49. M.S.S. Curren and J.W. King, J. Chromatogr. A, 954 (2002) 41. M. Kadota, M. Imanaka, S. Hino, J. Nanba, S. Take and H. Nakazawa, J. Food Hyg. Soc. Japan, 44 (2003) 69. D.W.M. Sin, C. Ho, Y.C. Wong, S.K. Ho and A.C.B. Ip, Anal. Chim. Acta, 517 (2004) 39. D.W.M. Sin, C. Ho, Y.C. Wong, S.K. Ho and A.C.B. Ip, Anal. Chim. Acta, 535 (2005) 23. D.L. Brandon, A.H. Bates, R.G. Binder, W.C. Montague, Jr., L.C. Whitehand and S.A. Barker, J. Agric. Food Chem., 50 (2002) 5791. H. De Ruyck, E. Daeseleire, H. De Ridder and R. Van Renterghem, J. Chromatogr. A, 976 (2002) 181. G. Dowling, H. Cantwell, M. O’Keeffe and M.R. Smyth, Anal. Chim. Acta, 529 (2005) 285. B. Shaikh, N. Rummel, C. Gieseker and R. Reimschuessel, J. Vet. Pharmacol. Ther., 29 (2006) 525. D.J. Fletouris, E.P. Papapanagiotou, D.S. Nakos and I.E. Psomas, J. Agric. Food Chem., 53 (2005) 893. M. Danaher, M. O’Keeffe, J.D. Glennon and L. Howells, Analyst, 126 (2001) 576. L. Howells and M.J. Souer, Analyst, 126 (2001) 155. S.B. Turnipseed, J.E. Roybal, W.C. Andersen and L.R. Kuck, Anal. Chim. Acta, 529 (2005) 159. H. Kim-Kang, L.S. Crouch, A. Bova, R.A. Robinson and J. Wu, J. Agric. Food Chem., 49 (2001) 5294. J.M. van de Riet, N.N. Brothers, J.N. Pearce and B.G. Burns, J. AOAC Int., 84 (2001) 1358. K. Halme, E. Lindfors and K. Peltonen, Food Addit. Contam., 21 (2004) 641. W.C. Andersen, J.E. Roybal and S.B. Turnipseed, J. AOAC Int., 88 (2005) 1292. P. Scherpenisse and A.A. Bergwerff, Anal. Chim. Acta, 529 (2005) 173. S.B. Turnipseed, W.C. Andersen and J.E. Roybal, J. AOAC Int., 88 (2005) 1312. L. Valle, C. Diaz, A.L. Zanocco and P. Richter, J. Chromatogr. A, 1067 (2005) 101. J.M. van de Riet, C.J. Murphy, J.N. Pearce, R.A. Potter and B.G. Burns, J. AOAC Int., 88 (2005) 744. W.C. Andersen, S.B. Turnipseed and J.E. Roybal, J. Agric. Food Chem., 54 (2006) 4517. K. Halme, E. Lindfors and K. Peltonen, J. Chromatogr. B, 845 (2007) 74. G. Dowling, P.P.J. Mulder, C. Duffy, L. Regan and M.R. Smyth, Anal. Chim. Acta, 586 (2007) 411. K. Mitrowska, A. Posyniak and J. Zmudzki, J. Chromatogr. A, 1089 (2005) 187. A.A. Bergwerff and P. Scherpenisse, J. Chromatogr. B, 788 (2003) 351. D. Fluchard, S. Kiebooms, M. Dubois and P. Delahaut, J. Chromatogr. B, 744 (2000) 139. P. Delahaut, P.-Y. Brasseur and M. Dubois, J. Chromatogr. A, 1054 (2004) 373. J. Cooper, P. Delahaut, T.L. Fodey and C.T. Elliott, Analyst, 129 (2004) 169.
Veterinary Drug Residues
337
176 V. Cerkvenik-Flajs, Anal. Chim. Acta, 586 (2007) 374. 177 S.B. Clark, S.B. Turnipseed, G.J. Nandrea, M.R. Madson, J.N. Sofos, J.A. Hurlbut and C.E. Shultz, J. AOAC Int., 85 (2002) 109. 178 F. Vinci, S. Fabbrocino, M. Fiori, L. Serpe and P. Gallo, Rapid Commun. Mass Spectrom., 20 (2006) 3412. 179 C. Igualada and F. Moragues, Anal. Chim. Acta, 529 (2005) 235. 180 P.E.A. Asea, K.D. Souster, C.D.C. Salisbury and J.O. Boison, J. Liq. Chromatogr. Relat. Technol., 27 (2004) 3013. 181 N. Van Hoof, K. De Wasch, S. Poelmans, H. Noppe and H. De Brabander, Rapid Commun. Mass Spectrom., 18 (2004) 2823. 182 E. Daeseleire, L. Mortier, H. De Ruyck and N. Geerts, Anal. Chim. Acta, 488 (2003) 25. 183 P.L. Boner, D.D. Liu, W.F. Feely, M.J. Wisocky and J. Wu, J. Agric. Food Chem., 51 (2003) 3753. 184 O.W. Parks and R.J. Maxwell, J. Chromatogr. Sci., 32 (1994) 290. 185 V.B. Reeves, J. Chromatogr. B, 723 (1999) 127. 186 D.A. Volmer, Rapid Commun. Mass Spectrom., 10 (1996) 1615. 187 L.S.G. Van Poucke, G.C.I. Depourcq and C.H. Van Peteghem, J. Chromatogr. Sci., 29 (1991) 423. 188 A. Sternesjo¨, C. Mellgren and L. Bjorck, Anal. Biochem., 226 (1995) 175. 189 W. Haasnoot, M. Bienenmann-Ploum, U. Lamminma¨ki, M. Swanenburg and H. van Rhijn, Anal. Chim. Acta, 552 (2005) 87. 190 R.K. Munns, D.C. Holland, J.E. Roybal, J.M. Storey, A.R. Long, G.R. Stehly and S.M. Plakas, J. AOAC Int., 77 (1994) 596. 191 J. Ferguson, A. Baxter, P. Young, G. Kennedy, C. Elliott, S. Weigel, R. Gatermann, H. Ashwin, S. Stead and M. Sharman, Anal. Chim. Acta, 529 (2005) 109. 192 T. Delatour, E. Gremaud, P. Mottier, J. Richoz, F.A. Vera and R.H. Stadler, J. Agric. Food Chem., 51 (2003) 6371. 193 J.P. Antignac, K. De Wasch, F. Monteau, H. De Brabander, F. Andre and B. Le Bizec, Anal. Chim. Acta, 529 (2004) 129. 194 D.J. Alderman, J. Fish Dis., 5 (1982) 113. 195 A.P. Pfenning, In: S.B. Turnipseed and A.R. Long (Eds.), Analytical Procedures for Drug Residues in Food of Animal Origin: Dyes, Science Technology System, West Sacramento, CA, 1988. 196 Crystal violet reports from 21/12/06, 21/2/06, 16/8/05 and 21/7/05. Available at http:// www.fishupdate.com 197 S.M. Plakas, D.R. Doerge and S.B. Turnipseed, In: D.J. Smith and W.H. Gingerich (Eds.), Xenobiotics in Fish: Disposition and Metabolism of Malachite Green and Other Therapeutic Dyes in Fish, Kluwer Academic/Plenum Publishers, New York, 1999. 198 J.L. Allen, J.E. Gofus and J.R. Meinertz, J. AOAC Int., 77 (1994) 553. 199 J.E. Roybal, A.P. Pfenning, R.K. Munns, D.C. Holland, J.A. Hurlbut and A.R. Long, J. AOAC Int., 78 (1995) 453. 200 J.A. Tarbin, K.A. Barnes, J. Bygrave and W.H.H. Farrington, Analyst, 123 (1998) 2567. 201 L.G. Rushing, S.F. Webb and H.C. Thompson, Jr., J. Chromatogr. B, 674 (1995) 125. 202 O. Dafflon, H. Gobet and H. Koch, Trav. Chim. Aliment. Hyg., 83 (1992) 215. 203 W. Fink and J. Auch, Deut. Lebensm.-Rundsch., 89 (1993) 246. 204 European Union Commission Decision 2004/25/EC as Regards the Setting of Minimum Required Performance Limits (MRPLs) for Certain Residues in Food of Animal Origin, Off. J. Eur. Union, L6 (2004) 38. 205 J.A. van Rhijn, P.P.J. Mulder, F. van Baardewijk, E.M. te Brinke and J.J.P. Lasaroms, Confirmatory Analysis of Traces of Malachite Green and Leucomalachite Green in Muscle Tissue of Atlantic Salmon, Proceedings of Euroresidue V Conference, Noordwijkerhout, The Netherlands, May 10–12, 2004. 206 W.C. Andersen, S.B. Turnipseed, C.M. Karbiwnyk, R.H. Lee, S.B. Clark, W.D. Rowe, M.R. Madson and K.E. Miller, Quantitative and Confirmatory Analyses of Crystal Violet (Gentian Violet) and Brilliant Green in Fish, U.S. Food and Drug Administration, Laboratory Information Bulletin #4395, 2007. 207 Bio Scientific Co., Austin, TX. Available at http://www.biooscientific.com
338
Sherri B. Turnipseed and Wendy C. Andersen
208 2004 Red Book. United States Department of Agriculture, Food Safety Inspection Service, 2004. Available at http://www.fsis.usda.gov/Science/2004_Red_Book/index.asp 209 National Milk Drug Residue Data Base. Food and Drug Administration, Center for Food Safety and Nutrition, 2004. Available at http://www.cfsan.fda.gov/Bear/milkrp03.html 210 S.A. Tittlemier, J. van de Riet, G. Burns, R. Potter, C. Murphy, W. Rourke, H. Pearce and G. Dufresne, Food Addit. Contam., 24 (2007) 14. 211 European Union Report for 2004 on the Results of Residue Monitoring in Food of Animal Origin in the Member States SANCO/3400/2005, Annex I, 2005. Available at http://europa.eu.int/ comm/food/food/chemicalsafety/residues/workdoc_2004_en.pdf 212 P.D. Patel, Trends Anal. Chem., 21 (2002) 96. 213 G. Cacciatore and M. Petz, Deut. Lebensm.-Rundsch., 101 (2005) 501. 214 S.A. Haughey and G.A. Baxter, J. AOAC Int., 89 (2006) 862. 215 U. Bilitewski, Anal. Chem., 72 (2000) 692A. 216 Biacore, Uppsala, Sweden. Available at http://www.biacore.com 217 P. Bjurling, G.A. Baxter, M. Caselunghe, C. Jonson, M. O’Connor, B. Persson and C.T. Elliott, Analyst, 125 (2000) 1771. 218 S.R. Crooks, G.A. Baxter, M.C. O’Connor and C.T. Elliot, Analyst, 123 (1998) 2755. 219 E. Gustavsson, J. Degelaen, P. Bjurling and A. Sternesjo¨, J. Agric. Food Chem., 52 (2004) 2791. 220 G. Cacciatore, M. Petz, S. Rachid, R. Hakenbeck and A.A. Bergwerff, Anal. Chim. Acta, 520 (2004) 105. 221 J.P. Ferguson, G.A. Baxter, J.D.G. McEvoy, S. Stead, E. Rawlings and M. Sharman, Analyst, 127 (2002) 951. 222 W. Haasnoot, G. Cazemier, M. Koets and A. van Amerongen, Anal. Chim. Acta, 488 (2003) 53. 223 M. Caldow, S.L. Stead, J. Day, M. Sharman, C. Situ and C. Elliot, J. Agric. Food Chem., 53 (2005) 7367. 224 C. Mellgren and A. Sternesjo¨, J. AOAC Int., 81 (1998) 394. 225 V. Dumont, A.C. Huet, I. Traynor, C. Elliott and P. Delahaut, Anal. Chim. Acta, 567 (2006) 179. 226 B. McCarney, I.M. Traynor, T.L. Fodey, S.R.H. Crooks and C.T. Elliott, Anal. Chim. Acta, 483 (2003) 165. 227 J.V. Samsonova, G.A. Baxter, S.R.H. Crooks and C.T. Elliot, J. AOAC Int., 85 (2002) 879. 228 H. Li, P.J. Kijak, S.B. Turnipseed and W. Cui, J. Chromatogr. B, 836 (2006) 22. 229 H.P.O. Tang, C. Ho and S.S. Lai, Rapid Commun. Mass Spectrom., 20 (2006) 2565. 230 U. Koesukwiwat, S. Jayanta and N. Leepipatpiboon, J. Chromatogr. A, 1140 (2007) 147. 231 R. Yamada, M. Kozono, T. Ohmori, F. Morimatsu and M. Kitayama, Biosci. Biotechnol. Biochem., 70 (2006) 54. 232 D.N. Heller, C.B. Nochetto, N.G. Rummel and M.H. Thomas, J. Agric. Food Chem., 54 (2006) 5267. 233 G. Stubbings, J.A. Tarbin, A. Cooper, M. Sharman, T. Bigwood and P. Robb, Anal. Chim. Acta, 547 (2005) 262. 234 B. Delepine and J.P. Moretain, Antibiotic Residues in Milk: LC-MS-MS Confirmation (Identification and Quantification) of Positive Results Obtained with Microbial Inhibitor Screening Tests, Proceedings of the Euroresidue V Conference, Noordwijkerhout, The Netherlands, May 10–12, 2004. 235 S. Smith, C. Gieseker, R. Reimschuessel and M.C. Carson, Multiclass Confirmation of Veterinary Drug Residues in Fish by Liquid Chromatography-Ion Trap Mass Spectrometry, FDA Science Forum, Washington, DC, April 27–28, 2005. 236 K. Granelli and C. Branzell, Anal. Chim. Acta, 586 (2007) 289.
CHAPT ER
11 Analytical Strategies to Control the Illegal Use of Banned Growth Promoters in Meat Producing Animals Bruno Le Bizec, Jean-Philippe Antignac and Gaud Pinel
Contents
1. Introduction 2. Chemical Properties, Health effects 2.1 Stilbenes 2.2 Antithyroid agents 2.3 Steroids 2.4 Resorcylic acid lactones (RALs) 2.5 b-Agonists 3. Analytical Methods 3.1 Steroids 3.2 Corticosteroids 3.3 b-Agonists 3.4 Thyrostats 3.5 Growth hormone 4. Occurrence in Foods 5. Future Trends References
339 340 340 341 341 342 342 342 342 346 348 351 354 357 358 358
1. INTRODUCTION Since 1 January 1989, according to Directive 88/146/EEC replaced later by Directive 96/22/EC [1], the European Commission (EC) prohibits the administering to a farm animal by any means whatsoever of, inter alia, substances having a thyrostatic, oestrogenic or gestagenic action for growth promotion purposes. Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00011-1
r 2008 Elsevier B.V. All rights reserved.
339
340
Bruno Le Bizec et al.
As a result, the use of the hormones oestradiol-17b-testosterone, progesterone, zeranol, trenbolone acetate and melengestrol acetate alone or in combinations for growth promotion purposes in meat production is prohibited. The prohibition covers both the use of these hormones for domestic production and imports from third countries of meat from animals treated with these hormones. The prohibition reflects the fact that the EC chose a level of sanitary protection of accepting no or ‘‘zero’’ additional risk to human health from the residues in meat and meat products of these hormones when used for growth promotion purposes. Even if banned substances are sometimes reduced and summarized to ‘‘hormones’’, the reality is different. In Europe, five classes of compounds are identified in the regulation, as listed in community Directive 96/23/EC: stilbenes (group A1), thyrostats (A2), steroids (A3) including estrogenic, androgenic and progestagenic substances, resorcylic acid lactones (A4) and b-agonistic drugs (A5). The control of growth promoters in meat producing animals is probably one of the most challenging areas in the field of chemical residue control in food, when considering the wide number of target substances, the variability of their chemical structures, their concentration level, as well as the variability of the biological matrix. Main compound families are anabolic steroids, stilbenes, resorcylic acid lactones, corticosteroids, b-agonists and thyrostats, even if some additional groups can be supposed to be already used (ecdysteroids, somatotropine, IGF-I). The complexity of target biological matrices as well as the trace level of residues obliges the Analyst to rely his strategy on analytical methods combining both specificity and sensitivity, respectively. Whereas, Enzyme Linked Immuno Sorbent Assay (ELISA) and Radio Immuno Assay (RIA) are still sometimes used for screening purpose, mass spectrometric methods constitute the obliged strategy during confirmatory processes, technically and strategically speaking. We will focus hereafter on the main strategies followed in the official network of reference laboratories in Europe, and we will develop especially the mass spectrometric approaches used from benchtop technologies to more hyphenated ones for the diagnostic absence/presence, and for the chemical structure determination of metabolites and new unknown compounds introduced onto the black market. Future of the control will be discussed.
2. CHEMICAL PROPERTIES, HEALTH EFFECTS 2.1 Stilbenes The bad reputation of hormones is mainly caused by the harmfulness of diethylstilbestrol (DES). The properties of DES as a growth promoter were discovered in 1954 in the USA. It has been widely used as a feed additive or as an implant into the ear to promote growth and increase feed efficiency in cattle and sheep (until 1979 in the USA). DES is a non-steroidal estrogenic agent which does not occur naturally. The estrogenic effect is mainly ascribed to the same spatial distance of the two OH-groups as for estradiol. Hexestrol and dienestrol are
Strategies to Control the Illegal Use of Banned Growth Promoters
341
synthetic non-steroidal estrogens that are structurally related to DES. Based on their carcinogenity, the EC banned their use in food producing and no residues of these anabolics should be present in animal products imported or produced within the EC (Directive 96/22/EC).
2.2 Antithyroid agents Action of these compounds is characterized by the inhibition of the thyroid gland function causing a decreased production of thyroid hormones, i.e., L-thyroxine (T4) and L-triiodothyronine (T3). Administration of thyrostatic drugs to cattle results in a significant increase in live weight-gain mainly consisting in the development of the gastro-intestinal tract and higher water retention in animal tissue. As a consequence, the meat is characterized by an inferior quality, mostly wet and colourless. Thyrostats can be divided into two main groups: Natural thyrostats. A series of natural products with oxazolidine-2-thiones chemical structures found in plant material in the form of glucosinolates. The 5-vinyl-oxazolidine-2-thione derivative is present in large amounts (up to 1%) in the seeds of Cruciferae (e.g., rapeseed). (2) Synthetic thyrostats. The first group contains thiouracil analogues such as thiouracil (TU), methylthiouracil (MTU), propylthiouracil (PTU) and phenylthiouracil (PhTU). The second group consists of the mercaptoimidazole analogues of which tapazol (TAP) is the most important. All are cheap drugs and readily available on the black market. Classified 2A and 2B by the International Agency for Research on Cancer (IARC), the use of thyrostatic drugs for promoting animal growth is prohibited in all EU member states (Directive 2003/74/EC amending Directive 96/22/EC).
(1)
2.3 Steroids Anabolic steroids can be distinguished according to their chemical structure (C18, C19 or C21) and origin (endogenous or xenobiotic). Apart from their hormonal activity and depending on the compound applied or combination used, anabolic steroids stimulate growth, leading to gain in protein deposition based on an improved food conversion rate. Estrone (E1), estradiol (E2) and estriol (E3) are the main natural estrogens. Only 17b-estradiol is used in anabolic preparations. By esterification of the OH-groups (positions 3 and 17) of 17b-estradiol, compounds with more efficient activity are obtained. Main synthetic estrogens are 17a-ethynylestradiol and mestranol. Testosterone, etiocholanolone, androsterone and 5a-dihydrotestosterone are among the main natural androgens. Esters of 17b-testosterone have been found in anabolic preparations used in meat production. Nandrolone (19-nortestosterone), norethandrolone, trenbolone, 4-chlorotestosterone, fluoxymesterone, 17a-methyltestosterone, stanozolol, boldenone (1-dehydrotestosterone), dianabol (17a-methylboldenone) are some examples of androgenic steroids discovered in the past in Europe for cattle production. Progesterone is the main natural progestagen; semi-synthetic derivatives, such as
342
Bruno Le Bizec et al.
acetate or caproate esters of 17a-hydroxyprogesterone, have already been demonstrated to be used. The most popular synthetic progestagens are medroxyprogesterone acetate, megestrol acetate, melengestrol acetate and chlormadinone acetate. Throughout the EC the use of xenobiotic anabolic agents is prohibited in food producing animals and no residues of these anabolics should be present in animal products imported into or produced within the EC (Directive 96/22/EC).
2.4 Resorcylic acid lactones (RALs) Zeranol has been widely adopted as a growth stimulant with estrogenic activity and is also employed to reduce stress in cattle. Zeranol may also be formed in vivo from the mycotoxins, zearalenone and a-zearalenol, that can be carried over from Fusarium contaminated feedstuff (maize, wheat, barley and oats) to animals. Application of zeranol to cattle has been banned in the European Union since 1985.
2.5 b-Agonists The control of b-agonists misuse received extra attention after outbreaks of food poisoning in 1990 in Spain caused by consumption of bovine liver. This was the first time that pharmacological residues found in slaughtered cattle were found to have caused acute intoxication in consumers. As therapeutic drugs, they have been first used as a bronchodilator for the treatment of pulmonary diseases in humans and animals. b-Agonists act specifically by binding to cell membrane b-receptors, and therefore, by activating the adenylate cyclase-cyclic AMP system. Physiological responses to stimulation of the b-receptors are increased lipolysis and reduced lipogenesis in adipose cells, increased glycogenolysis, increased protein synthesis and reduced proteolysis in striated muscle fibres, and vasodilatation, bronchodilatation and relaxation of smooth muscle fibres. Although clenbuterol is still probably the most popular b-agonist illegally used on farms, other b-agonists have been pointed out on the ‘‘black market’’. b-Agonists belong to the group of arylethanolamines, and can be catalogued in three chemical classes according to their chemical structure: the anilines (e.g., clenbuterol), resorcinols (e.g., terbutaline) and phenols (e.g., salbutamol). Zilpaterol ((7)-trans-4,5,6,7-tetrahydro-7-hydroxy-6-(isopropylamino)imidazo [1jk,4,5]-[1]benzazepin-2(1H)-one) is a new approved b-agonistic drugs (USA, Mexico, South Africa) characterized by a cyclic chemical structure.
3. ANALYTICAL METHODS 3.1 Steroids Monitoring programs to control their use are frequently based on the initial screening of animals for steroid abuse using chemical or immunochemical
Strategies to Control the Illegal Use of Banned Growth Promoters
343
methods [2,3], followed by the complete chemical confirmation of steroids in suspect samples by mass spectrometry (MS) [4–12]. Urine and hair samples are normally ad hoc matrices since they are readily available at both abattoir and farm. Until recently, the standard technique for steroid analysis has been gas chromatography (GC)-MS. This required the derivatization of the steroids using silylation or acylation reactions, depending on the individual properties of the steroid. Liquid chromatography (LC)-MS provides a universal detector, since steroids may be analysed without derivatization. The rules governing screening and confirmation of analytical methods for veterinary drug residues and their validation have been revised by the EU [13]. The rules have been extended to include a number of MS techniques, which have gained in popularity over the past decade, e.g., LC-MS, and acquisition techniques such as high resolution selected ion monitoring (HR-SIM) and selected reaction monitoring (SRM). Today, minimum required performance levels (MRPL) are lower and lower so that competent methods must be more sensitive (pg level), more robust whatever the biological matrix (hair, faeces, urine, tissue, etc.), more specific (HR-MS and tandem MS (MS/MS)) and relevant to challenging analytes such as ecdysteroids, or endogenous steroids. Analytical protocols dedicated to the extraction and purification of anabolic steroids in biological fluids and tissues are generally based on at least two stages. Single use solid-phase extraction (SPE) columns are generally utilized to extract and purify steroids from biological matrices. C18, C8, NH2 and SiOH are amongst the most popular stationary phases; SAX (strong anion exchange) columns are sometimes used for the isolation of steroid conjugates. Solid samples (faeces, hair, tissues, feeding stuff) are preliminary extracted either by accelerated solvent extraction (ASE), soxhlet or liquid–liquid extraction before further purification step(s). Conjugates are usually hydrolyzed either by enzymatic (glucuronidase) or chemical approaches (solvolysis or methanolysis). A digestive juice from Helix pomatia was used in the past for its b-glucuronidase and arylsulfatase activity. However, because a 3b-hydroxysteroid oxidoreductase and a 3-oxosteroid-5,4-isomerase activity have been observed in this formulation, use of H. pomatia is usually avoided in analytical procedures. Bacterial (Escherichia coli) preparations with a pure b-glucuronidase activity and no arylsulfatase activity are now generally accepted for hydrolysis. When GC-MS is used, steroids are quite always derivatized, the most popular approach being the silylation, acylation (acetylation, perfluoroacylation) or oxime formation. N-Methyl-N-(trimethylsilyl)-trifluoro-acetamide (MSTFA) is often used as silylating agent in combination with ammonium iodine (NH4I) or trimethyliodosilane (TMIS) as catalyst, and dithiothreitol (DTE) as antioxidant. When LC-MS is used, derivatization is not mandatory but is sometimes used to enhance the signal or improve the specificity. Standard reference steroids are generally available in Sigma (St Louis, MO, USA), Steraloids (Wilton, NY, USA) and Research Plus (Bayonne, NJ, USA). GC-MS is routinely used for steroid analysis; mass analysers are mainly quadrupoles, but ion trap technologies can be found as well. Single MS is progressively replaced by multidimensional approaches, either by triple
344
Bruno Le Bizec et al.
29 081205004 Sm(Mn, 1x1) 100
20.60 3747
19.86 2222
MRM of 4 Channels CI343 > 343 6.88e4 Area
%
20 18.50 18.75 19.00 19.25 19.50 19.75 20.00 20.25 20.50 20.75 21.00 21.25 21.50 21.75 22.00 22.25
Time
Figure 1 GC-QqQ-MS. Application to the detection of low pg.mL-1 (ppt) of gonadic steroids in children’s blood (2 mL). 17b-estradiol (0.9 ppt) eluted at 19.86 min, 17b-estradiol (1.3 ppt) at 20.60 min (PFB derivatization, negative chemical ionization, SRM acquisition, 343W343).
quadrupole (QqQ) and ion trap (external sources), for steroid analysis. One illustration of the ability of GC-MS/MS (QqQ) approach to bring ad hoc information is given in Figure 1. In this example, gonadic steroid concentrations as low as 0.9 ng L1 were made possible to quantify in limited sample size of blood (2 mL). High resolution-mass spectrometers (HR-MS) are mainly electromagnetic instruments operated at resolution equal or better than 10,000 (10% valley); they are used in confirmatory processes (control laboratories) or more generally when both sensitivity and specificity are needed. HR-MS approaches are possible nowadays on orbital ion trap systems as well at higher resolution values. One illustration of the signal specificity offer by this kind of analyser is given in Figure 2. Two isotope ions of boldenone sulphate are shown on a mass spectrum recorded after negative electrospray ionization (ESI) and full scan acquisition at a resolution better than 70,000. A tremendous separation of C19H25O5S and C13 18C1H25O5S species was made possible. In recent years, gas chromatography combustion isotope ratio mass spectrometry (GC-C-IRMS) has been developed to trace the origin of steroids (endogenous versus exogenous). This technique made it possible to discriminate exogenous testosterone/estradiol metabolites from endogenous ones, by measuring the 13C/12C ratio of the steroids [14–15]. Eluted compounds from the GC are combusted in a catalytic furnace to N2 and CO2. For the carbon isotope ratio determination, masses 44 and 45 are determined with great precision and accuracy. The measured carbon isotope ratio (13C/12C sample) is related to an international fossil carbonate standard ‘‘Pee Dee belemnite’’ or ‘‘PDB’’. This approach is already used in a few National Reference Laboratories in Europe for official controls. In all cases (low resolution-mass spectrometry (LR-MS), HR-MS, C-IRMS) capillary columns are preferred; typical dimensions are 30 m 0.25-mm i.d., 0.25-mm film thickness. Stationary phases are non-polar to medium polar. Helium (n55) is used as carrier gas at 1 mL min1. Injector and transfer line temperatures are set at high values, 2501C and 2801C, respectively.
Strategies to Control the Illegal Use of Banned Growth Promoters
345
041006002 #8 RT: 0.11 AV: 1 NL: 9.49E4 T: FTMS-p ESI Full ms [350.00-370.00] 365.14282 R=69901 z=1 32 C19H25O5 S1 100 95 90 85 80 75 70 Relative Abundance
65 60 55 50 45 40 35 30
366.14612 R=67804 z=1 13 32 C18 C1H25O5 S1
25 20 15 365.34247. R=69500 z=?
10 5 0 364.0
364.5
365.0
365.5 m/z
366.0
366.5
Figure 2 LC-HR-MS. Application to determination of the elemental composition of steroid conjugates (the example of boldenone sulphate is given). The ionization was performed in the negative ESI mode, and full scan acquisition mode was used at RW70,000. m/z 365.1428 corresponds to C19H25O5S and 366.1461 to C13 18C1H25O5S.
LC is either coupled to QqQ analyser or ion trap detectors (but at least in the MS/MS or multiple stages mass spectrometry (MSn) mode) operated in the positive or negative (steroid conjugates) ESI mode. Atmospheric pressure chemical ionization (APCI) or atmospheric pressure photon ionization (APPI) is preferred for non-polar steroids such as progestagen esters or estrogens, respectively. Reversed-phase LC is generally performed on octadecyl (or octyl) grafted silica stationary phase (e.g., 50 2 mm, 5 mm) equipped with a guard column (e.g., 10 2 mm, 5 mm). Elution solvents are based on methanol or acetonitrile and 0.5% (v/v) acetic acid in water. N2 is used as nebulization and desolvation gas. Potentials applied onto the capillary (from 3 to 4 kV), cone (from 15 to 35 V) and collision cell (from 5 to 30 V) are significantly different from one steroid group to another; the parameters have to be optimized for each class of compounds. One illustration is given on steroid conjugates (Figure 3); reversed-phase LC permitted the separation of 17b-boldenone sulphate and 17b-boldenone sulphate. Negative ESI offered a good specificity regarding boldenone metabolite spectrometric signals combined with a good sensitivity, thus authorizing the low ppt level detection of these two steroid sulphates in the urine sample.
346
Bruno Le Bizec et al.
020306025 Sm (SG, 2x1) 100
MRM of 6 Channels ES365,3 > 177,1 1,33e3
9,02 9,23
% 0 020306025 Sm(SG, 2x1) 100
9,049,23
MRM of 6 Channels ES365,3 > 97 6,23e3
9,02
MRM of 6 Channels ES365,3 > 97 5,91e3
% 0 020306025 Sm(SG, 2x1) 100
9,23 % 0 2,00
4,00
6,00
8,00
10,00
12,00
14,00
16,00
18,00
Time 20,00
Figure 3 LC-QqQ-MS. Application to the direct detection of steroid conjugates (the example of boldenone sulphate is given). The ionization was performed in the negative ESI mode; the SRM acquisition mode was selected. 17b-boldenone eluted at 9.02 min, and 17s-boldenone at 9.23 min.
3.2 Corticosteroids Fifty years after the discovery of natural corticosteroid hormones and their antiinflammatory properties, many synthetic derivatives of these molecules are today available. Their legal utilization in human and veterinary medicine is strictly regulated, with withdrawal periods between treatment and slaughtering and maximal residue levels in edible biological matrices for some compounds. These substances have been also illegally used as growth promoters in cattle, whereas these practices are not allowed in Europe. Indeed, low concentrations of glucocorticosteroids are known to increase weight-gain, reduce feed conversion ratio, and have a synergetic effect with other molecules such as b-agonists or anabolic steroids [16–18]. For many years, various analytical methods have been proposed for the identification of corticosteroid residues in various biological matrices. During the 1980s and early 1990s, the main detection methods used for corticosteroids were radioimmunology [19,20], fluorimetry [21,22] or LC with UV detection [23–27]. Nowadays, MS coupled to GC or LC is the method of choice for the unambiguous identification of these compounds at trace level in biological matrices. GC-MS with electronic impact ionization (EI) was the first MS technique to be applied for these compounds [28–38]. GC-C-IRMS was also used to distinguish natural endogenous corticosteroids from their exogenous analogues [39]. But the further development of LC-MS [40–43] and LC-MSn [44–53] with atmospheric pressure ionization (API) techniques permitted significant improvements in terms of sensitivity and specificity, as well as kinetic and metabolism studies [54]. The recently introduced ultra performance/fast LC systems should be an ultimate reason for considering now LC-MSn as the actual standard for corticosteroid analysis. Due to the moderate polarity of corticosteroids, their gas-chromatographic analysis requires preliminary derivatization step in order to increase their
Strategies to Control the Illegal Use of Banned Growth Promoters
347
volatility and avoid adsorption phenomenon. The most currently used techniques remain chemical oxidation followed by negative chemical ionization in MS, or silylation followed by positive electron ionization. Mixtures such as MSTFA/TMIS/DTE lead to mixtures of tri- to penta-TMS derivatives, unstable under EI conditions, and then leading to weak molecular ions and to a high number of fragment ions, and finally to a limited sensitivity. Alternatives to this derivatization strategy have been proposed, as for instance mixed oxime-TMS derivatives [55]. Another route is the use of boronic esters. This technique was widely used for a-g diol steroids, and consists of the action of methylboronic acid/ethylacetate followed by silylation. The derivative is stable and intense molecular ions for a-g diol compounds are observed even under EI conditions. However, its main disadvantage remains once again an insufficient sensitivity for the analysis of trace residue levels in complex biological matrices. Amongst the most popular approaches, the elimination of the polar C17 side chain by chemical oxidation and subsequent oxidation of residual hydroxyl made indeed corticosteroid analysis possible and efficient by GC approaches. This technique was the most currently used before the development of LC-MS systems. When LC is used, direct measurement of corticosteroids is then possible. The LC separation is significantly worse than the one observed in GC. However, when MS/MS is used, co-elution of corticosteroids is not a problem anymore. The recent development in chromatography (resolutive and fast) increased the number of theoretical plates, and thus authorized the chromatographic separation of corticosteroids with very close chemical structure. ESI as well as APCI is clearly well adapted for corticosteroids. Under slightly acidic conditions, these relatively polar compounds give an intense pseudomolecular ion [M+H]+ in ESI+ and an adduct with the conjugated base of the used organic acid [M+base] in ESI [56]. These diagnostic ions are suitable to be selected as precursor ions for further fragmentation in MS2. In ESI+, some numerous but not very specific fragment ions can be observed, which correspond to losses of water molecules and/or halogen atoms, as well as some other minor cleavages within the B and C rings. In ESI, the fragmentation is reduced to two ions; the pseudo-molecular ion [M–H] and the fragment corresponding to a cleavage of the side chain with loss of formaldehyde [M–CH2O–H]. This fragmentation pathway appears extremely efficient for measurement of a large number of corticosteroids at trace residue levels in biological matrices. An illustration is given in Figure 4 for liver extracts spiked with 1.5 ng g1 of fluocinolone acetonide; one can appreciate the great improvement both in terms of sensitivity and specificity when using MS/MS approach (QqQ). Moreover, if additional diagnostic ions are required, a high cone potential inducing the in-source fragmentation of the [M+base] ion can be used to select the resulting [M–CH2O–H] fragment as precursor; this ion can be further fragmented in the collision cell. Finally, the APCI techniques operating in the negative mode represent today the technique of choice for the ionization and fragmentation of corticosteroids because of its better sensitivity and specificity compared to all other ionization techniques. The chromatographic separation of isomers such as dexamethasone and dexamethasone may remain an ultimate analytical
348
Bruno Le Bizec et al.
110902012 100 m/z=511
21.37
SIR of 11 Channels ES511 5.94e4
17.98 17.51 16.79 % 15.35 15.82
10 110902011 511>393 100
8.28
MRM of 28 Channels ES 511 > 393 7.65e3
%
4
Time 2.00
4.00
6.00
8.00
10.00 12.00 14.00 16.00 18.00 20.00 22.00 24.00 26.00 28.00
Figure 4 Comparison of the spectrometric signal specificity after LC-MS and LC-MS/MS analysis [liver sample spiked with 1.5 ng g1 fluocinolone acetonide (RT ¼ 8.28 min)]. Negative ESI was used as ionization mode and SRM was used as acquisition technique.
challenge. Some specific stationary phases are today available permitting this separation. But the relative intensities of diagnostic ions produced in ESI can be another way to distinguish these two isomers, using conventional model [57] of multidimensional statistical approach [58].
3.3 b-Agonists b-agonists, the so-called b-sympathomimetics, are characterized by their structural and pharmacological properties, which are very close to those of catecholamines. These drugs are used as bronchodilators, tocolytics or heart tonics in human and veterinary medicine. During the past 20 years, several studies focused on the effects of such synthetic molecules on growth rate and performances, when administered per os, mixed with feedingstuffs. From 1984, it was pointed out that a specific b-agonist, the so-called clenbuterol, was able to increase notably the protein-to-fat ratio [59–62] in athletes and meat producing
Strategies to Control the Illegal Use of Banned Growth Promoters
349
animals. In the following years, these properties were also emphasized for other b-agonists such as cimaterol, ractopamine and fenoterol. Because of their ability to shift nutrients towards protein instead of lipid anabolism, such molecules were gathered under the generic name of ‘‘repartitioning agents’’ [63]. Basic knowledge on b-agonists concerns mainly the previously mentioned substances [64]. Although b-agonistic drugs have never been licensed for growth promoting purposes, their use as growth promoters appeared to spread to a large extent, especially in livestock. Since toxicological data on such pharmacological manipulations are lacking, their addition to animal feed has been forbidden within the European Union Member States. Furthermore, the illegal use of b-agonists was revealed to be of major concern for public health and some food poisoning cases were reported [65]. Faced with such problems, analytical techniques designed for the unambiguous detection and identification of b-agonists in biological matrices has been developed. Among the available techniques (e.g., thin-layer chromatography (TLC), radioimmunoassay (RIA), enzyme-linked immunosorbent assay (ELISA), high-performance LC (HPLC), infrared (IR) spectrometry), MS appeared to be the most efficient tool to provide results which are sensitive and specific enough to allow enforcement action. Consequently, several methods based on MS instrumentation have been set up, among which GC-MS and LC-MS often reinforced by MS/MS or HR-MS configurations are recognised today as the most powerful approaches. Concerning GC-MS techniques, trimethylsilylation or tert-butyldimethylsilylation are commonly used derivatization methods. However, when analysed under electron ionization conditions, these derivatives are well known to give very poor informative data (especially for clenbuterol-like compounds) and their use usually does not permit the identification of residues (according to official required quality criteria) below the 1 ng mL1 or ng g1 level in biological matrices. Consequently, other analytical tools based on different derivatives and/or ionization modes have been set up, notably for confirmatory purposes. Cyclic boronic derivatives [66–68] were shown to give far more informative data when analysed by means of GC-MS after EI ionization. In addition, 2-dimethylsilamorpholine, the so-called cyclic dimethylsilylmethylene derivatives [69] also proved to be of major interest for the confirmation step. Unfortunately, these cyclic derivatizations are useful for clenbuterol-like compounds but not easily feasible for b-agonists containing additional hydroxy substituent(s). Therefore, silylated (or cyclic) derivatives may be analysed as well in the positive chemical ionization (PCI) mode. If GC-MS instruments were historically the more widely used for various classes of residues, LC-MS today appears as the method of choice and the major actual investment for many laboratories, especially for the analysis of polar compounds. Undoubtedly, reversed-phase LC and positive ESI is nowadays the method of choice for most b-agonistic drugs as shown on Figure 5, where an incurred retina sample (100 mg) collected in an animal treated with ractopamine is shown. Even seven days after the end of the treatment, ractopamine can be detected and quantified on the basis of at least four transitions.
350
10.45;3013
MRM of 3 Channels ES+ 302 > 150 3.42e3 Height
%
9 VR-CO 100
8.64;18233
MRM of 3 Channels ES+ 302 > 164 1.87e4 Height
%
2 VR-CO 100
10.45;31670
MRM of 3 Channels ES+ 302 > 284 3.23e4 Height
8.64 24049
%
Time
1 2.00
4.00
6.00
8.00
10.00
12.00
14.00
16.00
18.00
20.00
Figure 5 LC-MS/MS ion chromatogram of an incurred pig retina sample, seven days after the end of the animal treatment by ractopamine. Positive ESI was used as ionization mode and SRM as acquisition technique. Retention time of ractopamine was 8.64 min, isoxsupinrine was used as internal standard (RT ¼ 10.45 min).
Bruno Le Bizec et al.
VR-CO 100
Strategies to Control the Illegal Use of Banned Growth Promoters
351
3.4 Thyrostats Most of known thyrostats or thyroid-inhibiting compounds are thionamides which are small molecules derived from TU or mercaptoimidazole. These substances show a goitrogen activity, thanks to their thiocarbamide group which inhibits the normal metabolism of the thyroid gland and causes a decreased production of thyroid hormones. The consequent hypothyroidism increases the growth rate of the animal although the observed weight-gain is mainly the result of water absorption and retention within edible tissue as well as filling of the gastro-intestinal tract [70–71]. Consequently, for several years during the 1980s, these substances have been employed as additives in animal feeds to increase the weight of cattle prior to slaughter; especially the use of MTU with a 5-g/day/animal dose for 30 days was widespread. The consequence of such abuse is not only the production of inferior meat quality (meat may be exudative), but overall the potential risk to human health of drug residues. Consumption of meat contaminated with thyrostats has caused an increased incidence in Spain of aplasia cutis, a characteristic scalp defect [72]. For these particular reasons, thyrostats have been banned within the European Union since 1981 (Directive 81/602/EC) [73] for animal production. These compounds have indeed been classified by IARC as belonging to group 2B that represents carcinogenic and teratogenic compounds. Different techniques have been developed in order to control the illegal use of such compounds in meat producing animals. Thyrostats are challenging compounds to analyse for several reasons linked to their chemistry. The first difficulty concerns their extraction from biological matrices in which they occur through six different tautomeric forms due to the delocalization of the p electrons on the ring structure. The second difficulty, when separated onto reversed-phase LC, is due to their high polarity that prevents a good retention and separation of these compounds on the stationary phase. Finally, the analysis by MS of these small molecular weight analytes (100–200 u) is not satisfactory in term of sensitivity (signal-to-noise ratio) since the signals are usually disturbed by the chemical noise, as illustrated by Blanchflower and co-workers [74]. These difficulties might be overcome thanks to derivatization procedures placed at the beginning of the protocol and occurring as nucleophilic substitution with halogenated compounds. The aims of the derivatization are numerous and include the stability of the compounds, the reduction of their polarity to improve their separation as well as the increase of their molecular weight to allow lower detection capabilities and limits of decision. Different derivative reagents have been studied and compared, such as pentafluorobenzylbromide (PFBBr), iodobenzylbromide (IBBr) and bromobenzylbromide (BrBBr). Thyrostats were first studied with colorimetric methods based on the reactivity of thiol or thione groups, with for example 2,6-dichloroquinonechloroimide or 7-chloro-4-nitrobenzo-2-oxal-1,3-diazole (NBD-Cl) [75,76]. Various techniques have been described in the literature for the detection of administration of thyrostats to animals. These range from weight measurement
352
Bruno Le Bizec et al.
of the thyroid gland [77] to various methods based on TLC [78–80], GC using nitrogen–phosphorus detection, flame photometric detection, or MS detection [81–82] and HPLC using either UV [83] or electrochemical detection [84]. More recently, methods based on LC coupled to MS have been published. Detection performances of the different published methods were 50 mg/L in urine using GC-MS, 20 mg kg–1, for six different thyrostats, in thyroid samples using LC-MS/MS [85] and 25 mg kg–1 in muscle with a GC-MS/MS detection [86]. More recently, a detection protocol performed in MS2 by LC-MS/MS (QqQ) after negative ESI was set up [87]. The protocol has been successfully applied to biological matrices (urine, tissues, faeces and hair) (Figure 6) and the multiresidue method was validated according to the EU criteria (2002/657/EC Decision) leading to improved performances of identification and quantification (mg L1 range). Thyrostats are also easily analysed in MS2 by GC tandem quadrupole MS/MS after electron ionization (Figure 7) [88,89]. Reliable, sensitive and specific methods, mandatory based on MS, have been set up to ensure efficient control of their illegal use. The newly developed protocols exhibit performances allowing detection and identification of the thyrostatic compounds in biological fluids and edible tissues in the mg kg1 or mg L1 range which is in accordance with the requirements of the European
259>42
BPTU (IS) 14.90 min
343>95
Standard sample
343>58 343>42
TU 11.84 min
343>127
259>42
BPTU (IS) 14.90 min
343>95
Urine sample
343>58 343>42
TU 11.84 min
343>127
Figure 6 SRM ion chromatograms for (a) standard sample (BPTU 50 mg L1 and TU 10 mg L1) and (b) urine sample (derivatized with IBBr and LC(ESI-)MSMS analysis).
J14 + TU 050506003 100
2: MRM of 5 Channels EI+ 368 > 241 2.37e4
13.18
368>241 % 4 13.19
2: MRM of 5 Channels EI+ 368 > 213 2.39e4
13.19
2: MRM of 5 Channels EI+ 368 > 168 5.00e4
13.19
2: MRM of 5 Channels EI+ 368 > 256 1.03e5
13.19
2: MRM of 5 Channels EI+ 368 > 335 2.39e5
368>213 % 4 050506003 100
368>168 % 2 050506003 100
368>256 % 1 050506003 100
368>335 % 0 10.00
Time 10.50
11.00
11.50
12.00
12.50
13.00
13.50
14.00
14.50
Figure 7 Urine sample spiked with TU (10 mg L1) (3-BrB/TMS derivative), GC(EI+)MSMS analysis, SRM acquisition
Strategies to Control the Illegal Use of Banned Growth Promoters
050506003 100
353
354
Bruno Le Bizec et al.
Union regarding the provisional MRPL suggested at 100 mg L1. Since high urine concentrations of residues (WW 100 mg L1) are generated upon drug administration aimed at increasing animal weight, methods currently running in laboratories enable efficient control of the illegal use of thyrostats. However, the occurrence of TU in bovine urines from national monitoring plans with quantifications in the range 1–10 mg L1 occasionally rises the question of its origin which might either be the consequence of an illegal administration or the result of an ‘‘endogenous’’ production. Until now, the identification of TU in animal biological matrices is systematically interpreted as the consequence of an illegal administration. Recent studies however [90,91] achieved an independent and confident identification (LC(ESI)MSMS, GC(EI+)MSMS and HR-MS (EI and NCI) measurements) of TU in bovine urine samples collected on animals never treated with any thyrostatic drugs and the demonstration of a relationship between a diet based on cruciferous and the occurrence of TU in urine. This result is of prime importance for laboratories and risk managers involved in the field of forbidden growth promoters control as evidence for presence of TU residue has to be carefully considered as a non-systematic proof of illegal administration.
3.5 Growth hormone Growth hormone (GH), also known as somatotropin (ST), is a 22-kDa protein naturally produced by the anterior pituitary gland. STs are important factors influencing metabolic and somatogenic processes including growth, immune function, reproduction and lactation in mammals [92–95]. It was known as early as the 1930s that the injection of dairy cows with pituitary extracts increased milk yield [96]. GHs are widely used outside Europe to stimulate milk production in dairy cows and as a general growth promoter in pigs [97]. Human GH is also thought to be widely abused in human sports since the increase in muscle size and strength makes them a viable alternative to anabolic steroids [98,99]. Recombinant DNA techniques allow the production of large quantities of recombinant GHs which may exhibit slightly different chemical structures from the pituitary ST, by adding a number of amino acids on the N-terminal side. Indeed, various forms of recombinant somatotropins (rSTs) with slightly different N-terminal sequences have been produced by several companies and described in literature [100]. Recombinant bovine and porcine STs, legally used in the USA since the approval by the Food and Drug Administration (FDA) in 1994 and in other countries, are banned in the European Union [101,102], for animal welfare and food safety reasons. Nevertheless, and because of widespread application, the illegal distribution and use cannot be excluded within the EC [103,104], putting a strong demand on the availability of screening and confirmatory analysis methods for rSTs. Until now, the detection of GH in plasma, milk and tissues has been based on RIAs and ELISA procedures allowing for quantification in the range 10–20 mg L1 [105–111], biosensor based methods have also been reported recently for the detection of STs in concentrated injection preparations [112]; however, none of
Strategies to Control the Illegal Use of Banned Growth Promoters
355
these methods allowed distinguishing between the endogenous and the rSTs since one of the challenging aspects in the detection of rST abuse is the high level of similarity between the endogenous, native hormone, and exogenous, synthetic recombinant hormone. New strategies intended to discriminate between endogenous and recombinant bovine ST have been set up. In this context, MS measurements with soft ionization modes such as ESI and matrix-assisted laser desorption (MALDI) adapted to proteins have been successfully reported for pure ST solutions. STs identification is either performed after accurate mass determination of the entire molecule (Figure 8) or after tryptic digestion and identification of the characteristic N-terminal end from the recombinant form (Figure 9) [113,114]. However, GH extraction and analysis from biological samples in order to investigate the potential misuse of rSTs encountered difficulties linked to the trace level (mg L1) at which the ST is present within matrices such as milk and blood [115]. Recently, however, a method based on appropriate equine plasma sample preparation, tryptic digestion and subsequent N-terminal MS measurements allowed for the detection of recombinant equine ST in horses treated with the molecule (Figure 10) [116]. This study is the first ever reported in the field and is very promising for the future and its application in the anti-doping and food safety controls. Indirect approaches to prove rST treatments have also been reported. They exploit circulating molecules that can be considered as analytical targets and indirect indicators of the treatment. Therefore, biomarkers of GH action are being investigated as potential test for GH abuse. Both insulin-like growth factor A17;1287.8 A16;1368.1
100
A19 1152.3 A20 1094.6
%
A15 1459.3
A21 1042.5 A14 1563.5
994.8
A13 1683.7 1823.4
0 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000
Figure 8 Example of positive ESI mass spectra of Monsanto recombinant bovine ST. Calculated mass is 21,815 Da.
356
Bruno Le Bizec et al.
0702003 100
Scan ES+ 913 1.00Da 1.41e6
78.61 2+
[M+2H]
913
%
0 0702003 100
Scan ES+ 1825 1.00Da 1.95e5
78.51
78.72 [M+H]
%
+
103.73 103.42
1825
104.95
103.12
102.51 0 0702003 100 0.13
Scan ES+ TIC 8.54e6
92.95 78.61
TIC 9.48 11.72
96.00
% 22.09 37.03 27.27 37.85 25.75 30.22 19.75
48.83 48.01
54.93
79.73 87.26 88.48
72.51
63.16
70.89
77.39
4
Time 10.00
20.00
30.00
40.00
50.00
60.00
70.00
80.00
90.00
100.00
Figure 9 HPLC-ESI ion chromatograms of characteristic N-term peptide extracted from the total ion current (TIC) chromatograms of recombinant bovine GH after trypsin treatment.
Figure 10 HPLC-ESI ion chromatograms of N-term peptide fragments of recombinant equine somatotropin (reST) in equine plasma 3 h after reST administration.
I (IGF-I) and insulin-like growth factor binding protein-3 (IGFBP-3) have been reported as suitable markers as they are notably under GH control and their concentrations increase after rST administration [117,118]. Their quantification has already been reported either by the use of specific immunoassays [119,120] or MS [121]. In horses, a threshold value was set at 800 ng mL1 for IGF-I in plasma above which a sample is considered as suspicious for GH abuse.
Surface Plasmon Resonance
Strategies to Control the Illegal Use of Banned Growth Promoters
357
220 170 120 70 20 -30 -10
40
90
140
190
Days
Figure 11 Kinetic of antibodies raised against reST in equine plasma from a horse treated with reST at day 0. Measurements with a biosensor immunoassay based on the Surface Plasmon Resonance (SPR) technology.
Detection in serum of antibodies raised against GHs as a consequence of their administration to animals has also been successfully reported as a long-term approach for the detection of GH abuse [122–126]. Immunological techniques such as ELISA [127], Western-Blot [128] or biosensor based immunoassays [127] have allowed for screening of administrated animals over several months (Figure 11).
4. OCCURRENCE IN FOODS As laid down in Article 8 of Directive 96/23/EC, the Commission shall report to Member States within the Standing Committee on the Food Chain and Animal Health on the outcome of the checks carried out, in particular on the implementation of the national plans and on the developments in the situation in the various regions of the Community. The aim of the annual report is to summarize the results of the national residue monitoring plans in the Member States. Report for 2005 on the results of residue monitoring in food of animal origin in the Member States includes around 780,163 (871,000 in 2004) samples for residue control in all food commodities. For hormones (steroids and zeranol derivatives), 0.13% (0.12% in 2004 and 2003) of the samples taken in bovines were found to be non-compliant and 0.44% in pigs (0.3% in 2004), mainly due to the presence of presumed endogenous nandrolone and contamination with the metabolite zearalenone. Whereas, no non-compliant results for antithyroid agents were reported from 2000 to 2004, 8 non-compliant were reported for thyrostatic agents in bovine in 2005 (mainly TU). The finding was enabled by improving the performance of the analytical methods used for the analysis lowering the limit of detection from 50 to 1 ppb, and caution should be taken regarding the origin of these thyrostat residues as explained before in this chapter. No non-compliant samples for stilbenes have been found in 2004 and 2005 in Europe. The number of non-compliant results for corticosteroids in bovines varied over the years from
358
Bruno Le Bizec et al.
186 in 2005 to 64 in 2004, and 130 in 2003; dexamethasone was the most frequently found substance for corticosteroids. For b-agonists, the incidence of non-compliant results increased from 0.02% of the bovines analysed in 2003 to 0.06% in 2004 and 0.08% in 2005.
5. FUTURE TRENDS Since the beginning of the implementation of the control laboratory network in Europe, chromatography coupled to MS was implemented increasingly especially in the field of growth promoters in food producing animals. Noncompliant samples are not disputed nowadays, the risk of false positives being extremely low especially when MS/MS or HR-MS techniques are used. Moreover, because of their sensitivity, MS techniques authorize the demonstration of an illegal use far away from the treatment. The remaining challenge is rather linked to the fishing of unknown anabolic compounds potentially used on the black market. The current tendency consists of on-line measurement of biological extracts by biological tests (estrogenic or androgenic receptors for instance) and parallel mass spectrometric characterization of the suspected anabolic steroid by accurate mass determination and fragmentation study on orbital ion trap or hybrid quadrupole-time of flight instruments (QqTOF).
REFERENCES 1 Commission of the European Communities, Council Directive 96/22/EC, Off. Eur. Commun. Legis., L125 (1996) 3. 2 M.L. Scippo, P. Gaspar, G. Degand, F. Brose, G. Maghuin-Rogister, P. Delahaut and J.P. Willemart, Anal. Chim. Acta, 275 (1993) 57. 3 F. Smets, H.F. De Brabander and G. Pottie, Archiv. fur Lubensmittelhygiene, 48 (1997) 25. 4 G. Van Vyncht, P. Gaspar, E. DePauw and G. Maghuin-Rogister, J. Chromatogr., 683 (1994) 67. 5 H.F. De Brabander, P. Batjoens, D. Courtheyn, J. Vercammen and K. De Wasch, J. Chromatogr. A, 750 (1996) 105. 6 E. Daeseleire, R. Vandeputte and C. Van Peteghem, Analyst, 123 (1998) 2595. 7 A.M.M. Stolker, P.W. Zoontjes and L.A. van Ginkel, Analyst, 123 (1998) 2671. 8 E. Daeseleire, A. de Guesquie`re and C. van Peteghem, J. Chromatogr., 562 (1991) 673. 9 L.A. van Ginkel, R.W. Stephany, H.J. van Rossum, H.M. Steinbuch, G. Zomer, E. van de Heeft and P.J.M. de Jong, J. Chromatogr., 489 (1989) 111. 10 S. Hartmann and H. Steinhart, J. Chromatogr. B, 704 (1997) 105. 11 B. Le Bizec, M.P. Montrade, F. Monteau and F. Andre´, Anal. Chim. Acta, 275 (1993) 123. 12 P. Marchand, B. Le Bizec, C. Gade´, F. Monteau and F. Andre´, J. Chromatogr. A, 867 (2000) 219. 13 Commission Decision of 12 August 2002 implementing Council Directive 96/23/EC concerning the performance of analytical methods and the interpretation of results-2002/657/EC. Off. Eur. Commun. Legis., L 221 (2002) 8–36. 14 V. Ferchaud, B. Le Bizec, F. Monteau, M.P. Montrade and F. Andre´, Analyst, 12 (1998) 2617. 15 V. Ferchaud, B. Le Bizec, F. Monteau and F. Andre´, Rapid Commun. Mass Spectrom., 14 (2000) 652. 16 J.P. Duchatel, J.M. Beduin, T. Jauniaux, F. Coignoul and H. Vindevogel, Ann. Med. Vet., 137 (1993) 557. 17 L. Istasse, V. De Haan, C. Van Eenaeme, B. Buts, P. Baldwin, M. Gielen, D. Demeyer and J.M. Bienfait, J. Anim. Physiol. Anim. Nutr., 62 (1989) 150.
Strategies to Control the Illegal Use of Banned Growth Promoters
359
18 M.L.J. Rijckaert and H.P.J. Vlemmix, The growth promoting effect of glucocorticosteroids, Department of chemical engineering, Eindhoven University of Technology, Eindhoven, The Netherlands, 1992. 19 S. Calvarese, P. Rubini, G. Urbani, N. Ferri, V. Ramazza and M. Zucchi, Analyst, 119 (1994) 2611. 20 S.M.R. Stanley, B.S. Wilhelmi and J.F. Rodgers, J. Chromatogr., 620 (1993) 250. 21 E. Neufeld, R. Chayen and N. Stern, J. Chromatogr. B, 718 (1998) 273. 22 K.E. Vanoosthuyze, L.S.G. Van Poucke and A.C.A. Deloof, Anal. Chim. Acta, 275 (1993) 177. 23 B.E. Cham, B. Sadowski, J.M. O’Hagan, C.N. De Wytt, F. Bochner and M.J. Eadie, Ther. Drug Monit., 2 (1980) 373. 24 E.P. Diamandis and M. D’Costa, J. Chromatogr., 426 (1988) 25. 25 E.T. Mallinson, J.S. Dreas, R.T. Wilson and A.C. Henry, J. Agric. Food Chem., 43 (1995) 140. 26 L.G. McLaughlin and J.D. Henion, J. Chromatogr., 529 (1990) 1. 27 P. Volin, J. Chromatogr. B, 671 (1995) 319. 28 T.A. Baillie, C.J.W. Brooks and B.S. Middleditch, Anal. Chem., 44 (1972) 30. 29 D. Courtheyn, J. Vercammen, H. De Brabander, I. Vandenreyt, P. Batjoens, K. Vanoosthuyze and C. Van Peteghem, Analyst, 119 (1994) 2557. 30 D. Courtheyn, J. Vercammen, M. Logghe, H. Seghers, K. De Wash and H. De Brabander, Analyst, 123 (1998) 2409. 31 T. Furut, N. Eguchi, H. Shibasaki and Y. Kasuya, J. Chromatogr. B, 738 (2000) 367. 32 T. Furut, T. Namekawa, H. Shibasaki and Y. Kasuya, J. Chromatogr. B, 706 (1998) 181. 33 J. Girault, B. Istin and J.B. Fourtillan, Biomed. Environ. Mass Spectrom., 19 (1990) 295. 34 G.R. Her and T.J. Watson, Biomed. Environ. Mass Spectrom., 13 (1986) 57. 35 O. Huetos Hidalgo, M. Jimenez Lopez, E. Ajenjo Carazo, T.B.A. San Andres Larrea and T.B.A. Reuvers, J. Chromatogr. B, 788 (2003) 137. 36 K. Minagawa, Y. Kasuya and S. Baba, J. Chromatogr., 343 (1985) 231. 37 L.M. Thienpont, V.I. De Brabendere, D. Sto¨ckl and A.P. De Leenheer, Anal. Biochem., 234 (1996) 204. 38 B.K. Yap, G.A. Johnston and R. Kazlauskas, J. Chromatogr., 573 (1992) 183. 39 R. Aguilera, M. Becchi, L. Mateus, M.A. Popot, Y. Bonnaire, H. Casabianca and C.K. Hatton, J. Chromatogr. B, 702 (1997) 85. 40 T. Cairns, E.G. Siegmund, J.J. Stamp and J.P. Skelly, Biomed. Mass Spectrom., 10 (1983) 203. 41 P. Gaignage, G. Lognay, M. Marlier, M. Severin and P. Dreze, Chromatographia, 28 (1989) 623. 42 G.M. Rodchenkov, V.P. Uralets, V.A. Semenov and P.A. Leclercq, J. High Res. Chrom. Commun., 11 (1988) 283. 43 H. Shibasaki, T. Furuta and Y. Kasuya, J. Chromatogr. B, 692 (1997) 7. 44 J.P. Antignac, B. Le Bizec, F. Monteau, F. Poulain and F. Andre´, Rapid Commun. Mass Spectrom., 14 (2000) 33. 45 F. Be´valot, Y. Gaillard, M.A. Lhermitte and G. Pe´pin, J. Chromatogr. B, 740 (2000) 227. 46 G. Brambilla, F. Buiarelli, G.P. Cartoni, F. Coccioli, C. Colamonici, A. Fagiolo, C. Giannini and B. Neri, J. Chromatogr. B, 755 (2001) 265. 47 K. De Wasch, H. De Brabander, D. Courteyn and C. Van Peteghem, Analyst, 123 (1998) 2415. 48 R. Draisci, C. Marchiafava, L. Palleschi, P. Cammaratta and S. Cavalli, J. Chromatogr. B, 753 (2001) 217. 49 M. Fiori, M.E. Pierdominici, F. Longo and G. Brambilla, J. Chromatogr. A, 807 (1998) 219. 50 M. O’Keeffe, S. Martin and L. Regan, Anal. Chim. Acta, 483 (2003) 341. 51 P.W. Tang, W.C. Law and T.S.M. Wan, J. Chromatogr. B, 754 (2001) 229. 52 O. Van den Hauwe, F. Dumoulin, J.P. Antignac, M.P. Bouche, C. Elliott and C. Van Peteghem, Anal. Chim. Acta, 473 (2002) 127. 53 O. Van den Hauwe, M. Schneider, A. Sahin, C.H. Van Peteghem and H. Naegeli, J. Agric. Food Chem., 51 (2003) 326. 54 M.C. Dumasia, E. Houghton, M.S. Moss, J. Chakraborty and V. Marks, J. Ster. Biochem., 25 (1986) 547. 55 E. Houghton, P. Teale, M.C. Dumasia and J.K. Wellby, Biomed. Mass Spectrom., 9 (1982) 459. 56 Y. Kim, T. Kim and W. Lee, Rapid Commun. Mass Spectrom., 11 (1997) 863. 57 K. De Wasch, H.F. De Brabander, M. Van de Wiele, Y. Vercammen, D. Courtheyn and S. Impens, J. Chromatogr. A, 926 (2001) 79.
360
Bruno Le Bizec et al.
58 J.P. Antignac, B. Le Bizec, F. Monteau and F. Andre´, J. Mass Spectrom., 37 (2002) 69. 59 G. Asato, Y.K. Baker, R.T. Bass, T.J. Bentley, S. Chari, R.H. Dalrymple, D.J. France, P.E. Gingher, B.L. Lences, J.J. Pascavage, J.M. Pensack and C.A. Ricks, Agric. Biol. Chem., 48 (1984) 2883. 60 Y.K. Baker, R.H. Dalrymple, D.L. Ingle and C.A. Ricks, J. Anim. Sci., 59 (1984) 1256. 61 R.H. Dalrymple, P.K. Baker, P.E. Gingher, D.L. Ingle, J.M. Pensack and C.A. Ricks, Poult. Sci., 63 (1984) 2376. 62 C.A. Ricks, R.H. Dalrymple, P.K. Baker and D. Ingle, J. Anim. Sci., 59 (1984) 1247. 63 J.M. Brockway, J.C. McRae and P.E.V. Williams, Vet. Rec., 120 (1987) 381. 64 D.H. Beermann, In: M.P. Schreibman, C.G. Scanes and P.K.T. Pang (Eds.), The Endocrinology of Growth, Development and Metabolism in Vertebrates, Academic Press, San Diego, 1994, p. 345. 65 J.F. Martinez-Navarro, Lancet, 336 (1990) 1311. 66 M. Edelhauser and E. Scherbaum, Dtsch. Lebensm.-Rundsch., 87 (1991) 37. 67 A. Polettini, A. Groppi, A. Ricossa and M. Montagna, Biol. Mass Spectrom., 22 (1993) 447. 68 W.J. Blanchflower, S.A. Hewitt, A. Cannavan, C.T. Elliott and G.D. Kennedy, Biol. Mass Spectrom., 22 (1993) 326. 69 M.C. Dumasia and E. Houghton, J. Chromatogr., 564 (1991) 503. 70 L. Kotter, G. Terplan and J. Schulz, Arch. Lebensmittelhyg., 10 (1959) 145. 71 H. Derblom, H. Johansson and G. Nylander, Acta Chir. Scand., 10 (1963) 1. 72 M.L. Martinez-Frı´as, A. Cereijo, E. Rodrı´guez-Pinilla and M. Urioste, Lancet, 339 (1992) 742. 73 E.C. Council directive 81/602, Off. J. Eur. Commun., L 222 (1981) 32. 74 W.J. Blanchflower, P.J. Hughes, A. Cannavan, M.A. McCoy and D.J. Kennedy, Analyst, 122 (1997) 967. 75 H.F. De Brabander, Ph.D. Thesis: The determination of thyrostatic drugs in biological material, Ghent University, Ghent, Belgium, 1986. 76 R.A. McAllister and K.W. Howells, J. Pharm. Pharmacol., 4 (1952) 259. 77 H.F. De Brabander and R. Verbeke, J. Chromatogr., 108 (1975) 141. 78 H.F. De Brabander and R. Verbeke, Trends Anal. Chem., 3 (1984) 162. 79 R. Zakrzewski and W. Ciesielski, J. Chromatogr. B, 784 (2003) 283. 80 K. De Wasch, H.F. De Brabander, L.A. Van Ginkel, A. Spaan, S.S. Sterk and H.D. Meiring, J. Chromatogr. A, 819 (1998) 99. 81 P. Batjoens, H.F. De Brabander and K. De Wasch, J. Chromatogr. A, 750 (1996) 127. 82 B. Le Bizec, F. Monteau, D. Maume, M.-P. Montrade, C. Gade and F. Andre, Anal. Chim. Acta, 340 (1997) 201. 83 R.K. Buick, C. Barry, I.M. Traynor, W.J. McCaughey and C.T. Elliott, J. Chromatogr. B: Biomed. Sci. Appl., 720 (1998) 71. 84 J.W. Pensabene, S.J. Lehotay and W. Fiddler, J. Chromatogr. Sci., 39 (2001) 195. 85 K. De Wasch, H.F. De Brabander, S. Impens, M. Vandewiele and D. Courtheyn, J. Chromatogr. A, 912 (2001) 311. 86 G.Y.F. Yu, E.J. Murby and R.J. Wells, J. Chromatogr. B, 703 (1997) 159. 87 G. Pinel, E. Bichon, K. Pouponneau, D. Maume, F. Andre´ and B. Le Bizec, J. Chromatogr. A, 1085 (2005) 247. 88 B. Le Bizec, J.P. Antignac, E. Bichon, G. Pinel, K. Worrall, WATERS Applications Note 720001124EN, 2005, 8pp. 89 L. Zhang, Y. Liu, M.X. Xie and Y.M. Qiu, J. Chromatogr. A, 1074 (2005) 1. 90 G. Pinel, D. Maume, Y. Deceuninck, F. Andre´ and B. Le Bizec, Rapid. Commun. Mass Spectrom., 20 (2006) 3183. 91 G. Pinel, S. Mathieu, N. Cesbron, D. Maume, H.F. De, F. Andre´ and B. Le Bizec, Food Addit. Contam., 29 (2006) 258. 92 C.J. Peel, T.J. Frank, D.E. Bauman and R.C. Gorewit, J. Dairy Sci., 66 (1983) 776. 93 T. Wise, J. Klindt, F.C. Buonomo and J.T. Yen, J. Anim. Sci., 72 (1994) 2404. 94 J.S. Christiansen, J.O. Jorgensen, S.A. Pedersen, J. Muller, J. Jorgensen, J. Moller, L. Heickendorf and N.E. Skakkebaek, Horm. Res., 36 (1995) 66. 95 V. Borromeo, D. Gaggioli, A. Berrini and C. Secchi, J. Immunol. Methods, 9242 (2002) 1. 96 S. Asdell, Am. J. Physiol., 100 (1932) 137. 97 T.D. Etherton, Nutrition, 17 (2001) 789.
Strategies to Control the Illegal Use of Banned Growth Promoters
361
98 D. Duchaine, Human Growth Hormone in Underground Steroid, Handbook II, HLR Technical Books, California, 1989, pp. 74–76. 99 Z. Wu, M. Bidlingmaier, R. Dall and J. Strasburger, Lancet, 353 (1999) 895. 100 K.E. Langley, P.H. Lai, J. Wypych, R.R. Everett, T.F. Berg, L.F. Krabill, J.M. Davis and L.M. Souza, Eur. J. Biochem., 163 (1987) 232. 101 Dec 1994/936/CE Off. J. no. L 366 31/12/1994, pp. 0019–0020. 102 Dec 1999/879/CE Off. J. no. L 331 23/12/1999, pp. 0071–0072. 103 H. Flodh, Acta Paediatr. Scand., 325 (1986) 1. 104 V. Borromeo, A. Berrini, C. Secchi, G.F. Brambilla and A. Cantafora, J. Chromatogr. B, 669 (1995) 366. 105 C.M. Zwickl, H.W. Smith and P.H. Bick, J. Agr. Food Chem., 38 (1990) 1358. 106 G.F. Brambilla, A. Berrini, V. Borromeo and C. Secchi, Anal. Chim. Acta, 275 (1993) 173. 107 M. Hennies and W. Holtz, J. Immunol. Methods, 157 (1993) 149. 108 X. Zhao and M. Bride, Domest. Anim. Endocrin., 11 (1994) 209. 109 L. Castegliero, G. Iannone, G. Grifoni, R. Rosati, D. Gianfaldoni and A. Guidi, J. Dairy Res., 74 (2007) 79. 110 J. Girard, T. Erb, A. Pampalone, A.N. Erbele and J.B. Baumann, Hormone Res., 28 (1987) 71. 111 C. Secchi, P.A. Biondi, A. Berrini, T. Simonic and S. Ronchi, J. Immun. Methods, 110 (1998) 123. 112 T.H.J. Heutmekers, M. Bremer, W. Haasnoot and M. Nielen, Anal. Chim. Acta, 586 (2007) 239. 113 N. Rochut, B. Le Bizec, F. Monteau and F. Andre, Analusis, 28 (2000) 280. 114 G. Pinel, F. Andre and B. Le Bizec, J. Agric. Food Chem., 52 (2004) 407. 115 M. Blockland, S. Sterk, L.A. Van Ginkel, R.W. Stephany and A.J.R. Heck, Anal. Chim. Acta, 438 (2003) 201. 116 L. Bailly-Chouriberry, Ph.D. Thesis: De´tection de l’administration de l’hormone de croissance e´quine recombinante: Application au controˆle anti-dopage dans les courses hippiques, Nantes University, Nantes, France, 2007. 117 A.T. Kickman, J.P. Miell, J.D. Teale, J. Powrie, P.J. Wood, P.L. Aidler, P.J. Milligan and D.A. Cowan, Clin. Endocrinol., 47 (1997) 43. 118 J.D. Wallace, R.C. Cuneo, R. Baxter, H. Orskov, N. Keay, C. Pentecost, R. Dall, T. Rosen, J.O. Jorgensen, A. Cittadini, S. Longobardi, L. Sacca, J.S. Christiansen, B.A. Bengtsson and P.H. Sonksen, J. Clin. Endocrinol. Metab., 84 (1999) 3591. 119 W.F. Blumm, M.B. Ranke, K. Kietzmann, E. Gauggel, H.J. Zeizel and J.R. Bierich, J. Clin. Endocrinol. Metab., 70 (1990) 1292. 120 M.A. Popot, S. Bobin, Y. Bonnaire, P.H. Delahaut and J. Closset, J. Res. Vet. Sci., 71 (2001) 167. 121 S. Kirsch, J. Widart, J. Louette, J.-F. Focant and E. De Paw, J. Chromatogr. A, 1029 (2007) 3049. 122 P.H. Bisk, A.C.G. Brown, H.W. Smith, R.N. Tamura and C.M. Zwickl, Anim. Biotechnol., 4 (1990) 61. 123 J.C. Juskevich and C.G. Guyer, Science, 249 (1990) 875. 124 C.M. Zwickl, H.W. Smith, R.N. Tamura and P.H. Bick, J. Dairy Sci., 73 (1990) 2888. 125 J.L. Burton, B.W. McBride, E. Block, D.R. Glimm and J.J. Kennely, Can. J. Anim. Sci., 74 (1994) 167. 126 M.L. Scippo, G. Degand, A. Duckaerts and G. Maghuin-Rogister, Ann. Med. Vet., 141 (1997) 581. 127 L. Bailly-Chouriberry, E. Chu-Van, G. Pinel, P. Garcia, M.-A. Popot, Y. Bonnaire, B. Le Bizec, Analyst, 133 (2008) 270. 128 G. Pinel, R. Buon, F. Aviat, C. Larre´, G. Andre´-Fontaine, F. Andre´ and B. Le Bizec, Anal. Chim. Acta, 529 (2005) 41.
CHAPT ER
12 Mycotoxins Carlo Brera, Barbara De Santis, Francesca Debegnach and Marina Miraglia
Contents
1. Introduction 2. Classes of Mycotoxins 2.1 Major mycotoxins 2.2 Minor mycotoxins 3. Health Effects 3.1 Cases of acute mycotoxicosis in humans 3.2 Effects of low doses of mycotoxins 3.3 Quantitative evaluation of human exposure to mycotoxins 3.4 Tolerable maximum limit for mycotoxins in food 4. Sampling 5. Analytical Methods 5.1 Introduction 5.2 Sample preparation 5.3 Determination and detection 5.4 Other methods 6. Occurrence in Food and Feed 6.1 Aflatoxins 6.2 Ochratoxin A 6.3 Fusarium toxins 6.4 Patulin 6.5 Multi-Fusarium toxins 6.6 Other mycotoxins 7. Decontamination Procedures 8. Future Needs Acknowledgement References
Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00012-3
364 366 367 371 376 376 377 379 383 383 385 385 386 387 401 402 403 403 411 412 413 414 416 418 419 419
r 2008 Elsevier B.V. All rights reserved.
363
364
Carlo Brera et al.
1. INTRODUCTION Microscopic filamentous fungi, commonly known as moulds, can develop on food commodities of plant origin (maize, wheat, etc.) and in some cases also on commodities of animal origin (meat products, sausages). These moulds can, in suitable environmental conditions, produce chemical toxic compounds, known as mycotoxins. The word mycotoxin stems from the Greek word ‘‘mykes’’, meaning mould, and ‘‘toxicum’’ meaning poison. Mycotoxins are naturally occurring secondary metabolites of some fungal species mainly belonging to the genera Aspergillus, Penicillium and Fusarium. Even if it is reasonable to argue that mycotoxins could have played a significant role in some of the human and animal diseases since the Roman era, the scientific interest for their implication for human and animal health began in the 1960s. Ergotism, for instance, that hit various populations of Central and North Europe in the Middle Age as a consequence of the high consumption rates of rye and other cereals containing some alkaloids produced by the Claviceps purpurea fungus, can be considered as the first recognized disease, known as S. Anthony’s Fire, to be related to mycotoxins [1,2]. Essential factors for mycotoxin production are both the stress of the plant, as derived by the extreme soil dryness or the lack of a balanced nutrient absorption and environmental factors such as climate changes, temperature, humidity, water activity, mechanical damage of kernels as well as insects and pest attack [3]. Currently more than 300 mycotoxins are known, but the scientific attention has been so far focused only to approximately 10 compounds presenting a known toxicological impact on human and animal health. Mycotoxins are characterized by differentiated chemical structures as a result of the multiple varieties of moulds responsible for their production. Among them, aflatoxins present a highly oxygenated heterocyclic structure, ochratoxins consist of a polyketidederived dihydroiso-coumarin moiety linked through the 12-carboxy group to phenylalanine, and trichothecenes (deoxynivalenol (DON), NIV, T-2 and HT-2 toxin, diacetoxyscirpenol (DAS)) are characterized by a quite similar chemical structure presenting a double bond between C9 and C10 and an epoxidic group with functional alcoholic and ester groups at the C12–C13 position responsible of their toxicity. Other relevant mycotoxin are zearalenone (ZEA) and its metabolites, that are estrogenic resorcylic acid lactone compounds, fumonisins (FBs) presenting a long linear carbon chain with ester, carboxylic- and aminosubstituting functional groups and patulin, a polyketide lactone. The toxic effects of mycotoxins are mainly related to genotoxicity, carcinogenicity, immunotoxicity, mutagenicity, nephrotoxicity and teratogenicity. Crops can be directly infested by toxic moulds and contaminated by mycotoxins: it has been calculated that, during the various cycles of the agrifood chain including production, processing, transport and storage, about 25% of crops are affected each year with ‘‘unacceptable’’ levels of mycotoxins. However, the percentage of crops affected by mycotoxins is much higher.
Mycotoxins
365
According to a 1993 World Bank report, ‘‘Investing in Health’’, approximately 40% of disability-adjusted life years lost to premature adult death in developing countries are due to diseases linked to mycotoxin-contaminated food consumption. The individuation of the intrinsic properties of a food commodity favourable to mycotoxin contamination is quite multifaceted. In general, substrates rich of carbohydrates and lipids are more exposed to mould attack and potential production of mycotoxins. The presence of mycotoxins in a food commodity can occur even in the absence of a visible mould infestation due to a ceased vital cycle of the microorganism or by the effect of a removal of the mould due to technological processing of the food commodity. Nevertheless, the presence of a visible mould on the surface of a food product does not represent a clear indication of the presence of a mycotoxin. In addition, one specific mycotoxin can be produced from different genera and species of moulds and one specific mould can produce more than one mycotoxin. Generally, plant-origin commodities directly contaminated by mycotoxins are cereals, with maize as the most risky crop, dried fruit, spices, grape, coffee, cocoa, fruit juices especially apple-based and, in minor extent, meat products and liquorice. During the storage cycle, mycotoxins can directly contaminate also cheeses and sausages. In addition, food products can become contaminated as a consequence of a carry over from contaminated feeds and be present in food of animal origin such as milk, eggs and, in a minor extent, meat. Even if some technological processing is able to reduce the level of mycotoxins of the raw commodity, some processed food such as wine and beer can result in contamination by mycotoxins as a result of the use of contaminated raw material. It has to be noted that mycotoxins resist high temperatures and the common domestic cooking procedures are not able to destroy them. In addition to food diet, humans and animals can also be exposed to mycotoxins by inhalation of heavily contaminated dusts. This phenomenon is particularly observed in certain working places such as harbours and warehouses and also in the houses as a result of an indoor contamination caused by wallpapers and mouldiness of domestic environments. The industrial processing is in some cases effective in reducing or at least modifying the pattern of contamination. For instance, milling of cereals determines a distribution of some mycotoxins present in raw kernels that is variable throughout the various milled fractions, with concentration factors in germ, bran and flour for feed preparations and dilution factors in grits and flour for human-intended use; roasting of coffee beans is another process able to largely destroy Ochratoxins A (OTA) (up to 90%). Apart from all the above-mentioned decontamination strategies, it should be considered that an integrated approach based upon the implementation of preventive actions starting from the seeding and modulated along the whole agri-food chain, is still the most effective strategy to eliminate or at least reduce the mycotoxin contamination in food and feed commodities.
366
Carlo Brera et al.
Mycotoxins can occur at pre-harvest, harvest and post-harvest stage. Therefore, in any of these phases preventive actions can be performed. Prevention through pre-harvest management is the best method for controlling mycotoxin contamination. The major effective actions are (i) a correct management of insect infestation, since insect-damaged kernels provide infection routes and allow kernel drying to moisture levels more favourable for growth of mould species, (ii) a suitable management of crop residues and crop rotation, (iii) a proper irrigation control and treatment of soil to avoid extreme conditions of either drought or excessive moisture, (iv) a development of naturally resistant plant varieties to fungal infection, since host resistance may present a promising strategy for the pre-harvest prevention of mycotoxin contamination. Among the strategies for enhancing host resistance, the genetic engineering research, aimed at the addition or enhancement of antifungal genes present in many endogenous low molecular weight compounds and biomacromolecules, is one of the most modern and debated issues involved in some controversial economic, ethic, safety and environmental aspects. During harvesting and post-harvest phases, it is important to control factors such as the avoidance of damaging kernels during the mechanical or manual harvesting procedures, and the use of appropriate and complete drying procedures of the agricultural products. This control is essential for preventing mycotoxin formation during storage. As soon as the crop is fully grown and the crop cycle is completed, harvesting should take place. Some studies have reported that crops left on the field for longer periods of time may present higher levels of toxin contamination. Decontamination procedures for reducing or eliminating the presence of mycotoxins in food products have not yet been standardized worldwide due to the related high costs and, in some cases, the scarce feasibility of effective results. However, chemical, biological and physical treatments are known to be effective somehow in reducing the mycotoxin content. This issue will be treated in Section 7.
2. CLASSES OF MYCOTOXINS Mycotoxins represent a quite wide spectrum of chemical compounds characterized by different molecular structures as a result of the numerous species of fungi responsible for their production. Major and minor classes of mycotoxins can be distinguished: among major class aflatoxins, ochratoxins, trichothecenes, FBs, patulin and zearalenone represent the most concern for human and animal health, while in the minor class, ergot alkaloids, citrinin, cyclopiazonic acid, sterigmatocystin, moniliformin, gliotoxin, citreoviridin, tremorgenic mycotoxins, penicillic acid, roquefortine, 3-nitropropionic acid, and fusaproliferin are noteworthy.
Mycotoxins
367
2.1 Major mycotoxins 2.1.1 Aflatoxins On the basis of their potent toxic effects aflatoxins, in particular aflatoxin B1 (AFB1) [CAS number: 1162-65-8], are historically the main toxins of concern since their discovery occurred in 1958. These toxins are mainly produced by two species of Aspergillus fungi genus, namely Aspergillus flavus and Aspergillus parasiticus, particularly in hot and humid areas, together with Aspergillus nomius and Aspergillus pseudotamarii [4,5]. Moisture higher than 85% and temperatures above 25% are favourable to the growth of aflatoxin-producing fungi during storage [6]. Aflatoxin B-hydroxilated metabolites, aflatoxins M1 and M2 [CAS number: 6885-57-0], are two toxins occurring in milk and derived products, as an effect of the fast metabolism of aflatoxins B1 and B2 (AFB2) in animals fed with aflatoxinscontaminated feeds. Aflatoxins (Figure 1) are substances that are chemically related to difuranocoumarin and classified in two broad groups according to their chemical
O
O
O
O
O
O O
O
OCH3
AFLATOXIN B1
OCH3
AFLATOXIN B2
O
O
O
OH
O
OH O
O O
O
OCH3
AFLATOXIN M2
AFLATOXIN M1 O
OCH3
O
O
O
O
O O
O O
OCH3
AFLATOXIN G1
Figure 1 Molecular structure of aflatoxins.
O
OCH3
AFLATOXIN G2
368
Carlo Brera et al.
structure; the difurocoumarocyclopentenone series (including AFB1 and AFB2 [CAS number: 7220-81-7]) and the difurocoumarolactone series (including aflatoxin G1 (AFG1) [CAS number: 1165-39-5], aflatoxin G2 (AFG2) [CAS number: 7241-98-7] and aflatoxin M1 (AFM1) [CAS number: 6795-23-9]). The G series contains a D-lactone ring, while the B series contains a cyclopentenone ring, which is responsible for the major toxicity of the B series. The aflatoxins fluoresce strongly in UV light (ca. 365 nm); AFB1 and AFB2 produce a blue fluorescence whereas AFG1 and AFG2 produce green fluorescence. Aflatoxins are crystalline substances, soluble in moderately polar organic solvents, such as chloroform, methanol, dimethysulfoxide, scarcely soluble in water (10–30 mg/mL) and insoluble in non-polar organic solvents. Aflatoxins in dry state are very stable to heat up to their melting point. Pure aflatoxins are destroyed by UV radiations, unstable at pHo3 and W10 and in the presence of oxidizing components.
2.1.2 Ochratoxins Ochratoxins A (OTA) [CAS number: 303-47-9], B and C (Figure 2) are compounds with phenylalanine containing dihydroisocoumarin. OTA, the toxin of most concern, also contains a chlorine atom on the aromatic ring, which accounts for its toxicity. Ochratoxin is produced by both Aspergillus ochraceus and Penicillium viridicatum (among others), with OTA being the most relevant toxin [7]. OTA is a colourless crystalline compound exhibiting blue fluorescence under UV light. Its sodium salt is soluble in water, as an acid, it is moderately soluble in polar organic solvents such as chloroform and methanol and dissolves in dilute aqueous sodium bicarbonate. On acid hydrolysis, OTA yields phenylalanine and an optically active lactone acid, ochratoxin a. Reaction in methanol and chloridric acid yields the OTA methyl ester, which can be used as a confirmatory reaction in high-performance liquid chromatography (HPLC) determination.
2.1.3 Trichothecenes Trichothecenes (Figure 3) are a cluster group of about 150 mycotoxins [8] produced by various species of different fungi of genera: Fusarium (in particular Fusarium langsethiae, Fusarium poae and Fusarium sporotrichioides), Myrothecium, Stachybotrys, Trichoderma, Cephalosporium, Trichothecium and Verticimonosporium [9,10]. Updated information on the chemical diversity of Fusarium species producing thricothecenes has also been published by Thrane [11]. In addition, an exhaustive COOH
O
OH
O
N H CH3 Cl
Figure 2 Molecular structure of OTA.
Mycotoxins
369
Figure 3 Molecular structure of the main trichothecenes. R ¼ OH or acyloxy group (most often acetoxy). For class B trichothecene DON, R1 ¼ OH, R2 ¼ H, R3 ¼ OH, and R4 ¼ OH.
review on taxonomy and clinical aspects of Fusarium species has been published by Nelson [12]. These toxins are chemically strictly related and are characterized by a basic group consisting of a common tetracyclic, sesquiterpenoid 12,13-epoxytrichothec-9-ene ring, the epoxide group known as responsible for causing the toxicity [13]. Depending on the presence on C7 of a side chain, trichothecenes are distinguished as type A and B. Group A includes toxin T-2 and HT-2 and DAS, also known as anguidine. Main trichothecenes of group B include DON, commonly known as vomitoxin, nivalenol (NIV), 3- and 15-acetoxy NIV and fusarenon X. Trichothecenes are chemically stable and can persist for long periods once formed. Group A trichothecenes (T-2 toxin, HT-2 toxin, neosolaniol, MAS and DAS) are highly soluble in ethyl acetate, acetone, chloroform, dichloromethane and diethyl ether. The Group B trichothecenes (DON, NIV, 3-acetylDON, 15acetylDON, fusarenone-X, scirpentriol and T-2 tetraol) are highly hydroxylated and relatively polar being soluble in methanol, acetonitrile and ethanol. DON [CAS number: 51481-10-8], contains one primary and two secondary hydroxyl groups and is soluble in water and polar solvents such as methanol and acetonitrile. Unlike many of the other trichothecenes, the molecule contains a conjugated carbonyl system and this results in some UV absorbance that assists its detection by TLC or HPLC methods. T-2 toxin [CAS number: 21259-20-1] and HT-2 toxin [CAS number: 26934-87-2] are mycotoxins produced by F. acuminatum, F. poae and F. sporotrichioides, which are commonly found in various cereal crops (wheat, maize, barley, oats and rye) and processed grains (malt, beer and bread). T-2-and HT-2 toxin often occurs together in infected cereals. Recently, a new Fusarium species, namely Fusarium langsethiae, was discovered as producing T-2 toxin [14].
2.1.4 Zearalenone ZEA (Figure 4) [CAS number: 17924-92-4] is a non-steroidal, phenolic resorcyclic acid lactone estrogenic toxin [15] produced mainly by Fusarium graminearum, Fusarium culmorum and Fusarium sacchari. ZEA is a white crystalline compound, which exhibits blue-green fluorescence when excited by long wavelength UV
370
Carlo Brera et al.
light (360 nm) and a more intense green fluorescence when excited with short wavelength UV light (260 nm). It is soluble in water, slightly soluble in hexane and progressively more soluble in benzene, acetonitrile, dichloromethane, methanol, ethanol and acetone. It is also soluble in aqueous alkali.
2.1.5 Fumonisins In 1988, Bezuidenhout [16] characterized the structures of FBs, a new group of mycotoxins that had been purified from cultures of Fusarium moniliforme. FBs are a family of 28 toxins. The mycotoxins are mainly produced by Fusarium verticillioides (Sacc.) Nirenberg (former F. moniliforme Sheldon) and Fusarium proliferatum. The most abundant and toxic is fumonisin B1 (FB1) [CAS number: 116355-83-0]. FB1 is chemically described as a diester of propane-1,2,3tricarboxylic acid and 2-amino-12,16-dimethyl-3,5,10,14,15-pentahydroxyeicosane [17,18]. The structure of FB1 is shown in Figure 5. Fumonisin B2 (FB2) [CAS number: 116355-84-1] is a deoxy-analogue of FB1 in which the corresponding epimeric units on the eicosane backbone have the same configuration. The full stereochemistry of fumonisins B3 (FB3) and B4 is unknown yet, but the amino terminal of FB3 has the same absolute configuration as that of FB1 [19,20]. FB1 typically accounts for 70–80% of the total FBs produced, while FB2 usually makes up 15–25% and FB3 usually makes up from 3% to 8% when cultured on corn or rice or in liquid medium [21]. From a structural point of view, FBs are correlated to the sphyngoid bases. The pure substance is a white hydroscopic powder that is soluble in water, acetonitrile–water or methanol. FBs are soluble in polar solvents because of the four free carboxyl groups, the hydroxyl groups and the amino group. Their insolubility in many organic solvents such as chloroform and hexane commonly used in mycotoxin analysis partly explains the difficulty
Figure 4 Molecular structure of ZEA.
COOH
HOOC
NH2 H3C
O OH OH O
OH OH HOOC
HOOC
Figure 5
Molecular structure of FB1.
O
CH3 CH3
O
Mycotoxins
371
OH
O O
Figure 6 Molecular structure of patulin.
in their original identification. Fumonisins B1 and B2 are reported to be stable over a 6-month period at 251C in acetonitrile–water (1:1).
2.1.6 Patulin Patulin (Figure 6) [CAS number: 149-29-1] was first isolated in the 1940s but is now known to occur worldwide in apple and apple products. Patulin is produced by different species of the genera Penicillium, Aspergillus and Byssochlamys moulds that may grow on a variety of foods including fruit, grains and cheese. Penicillium expansum is the most productive species. Patulin is reported to be destroyed by alcoholic fermentation and thus is not found in either alcoholic fruit beverages or vinegars produced from fruit juices [22,23]. Thermal processing appears to cause only moderate reductions in patulin levels, thus patulin present in apple juice will survive the pasteurization process [24–26]. The level of contamination is generally strictly related to the mouldiness and rot degree of food products even if the toxin is concentrated only in mouldy parts. Its presence in fruit juices, particularly apple juices, can be regarded as the main potential risk for humans, since rot or mouldy parts of the fruit could be employed in manufacturing of these products. From a chemical point of view it is a lactone. Patulin can be isolated as colourless to white crystals from ethereal extracts that have no optical activity. It melts at about 1101C. It is soluble in water, methanol, ethanol, acetone and ethyl or amyl acetate and less soluble in diethyl ether and benzene. It undergoes all the reactions expected from a secondary alcohol, reduces warm Fehlings solution and decolourizes potassium permanganate. It is stable in acid solutions but is susceptible to alkaline hydrolysis.
2.2 Minor mycotoxins 2.2.1 Ergot alkaloids The first documented epidemic of ergotism likely occurred in 944-945 AD, when some 20,000 people of the Aquitane region of France (about half of the population) died of the effects of ergot poisoning. Ergoline or ergot alkaloids were first isolated from ergot, a black tuber-like non-endophytic fungus that infects grains and causes the disease known as ergotism. More specifically, the ergot alkaloids are produced by several species of Claviceps, a genus of fungi that invades the female portion of the host plant and replaces the ovary with a mass of fungal tissue called sclerotium. The isolation by G. Barger and F.H. Carrin of ergotoxine, so named since it appeared to have more toxic effects than the
372
Carlo Brera et al.
therapeutic properties of ergot, was the starting point, followed by the isolation of ergotamine, the first ergot alkaloid used in therapeutic, in 1918 by A. Stoll. With the determination of the basic chemical structure of the ergot alkaloids in the early 1930s, an era of intensive exploration of synthetic derivatives began. The ergot alkaloids are indole compounds that are biosynthetically derived from L-tryptophan and represent the largest group of nitrogenous fungal metabolites found in nature. Over 80 different ergot alkaloids have been isolated, mainly from various Claviceps species (over 70 alkaloids), but also from other fungi and higher plants. In addition to the naturally occurring ergonovine (used as an oxytocic) and ergotamine (an analgesic used to control migraine), synthetic derivatives of continuing importance today are the oxytocic methergine, the antimigraine drugs dihydroergotamine and methysergide, the anti-senility nootropic (smart drug) Hyderginet and bromocriptine, used for numerous purposes including treatment of Parkinson’s disease. Newer synthetic ergolines used for Parkinson’s disease include pergolide and lisuride. Perhaps the most famous ergoline derivative of all is the psychedelic drug lysergide (LSD). To sum up, the ergot alkaloids comprise the largest group of nitrogen-containing fungal compounds and are generally divided into four major groups based on their chemical similarities: (1) the clavines (agroclavine, elymoclavine and lysergol), (2) the lysergic acids, (3) the lysergic acid amides (ergine, ergonovine, methergine, methysergide and LSD and (4) the ergopeptines (ergotamine, ergovaline, aergosine and a-ergocryptine) [27]. Selected members of these groups of compounds are involved in either nervous or gangrenous syndromes in humans and animals that consume grains or grain products contaminated with the sclerotia of the fungus.
2.2.2 Citrinin Citrinin [CAS number: 518-75-2] was first isolated as a pure compound from a culture of Penicillium citrinum in 1931 [28]. Later, yellowish coloured rice imported from Thailand to Japan in 1951 was found to be contaminated with P. citrinum and subsequent investigations showed that isolates of the fungus produced citrinin. Citrinin is a mycotoxin, which is produced by A. ochraceus, P. citrinum, and related species, which contaminate grain. It causes nephropathy in livestock and has been implicated as a cause of Balkan nephropathy in humans. It frequently co-occurs with OTA with which it showed a documented synergistic effect [29,30].
2.2.3 Cyclopiazonic acid Cyclopiazonic acid [CAS number: 18172-33-3] is mainly produced by Penicillium cyclopium and other fungi species including A. flavus. Because of this peculiar characteristic, it has the potential to co-occur with aflatoxins in a range of commodities. Cyclopiazonic acid is soluble in chloroform and dimethyl sulfoxide. It is a specific inhibitor of Ca2+-ATPase in the intracellular Ca2+ storage sites [31]. It is considered as a potent neurotoxin that may be fatal if swallowed or inhaled.
Mycotoxins
373
However, cyclopiazonic acid only appears to be toxic when present in high concentrations.
2.2.4 Sterigmatocystin Sterigmatocystin [CAS number: 10048-13-2] is mainly produced by the fungi Aspergillus nidulans and Aspergillus versicolor. It has been reported in mouldy grain, green coffee beans and cheese, although information on its occurrence in food is limited. It seems to occur much less frequently than the aflatoxins, even if no validated analytical methods have been carried out at microgram per kilogram (mg/kg) levels. Sterigmatocystin contains a xanthone nucleus and is considered as a precursor of AFB1 in biological pathway. Although it is a potent liver carcinogen similar to AFB1, current knowledge suggests that it is nowhere near as widespread in its occurrence. A number of closely related compounds such o-methyl sterigmatocystin are known and some may also occur naturally.
2.2.5 Moniliformin Moniliformin [CAS number: 71376-34-6] was discovered by Cole et al. [32] in 1973, while screening for toxic products of a North American isolate of F. moniliforme Sheldon (F. verticillioides [Sacc.] Nirenberg) cultured on corn. More recent studies demonstrated that previous ones that ascribed moniliformin production to F. moniliforme, actually tested an aggregate consisting of more than one species. Moniliformin is formed in cereals by a number of Fusarium species that include F. avenaceum, F. subglutinans and F. proliferatum and it occurs as the sodium or potassium salt of 1-hydroxycyclobut-1-ene-3,4-dione. It is an ionic compound forming sodium and potassium salts and is soluble in water and polar solvents. This mycotoxin has not yet received much attention because it does not appear to be carcinogenic and relatively high amounts appear to be necessary to cause significant toxicological effects.
2.2.6 Gliotoxin Gliotoxin [CAS number: 67-99-2] was discovered by Weindling and Emerson in 1936 [33] from culture filtrates of Gliocladium fimbriatum. It is a highly immunosuppressive toxin produced by a wide variety of widespread moulds. Interestingly, gliotoxin is produced by the organism Aspergillus fumigatus during its pathogenic state as a causative agent of the respiratory disease known as aspergillosis in turkeys. This compound belongs to a group of fungal metabolites, some of them toxic, called epipolythiodioxopiperazines. This toxin exhibits immunosuppressive activity against certain cells of the immune system. Intoxication of camels is reported due to the ingestion of this toxin and it seems to be involved in human infections caused by Candida albicans.
2.2.7 Citreoviridin Citreoviridin [CAS number: 77-92-9] a potent neurotoxin, originally was isolated from cultures of moulds obtained from rice associated with a disease called cardiac beriberi that has occurred for three centuries in Japan.
374
Carlo Brera et al.
Citreoviridin was obtained from Penicillium citreonigrum Biourge (synonyms: Penicillium citreoviride and Penicillium toxicarium), one of the so-called ‘‘yellowed rice’’ fungi [34] and subsequently from a number of other Penicillium species [35]. The toxin is also produced by P. ochrosalmoneum. Its structure was first discovered in 1964 by means of chemical degradation and 1 H NMR spectroscopy [36]. The fungus is favoured by the lower temperatures and shorter hours of daylight occurring in the more temperate rice-growing areas. Citreoviridin has been found in un-harvested corn in the United States. Citreoviridin is an unusual molecule consisting of a lactone ring conjugated to a furan ring, with a molecular weight of 402. Citreoviridin and aflatoxin have been found to occur simultaneously in maize, which indicates their possible interaction in producing animal disease [37]. Citreoviridin causes paralysis, dyspnea, cardiovascular disturbances and loss of eyesight in experimental animals [38]. Citreoviridin is structurally closely related to aurovertin B and to asteltoxin [39].
2.2.8 Tremorgenic mycotoxins These toxins are produced by a wide spectrum of fungi belonging to the genera Penicillium, Aspergillus, Claviceps and Acremonium [40]. On the basis of chemical similarity, at least 20 mycotoxins have been identified as tremorgens (compounds capable of inducing serious muscle tremor in one or more vertebrates). These toxins can be separated into four groups: the penitrems, the fumitremorgen verruculogen group, the paspalines and the tryptoquivaline group. Penicillium species produce the most tremorgenic mycotoxins [41]. The penitrems, produced by Penicillium species such as Penicillium crustosum, have been the most widely studied in laboratory animals [42] and in livestock [43]. Penitrem A [CAS number: 12627-35-9] has become recognised and used pharmacologically as a selective blocker of high conductance calcium-activated potassium channels [44–48]. Intoxication with these mycotoxins causing trembling syndromes has been documented in many animals, including dogs, cattle, sheep, rabbits, poultry and rodents [49,50]. Clinical signs include muscle tremor, uncoordinated movements, general weakness in the hind legs, and stiff, stilted movements of the forelegs. Other intoxications involving fungal tremorgens, most notably the penitrem mycotoxins, have been reported from mouldy cream cheese, hamburger buns (bread) and walnuts consumed by dogs [51]. Other noteworthy tremorgenic mycotoxins are lolitrem A–F. Lolitrem B [CAS number: 81771-19-9] is a potent neurotoxic indole-diterpen, generally considered to be the predominant alkaloid in endophyte-infected perennial ryegrass and responsible for ryegrass staggers in livestock [52]. Paxilline [CAS number: 57186-25-1] produced both by Penicillium species of fungi [40] and Acremonium lolii [53] also blocks high conductance
Mycotoxins
375
calcium-activated potassium channels [54] and is thought to be a precursor in the biosynthesis of lolitrem B by A. lolii [55,56].
2.2.9 Penicillic acid Penicillic acid [CAS number: 90-65-3] is a polyketide mycotoxin produced by several species of Aspergillus and Penicillium with particular emphasis on P. cyclopium and P. canescens. This mycotoxin is toxic in experimental animals and has been reported to be hepatocarcinogen in some animal species, and has also been reported to affect the heart.
2.2.10 Roquefortine Roquefortines A [CAS number: 58735-64-1], B and C are neurotoxic metabolites of Penicillium roqueforti [57]. P. roqueforti is also responsible for the so-called Penicillium roqueforti (PR) toxin, one of the most potent mycotoxins, that being unstable and rapidly perishable, does not pose a health problem. A study reported that roquefortine is also produced by cultures of Penicillium commune in combination with penitrem A [58].
2.2.11 3-Nitropropionic acid 3-Nitropropionic acid [CAS number: 504-88-1] is a known neurotoxic secondary metabolite produced by many species of Astragalus of the Leguminosae family. In 1992, Liu et al. [59] reported that some species of Arthrinium were the etiological fungi of mouldy sugarcane poisoning (MSP) occurring in China. The toxic metabolite 3-nitropropionic acid (NPA) produced by Arthrinium was the main causative agent. NPA is a plant fungal toxin, which inactivates mitochondrial succinate dehydrogenase [60].
2.2.12 Fusaproliferin Fusaproliferin is a toxic sesterterpene isolated from F. proliferatum, a widespread pathogen of cereals. In 1995, researchers in Italy reported a previously unknown toxin, fusaproliferin, produced by F. proliferatum and F. subglutinans [61–63]. It is a sesquiterterpene compound that is toxic to brine shrimp (Artemia salina), insects and human cell cultures in laboratory assays. It also has teratogenic effects on chicken embryos [64]. Fusaproliferin has been detected in livestock feed samples associated with feed refusal [65], but there is no direct evidence that it causes feed refusal symptoms. No mammalian feeding studies have been conducted to date. Although the concern of this compound in animal and human health has not been to be determined, its acute toxicity to brine shrimp exceeds that of more familiar compounds such as the FBs.
376
Carlo Brera et al.
3. HEALTH EFFECTS The impact on human health derived from the interaction between mycotoxins and human biosystems can range from acute to chronic effects and can derive from various sources of exposure namely dermal contact, inhalation and consumption of contaminated food, the latter being the more relevant and investigated route. As for most xenobiotics, the effects of mycotoxins are dependent on the dose, length of the exposure and possibly interaction with other toxic or non-toxic agents. For mycotoxins, as well as for other toxic agents, the systematic evaluation of the impact on human health is performed through the risk-assessment process that consists of the hazard identification, implying the toxicological and epidemiological assessment, the hazard characterization, involving the assessment of the dose response and the extrapolation to humans, the exposure assessment and the risk characterization. This latter step relies on the previous evaluations and as defined by the EC Scientific Steering Committee in 2000 [66] allows for ‘‘the quantitative or semiquantitative estimation, including attendant uncertainties, of the probability of occurrence and severity of adverse effect(s)/ event(s) in a given population’’. Basically risk characterization correlates the outputs of the hazard characterization with different levels of exposure and it should represent the basis for decision-making processes including the issue of defining maximum tolerable limits in foodstuff. The topic for mycotoxins has been thoroughly and extensively reviewed by Kuiper-Goodman in 2004 [67].
3.1 Cases of acute mycotoxicosis in humans Over past centuries the presence of mycotoxin, mainly aflatoxin and trichothecenes in food, has been reported to recurrently cause outbreak of acute intoxication even resulting in death. The most recent was reported in 2004 in eastern Kenya, where, due to aflatoxin contamination of home-grown maize, 317 cases of acute hepatic failure were identified with 125 cases occurring in persons who subsequently died. The case-control study conducted by AzzizBaumgartner et al. in 2005 [68] proved that aflatoxin concentration in maize, serum AFB1–lysine adducts concentrations and positive hepatitis B surface antigen titres were all associated with the case status. In addition, it was found that male mortality due to aflatoxicosis was higher than female mortality, similarly to that found for the 1974 outbreak of aflatoxicosis in India [69]. From an outbreak of hepatitis associated with consumption of corn contaminated with aflatoxins, over 100 deaths occurred in India in 1976, the ingested dose causative of the event at that time estimated by local authorities was 2–6 mg/day over a month [70]. Among other relatively recent cases of human aflatoxicosis, the death of 13 Chinese children due to acute hepatic encephalopathy has been reported by Lye et al. [71]. The above researches reported the acute toxicity in family clusters
Mycotoxins
377
probably due not only to common food eaten, but also to genetic polymorphism of cytocrome P450 enzymes [72]. Early symptoms of hepatoxicity from acute aflatoxicosis include anorexia, malaise and low-grade fever possibly turning into vomiting, abdominal pain, jaundice, hepatic failure and death. Fatty degenerative changes in the liver as centrolobular necrosis and fatty infiltration have also been reported [3]. Several outbreaks attributable to trichothecenes-contaminated food have been reported. In addition to the historical (1931–47) outbreaks of alimentary toxic aleukia (ATA) in the former USSR, several epidemic incidents attributable to trichothecenes have been recently reported in India, China and Japan [73–75]. Trichothecenes are often regarded as radiomimetic toxins since some related effects such as the effect on bone marrow are similar to those seen in radiation poisoning. T-2 and DAS were placed by the Centers for Disease Control and Prevention of USA on the ‘‘Selected Agents List’’ in relation to agents of biowarfare or terrorism [76].
3.2 Effects of low doses of mycotoxins By considering the overall low frequency of outbreaks of acute intoxication and the worldwide reported high rate of occurrence of mycotoxins at low concentration in food, it can be concluded that it is likely that the population is worldwide generally exposed to low doses of mycotoxins over long periods and consequently that most of the toxic effects exerted by mycotoxins are chronic. According to Kuiper-Goodman [67] and as far as chronic disease is concerned, the risk attributable to the presence of mycotoxins in food should be considered much more severe than other sources of risk such as anthropogenic contaminants, food additives and microbiological agents. This has prompted the most relevant international organizations such as WHO, IARC, ILSI, JECFA, SCF, EFSA to issue the topic of mycotoxin health impact, a considerable number of detailed reports being now available under the auspices of the above organizations. The wide variety of chemical compounds grouped under the common term of mycotoxins makes them responsible for a broad spectrum of chronic toxic effects and they range from the well-documented carcinogenic to the less-investigated immunosuppressive action. The most important and studied effects are genotoxicity and carcinogenicity. From the viewpoint of hazard characterization, genotoxic, carcinogenic and noncarcinogenic mycotoxins are considered separately. In this respect, a crucial and often controversial point is the appropriateness of the definition of a threshold dose based on the mechanism of action of the toxin. By definition, genotoxic compounds have a probability of inducing an effect at any small dose and their absence from food is strongly recommended. No threshold dose should, therefore, be established for genotoxic mycotoxins. Among mycotoxins, genotoxicity is so far fully established only for AFB1 and is still matter of debate for OTA. Due to its genotoxicity no safe dose can be
378
Carlo Brera et al.
postulated for AFB1 and the principle of ALARA (as low as reasonably achievable) is applied at European level in Regulation (CE) 1881/2006 [77]. Recently, it was however recognized that the principle of ALARA could be misleading since it does not provide the risk managers with the necessary basis for priorities; in addition, the approach of deriving the ‘‘safe dose’’ through extrapolation methods has been criticized in favour of approaches aimed at the establishment of a ‘‘margin of exposure’’. Therefore, the Scientific Committee of the EFSA recently put forward an opinion addressing the risk assessment of substances that are both genotoxic and carcinogen [78]. It is desirable that the case of AFB1 could be re-evaluated under this new perspective. As for carcinogenic mycotoxins, the IARC evaluated in 1993 the available studies on OTA, fusarin C, ZEA, DON, NIV, fusarenone X, T-2 [79] and in 1993 and again in 2002 the available studies for aflatoxins and fumonisin B1 [80]. The outputs of the evaluations were the following: AFB1 was assigned in Group 1 (with sufficient evidence of carcinogenicity in humans resulting in the evaluation of carcinogen to humans); AFM1, OTA and F. moniliforme (including FB1) toxins in group 2B (insufficient evidence of carcinogenicity in humans and sufficient evidence of carcinogenicity in experimental animals resulting in the evaluation of possibly carcinogenic to humans), ZEA and patulin in group 3 (for ZEA limited evidence in animals and for patulin negative evidence in humans and insufficient evidence for animals). A threshold dose should theoretically not be defined for carcinogenic DNAreactive mycotoxins, but only for mycotoxins with an indirect carcinogenic mechanism and for non-carcinogenic mycotoxins. For the two latter cases a ‘‘safe dose’’ is estimated usually as provisionally tolerable daily intake (PTDI) or acute reference dose (RfD), the latter being less used in mycotoxin evaluation since it is more appropriate in cases of high short-term dose or single exposure. The TDIs for the main mycotoxins have been obtained and reported in Table 1. For some mycotoxins the risk assessment process has been performed by various organizations under diverse toxicological basis and extrapolation methods, therefore resulting in different values for the proposed TDI or in other ‘‘safe dose unit measurements’’ such as provisional tolerable weekly intake (PTWI) as in the case of OTA. For this toxin a TWI was recently put forward by EFSA [81]. In addition, it is questionable if the impact on human health attributable to the combined toxic effect of mycotoxins could be higher than the impact attributable to the mycotoxins alone. This consideration is obviously valid for other classes of toxic compound, but for mycotoxins it could imply profound consequences due to the largely proven coexistence of several mycotoxins in food commodities. The issue was recently addressed by Speijers and Speijers [82] with particular reference to trichothecenes. The toxicology of mycotoxins can be reviewed both through their impact on biological systems/organs as reviewed by Richard [83] and Fung et al. [84] and by considering the toxic effects of the single mycotoxins. Most of the toxicological evaluation is based on studies/observations on experimental/farm animals, the epidemiology of toxic effect of mycotoxins is still scarcely developed, although
Mycotoxins
Table 1
379
TDI/TWI for the major mycotoxins
Mycotoxin
TDI (ng/kg bw per day)
Organization
OTA
4 5 5 14 120 (TWI) 2,000 2,000 400 3,000 1,000 1,000 1,000 1,000 100 100 500 200 400 400 400
Health Canada (1989, 1996) Nordic Council (1991) EU (1998) JECFA (1996, 2001) EFSA (2006 [81]) EU (2000) JECFA (2000) Health Canada (2001) Health Canada (1985) Health Canada (2001) Nordic Council (1998) EU (1999) JECFA (2000) Health Canada (1987) Nordic Council (1998) JECFA (2000) EU (2000) JECFA (1996) EU (2000) Health Canada (1996)
FBs
DON
ZEA
Patulin
Source: Adapted from Ref. [67].
some results are available for some toxins. The JECFA evaluated the potential risks for aflatoxins and OTA in 1987, 1997 and 1999 [85–88]. In the last report the evaluation for fumonisins B1, B2 and B3, DON and T-2 and HT-2 toxins have also been performed. The herein reported information are related to the major mycotoxins most of them being derived from those sources. For OTA, the reference report has been the EFSA opinion [81]. Information on the toxic effect of mycotoxins is given in the Table 2.
3.3 Quantitative evaluation of human exposure to mycotoxins In the frame of soundly evaluating the impact on human health due to mycotoxins, as usually performed in risk characterization, both the level of exposure of population and the sensitivity of particular groups shall be taken into account. For threshold mycotoxins, risk characterization matches the level of daily exposure lifetime with the TDI of the toxins. Whenever data are insufficient to obtain a TDI or for non-threshold mycotoxins, the exposure can usefully be compared with the NOEL (no observed adverse effect level) or the LOAEL (lowest observed adverse effect level) of the various toxins [67]. Therefore, uncertainties in risk characterization of mycotoxins reflect both hazard
380
Table 2
Carlo Brera et al.
The toxic effect of mycotoxins
Mycotoxin
Toxic effect
References
Aflatoxins
In animals: hepatoxicity and hepatocellular carcinoma. Aflatoxins intake seems to be able to reduce the resistance to bacterial, fungal and parasitic infections, suppressing the cell-mediated immune response In humans: the chronic toxicity of AFB1 is usually linked to hepatocellular carcinoma (studies performed before 1980 in population from Thailand, Kenya, Mozambique and Swaziland). AFB1 is considered the most potent carcinogen of the aflatoxins The carcinogenicity of AFB1 is higher in people carrier of hepatitis B virus In animals: carcinogenic to rodents; nephrotoxic, neurotoxic, teratogenic and immunosuppressive activity Genotoxicity is in debate. In humans: BEN and the development of urinary tract tumours are supported by epidemiological data Kidney is the target organ for OTA in all mammalian species, with the exception of mature ruminants, with wide differences reported within species and sex EFSA reported the recent toxicological data indicating that the site-specific renal toxicity as well as the DNA damage and genotoxic effects of OTA are most likely attributable to cellular oxidative damage In animals: affects the reproductive system of animals causing vulvovaginitis and estrogenic responses in swine In humans: suspected to be, together with its metabolites, an aetiological agent for premature thelarche, pubarche and breast enlargement in young children or fetuses exposed to this estrogenic compound In animals: rodents, non-human primates and other animal species fed with FB1-contaminated diets demonstrated the toxic effect in the liver and kidney. In horses and other equids, equine leukoencephalomalacia (ELEM) In humans: the consumption of FBs contaminated corn has been correlated with oesophageal cancer in regions of South Africa and China even if it does not subsist yet a confirmation of a direct implication
[89,90]
OTA
ZEA
FBs
[3]
[78]
[91,92]
[93,94]
[95,96]
Mycotoxins
381
Table 2 (Continued ) Mycotoxin
Patulin
Trichothecenes
Toxic effect
References
The consumption of contaminated corn was also considered as a cofactor in the high incidence of liver cancer in China Risk factor for neural tube defects in South Africa, China and in Southwestern USA Embryotoxicity accompanied by maternal toxicity and no reproductive or teratogenic effects Cytotoxicity and of some of the genotoxic and immunotoxic effects arose from the reaction of the patulin with the sulfhydryl group Antibiotic properties In animals: symptoms of acute/subacute toxicity of DON include vomiting, feed refusal, weight loss and diarrhea. Emesis and anorexia are mediated by the serotonergic system in the central nervous system (CNS) or via peripheral actions on serotonin receptors. In humans: DON, NIV, T-2 and HT-2 are considered the most important for human health although the paucity of available occurrence data on the last three toxins does not allow the EU Commission to consider the possibility of imposing maximum toleration for their presence in food
[97]
[94] [98] [82]
[99] [100]
[101]
Note: BEN, Balkan endemic nephropathy.
identification and exposure-related uncertainties. An opinion related to the uncertainties in dietary exposure assessment has been recently issued by the EFSA [102]. Exposure assessment for the more relevant mycotoxins has been carried out in Europe for many years. The mycotoxins so far considered in the framework of the Scientific Cooperation on Questions relating to Food (SCOOP) project tasks were aflatoxins in 1995 [103], OTA in 1996 and 2002 [104,105], patulin in 2003 [106] and Fusarium toxins also in 2003 [107]. The evaluations have been performed with a point estimate approach on the basis of the occurrence and consumption data available at the time of the exercise. In conclusion for OTA, FBs and patulin seem to be rather reassuring since the intakes of the toxins as derived from the SCOOP reports are generally below the TDIs. Any sound conclusion could be derived from the other Fusarium toxins, since the available occurrence data were not sufficient for deriving scientifically based intake values. However, some critical points and limitations of the SCOOP exposure assessments need to be highlighted.
382
Carlo Brera et al.
Among the factors implying the underestimation of the intake can be mentioned: (i) the accuracy of the sampling methodologies employed in the less recent occurrence data, (ii) the lack of data on mycotoxins occurrence for all the food matrices susceptible to contamination; as a consequence, in the total intake data the contribution of a certain number of food matrices were missing. This could be particularly relevant for OTA that is known to be eventually present in a large number of food commodities. Additional factors leading to underestimation/overestimation of the intake data from the SCOOP tasks are the evaluation of the data under the limit of detection (LOD) in the final estimate, the effect of technological procedures and the questionable compatibility of the food categorization systems between occurrence and consumption data. The intake of mycotoxins has also been evaluated in some countries by adopting methodologies other than the point estimate through occurrence and consumption data. Among them, the total diet approach has been recently followed by several countries, including France and Italy. In the French study [108], the intakes of OTA, aflatoxins including AFM1, patulin and trichothecens, FBs and ZEA have been evaluated. The intake results were as follows: for OTA the estimated average intake is 2.2 ng/kg bw/day for normo-reporters adults, 4.1 ng/kg bw/day for children (aged 3–14 years), while the 95th percentile exposure is 3.6 ng/kg bw/day and 7.8 ng/kg bw/day for the above groups of population. For vegetarian populations, the average intake was between 2.2 and 3.7 ng/kg bw/day depending on the group studied (ovolattovegetarian, lattovegetarian and vegan/macrobiotic) and the respective 95th percentiles values are 3.7 ng/kg bw/day for the first two groups and 8.5 ng/kg b.w./day for the third. The main food contributors to the intake were cereals and cereal products (70%), while the many other vectors (mainly grape-derived products, coffee, nuts and oilseed) contributed for less than 5% each). For vectors contributing similar results were found in the SCOOP task for OTA. However, the total diet methodology is more complete in terms of comprehensiveness of all the susceptible matrices. For aflatoxins the proportion of population exceeding the threshold of 1 ng/kg bw/day suggested by SCF/JECFA is in the range 0.01–3.4% for adults and children (3–14 years), and in the range 2.6–23% for the various classes of vegetarians. In the same study and for population other than vegetarians the intake of AFM1, patulin, trichothecens and FBs is very low as compared with the provisional daily intake proposed by JEFCA or SCF. Vegetarians resulted in more exposure, a proportion of them ranging from 3.8% (for DON and NIV) to 31% for ZEA exceeding the TDIs proposed by JEFCA or SCF. The explanation for this latter finding relies on the high percentage of susceptible cereals in the diet of this group of population. The Italian total diet study [109] on the exposure of Italian population to FB1 concluded that the intake was below the TDI value (2 mg/kg bw/day) suggested by the EU Scientific Committee for food, however being higher in the North West of Italy during winter.
Mycotoxins
383
A more modern methodology for the evaluation of risk characterization of mycotoxins is under development under the umbrella of the SAFEFOODS project (http://www.safefoods.nl) and is based on the probabilistic evaluation of both the hazard and exposure characterization.
3.4 Tolerable maximum limit for mycotoxins in food During the last few decades the knowledge of the health effect of mycotoxins in humans and animals has prompted many countries to establish maximum tolerable levels in food and feed. A recent enquiry from FAO [110] reviewed the topic. The main factors driving the establishment of maximum limits are the consideration of health effects and the economic interest of producers and traders. Other factors influencing decisions are the availability of information on the occurrence and exposure as well as that of sampling and analysis methods. According to the FAO report, up to 2003, at least 99 countries had mycotoxin regulation in a large variety of food and feed. The total population covered by mycotoxins legislation represents the 90% of the world’s inhabitants. Limits have been established for aflatoxins, OTA, patulin, ZEA and Fusarium toxins in most of the regulated countries. Depending on local needs minor mycotoxins are regulated such as agaric acid and phomopsin in Australia and New Zealand. Still a quite large range of limits can be observed among regulated countries: AFB1 (1–20 mg/kg in 56 countries), total aflatoxins (0–35 mg/kg in 75 countries), OTA (2.5–50 mg/kg in 37 countries), DON (300–2,000 mg/kg in 37 countries), ZEA (50–1,000 mg/kg in 16 countries), FBs (1,000–3,000 mg/kg in 6 countries), patulin (5–100 mg/kg in 33 countries). Europe has the most complete and detailed mycotoxin regulation, providing limits for a large variety of mycotoxins and foodstuff in also establishing limits in baby foods and food for medical purpose. Mycotoxin regulation in Europe is still evolving and Regulation 1881 of 2006 [77], setting maximum levels for certain contaminants in foodstuffs, provides a collection of all the limits established so far.
4. SAMPLING To make available reliable samples consists of (i) the decision of ‘‘why, where and when’’ to take samples, in other words, the process of statistically individuating the populations (sites) from which food samples should be taken; (ii) the process of ‘‘how’’ to take representative samples from the lot under investigation. While the first point has features common to other analytes, the second one presents almost unique characteristics for mycotoxins since only a few units (approximately 0.1% for a wide variety of agricultural commodities) are likely to be highly contaminated, resulting in an overall significant contamination of the lot [111,112]. Due to this heterogeneous distribution, the mycotoxin concentration in a bulk can be assumed the
384
Carlo Brera et al.
same as in a small sampled and analysed portion of the lot, only if an appropriate sampling plan is applied. The topic has been recently reviewed by Miraglia et al. [113]. Without the implementation of a good sampling plan a misclassification of the lot can easily occur, implying negative impact on the ultimate scope of the sampling: for monitoring/surveillance purposes a poorly developed sampling plan will result in false information on the level of contamination of the lot (usually false negative). In turn, a wrong contribution to the monitoring/ surveillance database to be used by risk assessors/managers will be given. For quality assurance purposes, incorrect sampling can likely imply undesirable economic and trade impact. Among the steps usually employed in the evaluation of the mycotoxin level in a lot (sampling, sample preparation and analysis), sampling step is by far the largest contributor to the total error, the associated variability being largely dependent on the level of the toxin. Since 1993, it was recognized that a sampling plan is a function of the employed testing procedures and of the acceptance/ rejection limit; the limit can or cannot be the legal depending on the ultimate scope of the sampling [114]. The variability associated with the sample preparation has so far been described for aflatoxin in several crops, for FBs in corn and for DON in wheat. In all cases, for a given size of sub-sample a decrease of the variance with a decrease of the particle size has been demonstrated. The slurry procedure can contribute to reduce the sample preparation variability with respect to the dry grinding [115]. Due to the variance associated with each step of the mycotoxin evaluation, a 100% level of certainty is far from being achievable; an overestimation leads to a risk for the seller/producer that a good lot could be wrongly rejected, while an underestimation can result in the buyer/ consumer risk of acceptance of a ‘‘bad’’ lot that, when processed, will produce food or feed not acceptable from the health or the trade point of view. The aim of any good-sampling plan is to reduce the above risks. Currently the most complete legislative reference for the issue has been given by the EU that since 2001 put in force a package of directives concerning sampling procedures for the most prominent mycotoxins, namely aflatoxins, patulin, Fusarium toxins and OTA. Recently the Commission Regulation 401/2006 [116] gives provisions for the sampling of the regulated mycotoxins in food (cereals and derived products, dried fruits, groundnuts, nuts, spices, milk and derived products, coffee and derived products, fruit juice and solid apple products). The basic principle underlying the provided sampling plan is the sampling of an usually high number of incremental samples evenly distributed in the lot, the gathering of the collected incremental samples in a number of aggregate (generally one) samples, the grinding or slurring of the aggregate(s) samples and the deriving of the laboratory samples from the aggregate sample(s). The number and weight of the incremental samples and the aggregate sample(s) are dependent from the matrix, and from the size of the lot under consideration.
Mycotoxins
385
5. ANALYTICAL METHODS 5.1 Introduction Notwithstanding the relevance of the sampling step in the mycotoxin evaluation, the quali/quantitative analysis represents the core of the whole process, huge efforts have been devoted in previous decades to the optimization of this step. Actually, before the implementation of the practical analysis, the analyst has to face many decisions, the first one being the selection of the fit-for-purpose method. Monitoring, exposure assessment, official control issue, quality control at production and research are all activities that require appropriate methods, the parameters to be weighed as the required limit of detection/quantification, achievable costs, required time of analysis, number of samples/time and need of rapid answer. In this section an overview of the methods for mycotoxin analysis is given. The classification of methods can be performed on different bases. With respect to the reliability and accountability of the results, methods can be:
Official Reference Confirmatory Screening.
Classification can be also usefully done according to the type of the chemical/ biological/physical principle used and the time of analysis: Chromatographic methods (HPLC, gas chromatography (GC), thin layer chromatography (TLC), liquid chromatography tandem mass spectrometry (LC-MS/MS)) Rapid methods (enzyme-linked immunosorbent assay (ELISA), lateral flow device (LFD), dip-sticks) Alternative methods (Biosensor, near- and mid-infrared spectroscopy (NIR/ MIR), capillary electrophoresis (CE), fluorescence polarization immunoassay (FPIA)). As a general rule, each laboratory involved in a loop leading to a final measurement of an analyte, such as mycotoxins, should address any effort to reach a high degree of analytical quality in terms of reliability of its measurements. More and more stringent is this need if applied to laboratories involved in official control activities. To stress this simple assumption, it should be reminded that the European legislation laid down in 2000s rendered mandatory, for laboratories, the existence of a quality assurance/control system and the requirement of being accredited. Some of the key elements to be satisfied for accreditation purposes are the use of validated methods (from inter or singlelaboratory trials), the participation to proficiency testing, the use of (certified) reference materials and the adequate training of the personnel.
386
Carlo Brera et al.
5.2 Sample preparation Mostly, the typical steps in mycotoxin analysis are represented by the extraction, clean-up and detection. In a few cases extraction and/or clean-up are not necessary.
5.2.1 Extraction step The very first step for food and feed analysis is usually represented by the extraction of mycotoxin from the matrix. The conventional procedures are liquid/ liquid extraction, employing a mixture of aqueous organic solvents depending on the mycotoxins (Table 3), and performed by stirring or by homogenization. Non-conventional extraction includes ultrasonic system, microwaves, accelerated solvent extraction (ASEs, Dionex Corporation, 1228 Titan Way, Sunnyvale, CA 94085, USA) [117–119], and supercritical fluid extraction (SFE). The ASE is an automated extraction technique that aims to reduce time and organic solvent volume required to perform traditional sample preparation. ASE uses a combination of elevated pressure and temperature with common liquid solvents to increase the efficiency of the extraction process. Supercritical fluids can be used to extract analytes from samples [120]. The main advantages of using supercritical fluids for extraction is that they are inexpensive, contaminant-free and less costly to dispose of safely with respect to organic solvents.
5.2.2 Clean-up step The main clean-up procedures are liquid/liquid partition, solid phase extraction (SPE) and multifunctional solid phase extraction (Mycoseps SPE). Polar, nonpolar and ion exchange-based SPE are commercially available. Mycosep cartridge is packed with different adsorbent material with the aim to retain particular groups of compounds that may create interferences in analytical methods. Multifunctional SPE columns allow mycotoxins to pass through aiming to remove the interferences from the sample. A number of analytical methods for multimycotoxin analysis include the use of SPE also for minor mycotoxins analysis [121–123]. The use of multimycotoxin cartridge OASIS HLB (Waters) [124], allows the simultaneous determination of DON, NIV, HT-2 and T-2 toxins. Table 3
Solvent for liquid/liquid extraction of mycotoxin analysis
Mycotoxin
Solvents
Aflatoxins OTA ZEA Trichothecenes FBs
Methanol/water, acetonitrile/water, acetone/water Methanol/NaHCO3 3%, acetonitrile/water Acetonitrile/water, methanol, acetonitrile Acetonitrile/water, water Methanol/water, acetonitrile/water, acetonitrile/methanol/ water Ethyl acetate
Patulin
Mycotoxins
387
The immunoaffinity columns (IAC), containing specific antibodies, have the purpose to specifically bind the mycotoxin as first step, followed by mycotoxin elution because of the antibody denaturation. IAC improvements are represented by the availability of multifunctional columns for the simultaneous determination of different mycotoxins and by the setting up of reusable IACs. The multimycotoxins now available are for aflatoxins and OTA and for aflatoxins/ OTA/ZEA [125]; new IAC columns for aflatoxins/FBs/OTA/ZEA/DON and aflatoxins /FBs /OTA/ZEA/DON/T-2 will be finalized in the year 2008. As for the advantage/disadvantage evaluation, SPE is rapid and offers the possibility of a multimycotoxins analysis; however, it is not really selective. The IAC is a good fit for the mycotoxin analysis in complex matrices as food and feed, since it is highly selective and allows high accuracy and sensitivity. The major disadvantage of IAC is represented by the fact that columns can only be used once and their costs are high. SPE and IAC are commercially available for almost all the major mycotoxins. The molecularly imprinted polymers (MIPs) are artificially synthesized polymeric matrices, highly stable, that show the capacity to recognize and specifically interact with particular substances. Polymeric stationary phases obtained by the technique of molecular imprinting, are valid alternatives to the immunoaffinity phases in terms of limited costs, column stability and reproducibility [126–128]. An MIP which recognized OTA, was prepared in a co-polymerizing reaction where a basic functional monomer, a cross-linking agent and a template miming OTA (a chloro-naphthoylamide) [129,130], makes a three-dimensional polymer structure with a high-binding capacity capable of recognizing the mycotoxin from various biologically relevant matrices. The molecular imprinted molecules have demonstrated the potential as a technique for the separation of analytes with a high degree of selectivity both for clean-up as an SPE adsorbent [131] and for packaging HPLC columns with polymer particles as in the case of molecularly imprinted molecules for DON and ZEA [132].
5.3 Determination and detection 5.3.1 Chromatographic methods 5.3.1.1 High-performance liquid chromatography. A wide variety of methods for most mycotoxins are based on HPLC, which is the methodology of choice for aflatoxins, OTA, ZEA, FBs and patulin. The HPLC separation is followed by fluorescence detection for aflatoxins, OTA, ZEA and FBs, usually as derivative compounds. UV detection is used for DON and patulin determination. Advantages of HPLC determination include excellent performance characteristics, low detection levels (as low as 0.1 ng/g) and safety for the operator. For aflatoxins, a large number of HPLC-based methods are available. The AOAC method 49.2.19A includes a Mycoseps clean-up procedure, followed by fluorescence detection of the trifluoroacetic acid (TFA) derivative, for aflatoxins in corn, almonds, Brazil nuts, peanuts and pistachio nuts [133]. The multifunctional column contains a mixture of reversed-phase, ion exclusion and ion exchange
388
Carlo Brera et al.
adsorbents. Packing retains interferences such as fats, proteinaceous compounds, pigment and carbohydrates extracted from the matrices. Methods including IAC and post-column derivatization with pyridinium bromide perbromide (PBPB) are reported for the determination of AFB1 and total aflatoxins in peanut butter, pistachio paste, fig paste and paprika powder [134], and for AFB1 determination in baby food (infant formula) [135]. Other derivatization reactions for aflatoxin analysis include post-column derivatization with iodine [136], electrochemically generated bromide (Kobra Cell) [137,138], photolytic derivatization [139] and pre-column derivatization with TFA [140]. HPLC methods, without any derivatization step, are also reported for the determination of AFM1 in milk and cheese [141,142], since this aflatoxin shows native fluorescence that allows this simplification in the analytical procedure. Methods for OTA determination by HPLC, mainly based on fluorescence detection, are available for different matrices. Official methods include OTA determination in barley, roasted coffee [143], baby food, and wine. Since OTA shows native fluorescence usually no derivatization step is required for the detection of this toxin. For confirmation purposes three methods are usually adopted, based on methylation [144,145], ammonia-derivative formation [146] or direct determination by LC-MS [147,148]. Notwithstanding, trichothecenes are frequently analysed by GC, HPLC methods are also available, such as that developed by Trucksess et al. [149] for DON in wheat-finished products. The purification step is performed by passing the extract through an SPE cartridge, and the HPLC separation is followed by UV determination. The LC determination of ZEA and a-zearalenol (a-ZOL) in corn was collaboratively studied by Bennett et al. [150]. The determination of ZEA and a-ZOL using UV or fluorescence detection has been adopted as an official method by AOAC [126]. The extraction is based on liquid/liquid partition between CHCl3 and water with the aid of diatomaceous earth. Other methods based on HPLC and fluorescence detection are reported by Tanaka et al. [151] and Seidel et al. [152]. FB analysis is usually performed by reversed-phase LC with fluorometric detection after pre-column derivatization with o-phtaldialdehide (OPA)/ 2-mercaptoethanol [153,154]. An AOAC-IUPAC collaborative study develops an LC method, based on the previous use of SPE cartridges for the determination of fumonisins B1, B2 and B3. This method has been adopted by AOAC International as an official first action method for corn analysis [133]; however, the method could not be successfully applied for the analysis of corn-based food products such as corn bran flour, corn bran breakfast cereals, mixed baby cereals and cornflakes due to low recoveries and inadequate clean-up. The use of IACs for the clean-up step has been reported to produce higher FB recovery [155]. LC with fluorescence detection is still the method of choice for the determination of FBs [153,154]. An AOAC-IUPAC collaborative study developed an LC method, based on the use of SPE cartridges and OPA as pre-column derivative agent for the determination of FB1, FB2 and FB3. This method was accepted as an official method of analysis [133]. A collaborative study was also
Mycotoxins
389
preformed using IAC clean-up and pre-column derivatization with OPA. The method is suitable for the determination of FB1 and FB2 [156]. The use of SAX (strong anion exchange)+C18 in the clean-up step for FBs analysis was presented by Moller and Gustavsson [157]. Also for patulin, HPLC determination is preferred. Since there is no IAC for patulin, the sample preparation step is different. According to the method reported by Mac Donald [158], the sample is extracted with ethyl acetate, employing the enzyme pectinase for ameliorating the extraction performance on fruit matrix, dried under a stream of nitrogen, redissolved in mobile phase and determined with HPLC. Patulin detection and quantification is then performed with UV detection (276 nm). A combination of Extrelut and Florisil cartridges for the patulin determination in apple cider [159] by LC method is used for extraction and clean-up steps. The use of SPE was also reported by Trucksess [160]. Minor mycotoxins analysis is also performed by HPLC, methods with fluorescence detection are reported for citrinin determination [161,162]. A method for the determination of cyclopiazonic acid in corn and rice by HPLC and UV with a photodiode array detector is reported [163]. The determination of cyclopiazonic acid in cheese is also performed by HPLC anticipated by an SPE clean-up step [123]. A wide number of HPLC methods for the analysis of various mycotoxins, tested by collaborative studies to evaluate their effectiveness, are periodically reported on Methods Committee Reports published in Journal of AOAC International. Validated methods for mycotoxins determination are also collected by CEN within WG5 Biotoxins of TC275. An overview of the official methods available for mycotoxins analysis is reported in Table 4. Mycotoxins HPLC chromatograms are shown in Figures 7 and 8.
5.3.1.2 Gas chromatography. Since trichothecenes do not strongly absorb in the UV-Visible range and are non-fluorescent, GC-based methods represent the most widely employed technique for their determination. In particular, the analytical techniques employing GC and capillary column are useful for the simultaneous determination of different trichothecenes. For the detection step heptafluorobutyryl (HFB), trimethylsilyl (TMS) and trifluoroacetyl derivatives are frequently used coupled with electron capture detection (ECD) [164,165]. However, MS is strongly recommended for peaks confirmation. A GC method for trichothecenes determination in barley and malt [166] has been validated and accepted by the American Society of Brewing Chemists in its Methods of Analysis, 8th ed. A method, for trichothecenes determination in barley and malt, has also been developed by supercritical fluid chromatography (SFC) [167]. Supercritical fluids can be used as the mobile phase to separate analytes with either a packed or capillary GC column. Compared with GC, capillary SFC can provide high-resolution chromatography at much lower temperatures. A GC method for the determination of DON in wheat is reported by AOAC Official methods [168].
390
Table 4
Carlo Brera et al.
List of Official AOAC and CEN methods
Mycotoxins
Matrix
Reference
Method
Aflatoxins (AFB1, AFB2, AFG1, AFG2)
Peanuts, pistachios, figs, and paprika powder
AOAC-999.07 CEN–EN 14123:2003
Aflatoxins
Nuts and nut products
AOAC–2005.08
Aflatoxins
Almonds, peanuts, pistachio nuts, brazil nuts Peanut butter Cereals, shell fruits and derived products
AOAC-994.08
IAC-HPLC with post column derivatization and fluorescence detection HPLC with postcolumn photochemical derivatization Mycosep-HPLC
AOAC-991.45 AOAC-991.31 CEN–EN 12955:1999
Aflatoxins Aflatoxins (AFB1 and AFs)
Aflatoxins (AFB1, AFB2, AFG1) AFB1
Corn
AOAC-993.16
Feeding stuffs
AOAC–2003.02 CEN–EN ISO 17375:2006
AFB1
Baby foods
AOAC–2000.16
Aflatoxins AFM1
Peanuts and corn Milk and milk powder
AFM1
Milk and milk powder Milk and cheese Foods for infants and young children Corn and barley Cereals and derived products
AOAC-993.17 AOAC–2000.08 CEN–EN ISO 14501:1999 CEN–EN ISO 14675:2003 AOAC-980.21 CEN-New itema
AFM1 AFB1
OTA OTA
AOAC–991.44 CEN–EN ISO 15141-1:1998
ELISA IAC-HPLC with post column derivatization and fluorescence detection ELISA IAC-HPLC with post column derivatization and fluorescence detection IAC-HPLC with post column derivatization and fluorescence detection TLC IAC-HPLC with fluorescence detection ELISA TLC –
HPLC Silica gel clean-up– HPLC with fluorescence detection
Mycotoxins
391
Table 4 (Continued ) Mycotoxins
Matrix
Reference
Method
OTA
Cereals and derived products
CEN–EN ISO 15141-2:1998
OTA
Barley
AOAC–2000.03
OTA
Roasted coffee
AOAC–2000.09
OTA
Barley and Roasted coffee
CEN–EN 14132:2003
OTA
Wine and beer
OTA OTA
Green coffee Barley and green coffee Foods for infants and young children Dried (vine) fruit
AOAC–2001.01 CEN – EN 14133:2003 AOAC–2004.10 AOAC–975.38
Bicarbonate cleanup–HPLC with fluorescence detection IAC-HPLC with fluorescence detection IAC-HPLC with fluorescence detection IAC-HPLC with fluorescence detection IAC-HPLC with fluorescence detection HPLC TLC
OTA
OTA
DON DON
DON
DON ZEA ZEA
ZEA
ZEA ZEA Fumonisins (FB1, FB2, FB3)
Wheat Cereals (including maize) and cereal products Foods for infants and young children Wheat Corn Cereals (including maize) and cereal products Foods for infants and young children Wheat and animal feed Corn Corn
CEN-New itema
CEN-New itema
AOAC–986.18 CEN-New itema
IAC–HPLC with fluorescence detection IAC–HPLC with fluorescence detection GC IAC–HPLC with UV detection
CEN-New itema
–
AOAC-986.17 AOAC–985.18 CEN-New itema
CEN-New itema
TLC HPLC IAC–HPLC with fluorescence detection –
AOAC-994.01
ELISA (qualitative)
AOAC-976.22 AOAC – 995.15
TLC HPLC
392
Carlo Brera et al.
Table 4 (Continued ) Mycotoxins
Matrix
Reference
Method
Fumonisins (FB1, FB2)
Maize based foods
AOAC–2001.04 CEN–EN 14352:2005
Fumonisins (FB1, FB2)
Maize
CEN-EN 13585:2002
FBs Fumonisins (FB1, FB2)
Corn Maize based foods for infants and young children Clear and cloudy apple juice and puree
AOAC-2001.06 CEN-New itema
IAC-HPLC with pre column derivatization and fluorescence detection SPE-HPLC with pre column derivatization and fluorescence detection ELISA -
Patulin
Clear and cloudy apple juice and puree
CEN-EN 14177:2004
Patulin Patulin
Apple juice Clear and cloudy apple juice and puree for infant and young children
AOAC-974.18 CEN-New itema
Patulin
AOAC–2000.02
Liquid/liquid partition cleanup–HPLC with UV detection Liquid/liquid partition cleanup–HPLC with UV detection TLC Liquid/liquid partition cleanup and SPE– HPLC with UV detection
a
Methods of analysis ready to be mandated according to the Mandate for standardization addressed to CEN in the field of methods of analysis for mycotoxins in food. Deadline 12/2008.
GC coupled with MS could be used for the confirmation of patulin in apple juice [155]. GC/MS methods are also reported operating both without [169] and with various derivatizing agents [170,171]. Limitations such as the need to derivatize the samples before analysis have led to a prevalence of LC-MS over GC-MS approaches [172]. Figure 9 shows a chromatogram obtained after separation and detection with GC-ECD after trimethylslylation of five B trichothecenes.
5.3.1.3 Thin-layer chromatography. The employment of TLC-based methods has decreased steadily over the past few years, but, especially in developing countries, this analytical technique is still routinely used. TLC methods allow for
Mycotoxins
393
Figure 7 HPLC chromatogram of a corn sample naturally contaminated with aflatoxins. Level of contamination: AFB1 and AFG1, each at 6.03 mg/kg, and AFB2 and AFG2, each at 1.49 mg/kg.
Figure 8 HPLC chromatogram of a wheat sample naturally contaminated with OTA. Level of contamination: 4.53 mg/kg.
a precise determination at levels not lower than 2 ng/g; their disadvantages however include the use of solvents that are considered to be ecological hazard. TLC techniques have been reviewed and updated for the analysis of selected Fusarium toxins by Krska [120]. A large number of TLC-based methods have been
394
Carlo Brera et al.
Figure 9 Gas chromatogram for wheat spiked with DON, 3-AcDON, 15 Ac-DON, Fus-X, and NIV at a concentration of about 1,000 ng/g. Source: International Programme Chemical Safety (IPCS) Inchem, www.inchem.org DON.
accepted by the AOAC as official methods including the methods for the determination of DON in barley and wheat, for aflatoxins in peanuts and corn, for AFM1 in milk and cheeses, for OTA in barley and in green coffee and for ZEA in corn. All the above-mentioned methods are reported in Table 4. The proposed use of TLC in combination with IACs represents a promising application that can improve the performance characteristics of the TLC-based methods [173]. An improvement in the technique includes the use of a microcomputer interfaced with a fluorodensitometer to simplify data handling [174]. New detection techniques for TLC have also been developed as alternatives to traditional TLC scanners; the employed principles are based on the use of a semiconductorbased detection cell (SeBaDeC) or of a modified office scanner. As the cost of commercial office scanners is very low, these are of special interest for the quantification of mycotoxins whenever other instruments are not available, such as in developing countries, in which this technique still represents the most economic method for the analysis of trichothecenes.
5.3.1.4 Liquid chromatography-mass spectrometry. LC coupled with MS and especially, LC-MS-MS have become very popular in recent years, because of the universal, selective and sensitive detection. Combining HPLC with MS/MS results in a powerful tool for characterization and identification especially for
Mycotoxins
395
detection of the so-called conjugated mycotoxins, in which the toxin is usually bound to a more polar substance such as glucose or other sugars. These conjugated are referred to as masked mycotoxins, as these substances escape routine detection methods but can release their toxic precursors after hydrolysis [175]. Also with LC-MS there is currently a strong trend toward multimycotoxin methods for the simultaneous determination, particularly for mycotoxins belonging to different chemical families [176]. This approach has the advantage of enabling the reduction or possibly the omission of sample clean-up. Determination of DON and NIV in corn [177] and a rapid determination of FB1 are performed without any clean-up or purification step by a liquid chromatographic/tandem mass spectrometrer using pneumatically assisted electrospray ionization (HPLC-ESI-MS), the mass analyser being a triple-stage quadrupole equipped with a standard ESI interface [178]. Other methods described in the literature include a clean-up step, for example, graphitised carbon black for extracts from corn meal samples before LC-ESI-MS-MS multiresidue analysis [179]. An HPLC-ESI-MS method was developed for the determination of 18 mycotoxins and metabolites, OTA, ZEA, a-ZOL, b-ZOL, a-zearalanol (zeranol), b-zearalanol (taleranol), FB1, FB2, T-2 toxin, HT-2 toxin, T-2 triol, DAS, 15-MAS, DON, 3-acetylDON, 15-acetylDON, deepoxy-DON and AFM1, in milk [180]. Results confirm that, especially for multimycotoxin methods expanding over a broad range of classes, sample pretreatment is a critical step, because even within a single class of mycotoxins significant losses may occur during extraction or clean-up. A method for the determination of 39 mycotoxins in wheat and maize using a single extraction step followed by LC-ESI-triple-quadrupole MS without the need for any clean-up, has recently been developed and validated in-house [181]. The analytes included type-A and type-B trichothecenes and related derivatives including conjugated DON, FBs, ochratoxins, ZEA, aflatoxins, moniliformin, enniatins and ergot alkaloids; the limits of detection ranged from 0.05 to 220 mg/kg. The extraction solvent mixture, diluted 1:2, and injection without any clean-up, was chosen as a compromise for the extraction of the 39 analytes from both wheat and maize. In addition to the multianalyte requirement, multisubstrate methods are even more demanding. This approach, nevertheless, has the advantages of speed and ease of application with one method for multiple mycotoxin-matrix combinations over a broad range of mycotoxin classes, which is of special interest for high-throughput routine analysis. LC-MS instruments using atmospheric pressure chemical ionization (APCI) interfaces have recently been employed for the determination and identification of ZEA, trichothecenes, including DON and NIV, at trace levels [118,119,182,183]. Figure 10 shows a total ion LC-MS-MS chromatogram obtained after clean-up of a spiked maize sample containing 100 mg/kg of each mycotoxin.
5.3.2 Capillary electrophoresis CE is an analytical technique more and more extensively used in food analysis. It is generally used as a chromatographic technique, where mycotoxins are separated from one another and from matrix components using electrical
396
Carlo Brera et al.
Figure 10 Total ion chromatogram obtained after clean-up with MycoSeps #226 columns and LC-MS-MS analysis of a spiked maize sample containing 100 mg/kg of each mycotoxin. Vertical lines illustrate change of ionization polarities from negative to positive (5.4 min) and back to negative (6.4 min). Source: Berthiller et al. Ref. [172].
potential [184]. Its main advantages are reduction of organic solvents, small sample volume, increased efficiency and resolution. However, due to the rather high detection limit, the technique is not generally suitable for the determination of low concentrations of mycotoxins. A method for patulin determination in apple juice by CE is available and presents the advantage of a relatively low limit of detection (3.8 mg/L) [185]. A method allowing the simultaneous determination of ochratoxins A and B and four aflatoxins is also reported [186]. Micellar electrokinetic capillary chromatography (MEKC) is particularly useful for detecting neutral compounds such as aflatoxins [187]. Recent advances in mycotoxin detection with CE include the use of cyclodextrins. Since some cyclodextrins are capable of significantly enhancing the native fluorescence of the estrogenic mycotoxin ZEA, a CE method for ZEA determination involving cyclodextrins, with a limit of quantification of 5 ng/g, is reported [188], while b-cyclodextrins combined with multiphoton excitation are used for aflatoxins detection [189].
5.3.3 Rapid methods Rapid methods, or screening methods, should be simple and easy-to-use, the method should be fast and capable of testing also mycotoxins in field. Rapid methods allow the testing of a large number of samples, but the confirmation of positive ones is recommended. A high reliability of the screening methods is
Mycotoxins
397
based on a low number of false positive, as well as on a low percentage of false negatives (less than 5%). These techniques meet one of the needs of the food industry production, represented by the availability of rapid methods allowing the ‘‘on-line control’’ of mycotoxins in food. Biosensors and kits based on dipstick techniques are promising methodologies based on immunochemical reactions [190].
5.3.3.1 Fluorescence polarization immunoassay. Several FPIA formats were studied using agrochemicals, toxins and a food pathogen to determine whether this technology was quicker to perform yet equivalent in sensitivity to ELISA technology. The sensitivity of FPIA was similar to ELISA for detecting DON in cereal products. FPIA, however, was the least labour-intensive and required the lowest time to be performed. ELISAs required approximately 3 h to perform following incubation overnight with coating conjugate. In contrast, the FPIAs required less than 90 min to be performed and no coating of plates was required. A FPIA based on a monoclonal antibody for the determination of OTA was developed [191]. Fluorescein-labelled OTA derivative (tracer) was synthesized and purified by thin-layer chromatography. The optimized OTA-FPIA had a dynamic range from 5 to 200 ng/mL with IC50 value of 30 ng/mL and a detection limit of 3 ng/mL. The method developed was characterized by high specificity and reproducibility. Cross-reactivity with other mycotoxins (ZEA, aflatoxins, patulin and T-2 toxin) was negligible (o0.1%). The results of OTA determination in barley were compared with those determined by indirect competitive ELISA. Recoveries for the samples spiked at 50, 100 and 500 ng/g levels were 91, 90 and 97%, respectively, for FPIA, and 98, 98 and 102%, for ELISA. Naturally contaminated barley samples were analysed by these methods but some disagreement was observed between the results. The FPIA method can be applied for screening of food samples for OTA residues without a complicated clean-up. The principle of FPIA was also used for the determination of DON in wheat and for aflatoxin determination in grains [192–195]. A number of instrument- and antibody-based methods, including ELISAs, have been developed to detect ZEA and related toxins in commodities and food [196]. Although convenient, the commercial ELISAs for small molecules such as ZEN require a washing step to separate bound and unbound enzyme labels before detection. In FPIAs, separation of bound and unbound labels is not required, a property that reduces the time needed to perform the assays. An FPIA for ZEN in maize was developed, combined with a rapid extraction technique; the assay could be used to detect as little as 0.11 mg/g of ZEN in maize within 10 min. The assay showed cross-reactivity to the ZEN analogs such as zearalanone, a-zearalanol, a-ZOL, b-ZOL, and b-zearalanol of 195, 139, 102, 71 and 20%, respectively, relative to ZEN (100%). Recovery of ZEN from spiked maize samples over the range 0.5–5 mg/g averaged 100.2%. The FPIA results were comparable to those obtained with a liquid chromatographic method. The FPIA provides a rapid method for screening of maize for ZEN.
398
Carlo Brera et al.
5.3.3.2 Enzyme-linked immunosorbent assay. The technology of ELISA is based on the ability of a specific antibody to distinguish the three-dimensional structure of a specific mycotoxin. Steps to perform an ELISA analysis are herein described: after the solvent extraction of the mycotoxin from the ground sample, a portion of the extract and a conjugate of an enzyme-coupled mycotoxin are mixed and added to the antibody-coated microtitre wells. Any mycotoxin in the sample extract is allowed to compete with the enzyme-conjugated mycotoxin for the antibody-binding sites. ELISA-based methods represent user-friendly methods at relatively low cost, also having the advantage to reduce the amount of organic solvent employed for the analysis with respect to LC analytical methods. ELISA tests are recommended for screening analysis because simultaneous determination of a high number of samples is allowed. However, the disadvantages of this technique are represented by the possibility of obtaining false positives when a cross-reaction of the antibodies with other mycotoxins may happen, as well as false negatives, when low levels of contamination, often close to the legal limit, are not detected. Interferences of the matrices can also occur during ELISA analysis. Therefore, the ELISA methods are suggested as low-cost screening methods prior to confirmatory analysis, in order to considerably lower the costs, when a high number of samples have to be analysed [190]. The WHO provides the criteria for the acceptance/validation of immunoassay-based kits and of other protein-binding systems [197]. An ELISA method for the detection of aflatoxins and ZEA in corn, wheat and feed (Agri-screen method) has been tested by an interlaboratory study and accepted as AOAC official method [133]. Different brands of ELISA kit are available for almost all the major mycotoxins. For OTA analysis, the available ELISA test kits have been widely applied to cereals, cereal products, dried fruits, coffee, cocoa, wine and tea, beans, potatoes, maize, wheat, flour, barley and beer [198–200]. Many immunochemical methods are given for trichothecenes [201–203]. As for patulin, no ELISA kit is commercially available since no specific antibodies have yet been developed. The detection limits associated with these methods greatly depend on the mycotoxin being evaluated and on the specific kit employed. 5.3.3.3 On-line control methods. Based on the same principle of ELISA test, other and even more faster screening methods are available. These techniques are designed for on-line mycotoxin determination. Membrane-based immunoassay. This method is based on a principle of direct competitive ELISA, in this case the anti-mycotoxin antibody is coated on a membrane surface. The membrane-based immunoassay methods are rapid, easy-to-use, suitable for testing mycotoxins in the field, and they do not require any equipment. However, interpretation of results may be difficult when the toxin concentration in the sample is close to the method cut-off. A membrane immunoassay method for OTA determination in roasted and green coffee was developed [204,205]. The obtained results are consistent with those obtained employing LC determination. Test kits based on this
Mycotoxins
399
immunoassay have been validated for OTA determination in wheat, rye, maize and barley [206]. LFD test/card/dip-stick. The LFD, also called strip test, is an immunochromatographic test, fundamentally similar to a pregnancy test kit. A typical test strip is composed of a sample pad, a conjugated pad, a membrane, an absorbent pad and an adhesive support. A sample extract is simply added onto the sample pad. Any mycotoxin present binds to the anti-mycotoxin antibody gold particle complex in the conjugate pad and migrate together with the anti2nd antibody gold particle complex along the membrane. The membrane contains a test zone and a control zone, onto which a mycotoxin–protein conjugate and a 2nd antibody are dried, respectively. The mycotoxin–protein conjugate in the test zone can capture any free anti-mycotoxin antibody gold particle complex, allowing colour particles to concentrate and form a visible line. Hence, a positive sample with a mycotoxin concentration greater than or equal to the assay cut-off level will result in no visible line in the test zone. Conversely, a negative sample with a mycotoxin concentration less than the cut-off level will form a visible line in the test zone. The control zone will always be visible regardless of the presence or absence of mycotoxin because the 2nd antibody always captures the anti-2nd antibody gold particle complex indicating the validity of the performed test. These immunochromatographic tests are user-friendly, very rapid and are particularly suitable for testing mycotoxins in the field, since they are semi-quantitative methods; for any positive samples, confirmation by a reference method, such as HPLC, is required. A dipstick enzyme immunoassay for the rapid detection of Fusarium T-2 toxin in wheat was developed [207], and kit from Romer, AgraStrips Lateral Flow Kit, qualitatively determines the presence of aflatoxins B1, B2, G1 and G2, and can be performed in 5 min. Additionally dipstick tests have been developed, which claim a detection limit of FB1 as low as 0.04–0.06 mg/g in corn-based foods. These techniques couple the rapidity with the possibility to detect many mycotoxins simultaneously [208]. R-Biopharm Roˆhne Ltd. produces cards for the rapid determination of AFB1, total aflatoxins and OTA, while other tests are available by Neogen Corporation for the determination of aflatoxins, OTA, DON, ZEA and FBs. Charm Science Inc. produces the Rosas tests (Rapid One Step Assay) for AFB1 in cereals, DON in wheat and barley, OTA in wine and ZEA in corn. These latter tests provide positive/negative response and no equipment is required to read the distinct visual results. However, an optional digital reflectance strip reader has also been approved to verify results and electronically record test data. The threshold of the test is based on set legal limits for the different mycotoxins. A collaborative study for AFM1 determination in milk was recently performed for a Rosa test [209]. Biosensors are compact analytical devices that use biological components (nucleic acids, enzymes, antibodies, cells), associated with a transduction system that process the signal produced by the interaction between the target molecule and the biological component. The advantages of this technology may include
400
Carlo Brera et al.
more rapid assays, reusable and long-life sensor elements, the capacity for continuous monitoring and industrially low-cost devices [210]. The use of biosensors for the detection of aflatoxins is rapidly increasing, including disposable DNA electrochemical biosensors [211], handled immunoaffinity fluorimetric biosensors [212] and biosensors based on lipid films and liposomes [213]. Potential application of biosensor devices in combination with MIPs in mycotoxin analysis has been reported for the analysis of OTA in a linear range of 0.05–0.5 ng/g demonstrating a novel combination of biosensor device and MIP technique [214]. Biosensors used for the analysis of mycotoxin are those based on the interaction of a specific antibody, or an antibody fragment, and the mycotoxin: Optical immunosensor. In optical immunosensors monoclonal antibodies are covalently coupled with an optical fibre, studies of the detection of FB1 in a quantitation range of 10–1000 ng/mL with a limit of detection of 10 ng/mL has been carried out [215]; an antibody-bound glass prism surface uses SPR for the direct detection of FB1, AFB1, DON and multimycotoxin in general [216–220]. The evanescent wave-based fibre optic immunosensor is another optical immunosensor that was applied for detection of FB and aflatoxin in maize in a rapid effective screening assay but it requires a clean-up step to increase sensitivity (0.4 mg/g) [221–223]. Piezoelectric immunosensor. An alternative biosensor is the quartz crystal microbalance (QCM) where the transduction measures the mass change at the surface resulting from interaction of an analyte with the receptor immobilized at the surface of the crystal. Hauck reported the determination of OTA in liquid food products; the method was applied in a linear range of 2–100 ng/mL [224]. Electrochemical immunosensor (screen-printed electrodes). These immunochemically based assays are used for detecting mycotoxins in food and have seen rapid development for their simplicity, adaptability, sensitivity and selectivity. Screen-printed electrodes are (antibody-based) sensors, with electrochemistry as the basis of the technique. A screen-printed electrode system as transducer for chronoamperometry and a monoclonal antibody for molecular recognition, was applied for the detection of AFM1, the high selectivity of immunoanalysis with the convenience of electrochemical probes, have shown that AFM1 can be measured with a detection limit of 0.025 mg/kg with a working range between 0.030 and 0.160 mg/kg. A comparison between the spectrophotometric and electrochemical procedure showed that a better detection limit and shorter analysis time could be achieved using electrochemical detection [225]. Pemberton showed the development of a screen-printed carbon electrochemical immunosensor array for mycotoxins that have a detection limit as low as 0.15 ng/mL for AFB1 analysis [226]. Being this value compatible with the requirements of the food industry, further studies using real samples from food extracts are essential for the application of the array. Sensitive immunosensors, using an indirect competitive ELISA format, have been used for the determination of AFB1 in barley. The high selectivity and
Mycotoxins
401
simplicity of an immunoassay combines with high sensitivity, rapidity and low cost of electrochemical measurements. This immunosensor (coated SPCE) can be stored for up to one month, to be ready for in situ determination. The immunosensor exhibited a linearity range that is comparable to that for conventional methods (HPLC) and had also a detection limit suitable for on-site monitoring [227].
5.4 Other methods 5.4.1 Fourier transform infrared photo-acoustic spectroscopy (FTIR-PAS) This technique has been in the past few years desirable as a confirmatory alternative, especially for control and monitoring purposes, in which a high number of analyses with high reliability in a short time are requested. This possibility would also be useful to obtain information on the exposure to many mycotoxins and on the effect of combined exposure to human health. Two techniques, PAS and diffuse reflectance spectroscopy (DRS), were coupled to an FTIR spectrometer to provide information about the MIR absorption spectra of corn infected with F. moniliforme and A. flavus, two mycotoxin producers [228].
5.4.2 Near- and mid-infrared spectroscopy NIR, 700–2,500 nm, and MIR, 2,500–30,000 nm, spectroscopy is a practical spectroscopic procedure for the detection of organic compounds, and has been used routinely for many years in the field for determination of protein and moisture in cereals. The technique is useful because of its non-destructiveness, accuracy, rapid response and easy operation, and has the potential for determination of a number of compounds. The NIR methodology can be applied for monitoring mould contamination in post-harvest maize, to distinguish contaminated lots from clean ones and to avoid cross-contamination with other material during storage and may become a powerful tool for monitoring the safety of the food supply. Pattersson and Aberg [229] investigated the use of NIR transmittance instrumentation in the wavelength range 570–1,100 nm for finding out the mycotoxin DON in wheat kernel. Principal component analysis and partial least square regression calculations were used to formulate the best models. The wavelength range 670–1,100 nm gave the best regression model with a slope of 0.949 having a correlation coefficient of 0.984 with a standard error of 381 mg mycotoxin DON/kg of wheat. All spectra (570–1,100 nm) were collected using the FOSS Infratec 1241 Grain Analyser with the added colour module, and reference analysis using HPLC or GC methods. Based on current findings, it appears that NIR could also be used as a screening tool to measure DON in cereals. The applicability of NIR for the rapid identification of mycotoxigenic fungi and their toxic metabolites [230] produced in naturally and artificially contaminated products, indicated that NIR could accurately predict the incidence of kernels infected by fungi, and by F. verticillioides in particular, as well as the
402
Carlo Brera et al.
quantity of ergosterol and FB1 in meal. The statistics of the calibration and of the cross-validation for mould infection and for ergosterol and F B1 contents were significant. A method based on mid-infrared/attenuated total reflection (ATR), which enables the determination of fungal infection with F. graminearum on corn within minutes, has been developed [231]. After the spectra were recorded, they were subjected to principal component analysis (PCA) and classified using cluster analysis. Observed changes in the spectra reflected changes in protein, carbohydrate and lipid contents. DON served as reference parameter. The developed method enabled the separation of samples with DON content as low as 310 mg/kg from non-contaminated (blank) samples. The investigated concentration range was 310–2,596 mg/kg for DON. The percentage of correctly classified samples was up to 100% for individual samples compared with a number of blank samples. For both, the MIR and the NIR spectroscopic approach further work on calibration development and the expansion of the calibration databases will reveal the true potential of IR spectroscopy for this kind of application.
6. OCCURRENCE IN FOOD AND FEED As already discussedin this chapter, two opposite but related factors contribute to the persistence of mycotoxins in crops and commodities, that are natural and man-made causes much often coexisting. The presence of mycotoxins in food and feed is, in fact, due to several multifaceted factors including environmental conditions, mainly climate and insects as fungi spores vectors, improper agricultural practices, wrong postharvest activities, no specific HACCP plans and scarce implementation of decontamination procedures. For the above, only an integrated and systematic approach from the farm to the consumer aimed at the reduction of these potent toxic compounds can be put into practice in the future. Data available on worldwide mycotoxins occurrence are characterized by an extreme degree of non-homogeneity, in terms of number of samples analysed, quality of the analytical methodology used, adopted sampling procedures, finalities and objectives of the monitoring or survey programs, and representativity at national level of the performed surveys. For this reason, quite recently the European Commission, according to Council Directive 93/5/EEC ‘‘on the assistance to the Commission and co-operation by the Member States in the scientific examination of questions relating to food’’, member states of the EU co-operated on problems facing the Commission in the area of food, performing five specific tasks on mycotoxins. The rationale for each task was to provide harmonized and reliable informative databases to be used by the Commission for the management of
Mycotoxins
403
problems related to food. All the information provided in the most recent tasks is listed in the specific databases available at the following Internet sites: Aflatoxins-SCOOP Task 3.2.1; not available on Internet OTA-SCOOP Tasks 3.2.7; http://www.ec.europa.eu/food/fs/scoop/3.2.7_en.pdf Patulin-SCOOP Task 3.2.8; http://www.ec.europa.eu/food/fs/scoop/3.2.8_ en.pdf Fusarium toxins (trichothecenes, ZEA and FBs)-SCOOP Task 3.2.10; http:// www.ec.europa.eu/food/fs/scoop/task3210.pdf Furthermore, it should be kept in due consideration that reliable occurrence databases are one of the key elements for a correct exposure assessment and constitution of worldwide regulations.
6.1 Aflatoxins As mentioned, the first European complete database on occurrence of aflatoxins in raw commodities and processed food has been concluded in 1991 within SCOOP Task 3.2.1 and published in 1997 [103]. That database, reflecting the situation at that time, reported unreliable or even missing information on various features such as the type and target of adopted sampling procedures, the implementation of quality assurance systems in the reported surveys, the use of validated methods and the representativity of the survey for the member state; for these reasons that source of information is now highly outdated. Aflatoxins can occur in various raw commodities and processed food products. Among raw commodities aflatoxins are mainly present in cereals, spices, cottonseed, copra, dried fruits and nuts; among processed food, eggs, pasta, bread and milk and cheese (AFM1) resulted naturally contaminated with aflatoxins. A list of some of the most interesting worldwide surveys on aflatoxin occurrence in food products is reported in Table 5.
6.2 Ochratoxin A As for OTA, the most recent European database is provided by the report of the SCOOP Task 3.2.7 [232]. Basically, participants were asked to provide information on the exposure of the population to OTA in their country through the elaboration of the following categories of data: 1 2 3 4 5
Occurrence data in food and beverages, including those from different methodological approaches (i.e., total diet, duplicate test portion) Consumption data Best estimate of dietary intake Occurrence data in biological fluids and intake as derived from data on serum Data of intake for lactating babies through the ingestion of breast milk.
Nut products Spices Corn products Sultanas, dried figs Miscellaneous foods at retail Maize-based food products Cereal, spices
Aflatoxins Aflatoxins Aflatoxins Aflatoxins Aflatoxins
Oil and Olives
Dried Figs Maize Spices Miscellaneous food products Cereals, peanuts
UHT milk Pasteurized, and UHT Goat milk
Aflatoxins
Aflatoxins
Aflatoxins Aflatoxins Aflatoxins Aflatoxins
AFM1 AFM1
Aflatoxins
Olives Breakfast and infant cereals Olives
Aflatoxins Aflatoxins
Aflatoxins
Aflatoxins
Food matrix
0.006–0.04 (oil) 0.03–1.5 (olives) 0.1–35.1 0.05–158 0.14–15.7 (red pepper) 0.14–81.64 (pistachio nuts) 1.5–10 (rice) 1.5–10 0.01– 0.54 0.011–0.161
o0.35 (Cereal products) 0.02–9.10 (ginger) 0.15–1.13 0.002–0.996 (ricebased infant food) 0.5–5.0
9.9–710 0.2–14.6 1.0–23.3 0.3–1500.0 0.10–2.59 (peanut butter) 2–59 (popcorn)
Concentration levels (mg/kg or mg/l)
Occurrence of mycotoxins in food matrices
Mycotoxin
Table 5
ELISA IAC/HPLC-FL
ELISA
IAC-HPLC-FL IAC-HPLC-FL IAC/HPLC-FL IAC/HPLC-FL
Liq-liq partition/ HPLC-FL IAC-HPLC-FL
IAC-HPLC-FL IAC-HPLC-FL
IAC-HPLC-FL
TLC
HPLC-FL HPLC-FL HPLC-FL IAC-HPLC-FL IAC-TFA-HPLC-FL
Analytical technique
Turkey Brazil
Cote d’Ivoire
Turkey Italy Hungary Qatar
Italy
Morocco
Greece Canada
Morocco
Brazil
UK UK Brazil Brazil Japan
Country
2005 2004–2005
2002
2003–2004 1995–1999 2004 2002
2002–2003
Unknown
2004 2002–2005
2002
2002–2003
2003–2004 2003–2004 1999–2001 2002–2003 2004–2005
Year
[249] [250]
[248]
[244] [245] [246] [247]
[243]
[242]
[240] [241]
[239]
[238]
[233] [234] [235] [236] [237]
Reference
404 Carlo Brera et al.
Corn products Miscellaneous foods at retail Maize-based food products Cereal, Olives Olives
Oil and Olives
Dried Figs Infant foods Beer Breakfast cereals Cereal-based infant foods
OTA OTA
OTA
OTA OTA OTA OTA OTA
OTA OTA OTA
OTA
OTA
AFM1
AFM1 AFM1 AFM1 AFM1 AFM1 AFM1 AFM1
AFM1
Raw, Pasteurizedand UHT milk Pasteurized homogenized commercial milk Cheese Ewe’s milk Cow milk Cheese Yoghurt Parmesan cheese Cow, ewe and goat raw milk Cow, ewe and goat cheese Spices
AFM1
0.1–0.234 (oil) 0.1–8.0 (olives) 0.1–26.3 0.035–0.740 0.012–0.205 0.066–0.975 1.67 (max value)
0.01–7.22 (Corn) 0.41–1.86 0.2–1.02
6.4–64 (corn flour)
0.2–152.2 (ground chilli) o 10 0.1–12.5 (raisin)
0.05–0.250
0.19–2.05 0.002–0.108 0.03–3.13 0.11–0.52 0.010–0.098 0.001–0.406 0.005–0.170
0.010–0.289
o0.02–0.26
IAC-HPLC-FL HPLC HPLC HPLC HPLC
IAC-HPLC-FL IAC-HPLC-FL Liq-liq partition/ HPLC-FL IAC-HPLC-FL
TLC
TLC IAC/HPLC-FL
HPLC-FL
HPLC/FL
TLC HPLC/FL HPLC HPLC IAC/HPLC IAC/HPLC-FL HPLC/FL
IAC/LC-FL
IAC/TLC
Turkey Spain Spain Spain Spain
Italy
Morocco Greece Morocco
Brazil
Brazil Japan
UK
Italy
Iran Italy Libya Libya Portugal Italy Greece
Colombia
Brazil
Unknown
2003–2004
2002–2003
2002 2004 Unknown
2002–2003
1999–2001 2004–2005
2003–2004
1997–1999
2003–2004 2000 2002 2002 2001 1993–1999 1999–2000
2004–2005
2002–2003
[244] [260] [260] [260] [261]
[243]
[239] [240] [242]
[238]
[235] [237]
[234]
[259]
[253] [254] [255] [255] [256] [257] [258]
[252]
[251]
Mycotoxins
405
Red wine Red wine
Rose´ wine
White wine
Red wine Dessert wine Rose´ wine White wine Wine Spices Pork products Rice and rice products Miscellaneous food products
OTA OTA
OTA
OTA
OTA OTA OTA OTA OTA OTA OTA OTA OTA
0.01–4.00 0.01–1.64 0.01–1.04 0.01–0.21 o 0.01 10.6–66.2 (red pepper) 0.01–28.42 4.3–27.3 0.20–4.91
0.05–0.22
0.05–0.09
Grape based products, wine
OTA
OTA
0.06–0.74 (organic rice) 0.100–1.637 (pea berry) 0.021–0.100 (grape juices) 0.021–0.071 (red wine) 0.001–14 (dried black vine fruits) 0.012–0.126 0.05–0.75
Cereal-based baby foods Grape
OTA
Concentration levels (mg/kg or mg/l)
Food matrix
Mycotoxin
Table 5 (Continued )
IAC/HPLC-FL IAC/HPLC-FL IAC/HPLC-FL IAC/HPLC-FL IAC/HPLC-FL IAC/HPLC-FL IAC/HPLC-FL HPLC-FL IAC/HPLC-FL
LC-MS/MS (ESI-MRM)
LC-MS/MS (ESI-MRM)
IAC/HPLC-FL LC-MS/MS (ESI-MRM)
IAC/HPLC-FL
IAC/HPLC-FL
IAC/HPLC-FL
Analytical technique
Lebanon Different geographical regions Different geographical regions Different geographical regions Italy Italy Italy Italy Hungary Hungary Italy Spain Qatar
South America
Portugal
Italy
Country
1997–2002 1997–2002 1997–2002 1997–2002 1997–2002 2004 2001–2002 Unknown 2002
2001–2004
2001–2004
2004 2001–2004
2001–2003
Unknown
Year
[267] [267] [267] [267] [267] [246] [268] [269] [247]
[266]
[266]
[265] [266]
[264]
[263]
[262]
Reference
406 Carlo Brera et al.
Beer Cocoa products and chocolate Raisins and currants Dried vine fruits Dried vine fruits Cereals, peanuts
OTA OTA
Grains Olives
Breakfast cereals Maize-based food products Cereals Maize Miscellaneous food products Cereals, peanuts
Cereals and cereal products Maize Wheat and rye flour Soy
OTA Citrinin
Citrinin ZEA
ZEA
ZEA ZEA ZEA
ZEA
ZEA ZEA ZEA
OTA OTA OTA
Cereals and cereal products Maize Maize Breakfast cereals
OTA
OTA OTA OTA OTA
Coffee
OTA
0.43–39.12 1–2 214 (flour)
50–200 (rice) 50-200 4–5072 (rye)
10–17 (corn) 50– 2531 0.18–6.81 (cornflakes)
1.5–42 76.8–448 (popcorn)
0.9–2.54 0.26–613.7 0.2–8.8 (dry fruit and bran) 0.3–231 (feed-wheat) 0.5– 0.52
0.31–5.87 (roasted ground) 0.003–0.185 0.1–23.1 (roasted cocoa shell) 0.1–34.6 0.1–26.6 0.2–53.6 0.14–0.91 (rice) 0.20–0.64 0.1–1.7
IAC/HPLC-FL IAC/HPLC-FL IAC/HPLC-FL
IAC/HPLC-FL
ELISA
IAC/HPLC-FL IAC/HPLC-FL IAC/HPLC-FL
IAC/HPLC-UV Liq-liq partition/ HPLC-FL HPLC/FL TLC
IAC/HPLC-FL IAC/HPLC-FL HPLC/FL
IAC/HPLC-FL
IAC/HPLC-FL IAC/HPLC-FL IAC/HPLC-FL; ELISA
IAC/HPLC-FL IAC/HPLC-FL
IAC/HPLC-FL
Croatia Denmark Germany
Germany
Cote d’Ivoire
Morocco Italy Qatar
France Brazil
UK Morocco
Croatia Croatia France
Germany
Sweden Canada UK Cote d’Ivoire
Belgium Spain
Brazil
2002 1998–2001 Unknown
2004
2002
2002 1995–1999 2002
2003 2002–2003
1999–2000 Unknown
2002 1996–1997 2003
2004
1999–2002 1998–2000 Unknown 2002
1998–2001 Unknown
1998–1999
[277] [281] [282]
[276]
[278]
[239] [245] [247]
[279] [238]
[280] [242]
[277] [278] [279]
[276]
[273] [274] [275] [248]
[271] [272]
[270]
Mycotoxins
407
Grains Miscellaneous food products Corn products Miscellaneous foods at retail Cereals Maize Cereals, peanuts
Maize Maize Cereals and cereal products Maize and maizebased products Corn products Beer Cornflakes Maize
Maize Breakfast cereals Cereal based products Cereal based products
Corn and corn-based products Maize
ZEA ZEA
FBs FBs FBs
FBs FBs FBs FBs
FBs
DON
FBs FBs FBs FBs
FBs
FBs FBs FBs
FBs FBs
Food matrix
Mycotoxin
Table 5 (Continued )
117–9357
50–160 43–1329 20–464 142.2–1377 (FB1) 68.4–3084 (FB2) 12–11661 1–1110 10–2870 (wheat) 10–2870 (wholemeal flour) 25–1642
113–2.026
20–8600 10–354 (popcorn grain) 30–5960 (corn) 53–47078 300–1500 300–6000 1190–12.950 200–110.000 5–6617
1–1790 2–67 (Bran)
Concentration levels (mg/kg or mg/l)
GC-ECD
HPLC
IAC/HPLC-FL HPLC/FL LC-MS LC-MS
HPLC/FL HPLC/FL HPLC/FL IAC/HPLC-FL
IAC/HPLC-FL
IAC/HPLC-FL ELISA IAC/HPLC-FL
IAC-HPLC-FL IAC-HPLC-FL ELISA
HPLC/FL SAX/LC-MS
IAC/HPLC-FL IAC/HPLC-FL
Analytical technique
Italy
USA
Croatia France Italy Italy
Taiwan South Africa Belgium Croatia
Portugal
Iran Nigeria Germany
Morocco Italy Cote d’Ivoire
Brazil Japan
Germany Germany
Country
1995–1999
1998
1996–1997 2003 Unknown 2001–2002
Unknown 2001–2004 2003–2004 2002
2005
2000 2003 2004
2002 1995–1999 2002
1999–2001 2004–2005
2000–2001 2000–2001
Year
[243]
[287]
[278] [279] [291] [292]
[288] [289] [290] [279]
[287]
[285] [286] [276]
[239] [245] [248]
[235] [237]
[283] [284]
Reference
408 Carlo Brera et al.
Wheat and rye flour
Corn Corn-based products Soy Grains Miscellaneous food products Cereal products Cereals Cereals Apple juices Apple-based foods Miscellaneous applebased products Apple juice concentrates Apple-based drinks Apple products Fruit products
Apple products
Cereals and pulses
DON
DON DON DON DON DON
DON DON DON Patulin Patulin Patulin
Patulin
T-2
Patulin Patulin Patulin
Patulin
DON DON DON DON
DON
Miscellaneous food products Cereals and cereal products Beer Grains Cereal based products Cereal based products
DON
2.5–38.8 1.4–74.2 0.5–69.3 (organic apple juice) 5–45 (carbonated apple juice) 450–1900
7–376
5–111 20–1440 (barley) 100–8600 8.1–122.6 (cloudy) 0.05–1166 W25
4.0–56.7 20–600 (feed) 7–930 (organic mix) 7–930 (wholemeal flour 20–2591 (durum wheat) 102–542 o20 260 (crisp) 7–6682 319–389 (Bran)
50–445
86.43–182.94
HPLC-UV
HPLC-UV
HPLC-UV HPLC-UV HPLC-DAD
HPLC-UV
GC-MS GC-MS TLC, HPLC HPLC-UV SPE/HPLC-UV SPE/HPLC-DAD
UV GC-MS GC-MS GC-MS GC-MS
GC-ECD
ELISA IAC/HPLC-UV GC-ECD GC-ECD
IAC/HPLC-DAD
IAC/HPLC-UV
Turkey
South Africa
Belgium Italy Italy
Turkey
Finland Norway Russia Belgium Italy The Netherlands
Brazil Brazil Germany Germany Germany
Denmark
European countries UK Italy Italy
Germany
Qatar
Unknown
1996–1998
2001 Unknown 2003–2004
1996–1997
1998 1996–1998 1989–2001 Unknown Unknown Unknown
1994–1995 2001–2002 Unknown 2000–2001 2000–2001
1998–2001
2000–2002 1999–2000 Unknown 2001–2002
2004
2002
[307]
[306]
[303] [304] [305]
[302]
[296] [297] [298] [299] [300] [301]
[294] [295] [282] [282] [284]
[281]
[293] [280] [291] [292]
[276]
[247]
Mycotoxins
409
Corn Wheat and rye flour Corn-based products Grains Cereal grains Miscellaneous food products Oat Cereals Cereal grains Wheat and rye flour Miscellaneous food products Oat Cereals Cereal grains Wheat and rye flour Corn-based products Soy Grains Miscellaneous food products Oat Cereal products Cereals
T-2 T-2 T-2 T-2 T-2 T-2
HT-2 HT-2 HT-2
T-2 T-2 HT-2 HT-2 HT-2 HT-2 HT-2 HT-2
T-2 T-2 HT-2 HT-2 T-2
Food matrix
Mycotoxin
Table 5 (Continued )
10–47 10–20 20–880 (oat)
10–703 20–380 (oat) 10–71 10–70 (durum wheat) 50–555 (corn grits) 11 (flour) 3–1469 5–33 (Bran)
10–703 20–380 (oat) 10–71 10–70 (durum wheat) 6–12(Flakes)
50–104 10–193 (rye) 50–767 (corn grits) 4–1810 o12 6–12(Flakes)
Concentration levels (mg/kg or mg/l)
GC-MS GC-MS GC-MS
GC-MS GC-MS GC-MS GC-ECD GC-MS GC-MS GC-MS GC-MS
GC-MS GC-MS GC-MS GC-ECD GC-MS
ELISA GC-ECD GC-MS GC-MS GC-MS GC-MS
Analytical technique
Poland Finland Norway
Poland Norway Italy Denmark Brazil Germany Germany Germany
Poland Norway Italy Denmark Germany
Brazil Denmark Brazil Germany Italy Germany
Country
1997 1998 1996–1998
1997 1996–1998 Unknown 1998–2001 2001–2002 Unknown 2000–2001 2000–2001
1997 1996–1998 Unknown 1998–2001 2000–2001
1994–1995 1998–2001 2001–2002 2000–2001 Unknown 2000–2001
Year
[309] [296] [297]
[309] [297] [308] [281] [295] [282] [283] [284]
[309] [297] [308] [281] [284]
[294] [281] [295] [283] [308] [284]
Reference
410 Carlo Brera et al.
Mycotoxins
411
Additional information was also asked, among others and whenever possible, on the following issues: – – – – –
Sampling procedures employed Methods of analysis Quality assurance of analytical data Data on OTA occurrence in working places Regulations related to the toxin (maximum limits, sampling plans, others). The main conclusions from the report were the following:
Cereals represented the main source of intake in almost all the European countries. Rye, among cereal grains, generally seemed to be the most frequently and heavily contaminated. Coffee was the main contributor in Greece. Beer contributed to the total intake to a low extent. Wine represented the main source of intake in Italy and, as far as consumers only are concerned, in the Netherlands. Cocoa including cocoa powder contained within chocolate, provided a considerable contribution to the total intake in the United Kingdom; such contribution for 1.5–4.5 years population being similar to that attributed to cereals. Dried fruits contributed generally to a low extent to the total intake, except for the young population in the United Kingdom. Meat and spices contribute to a low extent to the total intake. Other potential contributors such as fruit juice seemed to be the most susceptible commodity. Breast milk represents a relevant source of exposure for lactating babies. As for OTA occurrence in grapes and wine two interesting reviews are available in literature [310,311]. Other surveys related to OTA occurrence in foods are reported in Table 5.
6.3 Fusarium toxins Similarly to OTA, SCOOP Task 3.2.10. report includes information on the intake of Fusarium toxins. The report is structured in a general section (part I), the three subtasks (trichothecenes, ZEA and FBs) and an annex part (II). Among trichothecenes both type A and B are reported for information on occurrence and in particular the following are included type A trichothecenes (T-2 and HT-2 Toxin, T-2 triol, neosolaniol, DAS, MAS) and type B trichothecenes: (3-acetylDON, 15-acetylDON, fusarenon X). An exhaustive summary of the outputs of the task has also been published where data on the occurrence of trichothecenes in food and dietary intake by the population of EU member states are reported only for DON, NIV, T-2 and HT-2 toxin. Results showed that corn had the highest level of trichothecene contamination, although DON was most often found in wheat. Intake data indicated that the main source of trichothecene consumption was through wheat
412
Carlo Brera et al.
and wheat products, such as bread and pasta; however, there was a lack of consumption data in some countries, particularly relating to children and infant foods. Although the average intake for DON was found to be below the TDI, high intake levels were found to exceed it, especially in young children. Both average and high NIV intake levels were found to be far below the TDI, while most of the average and high intake levels for T-2 and HT-2 toxins were above the temporary TDI [312]. A quite recent review on worldwide occurrence of FBs in foods and agricultural crops has been published in 2004. Aspects considered include disease cycles of Fusarium spp., which are responsible for the majority of FB synthesis; the chemical structure of FBs; diseases with which FBs are associated; occurrence of fumonisins B1 and B2 in foods and crops from Africa, America, Europe and Oceania and fumonisins B1–B3 in foods and crops from Asia; factors affecting the incidence of crop infection with Fusarium spp. (climatic conditions and latitude, genotype, spoilage, infection with other fungal diseases) and aspects of food preparation that affect FB occurrence (temperature, use of alkaline solutions and water) [313]. Similarly to FBs, an updated review of the most recent databases on ZEA occurrence in foods has been recently reported. Data from Europe, Africa, North and South America, Asia and Oceania are duly reported [314]. A review of the most recent noteworthy publications on Fusarium toxin occurrence in foods are reported in Table 5.
6.4 Patulin Correspondingly to the other mycotoxins, the European Commission launched in 2000 a SCOOP Task to collect information on the intake of patulin by the European population. The results of the study have been described in the report of SCOOP Task 3.2.8. Basically, the following conclusions are reported: Apple juice/apple nectar represented the main source of intake in Austria, Belgium, France, Germany, Portugal UK and Norway (apple nectar). Pear juice contributed to the total intake to a low extent in Germany and Portugal. Grape juice contributed to the total intake to a low extent. Fruit juice represented the main source of intake in Italy, Sweden and Spain. In Italy and Spain the main fruit juice was apple juice. Cider including drinks based on cider, provided a considerable contribution to the total intake of male adults consumers in France. Purees contributed to a low extent to the total intake, with the exception of female adults and adults in France where it was the main source for patulin intake. Baby foods had a higher level for intake for 1–3 years old children in Germany than in Italy, with the reservation that Italy only took into account pap (baby food with or without milk powder), but Germany pap and juice.
Mycotoxins
413
Tomatoes, canned and concentrated, contributed generally to a low extent to the total intake. Among the category ‘‘Others’’, jellies and tomato products might be susceptible commodities. Fresh fruit represented the main source of intake in Italy. Other recent surveys related to patulin occurrence are reported in Table 5.
6.5 Multi-Fusarium toxins With reference to the new EC Regulation 1881/2006 that will be amended by the introduction of new maximum tolerable limits for Fusarium toxins, all the information available regarding the co-occurrence of Fusarium toxins in cereals represents very useful information both for the potential synergistic effect of these mycotoxins and for the development of new analytical methods able to co-extract, co-elute and co-detect these toxins in a single sample. Information about the co-occurrence of Fusarium toxins is schematized in Table 5. In particular, co-occurrence of AFs and OTA [234–246]; AFs, OTA and ZEA [238]; AFs, OTA, ZEA and FBs [235]; AFs, OTA and FBs [237]; AFs, OTA, ZEA and DON [248]; AFs, ZEA, FBs and DON [245]; AFs, OTA and CIT [242]; OTA, ZEA and FBs [239,277]; OTA, ZEA, FBs and DON [276]; OTA and FBs [278]; OTA, FBs and CIT [279]; OTA and DON [280]; FBs and DON [291]; ZEA, DON, NIV, T-2 and HT-2 [281]; DON and T-2 [294]; DON, NIV, T-2 and HT-2 [295] are reported. Surveys including a miscellaneous of Fusarium toxins are also available in literature. A total of 45 samples of soy food including whole beans, roasted soy nuts, flour and flakes, textured soy protein, tofu, protein isolate including infant formulas and fermented products (soy sauce) were randomly collected in food and health food stores and analysed for Fusarium toxins. A spectrum of 13 trichothecenes of the A-type as well as of the B-type was determined by GC/MS. Detection limits ranged between 1 and 19 mg/kg. At least one of the toxins investigated was detected in 11 out of a total of 45 samples of soy food belonging to different commodities. Scirpentriol, 15-MAS, 4,15-DAS, T-2 tetraol, HT-2 toxin, DON, 15- and 3-acetylDON, were detected in at least one sample, T-2 triol, T-2, neosolaniol, NIV and FUS-X were not detected in any sample. Five out of eleven samples were positive for one toxin, one sample for two, three, six or seven toxins, two samples for five toxins, demonstrating the possibility of a contamination of soy food with a spectrum of Fusarium toxins. Scirpentriol, DON and ZEA were found up to 108, 260 and 214 mg/kg, the other toxins did not exceed 61 mg/kg [282]. Samples of cereals, cereal by-products, corn plants and corn silage as well as non-grain-based feedstuffs (n ¼ 220) were collected during 2000 and 2001 in Germany and analysed for 16 Fusarium toxins. The trichothecenes scirpentriol, MAS, DAS, T-2 tetraol, T-2 triol, HT-2 and T-2 toxin (HT-2, T-2), neosolaniol, DON, 3-acetylDON (3-ADON), 15-acetyldeoxynivealenol (15-ADON), NIV and fusarenon-X were determined by GC/MS. ZEA and a- and b-ZOL were analysed
414
Carlo Brera et al.
by HPLC with fluorescence and UV detection. Detection limits were in the range 1–19 mg/kg. Results showed that, of 125 samples of wheat, oats, corn, corn by-products, corn plants and corn silage, only 2 wheat samples did not contain any of the toxins analysed. Mean levels of positive samples were between 6 and 758 mg/kg. Of 95 samples of hay, lupins, peas, soy meal, rapeseed meal and other oilseed meals, 64 samples were toxin negative. DAS, T-2 triol, neosolaniol and FUS-X were not detected in any sample, while mean levels of positive samples were between 5 and 95 mg/kg [283]. Occurrence of mycotoxins was investigated in 219 food samples of plant origin collected in German retail outlets during 2000 and 2001. Samples, including cereal products, fruits, oilseeds and nuts, were tested for the presence of Fusarium toxins by GC-MS and HPLC with fluorescence and UV detection. Of 84 samples of cereal products, 60 were positive for Z1 of the following toxins: DON, 15-acetyl-DON, 3-acetyl-DON, NIV, T-2 toxin, HT-2 toxin, T-2 tetraol and ZEA, at incidences of 57, 13, 1, 10, 12, 37, 4 and 38%, respectively; however, none of the cereal samples contained detectable levels of scirpentriol, MAS, DAS, T-2 triol, fusarenon-X, a-ZOL or b-ZOL. Contents of DON were in the range 8–389 mg/kg, whereas concentration of other toxins were o100 mg/kg. The pseudocereals tested, amaranth, quinoa and buckwheat, were not contaminated by any of the toxins investigated. Of 85 fruit and vegetable samples, 10 were toxin positive; ZEA and the type A trichothecenes, MAS, scirpentriol, DAS and HT-2 toxin were detected in 7, 3, 2, 1 and 1 samples, respectively. Of 35 samples of oilseeds and nuts, 7 were toxin positive, with HT-2, T-2 and ZEA being detected in 4, 3 and 4 samples, respectively. None of the B-type trichothecenes were found in vegetables, fruit, oilseeds or nuts, and levels of the detected toxins were all o50 mg/kg [284]. A total of 449 grain samples (102 barley, 169 wheat and 178 oat), collected from different regions of Norway from 1996 to 1998, mainly from grain loads and silos, were analysed for type A and B trichothecenes by GC-MS. DON and HT-2 toxin were the trichothecenes most frequently detected, followed by T-2 toxin, NIV and scirpentriol. Scirpentriol was detected in only seven samples (W20 mg/kg). Oats were the most heavily contaminated grain species with an incidence and mean concentration of positive samples of 70% and 115 mg/kg for HT-2 toxin, 30% and 60 mg/kg for T-2 toxin, 57% and 104 mg/kg for DON and 10% and 56 mg/kg for NIV; corresponding values for barley were 22% and 73 mg/kg, 5% and 85 mg/kg, 17% and 155 mg/kg and 6% and 30 mg/kg, respectively, and for wheat they were 1.2% and 20 mg/kg, 0.6% and 20 mg/kg, 14% and 53 mg/kg and 0%, respectively. Norwegian oats were found to contain HT-2 and T-2 toxin in concentrations that might pose a threat to human health for high consumers of oats. The amount of DON detected was found to be significantly lower than in the crop from previous years [297].
6.6 Other mycotoxins Fusarium mycotoxins, beauvericin, enniatins (A, A1, B, B1) and moniliformin, were analysed in 38 Finnish grain samples (22 barley, 14 wheat, 1 oat, 1 rye)
Mycotoxins
415
harvested in 2001–2002. The contaminating Fusarium spp. were identified using primer-specific PCR as well as morphological studies. All studied mycotoxins were found in the samples. Enniatins B and B1 were detected in all samples, and enniatin A, enniatin A1, beauvericin and moniliformin were found in 74, 95, 95 and 74% of the samples, respectively. Higher mycotoxin concentrations were detected in cereal grains harvested in 2001 than in those harvested in 2002. Mycotoxin levels were highest in samples harvested late in the autumn after a long rainy period. F. avenaceum, which infected up to 29.5% of kernels, was the most abundant Fusarium sp. in both years. A correlation (po 0.001) was found between F. avenaceum contamination level and the concentration of moniliformin, enniatin B and enniatin B1. It is suggested that the prevalence of beauvericin, enniatins and moniliformin in Finnish grain may pose a health risk to Finnish people and farm animals [315]. Norwegian grain samples (73 oats, 75 barley, 83 wheat) from the 2000–2002 growing seasons were examined for contamination with moniliformin, and the association between this fungal metabolite and the number of kernels infected with common Fusarium spp. was investigated. Before quantification of moniliformin using ion pairing RP-HPLC with diode array UV light detection, all samples were extracted using acetonitrile/water (84/16) and disposable strong anion exchange columns were used for clean up. The detection limit was 40 mg/kg. Moniliformin was found in 25, 32 and 76% of the barley, oats and wheat samples, respectively. Maximum concentrations of moniliformin in barley, oats and wheat were 380, 210 and 950 mg/kg, respectively. Prevalence of the moniliformin-producing F. avenaceum/arthrosporioides was as high as 100%, and on average, the infection level was W53%. Moniliformin concentrations were significantly correlated with grain species, growing season and infection with F. avenaceum/arthrosporioides and F. culmorum. Results indicate that the prevalence of moniliformin in Norwegian grain is high, especially in wheat, although it is thought that field conditions do not favour high levels of moniliformin contamination of grain [316]. Food-grade corn and corn-based foods intended for human consumption were analysed for the incidence and levels of FB1, FB2, moniliformin, and Fusarium fungi. One hundred food-grade commercial corn samples were obtained from two corn-processing companies at five different locations in the United States; 71% of samples contained FB1 at concentration of 43–1,642 mg/kg. None of the samples contained FB2; 50% of samples contained moniliformin (26–774 mg/kg). All samples were infected by Fusarium fungi at an infection rate of 8–88%. Of 34 samples of corn-based foods, purchased from supermarkets in Arizona, California, Nebraska and Ohio, 65% of samples contained FB1 (28–2,679 mg/kg). FB2 was detected in 29% of samples (30–797 mg/kg); 68% of samples contained moniliformin (31–858 mg/kg) and 62% of samples contained viable Fusarium mold propagules ranging from 9.5 10(1) to 5.5 10(5)/g). Simultaneous occurrence of FB1 and moniliformin was observed in 34% of corn samples and 53% of cornbased foods. It is concluded that the co-occurrence of FBs and moniliformin in food-grade corn and corn-based foods, shown in this study, indicates a risk of simultaneous exposure of consumers to both toxins [317].
416
Carlo Brera et al.
The occurrence of fusaproliferin was investigated in 22 samples of pre-harvest maize ears Fusarium rot, collected in 1994 in Italy. The most frequently recovered Fusarium species were F. moniliforme and F. proliferatum. Chemical analysis by high-perfomance LC and GC/MS identified FP (up to 500 mg/kg) in nine samples mostly infected by F. proliferatum. FP was often found to be associated with FB1 (up to 300 mg/kg) and beauvericin (up to 520 mg/kg). The occurrence of FP as a natural maize contaminant and its co-occurrence with FB1 and bauvericin is reported here for the first time [318]. Numerous samples (W2,000), representing 73 different kinds of Turkish foods and agricultural products, were analysed for total fungal flora. Samples were collected from 9 different agricultural geographical regions and from 34 different cities in Turkey. A total of 1977 isolates, representing 1,317 species and 40 different genera, were scanned for mycotoxin-producing activities, using 31 different mycotoxin standards. Qualitative screening, using TLC, specific solvent systems and standard methods, indicated 32.5% of the cultures were able to produce mycotoxin, with 19 different types of mycotoxins identified. The dominant mycotoxins, respectively, were roquefortin C and sterigmatocystin. Dominant fungal isolates varied by region. The extent of contamination was also determined and a mycotoxin risk profile was constructed for each agricultural region of Turkey [319].
7. DECONTAMINATION PROCEDURES An exhaustive review of the most used decontamination procedures is available on the Internet site of the European Mycotoxin Awareness Network (EMAN), http://www.mycotoxins.org. Typical biological detoxification can be defined as the enzymatic degradation or biotransformation of mycotoxins that can be obtained by either the whole cell or an enzyme system. Other approaches that can be regarded as biological include the use of biocompetitive agents and genetically engineered plants for reducing mycotoxin contamination. Lactic acid bacteria and yeasts expressing mycotoxin-degrading enzymes, may offer a natural way of providing these activities in fermentation processes. Biological degradation of aflatoxins has been reported for a number of microorganisms including lactic acid bacteria. Black yeast fungus and a bacterium strain have been found to hydrolyze FB1 to aminopentol and tricarballylic acid. The same microorganisms seem to be able to further detoxify aminopentol with release of CO2. Microbial strains (yeasts, fungi or bacteria) have been proposed for detoxification of DON, T-2 toxin, ZEA and other trichothecenes, but their practical use has not been shown. Among physical methods, mechanical separation, density segregation, colour sorting, removal of the fines or screenings from the bulk shipments of grains and nuts significantly reduce the mycotoxin content of grains. Simple washing procedures, using water or sodium carbonate solution, result in some reduction in concentrations of DON, ZEA and FBs in grains or corn cultures. Other
Mycotoxins
417
methodologies are irradiation either with gamma-rays, microwaves and UV light, and solvent extraction. Another approach to detoxification of mycotoxins involves the use of adsorbent materials with the capacity to tightly bind and immobilize mycotoxins in the gastrointestinal tract of animals, thus reducing the bioavailability of the toxin. Alluminosilicates (HSCAS) in aqueous suspensions have been reported to tightly bind aflatoxins in aqueous suspensions; markedly diminish aflatoxin uptake by the blood and distribution to target organs; prevent aflatoxicoses in farm animals; decrease the level of AFM1 in milk from lactating dairy cattle. Divinylbenzene-styrene polymers (anion-exchange resins) bentonite and activated carbon exhibited beneficial effects when added to T-2 contaminated diet fed to rats. The addition of the resin to ZEA-contaminated diet resulted in a major decrease in urinary excretion of conjugated ZEA and its metabolites by rats. Cholestyramine has been reported to reduce the bioavailability of FBs, ZEA and OTA in mice and/or rats. As for chemical methods, it should be noted that chemical treatment is not allowed within the EC for commodities destined for human food. The chemicals used fall into the categories of acids, bases (e.g., ammonia, sodium hydroxide), oxidizing reagents (e.g., hydrogen peroxide, ozone), reducing agents (e.g., bisulfite, sugars), chlorinating agents (e.g., chlorine), salts and miscellaneous reagents such as formaldehyde. Often chemical treatments have been used in combination with physical treatments to increase the efficacy of decontamination. A wide variety of chemicals, including calcium hydroxide monomethylamine, sodium bisulfite, moist and dry ozone, chlorine gas, hydrogen peroxide, ascorbic acid, hydrochloric acid, sulfur dioxide, formaldehyde, ammonia and ammonium hydroxide, have been found to be effective (at different extents) against several mycotoxins, including DON, ZEA, T-2 toxin, aflatoxins and FBs. Ammoniation is the method that has received the most attention for detoxification of aflatoxincontaminated feeds and has been successfully used in the United States, France, the UK and Africa. Ammoniation did not show the same efficacy against FBs since no reduction in toxicity was found when ammoniated FB1 was fed to rats despite reduction in FB1 content. The reaction with sodium bisulfite is one of the most effective against DON in corn, although the treatment is not suitable for direct application to human foods. In addition to the above-mentioned preventive actions, a further key contributing component of an integrated approach to food safety is represented from the adoption of HACCP principles. This approach is intensely used to control or reduce mycotoxin levels before industrial processing revealing, so far, as a useful tool to keep under control mycotoxin presence within acceptable ‘‘safe’’ levels and to prevent the persistence of mycotoxins in finished products. The most effective mycotoxin control measures are to dry the commodity such that the water activity (Aw) is too low to support mould growth and/or prevent mycotoxin production. To prevent the growth of most moulds the Aw needs to be around 0.70, which translates to a moisture content of approximately 14% for maize and 7.0% for groundnuts at 201C.
418
Carlo Brera et al.
Another important key critical control point for avoiding the processing of materials at unacceptable mycotoxin levels is the acceptance of the raw material, by the implementation of periodical testing performance including the adoption of reliable sampling procedures and validated methods of analysis.
8. FUTURE NEEDS Despite the huge amount of data available on the major mycotoxins, most of them mainly related to toxicological effect, occurrence and methods of analysis, the global view on the real impact of those toxic to human beings is still not fully clear. Many gaps in the available status of art and many factors contribute to the above uncertainty. A preliminary consideration is that the scenario of mycotoxin impact on human beings is unfortunately very differentiated among the different areas of the world, thus implicating the need of different approaches depending on the dimension of the problem. Toxicology on experimental animals is rather well developed; however, the transposition to human biological systems, even taking into account the safety factors, can represent a source of ambiguity as well as the lack of toxicological studies on the combined effects of the very likely coexistent toxins. In addition, a substantial lack of toxicological information still exists for the effects on immunological systems. This effect is well known as far as farm animals are concerned: the hypothesis of similar effects on human beings could incredibly increase the scenario of diseases attributable to mycotoxins. Epidemiological studies could represent a valuable approach parallel and complementary to toxicological studies, but in this respect there is a substantial lack of investigation, some studies, many of them inconclusive, being available in the more affected areas where the acute effects are prevalent on chronic effects. One of the main outputs of the toxicological studies is represented by the possibility to compare the derived TDIs with the actual intake of the population whatever the methodology for this latter evaluation could be (point estimation or probabilistic approach). Actually, at least at European level, in the past decades valuable evaluations of dietary intake have been performed for the main mycotoxins with the data at that time available. However, the reliability of those data could currently be questionable under several respects: (i) the adopted consumption database were not fully suitable to the mycotoxin problem; (ii) the occurrence data could suffer from poor sampling procedures that could generally lead to the underestimation of the data; (iii) at the time of the evaluations several food products had not yet been recognised as susceptible to contamination, their contribution therefore missing in the total dietary intake. An additional gap both in the TDIs and in the actual total intake of the population is the consideration of vulnerable groups of population such as youngest and eldest people as well as people affected by peculiar diseases such as coeliac, renal, hepatic and immunological disorders.
Mycotoxins
419
The above source of uncertainties suggests the need for new data for the total dietary intakes based on novel sets of data as obtained from fit for purpose plans. This need is consistent with the new vision of the risk analysis that recommends an iterative process in the acquisition of risk-related data. A corollary of the above future needs is related to the methods of analysis: the sector of reliable rapid methods should be further developed since they could certainly simplify the attainment of occurrence data as well as the implementation of prevention actions.
ACKNOWLEDGEMENT The authors wish to thank Mrs. Viviana Renzi for her valuable technical assistance in the editing of the text.
REFERENCES 1 M.K. Matossian, Poisons of the Past: Molds, Epidemics, and History, Yale University Press, New Haven, CT, 1989. 2 S.J. van Rensburg and B. Altenkirk, In: I.F.H. Purchase (Ed.), Mycotoxins, Claviceps purpurea: Ergotism, Elsevier, New York, 1974, pp. 69–96. 3 Council for Agricultural Science and Technology (CAST), Mycotoxins: Risks in Plant, Animal, and Human Systems, Report, January 2003, R139. 4 Y. Ito, S.W. Peterson, D.T. Wicklow and T. Goto, Mycol. Res., 105 (2001) 233. 5 C.P.B. Kurtzman, B.W. Horn and C.W. Hesseltine, Antonie van Leeuwenhoek J. Microbiol., 53 (1987) 147. 6 U.L. Diener, J. Stored Prod. Res., 5 (1969) 251. 7 A. Ciegler, D.I. Fennell, G.A. Sansing, R.W. Detroy and G.A. Bennett, Appl. Microbiol., 26 (1973) 271. 8 J.F. Grove, Nat. Prod. Rep., 5 (1988) 187. 9 J.E. Smith, C.W. Lewis, J.G. Anderson and G.L Solomons, Mycotoxins in human nutrition and health, Directorate-General XII, Science, Research and Development, European Commission, EUR 16048 EN, 1994. 10 U. Thrane, A. Adlerb, P.E. Clasenc, F. Galvanod, W. Langseth, H. Lew, A. Logrieco, K.F. Nielsen and A. Ritieni, Int. J. Food Microbiol., 95 (2004) 257. 11 U. Thrane, In: B.A. Summerell, J.F. Leslie, D. Backhouse, W.L. Bryden, L.W. Burgess and P.E. Nelson (Eds.), Fusarium, Developments in the Taxonomy of Fusarium Species Based on Secondary Metabolites, Memorial Symposium, APS Press, St. Paul, MN, 2001. 12 P.E. Nelson, M.C. Dignani and E.J. Anaissie, Clin. Microbiol. Rev. 7 (1994) 479. 13 International Programme On Chemical Safety (IPCS), Environmental Health Criteria 105-Mycotoxins, Selected: Ochratoxins, Trichothecenes, Ergot, 1990. Available at http://www.inchem.org/ documents/ehc/ehc/ehc105.htm 14 M. Torp and W. Langseth, Mycopathologia, 147 (1999) 89. 15 M.A. Diekman and M.L. Green, J. Anim. Sci., 70 (1992) 1615. 16 S.C. Bezuidenhout, W.C.A. Gelderblom, C.P. Gorst-Allman, R.M. Horak, W.F.O. Marasas, G. Spiteller and R. Vleggaar, J. Chem. Soc. Chem. Commun. (1988) 743. 17 S.C.E. Friend, L.A. Babiuk and H.B. Schiefer, Can. J. Comp. Med., 47 (1983) 291. 18 W.C.A. Gelderblom, K. Jaskiewicz, W.F.O. Marasas, P.G. Thiel, R.M. Horak, R. Vleggaar and N.P.J. Kriek, Appl. Environ. Microbiol., 54 (1988) 1806. 19 M. Bolger, R.D. Coker, M. Dinovi, D. Gaylor, M.O. Gelderblom, N. Paster, R.T. Riley, G. Shephard and J.A. Speijers, Safety Evaluation of Certain Mycotoxins in Food: Fumonisins, Food and
420
20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
48
49 50 51 52 53 54 55
Carlo Brera et al.
Agriculture Organization of the United Nations, Paper 74, World Health Organization Food Additives, Series 47, 2001, pp. 103–279. International Programme on Chemical Safety (IPCS), Environmental Health Criteria 219-Fumonisin B1, 2000. Available at http://www.inchem.org/documents/ehc/ehc/ehc219.htm J.P. Rheeder, W.F.O. Marasas and H.F. Vismer, Appl. Environ. Microbiol., 68(5) (2002) 2101. E.E. Stinson, S.F. Osman, C.N. Huhtanen and D.D. Bills, Appl. Environ. Microbiol., 36 (1978) 620. T. Long, Fate of patulin in fermentation products, Ministry of Agriculture, Fisheries and Food (UK), Research and Development Report No. 599, 1997. IARC, Monographs on the Evaluation of the Carcinogenic Risk of Chemicals to Humans, Vol. 40, IARC, Lyon, 1986. M.A. Harrison, J. Food Safety, 9 (1989) 147. E.R. McKinley and W.W. Carlton, In: R.P. Sharma and D.K. Salunkhe (Eds.), Mycotoxins and Phytoalexins, Patulin, CRC Press, Atlanta, 1991. Z. Reha´cek and P. Sajdl, Ergot Alkaloids, Elsevier Science, New York, 1990. A.C. Hetherington and H. Raistrick, Thom. Phil. Trans. Roy. Soc. Ser. B, 220 (1931) 269. T. Vrabcheva, E. Usleber, R. Dietrich and E. Ma¨rtlbauer, J. Agric. Food Chem., 48 (2000) 2483. R.R. Marquardt, Anim. Feed Sci. Technol., 58 (1996) 77. D.E. Goeger, R.T. Riley, J.W. Dorner and R. Cole, Biochem. Pharmacol., 37 (1988) 978. R.J. Cole, J.W. Kirksey, H.G. Cutler, B.L. Doubnik and J.C. Peckham, Science, 179 (1973) 1324. R. Weindling and O.H. Emerson, Phytopathology, 26 (1936) 1068. Y. Ueno and I. Ueno, Jpn. J. Exp. Med., 42 (1972) 91. D.W. Nagel, P.S. Steyn and N.P. Ferreira, Phytochemistry, 11 (1972) 3215. N. Sakabe, T. Goto and Y. Hirata, Tetrahedron Lett., 27(5) (1964) 1825. D.T. Wicklow, R.D. Stubblefield, B.W. Horn and O.L. Shotwell, Appl. Environ. Microbiol. Chem. Ind., 25 (1988) 972. Y. Ueno, In: I.F.H. Purchase (Ed.), Mycotoxins: Citreoviridin from Penicillium citreoviride Biourge, Elsevier, New York, 1974. L.J. Mulheirn, R.B. Beechey, D.P. Leworthy and M.D. Osselton, J. Chem. Soc. Chem. Commun., 24 (1974) 874. P.S. Steyn and R. Vleggaar, Prog. Chem. Org. Nat. Prod., 48 (1985) 1. P.G. Mantle and R.H.C. Penny, Vet. Annu., 21 (1981) 51. P.J. Norris, C.C.T. Smith, J. De Belleroche, H.F. Bradford, P.G. Mantle, A.J. Thomas and R.H.C. Penny, J. Neurochem., 34 (1980) 33. P.G. Mantle, P.H. Mortimer and E.P. White, Res. Vet. Sci., 24 (1977) 49. P. Breton, J.C. Bizot, J. Buee and I. Delamanche, Toxicon, 36 (1998) 645. D. Abramson, In: J.P. Felix (Ed.), Handbook of Plant and Fungal Toxicants, Toxicants of the Genus Penicillium, CRC Press, Boca Raton, FL, 1997. V.R. Beasley, A Systems Affected Approach to Veterinary Toxicology, Tremorgenic Mycotoxins and Various Staggers Syndromes, University of Illinois, Urbana, IL, 1997. J.I. Pitt, Diseases caused by viruses, parasites, and fungi, Penicillium. In: Y.H. Hui, S.A. Sattar, K.D. Murrel, W.K. Nip and P.S. Stanfield (Eds.), Foodborne Disease Handbook, Vol. 2, Marcel Dekker, New York, 1994. R.J. Cole, In: J.V. Rodricks, C.W. Hesseltine and M.A. Mehlman (Eds.), Mycotoxins in Human and Animal Health, Conference Proceedings, Tremorgenic Mycotoxins, Pathotox Publishers, Park Forest, South-IL, 1977. A.D. Hocking, K. Holds and N.F. Tobin, Aust. Vet. J., 65 (1998) 82. R. Puls and E. Ladyman, Can. Vet. J., 29 (1988) 569. L.H. Arp and J.L. Richard, J. Am. Vet. Med. Assoc., 175(6) (1979) 565. R.T. Gallagher, A.D. Hawkes, B.S. Steyn and R. Vleggaar, J. Chem. Soc. Chem. Commun., 9 (1984) 614. C.M. Weedon and P. Mantle, Phytochemistry, 26 (1987) 969. H.G. Knaus, O.B. McNaus, S.H. Lee, W.A. Schmalhofer, M. Garcia Calvo, L.M. Helms, M. Sanchez, K. Giangiacomo, J.P. Reuben and A.B. Smith, Biochemistry, 33 (1994) 5819. S.C. Munday-Finch, A.L. Wilkins, C.O. Miles and A.D. Hawkes, J. Agric. Food Chem., 43 (1995) 1283.
Mycotoxins
56 57 58 59 60 61 62 63 64 65 66
67
68
69 70 71 72 73
74 75 76 77 78
79 80 81
82 83
84
421
J. Penn and P.G. Mantle, Phytochemistry, 35 (1994) 921. A.A. El-Banna, J.I. Pitt and L. Leistner, Syst. Appl. Microbiol., 10 (1997) 42. R.E. Wagener, N.D. Davis and U.L. Diener, Appl. Environ. Microbiol., 39 (1980) 882. X. Liu, X. Luo and W. Hu, Biomed. Environ. Sci., 5 (1992) 161. C.J. Coles, D.E. Edmondson and T.P. Singer, J. Biol.Chem., 254 (1979) 5161. A. Logrieco, A. Moretti, F. Fornelli, V. Fogliano, A. Ritieni, M.F. Caiaffa, G. Randazzo, A. Bottalico and L. Macchia, Appl. Environ. Microbiol., 62 (1996) 3378. C. Manetti, V. Fogliano, A. Ritieni, A. Santini, G. Randazzo, A. Logrieco, L. Mannina and A.L. Segre, Struct. Chem., 6 (1995) 183. A. Ritieni, V. Fogliano, G. Randazzo, A. Scarallo, A. Logrieco, A. Moretti, L. Mannina and A. Bottalico, Nat. Toxins, 3 (1995) 17. A. Ritieni, A. Moretti, A. Logrieco, A. Bottalico, G. Randazzo, S.M. Monti, R. Ferracane and V. Fogliano, J. Agric. Food Chem., 45 (1997) 4011. G.P. Munkvold, H.M. Stahr, A. Logrieco, A. Moretti and A. Ritieni, Appl. Environ. Microbiol., 64 (1998) 3923. European Commission, Report of the EC Scientific Steering Committee’s Working Group on Harmonization of Risk Assessment Procedures in the Scientific Committees advising the European Commission in the area of human and environmental health, 26–27 October, 2000. Part 2, Appendx 1 — Glossary of terms. Available at http://europa.eu.int/comm/food/fs/sc/ssc/out82_en.html T. Kuiper-Goodman, Risk assessment and risk management of mycotoxins in food. In: N. Magan and M. Olsen (Eds.), Mycotoxins in Food Detection and Control, Woodhead Publishing, Cambridge, England, 2004, pp. 3–27. E. Azziz-Baumgartner, K. Lindblade, K. Gieseker, H. Schurz Rogers, S. Kieszak, H. Njapau, R. Schleicher, L.F. McCoy, A. Misore, K. DeCock, C. Rubin, L. Slutsker and the Aflatoxin Investigative Group, Case-control study of an acute aflatoxicosis outbreak, Kenya, 2004, Environ. Health Perspect., 113(12) (2005) 1779. K.A. Krishnamachari, R.V. Bhat, V. Nagarajan and T.B. Tilak, Indian J. Med. Res., 63 (1975) 1036. R.C. Patten, Am. J. Trop. Med. Hyg., 30 (1981) 422. M.S. Lye, A.A. Ghazali, J. Mohan, N. Alwin and R.C. Nair, Am. J. Trop. Med. Hyg., 53 (1995) 68. S.Y. Chen, C.J. Chen, W.Y. Tsai, H. Ashan, T.Y. Liu and J.T. Lin, Nutr. Cancer, 38 (2000) 179. J.M. Beaedall and J.D. Miller, Diseases in human with mycotoxins as possible causes. In: J.D. Miller and H.L. Trenholm (Eds.), Mycotoxins in Grain. Compounds Other Than Aflatoxins, Eagan Press, Pt. Paul, MN, 1994, pp. 487–539. X. Luo, Food poisoning associated with Fusarium toxins, Proceedings of the 7th International Symposium on Mycotoxins and Phycotoxins, Tokyo, 16–19 August 1988. R.V. Bhat, S.R. Beedu, Y. Ramakrishna and K.L. Munshi, Lancet, 7 (1989) 35. A.E. Desjardins, Trichothecenes: From yellow rain to green wheat, ASM News, 69(4) (2003) 182. Commission Regulation (EC) 1881/2006 of 19 December 2006 setting maximum levels for certain contaminants in foodstuffs. European Food Safety Assessment (EFSA)., Opinion of the scientific committee on a request from EFSA related to a harmonized approach for risk assessment of substances which are both genotoxic and carcinogenic, EFSA J., 282 (2005) 1–30. IARC, Monographs on the Evaluation of the Carcinogenic Risk of Chemicals to Humans, Vol. 56, IARC, Lyon, 1993. IARC, Monographs on the Evaluation of the Carcinogenic Risk of Chemicals to Humans, Vol. 82, IARC, Lyon, 2002. European Food Safety Assessment (EFSA), Opinion of the scientific panel on contaminants in the food chain on a request from the commission related to OTA in food Question N EFSA-Q2005-154, adopted on 4 April 2006. G.J.A. Speijers and M.H.M. Speijers, Toxicol. Lett., 153 (2004) 91. J.L. Richard, In: H. van Egmond, C. Brera and J. Gilbert (Eds.), Mycotoxins, toxicity and metabolism in animals: A systems approach overview: Mycotoxins and Phytotoxins—Developments in Chemistry, Toxicology and Food Safety, Alaken, Inc., Fort Collins, Colorado, 1998. F. Fung and R.F. Clark, J. Toxicol., 42 (2004) 217.
422
Carlo Brera et al.
85 JECFA, Evaluation of certain food additives and contaminants (Thirty-first report of the Joint FAO/WHO Expert Committee on Food Additives), WHO Technical Report Series 759, and corrigendum, 1987. 86 JECFA, Evaluation of certain food additives and contaminants (Forty-ninth report of the Joint FAO/WHO Expert Committee on Food Additives), WHO Technical Report Series 884, 1999. 87 JECFA, Evaluation of certain food additives and contaminants (Forty-sixth report of the Joint FAO/WHO Expert Committee on Food Additives), WHO Technical Report Series, 868, 1997. 88 World Health Organization (WHO), Evaluation of certain mycotoxins in food, Fifty-sixth report of the joint FAO/WHO Expert Committee on Food Additives, WHO Technical Report Series 906, Geneva, 2002. 89 G. Sabbioni, P. Skipper, G. Buchi and S.R. Tannenbaum, Carcinogenesis, 8 (1987) 819. 90 J.D. Groopman, L.G. Cain and T.W. Kensler, CRC Crit. Rev. Toxicol., 19 (1988) 113. 91 K. Painter, USA Today , Washington, DC (1997) 92 C.A. Saenz de Rodriguez, A.M. Bongiovanni and L. Conde de Borrego, J. Pediatr., 107 (1985) 393. 93 W.F.O. Marasas, Environ. Health Perspect., 109 (2001) 239. 94 L. Jackson and J. Jablonski, Fumonisins. In: N. Magan and M. Olsen (Eds.), Mycotoxins in Food: Detection and Control, Woodhead Publishing, Cambridge, England, 2004 95 N.A. Makaula, W.F. Marasas, F.S. Venter, C.J. Badenhorst, D. Bradshaw and S. Swanevelder, Afr. J. Health. Sci., 3 (1996) 11. 96 H. Zhang, H. Nagashima and T. Goto, Mycotoxins, 44 (1997) 29. 97 Y. Ueno, K. Iijima, S.D. Wang, Y. Sugiura, M. Sekijima, T. Tanaka, C. Chen and S.Z. Yu, Food Chem. Toxicol., 35 (1997) 1143. 98 Food and Agricultural Organization, World Health Organization, Evaluation of Certain Food Additives and Contaminants, 44th report of the joint FAO/WHO Expert Committee on Food Additives, Tech. Report Series Volume 859, WHO, Geneva, 1995. 99 R.J. Cole and R.H. Cox, In: R.J. Cole and R.H. Cox (Eds.), Tremorgen Group: Handbook of Toxic Fungal Metabolites, Academic Press, New York, 1981, pp. 355–509. 100 International Programme on Chemical Safety (IPCS), Selected Mycotoxins: Ochratoxins, Trichothecenes, Ergot, Environmental Health Criteria, Vol. 105 (1990). 101 International Life Science Institute (ILSI) Europe, Report Series; Trichothecenes with a special focus on DON, Summary Report of a Workshop, September 2003. 102 European Food Safety Assessment (EFSA), Opinion of the Scientific Committee related to Uncertainties in Dietary Exposure Assessment. Available at http://www.efsa.europa.eu/it/ science/sc_commitee/sc_opinions/uncertainty_exp.html 103 European Commission, Reports on tasks for scientific cooperation. Report of experts participating in Task 3.2.1. Risk assessment of aflatoxins. Report EUR 17526EN. Directorate-General for Industry, Luxembourg, Office for Official Publications of the European Communities, 1997. 104 European Commission, SCOOP-task 3.2.2., Assessment of dietary intake of OTA by the population in EU member states, Report EUR 17523 EN (revised version), 1997. 105 European Commission, SCOOP-task 3.2.7., Assessment of dietary intake of OTA by the population in EU member states, 2002. Available at http://europa.eu.int/comm/food/fs/scoop/3.2.7_en.pdf 106 European Commission, SCOOP-task 3.2.8., Assessment of dietary intake of Patulin by the population of EU member states, 2002, Available at http://europa.eu.int/comm/food/fs/scoop/3.2.8_en.pdf 107 European Commission, SCOOP-task 3.2.10., Collection of occurrence data of Fusarium toxins in food and assessment of dietary intake by the population of EU member States. (2003). Available at http:// europa.eu.int/comm/food/fs/scoop/task3210.pdf 108 Institute National de la Recherche´ Agronomique (INRA), The 1st French Total Diet Study, 2004. 109 C. Brera, S. Angelini, F. Debegnach, B. De Santis, A. Turrini and M. Miraglia, Valutazione analitica dell’esposizione del consumatore alla fumonisina B1, Rapporti Istisan 05/42 44-52, Proceedings of the First Italian National Congress on Mycotoxins, M. Miraglia and C. Brera (Eds.), 2005 (in Italian). 110 Food and Agriculture Organization of the United Nations (FAO), Worldwide regulation for mycotoxins in food and feed in 2003, Food and Nutrition Paper 81, Rome, 2004. 111 T.B. Whitaker and E.H. Wiser, J. Am. Oil Chem. Soc., 46 (1969) 377. 112 A.S. Johansson, T.B. Whitaker, W.M. Jr Hagler, F.G. Giesbrecht and J.H. Young, J. AOAC Int., 83 (2000) 1270.
Mycotoxins
423
113 M. Miraglia, B. De Santis, V. Minardi, F. Debegnach and C. Brera, Food Addit. Contam., 1 (2005) 31. 114 Food and Agriculture Organization (FAO), Sampling plans for aflatoxin analysis in peanuts and corn. Food and Nutrition Paper 55, 1993. 115 M.C. Spanijer, J.M. Scholten, S. Kastrup, U. Jorissen, T.F. Schatzk and N. Toyofuku, Food Addit. Contam., 23 (2006) 73. 116 Commission Regulation (EC) N 401/2006 of 23 February 2006 laying down the methods of sampling and analysis for the official control of the levels of mycotoxins in foodstuffs. 117 L. Pallaroni and C. von Holst, Anal. Bioanal. Chem., 376 (2003) 1618. 118 L. Pallaroni, C. von Holst, C.S. Eskilsson and E. Bjorklund, Anal. Bioanal. Chem., 374 (2002) 161. 119 D. Royer, H.U. Humpf and P.A. Guy, Food Addit. Contam., 21 (2004) 678. 120 R. Krska, J. Chromatogr. A, 815 (1998) 49. 121 O.G. Roch, G. Blunden, R.D. Coker and S. Nawaz, Chromatographia, 33 (1992) 208. 122 S.M. Poling and R.D. Plattner, J. Agric. Food Chem., 47 (1999) 2344. 123 C.G. Zambonin, L. Monaci and A. Aresta, Food Chem., 75 (2001) 249. 124 V.M.T. Lattanzio, M. Solfrizzo and A. Visconti, Food Addit. Contam. Vol. 25(3) (2008) 320. 125 N. Zabe, E. Waldleigh and B.A. Cohen, In: H. Njapau, S. Trujillo, H.P. van Egmond and D.L. Park (Eds.), Mycotoxins and Phycotoxins: Advances in Determination, Toxicology and Exposure Management: Simultaneous Determination of Aflatoxin, OTA and Zearalenone by a New Immunoaffinity Column, Wageningen Academic Publishers, The Netherlands, 2006. 126 J. Olsen, P. Martin and I.D. Wilson, Anal. Commun., 35 (1998) 13H. 127 B. Sellergen, Trends Anal. Chem., 18 (1999) 164. 128 D. Stevenson, Trends Anal. Chem., 18 (1999) 154. 129 C. Baggiani, G. Giraudi and A. Vanni, Bioseparation, 10 (2002) 389. 130 N.M. Maier, G. Buttinger, S. Welhartizki, E. Gavioli and W. Lindner, J. Chromatogr. B, 804 (2004) 103. 131 J. Jodbauer, N.M. Maier and W. Lindner, J. Chromatogr. A, 945 (2002) 45. 132 R. Weiss, M. Freudenschuss, R. Krska and B. Mizaikoff, Food Addit. Contam., 20 (2003) 235. 133 AOAC. In: C.P. Arlington (Ed.), International, Official Methods of Analysis, Vol. II, 17th ed., 2000. 134 R.C. Garner, M.M. Whattman, P.J.L. Taylor and M.W. Stow, J. Chromatogr., 648 (1993) 485. 135 J. Stroka, E. Anklam, U. Joerissen and J. Gilbert, J.AOAC Int., 84 (2001) 1116. 136 L.G.M. Tuinstra and W. Haasnoot, J. Chromatogr., 282 (1983) 457. 137 W. Kok, U.A. Brinkam and R.W. Frei, Anal. Chim. Acta, 162 (1986) 19. 138 W. Kok, C.H. van Neer, V.A. Traag and L.G.M. Tunistra, J. Chromatogr., 367 (1986) 231. 139 A. Papadopoulou-Bouraoui, J. Stroka and E. Anklam, J. AOAC Int., 85 (2002) 411. 140 R.M. Beebe, J. AOAC Int., 61 (1978) 1347. 141 S. Dragacci, F. Grosso, N. Pfauwathel-Marchond, J.M. Fremy, A. Venant and B. Lombard, Food Addit. Contam., 18 (2001) 405. 142 S. Dragacci, E. Gleizes, J.M. Fremy and A.A.G. Candlish, Food Addit. Contam., 12 (1995) 59. 143 A.C. Entwisle, A.C. Wiliams, P.J. Mann, J. Russel, P.T. Slack and J. Gilbert, J. AOAC Int., 84 (2001) 444. 144 A. Cantafora, M. Grossi, M. Miraglia and L. Benelli, Riv. Soc. Ital. Sci. Alim., 12 (1983) 103. 145 S. Uchiyama, Y. Saito and M. Vchiyama, J. Food Hygenic Soc. Jpn., 26 (1985) 651. 146 C. Micco, M.A. Ambruzzi, M. Miraglia, C. Brera, L. Benelli and S. Corneli, Food Addit. Contam., 12 (1995) 351. 147 D. Abramson, J. Chromatogr., 391 (1987) 315. 148 K.H. Ominski, A.A. Frohlich, R.R. Marqurdt, G.H. Crow and D. Abramson, Food Addit. Contam., 13 (1996) 185. 149 M.W. Trucksess, D.W.R. Ready, M.K. Pender, C.A. Ligmond, G.E. Wood and S.W. Page, J. AOAC Int., 79 (1996) 883. 150 G.A. Bennett, O.L. Shotwell and W.F. Kwolek, J. Am. Off. Assoc. Chem., 68 (1985) 958. 151 T. Tanaka, R. Teshirna, H. Ikebuchi, J. Sawada, T. Terao and M. Ichinoe, J. AOAC Int., 76 (1993) 1006. 152 V. Siedel, E. Poglitis, K. Shiller and W. Lindner, J. Chromatogr., 635 (1993) 227. 153 W.E. Sydenham, G.S. Shephard and P.G. Thiel, J. AOAC Int., 75 (1992) 313.
424
Carlo Brera et al.
154 P.F. Ross, P.E. Nelson, J.L. Richard, G.D. Osweiler, L.G. Rice, R.D. Plattner and T.M. Wilson, Appl. Environ. Microbiol., 56 (1990) 3225. 155 A. De Girolamo, M. Solfrizzo, C. von Holst and A. Visconti, Food Addit. Contam., 18 (2001) 59. 156 M. Solfrizzo, A. De Girolamo, A. Visconti, E. Sizoo and H.P. van Egmond. In: W. De Koe, R. Samson, H.P. van Egmond, J. Gilbert, Ponsen and Looyen (Eds.), Mycotoxins and Phycotoxins in Perspective at the Turn of the Millennium: Determination of Fumonisin B1 and B2 in Corn Based Foodstuffs by High Performance Liquid Chromatography after Immunoaffinity Cleanup — in House and Interlaboratory Validation, Ponsen and Looyen, Wageningen, The Netherlands, 2000. 157 T.E. Moller and H.F. Gustavsson, J. AOAC Int., 83 (2000) 99. 158 S. Mac Donald, M. Long and J. Gilbert, J. AOAC Int., 83 (2000) 1387. 159 M.P. Herry and N. Leneayer, J. AOAC Int., 79 (1996) 1107. 160 M.W. Trucksess and Y. Tang, J. AOAC Int., 82 (1999) 1109. 161 M. Llovera, R. Viladrich, M. Torres and R. Canela, J. Food Protect., 62 (1999) 202. 162 H.S. Rupp and S.B. Turnipseed, J. AOAC Int., 83 (2000) 612. 163 J.A. Roach, K.D. White, M.W. Trucksess and F.S. Thomas, J. AOAC Int., 83 (2000) 104. 164 B.I. Vazquez, C. Fente, C. Franco, A. Cepeda, P. Prognon and G. Mahuzier, J. Chromatogr. A, 727 (1996) 185. 165 B.J. Xu, X.Q. Jia, L.J. Gu and C.K. Sung, Food Control., 17 (2006) 271. 166 Y. Hayashi and T. Yoshizawa, Food Chem., 93 (2005) 215. 167 J. Mulders and H.A.M. van Impelen-Peek, Z. Lebensmitt. Forsch., 183 (1986) 406. 168 B.K. Tacke and H.H. Casper, J. AOAC Int., 79 (1996) 472. 169 S. Heisel, J. Am. Soc. Brew. Chem., 54 (1996) 268. 170 J.C. Young and D.E. Games, J. Chromatogr., 627 (1992) 247. 171 AOAC Official Method 986.18., J. AOAC Int., 29 (2001) 25. 172 F. Berthiller, R. Schuhmacher, G. Buttinger and R. Krska, J. Chromatogr. A, 1062 (2005) 209. 173 J. Stroka, R. Van Otterdijk and E. Anklam, J. Chromatogr. A, 904 (2000) 251. 174 T.B. Whitaker, J.W. Dickens and A.B. Slate, J. Peanut Sci., 17 (1990) 96. 175 F. Berthiller, C. Dall’Asta, R. Schuhmacher, M. Lemmens, A. Gerhard and R. Krska, J. Agric. Food Chem., 53 (2005) 3421. 176 M. Spanjer, P. Rensen and J. Scholten, In: H. Njapau, S. Trujillo, H.P. van Egmond and D.L. Park (Eds.), Mycotoxins and Phycotoxins: Advances in Determination, Toxicology and Exposure Management: Multi-Mycotoxin Analysis by LC-MS/MS in a Single Sample Extract, Wageningen Academic Publishers, The Netherlands, 2006. 177 R.D. Plattner and C.M. Maragos, J. AOAC Int., 86 (2003) 61. 178 M. Hartl, M. Herderich and H.U. Humpf, Eur. Food Res. Technol., 209 (1999) 348. 179 C. Cavaliere, P. Foglia, E. Pastorini, R. Samperi and A. Lagana`, Rapid Commun. Mass Spectrom., 19 (2005) 2085. 180 L.K. Sørensen and T.H. Elbaek, Rapid Commun. Mass Spectrom., 820 (2005) 771. 181 M. Sulyok, F. Berthiller, R. Krska and R. Schuhmacher, Rapid Commun. Mass Spectrom., 20 (2006) 2649. 182 E. Razzazi-Fazeli, J. Bo¨hm and W.J. Luf, J. Chromatogr. A, 854 (1999) 45. 183 A. Lagana`, R. Curini, G. D’Ascenzo, I. de Leva, A. Faberi and E. Pastorini, Rapid Commun. Mass Spectrom., 17 (2003) 1037. 184 C.M. Maragos, Sem. Food Anal., 3 (1998) 353. 185 R. Tsao and T. Zhou, J. Agric. Food Chem., 48 (2000) 5231. 186 R. Pen˜a, M.C. Alcaraz, L. Arce and M. Valca´rcel, J. Chromatogr. A, 967 (2002) 303. 187 J. Dickens and M. Sepaniak, J. Environ. Monit., 2 (2000) 11. 188 C.M. Maragos and M. Appell, J. Chromatogr. A, 1143 (2007) 252. 189 J. Wei, E. Okerberg, J. Dunlap, C. Ly and J.B. Shear, Anal. Chem., 72 (2000) 1360. 190 E. Anklam, J. Stroka and A. Boenke, Food Control., 13 (2002) 173. 191 W.B. Shim, A. Kolosova, Y.J. Kim, Z.Y. Yang, S.J. Park, S.A. Eremin, I.S. Lee and D.H. Chung, Int. J. Food Sci. Technol., 39(8) (2004) 829. 192 C.M. Maragos and R.D. Plattner, J. Agric. Food Chem., 50 (2002) 1827. 193 C.M. Maragos, M.E. Jolley and M.S. Nasir, Food Addit. Contam., 19 (2002) 400. 194 V. Lippolis, M. Pascale and A. Visconti, J. Food Protect., 69(11) (2006) 2712.
Mycotoxins
425
195 M.S. Nasir and M.E. Jolley, J. Agric. Food Chem., 50 (2002) 3116. 196 C.M. Maragos, M.E. Jolley, R.D. Plattner and M.S. Nasir, J. Agric. Food Chem., 49 (2001) 596. 197 World Health Organization (WHO), Requirements for kits for immunoassay and other protein binding systems, document number: WHO/BS/80.1270/HRP/80.1, Geneva, CH, 1980. 198 Z. Zheng, J. Hanneken, D. Houchins, R.S. King, P. Lee and J.L. Richard, Mycopathologia, 159 (2005) 265. 199 M.M. Abouzied, A.D. Horvath, P.M. Podlesny, N.P. Regina, V.D. Motodiev, R.M. KamenovaTozeva, N.D. Niagolova, A.D. Stein, E.A. Petropoulos and V.S. Ganev, Food Addit. Contam., 19 (2002) 755. 200 T. Gumus, M. Arici and M. Demirci, J. Inst. Brew., 110 (2004) 146. 201 M.R.A. Morgan, Tetrahedron, 45 (1989) 2237. 202 A.A.G. Candlish, In: J.E. Smith and R.S. Henderson (Eds.), Mycotoxins and Animal Foods: The Determination of Mycotoxins in Animal Feeds by Biological Methods, CRC Press, Boca Raton, FL, 1991. 203 J.J. Park and F.S. Chu, J. AOAC Int., 79 (1996) 465. 204 L. Sibanda, S. De Saeger, T.G. Bauters, H.J. Nelis and C. Van Petenghem, J. Food Protect., 64 (2001) 1597. 205 L. Sibanda, S. De Saeger, I. Barna-Vetro and C. Van Petenghem, J. Agric. Food Chem., 50 (2002) 6964. 206 S. De Saeger, L. Sibanda, A. Desmet and C. Van Petenghem, Int. J. Food Microbiol., 75 (2002) 135. 207 S. De Saeger and C. Van Peteghem, Appl. Environ. Microbiol., 62 (1996) 1880. 208 E. Schneider, E. Usleber and E. Martlbauer, J. Agric. Food Chem., 43 (1995) 2548. 209 R. Salter, D. Douglas, M. Tess, B. Markovsky and S.J. Saul, J. AOAC Int., 89 (2006) 1327. 210 L.D. Mello and L.T. Kubota, Food Chem., 77 (2002) 237. 211 G. Marrazza, I. Chianella and M. Mascini, Anal. Chim. Acta, 387 (1999) 297. 212 M.A. Carlson, C.B. Bargeron, R.C. Benson, A. Fraser, T.E. Phillips, J.T. Velky, J.D. Groopman, P.T. Strickland and E.H.W. Ko, Biosens. Bioelectron., 14 (2000) 841. 213 D.P. Nikolelis, U.J. Hianik and P. Krull, Electroanal, 11 (1999) 7. 214 J.C.C. Yu and E.P.C. Lai, React. Funct. Polym., 63 (2005) 171. 215 C.M. Maragos and V.S. Thompson, Nat. Toxins, 7 (1999) 371. 216 W. Mullett, E.P.C. Lai and J.M. Yeung, Anal. Biochem., 258 (1998) 161. 217 S.J. Daly, G.J. Keating, P.P. Dillon, B.M. Manning, R. O’Kennedy, H.A. Lee and M.R.A. Morgon, J. Agric. Food Chem., 48 (2000) 5097. 218 H. Schnerr, R.F. Vogel and L. Niessen, Food Agric. Immunol., 14 (2002) 313. 219 A.J. Tudos, E.R. den Lucas-van Bos and E.C. Stigter, J. Agric. Food Chem., 51 (2003) 5843. 220 B. Van der Gaag, S. Spath, H. Dietrich, E. Stigter, G. Boonzaaijer, T. van Osenbruggen and K. Koopal, Food Control., 14 (2003) 251. 221 C.M. Maragos and V.S. Thompson, Nat. Toxins, 7 (1999) 371. 222 C.M. Maragos, Exp. Med. Biol., 504 (2002) 85. 223 P.D. Patel, Trends Anal. Chem., 21 (2002) 96. 224 S. Hauck, C. Kosslinger, S. Drost and H. Wolf, Lebensmittelchemie, 52 (1998) 15. 225 L. Micheli, R. Grecco, M. Badea, D. Moscone and G. Palleschi, Biosens. Bioelectron., 21 (2005) 588. 226 R.M. Pemberton, R. Pittson, N. Biddle, G.A. Drago and J.P. Hart, Anal. Lett., 39 (2006) 1573. 227 N.H.S. Ammida, L. Micheli, S. Piermarini, D. Moscone and G. Palleschi, Anal. Lett., 39 (2006) 1559. 228 R.V. Greene, S.H. Gordon, M.A. Jackson and G.A. Bennett, J. Agric. Food Chem., 40 (1992) 1144. 229 H. Pattersson and L. Aberg, Food Control., 14 (2003) 229. 230 N. Berardo, V. Pisacane, P. Battilani, A. Scandolara, A. Pietri and A. Marocco, J. Agric. Food Chem., 53 (2005) 8128. 231 G. Kos, H. Lohninger and R. Krska, Anal. Chem., 75 (2003) 1211. 232 M. Miraglia and C. Brera, Report on Tasks for Scientific Cooperation, Directorate-General Health and Consumer Protection (SCOOP Task 3.2.7.), 2002. 233 Food Standard Agency, 2003. Available at http://www.food.gov.uk/search?p ¼ Q&mainresults ¼ mt_mainresults_yes&ts ¼ v2&w ¼ aflatoxins 234 Food Standard Agency, Food Survey Information Sheet 73/05, 2005. Available at http:// www.food.gov.uk/science/surveillance/fsis2005/ 235 L.M. Kawashima and L.M. Valente Soares, Cienc. Tecnol. Aliment., 26 (2006) 516.
426
Carlo Brera et al.
236 B.T. Iamanaka, H.C. de Menezes, E. Vicente, R.S.F. Leite and M.H. Taniwaki, Food Control., 18 (2007) 454. 237 Y. Sugita-Konishi, M. Nakajima, S. Tabata, E. Ishikuro, T. Tanaka, H. Norizuki, Y. Itoh, K. Aoyama, K. Fujita, S. Kai and S. Kumagai, J. Food Protec., 69 (2006) 1365. 238 B.L. Sekiyama, A.B. Ribeiro, P.A. Machinski and M.J. Machinski, Braz. J. Microbiol., 36 (2005) 289. 239 A. Zinedine, C. Brera, S. Elakhdari, C. Catano, F. Debegnach, S. Angelini, B. De Santis, M. Faid, M. Benlemlih, V. Minardi and M. Miraglia, Food Control., 17 (2006) 868. 240 S. Ghitakou, K. Koutras, E. Kanellou and P. Markaki, Food Microbiol., 23 (2006) 612. 241 J. Tam, M. Mankotia, M. Mably, P. Pantazopoulos, R.J. Neil, P. Calway and M. Scott, Food Addit. Contam., 23 (2006) 693. 242 C. El-Adlouni, M. Tozlovanu, F. Naman, M. Faid and A. Pfohl-Leskowicz, Mol. Nutr. Food Res., 50 (2006) 507. 243 A. Finoli, C. Vecchio and A. Planeta, Industrie Alimentari, 44 (2005) 506. 244 H.Z. Senyuva, J. Gilbert, S. Ozcan and U. Ulken, J. Food Protec., 68 (2005) 1512. 245 A. Pietri, T. Bertuzzi, L. Pallaroni and G. Piva, Food Addit. Contam., 21 (2004) 479. 246 B. Fazekas, A. Tar and M. Kovacs, Food Addit. Contam., 22 (2005) 856. 247 A.H.W. Abdulkadar, A.A. Al-Ali, A.M. Al-Kildi and J.-H. Al-Jedah, Food Control., 15 (2004) 543. 248 B. Sangare-Tigori, S. Moukha, H.J. Kouadio, A.M. Betbeder, D.S. Dano and E.E. Creppy, Food Addit. Contam., 23 (2006) 1000. 249 N. Unusan, Food Chem. Toxicol., 44 (2006) 1897. 250 C.A.F. Oliveira and J.C.O. Ferraz, Food Control., 18 (2007) 375. 251 L. Shundo and M. Sabino, Braz. J. Microbiol., 37 (2006) 164. 252 G.J. Diaz and E. Espitia, Food Addit. Contam., 23 (2006) 811. 253 A. Kamkar, Food Control., 17 (2006) 768. 254 M. Bognanno, L. Fauci, A. Ritieni, A. Tafuri, A. Lorenzo, P. de Micari, L. Renzo, S. di Ciappellano, V. Sarullo and F. Galvano, Mol. Nutr. Food Res., 50 (2006) 300. 255 A.M. Elgerbi, K.E. Aidoo, A.A. Candlish and R.F. Tester, Food Addit. Contam., 21 (2004) 592. 256 M.L. Martins and H.M. Martins, Int. J. Food Microbiol., 91 (2004) 315. 257 A. Pietri, T. Bertuzzi, M. Moschini and G. Piva, Ital. J. Food Sci., 15 (2003) 301. 258 V. Roussi, A. Govaris, A. Varagouli and N.A. Botsoglou, Food Addit. Contam., 19 (2002) 863. 259 F. Minervini, A. Visconti, A. Bottalico and M.T. Montagna, Industrie Alimentari, 40 (2001) 513. 260 C. Araguas, E. Gonzalez-Penas and A. Lopez de Cerain, Food Chem., 92 (2005) 459. 261 T.M. Legarda and P.A. Burdaspal, Alimentaria, 350 (2004) 11. 262 B. Beretta, R. Domenico, A. de Gaiaschi, C. Ballabio, C.L. Galli, C. Gigliotti and P. Restani, Food Addit. Contam., 19 (2002) 70. 263 R. Serra, C. Mendonca and A. Venancio, Int. J. Food Microbiol., 111 (2006) S35. 264 S.N. Chulze, C.E. Magnoli and A.M. Dalcero, Int. J. Food Microbiol., 111 (2006) S5. 265 A. El-Khoury, T. Rizk, R. Lteif, H. Azouri, M.L. Delia and A. Lebrihi, J. Agric. Food Chem., 54 (2006) 8977. 266 A.M. Chiodini, P. Scherpenisse and A.A. Bergwerff, J. Agric. Food Chem., 54 (2006) 7399. 267 C. Brera, J.M. Soriano, F. Debegnach and M. Miraglia, Microchem. J., 79 (2005) 109. 268 A. Pietri, T. Bertuzzi, A. Gualla and G. Piva, Ital. J. Food Sci., 18 (2006) 99. 269 L. Gonzalez, C. Juan, J.M. Soriano, J.C. Molto and J. Manes, Int. J. Food Microbiol., 107 (2006) 223. 270 G. Prado, M.S. Oliveira, F. de Moreira Abrantes, L. Golcalves dos Santos, T. Veloso and R.E. Souza Barroso, Cienc. Tecnol. Aliment., 20 (2000) 192. 271 E.K. Tangni, S. Ponchaut, M. Maudoux, R. Rozenberg and Y. Larondelle, Food Addit. Contam., 19 (2002) 1169. 272 J.S. Bonvehi, J. Agric. Food Chem., 52 (2004) 6347. 273 T.E. Moller and M. Nyberg, Food Addit. Contam., 20 (2003) 1072. 274 G.A. Lombaert, P. Pellaers, G. Neumann, D. Kitchen, V. Huzel, R. Trelka, S. Kotello and P.M. Scott, Food Addit. Contam., 21 (2004) 578. 275 S. MacDonald, P. Wilson, K. Barnes, A. Damant, R. Massey, E. Mortby and M.J. Shepherd, Food Addit. Contam., 16 (1999) 253. 276 G. Engelhardt, J. Barthel and D. Sparrer, Mol. Nutr. Food Res., 50 (2006) 401. 277 A.M. Domijan, M. Peraica, Z. Jurjevic, D. Ivic and B. Cvjetkovic, Food Addit. Contam., 22 (2005) 677.
Mycotoxins
278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319
427
Z. Jurjevic, M. Solfrizzo, B. Cvjetkovic, G. Avantaggiato and A. Visconti, Mycotoxin Res., 15 (1999) 67. A. Molinie, V. Faucet, M. Castegnaro and A. Pfohl-Leszkowicz, Food Chem., 92 (2005) 391. S. MacDonald, T.J. Prickett, K.B. Wildey and D. Chan, Food Addit. Contam., 21 (2004) 172. P.H. Rasmussen, F. Ghorbani and T. Berg, Food Addit. Contam., 20 (2003) 396. M. Schollenberger, H.M. Muller, M. Rufle, H. Terry-Jara, S. Suchy, S. Plank and W. Drochner, Int. J. Food Microbiol., 113 (2007) 142. M. Schollenberger, H.M. Mueller, M. Ruefle, S. Suchy, S. Plank and W. Drochner, Mycopathologia, 161 (2006) 43. M. Schollenberger, H.M. Mueller, M. Ruefle, S. Suchy, S. Planck and W. Drochner, Int. J. Food Microbiol., 97 (2004) 317. H. Yazdanpanah, G.S. Shephard, W.F.O. Marasas, L. Westhuizen, H. van der Rahimian, S.N. Safavi, P. Eskandari and S.A. Ghiasian, Mycopathologia, 161 (2006) 395. C.G. Afolabi, R. Bandyopadhyay, J.F. Leslie and E.J.A. Ekpo, J. Food Protect., 69(8) (2006) 2019. C.M. Lino, L.J.G. Silva, A.L.S. Pena and M.I. Silveira, Anal. Bioanal. Chem., 384 (2006) 1214. F.M. Liu, P.C. Chen, Y.M. Fu and D.Y.M. Shih, J. Food Drug Anal., 13 (2005) 273. G.S. Shephard, L. Westhuizen, P.M. van der Gatyeni, N.I.M. Somdyala, H.M. Burger and W.F.O. Marasas, J. Agric. Food Chem., 53 (2005) 9634. C. Paepens, S. Saeger, L. de Sibanda, I. Barna-Vetro, M. Anselme, Y. Larondelle and C. van Peteghem, J. Agric. Food Chem., 53 (2005) 7337. T. Cirillo, A. Ritieni, M. Visone and R.A. Cocchieri, J. Agric. Food Chem., 51 (2003) 8128. T. Cirillo, A. Ritieni, F. Galvano and R. Amodio Cocchieri, Food Addit. Contam., 20 (2003) 566. A. Papadopoulou-Bouraoui, T. Vrabcheva, S. Valzacchi, J. Stroka and E. Anklam, Food Addit. Contam., 21 (2004) 607. G. Prado, M.S. Oliveira, S.O. Ferreira, T.B.S. Correa and B.R.R. Affonso, Cienc. Tecnol. Aliment., 17 (1997) 259. T.V. Milanez, L.M. Valente-Soares and G.G. Baptista, Food Control., 17 (2006) 293. M. Eskola, P. Parikka and A. Rizzo, Food Addit. Contam., 18 (2001) 707. W. Langseth and T. Rundberget, Mycopathologia, 147 (1999) 157. V.A. Tutelyan, Toxicol. Lett., 153 (2004) 173–179. K. Baert, B. de Meulenaer, A. Kamala, C. Kasase and F. Devlieghere, J. Food Protect., 69 (2006) 1371. B. Beretta, A. Gaiaschi, C.L. Galli and P. Restani, Food Addit. Contam., 17 (2000) 399. G. Boonzaaijer, I. Bobeldijk and W.A. van Osenbruggen, Food Control, 16 (2005) 587. V. Gokmen and J. Acar, J. Chromatogr. A, 815 (1998) 99. E.K. Tagni, R. Theys, E. Mignolet, M. Maudoux, J.Y. Michelet and Y. Larondelle, Food Addit. Contam., 20 (2003) 482. A. Ritieni, J. Agric. Food Chem., 51 (2003) 6086. L. Piemontese, M. Solfrizzo and A. Visconti, Food Addit. Contam., 22 (2005) 437. N.L. Leggott and G.S. Shephard, Food Control., 12 (2001) 73. G.Z. Omurtag and D. Yazicioglu, Food Addit. Contam., 18(9) (2001) 844. A. Visconti, V.M.T. Lattanzio, M. Pascale and M. Haidukowski, J. Chromatogr. A, 1075 (2005) 151. J. Perkowski and T. Basinski, Food Addit. Contam., 19 (2002) 478. J. Varga and Z. Kozakiewicz, Trends Food Sci. Technol., 17(2) (2006) 72. P. Battilani, N. Magan and A. Logrieco, Int. J. Food Microbiol., 111 (2006) S2. R.C. Schothorst and H.P. van Egmond, Toxicol. Lett., 153 (2004) 133. J.M. Soriano and S. Dragacci, Food Res. Int., 37 (2004) 985. A. Zinedine, J.M. Soriano, J.C. Molto and J. Manes, Food Chem. Toxicol., 45 (2007) 1. M. Jestoi, M. Rokka, T. Yli-Mattila, P. Parikka, A. Rizzo and K. Peltonen, Food Addit. Contam., 21(8) (2004) 794. S. Uhlig, M. Torp, J. Jarp, A. Parich, A.C. Gutleb and R. Krska, Food Addit. Contam., 21 (2004) 598. T. Gutema, C. Munimbazi and L.B. Bullerman, J. Food Protect., 63 (2000) 1732. H. Hartung, C. Kinast, U. Kirchheim, G. Eckert, B. Meixner and F. Schoene, Getreidetechnologie, 58 (2004) 231. A. Ritieni, S.M. Monti, G. Randazzo, A. Logrieco, A. Moretti, G. Peluso, R. Ferracane and V. Fogliano, J. Agric. Food Chem., 45 (1997) 3039.
CHAPT ER
13 Phycotoxins Kevin J. James, Daniel O’Driscoll, Javier Garcı´a Ferna´ndez and Ambrose Furey
Contents
1. 2. 3. 4.
Introduction Seafood-Poisoning Toxins Paralytic Shellfish Poisoning (PSP) Toxins Diarrhetic Shellfish Poisoning (DSP) Toxins 4.1 Toxicity of DSP toxins 4.2 Analysis of DSP toxins 5. Azaspiracid Poisoning (AZP) Toxins 5.1 Determination of azaspiracids using LC-MS and LC-MSn methods 6. Amnesic Shellfish Poisoning (ASP) Toxins 7. Yessotoxins (YTXs) 7.1 Rapid screening methods for YTXs 7.2 Determination of yessotoxins using LC-MS and LC-MSn methods 8. Neurotoxin Shellfish Poisoning (NSP) Toxins References
429 430 430 432 435 435 439 440 442 445 446 447 448 452
1. INTRODUCTION Phytoplankton are microalgae and are the main contributor to the marine food web as well as oxygen on earth. The beneficial role of algae in the food chain arises from the fact that they are the only organisms that can readily make long chain polyunsaturated fatty acids (PUFAs). Shellfish feed on phytoplankton and the potential beneficial role of shellfish in the human diet has been attributed to the presence of oils that are rich in PUFAs. Shellfish are also a rich source of protein, essential minerals, especially iron, vitamins A and D. However, some marine microalgae are known to produce bioactive compounds that negatively impact on human health through their accumulation in shellfish [1,2]. Many of these toxins Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00013-5
r 2008 Elsevier B.V. All rights reserved.
429
430
Kevin J. James et al.
are known to be highly potent [3]. The proliferation of toxin-bearing algae, mainly diatoms and dinoflagellates, called harmful algal blooms (HABs), has been a major cause of concern in recent years [4]. Bivalve molluscs filter large volumes of water when grazing on microalgae, and can concentrate both bacterial pathogens and phycotoxins [5]. These shellfish, especially mussels, scallops, oysters and clams, are major vectors for toxins that are implicated in several human toxic syndromes. These include amnesic shellfish poisoning (ASP) [6], diarrhetic shellfish poisoning (DSP) [7], paralytic shellfish poisoning (PSP) [8], neurotoxic shellfish poisoning (NSP) [9] and azaspiracid poisoning (AZP) [10]. ASP first came to attention in Canada in 1987 when human fatalities occurred from eating mussels (Mytilus edulis) [11]. Domoic acid (DA), which is produced by marine diatoms of the Pseudo-nitzschia spp., was identified as the causative toxic agent [12,13]. ASP causes gastric upset, headache and dizziness but the syndrome was named due to the persistent short-term memory impairment experienced by some patients [11]. Toxins produced mainly by marine dinoflagellates are some of the most potent poisons known and have a major impact on human health [1]. The accumulation of toxins in shellfish and fish has led to serious human toxicosis as well as animal and bird deaths. Table 1 shows the toxins produced by marine phytoplankton.
2. SEAFOOD-POISONING TOXINS Six main classes that cause poisoning from the consumption of seafood are discussed, with an emphasis on the methods for their detection and determination. The phycotoxin poisonings are widely known by their acronyms and include: Paralytic Shellfish Poisoning (PSP), Diarrhetic Shellfish Poisoning (DSP), Azaspiracid Poisoning (AZP), Amnesic Shellfish Poisoning (ASP), Yessotoxins (YTX) and Neurotoxic Shellfish Poisoning (NSP). Other less common seafood-poisoning toxins that are not discussed in this review include ciguatoxins [14], tetrodotoxins [15] and palytoxins [16].
3. PARALYTIC SHELLFISH POISONING (PSP) TOXINS The PSP toxins are basic, water soluble compounds, which are extremely sensitive to alkaline pH and air-oxidation. PSP toxins are potent marine neurotoxins, which specifically block the excitation current in the nerve and muscle cells, and this finally results in signs of paralysis. To date, there are over 21 known saxitoxin congeners. The structures of saxitoxin (Figure 1) congeners vary by differing combinations of hydroxyl and sulphate substituents at four sites on the molecule (R1–R4). Based on the substitutions at R4, the saxitoxins can be subdivided into four sub-groups, the carbamate, sulfocarbamoyl, decarbamoyl and deoxydecarbamoyl toxins. Substitutions at R4 result in substantial changes in toxicity, with the carbamate toxins being the most potent [17].
Phycotoxins
Table 1
Seafood toxic syndromes and toxin-producing phytoplankton
Toxic syndrome
Toxins
Affected seafood
Source of toxins
Paralytic shellfish poisoning (PSP)
Saxitoxin (STX), Neosaxitoxin (NEO), Gonyautoxin (GTX) (21 analogues) Okadaic acid (OA), Dinophysistoxins (DTXs), Pectenotoxins (PTXs) Yessotoxins (YTXs)a
Shellfish, crustacions
Alexandrium spp. [136], Gymnodinium spp. [137]
Shellfish
Dinophysis spp. [35,38], Prorocentrum spp. [37,138]
Shellfish
Protoceratium reticulatum [108], Lingulodinium polyedrum [139] Karenia brevis (Ptychodiscus brevis) [140,9] Pseudo-nitzschia spp. [12,141] Protoperidinium crassipes [76] Gambierdiscus toxicus [142] Ostreopsis siamensis [143]
Diarrhetic shellfish poisoning (DSP)
a
431
Neurotoxin shellfish poisoning (NSP)
Brevetoxins (PbTx)
Shellfish, finfish
Amnesic shellfish poisoning (ASP) Azaspiracid poisoning (AZP) Ciguatera poisoning
Domoic acid (DA) and analogues Azaspiracids (AZAs) Ciguatoxins (CTXs)
Shellfish, finfish
Palytoxin poisoning
Palytoxin
Shellfish Finfish Seaweed, crabs, finfish
YTXs were originally included in the DSP category.
Human symptoms of PSP vary depending on the dose and the individual. In the case of a mild intoxication, a sensation of tingling or numbness of the lips is experienced, gradually progressing to the face and neck; pins and needles in the extremities; headache, vertigo, nausea, vomiting and diarrhoea occur in tandem. Extreme intoxication results in muscular paralysis, choking and extreme respiratory difficulty often culminating in respiratory failure [18]. Although marine dinoflagellates have been identified as the progenitors of PSP toxins that contaminate bivalve shellfish, these toxins are also produced in freshwaters by cyanobacteria (Aphanizomenon flos-aquae) [19] and have been responsible for mass mortalities of cattle and sheep [20]. Several analytical techniques have been developed to determine the PSP toxins including: receptor binding assay [21], mouse bioassay [22], liquid chromatography with fluorimetric detection (LC-FLD) [23], liquid chromatography with mass spectrometric detection (LC-MS) [24] and capillary electrophoresis [25].
432
Kevin J. James et al.
R4 NH
O O R1
NH
N
NH2 H2N
N R3
Saxitoxins STX GTX II GTX III NEO GTX I
R1 H H H OH OH
NH OH OH R2
R2 H OSO −3 H H − OSO 3
R3 H H − OSO 3 H H
Figure 1 Structure of the most common PSP toxins; R4 ¼ H; Carbamoyl.
Hydrophilic interaction LC with MS detection has also been used for the analysis of PSP toxins [26]. The most frequently used methods for PSP determination involve LC-FLD and these are based on the oxidation of PSP toxins to fluorescent products. These sensitive determinations can be performed post-column, as first developed by Oshima [27], and these remain the definitive methods for the determination of a wide range of PSP analogues. This derivatization procedure has also been used for the determination of PSP toxins in body fluids in the forensic investigation of fatal intoxications following shellfish consumption [18]. However, the pre-column oxidation method, developed by Lawrence et al., is more convenient for the routine monitoring of PSP toxicity and has recently been adopted as an AOAC International reference method [28–30]. PSP toxins are basic and can be readily extracted from a shellfish homogenate using dilute hydrochloric acid. The oxidation reaction can be carried out using either periodate or peroxide and the fluorescent products can be separated using either reversed-phase or ion exchange columns. Figure 2 shows the chromatograms that were obtained from contaminated mussel tissue [29]. The main disadvantage of this method is that not all PSP analogues can be identified as the oxidation step can produce the same fluorescent product from more than one PSP toxin.
4. DIARRHETIC SHELLFISH POISONING (DSP) TOXINS DSP is a widely distributed seafood contamination. Three classes of toxins were initially included in the DSP group (a) dinophysistoxins, (b) pectenotoxins (PTXs)
Phycotoxins
433
Figure 2 Sample chromatograms from the inter-laboratory study of determination of PSP toxins in various bivalve shellfish, using the Lawrence LC-FLD method that involves pre-column oxidation. (A) Analysis of mussels containing PSP toxins; (B) Analysis of clams containing PSP toxins. Adapted with permission from Ref. [29]. Copyright 2005 by AOAC International.
and (c) yessotoxins (YTXs) [7,31,32]. However, YTX is not diarrhetic and is no longer classified as a DSP toxin [33,34]. DSP was first reported in Japan in 1978 but the illness is now recognized as an important threat to public health throughout the world and outbreaks have resulted in prolonged closures of shellfish culturing industries. Dinophysistoxin-1 (DTX1) was identified in Japan as the causative toxin and was accumulated in bivalve shellfish through filter feeding on the dinoflagellate, Dinophysis fortii [35]. However, most incidents of DSP have involved the demethyl analogue, okadaic
434
Kevin J. James et al.
acid (OA), as the responsible toxin arising from a variety of Dinophysis sp. [36–38]. DTX2, an isomer of OA (Figure 3), was first isolated from Irish mussels and this was the predominant toxin during major DSP events in 1991 and 1994 [39,40]. DTX2 was subsequently identified in shellfish along the western coastline of Europe [25]. The PTXs were first isolated from toxic shellfish in Japan and frequently cooccur with OA and DTXs [7]. It is often observed that the toxin profiles in shellfish are more complex than in the marine phytoplankton where toxins originate. Thus, although PTX2 (Figure 4A, R ¼ CH3) is the main PTX in Dinophysis spp., several PTX analogues are found in shellfish tissues that are formed from PTX2 by repeated oxidation; PTX1 (R ¼ CH2OH), PTX3 (R ¼ CHO) and PTX6 (R ¼ COOH) as well as other PTX analogues that are formed by epimerization at C-7 [32]. Pectenotoxin-2 seco acids (PTX2SAs) have also been isolated and identified in dinoflagellates and shellfish [41,42]. PTX2SAs have an open chain structure and not a lactone ring like the rest of the PTXs (Figure 4B).
HO
O HO
O
OH
R1
O
O
O
O
OH
H
O
H OH 1
O R2 2
Figure 3 Structures of dinophysistoxins; Okadaic acid (OA); R ¼ Me, R ¼ H; dinophysistoxin-1 (DTX1); R1 ¼ R2 ¼ Me, dinophysistoxin-2 (DTX2); R1 ¼ H, R2 ¼ Me.
O
CH3 O
A)
O
O H3C
O OH CH3 O
OH OH
O
O
O
R CH3
O
O
B)
HO
CH3
O
CH3
H 3C
O
OH CH3 O
OH OH O O
O
O
OH H 3C
H 3C
O
O
O CH3
CH3
CH3
Figure 4 Structure of (A) Pectenotoxins; PTX2 (R ¼ CH3), PTX1 (R ¼ CH2OH), PTX3 (R ¼ CHO), PTX6 (R ¼ COOH) and (B) Pectenotoxin-2 seco acids (PTX2SAs).
Phycotoxins
435
4.1 Toxicity of DSP toxins Serious diarrhetic effects have only been proven for DTXs. Hamano et al. first investigated the diarrhetic effects caused by OA [43]. The three major DTXs, OA, DTX2 and DTX1, are potent inhibitors of protein phosphatases (PP1 and PP2A) [44] and they are tumour promoters [45]. This phosphatase inhibition may be linked to degenerative changes in absorptive epithelium cells of the small intestine thus producing diarrhoea. The EU regulatory limit for total DTXs in shellfish is 0.16 mg/g edible tissues. Although PTX2 can induce diarrhetic symptoms, this only occurs at relatively high levels when compared with the DTXs [46]. The PTX2SAs exhibit substantially less toxicity than PTXs, indicating that the cyclic structure of PTX2 is important for toxicity [41].
4.2 Analysis of DSP toxins Live animal bioassays were the first methods that were used for the detection of DSP toxins, but problems due to the lack of sensitivity, false positives, lack of method validation and the prohibition of such testing in many countries on ethical considerations, has led to an examination of a variety of alternative analytical methods [47,48].
4.2.1 Rapid screening methods for DSP toxins Rapid screening methods, based on immunoassays provide convenient alternatives to live animal bioassays for screening shellfish tissues but these methods cannot be used for the precise quantitative determination of the DSP toxins [49–51]. A very sensitive method utilized LC linked with a protein phosphatase assay that used a 32P-labeled substrate but there are problems associated with using radioactive materials in regulatory laboratories [52]. More convenient colourimetric phosphatase inhibition assays have been developed in which the ability of PP2A to dephosphorylate a colourless substrate, p-nitrophenyl phosphate (p-NPP), to a coloured substrate, p-nitrophenol, was used to determine OA and DTXs [53,54]. A fluorescent inhibition assay for these toxins provides enhanced sensitivity for DTX detection [55].
4.2.2 Determination of DSP toxins using LC-FLD LC-FLD using the carboxylic acid derivatizing reagent, 9-anthryldiazomethane (ADAM), has been the most widely used method for the determination of DTXs and PTX2SAs [38,56]. Other fluorimetric reagents have been successfully employed for the determination of DSP toxins and have been discussed in a previous review [48]. Unfortunately, PTX2 and most other PTXs cannot be determined using LC-FLD as they lack a carboxylic acid moiety. Although these LC-FLD methods are sensitive, sample clean-up, especially with shellfish samples, can be prolonged and relatively complicated [57,58]. The high sensitivity of LC-FLD was demonstrated when this method was used to show that the non-culturable phytoplankton, Dinophysis acuta, was the progenitor of DTX2 by the analysis of unialgal samples (22–100 cells), collected manually from microscope slides [38].
436
Kevin J. James et al.
4.2.3 Determination of DSP toxins using LC-MS and LC-MSn methods One of the earliest applications of LC-MS for the analysis of food contaminants was the determination of DSP toxins in shellfish [59]. LC-MS allows the determination of DTXs and PTXs without recourse to derivatization and multiple tandem MS methods do not require rigorous sample clean-up [60]. Table 2 summarizes the LC-MS methods that have been used for the analysis of DSP toxins (DTXs and PTXs). All of the MS methods used were carried out using an API source with an ionspray/electrospray interface, coupled to a single quadrupole or a triple quadrupole mass analyser. A major problem with LC-MS methods for the analysis of toxins in shellfish tissues is ion suppression and this is evident when using exhaustive extraction procedures, especially alcohols without sample clean-up. The consequence is that multi-toxin methods that encompass a wide range of analyte polarities are very difficult to validate for quantitative analysis but may play a role as screening methods for toxins. High performance size exclusion chromatography has been applied for the clean-up of raw extracts from mussel tissue. The proposed protocol can be performed automatically to enable the fast and sensitive analysis of a large number of samples. The recovery using this method was approximately 70% with good repeatability [61]. One method to determine the potential impact of ion suppression is to analyse an extract from a toxin-free shellfish sample with simultaneous infusion of a toxin standard. OA was used as a representative toxin and the signal for this toxin was acceptably consistent in the regions where toxins are expected to elute, thus showing that ion suppression did not significantly vary [62]. Different MS scans events have been applied for the identification and quantification of DSP toxins in shellfish and phytoplankton samples. Single scan MS experiments and selected ion monitoring (SIM) were used in most LC-MS applications. SIM is useful for the identification of toxins and screening samples but the lower selectivity when compared with multiple tandem MS does present difficulties, especially with shellfish samples whenever there is limited sample clean-up [63,64]. Both positive and negative modes have been used for the LC-MS determination of DSP toxins (Table 2). In positive ion mode, MS is notorious for generating multiple adduct ions for DSP toxins, with [M+NH4]+, [M+Na]+and [M+H]+ ions being observed together in the full scan spectra [64,65]. This has a detrimental effect on quantitation due to division of signal. It is prudent therefore to use an additive, for example, ammonium or sodium acetate, to assist in the formation of a predominant ion type. However, some adduct ions, especially the sodiated ions, are very stable and are difficult to fragment. The first LC-MS/MS method for polyether toxins was applied to the determination of four DTXs in shellfish using selected reaction monitoring (SRM). Three of these toxins are isomers with identical CID spectra and therefore chromatographic separation is essential [66]. Negative polarity does not exhibit the problems of multiple ion formation but in some instances the spectra may not be rich in product ions. Draisci et al. proposed a negative mode method for the different DTXs and PTXs but poor resolution was achieved for isomers [60]. Suzuki et al. developed another negative polarity method using LC-MS (SIM) for OA, DTX1 and PTX6 with reasonable detection limits [65].
Scallop Luna-C18(2) (P. yessoensis) (150 2 mm, Mussels 5 mm) (M. galloprovincialis) ACN:0.05% AcOH Scallop Symmetry C18 (70:30, v/v). (P. yessoensis) (150 2.1 mm, 3.5 mm) Develosil ODS-MG- ACN:0.05% AcOH (70:30, v/v). 5 (150 2 mm, 5 mm)
OA, DTX1, PTX6, PTX2SAs PTX1, PTX2
SIM; [M-H]
ESI
ESI
SIM; [M+NH4]+
SIM; [M-H]
ISP
ACN:H2O (80:20, v/v) 0.1% TFA (positive) and 2mM NH4OH (negative) ACN:H2O (7:3, v/v) containing 0.1% AcOH
[60] ([42])
[65] ([147])
[63] ([61,65,148,149])
nr
400 pg per injection
0.01–0.08 mg/g HP
[66] ([64])
0.03 mg/g HP
SRM; Product ion scan; [M+H]+ SIM; [M+H]+; [M-H]
ISP
ACN:H2O (80:20, v/v, 0.1% TFA)
[146]
8 ng/g HP
SIM; [M+H]+
[144] ([145])
References
0.4 mg/ml
Detection limit
SIM; [M+H]+
ISP
ISP
Ionization MS experiments source
70–80% MeOH in H2O 0.1% TFA
ACN:H2O (90:10, v/v) 0.1%TFA
PTX2, PTX2SAs
OA, PTX2SAs
OA, DTX1, DTX2, DTX2B
OA, DTX1, DTX2
Mussel (M. edulis)
5 mm Vydac 214TP (C4) column (250 2.1 mm) Phytoplankton Vydac201TP C-18 Mussels (M. edulis) (250 2.1 mm, 5 mm) Mussel (M. edulis), Supelcosil LC18DB Mussel (300 1 mm, (M. galloprovincialis) 5 mm) Mussel (M. edulis), Supelcosil LC18DB (M. galloprovincialis) (300 1 mm, 5 mm)
Mobile phase
OA, DTX-1, DTX-2, DTX-3
Stationary phase
Matrix
LC-MS methods for the determination of DSP toxins
Compound
Table 2
Luna-C18(2) (150 2 mm, 5 mm)
Luna-C18(2) (150 2.2 mm, 5 mm) C8 (50 2.1 mm, 3 mm)
Hypersil-BDS-C8 (50 2 mm, 3 mm)
Greenshell Mussel (P. cancliculus)
Mussel (M. edulis) Phytoplankton cells (D. acuta) Mussel (M. edulis) Oysters (C. gigas) Scallop (P. maximus)
Mussels (M. edulis)
PTX6, PTX2, PTX2SAs, PTX1i, PTX1SAs OA, DTX1, DTX2, PTX2, PTX2SAs OA, DTX1, DTX2, PTX1, PTX2
ACN:H2O 4mM NH4OH and 50 mM formic acid. ACN:H2O both containing 1 mM NH4OAc 5mM ammonium acetate (pH 6.8) in water and ACN (95% v/v) A=water and B=ACN–water (95:5), both with 50 mM formic acid and 2 mM ammonium formate.
Mobile phase
SIM; [M-H]; [M+H]+; [M+Na]+
ESI
SRM or Product Ion Scanning
SRM; [M-H]
ESI
Detection limit
nr
nr
0.5 ng/g
SRM; [M+NH4]+ 0.01 mg/g
ESI
ESI
Ionization MS experiments source
ESI, electrospray; ISP, ionspray; SSI, sonic spray; TSI, turbospray; HP, hepatopancreas tissues; SRM, selected reaction monitoring; nr, not reported.
OA, DTX1, PTX2, PTX2SAs
Stationary phase
Matrix
Compound
Table 2 (Continued )
[153] ([154])
[152]
[62] ([67])
[150] ([151])
References
439
Phycotoxins
x 17
Intensity %
100
2
x 136
3
5
50 4
1
x 23
x 233
B) 100 1 Intensity %
A)
6
5 x 28
50 x 14
4
3 0
1
2
3
4
5 6
7 8 (min)
9 10 11
0
1
2 3
4
5
6 7 (min)
8
9 10 11
Figure 5 LC-MS/MS of DSP toxins. (A) Irish mussels (M. edulis), (B) Norwegian mussels (M. edulis). (1) OA (2.8 min), (2) DTX2 (3.5 min), (3) PTX2SAi (4.9 min), (4) 7-epi-PTX2SA (6.5 min), (5) PTX2 (9.8 min), (6) DTX1 (6.65 min). (Signal amplification, if any, is shown above each peak.). LC conditions: a gradient of acetonitrile-water containing 1 mM ammonium acetate was used and the column was a Luna C-18(2) (150 2.1 mm, 5 mm, Phenomenex). Adapted with permission from Ref. [62]. Copyright 2004 by Elsevier.
The identification of DSP toxins in marine biological material is seriously hampered by the lack of commercial availability of many standard toxins and the isolation of toxins from shellfish tissues to use as standards is a very protracted process. Using LC-MS/MS, characteristic product ion spectra can be obtained for each component in a mixture without interference from the other components. However, for most applications where sensitivity of determination using LC-MS/MS is important, the monitoring of specific precursor/product ions with Q1 and Q3, respectively, whilst fragmentation occurs in Q2 (SRM/MRM) is necessary. Triple quadrupole MS offers excellent quantitative analysis with high selectivity and a wide calibration range. The polarity difference between neutral toxins, such as PTX2, and the acidic toxins has implications both for efficient LC separations and MS ionization efficiency. In Figure 5, the SRM negative mode (Q1/Q3 pairs) were: 803/255 (OA and DTX2), 876/137 (PTX2SAs), 817/255 (DTX1), 857/137 and (PTX2). The optimized LC gradient gave excellent resolution of the OA isomers, the PTX2SA isomers and PTX2 in relatively short run-times (10 min) [62,67]. The case with which toxins can be determine when present in widely different concentrations is demonstrated in Figure 5B. Thus, PTX2 (peak 5) has a signal that is 233 times less than DTXI (peak 6).
5. AZASPIRACID POISONING (AZP) TOXINS AZP is the most recently discovered toxic syndrome from shellfish consumption [10]. The first confirmed event was in 1995 in the Netherlands and resulted from
440
Kevin J. James et al.
the consumption of mussels (M. edulis) from Killary Harbour in Ireland. Azaspiracids have also been found in other European countries, including the UK, Norway, France and Spain [68–70] and throughout the western coastline of Ireland [71–73]. Azaspiracids possess a polyether backbone, that include a trispiro ring assembly, an azaspiro ring fused with a 2,9-dioxabicyclo (3.3.1) nonane, and a terminal carboxylic group and co-occurs with an isomer, AZA6, and demethyl and methyl analogues, AZA1 and AZA3, respectively. Symptoms of AZP include nausea, vomiting, diarrhoea and abdominal cramps; similar to DSP. However, AZA1 is distinctly different from DSP toxins as it target organs include liver, spleen, the small intestine and it has also been shown to be carcinogenic [74,75]. The dinoflagellate, Protoperidinium crassipes, was identified as the responsible organism for the production of azaspiracids. This was achieved with LC-MS3 using only 200 cells that were manually collected from a microscope slide [76]. Protoperidinium spp. are difficult to culture in a laboratory environment and extensive sampling may need to obtain wild phytoplankton. P. crassipes is distributed in temperate to tropical waters and may even form blooms in warm water estuaries [77]. Following the total synthesis by Nicolaou et al., the structure of AZA1 (and consequently the structures of other AZAs) has been revised [78]. Figure 6 shows the revised structures of azaspiracids.
5.1 Determination of azaspiracids using LC-MS and LC-MSn methods LC-MS quantitative analysis of a complex matrix, such as a shellfish tissue extract, can be problematic and interferences, including ion suppression, are to be expected. The first LC-MS method that was employed to determine AZA1–AZA3 involved a preliminary diol solid phase extraction (SPE) clean-up step [79]. A comprehensive study of the clean-up and toxin recoveries using various types of SPE showed that C-18 and diol phases were preferred for azaspiracids [80]. Sample clean-up using SPE should also be applicable for incorporation into less specific and less sensitive analytical methods for the determination of azaspiracids in seafood. LC-MS(/MS) is a universal method for marine toxins, and has been successfully applied to the simultaneous determination of various groups of polyether toxins [60]. The first LC-MS/MS method was developed by Draisci et al. for the determination of the predominant azaspiracid, AZA1, in mussels using a triple quadrupole instrument [81]. This was later extended to the analysis of other azaspiracids using a monolithic column [82]. Although monolithic columns produce high chromatographic resolution, the high flow rates involved mean that these columns are rarely adopted for use with MS instruments. Using an ion-trap detector (ITD) MS, LC-MS3 methods have been developed for a wide range of azaspiracids [83–86], that included the full chromatographic resolution of eleven azaspiracids using reversed-phase LC. The elucidation of the fragmentation pathways of azaspiracids was especially important for the development of analytical methods. To this end, the powerful complementary roles of hybrid quadrupole time-of-flight (QqTOF) MS that produces high mass accuracy data and ITD MS that yields MSn data (Figure 7, Table 3), was
Phycotoxins
441
R1 O HO
8
R3
A 10 3
1
O
H
O
B
O H 14
C
D 19 O
H
H 20
HO 21 22 O E 23 H 39
NH
OH R2 R4
H
I H
37
O
O G O
27 28
F 30
H
Toxin
R1
R2
R3
R4
AZA1
H
CH3
H
H
AZA2
CH3
CH3
H
H
AZA3
H
H
H
H
AZA4
H
H
OH
H
AZA5
H
H
H
OH
AZA6
CH3
H
H
H
AZA7
H
CH3
OH
H
AZA8
H
CH3
H
OH
AZA9
CH3
H
OH
H
AZA10
CH3
H
H
OH
AZA11
CH3
CH3
OH
H
Figure 6 Structures of azaspiracids.
demonstrated in a study of AZA1–AZA3 fragmentations [87]. These toxins exhibit charge-remote fragmentation in positive mode following the initial water loss from the geminal diol moiety. A significant fragmentation is the loss of the A-ring in azaspiracids which was observed at the MS3 stage. This results in the loss of the C1-C9 portion of azaspiracids that contains the R1 and R3 substituents, leaving a residual ion [M+H-H2O-C9H10O2R1R3]+, that retains R2 and R4 [87]. It was possible to select unique product ions for each azaspiracid isomer (Table 3), thus eliminating the requirement for complete chromatographic separation for the determination of isomers [86]. Figure 8 shows the chromatograms and spectra from the analysis of the isomers, AZA4 and AZA5, which have the same mass but were conveniently discriminated by the selection of characteristic
442
Kevin J. James et al.
R1 A-ring cleavage C-ring cleavage
A O H C H
HO O NH
10 100
H O
R2
A-ring
E
O
E-ring cleavage
G O
672.6
F
H
C27-C28 cleavage
G-ring cleavage
-H2O [C27H44NO5]+
C19-C20
60
362.4
-H2O
770.6
300
-H2O
C-ring
444.5
-H2O
-H2O
512.4 530.3
344.3
350
-H2O
806.6 462.4
0 250
-H2O
-H2O
-H2O
752.5
426.5 262.2 301.1
788.6
400
450
[M+H-5H2O]+
20
[C22H36NO3]+
40
E-ring
654.5
[C31H48NO6]+
C27-C28 [C16H26NO3-H2O]+
Relative Abundance (%)
C19-C20 cleavage OH
H
I
80
H
D O
[M+H-3H2O]
O
[M+H-2H2O]+
O
H
[M+H-4H2O]+
HO
B
[M+H-H2OC9H12O2]+
O
500
55
636.5 588.1
600 m/z
650
700
750
800
850
900
Figure 7 Multiple tandem mass spectrum (MS3) of AZA1, produced by positive electrospray ionization using a quadrupole ion-trap (ITD) instrument. The inset shows the main chargeremote fragmentation processes. (The G-ring fragmentation is not observed in ITD.) Adapted with permission from Ref. [86]. Copyright 2004 by Elsevier.
product ions formed by A-ring fragmentation [85]. Although LC-MSn using a ITD MS instrument is less sensitive than MRM methods using a triple quadrupole MS instrument, the ability to acquire spectra in MS2 and MS3 modes without a diminution in the sensitivity of detection is an important advantage of ITD MS.
6. AMNESIC SHELLFISH POISONING (ASP) TOXINS DA (Figure 9) is an excitatory amino acid that has been implicated as responsible for a toxic outbreak in Canada in 1987 [13]. The intoxicated patients exhibited
Phycotoxins
443
Table 3 Azaspiracid structural assignments, R1–R4 (see Figure 7), and the molecule-related and product ion masses using positive electrospray mass spectrometry Name
R1
R2
R3
R4
[M+H]+
[M+H–H2O]+
[M+H–H2O–C9H10O2R1R3]+
AZA1 AZA2 AZA3 AZA4 AZA5 AZA6 AZA7 AZA8 AZA9 AZA10 AZA11
H CH3 H H H CH3 H H CH3 CH3 CH3
CH3 CH3 H H H H CH3 CH3 H H CH3
H H H OH H H OH H OH H OH
H H H H OH H H OH H OH H
842.5 856.5 828.5 844.5 844.5 842.5 858.5 858.5 858.5 858.5 872.5
824.5 838.5 810.5 826.5 826.5 824.5 840.5 840.5 840.5 840.5 854.5
672.4 672.4 658.4 658.4 674.4 658.4 672.4 688.4 658.4 674.4 672.4
gastrointestinal disorders, including nausea, vomiting, abdominal cramps and diarrhoea, manifesting about 24 h after the consumption of mussels. This was followed by the neurological symptoms of headache, confusion, disorientation, seizures and coma within 48–72 h. However, the permanent loss of short-term memory in some of the survivors led this toxic syndrome to be named ASP. The toxin in mussels causing the intoxication was identified as DA, which is a tricarboxylic amino acid (Figure 9). It was later shown that diatoms of the PseudoNitzschia spp. were the causative organisms for producing DA [12]. Following this outbreak of ASP, there have been worldwide reports of DA contamination of seafood [88–91]. Several methods have been developed for the detection of DA in shellfish, including radioimmunoassay and enzyme immunoassay [92,93]. However, LC-UV is used by most regulatory agencies for the quantitative determination of DA in shellfish and a limit of 20 mg DA/g has been generally adopted [94,95]. Analysis is complicated somewhat by the presence of isomers of DA, as well as tryptophan, in naturally contaminated samples. The DA analogues differ from DA by isomerism involving diene side-chain and they are not always chromatographically resolved. A rapid and sensitive LC-UV method has been developed for analysis of DA in shellfish extracts without the need for SPE cleanup. Isocratic reversed-phase LC separation of DA and its isomers from shellfish matrix interferences and from the prevalent amino acid, tryptophan, was achieved by using an optimized mobile phase pH of 2.5 [96]. Fluorimetric derivatization of DA was used in the application of three LC-FLD methods and the improved sensitivity has allowed the determination of DA at much lower concentrations in seawater and marine phytoplankton. Derivatizing reagents used include fluorenylmethoxycarbonyl chloride (FMOC) [97], 6-aminoquinoloyl-N-hydroxysuccinimidyl carbamate [98] and 4-fluoro7-nitro-2,1,3-benzoxadiazole (NBD-F) [99]. However, only the NBD-F method could be readily applied to the analysis of DA in shellfish without post-reaction
444
Kevin J. James et al.
A
95
90
Relative Abundance
4.63
90 85 80 75
B (RT=3.73 min) min
80 70 658.5
60 50 40 30
790.4826.6
20
65 60
10
55
0
50 45
100
40
90
35
80
Relative Abundance
Relative Abundance
70
808.5
x5
100
3.73
100
30 25 20 15 10 5
764.6 448.6 374.1 251.3 380.4 467. 640.4 851.8 545.1 4 400 600 800 m/z
C (RT=4.63 min)
70 60 674.4
50 40 30
4
6
8
10
Time (min)
790.4 826.4
446.0 362.5 326.2 438.1 509.5 587.1
10 2
808.5
x5
20
0
1000
0
400
600 m/z
736.8 800
1000
Figure 8 (A) Chromatogram showing the separation of the isomers, AZA4 & AZA5, which was obtained using LC-MS3; AZA4 (3.73 min) and AZA5 (4.63 min). (B) and (C) are the mass spectra corresponding to AZA4 and AZA5, respectively. Reproduced with permission from Ref. [84]. Copyright 2002 by Elsevier. CH3 COOH H
COOH CH3
N
COOH
H
Figure 9 Structure of domoic acid.
clean-up using SPE. Figure 10 shows the LC-FLD chromatograms for extracts from scallops (Pecten maximus), following derivatization with NBD-F, in which DA and two DA isomers (arrowed) are resolved as well as tryptophan (Try).
Phycotoxins
445
Fluorescence Intensity
DA
Try
0
2
4
6
8
10
12 14 Time (min)
Figure 10 LC-FLD of domoic acid in an extract from scallops, contaminated with DA. DA isomers (arrowed) are resolved from DA and tryptophan (Try) does not interfere.
Other methods that have been employed for the determination of DA include capillary electrophoresis with UV detection [100] and derivatization followed by GC-MS [101]. Several LC-MS methods for DA have been developed [102,103], but the benefits of using multiple tandem MS, including improved selectivity and sensitivity, have been demonstrated [104,105].
7. YESSOTOXINS (YTXS) YTXs originally were isolated from the digestive glands of scallops (Patinopecten yessoensis) [106]. Originally classified as DSP toxins as they do not induce diarrhoea YTXs have now been removed from this category [33,34]. The YTXs are sulphonated polyether toxins (Figure 11) and have been reported in shellfish in several countries including, Japan [106], Norway [107], New Zealand [108] and Italy [109]. Structurally, YTX is unusual as it is a sulphonated polyether with eleven fused rings [106,110]. Homoyessotoxin (homoYTX) has an additional methylene in the sulphated side-chain and together with their 45-hydroxy analogues, these constitute the main YTXs that have been found in shellfish. Several low-abundant analogues of YTX have also been reported [111,112]. Toxicological studies carried out in rodents show that YTX is highly toxic towards mice after intraperitoneal (i.p.) administration but it is virtually non-toxic when ingested orally [34]. The dinoflagellate, Protoceratium reticulatum, was found to produce high levels of YTX in New Zealand and Japan [113] and Lingulodinium polyedrum (Gonyaulax polyedra) has been identified as the producer of homoYTX as well as YTX in shellfish collected in the Adriatic Sea [114]. The mouse bioassay that is used for regulatory control of shellfish is very sensitive to YTX and false positives assay results are common for DSP assays. This is an unfortunate scenario as this bioassay, which has the greatest sensitivity for the least toxic shellfish contaminant, is still the official EU method.
446
Kevin J. James et al.
OH C 502
O
439
O
467
O OH 541†/319
186 -O3S O
O
2-
[C55H80O21S2]
[C26H37O10S]-
[C46H68O20S2]2-
[C26H38O14S2]2-
396.1352
[C42H62O19S2]2-
467.1639
O
[C39H58O18S2]2-
O
[C35H52O16S2]2
O
[C11H16O10S2]2
96.9519 [HSO4]-
Intensity (counts)
O
O
2.0e4
1.0e4
396
O
-
-O3S
3.0e4
O
O
570.2317
-
233.1829 319.085 439.1582 502.1835 186.014 541.2050 284.0664 7 9 0.0
100
200
300 400 m/z (amu)
500
600
Figure 11 Nano ESI QqTOF MS spectrum of YTX in negative mode and the main fragmentation processes. Adapted with permission from Ref. [124]. Copyright 2004 by Elsevier.
A sensitive LC-FLD method has been developed using the highly fluorescent dienophile, 4-[2-(6,7-dimethoxy-4-methyl-3-oxo-3,4-dihydroquinoxaliny)ethyl]-1,2, 4-triazoline-3,5-dione (DMEQ-TAD) for the determination of YTX and two of its analogues 45-hydroxyYTX and 45,46,47-trinorYTX in mussels and scallops [115]. These YTXs possess a diene moiety and DMEQ-TAD undergoes a Diels-Alder reaction with the diene producing two epimers. Unfortunately, this means that a chromatogram will show two poorly resolved peaks for each YTX.
7.1 Rapid screening methods for YTXs There are various ELISA methods that have been developed for a wide range of marine biotoxins, such as ASP, NSP, DSP and PSP [116]. A competitive indirect ELISA for screening the total amounts of YTXs in shellfish samples has been developed recently by Briggs et al. [117]. This has a working range (I20–I80) of
Phycotoxins
447
50–1100 pg/mL, and is suitable for monitoring YTXs in shellfish as well as in algae and seawater [116,117]. The polyclonal antibodies (produced by different cells) used in the YTX-ELISA recognize multiple analogues of YTX and this is why results of YTX analysis by ELISA are expected to be higher than those by LC-FLD or LC-MS. Improvements in the extraction and clean-up of YTXs from mussels have been proposed [118] as well as a slot blot procedure as a functional assay for YTXs [119].
7.2 Determination of yessotoxins using LC-MS and LC-MSn methods LC-MS and LC-MSn are incomparable tools for unambiguous confirmation of known toxins and for the identification of novel compounds. They are particularly useful in analysis of toxins when their reference standards are unavailable or very limited and the discovery of a wide range of YTX analogues has been made possible due to the increasing availability of multiple tandem MS instruments. The first MS studies on YTX were performed by Murata et al. [106] using negative Fast Atom Bombardment (FAB) MS. YTX exhibited two molecule-related ions, the desodiated ion [M-Na] (m/z ¼ 1163) and [M-SO3Na+H-Na] (m/z ¼ 1061) and the latter was used for identification of YTXs [106,120,121]. The applicability of tandem MS to the structural elucidation of polyether compounds was well demonstrated by Naoki et al. for YTX [110]. Extensive fragmentation of YTX in negative mode produced spectra that were particularly informative, especially the repetitive cleavage of each ring of the toxin giving a regular fragmentation pattern by a process known as charge-remote fragmentation. Thus, on the basis of MS/MS data alone, the authors succeeded in assigning the number and location of 11 rings of YTX, confirming previous NMR data [110]. The first LC-MS and LC-MS/MS methods developed for direct identification of YTX in shellfish samples [122] used an API source with an ionspray interface. Analytically useful molecular-related ions were observed, including the [M-2Na+H] ion, which was the most abundant, and was therefore selected as a precursor ion for CID MS/MS experiments. LC-MS/MS, using SRM, was developed. This method included an acetone extraction of YTX from shellfish, followed by reversed-phase LC, with isocratic elution using aqueous acetonitrile containing ammonium acetate 4 mM as the mobile phase. An instrumental detection limit of ca. 50 pg was estimated [66,114]. A reversed-phase SIM LC-MS analysis in negative ion mode was used to determine eleven DSP toxins, DTXs, PTXs as well as YTXs in the same chromatographic run with a total time of 20 min. Chromatographic separation is performed isocratically with a mobile phase of acetonitrile–water (80:20 v/v) containing 2 mM ammonium acetate [60]. Detection limits for the investigated toxins ranged from 100 to 400 pg of injected material and this method was proposed as a screening method. The simultaneous determination of ten toxins associated with DSP by LC-MS in scallops was reported [63]. Mass spectrometric measurements were performed using an API source with an electrospray ionization (ESI) interface. Chromatographic separation was carried out using a combination of different columns and mobile phases. Carboxylic acid toxins were determined using SIM of the
448
Kevin J. James et al.
% Relative Intensity
100
50
14.0
15.0
16.0
17.0
18.0
19.0 20.0 Time (min)
21.0
22.0
23.0
24.0
Figure 12 Chromatogram of an extract of in picked cells of Protoceratium sp. using nano LC – QqTOF MS to determine YTX. Adapted with permission from Ref. [124]. Copyright 2004 by Elsevier.
deprotonated [M-H] ions, neutral toxins were using their [M+NH4]+ ions, while for YTXs were determined using their [M-Na] ions. Limits of detection in shellfish tissues were in the range, 40–80 ng/g. LC-MSn was used for the determination of YTX and 45-OHYTX in shellfish using an ESI source with an ion-trap mass spectrometer, in negative mode [123]. The molecule-related ion at m/z 1141 [M-2Na+H] was used as the precursor ion for multiple MS experiments. MS2 and MS3 gave major fragment ions at m/z 1061 [1141SO3H] and m/z 924 [1061-C9H13O]. Predominant ions, due to the fragmentation of the backbone structure of YTXs, were observed at the MS4 stage. Reversed-phase LC using a C16 amide column was preferable to C18 phases for the separation of YTX and 45-OHYTX, using acetonitrile–water (60:40) with 0.5% ammonium acetate as mobile phase. The detection limit corresponded to 3 ng/g in shellfish tissue [123]. The first application of nano LC-QqTOF MS for the analysis of phycotoxins has been reported. Figure 11 shows the QqTOF MS spectrum which produces high mass accuracy MS data and the main fragmentation processes in negative mode are shown. The high mass accuracy data of precursor and product ions are particularly valuable for confirmation of toxin identity. The high sensitivity of this method allows the analysis of micro-samples and was applied to determine YTX in Protoceratium cells that were manually collected from a microscope slide. Figure 12 shows the chromatogram from the determination of YTX in an extract from cells of P. reticulatum, picked from a microscope slide. The injection volume (1 ml) was the equivalent of one cell. The MS range was m/z 500–1200 and the chromatogram was produced by selecting the m/z 570, [M-2Na]2, ion [124].
8. NEUROTOXIN SHELLFISH POISONING (NSP) TOXINS The polycyclic ether toxins, brevetoxins (PbTx), are responsible for NSP cause massive kills of marine animals, including endangered species, and threaten
Phycotoxins
449
Figure 13 MS/MS spectrum of the ammonium adduct of brevetoxin-3 using nanoelectrospray ionization. Reproduced with permission from Ref. [163]. Copyright 2006 by Wiley.
human health (Figure 13). Brevetoxins are depolarizing substances that open voltage gated sodium ion channels in cell membranes, leading to uncontrolled sodium ion influx into the cell. The main route of human intoxication is from the consumption of shellfish [9,125]. The effects of NSP are felt within 30–60 min and include chills, headache, diarrhoea, muscle weakness, muscle and joint pain, nausea and vomiting. In extreme cases, altered perception of hot and cold, difficulty in breathing, double vision and difficulty in swallowing. These toxins also cause respiratory distress by inhalation of sea spray [126]. NSP has not been known to be fatal, with symptoms generally resolving within a few days. Many brevetoxins have been identified as being products of the red tide dinoflagellate, Karenia brevis (formerly Ptychodiscus brevis) [127,128]. Studies into the metabolic products produced in shellfish, especially mussels, have revealed multiple brevetoxin analogues [129,130]. Various approaches to the detection of brevetoxins have been used, including mouse bioassay which is based on the time until death of mice injected intraperitoneally with crude toxin extracts from shellfish [131]. Cell bioassays that detect brevetoxins due to their sodium channel enhancing effects [132,133] and receptor-based assays, and radioimmunoassays, provide good detection sensitivity and have been widely used as screening tests [134,135]. LC-MS methods for the identification and quantitation of brevetoxins have been important, especially in studies of bioconversion and production of analogues in fish and marine animals following intoxication by brevetoxins (Table 4). One of the problems in the use of MS methods for brevetoxins is the formation of sodium adducts that resist fragmentation. Early approaches involved the optimization of acidic media for flow injection electrospray MS/MS to improve
Cockle; (Austrovenus stutchburyi), Oyster; (Crassostrea gigas)
BTX-B1, PbTx-3
PbTx-3, BTX-B5, BTX-B1, PbTx-2, PbTx-3, BTX-B1
Cockle (Austrovenus stutchburyi), Oyster (C. gigas), Mussel (Perna canaliculus)
Oyster (Crassostrea Glycine-cysteine, gvirginica) glutamyl-cysteine and glutathione analogues of PbTx-A and PbTx-B
(A) 0.1% acetic acid in water and (B) 0.1% glacial acetic acid in ACN Cadenza CD-C18 (A) 0.1% formic acid – (150 3 mm, acetonitrile (45:55) 3 mm) and (B) ACN for PbTx-3 YMC J’Sphere Water-acetonitrile ODS-L80 S-4 gradient with 0.1% (150 2 mm) or acetic acid Luna C8(2), (250 2 mm, 5 mm) Cadenza CD-C18 0.1% formic acid(150 3 mm, MeOH, 0.1% formic 3 mm) acid-acetonitrile, 0.2 M ammonium acetate-MeOH (1:1) YMC J’Sphere ODS L80 S-4, (250 2 mm)
Oyster; (C. virginica)
PbTx-2, PbTx-3
Mobile phase
Stationary phase
Matrix
Compound
Table 4 LC-MS methods for the determination of NSP toxins
nr
0.4 and 2 ng/g for BTX-B1 and PbTx-3 nr
0.2–2 ng/g
SIM; [M+H]+
SRM; [M+H]+ and [M–Na]
SIM; MH+
SRM; [M+H]+; [M–H]; [M–Na]
ESI
ESI
ESI
[159]
[158]
[157]
[156]
Detection limit Reference
ESI
Ionization MS experiments source
450 Kevin J. James et al.
Cockle (A. stutchburyi), Mussel (Perna canaliculus)
Oyster (C. virginica)
Clams (Chione cancellata, C. mercenaria), Whelk (Busycon contrarium)
PbTx-2, PbTx-3 BTX-B5, BTX-B1
PbTx-3, PbTx-9, PbTx-7, PbTx-10
PbTx-3
(A) 0.1% formic acid– ESI acetonitrile (45:55); (B) 0.1% formic acid– acetonitrile (25:75); (C) 0.2 M ammonium acetate-MeOH (3:7) and (D) MeOH ESI water (A) and YMC J’Sphere acetonitrile (B), ODS-L80 S-4 (150 2) or Luna with 0.1% acetic acid (YMC column) C8(2) 100 A or 0.5% acetic acid (250 2 mm, (LUNA column) 5 mm) YMC ODS-L80 20% ACN to 65% ESI or (250 2 mm). ACN in 45 min APCI +0.1% formic acid Cadenza CD-C18 (150 3 mm, 3 mm)
nr
0.15 ng PbTx-3
25 ng PbTx-3
SRM; [M+H]+-895 [M+H]+-897 [MNa]-1016, [MH]-909
SIM; [M+H]+
SIM; [M+H]+
[162]
[161]
[160]
Phycotoxins
451
452
Kevin J. James et al.
the production of protonated species [127,128,155]. Another recent approach used by Wang and Cole was to use ammonium fluoride in the eluent which led to the formation of [M+NH4]+ adducts that readily converted to protonated species, followed by further fragmentation as shown in Figure 13 [163].
REFERENCES 1 2 3 4 5 6 7 8 9 10 11 12
13
14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
J.L.C. Wright, Food Res. Int., 28 (1995) 347. Y. Shimizu, Ann. Rev. Microbiol., 50 (1996) 431. P.J. Scheuer, J. Nat. Toxins, 5 (1996) 181. G.M. Hallegraeff, Phycologia, 32 (1993) 79. H. Huss, Food Control, 18 (1997) 91. E.C.D. Todd, J. Food Protec., 56 (1993) 69. T. Yasumoto, M. Murata, Y. Oshima, M. Sano, G.K. Matsumoto and J. Clardy, Tetrahedron, 41 (1985) 1019. L.M. Botana, J.M. Vieites, M.C. Louzao and A. Alfonso, In: L.M.L. Nollet (Ed.), Handbook of Food Analysis, Marcel Dekker, New York, 2004, p. 991. D.G. Baden, FASEB J, 3 (1989) 1807. M. Satake, K. Ofuji, H. Naoki, K.J. James, A. Furey, T. McMahon, J. Silke and T. Yasumoto, J. Am. Chem. Soc., 120 (1998) 9967. T.M. Perl, L.M. Bedard, T.M.D. Kosatsky, J.C. Hockin, E.C.D. Todd and R.S. Remis, New Engl. J. Med., 322 (1990) 1775. S.S. Bates, C.J. Bird, A.S.W. de Freitas, R. Foxall, M. Gilgan, L.A. Hanic, G.R. Johnson, A.W. McCulloch, P. Odense, R. Pocklington, M.A. Quilliam, P.G. Sim, J.C. Smith, D.V. Subba Rao, E.C.D. Todd, J.A. Walter and J.L.C. Wright, Can. J. Aquat. Sci., 46 (1989) 1203. J.L.C. Wright, R.K. Boyd, A.S.W. DeFreitas, M. Falk, R.A. Foxall, W.D. Jamieson, M.W. Laycock, A.G. McCuloch, P. McInnis, P. Odense, V.P. Pathak, M.A. Quilliam, M.A. Regan, P.G. Sim, P. Therault, J.A. Walter, M. Gilgan, D.A.J. Richard and D. Dewar, Can. J. Chem., 67 (1989) 481. R.J. Lewis and M.J. Holmes, Compar. Biochem. Physiol. C. Pharmacol. Toxicol. Endocrinol., 106 (1993) 615. T. Yasumoto and M. Yotsu Yamashita, J. Toxicol. Toxin Rev., 15 (1996) 81. R.E. Moore and G. Bartolini, J. Am. Chem. Soc., 103 (1981) 2491. Y. Shimizu, Pure Appl. Chem., 58 (1986) 257. C. Garcıa, M.d.C. Bravo, M. Lagos and N. Lagos, Toxicon, 43 (2004) 149. M. Ikawa, K. Wegener, T.L. Foxall and J.J. Sasner, Toxicon, 20 (1982) 747. A.R. Humpage, J. Rositano, A.H. Bretag, P.D. Baker, B.C. Nicholoson and D.A. Steffensen, Aust. J. Mar. Freshwater Res., 45 (1994) 761. G.J. Doucette, M.M. Logan, J.S. Ramsdell and F.M. Van Dolah, Toxicon, 35 (1997) 625. J.J. Sullivan, J. Shellfish Res., 7 (1988) 587. J.F. Lawrence and C. Me´nard, Fresenius J. Anal. Chem., 339 (1991) 494. P. Pereira, H. Onodera, D. Andrinolo, S. Franca, F. Araujo, N. Lagos and Y. Oshima, Toxicon, 38 (2000) 1689. A. Gago-Martinez, J.A. Rodriguez-Vasquez, P. Thibault and M.A. Quilliam, Nat. Toxins, 4 (1996) 72. C. Dell’Aversano, G.K. Eaglesham and M.A. Quilliam, J. Chromatogr. A, 1028 (2004) 155. Y. Oshima, J. AOAC Int., 78 (1995) 528. J.F. Lawrence, B. Wong and C. Menard, J. AOAC Internat., 5 (1996) 1111. J.F. Lawrence, B. Niedzwiadek and C. Menard, J. AOAC Int., 88 (2005) 1714. B. Ben-Gigirey, M.L. Rodriguez-Velasco, A. Villar-Gonzalez and L.M. Botana, J. Chromatogr. A, 1140 (2007) 78. T. Yasumoto, Y. Oshima and M. Yamaguchi, Bull. Jpn. Soc. Sci. Fish., 44 (1978) 1249. T. Yasumoto and M. Murata, In: E.P. Ragells (Ed.), Marine Toxins: Origin, Structure, and Molecular Pharmacology, American Chemical Society, Washington, 1990, p. 120.
Phycotoxins
453
33 H. Ogino, M. Kumagai and T. Yasumoto, Nat. Toxins, 5 (1997) 255. 34 T. Aune, R. Sørby, T. Yasumoto, H. Ramstad and T. Landsverk, Toxicon, 40 (2002) 77. 35 T. Yasumoto, Y. Oshima, W. Sugawara, Y. Fukuyo, H. Oguri, T. Igarashi and N. Fujita, Bull. Jpn. Soc. Sc. Fish., 46 (1980) 1405. 36 H.P. van Egmond, T. Aune, P. Lassus, G.J.A. Speijers and M. Waldock, J. Nat. Toxins, 2 (1993) 41. 37 J.S. Lee, T. Igarashi, S. Fraga, E. Dahl, P. Hovgaard and T. Yasumoto, J. Appl. Phycol., 1 (1989) 147. 38 K.J. James, A.G. Bishop, M. Gillmann, S.S. Kelly, C. Roden, R. Draisci, L. Lucentini, L. Giannetti and P. Boria, J. Chromatogr., 777 (1997) 213. 39 T. Hu, J. Doyle, D. Jackson, J. Marr, E. Nixon, S. Pleasance, M.A. Quilliam, J.A. Water and J.L.C. Wrigtht, J. Chem. Soc. Chem. Commun., 30 (1992) 39. 40 E.P. Carmody, K.J. James and S.S. Kelly, Toxicon, 34 (1996) 351. 41 M. Daiguji, M. Satake, K.J. James, A.G. Bishop, L. MacKenzie, H. Naoki and T. Yasumoto, Chem. Lett., (1998) 653. 42 K.J. James, A.G. Bishop, R. Draisci, L. Palleschi, C. Marchiafava, E. Ferretti, M. Satake and T. Yasumoto, J. Chromatogr. A, 844 (1999) 53. 43 Y. Hamano, Y. Kinoshita and T. Yasumoto, J. Food Hyg. Soc. Japan, 27 (1986) 375. 44 P. Cohen, C.F.B. Holmes and Y. Tsukitani, TIBS, 15 (1990) 98. 45 H. Fujiki and M. Suganuma, Adv. Cancer Res., 61 (1993) 143. 46 K. Terao, E. Ito, T. Yanagi and T. Yasumoto, Toxicon, 24 (1986) 1141. 47 J.M. Fremy, L. Puech, S. Krys and S. Dragacci, J. Applied Phycol., 11 (1999) 377. 48 K.J. James, A.G. Bishop, E.P. Carmody and S.S. Kelly, In: L.M. Botana (Ed.), Seafood and Freshwater Toxins: Pharmacology, Physiology and Detection, Marcel Dekker, New York, 2000, p. 217. 49 S. Matsuura, Y. Hamano, H. Kita and Y. Takagaki, Jpn. J. Toxicol. Environ. Health, 40 (1994) 365. 50 I. Imai, H. Sugioka, G. Nishitani, T. Mitsuya and Y. Hamano, Mar. Pollut. Bull., 47 (2003) 114. 51 M.P. Kreuzer, C.K. O’Sullivan and G.G. Guilbault, Anal. Chem., 71 (1999) 4198. 52 C.B.F. Holmes, Toxicon, 29 (1991) 469. 53 A. Tubaro, C. Florio, E. Luxich, S. Sosa, R. Della Loggia and T. Yasumoto, Toxicon, 34 (1996) 743. 54 H. Ramstad, S. Larsen and T. Aune, Toxicon, 39 (2001) 515. 55 M.R. Vieytes, O.I. Fontal, F. Leira, J.M.V. Baptista de Sousa and L.M. Botana, Anal. Biochem., 248 (1997) 258. 56 J.S. Lee, T. Yanagi, R. Kenma and T. Yasumoto, Agric. Biol. Chem., 51 (1987) 877. 57 H. Ramstad, J.L. Shen, S. Larsen and T. Aune, Toxicon, 39 (2001) 1387. 58 J.C. Marr, L.M. McDowell and A. Quilliam, Nat. Toxins, 2 (1994) 302. 59 S. Pleasance, M.A. Quilliam, A.S.W. de Freitas, J.C. Marr and A.D. Cembella, Rapid Commun. Mass Spectrom., 4 (1990) 206. 60 R. Draisci, L. Palleschi, L. Giannetti, L. Lucentini, K.J. James, A.G. Bishop, M. Satake and T. Yasumoto, J. Chromatogr., 847 (1999) 213. 61 C. Hummert, S. Kastrup, K. Reinhardt, M. Reichelt and B. Kluckas, Chromatographia, 51 (2000) 397. 62 P.F. Puente, M.J.F. Saez, B. Hamilton, M. Lehane, H. Ramstad, A. Furey and K.J. James, J. Chromatogr. A, 1056 (2004) 77. 63 H. Goto, T. Igarashi, M. Yamamoto, M. Yasuda, R. Sekiguchi and R. Featherstone, J Chromatogr., 907 (2001) 181. 64 R. Draisci, L. Lucentini, L. Giannetti, P. Boria and A. Stacchini, Toxicon, 33 (1995) 1591. 65 T. Suzuki and T. Yasumoto, J. Chromatogr., 874 (2000) 199. 66 R. Draisci, L. Lucentini, L. Giannetti, P. Boria, K.J. James, A. Furey, M. Gillman and S.S. Kelly, J. AOAC. Int., 81 (1998) 441. 67 P.F. Puente, M.J.F. Saez, B. Hamilton, A. Furey and K.J. James, Toxicon, 44 (2004) 919. 68 K.J. James, A. Furey, M. Lehane, H. Ramstad, T. Aune, P. Hovgaard, S. Morris, W. Higman, M. Satake and T. Yasumoto, Toxicon, 40 (2002) 909. 69 A. Bran˜a Magdalena, M. Lehane, S. Kris, M.L. Fernandez, A. Furey and K.J. James, Toxicon, 42 (2003) 105. 70 K.J. James, A. Furey, M. Lehane, C. Moroney, M. Satake and T. Yasumoto, In: W.J. de Keo, R.A. Samson, H.P. van Egmond, J. Gilbert and M. Sabino (Eds.), Mycotoxins and Phycotoxins in Perspective at the Turn of the Century, W.J. de Keo, Wageningen, 2001, p. 401.
454
Kevin J. James et al.
71 K. Ofuji, M. Satake, T. McMahon, J. Silke, K.J. James, H. Naoki, Y. Oshima and T. Yasumoto, Nat. Toxins, 7 (1999) 99. 72 K. Ofuji, M. Satake, T. McMahon, K.J. James, H. Naoki, Y. Oshima and T. Yasumoto, Biosci. Biotechnol. Biochem., 65 (2001) 740. 73 A. Furey, C. Moroney, A. Bran˜a-Magdalena, M.J. Fidalgo-Saez, M. Lehane and K.J. James, Environ. Sci. Technol., 37 (2003) 3078. 74 E. Ito, M. Satake, K. Ofuji, N. Kurita, T. McMahon, K.J. James and T. Yasumoto, Toxicon, 38 (2000) 917. 75 E. Ito, M. Satake, K. Ofuji, M. Higashi, K. Harigaya, T. McMahon and T. Yasumoto, Toxicon, 40 (2002) 193. 76 K.J. James, C. Moroney, C. Roden, M. Satake, T. Yasumoto, M. Lehane and A. Furey, Toxicon, 41 (2003) 145. 77 H.J. Jeong and M.I. Latz, Mar. Ecol. Prog. Series, 106 (1994) 173. 78 K.C. Nicolaou, Y.W. Li, N. Uesaka, T.V. Koftis, S. Vyskocil, T.T. Ling, M. Govindasamy, W. Qian, F. Bernal and D.Y.K. Chen, Angewandte Chemie-International Edition, 42 (2003) 3643. 79 K. Ofuji, M. Satake, Y. Oshima, T. McMahon, K.J. James and T. Yasumoto, Natural Toxins, 7 (1999) 247. 80 C. Moroney, M. Lehane, A. Bran˜a-Magdalena, A. Furey and K.J. James, J. Chromatogr., 963 (2002) 353. 81 R. Draisci, L. Palleschi, E. Ferretti, A. Furey, K.J. James, M. Satake and T. Yasumoto, J. Chromatogr., 871 (2000) 13. 82 D.A. Volmer, S. Brombacher and B. Whitehead, Rapid Commun. Mass Spectrom., 16 (2002) 2298. 83 A. Furey, A. Bran˜a-Magdalena, M. Lehane, C. Moroney, K.J. James, M. Satake and T. Yasumoto, Rapid Commun. Mass Spectrom., 16 (2002) 238. 84 M. Lehane, A. Bran˜a-Magdalena, C. Moroney, A. Furey and K.J. James, J. Chromatogr., 950 (2002) 139. 85 K.J. James, M. Diaz Sierra, M. Lehane, A. Bran˜a Magdalena and A. Furey, Toxicon, 41 (2003) 277. 86 M. Lehane, M.J. Fidalgo Sa´ez, A. Bran˜a Magdalena, I. Ruppe´n Can˜a´s, M. Dı´az Sierra, B. Hamilton, A. Furey and K.J. James, J. Chromatogr., 1024 (2004) 63. 87 M. Diaz-Sierra, A. Furey, B. Hamilton, M. Lehane and K.J. James, J. Mass Spectrom., 38 (2003) 1178. 88 A. Miguez, M. Luisa Fernandez and S. Fraga, In: T. Yasumoto, Y. Oshima and Y. Fukuro (Eds.), Harmful and Toxic Algal Blooms, Intergovernmental Oceanographic Commission of UNESCO, Paris, 1998, p. 143. 89 Z. Amzil, J. Fresnel, D. Le Gal and C. Billard, Toxicon, 39 (2001) 1245. 90 C.J. Bird and J.L.C. Wright, World Aquaculture, 20 (1989) 40. 91 L. Rhodes, D. White, M. Syhre and M. Atkinson, In: T. Yasumoto, Y. Oshima and Y. Fukuyo (Eds.), Seventh International Conference on Toxic Phytoplankton, UNESCO, Sendai, Japan, 1995, p. 155. 92 J.F. Lawrence, C. Cleroux and J.F. Truelove, J. Chromatogr., 662 (1994) 173. 93 K. Kawatsu, Y. Hamano and T. Noguchi, J. AOAC Int., 83 (2000) 1384. 94 M.A. Quilliam, P.G. Sim, A.W. McCulloch and A.G. McInnes, Intern. J. Environ. Anal. Chem., 36 (1989) 139. 95 J.F. Lawrence, C.F. Chrabonneau and C. Me´nard, J. Assoc. Off. Anal. Chem., 74 (1991) 68. 96 A. Lo´pez-Rivera, B. Sua´reza, M. Ferna´ndez Amandi, A. Furey and K.J. James, Anal. Bioanal. Chem., 381 (2005) 1541. 97 R. Pocklington, J.E. Milley, S.S. Bates, C.J. Bird, A.S.W. DesFreitas and M.A. Quilliam, Intern. J. Environ. Anal. Chem., 38 (1990) 351. 98 T. Sun and W.H. Wong, J. Agric. Food Chem., 47 (1999) 4678. 99 K.J. James, M. Gillman, M. Lehane and A. Gago-Martinez, J. Chromatogr., 871 (2000) 1. 100 J.Y. Zhao, P. Thibault and M.A. Quilliam, Electrophoresis, 18 (1997) 268. 101 S. Pleasance, M. Xie, Y. LeBlanc and M.A. Quilliam, Biomed. Environ. Mass., 19 (1990) 420. 102 P. Thibault, M.A. Quilliam, W.D. Jamieson and R.K. Boyd, Biomed. Environ. Mass Spectrom., 18 (1989) 373. 103 N. Pineiro, E. Vaquero, J.M. Leao, A. Gago-Martinez and J.A. Rodriguez-Vazquez, Chromatographia, 53 (2001) S231.
Phycotoxins
455
104 A. Furey, M. Lehane, M. Gillman, P. Ferna´ndez-Puente and K.J. James, J. Chromatogr., 938 (2001) 167. 105 P.T. Holland, P. McNabb, A.I. Selwood and T. Neil, J. AOAC Int., 86 (2003) 1095. 106 M. Murata, M. Kumagai, J.S. Lee and T. Yasumoto, Tetrahedron Lett., 28 (1987) 5869. 107 M. Daiguji, M. Satake, H. Ramstad, T. Aune, H. Naoki and T. Yasumoto, Nat. Toxins, 6 (1998) 235. 108 M. Satake, L. MacKenzie and T. Yasumoto, Nat. Toxins, 5 (1997) 164. 109 M. Satake, A. Tubaro, J.S. Lee and T. Yasumoto, Nat. Toxins, 5 (1997) 107. 110 H. Naoki, M. Murata and T. Yasumoto, Rapid Commun. Mass Spectrom., 7 (1993) 179. 111 P. Ciminiello, E. Fattorusso, M. Forino, R. Poletti and R. Viviani, Eur. J. Org. Chem., 3 (2000) 291. 112 C.O. Miles, A.L. Wilkins, D.J. Jensen, J.M. Cooney, M.A. Quilliam, J. Aasen and A.L. MacKenzie, Chem. Res. Toxicol., 17 (2004) 1414. 113 M. Satake, T. Ichimura, K. Sekiguchi, S. Yoshimatsu and Y. Oshima, Nat. Toxins, 7 (1999) 147. 114 R. Draisci, E. Ferreti, L. Palleschi, C. Marchiafava, R. Polleti, A. Milandri, A. Ceredi and M. Pompei, Toxicon, 37 (1999) 1187. 115 T. Yasumoto and A. Takizawa, Biosci. Biotechnol. Biochem., 61 (1997) 1775. 116 W.J. Fischer, I. Garthwaite, C.O. Miles, K.M. Ross, J.B. Aggen, A.R. Chamberlin, N.R. Towers and D.R. Dietrich, Environ. Sci. Technol., 35 (2001) 4849. 117 L.R. Briggs, C.O. Miles, J.M. Fitzgerald, K.M. Ross, I. Garthwaite and N. Towers, J. Agric. Food Chem., 52 (2004) 5836. 118 C. Afonso, A. Alfonso, M.J. Pazos, M.R. Vieytes, T. Yasumoto, A. Milandri, R. Poletti and L.M. Botana, Anal. Biochem., 363 (2007) 228. 119 S. Pierotti, C. Albano, A. Milandri, F. Callegari, R. Poletti and G.P. Rossini, Toxicon, 49 (2007) 36. 120 J.-S. Lee, K. Tangen, E. Dahl, P. Hovgaard and T. Yasmoto, Bull. Jpn Soc. Sci. Fish., 54 (1988) 1953. 121 T. Yasumoto, M. Murata, J.S. Lee and K. Torigoe, In: S. Natori, K. Hashimoto and Y. Ueno (Eds.), Mycotoxins and Phycotoxins ’88, Elsevier, Amsterdam, 1989, p. 375. 122 R. Draisci, L. Giannetti, L. Lucentini, E. Ferreti, L. Palleschi and C. Marchiafava, Rapid Commun. Mass Spectrom., 12 (1998) 1291. 123 M. Ferna´ndez Amandi, A. Furey, M. Lehane, H. Ramstad and K.J. James, J. Chromatogr., 976 (2002) 329. 124 I.R. Canas, B. Hamilton, M.F. Amandi, A. Furey and K.J. James, J.Chromatogr. A, 1056 (2004) 253. 125 D.G. Baden, Int. Rev. Cytol., 82 (1983) 99. 126 D.G. Baden, T.J. Mende and G. Bikhazi, Toxicon, 20 (1982) 929. 127 Y. Hua, W. Lu, M.S. Henry, R.H. Pierce and R.B. Cole, Anal. Chem., 67 (1995) 1815. 128 Y. Hua, W. Lu, M.S. Henry, R.H. Pierce and R.B. Cole, J. Chromatogr., 750 (1996) 115. 129 H. Ishida, N. Muramatsu, T. Kosuge and K. Tsuji, In: T. Yasumoto, Y. Oshima and Y. Fukuyo (Eds.), Harmful and Toxic Algae Blooms, Intergovernmental Oceanographic Commission of UNESCO, Paris, 1996, p. 491. 130 A. Morohashi, M. Satake, H. Naoki, H.F. Kaspar, Y. Oshima and T. Yasumoto, Nat. Toxins, 7 (1999) 45. 131 R. Dickey, E. Jester, R. Granade, D. Mowdy, C. Moncreiff, D. Rebarchik, M. Robl, S. Musser and M. Poli, Nat. Toxins, 7 (1999) 157–165. 132 R.L. Manger, L.S. Leja, S.Y. Lee, J.M. Hungerford and M. Wekell, Anal. Biochem., 214 (1993) 190. 133 R.L. Manger, L.S. Leja, S.Y. Lee, J.M. Hungerford and M. Wekell, In: F. Shahidi, Y. Jones and D.D. Kitts (Eds.), Seafood Saf. Process. Biotechnol. Technomic Publishing Company, Lancaster, PA, 1997, p. 11. 134 D.G. Baden, M. Kinoshita, E.Y. Lee and L. Hale, Mol. Appr. Food Saf, (1995) 209. 135 M.A. Poli, K.S. Rein and D.G. Baden, J. AOAC Int., 78 (1995) 538. 136 Y. Oshima, M. Hasegawa, T. Yasumoto, G. Hallegraeff and S. Blackburn, Toxicon, 25 (1987) 1105. 137 Y. Oshima, S.I. Blackburn and G.M. Hallegraeff, Mar. Biol., 116 (1993) 471. 138 R.W. Dickey, S.C. Bobzin, D.J. Faulkner, F.A. Benscath and D. Andrezejewski, Toxicon, 28 (1990) 371. 139 A. Tubaro, L. Sidari, R. Della Loggia and T. Yasumoto, In: B. Reguera, J. Blanco, M.L. Ferna´ndez and T. Wyatt (Eds.), Harmful Algae, Xunta de Galicia and Intergovernmental Oceanographic Commission of UNESCO, Vigo, 1998, p. 470.
456
Kevin J. James et al.
140 Y.Y. Lin, M. Risk, S.M. Ray, D.V. Engen, J. Clardy, J. Golik, J.C. James and K. Nakanishi, J. Am. Chem. Soc., 103 (1981) 6773. 141 L. Fritz, M.A. Quilliam and J.L.C. Wright, J. Phycol., 28 (1992) 439. 142 M. Satake, M. Murata and T. Yasumoto, Tetrahedron Lett., 34 (1993) 1975. 143 M. Usami, M. Satake, S. Ishida, Y. Inoue, Y. Kan and T. Yasumoto, J. Am. Chem. Soc., 117 (1995) 5389. 144 J.C. Marr, T. Hu, S. Pleasance, M.A. Quilliam and J.L.C. Wright, Toxicon, 30 (1992) 1621. 145 S. Pleasance, M.A. Quilliam and J.C. Marr, Rapid Commun. Mass Spectrom., 6 (1992) 121. 146 M.A. Quilliam, In: D. Barcelo (Ed.), Applications of LC-MS in Environmental Chemistry, Elsevier, Amsterdam, 1996, p. 415. 147 T. Suzuki, L. Mackenzie, D. Stirling and J. Adamson, Toxicon, 39 (2001) 505. 148 S. Ito and K. Tsukada, J. Chromatogr., 943 (2001) 39. 149 P. Vale and A.M. Sampayo, Toxicon, 40 (2002) 979. 150 L. MacKenzie, P. Holland, P. McNabb, V. Beuzenberg, A. Selwood and T. Suzuki, Toxicon, 40 (2002) 1321. 151 M.A. Quilliam, P. Hess and C. Dell’Aversano, In: W.J. De koe, R.A. Samson, H.P. Van Egmond, J. Gilbert and M. Sabino (Eds.), Mycotoxins and Phycotoxins in Perspective at the Turn of the Millennium, W. J. De Koe, Amsterdam, 2002, p. 385. 152 L.A. Stobo, J. Lacaze, A.C. Scott, S. Gallacher, E.A. Smith and M.A. Quilliam, J. AOAC Int., 88 (2005) 1371. 153 A. Vershinin, A. Moruchkov, S.L. Morton, T.A. Leighfield, M.A. Quilliam and J.S. Ramsdell, Harmful Algae, 5 (2006) 558. 154 P. Ciminiello, C. Dell’Aversano, E. Fattorusso, M. Forino, S. Magno, F. Santelia and M. Tsoukatou, Toxicon, 47 (2006) 174. 155 Y. Hua and R.B. Cole, Anal. Chem., 72 (2000) 376. 156 S.M. Plakas, K.R. El Said, E.L.E. Jester, H.R. Granade, S.M. Musser and R.W. Dickey, Toxicon, 40 (2002) 721. 157 A. Nozawa, K. Tsuji and H. Ishida, Toxicon, 42 (2003) 91. 158 Z. Wang, S.M. Plakas, K.R. El Said, E.L.E. Jester, H.R. Granade and R.W. Dickey, Toxicon, 43 (2004) 455. 159 H. Ishida, A. Nozawa, H. Nukaya and K. Tsuji, Toxicon, 43 (2004) 779. 160 H. Ishida, A. Nozawa, H. Nukaya, L. Rhodes, P. McNabb, P.T. Holland and K. Tsuji, Toxicon, 43 (2004) 701. 161 S.M. Plakas, Z. Wang, K.R. El Said, E.L.E. Jester, H.R. Granade, L. Flewelling, P. Scott and R.W. Dickey, Toxicon, 44 (2004) 677. 162 M.A. Poli, S.M. Musser, R.W. Dickey, P.P. Eilers and S. Hall, Toxicon, 38 (2000) 981. 163 W. Wang and R.B. Cole, J. Mass Spectrom., 41 (2006) 996.
CHAPT ER
14 Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls Marie-Louise Scippo, Gauthier Eppe, Claude Saegerman, Georges Scholl, Edwin De Pauw, Guy Maghuin-Rogister and Jean-Franc- ois Focant
Contents
1. Introduction 2. Physical and Chemical Properties and Use of POPs 3. Health Effects 3.1 Effects on reproduction 3.2 Carcinogenicity 3.3 Other effects 3.4 Mode of action of dioxins and toxicity equivalence 4. Analytical Methods 4.1 Extraction 4.2 Clean-up 4.3 Determination by gas chromatography (GC) 4.4 Determination by biological techniques 5. Occurrence in Food 6. Future Trends References
457 460 462 462 462 463 463 467 467 468 469 489 495 496 498
1. INTRODUCTION Persistent organochlorine pollutants (POPs) are chemical substances that have long half-lives in air, soil, sediments or biota and thus persist in the environment. Because of their high lipophilicity, they can contaminate all levels of the food chain and bioaccumulate up to higher trophic levels. They undergo long-range transport and are found in remote places such as the Artic. They are toxic and cause adverse health effects to human and wild life. Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00014-7
r 2008 Elsevier B.V. All rights reserved.
457
458
Marie-Louise Scippo et al.
The POP group includes 12 substances (the dirty dozen). Among the chemical compounds that have been identified as POPs, nine are agrochemicals (aldrin, chlordane, 2,2-bis(4-chlorophenyl)-1,1,1-trichloroethane (DDT), dieldrin, endrin, heptachlor, hexachlorobenzene (HCB), mirex and toxaphene), and three are industrial substances (polychlorinated biphenyls (PCBs), polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs)) (Table 1) [1,2]. From the latter group, PCDD/PCDFs have never been produced deliberatively but are released as accidental by-products from combustion processes or industrial synthesis of other chlorinated chemicals. Although neither dioxins nor furans have ever had any commercial applications, PCBs have been heavily synthesized since 1930 (global estimated production of 106 t [1]) for a variety of industrial uses, such as dielectrics in transformers and capacitors, heat exchange fluids, paint additives and in plastics [3]. PCBs, which were supposed to be confined in industrial settings can however, like dioxins and furans, be virtually found in all global ecosystems [4]. The international community is taking action to reduce the background POP contamination level. For example, the UN-ECE (Convention on Long-Range Transboundary Air Pollution of the United Nations-Economic Commission for Europe) protocol on POPs, [5,6] and the Stockholm POP convention [7,8] entered in force, in October 2003 and May 2004, respectively. Both texts focus on the prohibition or restriction of production, restriction on export and import, handling of existing stocks, safe disposal of wastes and reduction of emissions for unintentionally produced POPs. The European Union has adopted both the UN-ECE protocol and the Stockholm convention in its Council Regulation (EC) No 850/2004 [9]. As the top predators, humans are exposed to significant levels of POPs because of biomagnification. Human exposure to POPs can be estimated by biomonitoring of blood, milk and other (adipose) tissues. The primary matrix used for biomonitoring of persistent toxicants is blood. Blood sampling is still an invasive procedure, but less invasive than adipose tissue collection, which requires surgery. Breast milk is also valuable because it is relatively easily collected and not only represents a biomonitoring matrix, but is also a source of nutrition for a segment of the population [10]. Because only a part of the population can be sampled, and due to the depuration rates that have to be taken into account while breast-feeding is taking place, human milk analysis is usually restricted to infant exposure studies rather than general population studies. Lots of biomonitoring data are available for POPs till date. They all point out a general decrease of the human body burden for the listed POPs. Exposure to other emerging persistent contaminants, such as brominated flame retardants, is increasing but is out of the scope of the present chapter [11,12]. Except for particular occupational exposures (e.g., people working in a pesticide plants), the consumption of food of animal origin is the principal source of human exposure to POPs [13–20]. It is well-recognized that foodstuffs from animal origin account for more than 90% of the human exposition, with meats, eggs, dairy and fish products as the main contributors [21–25]. The proportion of the exposure for background subjects from inhalation or direct contact with dioxins in the environment is estimated to be no more than a few percent [26].
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
Table 1
Structure of the 12 POPs of the Stockholm convention [7,8]
Name of the POP
Structure
Use
Aldrin
Insecticide
Chlordane
Insecticide
Chlordecone
Insecticide
DDT
Insecticide
Dieldrin
Insecticide
Endrin
Insecticide
Heptachlor
Insecticide
459
460
Marie-Louise Scippo et al.
Table 1 (Continued ) Name of the POP
Structure
Use
Hexachlorobenzene
Fungicide, byproduct of industrial process
Mirex
Insecticide
Toxaphene
Insecticide
PCB
3
2
4
Clw 5 PCDD
2' 1 1'
6
1 2
4'
6' 5' Clz
O
9 8
3 4
Clx PCDF
O
1
7 Cly
6 9
2
8
3 Clx
Industrial uses
3'
4
O
7 6
By-product of industrial or natural process
By-product of industrial or natural process
Cly
Consequently, in an attempt to maintain the declining exposure trend, a careful monitoring of our foodstuffs is mandatory. International regulation offices have therefore defined control levels to facilitate the screening and the decision concerning the consumability of foodstuffs. This chapter discusses some of the aspects of the analysis and occurrence of POPs in food of animal origin, with emphasis on PCBs and dioxins.
2. PHYSICAL AND CHEMICAL PROPERTIES AND USE OF POPS POPs are highly stable organic compounds, resistant to thermal degradation and biological metabolism. They are all chlorinated compounds, the higher the
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
461
chlorination level, the better it resists degradation [27]. POPs are virtually nonsoluble in water, their high Kow values allow them to penetrate the phospholipidic membrane of cells and accumulate in fat tissue of living organisms. POPs have long half-lives (e.g., 10–12 years in soil for dioxin or endrin). They are semivolatile, so that they are subject to long-range transport by atmospheric currents. The nine organochlorine pesticides (OCPs) were introduced from 1920 to 1950 mainly for agricultural use. By 1990, the production and use of these substances were banned in western countries due to their human toxicity. Some of them are still in use as intermediates for other chemical synthesis or in developing countries against malaria [28,29]. For aldrin and DTT, metabolites (dieldrin and DDE, respectively) can be more persistent than the original compound [30]. PCDDs and PCDFs are two groups of planar tricyclic compounds that have similar chemical structures and properties. Dioxins are made of two six carbon atom aromatic rings connected together by two bridging oxygen atoms, whereas only one oxygen atom ensures the connection for furans. PCBs can be defined as bicyclic compounds since the two aromatic rings are connected together with no intervention of oxygen atoms (Table 1). Numbers on aromatic rings represent potential positions for chlorine atoms, these being in maximum 8 (0 p x,y p 4) in case of PCDDs and PCDFs and 10 (0 p w,z p 5) for PCBs. All together, dioxins (75), furans (135) and PCBs (209) represent 419 molecules (congeners), depending on the number and position of chlorine atoms on aromatic rings. In the case of PCBs, the planarity of molecules depends on the chlorine substitution pattern. If no chlorine atoms are present in positions 2,6,2u,6u (ortho positions), the molecule adopts a planar geometry, similar to the one observed for dioxins and furans. Once chlorine atoms start to be connected in ortho positions, steric hindrance drives the molecule to evolve to a non-planar configuration. These substitutional and geometrical parameters are of prime interest since they are closely related to the toxicity of these compounds. They are only very slightly volatile, sparingly soluble in non-polar solvents and almost insoluble in water. They are also persistent in environment and prevalent in biota due to extreme stability in environment (t1/2 environment ¼ 10–12 years) and due to bioavailability–bioaccumulation (mainly 2,3,7,8-substituted congeners) in humans (t1/2 human ¼ 5–10 years in adults) [32]. Their dispersion in the atmosphere is likely to occur mainly in particulate aerosols [33]. PCDDs and PCDFs are not produced intentionally but occur frequently as unwanted by-products in chemical processes, such as the synthesis of pesticides or PCBs [34]. Combustion processes are recognized as the major sources of PCDDs and PCDFs. Most thermal reactions, which involve the burning of chlorinated organic or inorganic compounds, appear to result in the formation of these substances. PCDDs and PCDFs have been detected in emissions from the incineration of various types of wastes, particularly municipal, medical and hazardous wastes, from the production of iron and steel and other metals, from fossil fuel plants, domestic coal and wood fires, especially those involving chlorine-containing materials, such as polyvinyl chloride (PVC) and PCBs [35]. Dioxins released into the environment many years ago continue to contribute to contemporary exposure [36].
462
Marie-Louise Scippo et al.
Individual PCB congeners are often crystalline but commercial mixtures exist as viscous liquids or resins. They have low chemical reactivity and rather high density. They have low electrical resistance, which, in combination with their heat stability, makes them very suitable as cooling liquids in electrical equipment [37]. They were produced between 1930 and 1970 and commercialized in relative large quantities for use as dielectrics, hydraulic fluids, plastic and paint additives [38]. The universal distribution of PCBs throughout the world suggests that PCBs undergo long-range transport by air [39].
3. HEALTH EFFECTS Numerous adverse health effects are attributed to POPs. OCPs are suspected to act as endocrine disruptors, causing perturbations at the reproductive stage [40–44], but this is still controversial and not formally demonstrated [45–47]. Various effects have been reported in animals exposed to PCDDs, PCDFs and PCBs [48]. Many of the toxic effects of dioxins were high dose effects [49,50]. The most commonly reported pathologies are endometriosis, immunotoxic effects, cancer, birth defects, effects on the reproductive and the neuro-endocrineimmune systems, altered metabolism and specific organ dysfunction [35,51–56].
3.1 Effects on reproduction Evidence of POPs effects on reproduction comes from wild life, with numerous examples of accidental (or not) contamination having caused perturbation of the reproductive system of the fauna (e.g., the accidental contamination of the lake Apopka in Florida with DDT, where alligators display altered reproductive functions [57], development and reproductive defects in fish-eating birds [58], other examples are reviewed in Ref. [59]). Effects on human male reproduction have been described for some POPs, such as PCBs and DTT (the latter acts through its active metabolite 1,1-dichloro-2,2-bis (p-chlorophenyl)-ethylene or p,pu-DDE) [60–62]. These substances alter sperm motility [63–65] or sperm chromatin integrity [66,67], but seem to have no effect on sperm concentration [68]. They also may be the cause of an increased time to pregnancy [69]. OCPs act as endocrine disruptors by interfering with the estrogen or the androgen receptor or by disturbing the hormonal function (reviewed in Ref. [70]).
3.2 Carcinogenicity First classified as probably carcinogen for humans (class B2) by the US EPA in 1987 [71], aldrin and dieldrin were then described as ‘‘not likely human carcinogen’’ [72,73], since reported epidemiologic studies showed no correlation between pesticide exposure and cancer [74,75]. POPs and PCBs contamination of the environment is suspected to be the cause of the increasing incidence of breast cancer in European countries [76]. DDT is classified by International Agency for Research on Cancer (IARC) as possibly carcinogenic to humans (group 2B) [30].
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
463
Dioxins are carcinogenic in several animal species [77] and humans, and increased risk of cancer has been demonstrated at exposure levels more than 100 times the normal intake of the general population [78]. Dioxins are classified as human carcinogenic by the IARC [79–81] and either ‘‘carcinogenic to humans’’ or ‘‘likely to be a human carcinogen’’ by EPA [35]. This is consistent with the observations of Bertazzi et al. [82,83], showing an increase of rectal and lung cancer cases, 20 years after the 1976 Seveso accident. However, there is no consensus in the scientific community on the carcinogenicity of tetrachlorodibenzo-p-dioxion (TCDD), controversial for some [84] and confirmed for others [80].
3.3 Other effects TCDD is known to cause chloracne [82,85–87] and POPs, in general, are suspected to cause diabetes in humans [88,89]. More particularly, TCDD could be one of the multiple factors causing atherosclerosis, hypertension, vascular ocular changes and signs of neural system damage [90].
3.4 Mode of action of dioxins and toxicity equivalence Toxicological properties of dioxins, furans and PCBs are directly related to their chemical structure (number and position of chlorine atoms) [91]. Over the 419 possible congeners that can theoretically be released in the environment, 17 congeners substituted in position 2,3,7,8 (seven PCDDs and ten PCDFs) as well as 12 ‘‘dioxin-like’’ PCBs (Table 1) present such a sterical conformation that they can efficiently bind to an intracellular receptor, with which a stable complex can be formed [92]. This dioxin-specific receptor is called arylhydrocarbon receptor (AhR) [93,94]. Briefly, once the dioxin–AhR complex is formed, it can enter the nucleus, bind to another regulatory protein (AhR nuclear translocator, Arnt), access the genetic material of the cell and activate the transcription of target genes such as a cytochrome P450 detoxifying enzyme, the CYP1A1, via binding to a specific sequence of the DNA referred as the Dioxin Responsive Element (DRE) (Figure 1) [95–97]. As the dioxin molecules are very stable in the cell and not metabolized, AhR is abnormally maintained under its activated form, with adverse effects on physiologic functions [55,97–101]. The involvement of AhR in many cellular- and tissue-specific functions could explain most effects of dioxins, such as chloracne, teratogenic effect (e.g., cleft palate), immunosuppression, carcinogenesis [101] and/or oxidative stress [102]. Structure–activity requirements based on AhR binding characteristics can be used to predict the relative potencies (REP) of different agonists for producing toxic effects [103]. In other words, toxic potency of congeners correlates with their ability to bind the AhR. It appears that the lateral 2,3,7,8 position of the dioxin molecule has to be fully chlorinated to induce toxicity. Removal of any of these substituents or moving them to an apical (1,4,6 or 9) position dramatically decreases the toxicity [104]. Among dioxins, 2,3,7,8-TCDD has the greatest
464
Marie-Louise Scippo et al.
Cytoplasm
Dioxin
Nucleus
Hsp 90 AhR
Arnt
TGCGTG
DNA
DRE
Figure 1 Simplified mechanism of action of dioxins.
affinity for binding to the AhR and is often described as the most potent animal teratogen [105,106]. The concept of toxic equivalence factors (TEFs) has been established for evaluating congeners other than TCDD (the most toxic, with a TEF of 1) and mixtures of dioxins [107,108]. TEFs values (called I-TEFs) for humans were first proposed by NATO for 10 dioxin and 7 furan congeners [109], then, 12 dioxin-like PCBs congeners were added. TEFs were re-evaluated by the WHO in 1998 [108] and in 2006 [110]. During the first re-evaluation, the TEF for PCDD was increased from 0.5 to 1, while during the second re-evaluation, dioxin-like PCBs TEFs were decreased (Table 2, columns 2–5). These TEFs are used to calculate toxic equivalent (TEQ) content of feed and food samples, assuming that the effect of the 29 targeted congeners are additive. This facilitates risk assessment and regulatory control of exposure to these mixtures [111]. In practice, when an analytically measured congener concentration is multiplied by its TEF, it is converted into TEQs, which indicate how much 2,3,7,8-TCDD would be needed to produce the same toxic effect as the dose in question [112]. The global toxicity for a sample containing several different congeners can be obtained using the formula depicted in the following equation: TEQ ¼
X X X ðPCBi TEFi Þ ðPCDDFi TEFi Þ þ ðPCDDi TEFi Þ þ n1
n2
n3
Using the available toxicological database on dioxins in 1998, the WHO established a tolerable daily intake (TDI) in humans between 1 and 4 pg TEQ/kg bw/day [113]. This TDI is based on the range of lowest observed adverse effect level (LOAEL) for the most sensitive experimental animals and could be transformed into a range of estimated long-term human daily intake (EDI) of 14–37 pg TCDD/kg bw/day when applying an uncertainty factor of 10 [53].
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
465
Table 2 List of 29 congeners of dioxins, furans and dioxin-like PCBs to which a TEF has been assigned. I-TEFs, 1988 [109]; WHO-TEFs, 1998 [108]; WHO-TEFs, 2005 [110]; DR-CALUX REP, relative potencies measured with the DR-CALUX assay [215] I-TEFs (1988)
WHO TEFs (1998)
WHO TEFs (2005)
DR-CALUX REP
Dioxins 2,3,7,8-TCDD 1,2,3,7,8-PeCDD 1,2,3,4,7,8-HxCDD 1,2,3,7,8,9-HxCDD 1,2,3,6,7,8-HxCDD 1,2,3,4,6,7,8-HpCDD OCDD
1 0.5 0.1 0.1 0.1 0.01 0.001
1 1 0.1 0.1 0.1 0.01 0.0001
1 1 0.1 0.1 0.1 0.01 0.0003
1 0.5 0.1 0.06 0.06 0.03 0.0005
Furans 2,3,7,8-TCDF 2,3,4,7,8-PeCDF 1,2,3,7,8-PeCDF 1,2,3,4,7,8-HxCDF 1,2,3,7,8,9-HxCDF 1,2,3,6,7,8-HxCDF 2,3,4,6,7,8-HxCDF 1,2,3,4,6,7,8-HpCDF 1,2,3,4,7,8,9-HpCDF OCDF
0.1 0.5 0.05 0.1 0.1 0.1 0.1 0.01 0.01 0.001
0.1 0.5 0.05 0.1 0.1 0.1 0.1 0.01 0.01 0.0001
0.1 0.3 0.03 0.1 0.1 0.1 0.1 0.01 0.01 0.0003
0.4 0.4 0.1 0.07 0.08 0.1 0.1 0.01 0.04 0.004
Coplanar or non-ortho substituted PCBs 3,4,4u,5-TrCB (PCB 81) – 3,3u,4,4u-TrCB (PCB 77) – 3,3u,4,4u,5-PeCB (PCB 126) – 3,3u,4,4u,5,5u-HxCB (PCB 169) –
0.0001 0.0001 0.1 0.01
0.0003 0.0001 0.1 0.03
0.002 0.0004 0.04 0.0008
Mono-ortho substituted PCBs 2,3,3u,4,4u-PeCB (PCB 105) 2,3,4,4u,5-PeCB (PCB 114) 2,3u,4,4u,5-PeCB (PCB 118) 2u,3,4,4u,5-PeCB (PCB 123) 2,3,3u,4,4u,5-HxCB (PCB 156) 2,3,3u,4,4u,5u-HxCB (PCB 157) 2,3u,4,4u,5,5u-HxCB (PCB 167) 2,3,3u,4,4u,5,5u-HpCB (PCB 189)
0.0001 0.0005 0.0001 0.0001 0.0005 0.0005 0.00001 0.0001
0.00003 0.00003 0.00003 0.00003 0.00003 0.00003 0.00003 0.00003
NR 0.00002 NR NR 0.00002 NR NR NR
Congener
Note: NR: no response observed.
– – – – – – – –
466
Marie-Louise Scippo et al.
The upper limit of the TDI should be considered as the maximum tolerable intake on a provisional basis with the ultimate goal to reduce human intake levels below 1 pg TEQ/kg bw/day. More recently a tolerable weekly intake (TWI) of 14 pg/kg bw/week [49] and a tolerable monthly intake (TMI) of 70 pg/kg bw/month [50,107] were also determined respectively to reflect the long half-life of TCDD. The above three methodologies assume a threshold for human cancer risks. Another recent international evaluation based on a non-threshold effect [114,115] estimates the lifetime risk for all cancers to be 1 103 risk/pg TEQ/kg bw/day. According to the TWI of 14 pg WHO-TEQ/kg bw/week, maximum tolerable concentrations have been fixed in feed and food in Europe [116] (Table 3). With the aim to reduce the dioxin contamination of feed and food, Europe has proposed alert levels [117] at which it is recommended to member states to investigate to find and eliminate the source of the contamination. These actions
Table 3 Maximum levels [116] and action thresholds [117] for dioxins, furans and dioxin-like PCBs, for some food matrices Maximum levels (pg WHOTEQ/g fat or product)
Action threshold (pg WHO-TEQ/g fat or product)
Sum of dioxins and furans
Sum of dioxins, furans and dioxinlike PCBs
Sum of dioxins and furans
Dioxinlike PCBs
3
4.5
1.5
1
2 1
4 1.5
1.5 0.6
1.5 0.5
Milk and milk products, including butter fat, hen eggs and egg products
3
6
2
2
Marine oil (fish body oil, fish liver oil and oils of other marine organisms intended for human consumption)
2
10
1.5
6
Mixed animal fats
2
3
1.5
0.75
Muscle meat of fish and fishery products and products thereof with the exception of eel
4
8
3
3
Meat, meat products and fat Ruminants (bovine animals and sheep) Poultry and farmed game Pigs
pg WHO-TEQ/g product.
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
467
would be helpful to decrease the background contamination of feed and food, and Europe would like to propose lower maximum tolerable levels by 31 December 2008.
4. ANALYTICAL METHODS PCDDs, PCDFs and dioxin-like PCBs are found at levels as low as pico- or femtogram per gram of matrix depending on the investigated food sample. In addition, matrix-related interferences are present in concentrations at orders of magnitude higher than the analytes of interest. For those reasons, a complex multi-step approach is required to (1) extract the analytes from the matrix core, (2) separate undesirable interferences and (3) finally isolate, separate and quantify analytes of interest. In terms of cost per sample and sample throughput, it is not only the final measurement of the analyte concentration, but — maybe even more importantly — the complex sample preparation procedure, which makes this measurement possible. For PCBs, a minimum number of seven essential PCBs (IUPAC number 28, 52, 101, 118, 138, 153, 180) are screened for the monitoring of food, fish and environmental samples. They are found at higher levels compared to dioxins (i.e., low nanogram to microgram per gram of matrix depending on the investigated biological sample). For this reason, the analytical methodologies are less complex. Several review papers on analytical methodologies for OCPs and PCBs are available in the literature. Keith [118] summarized US EPA methods for PCBs and OCP in sediment and biological materials. Wells and Hess [119,120] reviewed and recommended methods for the separation, isolation and recovery of OCPs and PCBs from soils, sediment and biological matrices. De Boer and Law [121] provided a useful overview of current analytical methodology for OCPs and PCBs. More recently, Muir and Sverko [122] outlined analytical methods to measure PCBs and OCPs in environmental and biological samples.
4.1 Extraction The extraction device presented by Professor von Soxhlet in 1879, which re-circulates the extraction solvent while accumulating extracted analytes in a heated flask, is still used in the dioxin field and is often considered as the reference extraction method, at least for solid samples, such as soils, sediments and fly ashes [123,124]. For liquid samples, liquid–liquid extraction (LLE) has been used for a long time, mainly for biological fluids [125,126]. Although easy to set up, several critical drawbacks such as phase emulsions, required quantities of solvent and intensive handling make it unappealing to use. Extractions of biological tissues using supercritical fluid extraction (SFE) have also been reported using supercritical CO2 [127]. During an extraction cycle, static (fluid immobilized with the sample in the closed vessel) and dynamic (percolation of the fluid through the cell) modes can be used together to ensure both penetration of the matrix by the fluid and to avoid saturation of the fluid
468
Marie-Louise Scippo et al.
[128]. Co-extracted lipids may be eliminated in part by directly adding adsorbents inside the cell [129–132]. SFE may be coupled with various analytical methods like gas chromatography (GC) but very fine-tuning is then required [133,134]. Since first reports on the use of domestic microwave ovens to carry out extraction of organic compounds, microwave-assisted extraction (MASE) has been applied to OCPs and PCBs present in solid matrices [135–137]. Selected extraction solvents usually have high dielectric constant to absorb the microwave energy efficiently. In pressurized liquid extraction (PLE), also named PFE (pressurized fluid extraction), organic solvents are used in the liquid phase at temperatures above their boiling point. The stainless steel extraction cell can generally be heated up to 2001C and pressurized up to 3,000 psi. A minimum extraction time of 10 min is usually required to ensure efficient transfer of analytes out of the sample matrix [138]. For extraction from high-fat content biological samples, quantitative recovery rates can be obtained using classical organic solvents but hexane is usually preferred to solvent mixtures because less matrix-related interferences are co-extracted under mild temperature conditions [139]. Drying of the sample can be carried out using lyophilization prior to extraction. This reduces the risk of extracting traces of water, which may lead to over estimation of the lipid content of the sample. The pre-lyophilization freezing process can be accelerated by cryohomogenization of the samples using liquid nitrogen [140]. The dry material can then be easily homogenized before extraction. Among potential alternative techniques, solid phase extraction (SPE) constitutes the alternative of choice for extraction of dioxins from liquid samples. Bonded-silicas [141,142] and styrene-divinyl benzene synthetic polymer [143,144] are well suited for isolating groups of compounds from sample matrix components. The use of vacuum manifold and automated SPE workstation easily regulates flow rates through the cartridges. In the case of dioxins and related compounds, the use of C18 cartridges has been reported for water, serum and milk [145–151]. Good recovery was achieved when fat globules were efficiently disrupted in order to release the pollutants from the lipoproteins. It has successfully been applied in the dioxin field by different laboratories [152,153]. Solid phase dispersion on diatomaceous earth can also be used in SPE cartridge format. This is a valuable SPE method for the extraction of milk samples without the inconvenience of losing part of the lipids during the extraction step. Lipids are therefore quantitatively extracted from the milk matrix and isolated for gravimetric determination prior to further clean-up.
4.2 Clean-up Highly efficient clean-up procedures are required to purify samples issued from the extraction step prior to the final analysis and quantification. Classical solid– liquid adsorption chromatographic separations based on sorbents, such as silica, alumina and Florisil, have long been regarded as important in the field [154]. For biological samples, sulfuric acid silica or gel permeation chromatography (GPC) columns are used to remove the bulk of the lipids and other oxidizable
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
469
components. Basic alumina columns are then used to separate dioxins from pesticides and PCBs [155]. Activated carbon sorbent can join the column set as a complementary fractionation tool to alumina [156–158]. Due to its affinity for certain planar aromatic systems, especially those with adjacent aromatic rings and electronegative substituents, carbon-based sorbent can fractionate the planar dioxins, furans and PCBs from other classes of aromatic compounds, improving sample clean-up. The multi-sorbent clean-up procedure can be automated. The fractionation procedure can be tuned to allow the collection of different fractions [159]. To accommodate foodstuffs analysis, generally characterized by low levels of POPs and high lipid content, high capacity disposable silica columns have been developed to accommodate 4–5 g of lipids on-column [140]. Coupling the extraction and clean-up steps can further be done to reduce sample and extracts handling [160]. Recent reports proposed on-line PLE and clean-up for PCB analysis in solid food and feedingstuffs by directly adding sorbents such as acidic silica and activated carbon inside the extraction cell [161,162]. Another approach for the sample preparation of solid samples is the use of a modified version of the automated clean-up system described earlier. Either an SPE or a PLE system is directly connected to the clean-up instrument and the resulting integrated system is fully automated [160]. This system was studied for the on-line extraction and clean-up of different foodstuff types.
4.3 Determination by gas chromatography (GC) Once extracted and purified from matrix interferences, the chromatographic separation of the target compounds has to take place before analysis. Due to the semi-volatility of dioxins and related compounds, GC is used to separate the different congeners and to allow non-ambiguous identifications.
4.3.1 Injection This paragraph summarizes different injection techniques that have been reported for POPs analysis. Splitless injection is the most frequently used technique for detecting ultra-traces of dioxins, PCBs and OCPs [163]. It is a robust and reliable injection technique. Generally, a volume of maximum 2 mL is injected into a hot injector left at a temperature between 2501C and 3001C. On-column injection may be used as an alternative for OCPs [164] in particular for DDT that is easily degraded in hot injector above 1501C. Large-volume injectors (LVI) are becoming more popular taken into account that the low concentrations of dioxins and furans occur in biological materials required a high sensitive technique. There are three ways of injecting large volume onto the GC column: on-column injection, loop-type injection and Programmable Temperature Vaporizer (PTV) injection. On-column LVI is a less successful way of injection for dioxins compared to PTV injector [165–167], particularly because of the strong influence of solvent-impurities in the chromatogram and contamination of the column and detector. These techniques enable injection of volume as large as 100–200 mL, but most dioxin
470
Marie-Louise Scippo et al.
applications by PTV injection use 5–30 mL. The main drawback of PTV is the number of parameters to optimize compared to simple split/splitless technique.
4.3.2 GC Separation techniques 4.3.2.1 Classical gas chromatography (GC). Capillary high-resolution GC (HRGC) columns ensure the required selectivity, especially for congeners of the same chlorination level. The separation characteristics and elution profiles on GC columns have been studied. Ryan et al. [168] published a comprehensive study on separation characteristics and elution profiles of different GC columns. An appropriate combination of column length, internal diameter and stationary phase polarity is needed. For the analysis of biological samples, non-polar GC columns are usually used. They allow separation between homologue groups and can separate 2,3,7,8-substituted congeners from each other [169], showing the efficiency of a non-polar (methyl polysiloxane with 5% phenyl) column to separate the 2,3,7,8 toxic congeners from the rest, especially for 2,3,7, 8-tetrachlorodibenzofuran (TCDF). The apolar GC column is the most widely used column for 2,3,7,8-PCDD/Fs and non-ortho PCBs analysis in foodstuffs, feedingstuffs and human samples. Usually 40–60 m columns with 0.18–0.25 mm internal diameter and 0.15–0.25 mm film thickness are selected. With polar phase (cyanopropyl stationary phases), the resolving power specially improves for the separation of the 22 TCDD congeners, but separation of 2,3,7,8-TCDF and 1,2,3,7,8-PeCDF still remains incomplete [170]. This column is used for environmental matrices (e.g., fly ash, air, soils, sediments and biota) characterized by the presence of many PCDD/Fs congeners. The major drawback of the polar column is the non-linked phase and its low stability at elevated temperature (withstand temperature up to 2751C), which tends to produce significant bleed. For PCB fractions, the 8% phenyl polycarborane-siloxane is often used. The carborane group has a high affinity for PCBs with a low degree of ortho-substitution. Although this phase does not allow the separation of all the 209 PCB congeners, it separates some critical pairs of co-elutions present with other phases [171]. For example, indicator trichlorinated PCB-28 and PCB-31 (not followed), pentachlorinated mono-ortho PCB-123 and PCB-118, as well as hexachlorinated PCB-163 (not followed) and the indicator hexachlorinated PCB-138 are separated. A 25 m 0.25 mm 0.2 mm HT-8 seems to be a good compromise between the required resolving power and the GC run time of roughly 30 min. It should be mentioned that till date, none of the existing stationary phases is capable of the separation of all the PCB congeners. Even emerging hyphenated methods such as comprehensive two-dimensional GC (GC GC) coupled to time-of-flight mass spectrometry (TOF-MS) can at the most separate 192 congeners [172].
4.3.2.2 Comprehensive Two-dimensional Gas Chromatography (GC GC). GC GC has been developed to meet an increasing need for complex sample analysis and to address limitations, such as peak capacity, dynamic range and restricted specificity of mono-dimensional (classical) GC systems (i.e., to improve the global efficiency of
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
471
the separation). It is a chromatographic technique where the entirety of a sample is subjected to two orthogonal separation processes. This is the case when two independent separation mechanisms are used (orthogonality rule), and when the separation obtained in the first dimension is maintained in the second dimension (conservation rule) [173]. This technique is based on the fast sampling and transfer of the sample by a cryogenic modulator located between the first dimension (1D) column and the second dimension (2D) column connected in series. The entire 1D chromatogram is continuously sampled following a modulation period (PM) of a few seconds and sent into 2D for a fast GC-type separation (Figure 2A). Because modulation occurs during the 1D separation, the total GC run time of a GC GC separation is the same as in classical GC. As in classical GC, a trace is monitored continuously at the detector located at the end of 2D. In reality, series of high-speed secondary chromatograms of a length equal to PM (3–10 s) are recorded one after another (Figure 2B). They can be computerized by specific software and combined to describe the multi-dimensional elution pattern by means of contour plots in the chromatographic separation space (Figure 2C). In GC GC the peak capacity (the maximum number of peaks that can be placed next to each other in the available chromatographic separation space at a given resolution) is equal to the product of the peak capacities of the two coupled systems making GC GC well suited to accommodate complex mixtures of compounds. Compared to classical GC, the analytical speed (number of compounds separated per unit of time) is greatly enhanced. GC GC also improves specificity (2 retention times (tR)), selectivity (phase combination) and sensitivity (peak compression resulting in signal enhancement because of mass conservation) [175,176].
4.3.3 Gas chromatography and mass spectrometry (GC-MS) It was clear over 30 years ago that GC-MS was the instrumental method of choice for POP determinations and specially for PCDD-Fs. MS provides not only a very specific quantification but also ensures the unambiguous identification of target compounds. However, not all GC/MS can measure dioxins. As already mentioned, the complexity to measure these compounds is also related to the low levels at which they occur in environmental matrices but particularly in food and feed samples (parts-per-quadrillion: 1015 g 2,3,7,8-TCDD/g of sample to parts-per-billion levels: 109 g 2,3,7,8-TCDD/g of sample). The required sensitivity is achieved by a combination of high-resolution and high-mass accuracy using double focusing magnetic sector instruments called high resolution mass spectrometer (HRMS). In the past few years, other MS-based detection techniques have been investigated as alternative to GC-HRMS for dioxins and related compounds, such as GC-ion trap in MS/MS mode, GC GCTOF-MS and GC GC-HRMS.
4.3.3.1 The reference GC-HRMS method. The GC-HRMS method has been recently reviewed by Eppe et al. [177] and Reiner et al. [178].
Marie-Louise Scippo et al.
Injector
Detector (A)
Modulator
1
2D
D
0
PM
1
2 3 4
X
5
Y X+Y
6 7 8 2t X R
1t R 2t
2t 2t
RX
2t
2t
RY
1
RY
2t RY
RY 2t
RX
2t Y R
RX
2t
RX 2t X R 2t
Intensity
472
2t
2t X R
3
2
(B) RY
4
5
6
RY
7
1
tR ,2tR
PM Intensity X
Y 7
1
(C) 6
tR
5
4
3
2
1 2t
X
Y
1
t Y
1
tR
R
1
tRX 2
2
tRX
tRY
2t R
R
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
473
The extreme sensitivity of HRMS instrument is gained by the ability to monitor specific characteristic ions in the mass spectrum of the target compound. It is called the selected ion monitoring (SIM) mode. By this scan mode, a few femtograms of 2,3,7,8-TCDD injected in GC-HRMS can be detected. These performances are unmatched by any other techniques and it makes GC-HMRS the reference or the ‘‘gold standard’’ method for dioxins. Even after an extensive clean up and a high resolution chromatographic separation, the risk of interferences is still high. For that reason, the resolution R (R ¼ M/LM) of the mass spectrometer should be set at least at 10,000 (10% valley definition). This allows mass discrimination at the 0.03–0.05 mass unit (Da) level in the tetra- to octa-substituted congeners mass range. The number of ions, which can be measured at any one time, is generally limited because at least ten sampling points for each GC peak are needed in order to get a Gaussian peak for accurate integration and quantification. Selected ions are therefore grouped in various segments. In addition, to control the mass accuracy, a lock mass is measured in each cycle and a lock mass check is often included (e.g., perfluorokerosene, PFK). The lock mass is ideally located within the measured mass range. As mentioned, within each segment, the number of compounds (i.e., the number of specific ions) is limited. A quantification mass (the most abundant peak from the ions cluster) and a confirmatory mass (based on relative isotopic ratio of naturally occurring chlorinated isotopes) are required for native as well as for internal standard (Table 4). Thus, four masses are needed for one target congener. A maximum of three to four compounds can therefore be measured. In order to overcome this limitation, the chromatogram is sliced in time windows by grouping target compounds based on their retention time. The chromatographic challenge is then to bring the compound by groups (chromatographic windows) with no overlap, which would result in loss of congener measurement. Hence, one of the major drawbacks of SIM mode is the necessity to redefine windows any time the chromatographic parameters are modified (i.e., cutting or changing the column). The presence of congeners affected by different TEFs leads to severe requirements for isomeric separation, which is relied on HRGC. The retention time of native and labeled standard peaks must be within a range of 2 s. To control the chlorination level and therefore the identity and the absence of interfering compounds, the measurement of the isotopic composition of the two most intense ions of both native and 13C-labeled ion clusters must be 715% Figure 2 Scheme of the column coupling in the GC GC setup and how data are handled (not to scale). (A) The modulator allows rapid sampling of the analytes eluting out of 1D and reinjection in 2D. The modulation process is illustrated for two overlapping compounds (X and Y) coming out of 1D at a defined first-dimension retention time (1tR). As the modulation process occurs during a defined modulation period (PM), narrow bands of sampled analytes are entering 2D and appear to have different second-dimension retention times (2tRX and 2tRY). (B) Raw data signal as recorded by the detector through the entire separation process. (C) Construction of the two-dimensional contour plot from the collected high-speed secondary chromatograms of (B), in which similar signal intensities are connected by contour lines. Reproduced from Ref. [174].
TCB 20–26 TCB13C12 Lock mass TCDF 26–30 TCDF 13C12 TCDD TCDD 13C12 TCDD 13Ca6 PeCB PeCB 13C12 Lock mass PeCDF 30–35 PeCDF 13C12 PeCDD PeCDD 13C12 HxCB
Window (min)
291.9194 303.9597 316.9824 305.8987 317.9389 321.8936 333.9339 331.9078 325.8804 337.9207 330.9792 339.8597 351.9000 355.8546 367.8949 359.8415
[M+2] [M+2] [l] [M+2] [M+2] [M+2] [M+2] [M+6] [M+2] [M+2] [l] [M+2] [M+2] [M+2] [M+2] [M+2]
Quantitation ion
[M] [M] [l] [M] [M] [M] [M] [M+4] [M+4] [l] [M] [M] [M] [M] [M+4]
289.9224 301.9626 316.9824 303.9016 315.9419 319.8965 331.9368 327.8775 339.9177 330.9792 337.8627 349.9029 353.8576 365.8978 361.8385
Confirmation ion
Monitored ions
110 40 50 100 15 100 15 85 100 15 50 120 15 150 15 100 10
0.77 0.77 0.77 0.77
10
0.61 0.61 0.61 0.61 0.81
0.64 0.64
0.77 0.77
0.53–0.71 0.53–0.71 0.53–0.71 0.53–0.71 0.69–0.94
0.56–0.75 0.56–0.75
0.65–0.88 0.65–0.88 0.65–0.88 0.65–0.88
0.65–0.88 0.65–0.88
Theoretical 15% for isotopic isotopic ratios ratios
10
Ion dwell time Interscan time (ms) (ms)
Table 4 Target masses for PCDD/Fs and non-ortho PCBs in SIM mode for HRMS
474 Marie-Louise Scippo et al.
371.8817 380.9760 373.8207 385.8610 389.8156 401.8559 380.9760 407.7818 419.8220 423.7767 435.8169 430.9728 459.7348 471.7750 443.7398 455.7801 466.9728
[M+2] [l] [M+2] [M+2] [M+2] [M+2] [l] [M+2] [M+2] [M+2] [M+2] [l] [M+4] [M+4] [M+4] [M+4] [l]
373.8788 380.9760 375.8178 387.8580 391.8127 403.8530 380.9760 409.7788 421.8190 425.7737 437.8140 430.9728 457.7377 469.7780 441.7428 453.7830 466.9728
Syringe standard added prior to GC-HRMS analysis and used for recovery.
a
HxCB 13C12 Lock mass HxCDF 35–42 HxCDF 13C12 HxCDD HxCDD 13C12 Lock mass HpCDF 42–47 HpCDF 13C12 HpCDD HpCDD 13C12 Lock mass OCDD 47–52 OCDD 13C12 OCDF OCDF 13C12 Lock mass [M+4] [l] [M+4] [M+4] [M+4] [M+4] [l] [M+4] [M+4] [M+4] [M+4] [l] [M+2] [M+2] [M+2] [M+2] [l]
15 50 150 15 150 15 50 150 15 150 15 50 150 15 150 15 50 0.81 0.81 0.81 0.81 1.04 1.04 1.04 1.04 0.89 0.89 0.89 0.89
10
10
10
0.81
0.75–1.01 0.75–1.01 0.75–1.01 0.75–1.01
0.88–1.20 0.88–1.20 0.88–1.20 0.88–1.20
0.69–0.94 0.69–0.94 0.69–0.94 0.69–0.94
0.69–0.94
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
475
476
Marie-Louise Scippo et al.
around the theoretical ion abundance ratio (Table 4). Any deviation out of this range will cause rejection of the congener’s result. The power of MS in quantitative analysis is, in fact, further enhanced by the isotopic dilution technique. This technique consists of spiking samples with an ideal internal standard, which is the isotopically labeled standard (e.g., 13C12 2,3,7,8-TCDD), showing almost identical characteristics to the compound of interest (e.g., 12C12 2,3,7,8-TCDD). The small mass difference (e.g., m/z 12) enables the discrimination between the compound of interest and its internal standard (Table 4). A calibration performed for all the PCDD/Fs and DL-PCBs with known amounts of native and internal standard congeners allows calculating the Relative Response Factor (RRF). The RRF takes into account the discrepancy that can be observed during MS ionization between natives and internal labeled standards. Thus, the RRF value directly affects the congener quantification as indicated in the following equation: ½congeneri ¼
ðA1native;i þ A2native;i Þ Qi ðA1labeled;i þ A2labeled;i Þ RRFi m
where [congener]i is the concentration of the congener i (e.g., ng/kg), areas A1native;i and A2native;i are the areas of the quantitation and confirmation ions for the native congener i, A1labeled;i and A2labeled;i the areas of the quantitation and confirmation ions for its corresponding labelled compound i, Qi is the amount of the corresponding recovery standard i spiked (e.g., ng) in the sample, RRFi the relative response factor of the congener i and m the weight of the sample (e.g., kg).
4.3.3.2 GC-QIST/MS. Tandem MS as ion trap (Quadrupole ionstorage/MS, QIST/MS) MS/MS have been developed and used to analyse dioxins and related compounds. Dioxin analysis in MS/MS mode by ion trap MS is a wonderful application and illustration of ion trap theory [179–183]. Basically, the lack of selectivity in full scan mode with these benchtop instruments (i.e., mass unit resolution) is compensated by operating the instrument in MS/MS mode. The dioxin or furan precursor ion loses a fragment of COCl which is characteristic of these molecules. No other similar halogenated organic compound fragments in this way, improving considerably the selectivity of the method. A global overview of MS/MS scan functions occurring in-time is shown in Figure 3 for the TCDD example [181]. The abscissa axis represents the time in milliseconds and the ordinate represents the amplitude of the voltages. RF corresponds to the potential applied to the ring electrode and the supplementary alternating voltages applied to the end-cap electrodes in dipolar fashion, which are referred to as waveforms. The first step consists of isolating the two most intense ions in the precursor ion cluster (e.g., m/z 320 and 322), that is the predominant transition [M]+ and [M+2]+ . Ions with m/z o320 are ejected using the mass selective axial instability mode by ramping the rf amplitude voltage. The ions’ ejection is facilitated by the concurrent application of axial modulation with amplitude of 3 V. When ions of m/z 320 arrive close to the instability region (qz ¼ 0.908), the rf amplitude is modulated moderately in order to avoid
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
Cl 2 Cl 3
9
1 O O
4
+ [M] m/z 320
6
8 Cl 7 Cl
+ [M+2] m/z 322
Analytical RF ramp
Modulation
m/z 280
Eject > m/z 322
RF Ramp Eject < m/z 320
RF
477
m/z 160
m/z 165 m/z 140 qz= 0.4
|Ionization|
Pre-isolation Waveform
A
B Eject > m/z 322
Broadband Waveform CID Waveform
C
Eject < m/z 320
Axial Modulation
MFI Mass Analysis
Time ( ms)
Figure 3 Scan function for MS/MS of dioxin (TCDD). Reproduced from Ref. [181].
the ejection of the selected ions. Then, when ions of m/z o320 are ejected, the rf is a little bit decreased and the ejection of ions with m/z W322 can start. It is achieved by applying a broadband waveform. Ions are ejected by matching the frequency (500 Hz steps) with the secular frequency of ions of a higher m/z ratio. Once isolation of the selected ions is completed, the rf voltage is dropped to obtain a qz value of 0.4. Ions of m/z 322 migrate on the left side of the axial qz axis to a more stable region of the stability diagram. In MS/MS, collision induced dissociation (CID) process can be affected in four modes: (1) single frequency irradiation (SFI), (2) multi-frequency irradiation (MFI), (3) secular-frequency modulation and (4) non-resonant excitation. The first three resonant modes were investigated and compared by Plombey and March [180] for dioxin application. They concluded that the tuning requirements of MFI and the duration of irradiation were compatible with the gas chromatographic time scale. During CID process, PCDDs fragmentation is characterized by losses of Cl , COCl , 2COCl and PCDFs fragmentation by losses of Cl , COCl , COCl2 and COCl3 . The main fragment used for quantification by isotopic dilution technique is the loss of COCl for both PCDDs and PCDFs, whereas the loss of Cl2 characterizes the main fragment used for PCBs quantification.
478
Marie-Louise Scippo et al.
4.3.3.3 Isotopic dilution technique for quantification by MS/MS technique. The principle is exactly the same as already reported for HRMS. The main difference is characterized here by the fact that instead of following the two most abundant molecular ions at 10,000 resolution in SIM mode, the two product ions [M+2CO35Cl ] and [M+2CO37Cl ] are monitored for both native and labelled molecular ions. It is called a selected reaction monitoring (SRM). Within a time window, the instrument alternatively scans the native and the label congener. Only 2,3,7,8-chloro-substituted congeners are followed. As for HRMS, the chromatogram is sliced into seven time windows from tetra-through-octa chlorinated dioxins and furans on a Rtx-5MS as shown in Figure 4 and Table 5. Compounds are numbered from 1 to 17 from TCDF to OCDF (see Table 5) for numbering correspondences. As native congeners co-elute with its corresponding labelled 13C12 isomer, the native peak maxima should fall within 3 s of their corresponding 13C labelled analogues for identification. In windows 1, 2 and 4, the native compound and its corresponding labelled internal standard are monitored in MRM mode. For windows 3, 5, 6 and 7, MRM is performed by monitoring alternatively four molecular ions. After isolation, the molecular ion is replaced in the stability diagram at a value of qz ¼ 0.45. The optimum voltage applied to the end-cap electrodes during CID varies between 5.5 and 6 V, whereas CID time has been optimized to 30 ms. The specificity of MS/MS is achieved by monitoring two product ions and by checking their isotopic ratios. If the most abundant ion from the isotopic cluster is selected for MS/MS (i.e., [M+2] for TCDD), then the isotopic ratio for product ions does not follow the natural abundance of N-1 Cl (i.e., 3 Cl). Indeed, there is
Figure 4 Retention time of the seven toxic PCDDs and ten PCDFs on a Rtx5-MS column.
2,3,7,8-TCDF 2,3,7,8-TCDF 13C12 2,3,7,8-TCDD 2,3,7,8-TCDD 13C12 1,2,3,7,8-PeCDF 1,2,3,7,8-PeCDF 13C12 2,3,4,7,8-PeCDF 2,3,4,7,8-PeCDF 13C12 1,2,3,7,8-PeCDD 1,2,3,7,8-PeCDD 13C12 1,2,3,4,7,8-HxCDF 1,2,3,4,7,8-HxCDF 13C12 1,2,3,6,7,8-HxCDF 1,2,3,6,7,8-HxCDF 13C12 2,3,4,6,7,8-HxCDF 2,3,4,6,7,8-HxCDF 13C12 1,2,3,4,7,8-HxCDD 1,2,3,4,7,8-HxCDD 13C12 1,2,3,6,7,8-HxCDD 1,2,3,6,7,8-HxCDD 13C12 1,2,3,7,8,9-HxCDD 1,2,3,7,8,9-HxCDD 113C12 1,2,3,7,8,9-HxCDF 1,2,3,7,8,9-HxCDF 13C12
1
12
11
10
9
8
7
6
5
4
3
2
Compounds
Peak
29–33.5
25.7–29
21.95–25.7
21.4–21.95
20–21.4
Window (min)
306 318 322 334 340 352 340 352 356 368 374 386 374 386 374 386 390 402 390 402 390 402 374 386
[M+2] [M+2] [M+2] [M+2] [M+2] [M+2] [M+2] [M+2] [M+2] [M+2] [M+2] [M+2] [M+2] [M+2] [M+2] [M+2] [M+2] [M+2] [M+2] [M+2] [M+2] [M+2] [M+2] [M+2]
Molecular ions
5.5 5.5 5 5 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6
CID (V)
30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30
Collision time (ms)
0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45 0.45
q value
241/243 252/254 257/259 268/270 275/277 286/288 275/277 286/288 291/293 302/304 309/311 320/322 309/311 320/322 309/311 320/322 325/327 336/338 325/327 336/338 325/327 336/338 309/311 320/322
Product ions
0.33 0.33 0.33 0.33 0.25 0.25 0.25 0.25 0.25 0.25 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20
Isotopic ratios
Table 5 Main parameters optimized for MS/MS analysis of dioxins and furans. The congener’s classification corresponds to the elution order on Rtx5-MS 40 m column
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
479
1,2,3,4,6,7,8-HpCDF 1,2,3,4,6,7,8-HpCDF 13C12 1,2,3,4,6,7,8-HpCDD 1,2,3,4,6,7,8-HpCDD 13 C12 1,2,3,4,7,8,9-HpCDF 1,2,3,4,7,8,9-HpCDF 13C12 OCDD OCDD 13C12 OCDF OCDF 13C12
13
17
16
15
14
Compounds
Peak
Table 5 (Continued )
37.5–43
33.5–37.5
Window (min)
410 422 460 472 444 456
410 422 426 438 [M+4] [M+4] [M+4] [M+4] [M+4] [M+4]
[M+4] [M+4] [M+4] [M+4]
Molecular ions
6 6 6 6 6 6
6 6 6 6
CID (V)
30 30 30 30 30 30
30 30 30 30
Collision time (ms)
0.45 0.45 0.45 0.45 0.45 0.45
0.45 0.45 0.45 0.45
q value
345/347 356/358 395/397 406/408 379/381 390/392
345/347 356/358 361/363 372/374
Product ions
0.40 0.40 0.33 0.33 0.33 0.33
0.40 0.40 0.40 0.40
Isotopic ratios
480 Marie-Louise Scippo et al.
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
481
one chance out of four to lose CO37Cl , whereas there are three chances out of four to lose CO35Cl . Thus, the ratio of product ions (i.e., the ratio 257/259) equals to 0.33 (see Table 5). The others ratios from tetra to octa chlorinated congeners can be calculated the same way. Obviously, to ensure the production of two different daughter ions, the precursor ions have to contain at least one 37Cl. The analytical quality criterion for screening technique allows a broader range of isotopic ratios (i.e., 725%). In addition, it should be added that the labelled product ions are characterized by [M + 11], as one carbon is lost during fragmentation.
4.3.3.4 GC GC coupled to time-of-flight mass spectrometry (TOF/MS). GC GC can be coupled to MS. Most commonly, TOFMS is used because it offers the fast acquisition rate required for accurate characterization of GC GC peaks that have a width at the base of 100–250 ms. Sector, quadrupole and ion trap MS that are popular in the environmental field can barely be used because of the time it takes for those instruments to scan even a limited number of masses (SIM) and move to another mass cluster. Recent reports have, however, pointed out the potential use of quadrupole system for certain GC GC applications [184]. TOFMS can acquire at rates up to 500 scans per seconds [185], which corresponds to 50 data points per 100 ms peaks. Contrary to sector, quadrupole and traps operating in SIM mode, a full mass spectrum is collected during each TOFMS acquisition. Additionally, because all ions are virtually collected at the same time point of the chromatogram, TOFMS conduct to non-skewed mass spectra. High quality information is, therefore, available for any mass included in the collected mass range, allowing mass spectral deconvolution of overlapped GC peaks presenting different fragmentation patterns [186]. Pure mass spectra can be obtained even in the case that the purity of the compound in the chromatographic peak is poor (chromatographic co-elution). Accurate peak identification and quantification are thus possible based on deconvoluted ion currents (DIC). GC GC coupled to TOFMS is therefore an analytical tool ideally suited for the measurement of families of contaminants in complex matrices, such as food. In practice, mass spectral data are recorded continuously. They are then compared and combined following similarity criteria to identify a 2D (second dimension) peak constituting a cluster corresponding to the same analyte. GC GC-TOFMS can also be used with isotope dilution (ID) to quantify target compounds. For quantification, two masses were summed up for both native and label compounds and quality assurance/quality control (QA/QC) similar to those used for GC-IDHRMS were applied (Table 6). GC GC-IDTOFMS method LOQs (limit of quantifications) are not as good as for GC-IDHRMS, but were as low as 0.5 pg on column for some congeners. Figure 5 illustrates how low the signal for such levels can be regarding the total ion current and the 13C-labelled compounds. Three modulation cycles (PM ¼ 4 s) are represented. The signal in Figure 5A is based on the TIC and is mainly a result of matrix interferences still present after the sample preparation procedure. Figure 5B is the reconstructed ion current (RIC) based on the ions of the label compound (m/z 352+354) at a concentration of approximately 85 pg (10 mL of a 50 pg/mL standard solution, 75% recovery rates, 1.2 mL injected out of
Congenera
TriCB-28 TeCB-52 TeCB-80b PeCB-101 TeCB-81 TeCB-77 PeCB-123 PeCB-118 PeCB-114 HxCB-153 PeCB-105 HxCB-138 1,2,3,4-TeCDDb,c 2,3,7,8-TeCDF 2,3,7,8-TeCDD PeCB-126 HxCB-167
Peak number
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
tR (s)
727 751 895 923 1,025 1,061 1,094 1,106 1,126 1,150 1,186 1,233 1,252 1,264 1,292 1,340 1,381
1
tR (s)
1.91 2.09 2.11 2.34 2.27 2.32 2.56 2.56 2.69 2.57 2.79 2.81 2.56 2.56 2.46 2.46 2.69
2
258 290 – 328 290 290 328 328 328 362 328 362 – 304 320 328 362
256 292 – 326 292 292 326 326 326 360 326 360 – 306 322 326 360
C12-natives
12
270 302 302 340 302 302 340 340 340 374 340 374 328 316 332 340 374
268 304 304 338 304 304 338 338 338 372 338 372 – 318 334 338 372
C12-labels
13
Quantification masses
0.98 0.77 0.77 0.65 0.77 0.77 0.65 0.65 0.65 0.82 0.65 0.82 – 0.77 0.76 0.65 0.82
Theoretical isotope ratios
0.78–1.18 0.62–0.92 0.62–0.92 0.52–0.78 0.62–0.92 0.62–0.92 0.52–0.78 0.52–0.78 0.52–0.78 0.66–0.98 0.52–0.78 0.66–0.98 – 0.62–0.92 0.61–0.91 0.52–0.78 0.66–0.98
Acceptable range (20%)
Table 6 Principal chromatographic and mass spectrometric parameters for the GC GC-IDTOFMS separation of the selected PCBs and PCDD/Fs. Reproduced from Ref. [184]
482 Marie-Louise Scippo et al.
b
c
HxCB-156 HxCB-157 HpCB-180 1,2,3,7,8-PeCDF 2,3,4,7,8-PeCDF 1,2,3,7,8-PeCDD HxCB-169 HpCB-189 1,2,3,4,7,8-HxCDF 1,2,3,6,7,8-HxCDF 1,2,3,4,7,8-HxCDD 1,2,3,6,7,8-HxCDD 2,3,4,6,7,8-HxCDF 1,2,3,7,8,9-HxCDD 1,2,3,7,8,9-HxCDF 1,2,3,4,6,7,8-HpCDF 1,2,3,4,6,7,8-HpCDD 1,2,3,4,7,8,9-HpCDFb OCDD OCDF
Numbering of PCBs according to IUPAC. Congeners used for recovery calculation. This congener is 13C6-1,2,3,4-TeCDD only.
a
18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37
1,476 1,496 1,512 1,559 1,675 1,691 1,711 1,875 2,025 2,037 2,185 2,197 2,209 2,264 2,296 2,436 2,519 2,543 2,703 2,707
2.84 2.89 2.81 2.61 2.61 2.54 2.42 2.76 2.52 2.54 2.42 2.42 2.46 2.37 2.54 2.39 2.46 2.69 2.94 3.15
362 362 396 342 342 358 362 396 376 376 392 392 376 392 376 410 426 – 458 442
360 360 394 340 340 356 360 394 374 374 390 390 374 390 374 408 424 – 460 444
374 374 408 354 354 370 374 408 388 388 404 404 388 404 388 422 438 422 470 454
372 372 406 352 352 368 372 406 386 386 402 402 386 402 386 420 436 420 472 456
0.82 0.82 0.98 0.65 0.65 0.66 0.82 0.98 0.82 0.82 0.82 0.82 0.82 0.82 0.82 0.98 0.98 0.98 0.88 0.88
0.66–0.98 0.66–0.98 0.78–1.18 0.52–0.78 0.52–0.78 0.53–0.79 0.66–0.98 0.78–1.18 0.66–0.98 0.66–0.98 0.66–0.98 0.66–0.98 0.66–0.98 0.66–0.98 0.66–0.98 0.78–1.18 0.78–1.18 0.78–1.18 0.70–1.05 0.70–1.05
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
483
160000
(A)
Counts
120000
80000
40000
0 Label 5000
(B)
Counts
4000
3000
Label
2000 Label
1000
0 Native
200 (C)
Counts
150
100
50
0 tR 1547 2 tR 3.6 1
1549 1.6
1551 3.6
1553 1.6
1555 3.6
1557 1.6
1559 3.6
Figure 5 GC GC-IDTOFMS raw chromatogram for 1,2,3,7,8-PeCDF in a fish sample. (A) TIC trace, (B) RIC trace for the 13C label and (C) RIC trace for the native (1.1 pg injected). Reproduced from Ref. [184].
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
485
Figure 6 Three-dimensional view of abiological sample where target analytes (2tR ¼ 1–2 s) are separated from the bulk of matrix interferences (2tR ¼ 0–1 s). Reproduced from Ref. [10].
5 mL). Figure 5C is the RIC of the native (12C) 1,2,3,7,8-PeCDF (1.1 pg), only one 2D peak was obtained because of the very low level. That native peak signal was several orders of magnitude lower than the TIC trace. Increasing sample sizes is not feasible in practice because the larger the sample size, the larger the quantities of solvents and sorbents, the higher the BC levels, and the higher the LOQs. This single injection method correlates with the well-established and accepted reference GC-IDHRMS methods, which require, at least, three separate injections to report all of the analytes. Most of the potentially interfering compounds are separated from the analytes of interest in the chromatographic GC GC space, due to the increased peak capacity (Figure 6).
4.3.3.5 Comparison between GC-IDHRMS, GC-IDQISTMS/MS and GC GCIDTOFMS. GC-IDHRMS, GC-IDQISTMS/MS and GC GC-IDTOFMS performances can be compared for the measurement of dioxins and PCBs in food samples. Figures 7 and 8 illustrate the comparison for the non-ortho and mono-ortho-PCBs and
16
300
A) 2500
250
2000
GCxGC-IDTOFMS GC-IDHRMS
14
GC-IDQISTMS/MS
12 10
1500
8
150 1000
6
100
4 50
B)
350 300
100
1.0
80
0.8
60
0.6
40
0.4
20
0.2
0
0.0
HxCB-169
TeCB-77
HpCB-189
HxCB-167
HxCB-157
HxCB-156
0 PeCB-123
0
PeCB-114
PeCB-118
PeCB-105
0
2 PeCB-126
500
TeCB-81
pg/g fw
200
pg/g fw
250 200 150
1.4
100
30
1.2
25
1.0
20
0.8
15
0.6
10
0.4
20
5
0.2
0
0
0.0
HxCB-169
PeCB-126
TeCB-81
TeCB-77
HpCB-189
HxCB-167
HxCB-157
HxCB-156
35
80
HxCB-169
PeCB-126
TeCB-81
TeCB-77
HpCB-189
HxCB-167
HxCB-157
HxCB-156
PeCB-118
40
PeCB-123
60
PeCB-114
pg/g fw
PeCB-123
120
PeCB-105
C)
PeCB-114
0
PeCB-118
50
PeCB-105
100
Figure 7 Comparison of GC-IDHRMS with GC GC-IDTOFMS and GC-IDQISTMS/MS for the measurement of non-ortho and mono-ortho-PCBs in fish (A), in pork (B) and in milk (C) samples (n ¼ 6). Reproduced from Ref. [184].
4 A) 3.5 GCxGC-IDTOFMS GC-IDHRMS GC-IDQISTMS/MS
pg/g fw
3 2.5 2 1.5 1 0.5 0 1.2 B) 1
pg/g fw
0.8 0.6 0.4 0.2 0 0.25
0.87 ± 0.18
0.95 ± 0.05
C) 0.85 ± 0.05
pg/g fw
0.2
0.15
0.1
OCDF
1,2,3,4,7,8,9-HpCDF
1,2,3,4,6,7,8-HpCDF
2,3,4,6,7,8-HxCDF
1,2,3,7,8,9-HxCDF
1,2,3,6,7,8-HxCDF
1,2,3,4,7,8-HxCDF
2,3,4,7,8-PeCDF
1,2,3,7,8-PeCDF
2,3,7,8-TeCDF
OCDD
1,2,3,7,8,9-HxCDD
1,2,3,4,6,7,8-HpCDD
1,2,3,6,7,8-HxCDD
1,2,3,4,7,8-HxCDD
1,2,3,7,8-PeCDD
0
2,3,7,8-TeCDD
0.05
Figure 8 Comparison of GC-IDHRMS with GC GC-IDTOFMS and GC-IDQISTMS/MS for the measurement of PCDD/Fs in fish (A), in pork (B) and in milk (C) samples (n ¼ 6). Reproduced from Ref. [184].
488
Marie-Louise Scippo et al.
PCDD/Fs, respectively, in naturally contaminated fish, pork and milk samples. All three methods performed similarly in terms of non-ortho and mono-ortho-PCB measurement for the three investigated matrices independent of the levels. Lower relative standard deviations (RSDs) were observed for the reference GC-IDHRMS method. For PCDD/Fs (Figure 8), levels in the unfortified matrices were much lower than for PCBs and can be considered as the background levels currently encountered in the EU. For fish, because of the relatively high levels and the relatively large sample sizes (15 g), both GC GC-IDTOFMS and GC-IDQISTMS/MS compared well with GC-IDHRMS. However, although the RSDs for GC-IDHRMS were 7–14%, GC GC-IDTOFMS and GC-IDQISTMS/MS RSDs ranged from 10 to 60% and from 5 to 30%, respectively. In practice, such concentrations were very close to the lower end of the working range defined by the calibration standards and on the edge of the LOQs. In the case of pork (30 g sample size) and milk (130 g sample size), which are characterized by low background levels, the RSDs were higher (up to 90%). Such variations were not acceptable. Despite the poor precision, the congener distribution was still well defined for all matrices and can be used to describe specific matrix patterns for contamination source tracking or fingerprinting of sets of samples. Like GC-IDQISTMS/MS, GC GC-IDTOFMS is capable of measuring low levels of PCBs and dioxins in foodstuffs but cannot currently reach the same sensitivity as GC-IDHRMS. GC GC-IDTOFMS offers at least as much QA/QC checks than the other methods (ID quantification, isotope ratio check, dual set of retention time check). The large ion volume in the TOFMS source makes it unlikely to be as influenced by sample extract quality as other classical small source types, a significant advantage for routine use. Furthermore, the TOFMS instrument showed itself to be more robust than QISTMS, where the ion trap can easily be contaminated by matrix interfering ions, reducing sensitivity when used on a routine basis. Although the measurement of PCBs is under control, further improvement in sensitivity at the sub-picogram level, together with reduced data handling and processing time requirements are still needed. If accomplished, GC GC-TOFMS could be set up as a true alternative to GC-IDHRMS for routine ultra-trace measurement of PCDD/F in challenging foodstuff matrices. The integration of PCBs and other types of analytes into the EU regulation is making GC GC-IDTOFMS one of the promising alternatives for the future. In addition, GC GC coupled to micro electron capture detection (micro-ECD) were reported for the measurement of selected POPs [187]. Valuable data were obtained but the lack of mass spectral data would only allow this technique to be considered as a screening tool in the EU standards.
4.3.3.6 GC GC coupled to sector high resolution mass spectrometry (HRMS). Although the scanning rate limitation of sector instruments does not make it as the detector of choice for GC GC, they can be useful in a particular situation. Because of the zone compression due to cryogenic modulation, one can imagine using the modulator as a signal enhancer for selected congeners exhibiting extremely low levels. That is the case for 2,3,7,8-TCDD and 1,2,3,7,8PeCDD [188]. Under optimized conditions, sub-femtogram levels of 2,3,7,8-TCDD and 1,2,3,7,8-PeCDD can be detected in real samples. In those conditions, only one
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
489
native and one label ion can be monitored to ensure adequate cycling time of the MS and accurate description of the narrow GC GC peaks. A full validation of that methodology is still to be done but the use of GC GC-IDHRMS in parallel to GC-IDHRMS will definitely ease measurement of real samples and limit the number of non-detected compounds to a minimum.
4.4 Determination by biological techniques Several kinds of bioassays can be used to detect dioxins and dioxin-like compounds [189], such as immunoassays [190,191], enzymatic assays (arylhydrocarbon hydroxylase (AHH) assay and ethoxyresorufin-O-dealkylase (EROD) assay) [192–198], PCR [199] and cell-based methods. If immunoassays are useful for environmental samples [200–202], they seem to be not sensitive enough for food samples, where levels and maximal tolerable concentrations are very low. On the contrary, cell-based assays are widely used for the screening of food and feed samples. In the framework of the official monitoring of dioxins in food and feed, if one sample gives a positive response in the screening test, the result has to be confirmed using the reference high resolution GC–high resolution MS method [203].
4.4.1 Cell-based assays The most used cell-based assay to detect dioxin and dioxin-like compounds is named CALUX (Chemically Activated LUciferase gene eXpression). The CALUX assay is based on the use of eukaryotic cells, genetically modified to contain the firefly luciferase gene under the control of a promoter containing at least one DRE. When these cells are exposed to dioxins, dioxins enter into the cells by easily crossing the phospholipidic membrane of the cells and bind to the cytoplasmic Ah receptor. The complex dioxin–AhR is then translocated into the nucleus of the cell and bind to DREs, inducing the expression of the luciferase gene, and subsequently of the synthesis of the firefly luciferase protein. After substrate (ATP and luciferin) addition, one can measure the emission of light, which is correlated to the concentration of dioxin. The first CALUX assay was described by Aarts et al. in 1993 [204]. Nowadays, at least two commercial systems exist, using either rat (DR-CALUXs, BDS [205]) or mouse cells (CALUXs, XDS [206]). Other non-commercial assays have been developed with rat [207], mouse [208] or human cells [209–211]. The application of the CALUX bioassay for the monitoring of dioxins in feed and food has been recently reviewed by Windal et al. [212] and Hoogenboom et al. [213]. From the 29 targeted dioxin and dioxin-like congeners, TCDD is the most potent in the CALUX assay. The relative equivalent potency (REP) for the other congeners are close to the 1998 WHO-TEFs for dioxins and furans, but not for DLPCBs (Table 2). Except PCB 126, dioxin-like PCBs display very low REP. The agreement between REP and TEFs becomes better for dioxin-like PCBs considering the 2005 WHO-TEFs (Table 2). Many ligands, such as benzo(a)pyrene, thiabendazole, bilirubin and curcumin [214], are able to bind to Ah receptor and to induce the synthesis of luciferase in
490
Marie-Louise Scippo et al.
the CALUX assay. However, when detecting dioxins in feed and food samples, these ligands are eliminated during the clean-up step of the extracted fat done on an acidic silica column. The steps involved in a CALUX analysis are summarized in Figure 9. Dioxins are eluted from the acidic silica column using hexane, which is evaporated almost to dryness before adding dimethylsulfoxide (DMSO), a solvent for dioxins, soluble in culture media and not toxic for cells until the concentration of 1%. A second column of activated charcoal can be added after the acidic silica, to separate DL-PCBs from PCDD/Fs [212,215]. Two approaches can be used for the cell analysis. In the quantitative method, unknown extracts are analysed together with a TCDD calibration curve, and results are expressed in TEQ (or TCDD equivalents). Figure 9 shows an example of TCDD calibration curve (obtained with the H4IIE DR-CALUX cells from BDS) and of the calculation of an unknown sample. The ‘‘instrumental’’ limit of detection (LOD) can be considered as the first point of the calibration curve (0.1 pg TCDD/mL culture medium), which is statistically different from the solvent (DMSO) response. When analysing samples, because of the background response of the procedure blank and the effect of the matrix, the LOD is slightly higher, but remains low enough to detect contaminated samples at maximal tolerable concentrations, using the protocol briefly described in Figure 9. A screening approach can also be used, where the response of the unknown sample is compared to a reference sample near the tolerance level. In the quantitative method, the comparison between HRMS and CALUX results often shows discrepancies, partly due to differences between the WHO-TEF [108] values and the CALUX REP values (Table 2) [184,216] assigned to each of the PCDD, PCDF and DL-PCB congeners. In addition, although analyte recovery rates are taken into account for calculations in HRMS, no correction for analytes loss based on internal standards is possible in a cell-based assay. Such differences make difficult the strict decision of compliance or suspicion of non-compliance for samples submitted to biological screening. To decrease these discrepancies, it is possible to correct CALUX results of unknown samples with CALUX results obtained from reference samples. This method works well for reference and unknown samples displaying congener profiles corresponding to a classical background contamination, but can lead to higher discrepancies in other cases. For example, in a recent European project called DIFFERENCE (Dioxins in Food and Feed-Reference Methods and New Certified Reference Materials), CALUX participating laboratories received together with candidate reference materials (named here below unknown pork, fish and milk samples), reference samples for correction of CALUX results (named here later ‘‘CALUX’’ reference samples). HRMS results for these ‘‘CALUX’’ reference samples were available in order to calculate a correction factor (the ratio between the HRMS result and the CALUX result) to apply to unknown samples. Both pork and fish ‘‘CALUX’’ reference samples had a congener profile that corresponded to a classical background contamination (similar to the pattern of
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
10g of feed sample or 2 g of fat
Homogenisation
Fat extraction Shaken solid / liquid extraction with hexane Clean-up (acidic silica column) Elution of PCDD/F/DL-PCBs with hexane Solvent evaporation TCDD standard solutions inDMSO (25 µL)
Sample extract in DMSO
Triplicate analysis on cells (DMSO extracts are diluted in medium to 0.8% DMSO) 24 hours exposition Lysis of cells Substrate (ATP and luciferin) addition Luminescence measurement (luminometer)
120
Unknown calculation: y = 108128.9/(1+(x/4)-1.1) +
96 RLU (Thousands)
+
+
72
-2 pg/8 µL DMSO
EC50
48
+
-(2*25/8) pg/ 25 µL DMSO
Unknown
24 + 0 0.05 0.1
+
-6.25 pg/2 g fat
LOD
+ 1
RLU = 35 000 EqTCDD conc.: -2 pg/ml medium
10
TCDD concentration (pg/ml medium)
100
-3.12 pg eq. TCDD/ g fat
Figure 9 Schematic representation of all the steps involved in a CALUX analysis. RLU, relative light unit.
491
492
Marie-Louise Scippo et al.
the unknown samples). It was not the case for the milk ‘‘CALUX’’ reference sample, which contained an abnormally high concentration of PCB-118, due to an over-fortification for this congener during the reference sample preparation. Because the REP of PCB 118 is very low, the CALUX result for this milk sample was much lower than the HRMS one, so the correction factor was very high leading to an overestimation of the unknown samples [184]. Another difficulty of the screening stage is to determine a limit of decision ‘‘in order to select those samples with levels of dioxins and dioxin-like PCBs that are less than 25% below or exceed the maximum level’’ [203] but yielding to a rate of false negative decisions lower than 1%. Furthermore, the rate of false positive decisions should be very low to ensure profitable use of the screening procedure (all samples suspected to be positive at the screening stage have to be tested by a confirmatory method, i.e., the HRMS method). To achieve that goal, we propose to use a statistical approach similar but not identical to the one described by Van Overmeire et al. [217]. To determine the rate of false negative samples (true positive samples declared negative at the screening stage), the first step is to define the limit at which a sample is declared positive. The non-compliance of a sample (true positive sample) is only declared at the confirmatory step (HRMS) if its concentration is above the maximal limit taking into account the measurement uncertainty [203] (what we call here the HRMS decision limit). As two maximal limits are currently fixed in the European Regulations, one for the PCDD/Fs TEQ level and one for the total PCDD/Fs+DL-PCBs TEQ content of the samples, the lowest maximum limit (based on PCDD/Fs TEQ) was chosen to calculate a CALUX decision limit, to be sure to avoid false negative decisions. In Figure 10, the dotted distribution corresponds to the expected HRMS results for a population of positive samples, contaminated with a PCDD/F TEQ corresponding to the maximum legal limit plus the expanded uncertainty (considering that an average expanded uncertainty of 20% is associated to a HRMS measurement). In order to obtain less than 1% of false negative decisions (which corresponds to the beta error) at the screening stage, the CALUX decision limit is calculated as the inferior limit of the 99% unilateral confidence interval of a population of results characterized by a mean being equal to the GC-HRMS decision limit and a coefficient of variation (CV) of 25%, which is an average reproducibility CV of the CALUX analysis (Figure 10). This CALUX decision limit has been calculated assuming that the recovery of the CALUX method, after correction with a reference sample, is 100% when compared to the HRMS result (which was shown to be almost achieved in the DIFFERENCE study). This mode of calculation leads to a CALUX decision limit being roughly the half of the PCDD/Fs WHO-TEQ maximal limit. As an example, more than 300 feed and food samples were analysed routinely in the laboratory of MS in 2004 and 2005. In order to compare all results on a same graph, the relative PCDD/F TEQ (Figure 11A) or total (Figure 11B) concentration, which is the ratio between the HRMS measured concentration and the respective maximum regulatory limit, were calculated. Graphs C and D of
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
Maximal HRMS DL Level : 0.75
frequency
CALUX DL
493
β = 1%
0.39
0.75 0.94 Contamination level (ppt)
Figure 10 Distribution of the expected measurements of positives samples containing a PCDD/F TEQ corresponding to the GC-IDHRMS decision limit, i.e., the PCDD/F TEQ maximal level (0.75 in this example)+the measurement uncertainty. Dotted line: distribution of expected GC-HRMS results (mean ¼ GC-HRMS decision limit, CV ¼ 10%). Plain line: distribution of expected corrected CALUX results for the same population of positive samples (mean ¼ GC-HRMS decision limit, CV ¼ 25%). DL: Decision limit. CALUX DL ¼ HRMSDL-two times the standard deviation of the mean of the expected CALUX measurements calculated with a CV of 25%. b: beta error, percentage of true positive samples below the CALUX decision limit (rate of false negative samples).
Figure 11 show the results obtained for some samples analysed with the CALUX method, relative to the PCDD/F regulatory limit in graph C and to total TEQ regulatory limit in graph D. In graph A, results are sorted by ascending PCDD/F TEQ concentration and samples are displayed in the same order in graphs B, C and D. All samples above 1 are thus above the regulatory limit. We see on graphs A and B that 93.4% of these samples are negative, 2.8% are above the PCDD/Fs maximum level and 3.8% are above the total maximum level only, from which 11 milk samples out of 83. Comparing graphs A and B with graphs C and D, the global pattern of the CALUX relative concentrations (graphs C and D) are the same as the HRMS ones (graphs A and B), and patterns of graphs B and D are more similar than those of graphs A and C (in terms of number of samples above 1), indicating that the distribution of the CALUX concentrations are more related to the HRMS ones when they are relative to the total TEQ maximum levels. Several ring tests have shown that CALUX is suitable for dioxin monitoring in food [218–222], and this cell-based assay is indeed used for the official screening of feed and food samples in several European countries.
Relative concentration
0.01
0.1
1
10
100
0.01
0.1
1
10
100
0
0
50
50
100
100
150 200 Sample n°
150 200 Sample n°
250
250
300
300
C
A
0.01
0.1
1
10
100
0.01
0.1
1
10
100
0
0
50
50
100
100
150 200 Sample n°
150 200 Sample n°
250
250
D
B
300
300
Figure 11 (A, B) PCDD/Fs (A) and sum of PCDD/Fs and DL-PCBs (B) concentrations measured by GC-HRMS in 314 feed and food samples. Concentrations are expressed as relative concentration (log scale) ( ¼ the ratio between the HRMS measured concentration and the respective maximum regulatory limit). (C, D) CALUX measured concentrations relative to the PCDD/F regulatory limit (C) and to total TEQ regulatory limit (D). CALUX measurements have been realized on a limited number of samples taken from the 314 samples analysed by GC-HRMS. The samples keep the same numbering in the four graphs. The plain line indicates the value of 1 (the maximal limit), the inferior dotted line corresponds to 0.5 (the CALUX decision limit) and the superior dotted line corresponds to 1.2 (the HRMS decision limit).
Relative concentration
Relative concentration Relative concentration
494 Marie-Louise Scippo et al.
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
495
5. OCCURRENCE IN FOOD Residues of POPs from the ‘‘dirty dozen’’ of the Stockholm convention can be present in all categories of food, such as baked goods, fruit, vegetables, meat, fish, poultry and dairy products. It is common to find residues of more than one POP in a single food item. From the OCP group, residues of DDT (and its metabolites such as DDE) and dieldrin are the most commonly found, in a recent study in USA [223]. The Joint FAO/WHO Meeting on Pesticide Residues (JMPR) [224] derived a provisional tolerable daily intake (PTDI) for a lot of pesticides including those of the Stockholm Convention. For DDT for example, even if it was estimated that the human exposure is now decreased to 10% of that occurring 30 years ago, with a mean dietary intake for adults and children in European Countries of 5–30 ng/kg bw/day, the intake is still more than two orders of magnitude below the JPMR PTDI of 0.01 mg/kg bw [30]. Darnerud et al. [225] came to the same conclusions regarding the POPs contamination of Swedish food. HCB, another member of the ‘‘dirty dozen’’, is found predominantly in fish derived products such as fish oil and in vegetables seeds and oils. On the contrary to DDT, the dietary intake of HCB in Europe is far below suggested health-based guidance value of 170 ng/kg bw/day [226]. This is also the case for endrin, for which human daily intake for adults and children seems to be below 1 ng/kg bw, resulting in a human exposure far below the JPMR PTDI of 200 ng/kg bw [227]. For aldrin and dieldrin, found mostly in fish derived products, the EFSA estimated a daily intake for adults and children ranging from 1 to 10 ng/kg bw, which is below the JPMR PTDI of 100 ng/kg bw [228]. Humans are exposed to dioxins and dioxin-like compounds predominately through their diet, with dairy products, eggs, meats and fish contributing roughly 90% of the exposure [13,14,229–232], although no single food group emerges as principal contributor [233], except in Nordic countries where the intake of fish is of major importance for the total intake of POPs [19,234]. A common hypothesis explaining the presence of dioxins in livestock is that animals consume feed that has been contaminated by emissions from combustion sources via atmospheric depositions. Because of their high affinity for lipid-rich tissues [235], the dioxins bioaccumulate in the fats of these animals and are passed on to the humans who consume them [236,237]. For humans, vegetables constitute only a small part of the total dioxin intake from food [238–240]. When evaluating standard diets in different parts of the world the results indicated that the estimated intakes of dioxins and dioxin-like compounds approach or exceed the monthly tolerable intake of 70 pg/kg bw/month [241]. Because fatty fish consumption is widely recommended for nutritional reasons (fatty fish is an important source of ‘‘good’’ n-3 polyunsaturated fatty acids), POP and more particularly dioxin contamination of fish has been extensively studied in recent years. In a recent study, the EFSA compared the contamination status of wild and farmed fish in Europe. Salmon is
496
Marie-Louise Scippo et al.
predominantly farmed in Europe while species such as herring and tuna are mostly of wild origin. The conclusion was that there is no difference between both farmed and wild fish, with respect to their safety for the consumer [242]. However, the problem of the harmonization of the sampling has been pointed out [242,243]. Other studies report different results showing that farmed salmon is more contaminated than wild salmon, because of the contaminated feed containing fish oil and other animal fat [244,245]. Risk-benefit analysis showed in most cases that fish consumption could not cause adverse health effects in consumers [246–248], but in their recent review about the dioxin contamination of edible fish species, Domingo and Bocio [249] conclude that some groups of population frequently consuming high quantities of certain species could be significantly increasing health risks due to PCDD/F and PCB exposure. Another kind of food that may be highly contaminated with dioxins and dioxin-like substances are eggs from free range hens. Several reports show that these eggs display higher levels of dioxins than industrial ‘‘battery’’ eggs, with a possible impact of the dioxin body burden of consumers eating a lot of such eggs (which is often the case of hen owners) [229,250]. Food incidents were occasionally reported with dioxins and dioxin-like compounds involving different animal species of origin and occurring at different links of the food chain [31], sometimes the result of the environmental contamination (e.g., thunder on pylon with old transformer in pasture of cattle) [114], feed contamination (e.g., contamination of dairy products, due to high concentrations of dioxins in citrus pellets, which were added to the cattle feed) [251] or in failure to the process (e.g., leakage of PCBs from a transformer stored in a pig slaughtering plant) [36]. Some examples are illustrated. In 1979, widespread distribution of chicken and egg-based products and fat contaminated with PCBs occurred across the United States and as far away as Canada and Japan. The contamination was traced to an accidental leakage of PCBs from a transformer stored in a pig slaughtering plant in Montana [252]. Twenty years later, a Belgian PCB incident occurred when a mixture of PCBs contaminated with dioxins was accidentally added to a stock of recycled fat used in the production of animal feeds for more than 2,500 farms (poultry, pigs and cattle). This resulted in a major food crisis, which rapidly extended to the whole country and could be resolved only by the implementation of a large PCB/dioxin food-monitoring program [253,254]. Several studies concluded that it is unlikely that this incident could have caused adverse effects in the general population of this country [230,254,255]. These episodes illustrate the need for vigilance on fat recycling and a professional risk assessment as a basis for measures to be taken [31].
6. FUTURE TRENDS For the protection of the environment and the food chain, the identification of the toxic chemicals themselves is not the most important issue. The toxicity of
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
497
a sample is what matters, as the chemicals are often present in complex mixtures, this leads the analyst to face a situation in which the individual toxic contributions must be summed without knowing what are toxic on one hand and without indication of their TEF on the other hand. That situation is somewhat similar to those for which bioassays such as CALUX have been developed to screen for potential non-compliant samples. The final decision is however taken on the basis of a well-defined set of chemicals, listed in regulations, after GC-HRMS confirmation. It is important to note that most regulations are based on identified chemicals and not on open lists of chemicals presenting the same toxicity. In order to trace the source of pollution, the molecular ‘‘signature’’ of the toxic mixture may be important information. As a consequence, strategies involving a screening step based on ‘‘fast and cheap’’ methods with a confirmation step of positive ones by heavier methods have been adopted. In the case of unwanted chemicals such as dioxins, the existing strong legislative basis for the control of emissions should insure a progressive decrease in exposure, limited however by their large lifetime in environmental reservoirs. The major sources have been identified and minor sources are now under scrutiny. The environmental release has been strongly down-regulated and the effects on the human body burden are clearly observed. This led the EPA to claim ‘‘having won the war against dioxins’’. However, for specific foodstuffs (e.g., milk), the decrease is not as fast as it could be due to the presence of long-term environmental background pollution in strongly industrialized countries. It is worthwhile to note that even if the dioxins levels constantly decreases, in some food the TEQ is stable or even increased. This is typically due to the nature of the Dioxins regulations. The addition of new items on the list may balance the decrease in TEQ contribution of previously listed compounds. This was the case when the dioxin-like PCBs were introduced in the dioxin family. With that in mind, what are the most expected trends in the field of POPs monitoring and dioxins in particular? The dual strategies including a screening test based on bioassays and a physico-chemical method for confirmation have shown their efficiency. They should be adapted to extend the set of chemicals listed in regulations. The bioassay will remain very useful to screen large number of samples and to sieve between background level samples and samples that need to be confirmed. In addition, bioassay will reveal the presence of unknown chemicals showing a dioxin-like activity. The identification of such new chemicals will be guided by bioassays. New simple and specific assays could be designed using the fast developments in the omics technologies. Transcriptomic analysis can reveal sets of genes controlled by specific chemicals. Proteomics techniques to screen multiple xenobiotic contaminants can be based on the selection of biomarkers of exposure. A specific protein expression signature may reflect not only the exposure, but also provide information about potential physiological effects [256]. Simple screening tests based on the quantification of sets of biomarkers would enable the identification of the presence of families of compounds with the same biological activity, allowing subsequently the identification of new compounds, and the testing of the toxicity of new chemicals. Still under
498
Marie-Louise Scippo et al.
development, such proteomic studies have already shown their capacity in detecting early effects of pollutants on living systems and giving new insights in the mechanism of action of these contaminants. Fast-GC and improved chromatographic separation capacity techniques (GC GC) coupled with fast mass spectrometers will allow the quantification of larger set of chemicals. Hyphenated tools illustrated in this chapter showed their abilities and limitations as alternative and complementary methods to GC/HRMS for POPs analysis. New hybrid mass spectrometers such as ion trap coupled with TOFMS should probably provide the required sensitivity and specificity to face tomorrow’s analytical challenges. One of these challenges is to lower detection limits as background levels of dioxins and related compounds in the environment and in biological samples have declined for several years. They are low enough for most regulatory purposes; however, the analytical performance should not be considered as a driving force for new regulations, but as tools to make the regulations correctly applied. More efforts are particularly needed to push the detection limits lower for biological monitoring studies to measure subtle effects from these contaminants with methods enabling the discrimination between target compounds and potentially interfering compounds at such low levels close to detection limits.
REFERENCES 1 2 3 4 5
6 7 8 9
10 11 12 13 14 15 16 17 18
K.C. Jones and P. de Voogt, Environ. Pollut., 100 (1999) 209. C. Schmidt, Environ. Health Perspect., 107 (1999) A18. M.D. Erickson (Ed.), Analytical Chemistry of PCBs, CRC Press LLC, Boca Raton, 1997. A. Nadakavukaren (Ed.), Our Global Environment, a Health Perspective, Waveland Press, Inc, Prospect Heights, 2000. UN-ECE. Protocol to the 1979 convention on long range transboundary air pollution on persistent organic pollutants, 1998. Available at http://www.unece.org/env/lrtap/pops_h1.htm. Accessed on 15 February 2007. D. Lerche, E. van den Plassche, A. Schwegler and F. Balk, Chemosphere, 47 (2002) 617. Stockholm convention on persistent organic pollutants, Off. J. Eur. Union L, 209 (2006) 3. UNEP. Stockholm convention on persistent organic pollutants, 2001. Available at http:// www.pops.int/. Accessed on 15 February 2007. Regulation (EC) No 850/2004 of the European Parliament and of the Council of 29 April 2004 on persistent organic pollutants and amending Directive 79/117/EEC., Off. J. Eur. Union L, 229 (2004) 5. J.F. Focant, A. Sjodin, W.E. Turner and D.G. Patterson, Anal. Chem., 76 (2004) 6313. F. Rahman, K.H. Langford, M.D. Scrimshaw and J.N. Lester, Sci. Total Environ., 275 (2001) 1. G.M. Solomon and P.M. Weiss, Environ. Health Perspect., 110 (2002) A339. C.C. Travis and H.A. Hattemerfrey, Sci. Total Environ., 104 (1991) 97. G.F. Fries, J. Anim. Sci., 73 (1995) 1639. C.H. Walker (Ed.), Organic Pollutants. An Ecotoxicological Perspective, Taylor & Francis, New York, 2001. A.K.D. Liem, P. Furst and C. Rappe, Food Addit. Contam., 17 (2000) 241. A. Schecter, P. Cramer, K. Boggess, J. Stanley, O. Papke, J. Olson, A. Silver and M. Schmitz, J. Toxicol. Environ. Health, 63 (2001) 1. C.Y. Juan, G.O. Thomas, A.J. Sweetman and K.C. Jones, Environ. Int., 28 (2002) 303.
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
499
19 H. Kiviranta, M.A.L. Ovaskainen and T. Vartiainen, Market basket study on dietary intake of PCDD/Fs, PCBs, and PBDEs in Finland, Environ. Int., 30 (2004) 923–932. 20 A. Bocio and J.L. Domingo, Environ. Res., 97 (2005) 1. 21 C.C. Travis and H.A. Hattermer-Frey, Chemosphere, 16 (1987) 2331. 22 H. Beck, K. Eckart, W. Mathar and R. Wittkowski, Chemosphere, 18 (1989) 417. 23 P. Fu¨rst, C. Fu¨rst and W. Groebel, Chemosphere, 20 (1990) 787. 24 US EPA (United States Environmental Protection Agency), Estimating exposure to dioxin-like compounds. Exposure Assessment group, office of health and environmental assessment, office of research and development. EPA/600/6-88/005Ca-c. 25 A.K.D. Liem, Organohalogen Compd., 44 (1999) 1. 26 J.R. Startin, In: A. Schecter (Ed.), Dioxins and Health, Plenum Press, New York, NY, 1994, p. 115. 27 L. Ritter, K.R. Solomon, J. Forget, M. Stemeroff and C. O’Leary, An assessment report on: DDT, aldrin, dieldrin, endrin, chlordane, heptachlor, hexachlorobenzene, mirex, toxaphene, polychlorinated biphenyls, dioxins and furans. The International Programme on Chemical Safety (IPCS) within the framework of the Inter-Organization Programme for the Sound Management of Chemicals (IOMC), 1995. Available at http://www.chem.unep.ch/pops/indxhtms/asses0.html. Accessed on February 15, 2007. 28 V. Turusov, V. Rakitsky and L. Tomatis, Environ. Health Perspect., 110 (2002) 125. 29 C. Wendo, Lancet, 363 (2004) 1376. 30 Opinion of the scientific panel on contaminants in the food chain on a request from the commission related to DDT as an undesirable substance in animal feed, The EFSA J. 433 (2006) 1. Available at http://www.efsa.europa.eu/etc/medialib/efsa/science/contam/contam_opinions/ ej433_ddt.Par.0001.File.dat/CONTAM_ej433_DDT_en.pdf. Accessed on February 15, 2007. 31 C. Saegerman, L. Pussemier, A. Huyghebaert, M.L. Scippo and D. Berkvens, Rev. Sci. Tech. Off. Int. Epizoot., 25 (2006) 655. 32 Expertise Collective, Dioxines dans l’Environement, Quels Risques pour la Sante´?, Synthe`se et Recommandations. INSERM, Paris, France, 2000. Available at http://ist.inserm.fr/basisrapports/ dioxine.html. Accessed on February 15, 2007. 33 Polychlorinated dibenzodioxins and dibenzofurans, In: Air Quality Guidelines, 2nd ed., Chapter 5.11. WHO Regional Office for Europe, 2000. Available at http://www.euro.who.int/document/ aiq/5_11pcddpcdf.pdf. Accessed on 15 February 2007. 34 Dioxin and furan inventories: National and regional emissions of PCDD/PCDF. UNEP Chemicals, Geneva, 1999. Available at http://www.chem.unep.ch/pops/pdf/dioxinfuran/ difurpt.pdf. Accessed on 15 February 2007. 35 An inventory of sources and environmental releases of dioxin-like compounds in the United States for the years 1987, 1995, and 2000, National Center for Environment Assessment, Office of Research and Development, United States Environmental Protection Agency, Washington, DC, 2006. Available at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid ¼ 159286. Accessed on February 15 2007. 36 Compilation of EU dioxin exposure and health data, summary report. European Commission and United Kingdom (Department of the Environment, Transport and Regions), 1999. Available at http:// europa.eu.int/comm/environment/dioxin/pdf/summary.pdf. Accessed on 15 February 2007. 37 J. Tuomisto, T. Vartiainen and J. T. Tuomisto, KTL-synopsis on Dioxins and PCBs, 1999. Available at http://www.ktl.fi/dioxin/litinfo.html. Accessed on 15 February 2007. 38 A.A. Seawright, Chemical residues in foods of animal origin. In: Animal health in Australia, Vol. 2, Chemical and Plant Poisons, Australian Government Publishing Service, Canberra, 1982, p. 235. 39 Polychlorinated biphenyls (PCBs). In: Air quality guidelines, 2nd ed., WHO Regional Office for Europe, Copenhagen, 2000, Chapter 5.10. Available at http://www.euro.who.int/document/aiq/ 5_10pcbs.pdf. Accessed on 15 February 2007. 40 M.D. Anway, A.S. Cupp, M. Uzumcu and M.K. Skinner, Science, 308 (2005) 1466. 41 P. Cocco, Cad. Saude Publica., 18 (2002) 379. 42 J. Mendes, Food Chem. Toxicol., 40 (2002) 781. 43 R. Sharpe and D. Irvine, Br. Med. J., 328 (2004) 447. 44 S. Kumar, J. Occup. Health, 46 (2004) 1.
500
45 46 47 48 49
50
51
52 53
54 55 56 57 58 59 60 61 62 63 64 65 66 67 68
69 70 71
Marie-Louise Scippo et al.
J.P. Bonde and L. Storgaard, Int. J. Androl., 25 (2002) 262. S. Safe, Toxicol, 205 (2004) 3. S. Safe, Trends Endocrinol. Metab., 16 (2005) 139. L.W.D. Weber and H. Greim, J. Toxicol. Environ. Health, 50 (1997) 195. Opinion of the Scientific Committee on food on the risk assessment of dioxins and dioxin-like PCBs in food adopted on 30 May. Update based on new scientific information available since the adoption of the SCF opinion of 22 November 2000. European Commission, Health and Consumer Protection Directorate-General, 2001. Available at http://europa.eu.int/comm/food/fs/sc/scf/ out90_en.pdf. Accessed on February 15 2007. Joint Food and Agriculture Organization/World Health Organization (WHO) Expert Committee on Food Additives (JECFA). Polychlorinated dibenzodioxins, polychlorinated dibenzofurans, and coplanar polychlorinated biphenyls. WHO Food Additives Series 48. WHO, Geneva, 2002. Available at http://www.inchem.org/documents/jecfa/jecmono/v48je20.htm. Accessed on February 15, 2007. R.J. Kavlock, G.P. Daston, C.D. Rosa, P. Fenner-Crisp, L.E. Gray, S. Kaattari, G. Lucier, M. Luster, M.J. Mac, C. Maczka, R. Miller, J. Moore, R. Rolland, G. Scott, D.M. Sheehan, T. Sinks and H.A. Tilson, Environ. Health Perspect., 104 (1996) 715. M. Kogevinas, Human Reprod., 7 (2001) 331. Executive summary. In: Assessment of health risk of dioxins: Re-evaluation of the tolerable daily intake, WHO, Geneva, 1998, pp. 1–19. Available at http://www.who.int/ipcs/publications/en/exesum-final.pdf. Accessed on February 15, 2007. D.O. Carpenter, K.F. Arcaro, B. Bush, W.D. Niemi, S. Pang and D.D. Vakharia, Environ. Health Perspect., 106 (1998) 1263. P.K. Mandal, J. Comp. Physiol. B, Biochem. Syst. Environ. Physiol., 175 (2005) 221. L.L. Needham, D.B. Barr, S.P. Caudill, J.L. Pirkle, W.E. Turner, J. Osterloh, R.L. Jones and E.J. Sampson, Neurotoxicology, 26 (2005) 531. L.J. Guillette, D.A. Crain, M.P. Gunderson, S.A.E. Kools, M.R. Milnes, E.F. Orlando, A.A. Rooney and A.R. Woodward, Amer. Zool., 40 (2000) 438. A.T. Bosveld and M. Van den Berg, Toxicol, 181–182 (2002) 155. P. Vasseur and C. Cossu-Leguille, Chemosphere, 62 (2006) 1033. B. Bush, A. Bennett and J. Snow, Arch. Environ. Contam. Toxicol., 15 (1986) 333. W.R. Kelce, C.R. Stone, S.C. Laws, L.E. Gray, Jr, J.A. Kemppainen and E.M. Wilson, Nature, 375 (1995) 581. S.S. Raychoudhurry, A.F. Flowers, C.F. Millette and M.F. Finalay, J. Androl., 21 (2000) 964. R. Hauser, L. Altshul, Z. Chen, L. Ryan, J. Overstreet, I. Schiff and D.C. Christiani, Environ. Health Perspect., 110 (2002) 229. J. Richthoff, L. Rylander, B.A.G. Jonsson, H. Akesson, L. Hagmar, P. Nilsson-Ehle, M. Stridsberg and A. Giwercman, Environ. Health Perspect., 111 (2003) 409. A. Rignell-Hydbom, L. Rylander, A. Giwercman, B.A.G. Jo¨nsson, P. Nilsson-Ehle and L. Hagmar1, Human Reprod., 19 (2004) 2066. M. Spano`, G. Toft, L. Hagmar, P. Eleuteri, M. Rescia, A. Rignell-Hydbom, E. Tyrkiel, V. Zvyezday and J.P. Bonde, Human Reprod., 20 (2005) 3488. C. de Jager, P. Farias, A. Barraza-Villarreal, M.H. Avila, P. Ayotte, E. Dewailly, C. Dombrowski, F. Rousseau, V.D. Sanchez and J.L. Bailey, J. Androl., 27 (2006) 16. G. Toft, A. Rignell-Hydbom, E. Tyrkiel, M. Shvets, A. Giwercman, C.H. Lindh, H.S. Pedersen, J.K. Ludwicki, V. Lesovoy, L. Hagmar, M. Spano`, G.C. Manicardi, E.C. Bonefeld-Jorgensen, A.M. Hulstrup and J.P. Bonde, Epidemiology, 17 (2006) 450. A. Axmon, A.-M. Thulstrup, A. Rignell-Hydbom, H.S. Pedersen, V. Zvyezday, J.K. Ludwicki, B.A.G. Jo¨nsson, G. Toft, J.-P. Bonde and L. Hagmar, Human Reprod., 21 (2006) 657. R.W. Bretveld, C.M.G. Thomas, P.T.J. Scheepers, G.A. Zielhuis and N. Roeleveld, Reprod. Biol. Endocrinol., 4 (2006) 30. Carcinogenicity assessment of aldrin and dieldrin. US Environmental Protection Agency, Carcinogen Assessment Group, Office of Health and Environmental Assessment, Washington, DC, Report EPA/600/6-87/006, 1987.
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
501
72 D.E. Stevenson, E.F. Walborg, D.W. North, R.L. Sielken, C.E. Ross, A.S. Wright, Y. Xu, L.M. Kamendulis and J.E. Klaunig, Toxicol. Lett., 109 (1999) 123. 73 G. de Jong, G.M. Swaen and J.J. Slangen, Occup. Environ. Med., 54 (1997) 702. 74 G.M.H. Swaen, G. de Jong, J.J.M. Slangen and L.G.P.M. van Amelsvoorta, Toxicol. Ind. Health, 18 (2002) 63. 75 R.L. Sielken, R.S. Bretzlaff, C. Valdez-Flores, D.E. Stevenson and G. de Jong, Risk Anal., 19 (1999) 1101. 76 K.J. Aronson, A.B. Miller, C.G. Woolcott, E.E. Sterns, D.R. McCready, L.A. Lickley, E.B. Fish, G.Y. Hiraki, C. Holloway, T. Ross, W.M. Hanna, S.K. SenGupta and J.-P. Weber, Cancer Epidemiol. Biomarkers Prev., 9 (2000) 55. 77 P.C. Mann, Toxicol. Pathol., 25 (1997) 72. 78 K. Steenland, L. Piacitelli, J. Deddens, M. Fingerhut and L. Chang, J. Natl. Cancer Inst., 91 (1999) 779. 79 D.B. McGregor, C. Partensky, J. Wilbourn and J.M. Rice, Environ. Health Perspect., 106 (1998) 755. 80 K. Steenland, P. Bertazzi, A. Baccarelli and M. Kogevinas, Environ. Health Perspect., 112 (2004) 1265. 81 Polychlorinated dibenzo-para dioxins and polychlorinated dibenzofurans. IARC monographs on the evaluation of carcinogenic risks to humans. Vol. 69, Lyon, France, 1997, pp. 1–643. Available at http://monographs.iarc.fr/ENG/Monographs/vol69/volume69.pdf. Accessed on February 15, 2007. 82 P.A. Bertazzi, D. Consonni, S. Bachetti, M. Rubagotti, A. Baccarelli, C. Zocchetti and A.C. Pesatori, Am. J. Epidemiol., 153 (2001) 1031. 83 A.C. Pesatori, D. Consonni, S. Bachetti, C. Zocchetti, M. Bonzini, A. Baccarelli and P.A. Bertazzi, Ind. Health, 41 (2003) 127. 84 P. Cole, D. Trichopoulos, H. Pastides, T. Starr and J.S. Mandel, Reg. Toxicol. Pharmacol., 38 (2003) 378. 85 F. Caramaschi, G.D. Corno, C. Favaretti, S.E. Giambelluca, E. Montesarchio and G.M. Fara, Int. J. Epidemiol., 10 (1981) 135. 86 A.A. Panteleyev and D.R. Bickers, Exp. Dermatol., 15 (2006) 705. 87 A. Finkelstein, E. Rotman, A. Eisenkraft, A. Krivoy, I. Laish, Z. Tashma, A. Hoffman and Y. Yehezkelli, Harefuah, 144 (2005) 729. 88 S. Fierens, H. Mairesse, J.F. Heilier, C. De Burbure, J.F. Focant, G. Eppe, E. De Pauw and A. Bernard, Biomarkers, 8 (2003) 529. 89 D.H. Lee, I.K. Lee, K. Song, M. Steffes, W. Toscano, B.A. Baker and D.R. Jacobs, Diabetes Care, 29 (2006) 1638. 90 D. Pelclova, P. Urban, J. Preiss, E. Lukas, Z. Fenclova, T. Navratil, Z. Dubska and Z. Senholdova, Rev. Environ. Health, 21 (2006) 119. 91 S. Safe, Ann. Rev. Pharmacol. Toxicol., 26 (1986) 371. 92 S. Safe, S. Bandiera, T. Sawyer, L. Robertson, L. Safe, A. Parkinson, P.E. Thomas, D.E. Ryan, L.M. Reik, W. Levin, A. Denomme and T. Fujita, Environ. Health Perspect., 60 (1985) 47. 93 L. Poellinger, Food Addit. Contam., 17 (2000) 261. 94 M.E. Hahn, Chem. Biol. Interact., 141 (2002) 131. 95 J.P. Whitlock, Annu. Rev. Pharmacol. Toxicol., 39 (1999) 103. 96 J.J. Whyte, R.E. Jung, C.J. Schmitt and D.E. Tillitt, Crit. Rev. Toxicol., 30 (2000) 347. 97 J. Mimura and Y. Fujii-Kuriyama, Biochim. Biophys. Acta, 1619 (2003) 263. 98 M.S. Denison, A. Pandini, S.R. Nagy, E.P. Baldwin and L. Bonati, Chem. Biol. Interact., 141 (2002) 3. 99 B. Oesch-Bartlomowicz, A. Huelster, O. Wiss, P. Antoniou-Lipfert, C. Dietrich, M. Arand, C. Weiss, E. Bockamp and F. Oesch, Proc. Natl. Acad. Sci. USA, 102 (2005) 9218. 100 A. Puga, C.R. Tomlinson and Y. Xia, Biochem. Pharmacol., 69 (2005) 199. 101 K.W. Bock and C. Kohle, Biochem. Pharmacol., 72 (2006) 393. 102 F. Matsumura and C.F.A. Vogel, Biol. Chem., 387 (2006) 1189. 103 R.E. Peterson, H.M. Theobald and G.L. Kimmel, Crit. Rev. Toxicol., 23 (1993) 283. 104 K. Hu and N.J. Brunce, J. Toxicol. Environ. Health B, 2 (1999) 183. 105 D. Mukerjee, J. Air Waste Manage. Assoc., 48 (1998) 157. 106 J.G. Hengsteler, B. Van Der Burg, P. Steinberg and F. Oesch, Drug Metab. Rev., 31 (1999) 917.
502
Marie-Louise Scippo et al.
107 Methodologies and principles for setting tolerable intake levels for dioxins, furans and dioxin-like PCBs. Summary Report EFSA Scientific Colloquium 1, 28–29 June 2004, Brussels, EFSA. Available http://www.efsa.europa.eu/etc/medialib/efsa/science/colloquium_series/no1_dioxins/ at 599.Par.0008.File.dat/colloq01_report_v2_en1.pdf. Accessed on February 15, 2007. 108 M. van den Berg, L. Birnbaum, A. Bosveld, B. Brunstrom, P. Cook, M. Feeley, J.P. Giesy, A. Hanberg, R. Hasegawa, S. Kennedy, T. Kubiak, J.C. Larsen, F.v. Leeuwen, K. Liem, C. Nolt, R. Peterson, L. Poellinger, S. Safe, D. Schrenk, D. Tillitt, M. Tysklind, M. Younes, F. Waern and T. Zacharewski, Environ. Health Perspect., 106 (1998) 775. 109 NATO (North Atlantic Treaty Organization), International toxicity equivalence factors (I-TEF) method of risk assessment for complex mixtures of dioxins and related compounds. Pilot Study on International Information Exchange on Dioxin and Related Compounds, Report Number 176, August 1988. Committee on Challenges of Modern Society. 110 M. van den Berg, L.S. Birnbaum, M. Denison, M.D. Vito, W. Farland, M. Feeley, H. Fiedler, H. Hakansson, A. Hanberg, L. Haws, M. Rose, S. Safe, D. Schrenk, C. Tohyama, A. Tritscher, J. Tuomisto, M. Tysklind, N. Walker and R.E. Peterson, Toxicol. Sci., 93 (2006) 223. 111 M. van den Berg, R.E. Peterson and D. Schrenk, Human risk assessment and TEFs, Food Addit. Contam., 17 (2000) 347. 112 C. Bernes (Ed.), Persistent Organic Pollutants. A Swedish View of an International Problem, Swedish Environmental Protection Agency, Stockholm, 1998. 113 F.X. Van Leeuwen, M. Feeley, D. Schrenk, J.C. Larsen, W. Farland and M. Younes, Chemosphere, 40 (2000) 1095. 114 Guidance for assessing chemical contaminant, data for use in fish advisories, Vol. 1. Fish sampling and analysis, 3rd ed. EPA 823-R-95-007, Office of Water, Washington, DC, 2000. 115 Guidance for assessing chemical contaminant data for use in fish advisories, Vol. 2. Risk assessment and fish consumption limits, 3rd ed., United States Environmental Protection Agency, Washington, DC, 2000. Available at http://www.epa.gov/ost/fishadvice/volume2/index.html. Accessed on February 15, 2007. 116 COMMISSION REGULATION (EC) No 1881/2006 of 19 December 2006 setting maximum levels for certain contaminants in foodstuffs., Off. J. Eur. Union, L364 (2006) 5. 117 COMMISSION RECOMMENDATION of 6 February 2006 on the reduction of the presence of dioxins, furans and PCBs in feedingstuffs and foodstuffs., Off. J. Eur. Union, L42 (2006) 26. 118 L.H. Keith, Compilation of EPA’s sampling and analysis methods, 2nd ed, CRC Press, Boca Raton, 1996. 119 D.E. Wells and P. Hess, Separation, clean-up and recoveries of persistent trace organic contaminants from soils, sediment and biological matrices. In: E. Barcelo´ (Ed.), Sample handling and trace analysis of pollutants, techniques, applications and quality assurance, Elsevier, Amsterdam, 2000, pp. 73–116. 120 D.E. Wells and P. Hess, Determination and evaluation of chlorinated biphenyls. In: E. Barcelo´ (Ed.), Sample handling and trace analysis of pollutants, techniques, applications and quality assurance, Elsevier, Amsterdam, 2000, pp. 239–285. 121 J. De Boer J and R.J. Law, J. Chromatogr. A, 1000 (2003) 223. 122 D. Muir and E. Sverko, Anal. Bioanal. Chem., 386 (2006) 769. 123 USEPA (United States Environmental Protection Agency), EPA-1613: Tetra through octachlorinated dioxins and furans by isotopic dilution HRGC-HRMS, Washington, DC, 1994. 124 EN (European Standard)., EN-1948: European Standard, Stationary Source Emissions — Determination of the Mass Concentration of PCDDs/PCDFs, Brussels, Belgium, 1996. 125 V.W. Burse, S.L. Head, M.P. Korver, P.C. McClure, J.F. Donahue and L.L. Needham, J. Anal. Toxicol., 14 (1990) 137. 126 H.B. Greizerstein, P. Gigliotti, J. Vena, J. Freudenheim and P.J. Kostyniak, J. Anal. Toxicol., 21 (1997) 558. 127 W. Fiddler, J.W. Pensabene, R.A. Gates and D.J. Donoghue, J. Agric. Food Chem., 47 (1999) 206. 128 V. Camel, A. Tambute´ and M. Caude, J. Chromatogr., 642 (1993) 263. 129 S. Bøwadt, B. Johansson, P. Fruekilde, M. Hansen, D. Zilli, B. Larsen and J. De Boer, J. Chromatogr. A, 675 (1994) 189.
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
503
130 B. van Bavel, P. Dahl, L. Karlsson, L. Hardell, C. Rappe and G. Lindstro¨m, Chemosphere, 30 (1995) 1229. 131 E. Anklam, H. Berg, L. Mathiasson, M. Sharman and F. Ulberth, Food Addit. Contam., 15 (1998) 729. 132 R.W. Vannoort, J.-P. Chervet, H. Lingeman, G.J. De Jong and U.A. Th. Brinkman, J. Chromatogr. A, 505 (1990) 45. 133 M. Yeakub and R.B. Cole, Anal. Chem., 70 (1998) 3242. 134 V. Janda, K.D. Bartle and A.A. Cliford, J. Chromatogr., 642 (1993) 283. 135 K. Ganzler, A. Salgo and K. Valko, J. Chromatogr., 371 (1986) 299. 136 V. Lopez-Avila and J. Benedicto, Trends Anal. Chem., 15 (1996) 334. 137 C.S. Eskilsson and E. Bjo¨rklund, J. Chromatogr. A, 902 (2000) 227. 138 B.E. Richter, B.A. Jones, J.L. Ezzell, N.L. Porter, N. Avdalovic and C. Pohl, Anal. Chem., 68 (1996) 1033. 139 L. Ramos, E.M. Kristenson and U.A. Th. Brinkman, J. Chromatogr. A, 975 (2002) 3. 140 J.-F. Focant, G. Eppe, C. Pirard and E. DePauw, J. Chromatogr. A, 925 (2001) 207. 141 V. Lopez-Avila, Crit. Rev. Anal. Chem., 29 (1999) 195. 142 R.E. Majors, LC-GC Int., (September) (1998) 8. 143 C.D. Sandau, A. Sjo¨din, M.D. Davis, J.R. Barr, V.L. Maggio, A.L. Waterman, K.E. Preston, J.L. Preau, Jr, D. Barr, L.L. Needham and D.G. Patterson, Jr, Anal. Chem., 75 (2003) 71. 144 A. Sjo¨din, R.S. Jones, C.R. Lapeza, J.-F. Focant, E. McGahee, III and D.G. Patterson, Jr, Anal. Chem., 76 (2004) 1921. 145 M.J. Redondo, Y. Pico, J. Server-Carrio, J. Manes and G. Font, J. High Resolut. Chromatogr., 14 (1991) 597. 146 J. Manes, G. Font and Y. Pico`, J. Chromatogr., 642 (1993) 195. 147 Z. Cai, V.M. Sadagopa Ramanujam, D.E. Giblin and M.L. Gross, Anal. Chem., 65 (1993) 21. 148 J.W. Brock, V.W. Burse, D.L. Ashley, A.R. Najam, V.E. Green, M.P. Korver, M.K. Powell, C.C. Hodge and L.L. Needham, J. Anal. Toxicol., 20 (1996) 528. 149 A. Pauwels, D.A. Wells, A. Covaci and P.J.C. Scheppens, Organohalogen Compd., 35 (1998) 167. 150 C.-Y. Chen, J.R. Hass and P.W. Albro, Environ. Sci. Technol., 34 (2000) 5172. 151 L. Brossa, R.M. Marce´, F. Borrull and E. Pocurull, J. Chromatogr. A, 963 (2002) 287. 152 E. Abad, J. Saulo´, J. Caixach and J. Rivera, J. Chromatogr. A, 893 (2000) 383. 153 E. Eljarrat, J. Saulo´, A. Monjonell, J. Caixach and J. Rivera, Fresenius J. Anal. Chem., 371 (2001) 983. 154 A.V. Holden and K. Marsden, J. Chromatogr., 44 (1969) 481. 155 R. Loos, S. Vollmuth and R. Niessner, Fresenius J. Anal. Chem., 357 (1997) 1081. 156 L.M. Smith, Anal. Chem., 53 (1981) 2152. 157 R.R. Chang, W.M. Jarman, C.C. King, C.C. Esperanza and R.D. Stephens, Chemosphere, 20 (1990) 881. 158 R.R. Chang, W.M. Jarman and J.A. Hennings, Anal. Chem., 65 (1993) 2420. 159 C. Pirard, J.-F. Focant and E. DePauw, Anal. Bioanal. Chem., 372 (2002) 373. 160 J.F. Focant, C. Pirard and E. De Pauw, Talanta, 63 (2004) 1101. 161 A. Mu¨ller, E. Bjo¨rklund and C. von Holst, J. Chromatogr. A, 925 (2001) 197. 162 J.L. Gomez-Ariza, M. Bujalance, I. Giraldez, A. Velasco and E. Morales, J. Chromatogr. A, 946 (2002) 209. 163 F. Smedes and J. De Boer, Trends Anal. Chem., (1997) 503. 164 R.P. Snell, J.W. Danielson and G.S. Oxborrow, J. Chromatogr. Sci., 25 (1987) 225. 165 A. Covaci, J. De Boer, J.J. Ryan, S. Voorspoels and P. Schepens, Anal Chem., 74 (2002) 790. 166 A. Fernandes, S. White, K.D’. Silva and M. Rose, Talanta, 63 (2004) 1147. 167 G. Eppe, J.-F. Focant, C. Pirard and E. De Pauw, Talanta, 63 (2004) 1135. 168 J.J. Ryan, H.B.S. Conacher, L.G. Panopio, B.P.Y. Lau, J.A. Hardy and Y. Masuda, J. Chromatogr., 541 (1991) 131. 169 D. Fraisse, O. Paisse, L. Nguyen Hong and M.F. Gonnord, Fresenius J. Anal. Chem., 348 (1994) 154. 170 A.K.D. Liem, Trends Anal. Chem., 18 (1999) 499. 171 B. Larsen, M. Cont, L. Montanarella and N. Platzner, J. Chromatogr. A, 708 (1995) 115. 172 J.F. Focant, A. Sjo¨din and D.J. Patterson, J. Chromatogr. A, 1040 (2004) 227. 173 J.C. Giddings, Anal. Chem., 56 (1984) 1258A.
504
Marie-Louise Scippo et al.
174 J.F. Focant, E. Reiner, K. MacPherson, T. Kolic, A. Sjo¨din, D.J. Patterson, S. Reese, F. Dorman and J. Cochran, Talanta, 63 (2004) 1231. 175 J.B. Phillips and J. Beens, J. Chromatogr. A, 856 (1999) 331. 176 J.M.D. Dimandja, Anal. Chem., 76 (2004) 167A. 177 G. Eppe, J.F. Focant and E. De Pauw, In: W.M.A. Niessen (Ed.), The Encyclopedia of Mass Spectrometry, Hyphenated Methods, Elsevier, Amsterdam, The Netherlands, 2006, pp. 531–541. 178 E.J. Reiner, R.E. Clement, A.B. Okey and C.H. Marvin, Anal. Bioanal. Chem., 386 (2006) 791. 179 M. Lausevic, M. Splendore and R.E. March, J. Mass Spectrom., 31 (1996) 1244. 180 J.B. Plombey and R.E. March, Anal. Chem., 68 (1996) 2345. 181 R.E. March, J. Mass Spectrom., 32 (1997) 351. 182 M. Splendore, J.B. Plombey, R.E. March and R.S. Mercer, Int. J. Mass Spectrom. Ion Process., 165–166 (1997) 595. 183 J.B. Plombey, M. Lausevic and R.E. March, Mass Spectrom. Rev., 19 (2000) 305. 184 J.F. Focant, G. Eppe, M.L. Scippo, A.C. Massart, C. Pirard, G. Maghuin-Rogister and E. De Pauw, J. Chromatogr. A, 1086 (2005) 45. 185 P.A. Leclercq and C.A. Cramers, Mass Spectrom. Rev., 17 (1998) 37. 186 J.W. Cochran, J. Chromatogr. Sci., 40 (2002) 254. 187 C. Danielsson, K. Wiberg, P. Koryta´r, S. Bergek, U.A. Th. Brinkman and P. Haglund, J. Chromatogr. A, 1086 (2005) 61. 188 D.G. Patterson, S.M. Welch, W.E. Turner and J.F. Focant, Organohalogen Compd., 67 (2005) 107. 189 J. Diaz-Ferrero, M.C. Rodriguez-Larena, L. Comellas and B. Jimhnez, Trends Anal. Chem., 16 (1997) 563. 190 R.O. Harrison and R.E. Carlson, Chemosphere, 34 (1997) 915. 191 M. Shimomura, Y. Nomura, K.H. Lee, K. Ikebukuro and I. Karube, Analyst, 126 (2001) 1207. 192 J.A. Bradlaw and J.L. Casterline, J. Assoc. Off. Anal. Chem., 62 (1979) 904. 193 T. Zacharewski, M. Harris and S. Safe, Arch. Biochem. Biophys., 272 (1989) 344. 194 E. Tillitt, G.T. Ankley, D.A. Verbrugge, J.P. Giesy, J.P. Ludwig and T.J. Kubiak, Arch. Environ. Contam. Toxicol., 21 (1991) 91. 195 A. Hanberg, M. Stahlberg, A. Georgellis, C. de Wit and U.G. Ahlborg, Pharmacol. Toxicol., 69 (1991) 442. 196 S. Safe, Environ. Health Perspect., 101 (1993) 317. 197 R.W. Gale, E.R. Long, T.R. Schwartz and D.E. Tillitt, Environ. Toxicol. Chem., 19 (2000) 1348. 198 T. Bovee, Ph.D. Thesis: Development, Validation and Routine Application of the in vitro REA and DR-CALUX Reporter Gene Bioassays for the Screening of Estrogenic Compounds and Dioxins in Food and Feed, Wageningen, NL, 2005. 199 X. Sun, F. Li, Y.J. Wang, Y.R. Li, Y.H. Su, Y.Y. Li, H. Yan and S.Q. Xu, Toxicol. Sci., 80 (2004) 49. 200 G.S. Nunes, Quim. Nova, 28 (2005) 462. 201 M. Nichkova, E.K. Park, M.E. Koivunen, S.G. Kamita, S.J. Gee, J. Chuang, J.M. Van Emon and B.D. Hammock, Talanta, 63 (2004) 1213. 202 M. Nording, M. Nichkova, E. Spinnel, Y. Persson, S.J. Gee, B.D. Hammock and P. Haglund, Anal. Bioanal. Chem., 385 (2006) 357. 203 Commission Regulation (EC) No 1883/2006 of 19 December 2006 laying down methods of sampling and analysis for the official control of levels of dioxins and dioxin-like PCBs in certain foodstuffs., Off. J. Eur. Union L, 364 (2006) 32. 204 M.S. Denison, J.M.M.J.G. Aarts, L.H.J. de Haan, J.A.C. Schalk, M.A. Cox and A. Brouwer, Organohal. Comp., 13 (1993) 361. 205 BDS (BioDetection Systems). Available at http://www.biodetectionsystems.com/ 206 XDS (Xenobiotci Detection System). Available at http://www.dioxins.com/ 207 X. Cui, J. Palamanda, L. Norton, A. Thomas, Y.Y. Lau, R.E. White and K.-C. Cheng, J. Pharmacol. Toxicol. Meth., 47 (2002) 143. 208 K.E. Joung, Y.H. Chung and Y.Y. Sheen, Sci. Total Environ., 372 (2007) 657. 209 J.M. Jones and J.W. Anderson, Environ. Toxicol. Pharmacol., 7 (1999) 19. 210 M. Long, P. Laier, A.M. Vinggaard, H.R. Andersen, J. Lynggaard and E.C. Bonefeld-Jorgensen, Toxicol, 194 (2003) 77.
Persistent Organochlorine Pollutants, Dioxins and Polychlorinated Biphenyls
505
211 Z.R. Zhang, S.Q. Xu, X. Sun, Y.J. Xu, X.K. Cai, Z.W. Liu, X.L. Tan, Y.K. Zhou, J.Y. Zhang and H. Yan, World J. Gastroenterol., 9 (2003) 1460. 212 I. Windal, M.S. Denison, L.S. Birnbaum, N. Van Wouwe, W. Baeyens and L. Goeyens, Environ. Science Technol., 39 (2005) 7357. 213 L. Hoogenboom, L. Goeyens, S. Carbonnelle, J. van Loco, H. Beernaert, W. Baeyens, W. Traag, T. Bovee, G. Jacobs and G. Schoeters, Trends Anal. Chem., 25 (2006) 410. 214 M.S. Denison and S.R. Nagy, An. Rev. Pharmacol. Toxicol., 43 (2003) 309. 215 N. Van Wouwe, I. Windal, H. Vanderperren, G. Eppe, C. Xhrouet, E. De Pauw, L. Goeyens and W. Baeyens, Talanta, 63 (2004) 1269. 216 M.L. Scippo, G. Eppe, E. De Pauw and G. Maghuin-Rogister, Talanta, 63 (2004) 1193. 217 I. Van Overmeire, J. Van Loco, P. Roos, S. Carbonnelle and L. Goeyens, Talanta, 63 (2004) 1241. 218 M. Engwall, G. Lindstro¨m and B. Van Bavel, In: M. Engwall (Ed.), The First Round of Inter¨ rebro University, Laboratory Comparison of Dioxin-Like Coumpounds in Food Using Biosassays, O Sweden, 2003. 219 M. Engwall and B. Van Bavel, In: M. Engwall (Ed.), The Second Round of Inter-Laboratory ¨ rebro University, Sweden, 2004. Comparison of Dioxin-Like Coumpounds in Food Using Biosassays, O 220 G. Gizzi, L.A.P. Hoogenboom, C. Von Holst, M. Rose and E. Anklam, Food Add. Contam., 22 (2005) 472. 221 J. Van Loco, S.P.J. Van Leeuwen, P. Roos, S. Carbonnelle, J. De Boer, L. Goeyens and H. Beernaert, Talanta, 63 (2004) 1169. 222 H.T. Besselink, E. Felzel, A. Jonas and A. Brouwer, Organohalogen Compd., 68 (2006) 249. 223 K.S. Schafer, S.E. Kegley and S. Patton, Nowhere to Hide. Persistent Toxic Chemicals in the us Food Supply, 2nd ed., Pesticide Action Network North America y Commonweal, San Francisco, 2001. Available at http://www.panna.org/resources/documents/nowhereToHideAvail.dv.html. Accessed on February 15, 2007. 224 International Programme on Chemical Safety. Inventory of IPCS and other WHO pesticide evaluations and summary of toxicological evaluations performed by the Joint Meeting on Pesticide Residues (JMPR). Evaluations through 2002, 7th edition. Available at http:// www.inchem.org/documents/jmpr/jmpeval/jmpr2002.htm. Accessed on February 15, 2007. 225 P.O. Darnerud, S. Atuma, M. Aune, R. Bjerselius, A. Glynn, K.P. Grawe and W. Becker, Food Chem. Toxicol., 44 (2006) 1597. 226 EFSA. Opinion of the scientific panel on contaminants in the food chain on a request from the commission related to hexachlorobenzene as undesirable substance in animal feed. The EFSA J., 402 (2006) 1. Available at http://www.efsa.europa.eu/etc/medialib/efsa/science/contam/ contam_opinions/ej402_hexachlorobenzene.Par.0001.File.dat/CONTAM_op_ej402_hexachlorobenzene_en.pdf. Accessed on February 15, 2007. 227 EFSA. Opinion of the scientific panel on contaminants in the food chain on a request from the commission related to endrin as undesirable substance in animal feed. The EFSA J., 286 (2005) 1. Available at http://www.efsa.europa.eu/etc/medialib/efsa/science/contam/contam_opinions/ 1252.Par.0001.File.dat/contam_op_ej286_endrin_en1.pdf. Accessed on February 15, 2007. 228 EFSA. Opinion of the scientific panel on contaminants in the food chain on a request from the commission related to aldrin and dieldrin as undesirable substance in animal feed. The EFSA J., 285 (2005) 1. Available at http://www.efsa.europa.eu/etc/medialib/efsa/science/contam/ contam_opinions/1251.Par.0001.File.dat/contam_op_ej285_aldrinanddieldrin_en1.pdf. Accessed on February 15, 2007. 229 L. Pussemier, L. Mohimont, A. Huyghebaert and L. Goeyens, Talanta, 63 (2004) 1273. 230 C. Saegerman, D. Berkvens, F. Boelaert, N. Speybroeck, I. Van Vlaenderen, M. Lomba, A. Ermens, P. Biront, F. Broeckaert, A. De Cock, L. Mohimont, S. Demont, G. De Poorter, B. Torfs, J.M. Robijns, V. Monfort, J.P. Vermeersch, L. Lengele and A. Bernard, J. Toxicol. Env. Health, 65 (2002) 1289. 231 A.J. Baars, M.I. Bakker, R.A. Baumann, P.E. Boon, J.I. Freijer, L.A.P. Hoogenboom, R. Hoogerbrugge, J.D. van Klaveren, A.K.D. Liem, W.A. Traag and J. de Vries, Toxicol. Lett., 151 (2004) 51. 232 J.M. Llobet, J.L. Domingo, A. Bocio, C. Casas, A. Teixido and L. Muller, Chemosphere, 50 (2003) 1193.
506
Marie-Louise Scippo et al.
233 X.G. Guo, M.P. Longnecker and J.E. Michalek, J. Toxicol. Env. Health, 63 (2001) 159. 234 Y. Lind, P.O. Darnerud, M. Aune and W. Becker, Exposure to organic environmental pollutants via foods. Intake calculations for ~PCBs, PCB-153, ~DDT, p,pu-DDE, PCDD/PCDF, dioxin-like PCB, PBDE and HBCD based on consumption data from Riksmaten 1887–98 (in Swedish). NFA Report no. 26-2002, National Food Administration, Sweden, 2002 235 H.B. Matthews and R.L. Dedrick, Pharmacokinetics of PCBs, Annu. Rev. Pharmacol. Toxicol., 24 (1985) 85. 236 G.F. Fries and D.J. Paustenbach, J. Toxicol. Environ. Health, 29 (1990) 1. 237 C.A. Kan and G.A.L. Meijer, Anim. Feed Sci. Technol., 133 (2007) 84. 238 H. Kiviranta, A. Hallikainen, M.L. Ovaskainen, J. Kumpulainen and T. Vartiainen, Food Addit. Contamin., 18 (2001) 945. 239 S. Patandin, P.C. Dagnelie, P.G.H. Mulder, E.O. de Coul, J.E. van der Veen, N. Weisglas-Kuperus and P.J.J. Sauer, Environ. Health Perspect., 107 (1999) 45. 240 J.I. Freijer, R. Hoogerbrugge, J.D. van Klaveren, W.A. Traag, L.A.P. Hoogenboom, A.K.D. Liem, Dioxins and dioxin-like PCBs in foodstuffs: Occurrence and dietary intake in The Netherlands at the end of the 20th century. RIVM report 639102 022, Bilthoven, 2001. 241 WHO (World Health Organization) PCBs and dioxins in salmon. WHO, Geneva, 2005. Available at http://www.who.int/foodsafety/chem/pcbsalmon/en/print.html. Accessed on February 15, 2007. 242 EFSA, Opinion of the CONTAM Panel related to the safety assessment of wild and farmed fish. Available at http://www.efsa.europa.eu/etc/medialib/efsa/science/contam/contam_opinions/ 1007.Par.0005.File.dat/contam_opinion_ej236_swaff_v2_en1.pdf. Accessed on Febuary 15, 2007. 243 J. Burger, M. Gochfeld, S. Burke, C.W. Jeitner, S. Jewett, D. Snigaroff, R. Snigaroff, T. Stamm, S. Harper, M. Hoberg, H. Chenelot, R. Patrick, C.D. Volzi and J. Weston, Environ. Res., 101 (2006) 34. 244 R.A. Hites, J.A. Foran, D.O. Carpenter, M.C. Hamilton, B.A. Knuth and S.J. Schwager, Science, 303 (2004) 226. 245 X.Y. Huang, R.A. Hites, J.A. Foran, C. Hamilton, B.A. Knuth, S.J. Schwager and D.O. Carpenter, Environ. Res., 101 (2006) 263. 246 J.L. Domingo, A. Bocio, G. Falco` and J.M. Llobet, Toxicology, 230 (2007) 219. 247 J.A. Foran, D.O. Carpenter, D.H. Good, M.C. Hamilton, R.A. Hites, B.A. Knuth and S.J. Schwager, Am. J. Prev. Med., 30 (2006) 438. 248 J. Willems, J. Van Camp, W. Verbeke and K. Cooreman, Integrated evaluation of marine food items: Nutritional value, safety and consumer perception. Scientific support plan for a sustainable development policy (SPSD II). Part 1: Sustainable production and consumption patterns. Final report CP/56, 2006. Available at http://www.belspo.be/belspo/home/publ/pub_ostc/CPagr/ rappCP56_en.pdf. Accessed on February 15, 2007. 249 J.L. Domingo and A. Bocio, Environ. Int., (2007) 397. 250 I. Van Overmeire, L. Pussemier, V. Hanot, L. De Temmerman, M. Hoenig and L. Goeyens, Food Add. Contam., 23 (2006) 1109. 251 G.K. Carvalhaes, P. Brooks, C.G. Marques, J.A.T. Azevedo, M.C.S. Machado and G.C. Azevedo, Lime as the source of PCDD/F contamination in citrus pulp pellets from Brazil and status of the monitoring program, Chemosphere, 46 (2002) 1413. 252 D.P. Drotman, P.J. Baxter, J.A. Liddle, C.D. Brokopp and M.D. Skinner, Am. J. Public Health, 73 (1983) 290. 253 A. Bernard, C. Hermans, F. Broeckaert, G. De Poorter, A. De Cock and G. Houins, Nature, 401 (1999) 231. 254 A. Bernard, F. Broeckaert, G. De Poorter, A. De Cock, C. Hermans, C. Saegerman and G. Houins, Environ. Res., 88 (2002) 1. 255 B. Vrijens, S. De Henauw, K. Dewettinck, W. Talloen, L. Goeyens, G. De Backer and J.L. Willems, Food Addit. Contam., 19 (2002) 687. 256 A.D. Benninghoff, Toxicol. Sci., 95 (2007) 1.
CHAPT ER
15 Brominated Flame Retardants as Food Contaminants Adrian Covaci, Stefan Voorspoels, Kyle D’Silva, Janice Huwe and Stuart Harrad
Contents
1. Introduction 1.1 Definition and classification of BFRs 1.2 Physical and chemical properties 1.3 Toxicological aspects of BFRs 2. Analytical Methods 2.1 Sample preparation 2.2 Instrumental analysis 2.3 Quality assurance/quality control 3. Occurrence in Food 3.1 PBDE levels in food and dietary intake in North and South America 3.2 PBDE levels in food and dietary intake in Europe and Asia 3.3 Levels of HBCDs and TBBP-A in food and dietary intake 3.4 PBDD/Fs 4. Regulatory/Safety Aspects and On-Going Monitoring Programmes 5. Future Trends in the BFR Research in Food Acknowledgement References
507 507 509 510 512 512 526 540 542 542 548 556 559 560 562 563 563
1. INTRODUCTION 1.1 Definition and classification of BFRs Brominated flame retardants (BFRs) are currently the largest market group of flame retardants (FRs) because of their low cost and high efficiency. Currently, there are more than 75 different BFRs recognized commercially [1]. The five
Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00015-9
r 2008 Elsevier B.V. All rights reserved.
507
508
Adrian Covaci et al.
Polybrominated diphenyl ether (PBDE)
Polybrominated biphenyl (PBB)
O
Brx
Brx
Bry
x+y= 1 to 10
Tetrabromobisphenol-A (TBBPA)
Bry
x+y= 1 to 10
Hexabromocyclododecane (HBCD)
Br
Br
Br
CH3
Br
HO
OH
Br
CH3
Br
Br
Br
Br Br
Polybrominated Dibenzo-p-dioxins (PBDDs) 4
4
6
O
3 Brx
Polybrominated Dibenzofurans (PBDFs)
7
2
8 1
Brx
Bry
7
2
8 1
9
O
6
3
1,2-Bis(2,4,6-tribromophenoxy)ethane (BTBPE) Br
9
O
x+y = 1 to 8
Decabromodiphenylethane Br
Br Br
Br
Br
O
Bry
Br
Br Br
Br
Br
O
Br
Br Br
Br
Br
Figure 1 Chemical structures of the most important brominated flame retardants.
major BFRs are tetrabromobisphenol-A (TBBP-A), hexabromocyclododecanes (HBCDs), and three technical mixtures of polybrominated diphenyl ethers (PBDEs): penta-BDE, octa-BDE, and deca-BDE (Figure 1). The production of some BFRs, such as the polybrominated biphenyls (PBBs), ceased some time ago, and can therefore be regarded as ‘‘legacy’’ pollutants.
Brominated Flame Retardants as Food Contaminants
509
PBDEs, HBCDs, and TBBP-A are used as additive or reactive components in a variety of polymers, such as polystyrene foams, high-impact polystyrene and epoxy resins, which are further used in a wide range of consumer products, including computers, electronics and electrical equipment, televisions, textiles, foam-padded furniture, insulating foams, and other building materials. BFR production has increased dramatically over the past 20 years, with the largest relative increase in market demand at this time being found in Asia. More than 200,000 metric tons of BFRs are produced each year [2]. Although hexa-BB is one of the 16 compounds or groups of compounds included in the Persistent Organic Pollutants (POPs) Protocol to the UN/ECE Convention on Long Range Transboundary Air Pollution (LRTAP), currently BFRs are not included within the aegis of the Stockholm Convention on POPs. However, penta-BDE is one of the five compounds or compound classes under active consideration for future inclusion within the scope of the Convention. Penta-BDE was also identified as a hazardous substance by the European Commission and is now included in the list of priority substances annexed to the European Water Framework Directive [3,4]. Polybrominated dibenzo-dioxins and furans (PBDD/Fs) have no perceptible commercial use and are not manufactured. They occur as trace contaminants in some BFR products and can also be produced during combustion or degradation of these chemicals [5]. PBDD/Fs are structurally similar to the corresponding chlorinated dioxins and furans (PCDD/Fs) and are possibly more toxic [6]. Significant concentrations of PBDFs were recently found in technical PBDE mixtures (DE-71, DE-79, and DE-83) by Hanari et al. [7]. Spillage and emissions occur during production and use, but also as a result of disposal at the end-of-life of products in which they are employed, account for the widespread presence of BFRs in the environment, food, and humans. Dietary ingestion is believed to be a primary exposure vector of BFRs and PBDD/Fs to humans. Consequently, their accurate analysis in food has become very important if we are to understand the risks associated with these compounds balanced against their benefits.
1.2 Physical and chemical properties PBDEs: The commercial products are waxy solids, have boiling points between 3101C and 4251C [8] and have low vapour pressures ranging from 3.9 to 13.3 Pa at 20–251C [9]. Their solubility in water is very poor, especially that of the higher BDEs. The n-octanol/water partition coefficient (log Kow) ranges between 4.3 and 9.9 [9]. PBDEs are thermally labile and break down readily with heat, which enables them to act as effective FRs. Both aliphatic and aromatic carbon–bromine covalent bonds are relatively weak due to the large atomic size of bromine. As a result, polybrominated organics, including PBDEs, tend to break down often with the cleavage of an HBr leaving group [10]. This reactive leaving group ‘quenches’ the flame preventing further ignition. Higher BDEs, such as BDE 209 in particular, also can degrade upon exposure to UV light [11,12]. This can be
510
Adrian Covaci et al.
particularly problematic during analysis if no proper measures are taken to prevent UV degradation. PBBs: PBBs are similar in their structure, use, manufacture, contamination pathways, and toxicological impact as PBDEs [13]. PBBs have similar physicochemical properties to PBDEs: PBBs are also solids with low volatility and water solubility that decreases with increasing bromine number [13]. These compounds are relatively stable and chemically unreactive. However, they are also thermally labile and susceptible to photo-degradation in the environment [14]. The convention regarding systematic numbering of PBB and PBDE congeners is analogous to that of polychlorinated biphenyls (PCBs; [15]) — there are 209 possible PBB and PBDE congeners. However, PBB formulations tend to contain a lower number of congeners compared to PCB formulations [13]. HBCDs: Aliphatic brominated compounds are less thermally stable than their aromatic analogues [10]. Technical HBCD is highly labile and readily decomposes at 2301C, just a little over its melting point (178–1831C) [1]. It is a yellowish white, waxy odourless solid (vapour pressure: 0.0002 Pa at 201C) that is practically insoluble in water (0.002 g/100 mL at 201C), but readily soluble in organic solvents, and has a log Kow value of 7.6. HBCD has a half-life of 3 days in air and 2–25 days in water [16]. It exists predominantly as three different isomers (a, b, and g). However, the relative abundance of these isomers in the technical formulations is very different from that in environmental media. Research has revealed that environmental transformation and interconversion of the HBCD isomers occurs [17]. HBCD has been found in sediments that are several decades old, indicating it to be persistent [18]. TBBP-A: TBBP-A is a white crystalline powder, with a melting point of approximately 1801C and boiling point of 3161C. It is non-volatile with a vapour pressure much less than 1 mm Hg at 201C. TBBP-A has a low solubility in water (log Kow ¼ 4.5), but is very soluble in methanol and acetone [19]. UV light and bacteria can both degrade TBBP-A. The main UV photolysis product is 2,4,6tribromophenol among a number of other decomposition products, including bromobenzenes and bisphenol-A [20]. Environmental photolytic degradation of TBBP-A has a half-life ranging from 7 to 81 days in water. Moreover, bacteria degrade TBBP-A in soils and sediments under both aerobic and anaerobic conditions with a half-life of approximately 2 months [16]. PBDD/PBDFs: Theoretically, there are a total of 210 PBDD/Fs congeners. Generally, PBDD/Fs resist chemical transformations, have a low biological degradation rate, and are lipophilic, chemically stable and persistent [21]. PBDD/ Fs in soil have been shown to decompose photolytically under daylight in laboratory conditions and degradation typically occurred via debromination [22]. Half-lives for some isomers were up to 160 days.
1.3 Toxicological aspects of BFRs To fully understand the toxicology of BFRs, information on their effects in wildlife and, especially, in man is still inadequate. Several reviews have covered the knowledge on this subject and a summary of the biological effects presented
Brominated Flame Retardants as Food Contaminants
511
in these reviews is given below [6,16,23,24]. In addition, new data from some recent publications are also included. PBDEs: Generally, the lower BDEs (tri- to hexa-congeners), present in the penta-BDE formulation, are more bioavailable and persistent and, therefore, cause adverse effects at lower doses than the octa- and deca-BDE formulations. Thyroid hyperplasia, decreased T4 levels at 10 mg/kg body weight (bw) and effects in the liver at 2 mg/kg bw have been observed in dosing studies with rats. The noobserved effect levels (NOELs) were established at 1 mg/kg for penta-BDE, 100 mg/kg for octa-BDE, and W1,000 mg/kg for deca-BDE [23]. Fetal toxicity/ teratogenicity has been demonstrated for octa-BDE in rats and rabbits from 2 mg/ kg bw [24]. Carcinogenicity studies, only performed for deca-BDE, showed increased incidences of neoplastic nodules in the livers of rats at the lowest dose tested (1,200 mg/kg bw/d) [25]. However, deca-BDE is not listed as human carcinogen by the International Agency for Research in Cancer (IARC) [26]. Of more concern are effects on neurobehavioural development, thyroid hormone homeostasis, and other potential endocrine disruptions that can occur at much lower doses. Developmental neurotoxic effects have been observed in mice in a dose- and time-dependent manner for BDEs 47, 99, 153, 183, 203, 206, and 209 [27– 29] and in mice and rats for the major congeners in penta-BDE [30]. A NOEL for BDE 99 was found between 0.4 and 0.8 mg/kg bw [28]. Serum thyroid hormone levels (T3 and T4) in rats and mice decreased after oral exposure to commercial penta-BDE and octa-BDE formulations or their major components [23,24]. DecaBDE had no effect on serum T4 and T3 levels or hepatic EROD (ethoxyresorufin-Odealkylase) activity in rats after oral administration [31]. American kestrel nestlings exposed to environmentally relevant concentrations of PBDEs (100 mg/ kg in food) showed decreased plasma T4 levels, immune system modulations, and other metabolic changes [32,33]. In a battery of in vitro tests, Hamers et al. [34] demonstrated effects of various PBDEs on androgenic, estrogenic, thyroidal, progestagenic, and aryl hydrocarbon receptor (AhR) endocrine systems. HBCDs: Compared to PBDEs, the toxicological database for HBCDs is still limited. Acute toxic effects appear to be low [16,24]. However, there are indications that oral exposure to HBCDs induces drug-metabolizing enzymes in rats, such as hepatic cytochrome P450 [35] and that HBCDs may induce cancer by a non-mutagenic mechanism [36]. There are reports that HBCDs can disrupt the thyroid hormone system [24,34] and affect the thyroid hormone receptormediated gene expression [37]. Following neonatal exposure in rats, developmental neurotoxic effects, such as aberrations in spontaneous behaviour, learning, and memory function, were observed already at 0.9 mg/kg bw [29]. HBCDs can also alter the normal uptake of neurotransmitters in rat brain [38]. TBBP-A: Rodent studies have indicated that TBBP-A is not acutely toxic and does not produce adverse effects on behaviour, appearance, food consumption, body weight gain, or mortality in rats at up to 100 mg/kg bw/d in 30- and 90-day exposure studies [19]. TBBP-A is more toxic in fish and marine species (LC50o1 mg/L) [19]. Up to now, no long-term exposure data are available [19]. In vitro studies have shown TBBP-A to be hepatotoxic, immunotoxic, and neurotoxic [16]. The endocrine disrupting ability of TBBP-A has been
512
Adrian Covaci et al.
demonstrated in vitro for the thyroid hormone and oestrogen systems [34,39–41]. Results from these studies showed that the binding affinity of TBBP-A to transthyretin (TTR) is 2–10 times greater than that of T4, that TBBP-A is a relatively potent estradiol sulfotransferase inhibitor, and that TBBP-A induces thyroid hormone-dependent production of growth hormone in cells. In ovariectomized mice, TPPB-A also showed dose-dependent oestrogenic activity between 20 and 500 mg/kg bw/d [40]. PBDD/Fs and PBBs: These classes of brominated compounds are thought to exhibit similar toxicities to their chlorinated counterparts, which have been studied in depth. The limited data available on the toxicity of PBDD/Fs suggests a classic dioxin-like mode of action [5,6]. In vitro assays of enzyme induction or AhR-binding potency show the brominated analogues to be generally less active than chlorinated analogues. However, tri-BDDs were more potent than tri-CDDs and tetrabrominated dibenzo-p-dioxin (TBDD) was more potent than or as potent as tetrachlorodibenzodioxin (TCDD) in CYP1A1 enzyme induction, in causing thymic atrophy, and in acute toxicity in several species [6]. The WHO has established toxic equivalency factors (TEFs) for PBDD/Fs equivalent to the corresponding PCDD/Fs for the present time. In animal studies, PBBs were found to cause cancer, thymic atrophy, wasting syndrome and delayed death, immune suppression, and reproductive effects leading to decreased fetal viability [9]. The major sites of toxicity were the liver, where lesions, carcinomas, and enzyme induction occurred, and the thymus, where weight loss and atrophy was observed. In occupationally exposed cohorts, chloracne and hypothyroidism were present [9]. Other studies have shown that PBBs elicit similar or greater toxic responses than PCBs in early-life trout mortality studies and in immune responses in human granulocytes [42]. To conclude, the acute toxicity of the most prevalent BFRs appears to be low in most cases. However, neurodevelopmental, immunogenic, and endocrine disrupting effects can occur at low and even environmentally relevant levels. These more subtle adverse outcomes are a major concern and further research on the actual levels at which these effects occur is needed because BFRs will continue to appear both in industrial applications and, even after the production has ceased, in our environment.
2. ANALYTICAL METHODS 2.1 Sample preparation The tremendous growth observed in previous years in the number of papers dealing with the determination of the BFR in different environmental and biological matrices has developed a wide variety of analytical approaches for both sample preparation and instrumental analysis. There are already several reviews [43–47] that pointed out these progresses. For PBDEs, analytical procedures have been derived from previously established protocols based on gas chromatography-mass spectrometry (GC-MS) for trace POPs, such as
Brominated Flame Retardants as Food Contaminants
513
organochlorine pesticides, PCBs or PCDD/Fs. However, due to particular physico-chemical properties, the determination of individual HBCD diastereoisomers and TBBP-A requires specific analytical approaches based on liquid chromatography-mass spectrometry (LC-MS). Because of the complexity of matrices and the low levels at which these compounds are present in food samples, such analytical procedures include a number of steps for exhaustive extraction and preconcentration of the target compounds, followed by purification and fractionation before final chromatographic separation and detection. The similarities among the analytical methods have allowed the simultaneous determination of several families of BFR microcontaminants [48].
2.1.1 Extraction The selection of the extraction technique depends on the nature (solid or liquid) of the investigated matrices. The amount of sample required varies largely depending on the contamination level anticipated in the sample and on the detection power provided by the chosen technique. The yield of the extraction procedure is determined by several factors such as the analyte solubility in the extraction mixture, the accessibility of the extraction solvent to the matrix and the extraction time. The first two factors determine the equilibrium that can be reached at a certain stage of the extraction, whereas accessibility and extraction time are more related to the kinetics of the extraction. A non-polar organic solvent, like hexane, may have a high solubility for most BFRs, but does not have access to the inner part of biological tissues, which contain many polar groups. Conversely, polar solvents such as methanol can lead to the excessive extraction of interferences from complex matrices, such as food. Table 1 summarizes relevant methods related to BFRs in feedstuffs, foodstuffs, and animal tissue samples from recent publications. Homogenization and drying of samples are usually the only universal steps carried out before extraction. Soxhlet extraction is one commonly used method for fish and food composite samples. The duration of a Soxhlet extraction is usually 12–24 h and requires 200–300 mL solvent. For fish tissues, PBDEs have been efficiently extracted from lyophilized fillets with toluene or with dichloromethane (DCM):n-hexane (1:1, v/v). The former resulted in recoveries greater than 60% of 15 tri- to heptaBDEs [60] and the latter in recoveries ranged from 47% to 75% for 16 tri- to hepta-BDEs [72]. In addition to the PBDEs, these authors also reported the co-extraction of PCDDs/Fs, PCBs, and polychlorinated naphthalenes (PCNs). Recoveries above 50% were achieved for 5 tetra- to hexa-BDEs from freeze-dried duplicate diet samples using DCM:n-hexane (1:1, v/v) [95] or from freeze-dried market basket composites using toluene [94]. Toluene, DCM:n-hexane (1:1, v/v), or petroleum ether were also efficient in extracting tetra- to octa-BDEs from freeze-dried food composites, such as vegetables, fruit, cereals, eggs, milk, dairy products, meat, and fish (54–115% recoveries) [91,93]. For vegetable extracts, Ohta et al. [83] removed chlorophyll and other pigments from vegetable samples by adding silver nitrate-impregnated silica gel that was allowed to react for 12 h with the extract and then filtered away.
Fish feed and fish (10–100) Fish and vegetable oil (0.5–0.7)
Fish oil (5)
Bivalves (1–5)
Fish (0.5)
Fish tissue (40)
Fish tissue
Mono-deca-BDEs (35)
Tri-hexa-BDEs (8)
Tri-deca-BDEs (22)
Tetra-hexa-BDEs (6)
Tri-hepta-BDEs (15)
Tri-hepta-BDEs (7)
Tri-hepta-BDEs (7)
Fish feed, fish, and shellfish (1.5) Fish feed, fish, and shellfish (1)
Tetra-penta-BDEs (3)+PBBs (2) Tetra-penta-BDEs (3)+PBBs (2)
Freeze-dry+mixing with Na2SO4
Freeze-drying
Freeze-dried and reconstituted with 0.5 mL H2O
Homogenization+dry at 701C+Hydromatrix
–
Homogenization+ mixing with Na2SO4 –
Grind+freeze-dry
PLE (C6, 10 MPa)
MSPD (C18, 1 g+ Al2O3, 30 mL Hex) SFE (in-cell basic Al2O3+SiO2–H2SO4; CO2, 601C)+C18 trap (251C) Column extraction (Cyclohex:DCM) Ultrasonic bath extraction (Hex, 5 min) PLE with acidified silica (Hex) PLE (Acet:DCM, 1:1, 1001C, 11 MPa, 2) MSPD (Na2SO4, 2 g +Florisils, 1.5 g)+ SiO2–H2SO4 (C6, 20 mL) Soxhlet (Tol, 20 h)
Preservative, dechlorinating, and complexing agents
Surface and ground water (1,000)
Tetra-hexa-BDEs (4) +Hexa-BB+HBCDs +TBBP-A
Freeze-drying
HS-SPME (PDMS, 1001C, stirring, 30 min) PDMS stir bar (ambient T, 20–25 h) SDVB solid-phase extraction disk
Filtration; KHCO3/ NaCl+acetic anhydride MeOH addition (20%)
Tap water+ wastewater (10) Surface water (100)
TBBP-A+ bromophenols (7) Tri-hexa-BDEs (9)
SiO2–H2SO4+Carbon+ Al2O3 SiO2–H2SO4+SiO2 KOH+basic Al2O3
GC-ITD-MS/MS
GC-EI-MS
GC-ECD
Fractionation on SiO2 (2 g), elution with DCM:Hex (1:4)
GC-ECNI-MS
SiO2–H2SO4
GC-MS/MS or GC-EI-LRMS GC-ECD
GC-EI-HRMS
GPC on-line with graphitized carbon GPC+Florisils
GC-ITD-MS/MS
Desorption from C18 trap (Hex, 2 mL)+ HS-SPME (751C, 60 min) SiO2–H2SO4; Al2O3
33–104
W 60
81–106
W 50
89–101
92–101
70–117
82–101
GC-ITD-MS/MS
GC-MS
_
94–106
–
PTV-GC-EI-MS
_
Tetra-pentaBDEs: 87–109 Hexa-BDEs: ND-7 TBBP-A: 20–109
Recovery (%)
PBDEs: 78–93 Hexa-BB: 83–95 TBBP-A: 93–107 HBCDs: 32–124 70–96
GC-ITD-MS/MS
GC-ITD-MS/MS
Instrumental analysis
–
–
Extraction procedure Clean-up HS-SPME (PDMS, 1001C, stirring, 30 min)
Tap water+ wastewater (10)
Tetra-hexa-BDEs (6)
Pretreatment
Filtration
Sample type (g, mL)
Overview of typical analytical procedures used for the determination of PBDEs, HBCDs, and TBBP-A in selected matrices
BFRs (# of congeners)
Table 1
[61]
[60]
[59]
[58]
[57]
[56]
[55]
[54]
[53]
[52]
[51]
[50]
[49]
Reference
Fish and mussels (4)
Fish
Fish (10)
Fish
Fish (10)
Fish (10)
Fish and shellfish (25)
Fish
Mono-hepta-BDEs (23)
Tetra-hepta-BDEs (8)
Tetra-hexa-BDEs (6)
Mono-deca-BDEs (43)
Di-hexa-BDEs (13)
Tri-hepta-BDEs (18)
Tri-hepta-BDEs (13)
Fish tissues Fish tissues (3–5) Fish tissue (0.5)
Tetra-hepta-BDEs (6) Tri-deca-BDEs (27) Mono-deca-BDEs (40), total HBCD Tetra-penta-BDEs (3)
Column extraction (EtOAc: petr. ether, 10:90)
Mixing with Na2SO4
Freeze-drying
_
Soxhlet (150 mL DCM:Hex, 1:1, 24 h)
SLE (Acet:Hex, 200 mL); water wash; Na2SO4 to dry
Column extraction (DCM:Hex, 1:1)
Soxhlet (DCM, 16 h)
Mixing with Na2SO4
Mixing with Na2SO4
PLE (DCM, 1001C, 68 atm)
Freeze-drying
Mixing with Na2SO4
Soxhlet (DCM, 24 h) PLE (DCM) PLE (Al2O3, DCM:Hex, 1:1, 1001C, 10 Mpa) MAE (DCM:Pent, 1:1; 1151C) or Soxhlet (DCM, 150 mL, 6 h) Column extraction (300 mL DCM)
Mixing with Na2SO4 Mixing with Na2SO4 Freeze-dry +homogenization Mixing with Na2SO4
GPC on Biobeadst S-X3 (DCM:Hex)+SiO2 (DCM) GPC on Envirobeadss S-X3 (EtOAC); Florisils (EtOAc:Hex, 7:93) GPC on Envirosept (DCM); SiO2 SPE (DCM:Hex, 3:2) GPC on Biobeadst S-X3; Florisils, SiO2, and Al2O3 Multi-layer silica (basic, neutral, acidic, neutral) (DCM:Hex, 1:1); Al2O3 (DCM:Hex, 1:1) GPC on Envirogelt (DCM); SiO2+ SiO2–H2SO4 (Hex); Florisils (DCM); Carbopak (Hex and Hex:DCM, 2:1) Multi-layer silica (AgNO3/neutral/ acidic/neutral/ basic/neutral); Al2O3; Florisils; GPC on Biobeadst S-X-3 (DCM:Hex, 1:1)
SiO2–H2SO4+GPC
GPC or Al2O3+Florisils GPC+SiO2 –
47–75
66
GC-EI-HRMS
GC-EI-HRMS
n.r.
83
GC-EI-MS
GC-EI-HRMS
95–110
GC-ECNI-MS
n.r.
65–120
GC-EI-HRMS
GC-EI-HRMS
89–97
98 76–80 52–103
GC-EI-MS
GC-MS GC-ECNI-MS GC-ECNI-MS
[72]
[71]
[70]
[69]
[68]
[67]
[66]
[65]
[62] [63] [64]
Adipose (6–20)
No matrix
Dairy products and fish (5–10)
Mono-penta-BDD/Fs
Mono-penta-BDD/Fs
Tri-hepta-BDEs (10)+ PBBs (5)
Freeze-dry; grind with SiO2:Na2SO4 (1:1)
–
Mixing with Na2SO4
Freeze-drying
SFE (Na2SO4+Al2O3, CO2, 401C)+C18 trap MSPD (Acet:Hex, 1:1)
Column extraction (DCM:Hex, 1:1)
SFE (basic Al2O3, CO2, 401C)+ C18 trap (401C) PLE (Hex, 1001C, 1,500 psi)
Mixing with Na2SO4
Methoxy-PBDEs (5)+ Mono-hexa-BDEs (22) Tetra-hepta-BDEs (14)+PBDD/Fs (9)
Soxhlet (6–12 h, Hex:Acet, 3:1)
Mixing with Na2SO4
Fish, mussels, and marine mammals Fish, adipose, liver, and milk fat (1) Fish, shellfish, and seaweed (20–100)
Tetra-deca-BDEs (6)
Column extraction (Acet:Hex, 7:3+ DE:Hex, 1:9)
Mixing with Na2SO4
Soxhlet (Acet:Hex, 1:1, 4 h)
Mixing with Na2SO4
Fish muscle and porpoise blubber (5) Fish (10–25)
a-,b-,gHBCD TBBP-A
Methoxy-PBDEs+ PBDEs
Soxhlet (DE:Hex or DCM)
Mixing with Na2SO4
Tuna (20)
Mono-deca-BDEs (11)+a-,b-,gHBCD
GC-EI-MS GC-ECNI-MS
GC-ECNI-MS
GC-EI-HRMS
LC-ESI-MS
GC-EI-MS for PBDEs; LC-ESI-MS/MS for HBCDs
Instrumental analysis
Multi-layer SiO2 (neutral, acidic, and basic, Hex); carbon SPE; PYE HPLC column
GC-ITD-MS/MS
Treatment with conc. GC-EI-HRMS H2SO4; SiO2 (DCM:Hex, 10:90); Florisils (Hex+DCM:Hex, 60:40); Carbon for PBDD/Fs GC-EI-HRMS Multi-layer SiO2 (basic/neutral/acidic/ neutral, Hex); Carbopak – GC-EI-HRMS
Treatment with conc. H2SO4; 2 GPC (DCM:Hex, 1:1); Florisils (DCM:Hex, 1:1, then MeOH:DCM, 7:93) 2 GPC (DCM); SiO2; treatment with conc. H2SO4 –
GPC on Biobeadst S-X3; SiO2 fractionation (Hex+DCM:Hex, 5:95 or 50:50 for HBCD) GPC+ SiO2–H2SO4+ deact SiO2 (1.5% H2O)
Extraction procedure Clean-up
Pretreatment
Sample type (g, mL)
BFRs (# of congeners)
Table 1 (Continued )
n.r.
5–74
39–139
PBDEs: 58–79 PBDD/Fs: 50–56
n.r.
n.r.
n.r.
[82]
[81]
[81]
[80]
[78,79]
[46]
[77]
[75,76]
[73,74]
PBDEs: 60–120 HBCD: 60–120
80127
Reference
Recovery (%)
Homogenization
Shrimps, Fish tissue (10)
Egg and Fish (5–10)
Tri-hepta-BDEs (10)+ deca-BDE Tetra-penta-BDEs (3), total HBCD
PBBs (atropisomers)
Tetra-penta-BDEs (3), TBBP-A
Mixing with Na2SO4
Bovine adipose+ swine organs (1–5)
Tri-hepta-BDEs (11)+ TBBP-A
Homogenization+ mixing with Na2SO4
Homogenization+ mixing with Na2SO4
Egg (10)
Egg (20)
Homogenization
Egg, adipose, and muscle (0.5–1)
Homogenized+ hydromatrix
Pasteurization
Milk (1)
Tri-deca-BDEs (8)
Fish: mix with Na2SO4
Milk: freeze-dried
Fish and milk (5–100)
Tri-deca-PBDEs (9)
Freeze-drying
a-,b-,g-HBCD+TBBP-A+tri- Adipose tissue and deca-BDEs (30) milk (0.5–1)
Fish, meat, and milk vegetables
PBDEs
Column extraction (Acet:Cyclohex, 1:3, 1 h) Column extraction (Acet:Cyclohex, 1:3)
Hot Soxhlet (Hex:Acet, 3:1; 75 mL, 2 h) SLE (Acet:Hex, 5:2+ 2 DE:Hex, 1:10)+ 0.9% NaCl in 0.1M H3PO4 SLE (Acet:Hex, 5:2+ MTBE:Hex, 9:1)
Diatomaceous earth (elution with DCM) PLE (Acet:DCM, 1:1, 1001C, 1,500 psi)
Fat: SLE (Acet:DCM, 1:1, 12+6 mL)+LLE (AcN, 3 mL+Hex, 3 3 mL)
Saponification with KOH:EtOH (2 h); LLE with Hex; Soxhlet (5 h) with Tol Fish: column extraction (Cyclohex:DCM, 150– 600 mL); Milk:LLE (Pent+DE+EtOH+ potassium oxalate) Milk: LLE (AcN, 3 mL+Hex, 3 3 mL)
Treatment with conc. H2SO4; SiO2–H2SO4 (Hex); activated SiO2 (DCM) GPC+ deact Florisils (0.5% H2O)+derivatization GPC; Florisils; SiO2 (Hex+Hex:EtOAc, 9:1); SiO2 HPLC (Hex); b-PMCD HPLC (AcN:water, 60:40)
Treatment with conc. H2SO4
Partition with Hex/ 0.1 M H3PO4, 1% KCl; GPC on Biobeadst S-X3 (DCM:Hex); SiO2 SPE SiO2–H2SO4
Hex layer (PBDEs): Oasis HLB SPE+SiO2+ SiO2–H2SO4 ACN layer (HBCD+ TBBP-A): enzymatic hydrolysis (501C, 4 h)+ Oasis HLB+silica SPE SiO2+SiO2–H2SO4
Multi-layer SiO2 (AgNO3/acidic/basic) (DCM:Hex, 5:95); active carbon (DCM:Hex, 1:3) SiO2–H2SO4; Al2O3
56–94
n.r.
GC-EI-MS/MS
PBDEs: 96–126
PBDEs: 96–126 HBCD: 112–120
81–103
PBDEs: 68–119 TBBPA: 22–41
LC-TOF-MS GCHRMS
GC-ECNI-MS
GC-ECNI-MS
GC-ECNI-MS
GC-ECNI-MS
60–89
PBDEs: 60–110
LC-ESI-MS/MS for HBCD
GC-HRMS
g-HBCD: 40 TBBPA: 40
60–120
W 80
GC-EI-HRMS for PBDEs+TBBP-A
GC-EI-HRMS
GC-EI-HRMS
[92]
[91]
[90]
[89]
[88]
[87]
[86]
[85]
[84]
[83]
Hamburger mixed with Celite
Freeze-dry+ homogenization
10 food groups
Duplicate diets (50)
Fish and meat
Meat fat, bacon, and hamburger (5)
Fatty foodstufsa (10 g lipids)
Tetra-hexa-BDEs (5)
Tetra-hexa-BDEs (5)
Mono-deca-BDEs (31)
Mono-deca-BDEs (42)
Tri-hepta-BDEs (16)
Soxhlet (DCM:Hex, 1:1) SLE (DCM)+filtration or PLE (iPrOH:DCM:Hex, 35:35:30, 1251C, 1,500 psi) Column extraction: SiO2–H2SO4+SiO2– KOH+Carbon (DCM:Hex, 4:6)
Soxhlet (DCM:Hex, 1:1, 16–24 h)
Soxhlet (Tol, 24 h)
Soxhlet (Tol or DCM:Hex, 1:1, 24 h)
SiO2–H2SO4+ SiO2–KOH+ Al2O3 (15 mL Hex+ 30 mL DCM:Hex, 30:70)
SiO2–H2SO4+ SiO2+SiO2–KOH+ Al2O3
Multi-layer SiO2 (neutral/acidic/ neutral/basic/neutral); alumina; GPC Biobeadst S-X3 SiO2+SiO2–H2SO4 (DCM:Cyclohex, 1:1); carbon (DCM:Cyclohex, 1:1); Al2O3 (DCM:Hex, 2:98); carbon (DCM:Hex, 1:1) Treatment with conc. H2SO4; SiO2–H2SO4 (Hex); LLE (DMSO:Hex); Florisils SiO2; active carbon
Extraction procedure Clean-up
GC-HRMS
GC-EI-HRMS
GC-EI-HRMS
50100
76114
W 85
54–104
n.r.
GC-EI-HRMS
GC-EI-LRMS
54–115
Recovery (%)
GC-EI-HRMS
Instrumental analysis
[86]
[97]
[96]
[95]
[94]
[93]
Reference
Notes: Solvents: Acet, acetone; AcN, acetonitrile; Hex, hexane; DCM, dichloromethane; EtOAc, ethyl acetate; Pent, pentane; i-PrOH, 2-propanol; DE, diethyl ether; Tol, toluene; MeOH, methanol; EtOH, ethanol; MTBE, methyl tert-butyl ether; Cyclohex, cyclohexane; petr. petroleum; and DMSO, dimethylsulfoxide. Solvent mixtures: proportions as v/v; when possible, steps involved mentioned as: no. of cycles volume/time per cycle; and n.r., not reported . Other acronyms, as identified in the body text. a Fatty foodstuffs include cod liver oil, breast milk, beef, pork, turkey, salmon, egg, and cheese.
Homogenized
Homogenized and freeze-dry
Composite and freeze-dry
Composite, freeze-dry, and mixing with Na2SO4
11 food groups (10)
Tetra-octa-BDEs
Pretreatment
Sample type (g, mL)
BFRs (# of congeners)
Table 1 (Continued )
Brominated Flame Retardants as Food Contaminants
519
Wet samples (e.g., tissues) should be ground with anhydrous sodium sulfate (Na2SO4) to a dry paste before Soxhlet extraction. This procedure is the basis for a draft US EPA method to analyse mono- to deca-BDEs in tissue [98]. Variations of this method have been used to measure a range of PBDEs from fish and mussel tissues using DCM as the extraction solvent [62,69] or n-hexane:acetone (3:1, v/v) [46] and meat and poultry samples using DCM:n-hexane (1:1, v/v) [96]. Soxhlet and n-hexane:acetone (3:1, v/v) were also used to extract PBDEs from various food items, including hamburgers and pizzas [99]. HBCD isomers have been extracted from spiked fish fillet that was dried with Na2SO4 using a binary solvent mixture of acetone:n-hexane (either 1:1 or 3:1, v/v) in the Soxhlet and gave good recoveries of each stereoisomer: 84%721% for a-HBCD; 66%715% for b-HBCD; and 82%712% for g-HBCD [76]. An alternative to Soxhlet extraction is accelerated solvent extraction (ASE) or pressurized liquid extraction (PLE), which applies heat and pressure to increase the extraction efficiency of analytes from a complex matrix. This method is automated and decreases the time required for extraction (generally o0.5 h/ sample) and the amount of solvent consumed (generally o50 mL) as compared to Soxhlet extraction. Wet samples are mixed with a drying agent such as diatomaceous earth (Celite, Hydromatrix) or Na2SO4 before extraction. Huwe et al. [97] used an ASE method to extract PBDEs from hamburgers using a ternary solvent system of 2-isopropanol:n-hexane:DCM (35:30:35, v/v) at 1251C and 1,500 psi. Recoveries ranged from 35% to 150%, but they were somewhat lower for BDE 209. Saito et al. [87] investigated the optimum conditions for ASE extraction of 59 different organohalogenated compounds, including PBDEs and TBBP-A, from swine organs and cattle adipose tissue. Hydromatrix proved more efficient for dehydrating the tissues before ASE extraction than Na2SO4. A mixture of DCM:acetone (1:1, v/v) at 1001C and 1,500 psi proved to be the best solvent combination for lipid extraction compared to 9 other solvent systems. The overall analytical method yielded recoveries of tri- to hepta-BDEs greater than 68% and recoveries of TBBP-A between 21% and 79%. Lyophilized fish tissues were extracted by ASE with DCM at 601C and 1,000 psi to determine the levels of tetra- to hexa-BDEs [68]. Lyophilized fish, shellfish, and seaweed samples have also been extracted by ASE with n-hexane at 1001C and 1,500 psi to determine PBDEs and PBDD/Fs [80]. This method was validated with dried sardines and showed overall recoveries of 58–79% for tetrato hepta-BDEs and of 50–56% for tetra- to hexa-BDD/Fs. The relative standard deviations (RSD) of the recoveries were less than 13%. Eljarrat et al. [64] adapted a selective PLE method (involving the addition of alumina in the extraction cell) for the simultaneous analysis of PBDEs and total HBCDs in fish tissue obtaining ready-to-analyse extracts. The efficiency of this particular PLE procedure proved to be similar to other PLE-based methods in which clean-up was carried out offline by manual [68,80] or semi-automated [61] multi-step procedures. Microwave-assisted extraction (MAE) has been used to extract PBDEs from fish and mussel samples [65]. Homogenized, fresh tissues were ground with Na2SO4 and extracted with n-pentane:DCM (1:1, v/v) at a temperature of 1151C for 15 min. For MAE, purification was carried out off-line after solvent separation
520
Adrian Covaci et al.
from the matrix components, but its high extraction efficiency allowed a significant reduction of the extraction time compared to Soxhlet extraction. Recoveries in the range of 8997% (RSDs o14%) were reported for BDEs 47, 99, and 100 from spiked marine biological tissues with variable fat and moisture contents (range 1.238% and 4878%, respectively). Moreover, the use of MAE provided only slightly lower concentrations (difference o15%) than the Soxhlet procedure used as reference method (6 h extraction with 150 mL DCM) for the analysis of two reference materials (SRM 1588a-cod liver oil and SRM 2978mussel tissue) [65]. Supercritical fluid extraction (SFE) is a method that extracts compounds from a matrix by passing a supercritical fluid (usually CO2) through the matrix thereby eluting and trapping the extracted compounds on a sorbent material as they flow out of the SFE vessel. Wolkers et al. [78,79] applied SFE to extract PBDEs from fish tissue and simultaneously removed lipids from the samples. In brief, the samples (1 g) were homogenized with Na2SO4 (5 g), packed under a layer of basic aluminium oxide (4.5 g) in the SFE cell, and extracted with supercritical CO2 at 401C and 280 bar at a flow rate of 2 mL/min for 25 min. The extracted compounds were adsorbed onto an octadecyl-modified silica support (ODS) and subsequently eluted with n-hexane and DCM. The authors noted that in order to determine the lipid content of the samples, a separate column extraction was necessary due to the destruction of lipids in the SFE. A modification of this method has been tested for potential extraction of PBDD/Fs onto a carbon support trap and showed inconsistent recoveries of mono- to penta-BDD/Fs (5–74%) [81]. To optimize a SFE method for extraction of PBDEs and PBBs from fish and fish feed, Rodil et al. [54] investigated critical variables, such as temperature, pressure, static and dynamic extraction times, CO2 flow rates, and the choice of adsorbent for integrated lipid removal. Of the four adsorbents that were evaluated (basic alumina, Florisils, acidified silica, and ODS), all were efficient at lipid removal, but the best clean-up was obtained layering acidified silica and basic alumina. The results showed that dynamic extraction time and pressure were the two most significant factors for SFE. The final extraction procedure entailed filling the SFE cell from bottom to top with freeze-dried sample (1 g), basic alumina (1.5 g), and acidified silica (1.5 g), and then extracting with supercritical CO2 at 601C and 165 bar with a flow rate of 2 mL/min for 5 min of static extraction and 27 min of dynamic extraction. The extracted compounds were trapped on a ODS support and subsequently eluted with n-hexane to give average recoveries of 77–101% and RSDs of 7–17% for PBBs 15 and 49 and BDEs 47, 99, and 100 [54]. Several extraction methods that require no heat or pressure have also been employed to extract lipophilic compounds from food matrices. These techniques include direct homogenization of the matrix in an organic solvent, liquid–liquid extraction (LLE) of liquid matrices such as milk, liquid–solid extraction, or matrix solid-phase dispersion (MSPD). For high lipid content matrices such as butter, oil and fish tissue, the direct mixing with a Polytron or Ultra Turrax homogenizer in an organic solvent has
Brominated Flame Retardants as Food Contaminants
521
been employed to extract BFRs. The choice of solvents include: (i) a two-step extraction with n-hexane:acetone (5:2, v/v) followed by n-hexane:ether (9:1, v/v) to extract PBDEs and HBCDs from fat, muscle, and eggs [89,90]; (ii) DCM to extract PBDEs from trimmed fat and bacon [97]; (iii) acetone:n-pentane:water (1:1:1, v/v) to extract PBDEs and HBCDs from fish tissues [46,76]; and (iv) nhexane:acetone (1:2, v/v) to extract fish and shellfish [71]. An LLE method that uses saturated potassium oxalate solution, ethanol, ether, and n-pentane has been applied to the extraction of PBDEs from whole milk samples [84]. Results of analyses utilizing this extraction method showed accuracy within 20% of the true value based on standard addition and a precision of 86–99%. Another liquid–liquid/solid extraction method coupled saponification of freeze-dried fish and meats (20 g) or raw milk (50 mL) in 1 M KOH/ ethanol solution (150 mL) and extraction of PBDEs into n-hexane (120 mL) [83]. Cariou et al. [85] used liquid–liquid partitioning to extract HBCDs, TBBP-A and PBDEs from lyophilized milk with minimal amounts of solvent. The freeze-dried milk (1 g) was first extracted with acetone:DCM (1:1, v/v), after which the dried extract was partitioned with acetonitrile and n-hexane. The acetonitrile phase contained the HBCDs and TBBP-A, and the hexane phase contained the PBDEs. Recoveries were low but satisfactory for HBCDs and TBBP-A (40% for each) and higher for the PBDEs, including BDE-209 (60–110%). A common liquid–solid extraction method is the extraction by open column packing. Wet tissues are mixed with anhydrous Na2SO4 to a dry paste, packed in open glass columns, and extracted with organic solvents. The amount of solvent needed typically ranges from 100 to 600 mL and it is determined by the initial sample size. PBDEs have been extracted from fish with acetone:n-hexane followed by n-hexane:ether [77]. Other solvents that have been used to extract PBDEs from fish tissue include DCM [66], a mixture of cyclohexane (or n-hexane) and DCM [55,70,84], and ethyl acetate:petroleum ether [67]. PBDEs and PBBs were extracted from eggs on an open column using a binary solvent system of cyclohexane:acetone (3:1, v/v) [100]. A slight method modification in which sulfuric acid-containing Na2SO4 (1% w/w) was used as the drying agent facilitated extraction of TBBP-A and other phenolic compounds from eggs [91]. Fernandes et al. [48] needed 400 mL of DCM:n-hexane (2:3, v/v) to elute PBDEs from a multi-layer column containing 5 g lipid weight (lw) of food (5–200 g dry weight). Open column extraction of PBDD/Fs from adipose tissue has been demonstrated with n-hexane:DCM (1:1, v/v) and shown to give overall recoveries of 30–139% for mono- to penta-BDD/Fs after purification [81]. MSPD is similar to open-column extraction, but may consume less solvent and can combine cleanup with extraction. Carro et al. [53] optimized MSPD for the analysis of PBDEs and PBBs in fish feed and fish tissue. They have found that alumina was a better general adsorbent than Florisils, that the use of pressure to elute the column was better than gravity flow, that acidified silica gel performed best as the last absorbent (bottom of column), and that the addition of anhydrous Na2SO4 to the sample decreased extraction efficiency. The optimal procedure was to grind the freeze-dried sample (1.5 g) with ODS (1 g) and to place it on top of a syringe barrel filled with (from top to bottom) alumina (1.5 g) and acidified silica
522
Adrian Covaci et al.
(2 g), placing frits at the top and bottom of the barrel. The column was then eluted with hexane (30 mL) using the syringe plunger to apply pressure. Recoveries of 3 PBDE and 2 PBB congeners varied between 70% and 96%. Martinez et al. [59] applied MSPD to the extraction of PBDEs from beef and chicken fat, and fish samples by grinding naturally contaminated fish tissue (0.5 g) with anhydrous Na2SO4 (2 g) and Florisils (1.5 g), placed on top of an acidified silica cartridge (5 g). Only 20 mL n-hexane was needed for the complete elution of analytes. The procedure removed 99% of the lipids and resulted in recoveries of 89–95% for 6 tetra- to hexa-BDEs. Except for a subsequent fractionation of PBDEs from PCBs on silica, no other treatment was required before analysis by GC with electron capture detection (GC-ECD). Substituting Florisils for acidified silica proved to be less efficient for lipid removal. Freeze-dried dairy products, i.e., cheese and milk, have also been extracted using MSPD by homogenizing the sample (5–10 g) with silica (10 g) and anhydrous Na2SO4 (10 g) and column extracting with acetone:n-hexane (1:1, v/v) (400 mL) [82]. After further fractionation, PBDEs and PBBs were identified. In another study, whole milk samples (1 g) were added directly to solid-phase extraction (SPE) cartridges containing Hydromatrix (0.8 g), dried with a pressurized stream of nitrogen (120 min, 10 psi), and eluted with DCM (12 mL) [86]. Using an automated SPE workstation, multiple samples could be processed simultaneously and automatically. LLE is a simple approach for the determination of BFRs in aqueous samples. However, because of the hydrophobic character of BFRs (except for TBBP-A) and thus low concentrations in water, large volumes (up to 1,000 mL) are typically required to ensure detectability. Suzuki and Hasegawa [101] reported recoveries above 77% for a-, b-, and g-HBCD, after two sequential LLE with DCM. However, the authors suggested SPE on Abselut Nexus cartridges as a faster and valuable alternative allowing the simultaneous determination of TBBP-A (recovery 103716%) and a significant reduction in the organic solvent consumption (from 50 mL DCM to 5 mL acetone) that still provided acceptable recoveries (5485%) of the 3 HBCD diasteroisomers. An US EPA analytical method was developed using SPE discs to simultaneously extract PBDEs, HBCDs, and TBBP-A from drinking water [52]. The method utilizes styrenedivinylbenzene discs (47 mm) to extract 1 L water and small amounts of solvents (5 mL each) to sequentially elute the analytes. The recoveries of BDEs 47, 99, 100, and 153, HBCDs and TBBP-A from three spiked water samples ranged between 78% and 107% (RSDo7%). No further purification was needed before analysis. Solid-phase microextraction (SPME), a rapid, solvent-free and low-cost analytical technique, has also been evaluated for the analysis of BFRs. Since PBDEs have relatively high molecular masses and low vapour pressures, one would expect to achieve higher recoveries by direct immersion of the fibre in a liquid sample than by sampling the headspace (HS) when using SPME as preconcentration step. Nevertheless, Polo et al. [49] observed the opposite trend when analysing tetra- to penta-BDEs in tap water and wastewater from an urban treatment plant (spiking level, 0.021.0 ng/L). Besides filtration, no other pretreatment was required before direct HS-SPME of 10 mL water heated at
Brominated Flame Retardants as Food Contaminants
523
1001C for 30 min. Apart from the enhanced extraction efficiencies, the use of HSSPME instead of direct immersion prevented the contamination with non-volatile compounds and prolonged the lifetime of the fibre. Linear responses were observed in the 0.2500 ng/L range, with recoveries W 87% and RSDso19%. However, since hexa-BDEs (BDE 153 and 154) could not be recovered under the proposed experimental conditions, the method seems to be limited up to pentaBDE congeners [49]. In a similar manner, TBBP-A and seven other phenolic BFRs were also amenable to HS-SPME [50]. When combined with an in situ acetylation step, the derivatized phenolic compounds were efficiently extracted from water samples by HS-SPME at 1001C in 30 min (recoveries 20–117%, RSDo15%). For TBBP-A, but not for the other brominated phenols, a somewhat more efficient extraction was obtained with direct immersion SPME at 251C. Fontanals et al. [102] have demonstrated the use of hollow-fibre microporous membrane LLE for PBDEs in water. The hollow-fibre membrane was filled with organic solvent and immersed into the aqueous sample, spiked with PBDEs at ng/L level, and stirred. The technique attained good spike recoveries (range 85–110%) and enrichment factors. A closely related technique, stir bar sorptive extraction (SBSE) on a polydimethylsiloxane (PDMS) stir bar, has been utilized for the quantitative preconcentration of tri- to hexa-BDEs from 100 mL of surface water contaminated by the effluents from a plastic-production company [51]. The analytes are then thermally desorbed from the stir bar in a GC injection port. The only sample pretreatment required was the addition of 20% methanol (v/v) to the water sample. The long preconcentration time used in the experiments (25 h) resulted in low limits of detection (LODs) of 0.410 ng/L, although GC-MS with electron ionization (EI) in scan mode was used for the final detection. However, a rather long preconditioning of the stir bar (3001C, 4 h) was required to avoid cross contamination. Under these conditions, the carryover was o2% for tri- to hexaBDEs after the analysis of water samples spiked at the 600 ng/L level [51].
2.1.2 Clean-up The non-selective nature of the exhaustive extraction procedures and the complexity of the sample matrices result in complex extracts that require further purification. Despite the inherent advantages derived from partial or complete integration of these tedious and time-consuming purification treatments, or by combining the clean-up treatment with the extraction [79], up to now the development in this field has been rather limited and the analytical steps involved in clean-up protocols for BFRs have usually been carried out off-line. Typical purification and fractionation procedures are summarized in Table 1. For food samples, lipid elimination should be accomplished before chromatographic analysis by destructive or non-destructive methods. Otherwise, similar protocols can be used for purification of the extracts almost irrespective of the matrix nature.
2.1.2.1 Non-destructive clean-up. Gel permeation chromatography (GPC) and adsorption chromatography on selected adsorbents are non-destructive
524
Adrian Covaci et al.
treatments applied for elimination of lipids and other high molecular mass compounds from the sample matrix. GPC is mainly done using polystyrenedivinylbenzene columns and DCM as eluent [58,62,68]. For complex matrices, two serially connected GPC columns [71] or GPC combined with further clean-up by adsorption chromatography [46] or concentrated sulfuric acid treatment [75] are often required for complete fat removal and isolation of BFRs. Silica gel, alumina, and Florisils with different degrees of activation have been widely used for lipid removal by adsorption chromatography under atmospheric conditions (Table 1). Because of its limited capacity for retention of lipids, silica has been used in combination with alumina [46] or Florisils [103]. Alumina alone has also been shown to be suitable for lipid removal [62]. The higher lipid retaining capacity of alumina and Florisils has made these adsorbents to be preferred as fat retainers also in procedures involving MSPD [59], in-cell PLE [64], and SFE [54,79]. As an alternative to these sorbents, Carro et al. [53] proposed the use of non-polar adsorbents, such as ODS, for a preliminary fat retention during MSPD. For obvious reasons, when extraction and clean-up is combined in a single step, the total lipid content determination should be carried out separately on an aliquot of the sample.
2.1.2.2 Destructive clean-up. Similarly to other organohalogenated compounds, BFRs are stable under strong acidic conditions [43,46]. Owing to its efficient organic matter removal, sulfuric acid treatment is one of the most used destructive treatments in BFR analysis (Table 1). The simplest approach consists in the direct addition of the acid to the sample extract [46,89,95]. However, this treatment requires several sequential LLE and centrifugation steps, which results in a highly manipulative and time-consuming procedure. The dispersion of sulfuric acid onto the surface of activated silica gel results in an adsorbent that can be easily loaded onto a column. The use of acidified silica avoids the emulsion problems often encountered during LLE, reduces the sample handling and solvent consumption and increases sample throughput [43]. The lipid destruction with concentrated acid may allow the removal of a higher lipid amount than adsorption chromatography. Only 5 g of acidified silica (40%, w/w) prepacked in an SPE cartridge was sufficient for the purification of 0.7 g of fish or vegetable oil samples [56]. The target analytes, which included 7 tri- to heptaBDEs, were quantitatively eluted with 15 mL n-hexane and 10 mL DCM. Silica gel can also be modified with alcoholic NaOH [79] or KOH [48,103]. However, it should be mentioned that, while PBBs, PBDEs, and TBBP-A are stable under basic conditions, such treatment degrades HBCDs [46]. Basic conditions can also be used during the saponification of food samples (heating with ethanolic KOH) [91]. However, the conditions for saponification are critical as too high temperatures and too long saponification times may cause degradation of higher BDEs and BBs [46,91], leading to an underestimation of their concentration and a relative overestimation of lower BDEs and BBs. Although in many applications the use of acidified silica is enough to yield sufficiently clean extracts, several studies have described the use of acidified
Brominated Flame Retardants as Food Contaminants
525
silica in combination with neutral silica and base-modified silica [61,97,103] in multi-layer columns for improved purification necessary for high-resolution mass spectrometry (HRMS) analysis. All approaches provide similar satisfactory results concerning recovery and reproducibility.
2.1.3 Fractionation For specific applications, isolation of the target analytes from other organohalogenated compounds present in the extract can be mandatory to avoid interferences during final instrumental analysis. Owing to their higher polarity than other organohalogenated pollutants typically present in the extract, e.g., PCBs and PBDEs can be isolated in a separate fraction using classical sorbents, such as silica gel, alumina, and Florisils. On silica gel, PBDEs elute with mixtures of DCM and n-hexane [59], mixtures of diethyl ether and n-hexane [46] or with DCM [90] in a second, more polar, fraction after PCBs have been eluted with nhexane. However, BDE 209 elutes quantitatively in the first fraction with the PCBs [46,73]. A better separation of PCBs and PCDD/Fs from PBDEs was accomplished with silver nitrate (AgNO3)-impregnated silica gel [72]. PCBs and PCDD/Fs eluted from a multi-phase silica column containing AgNO3-silica in 2% DCM:n-hexane (v/v), whereas tri- to hepta-BDEs eluted in 10% DCM:nhexane (v/v) with as little as 1.5% overlap. Deactivated silica gel has also been successfully applied for the quantitative isolation of PBDEs from HBCDs and TBBP-A [75,76]. In this case, iso-octane was used for the elution of PBDEs, while a more polar mixture, i.e., 15% diethyl ether:iso-octane (v/v), was required to elute HBCDs and TBBP-A. Alumina and Florisils show less selectivity for PBDEs than silica gel and, using n-hexane and 20% DCM:n-hexane (v/v) as the eluent, some planar PCBs were found to elute together with PBDEs in the latter fractions [59]. In addition, lower BDEs, e.g., BDE 47, partially eluted in the first fraction when using Florisils columns [101]. Ashizuka et al. [80] successfully separated PBDEs from PBDD/Fs on Florisils by first eluting the PBDEs with n-hexane and then the PBDD/Fs with DCM:n-hexane (3:2, v/v). Florisils (activated at 4501C for 12 h and subsequently deactivated with 0.5% H2O, w/w) has been successfully used to separate neutral organohalogenated compounds from phenolic analytes, including TBBP-A [91]. In this case, neutral compounds were firstly eluted with mixtures of DCM and n-hexane (1:3, v/v), whereas polar mixtures of acetone and n-hexane (15:85, v/v) and methanol and DCM (12:88, v/v) were needed to elute phenolic analytes. Polystyrene divinyl benzene-based sorbents, such as Oasis HLBs, are a valuable alternative for the fast separation of HBCD diasteroisomers from TBBP-A. Only 7 mL of a mixture DCM:n-hexane (1:1, v/v) was required to elute HBCDs from the SPE cartridge, whereas 8 mL of DCM sufficed for subsequent quantitative elution of TBBP-A [85]. Activated carbon has been used to separate the bulk of PCBs and PBDEs from the planar non-ortho-PCBs and PCDD/Fs [48,60]. Although this sorbent provided an efficient separation, large solvent volumes, e.g., 100 mL of n-hexane and 400 mL of DCM:n-hexane (2:3, v/v), were required to ensure quantitative elution of ortho-PCBs and PBDEs [48]. The higher efficiency provided by the use of
526
Adrian Covaci et al.
porous graphitic carbon (Hypercarb)-HPLC (high-pressure liquid chromatography) resulted in a better separation between PBBs and lower BDEs, on one hand and higher BDEs (including BDE 209) and PBDD/Fs, on the other hand [7]. However, the separation between the two latter classes of brominated compounds required an extra fractionation step on a 2-(1-pyrenyl)ethyldimethylsilyl (PYE) HPLC column. Even in these conditions, BDE 209 was not separated from 2,3,7,8-T4BDD/F using DCM:n-hexane (1:10, v/v) as mobile phase [7]. In another application, Go´mara et al. [104] have shown that the addition of 2% toluene to iso-octane and the increase in the temperature of the PYE column to 451C resulted in significant reduction of the elution time of the more retained PBDEs and PBBs. Under these experimental conditions, an acceptable separation between PCBs and PBDEs+PBBs was achieved within 10 min. Only the lower BDEs investigated (BDEs 17 and 28) were found to elute in the bulk PCB fraction, while CBs 170 and 194, which were strongly retained, were eluted in the second collected fraction containing the 8 tetra- to hepta-BDEs and 9 penta- to hepta-BBs studied [104]. Although most purification procedures are carried out in discrete steps subsequent to extraction, some progress has been made in combining fractionation and extraction or various fractionation steps in an automated, on-line manner to reduce the overall complexity of the process. SFE has been shown to provide one-step extraction and clean-up for small samples (1 g) of fish, milk, and fat when alumina [79] or alumina and acidified silica [54] are added to the extraction vessel as a lipid retainer. The analytes were eluted onto an ODS trap, desorbed with solvent, and analysed. Eljarrat et al. [64] showed that PLE in the presence of alumina extracted and purified samples of liver or muscle (0.5 g) sufficiently for direct analysis of PBDEs and HBCDs . With larger sample sizes of fish, oil, or vegetables (10 g), PLE with acidified silica as a lipid retainer was used in combination with a short GPC column coupled to a graphitized carbon black SPE column to successfully purify PBDEs and PCBs and also to recover PCDD/ Fs in a separate fraction [57]. Combined on-line clean-up processes for BFRs include the use of an automated dioxin clean-up instrument (Power Prep, FMS Inc., USA) [61,97] or an automated SPE system (RapidTracet, Zymark, USA) [86,87] to simplify multi-column fractionation. Using custom-made smaller columns on the PowerPrept unit, samples containing 0.2 g of lipids were processed in 20 min using 80 mL of solvent [61]. With the RapidTracet SPE system, Sjo¨din et al. [86] were able to process 20 milk samples (1 g each) in 2.5 h using only 20 mL of solvent per sample. Separation of PBDEs and TBBP-A could be accomplished on silica gel cartridges with the RapidTracet by first eluting with 5% DCM:hexane (PBDEs, PCBs) and then with 10% MeOH:DCM (TBBP-A and other phenolic compounds) [87].
2.2 Instrumental analysis Separation, identification and quantification of BFRs are generally performed by means of GC-MS and/or LC-MS. These instrumental techniques enable the analysis of a wide range of BFRs in a variety of food items. The physico-chemical
Brominated Flame Retardants as Food Contaminants
527
properties of the compound determine which technique should be selected. In general, PBDEs use GC, whereas for HBCDs and TBBP-A, LC is preferred. This section will provide insight into the instrumental aspects of BFR analysis and the associated quality control measures that are imperative for confident analysis of BFRs in food.
2.2.1 PBDEs and PBBs The most applied analytical method for PBDEs is GC-MS. One of the most crucial steps of the analysis is the injection of the extract into a GC system. The GC column then separates the different PBDE congeners from each other and from interferences that are eventually present in the extract. Finally, the analytes are detected, identified, and quantified using MS.
2.2.1.1 GC injection. The most frequently used injection techniques for PBDEs and PBBs are splitless, on-column injection and programmed temperature vapourization (PTV) in solvent vent mode [43]. In splitless injection, the transfer of the analytes into the analytical column is controlled by the volume of the liner and by the injected volume. A too small liner can result in overload (where the vapour volume of the injection exceeds the volume of the injector liner) and this can cause memory effects and loss of analytes. Very large liner volumes can lead to poor transfer of early eluting compounds to the column. Injector temperatures are usually set between 2501C and 3001C. For octa- to deca-BDEs, some degradation might occur if the residence time in the liner is too long, whereas discrimination of higher BDEs is possible when the residence time is too short. A pressure pulse (pulsed splitless) may help to improve the injection performance. Small injection volumes (typically 1 mL) are preferred, but larger volumes can improve the LOD. The use of PTV allows the injection of large volumes of extract at low temperature. This technique gives enhanced LODs and improved column transfer for higher brominated compounds [105–107]. Injections of large volumes of extracts, up to 20 mL [105] or 50–100 mL [108], may be good options for the determination of PBDEs in samples with low concentrations, such as food. In these cases, the extracts should be very clean to reduce interferences during the GC separation. The use of an autosampler is a prerequisite for obtaining an acceptable reproducibility of the injection. For BDE 209, it is possible to differentiate whether degradation has occurred during the sample preparation (e.g., photolytic decomposition) or during injection. The presence of nona-, octa- and, eventually, other lower BDE congeners indicates that degradation occurred during sample preparation. The presence of a hump or a rising baseline in the chromatogram before BDE 209 indicates degradation during injection. A dirty GC system (liner or column) may lead to partial or complete losses of BDE 209. For BDE 209, a pressure-pulse injection should be used to reduce the exposure to high injector temperatures. Also, the maximum injection temperature should not be higher than 3001C. Alternatively, on-column injection may be used: the extract is injected directly
528
Adrian Covaci et al.
into the column [66] or in a glass insert fitted into a septum-equipped programmable injector kept at low temperature [108,109]. No significant degradation of higher BDEs, including BDE 209, was observed. However, this technique requires an intensive clean-up of the extracts because the presence of matrix components impedes chromatography and quickly deteriorates the GC column. Further, Bjo¨rklund et al. [108] used a rotary-valve on-column injector, which has a number of advantages: (i) decreased discrimination of higher BDEs, (ii) no thermal degradation in the injector, (iii) no liner needed, (iv) availability of large volume injection, and (v) easy hyphenation with a preceding HPLC. Good precision was obtained for injection volumes up to 50 mL. For samples with very low contamination levels, injection of 50 mL might not be satisfactory in regard to LODs. Therefore, other types of injection, such as loop-type injection with an early solvent vapour exit were investigated [110]. Up to 500 mL could be injected with high reproducibility and low carryover.
2.2.1.2 GC separation. Although 209 PBDE congeners are theoretically possible, only a small number can be found in technical PBDE mixtures [13]. However, the congener profiles found in food of animal origin match those of the technical mixture only to a limited extent, probably due to selective uptake, metabolism and degradation [111]. Therefore, the contamination with PBDEs is preferably monitored by the determination of selected individual congeners. Several congeners, such as BDEs 28, 47, 99, 100, 153, 154, and 183 are frequently detected, while BDE 209 was only seldomly found [112]. This means that singlecapillary column GC may offer sufficient resolution for a congener-specific determination. To achieve enough separation between PBDEs and possible interferences, there is, however, a need for using sufficiently long columns (30–50 m) and small diameters (p 0.25 mm). Good resolution may also be obtained by using narrow bore columns (internal diameter ¼ 0.1 mm) [105]. The sequential use of two columns with different characteristics has also been applied; a short column for higher BDEs and a long column to separate lower BDEs [88]. PBDEs can be relatively easily separated on non-polar or semi-polar columns such as 100% methyl-polysiloxane type (DB-1) and 5% phenyl-dimethyl polysiloxane type (DB-5 or CP-Sil 8). The most frequently used lengths are 25–60 m [46]. Several other columns, such as 10 m 0.10 mm internal diameter 8% phenyl-polycarborane-siloxane HT-8 [88] or AT-5 [105], 60 m 14% cyanopropylphenyl 86% dimethyl-polysiloxane (DB-1701) [66] were successfully used. All these columns display a good resolution for most compounds, but each type of column should first be tested for possible co-elutions of target compounds, internal standards and other compounds present in the extract. The impact of the co-elutions depends on the sample clean-up, pollutant load, chromatographic system and the detection method. Alaee et al. [113] have indicated that there are potentially 10 PBDE congeners that can co-elute with organochlorine pesticides or PCBs, with a particular concern addressed to CB 180 and BDE 47 or to CB 194 and BDE 100. Such
Brominated Flame Retardants as Food Contaminants
529
co-elutions between PCBs and PBDEs are resolved by the use of MS detection, but can lead to errors when ECD is used. Important co-elution when using MS are the co-elution on DB-5/CP-Sil 8 of BB 153 and BDE 154. BB 153 was already found in fish from the Great Lakes [114]. Using a HT-8 column, BB 153 and BDE 154 do not co-elute, but now BDE 85 co-elutes partially with BDE 154 [43]. Ikonomou et al. [115] reported the co-elution of lower brominated congeners, BDEs 28 and 33, on a 30-m DB-5 column. Recently, Vetter [116] has shown that BDE 99 may co-elute with a natural bromine-containing compound, whereas BDE 47 and BDE 99 may interfere with breakdown products of HBCDs [117]. Koryta´r et al. [118] have investigated the elution order of 126 PBDEs on seven different GC stationary phases. The resulting database facilitates selection of the most suitable GC columns for developing a quantitative, congener-specific PBDE analysis and the testing of retention prediction algorithms based on structure relationships of GC phases and congener substitution patterns. Stationary phasedependent degradation was observed, indicating that column equivalency is not always a suitable criterion for column selection [106,118]. Based on three criteria, namely (i) the number of PBDEs involved in co-elutions, (ii) the number of co-eluting groups, and (iii) the number of co-elutions observed for major PBDEs, a DB-XLB column was found to be the most efficient for PBDE congener-specific separation, with a DB-1 column as runner-up. The latter is, however, preferred for routine analysis because it causes less degradation of higher brominated congeners. Degradation of certain congeners in the GC system is frequently observed. Bjo¨rklund et al. [106] described how the characteristics of the GC system significantly influence the determination of PBDEs by GC-MS. If not selected properly, the column brand, type of retention gap, press-fit connector, and stationary phase, as well as column length and injection technique may have a very strong influence on the trueness and precision of the analysis. By selecting an erroneous GC set-up, the yield of nona- and deca-BDEs can be reduced to zero and the precision of the determination of congeners with more than five bromine atoms can be strongly decreased. In a system with on-column injection, it is mandatory to use a retention gap, but care should be taken as some coatings can cause excessive degradation of highly brominated congeners. Bjo¨rklund et al. [106] have observed that the highest degree of degradation for BDE 209 was observed for untreated, intermediate polar and polar retention gaps. The best results were obtained with a Silteks (Restek) deactivated retention gap. For BDE 209, the GC column should be relatively short, preferably 10–15 m, to reduce as much as possible the residence time of BDE 209 in the system [46]. The separation is not very critical, as all other PBDEs will elute earlier in the chromatogram and will not interfere with the peak of BDE 209. The oven temperature should not exceed 3001C and it should be applied only for a short time at the end of the oven temperature program. The short column for BDE 209 will also help to focus the peak, resulting in a better peak shape and response. The film thickness of the short column used for BDE 209 analysis should preferably be 0.1–0.2 mm, again with the aim not to extend the exposure to high temperatures unnecessarily [46]. Bjo¨rklund et al. [106] have shown that the best
530
Adrian Covaci et al.
responses for BDE 209 were obtained using a DB-1 column, whereas the worst results were obtained on a HP-1 column. It is highly possible that BDE 209 is sensitive to the type of column used, although batch-to-batch variations in the selectivity cannot be neglected. To overcome the remaining quality pitfalls associated with the degradation of BDE 209, the use of 13C-labelled BDE 209 as internal standard is encouraged [47]. Given the simultaneous presence of PBDEs and other halogenated contaminants in food samples, comprehensive two-dimensional (GC GC) techniques may offer more separation power as the detector does not always provide the required selectivity (Figure 2). Koryta´r et al. [119] evaluated six column combinations for the GC GC separation of PBDEs with m-ECD or time-of-flightmass spectrometry (TOF-MS) as detectors. They concluded that a DB-1 00765HT combination was the most suitable because of (i) the highest number of PBDE congeners separated; (ii) the least decomposition of higher brominated congeners; and (iii) the most suitable maximum operating temperature. With this set-up, there were only 17 co-eluting pairs involving 35 congeners. Focant et al. [120] have set-up a multi-residue method for PBDEs and PBBs in human milk using comprehensive GC GC-TOF-MS and isotope dilution. In contrast to the reference methods based on single dimension GC-MS, a single injection resulted in accurate identification and quantification with method LODs ranging between 1 and 15 pg/g. Whereas the GC GC ensured the chromatographic separation of most compounds, TOF-MS allowed mass spectral deconvolution of co-eluting compounds, as well as the use of 13C-labelled internal standards.
2.2.1.3 Detection. The most widely used detectors for PBDE determination are mass spectrometers operated either in electron capture negative ionization (ECNI) or in EI mode [43]. Occasionally, ECD has been used for specific applications. The different detection methods are discussed later. The advantages and drawbacks of the different available detection modes for BFRs are summarized in Table 2. 2.2.1.4 Mass spectrometric detection. Low resolution MS (LRMS) can be more easily routinely applied, while HRMS requires more experienced users and is much more costly and labour intensive. HRMS has a number of advantages over LRMS (such as increased sensitivity and selectivity), but is almost exclusively operated in EI mode. For LR-MS, ECNI, in addition to EI, can be used to obtain an increased sensitivity for (higher) brominated compounds. 2.2.1.5 Electron ionization. In EI-MS, the major ions formed from PBDEs are the M+ and the [M-2Br]+, which can be used for identification and quantification [43]. This ionization technique facilitates the analysis of PBDE congeners in the presence of possible co-eluting compounds (such as PCBs). EI-LRMS has relatively low sensitivity for higher BDE congeners (hepta- to deca-BDE).
Figure 2 Overlaid GC GC-ECD chromatograms on DB-1 007-65HT column combination of PBDEs (green), fluorinated PBDEs (orange), other BFRs (red), and PBDE metabolites (blue). Upper inserts show second dimension chromatograms for 4F-BDE 27/BDE 27 and BB 153/BDE 154. Lower insert shows part of GC GC-ECD contour plot of dust extract. Reproduced with permission from Ref. [119].
Brominated Flame Retardants as Food Contaminants
531
532
Table 2
Adrian Covaci et al.
Advantages and drawbacks of different detection techniques for BFRs
Detection
Advantages
Drawbacks
Fair sensitivity for BFRs Purchase cost Maintenance cost Easy to use
Interferences from other halogen-containing species Limited linear range Very low selectivity
EI-LRMS
Facilitates the use of labelled standards Good selectivity Relatively cheap and easy to use
Low sensitivity
ECNI-LRMS
Relatively cheap and easy to use Good sensitivity Good selectivity for brominated compounds
Frequent source maintenance required
QTrap-MS
Relatively cheap Good sensitivity Very good selectivity
Needs adequate optimization of operating conditions Consistent but sometimes unpredictable fragmentation
ITD-MS/MS
Relatively cheap Good selectivity No isobaric interferences
Needs adequate optimization of operating conditions Limited linear range Low sensitivity for higher BDEs Interferences between precursor and fragment ions for co-eluting PBDEs
HR-TOFMS
Full scan spectra Fast scan rate Spectral deconvolution and identification of unknown BFRs/contaminants Bench-top high resolution easy to use system Excellent screening tool Can also be used in ECNI mode
Limited dynamic range Matrix can saturate detection system Quantitation can be difficult
GC-MS ECD
Brominated Flame Retardants as Food Contaminants
533
Table 2 (Continued ) Detection
Advantages
Drawbacks
HRMS
Good sensitivity Very good selectivity Necessary for PBDD/Fs
Purchase cost Maintenance cost Experienced analyst required Exclusive use in EI mode
Relatively cheap Easy to use system Good selectivity Good sensitivity
Low sensitivity Relatively low selectivity Needs adequate optimization of operating conditions Purchase cost Needs adequate optimization of operating conditions Cut-off limitations for daughter ions Limited linear range
LC-MS Single Q-MS Triple Q-MS
ITD-MS/MS
Good selectivity Fair sensitivity
However, this ionization mode offers greater choice in ion selection compared to ECNI mode. EI-LRMS has been used by Dodder et al. [121] for the analysis of PBDEs (except BDE 209) in fish samples. Covaci et al. [105] have shown that EI-LRMS combined with large volume injection (20 mL), can be used for the analysis of samples with low PBDE concentrations. The detection limits in selected ion monitoring (SIM) mode varied from 0.05 to 0.30 mg/kg lw, depending on the bromination degree (tri- to hexa-BDEs). In this way, similar sensitivity to ECNILRMS, combined with a higher selectivity, was obtained by EI-LRMS. Moreover, due to the possibility of measuring the molecular ion and other distinctive fragments, EI-LRMS is the technique of choice for the identification of mixed organohalogenated compounds [116]. Another advantage of EI-MS is that it allows the use of various 13C-labelled internal standards. This is not possible in ECNI-MS (except for 13C-BDE 209), since generally only the [Br] ions (m/z 79 and 81) are monitored. HRMS is preferred over LRMS for its higher sensitivity (compared with EI-LRMS) and selectivity (compared with ECNI-LRMS). The first two worldwide interlaboratory studies on BFRs [122] revealed those laboratories using EI-HRMS obtain somewhat lower detection limits. On the contrary, a superior performance for HRMS could not be demonstrated. A similar conclusion was reached by Thomsen et al. [123] who stated that GC/ECNI-LRMS and GC/EI-HRMS are equally well suited for the determination of PBDEs in biological samples, as well
534
Adrian Covaci et al.
as in standard solutions, with respect to response, detection limits and repeatability. Both techniques can be used complementarily when confirmation of the results obtained by GC/ECNI-LRMS is necessary. The ions monitored in EI-HRMS are similar to those in EI-LRMS, but the target mass fragments can be determined much more accurately, which adds considerably to the selectivity of the technique. Recently, the simultaneous analysis of PBDEs in fish measured at high mass resolution with TOF-MS could be carried out thanks to the availability of full spectral information even at very low concentrations [124]. This unique performance feature of TOF-MS is possible without compromising signal intensity or acquisition speed settings (which may result in a rather poor spectra/peak quality). Furthermore, the application of chemical ionization resulted in a 20–100-fold decrease in sensitivity [124]. Several potential chromatographic interferences can hamper good quality data [43,125]. When working in EI-MS, potential interferences originate from chlorinated compounds, such as PCBs. The nominal masses corresponding to ions monitored for di-BDEs and penta-CBs are the same (m/z 326), whereas a similar interference occurs for tetra-BDEs and hepta-CBs. Special attention should be paid to the co-elution between BDE 47 and CB 180 on 30 m DB-5 type columns [43] and therefore, identification criteria should be very restrictive (retention time and relative isotopic peak ratios).
2.2.1.6 Electron capture negative ionization (ECNI-LRMS). Electron capture ionization is a ‘‘soft’’ ionization technique based on interactions between thermal energy electrons and electrophilic molecules, such as PBDEs. In ECNI mode, the electron energy should be very low to facilitate electron capture and depends on the molecular structure of the analyte [126]. Koryta´r et al. [118] found that less co-elutions for PBDE congeners with different bromine numbers were observed compared to PCBs. This means that the use of MS detection in the EI mode, which enables a separate quantification of co-eluting homologues with a different number of bromine substituents, is not of primary importance and that detection in the ECNI mode will yield reliable results in many cases. Being a very sensitive technique, ECNI-MS is widely used for the determination of low amounts of PBDEs in various samples [109,127–129]. Brominated compounds show a typical 79Br (50.5%) and 81Br (49.5%) isotope distribution pattern [129]. To overcome quality problems associated with the degradation of BDE 209, the use of 13C-labelled BDE 209 for isotopic dilution in the ECNI-MS mode as proposed by Bjo¨rklund et al. [130] has found a broad application. Owing to the overlap of the ion clusters of native and labelled BDE 209, the ion selection should be done with care. A combination of the [Br] (m/z 79 and 81) and [C6Br5O] (m/z 486.7 and 488.7 for BDE 209; and m/z 494.7 and 496.7 for 13C-BDE 209) ions in ECNI-MS significantly increases selectivity, sensitivity and accuracy in the determination of BDE 209. Apart from using adequate standards, Bjo¨rklund et al. [130] also highlighted the need to optimize several other parameters, such as ionization energy, moderating gas pressure, ion
Brominated Flame Retardants as Food Contaminants
535
source temperature, and analyser temperature. Other parameters, such as the type of moderator gas and the instrument used, were also found to influence the spectral data [131]. For ECNI-MS, other brominated compounds, such as MeOPBDEs or PBBs, could also interfere with the PBDE determinations. One MeOtetra-BDE congener and one MeO-monochloro-tetra-BDE were found to co-elute with BDE 100 and BDE 99, respectively, using a DB-5 column and alternative stationary phases that can resolve these co-elutions have been suggested [132].
2.2.1.7 Electron capture detection. Although ECD is known to be very sensitive for organohalogenated compounds (such as PCBs and organochlorine pesticides), it has been proven useful only in applications where concentrations of PBDEs were relatively high [133]. Despite its relatively low purchase and maintenance costs, combined with a relatively good sensitivity for compounds with 4 or more bromine atoms, several drawbacks have reduced its application. One major problem is that the sensitivity is not only influenced by the bromine/ halogen load, but also by the substitution pattern of the rings [129]. This results in unequal responses for the different congeners. Furthermore, ECD is known for its narrow linear range [129]. Another drawback is the lack of selectivity. Any halogen-containing molecules will produce a signal and therefore PBDE analysis can be influenced, especially when PCBs are present at high concentrations [113]. Many of these co-elutions can be avoided by an adequate sample preparation and by appropriate column selection and optimization of the oven temperature program. 2.2.1.8 New modes of detection. Recently, new analytical approaches, such as ion-trap MS (ITD-MS/MS; ITD, ion-trap detector) [82,134,135] or quadrupole ionstorage MS (QTrap-MS) [136,137] were evaluated for the analysis of PBDEs. Go´mara et al. [82] have established a method for the determination of 10 PBDE congeners by means of GC-ITD-MS/MS operated in EI mode. The fragment ions monitored correspond to loss of two Br atoms from the molecular ion. The feasibility of the overall method (sample preparations plus instrumental detection) has been evaluated by participating in interlaboratory comparison exercises with satisfactory results. Using GC-QTrap-MS for the analysis of 20 PBDEs, the obtained sensitivity was similar to that of ECNI and greater than that of EI quadrupole MS [137]. This technique is promising for food analysis because of its superior selectivity compared to the commonly used ECNI-MS. A drawback of QTrap-MS is the varying isolation and fragmentation depending on the degree of bromination [137]. Nevertheless, QTrap-MS may constitute a low-cost, rapid, and reliable alternative to HRMS.
2.2.2 HBCDs HBCDs can be determined by GC-ECNI-MS, but this approach is more problematic than for most PBDEs. Technical HBCD consists of three diastereoisomers: a-, b-, and g-HBCD, the latter being predominant [17]. Interconversion of the HBCD diastereoisomers occurs when technical HBCD is exposed to
536
Adrian Covaci et al.
BDE 77 (IS)
BDE 77 (IS)
BDE 47 + HBCD breakdown products
HBCD
(a)
BDE 128 (IS)
BDE 47
BDE 128 (IS)
(b)
Figure 3 Co-elution of HBCD breakdown products with BDE 47 on a 25 m 0.22 mm 0.25 mm HT-8 capillary column; (a) sample with high HBCD levels and (b) sample with no HBCD [117]. Reproduced with permission from Ref. [117].
temperatures above ca. 1601C and therefore diastereoisomer-specific analysis of HBCDs by GC-MS is not possible. At higher temperatures (around 2401C), as well as in dirty injection systems, HBCDs further degrade to lower brominated analogues (Figure 3) [117]. Close inspection of chromatograms shows that the HBCD peak is always somewhat broader than the near eluting PBDE peaks. Since the response factors of the three diastereoisomers do not apparently differ very much [138], HBCDs can be quantified as total HBCDs by GC-MS. However, uncertainties are larger compared to those obtained for a number of PBDEs, which is shown by a larger RSD in quality charts (ca. 25–30%). When analysing HBCDs by GC-MS, the cleanliness of extracts and the liner are essential. In contrast to GC, reversed-phase LC, coupled to electrospray ionization (ESI) or atmospheric pressure chemical ionization (APCI) MS, is a versatile tool for the diastereoisomer-specific determination of HBCDs in environmental samples. Although the structure and chemical properties of HBCD suggest the use of APCI for this molecule, Budakowski and Tomy [139] have shown that this technique does not meet the expectations and that the ion intensities using ESI were significantly higher. Using LC-ESI-MS/MS and single reaction monitoring for the transition [M-H] (m/z 640.6) - [Br] (m/z 79 and 81), Budakowski and Tomy [139] have developed a selective and sensitive method with LODs of 4–6 pg on-column for a standard solution of g-HBCD. Jana´k et al. [140] have further optimized both the LC and MS conditions resulting in baseline separation of the HBCD diastereoisomers and in LODs of 0.5 and 5 pg on-column for g-HBCD in standard solutions and fish extracts, respectively (Figure 4). However, the sensitivity of ESI-MS is substantially lower compared with GC-ECNI-MS. This method is therefore only applicable for the analysis of relatively highly polluted samples, such as fatty fish. Although LC-MS/MS is now the method of choice for the determination of HBCDs, several pitfalls can hamper results of good quality. Tomy et al. [141] have studied crucial parameters, such as co-elution with other analytes or with matrix components, which can lead to ion-suppression. This effect can be compensated for by means of (i) standard addition method, (ii) dilution of the sample, (iii) improved sample clean-up, (iv) improved chromatographic separation, (v) use of
Brominated Flame Retardants as Food Contaminants
537
Figure 4 Chromatographic separation by LC/MS of HBCD diastereoisomers in standard and technical mixtures.
a matrix-matched external standards, or (vi) spiking the sample with a labelled internal standards before injection (e.g., deuterated HBCDs). This latter standard performs a dual role: to compensate for instrumental fluctuations of the mass spectrometer between injections and to compensate for matrix-related ion suppression or enhancement effects that can occur in the ion source. Tomy et al. [141] concluded that accurate measurements of native HBCD diastereoisomers in environmental matrices are compromised without the use of a labelled standard. Triple quadrupole instruments are preferred due to their high selectivity and sensitivity. Additionally, Morris et al. [76] compared the performances of single quadrupole MS and ITD-MS for the analysis of HBCDs. Using a single quadrupole MS, collision-induced dissociation is not possible, which gives the ITD-MS a theoretical advantage. Although ITD-MS allows the monitoring of daughter ions, the HBCD-specific transition (m/z 640.6 - m/z 79 and 81) cannot be used because the m/z of the daughter ion is lower than the cut-off value of the instrument (typically 25% of the parent ion). Differences in the sensitivity of different HBCD diastereoisomers were observed between the two MS instruments [76]. The a-HBCD diastereoisomer was the most sensitive on the quadrupole MS, whereas the g-HBCD diastereoisomer was the most sensitive on the ITD-MS. The linearity of the response was limited (20250 ng/mL). The decreased response in ESI-MS at high analyte concentration was attributed to ‘‘analyte saturation’’, where charge competition occurs in the trap [76]. LOQs were around 150 pg on-column for both quadrupole and ITD instruments. Morris et al. [76] also reported the presence of a weaker MS signal at m/z 676.7 [M+Cl– H] originating from a chlorine adduct. However, the abundance of this
538
Adrian Covaci et al.
fragment is variable for real samples. More information regarding the analysis of HBCDs can be found in recent reviews by Covaci et al. [142] and Law et al. [17].
2.2.3 TBBP-A Although TBBP-A is the most widely used brominated flame retardant, this compound is not frequently measured, probably due to its presence at lower concentrations compared to PBDEs and HBCDs and to its lower bioaccumulation potential. Among the predominant BFRs, TBBP-A is the most polar molecule, which demands therefore more complicated methods for a proper determination. While derivatization is required before GC analysis, LC presents the advantage that no derivatization step is required, but, in this case, the extract should be acidified [47]. Both the derivatization and acidification step can introduce errors and/or losses [47]. In terms of detection power, LC-ESI-MS/MS can be competitive with published GC-EI-MS/MS techniques, with LODs in the ppt range [143]. A GC-HRMS method requiring derivatization with methyl-chloroformate was developed by Berger et al. [91]. However, this method suffered from a rather restricted linear range and incomplete derivatization, leading to low recoveries. This might also be explained by the presence of bulky bromine substituents adjacent to the two hydroxyl groups, resulting in an incomplete double derivatization. For the quantification of egg sample extracts, LC-ESI-TOF-MS was superior to GC-MS, with a LOQ of 3 pg TBBP-A on column [91]. This was explained by the high-resolution filtering potential of the TOF-MS, which eliminates the matrix background from the mass chromatograms. The commercial availability of 13C-TBBP-A has improved the quality of the LC-MS analysis to a great extent. The occurrence of matrix effects, which can affect analyte ion intensity, accuracy, and reproducibility, can be much diminished by the use of labelled standards. Furthermore, the soft ionization in LC-ESI-MS enables monitoring the intact molecule [144]. Together with sample clean-up, these two features improve both trueness and precision of the analysis. To¨llback et al. [144] have found that ESI in negative ionization mode was optimal, with sensitivity up to 40 times higher compared to APCI. The use of selected reaction monitoring (SRM) produced mainly ions with m/z 79 and 81. Other fragments could significantly made the LODs worse, because they were only formed in low amounts, even at high collision energy. The most sensitive method was run in SIM (m/z 542.7 and 544.7). To¨llback et al. [144] also noted that TBBP-A standard solution can be debrominated if not protected properly from light. Apart from triple quadrupole MS, ITD-MS was also used successfully for the determination of TBBP-A [145]. An LOD of 5 pg on-column could be obtained for standard solutions. This value is comparable to the LOD reported for GC-ECNIMS after derivatization [127]. The ITD scan range was set from m/z 145–543, with mass transitions from m/z 543 to 528 and from m/z 543 to 448 being also useful. Surprisingly, little ion suppression of the TBBP-A signal from sediment matrix components in the ESI process was observed [145]. Given its successful
Brominated Flame Retardants as Food Contaminants
539
application on complex samples such as sewage sludge, this technique could be very promising for the analysis of food samples. In a study on degradation products of TBBP-A formed after UV-exposure, ESI did not prove to be very useful, whereas the ionization of TBBP-A degradation products by means of atmospheric pressure photo ionization (APPI) was very efficient [146]. A potential drawback of APPI is its susceptibility towards the mobile phase composition. Higher signals were seen at the end of the gradient elution, close to 100% acetonitrile. This particular feature could constitute a limitation for the quantitative analysis of mixtures of BFRs, their degradation products or metabolites [146].
2.2.4 PBDD/Fs HRMS appears to be the only instrumental technique able to reliably analyse PBDD/Fs in low contaminated matrices [147]. This technique combines excellent selectivity and sensitivity that is obligatory for the analysis of these ultra-trace contaminants. Furthermore, 13C-labelled surrogate PBDD/Fs have been commercially available for a few years and this has served to increase the number of laboratories analysing PBDD/Fs. However, there are still too few publications relating to the instrumental analysis of PBDD/Fs in food. Conversely, PBDD/Fs have been routinely determined by HPLC-UV and HPLC-MS at relatively high levels, up to parts per billion, in waste of electric and electronic equipment [148]. Current analytical methodology for PBDD/Fs is analogous to methods used for chlorinated dioxins. Indeed several groups working independently have optimized methods of surprising similarity [48,80,81]. In general, samples are extracted and cleaned following published methodology for PCDD/Fs. Analysis is typically carried out by HRGC-HRMS operated in positive EI using SIM mode. Differences are seen in the choice of chromatographic column, with DB-5-type columns being the most commonly used. On the whole, thin films (e.g., 0.1 mm) are required to minimize sorption and degradation on column. Column lengths vary from 15 to 60 m. Unfortunately, two hexabromodioxins (1,2,3,4,7,8-H6BDD and 1,2,3,6,7,8-H6BDD) are shown to co-elute on a DB5-MS-type phase, regardless of column length [81]. Consequently these compounds are typically reported as a total of two congeners. However, even when employing GC-HRMS, LODs for PBDD/Fs in food are typically an order of magnitude higher than PCDD/Fs using the same technique [149,150]. This poorer detection power is due in part to inferior molecular ion yields for PBDD/Fs and greater susceptibility to degradation in the harsh environment of a GC injector, column and interface than that of chlorinated dioxins. The presence of PBDDs in the marine environment has been recently demonstrated by their detection in blue mussels from the Baltic Sea [151]. Furthermore, their natural formation from naturally produced precursor molecules such as HO-PBDEs by cyanobacteria has been demonstrated [152]. The analytical procedures were similar to those routinely used for the determination of PBDEs in biological samples. Identification and characterization of PBDD congeners was done using GC-HRMS and three GC columns of
540
Adrian Covaci et al.
different polarity, including a column with an enantioselective stationary phase. The identity of several PBDD congeners could be unequivocally confirmed since some congeners were available as individual reference standards.
2.2.5 New BFRs Only few reports on new or previously uninvestigated BFRs have been published. Since these new BFRs have similar structures to those of already known BFRs, existing analytical methodologies are commonly applied. Kierkegaard et al. [153] have investigated the presence of decabrominated diphenyl ethane (DeBDethane), marketed as an alternative to BDE 209, in abiotic matrices. Identification was performed using HRMS by monitoring the most abundant ion fragment [C6Br5CH2]+, while quantitative measurement is achieved by means of ECNIMS due to its higher sensitivity. Similar to BDE 209, a rising baseline was observed before the DeBDethane peak, suggesting degradation in the GC system. Seeing the similarities between BDE 209 and DeBDethane, such as degradation in the GC system, Konstantinov et al. [154] emphasized that similar measures should be taken to ensure good quality data (e.g., the use of corresponding 13C-labelled standards as internal standards). Using similar techniques as used for the analysis of PBDEs, e.g., GC-ECNI-MS, Hoh et al. [155] have reported the presence of 1,2-bis(2,4,6-tribromophenoxy)-ethane (TBE) in abiotic samples. The occurrence of these new BFRs in food samples has not been reported yet.
2.3 Quality assurance/quality control Quality Assurance (QA) is a set of procedures consisting of quality control (QC) activities that are undertaken to affirm the quality of analytical results. As a general rule, between 10% and 20% of the analysis time is spent to ensure good quality of the performed analyses [84]. To avoid potential sources of error during sample preparation for BFR analysis, some treatments should be avoided to preserve the integrity of particular BFRs. For instance, HBCDs are not stable under alkaline conditions, whereas high temperatures and/or extensive saponification times can result in decomposition of highly BDEs and BBs [46]. Complete evaporation of the extracts to dryness should be avoided as PBDEs and PBBs tend to adsorb to glass even more strongly than PCBs, which may result in incomplete dissolution upon reconstitution. For BDE 209, solvents such as toluene, DCM or acetone:n-hexane mixtures are preferred because of its limited solubility in other organic solvents [43]. Similarly, TBBP-A tends to adsorb to glass when using n-hexane as solvent, whereas it remains in solution with methanol [156]. BDE 209 and possibly other higher BDE congeners are photosensitive and thus direct exposure to UV light should be avoided. Wrapping the containers, extraction funnels and solvent receptacles with aluminium foil or using amber glassware are probably the simplest preventive measures. Additional recommendations regarding this issue are given by de Boer and Wells [47]. Measures to be performed on a routine basis include the regular analysis of a reagent and procedural blank for each 10 samples [84]. Procedural blanks should
Brominated Flame Retardants as Food Contaminants
541
be analysed under the same conditions as the samples and should be considered for the final results. According to Pa¨pke et al. [84], BFR values in samples should only be reported when exceeding the levels found in procedural blanks by a minimum factor of two. Alternatively, it was proposed that reported levels of BFRs should be above a value equal to the procedural blank value plus 10 [61], 5 [156] or 3 times [62,88] the associated standard deviation (SD) of the procedural blanks. However, this method can only be applied if the blank values are relatively constant (RSDo30%). Dodder et al. [121] applied a correction for procedural blanks if the blank value was between 10% and 20% of the measured value in the sample. If the procedural blank value was less than 10%, no corrective action was taken. Data was excluded from further consideration if the blank value exceeded 30% of sample measurements. Some analytical alternatives to reduce blank values have been recommended by Pa¨pke et al. [84]. Seeing the low BFR levels that are generally measured in food, the use of a method blank cut-off value equal to 3 times SD of the blank measurement is a good compromise between detection power and data quality. Using this approach, a 99.5% probability is ensured that the measured value originates from the sample and not from the blank. Thomsen et al. [157] have observed that the analyte response can be (positively) affected by the matrix residues that are present in the extract. This is probably caused by an increased protection of the analytes from adsorption in the injector when matrix residues are present in the extract and results in more analytes being introduced into the chromatographic column. Sellstro¨m [129] has reported a similar effect for fish tissue for which the recovery of BDE 209 was higher when a matrix was present. If relative recoveries from spiked samples are acceptable and not statistically different from recoveries calculated from standard solutions, calibration curves can be made from standard solvent-based solutions [157]. If not, the matrix effect should be investigated and if pronouncedly present, calibration curves should be established by means of matrix matched spiked standards. For HBCD analysis by LC-MS, the opposite is generally the case; the presence of matrix constituents give rise to suppression of the analyte ions in the ionization chamber, resulting in a lower sensitivity [158]. The best procedure to evaluate the accuracy of analytical methods used for BFR determination is the analysis of reference materials. There is still a limited number of reference materials certified for BFRs (NIST SRM 2585 – indoor dust; NIST SRM 1589a – lyophilized human serum; NIST, National Institute of Standards and Technology) and more materials are needed. When reference materials are not available, the standard addition method may still be accepted as a valid approach to evaluate the trueness and precision of the analytical procedures [84]. Preferably, validation should be performed using a QC sample spiked, at least, at two different spiking levels. When possible, proper incubation and aging of the spiked samples should be carried out so that the spiked compounds mimic as much as possible the behaviour of the naturally incurred analytes [59]. 13 C-labelled PBDEs are preferred as internal standards for quantification based on the isotopic dilution method [43,47]. When this approach is not
542
Adrian Covaci et al.
possible, e.g., during GC-ECNI-MS analysis, PBDE congeners that are not present in the samples to be analysed or fluorinated derivatives (F-PBDEs) can be used as internal standards [159]. Additional recommendations regarding internal standards are given by Pa¨pke et al. [84]. Shewhart plots for target compound data in selected QC samples allow an efficient detection of special causes of variation during the analysis and are considered as a valuable approach for internal QC [84]. External QC should include regular participation in interlaboratory studies and proficiency tests. Additional suggestions and recommendations related to QC/QA can be found in the dedicated literature [47,84]. Since 1999, several international interlaboratory studies have been organized to improve the quality of the analysis of BFRs. A wide range of matrices has been used during these exercises and this has enabled researchers to adequately validate their methods and to implement reliable QC procedures. Four interlaboratory studies were organized by the combined effort of The Netherlands Institute for Fisheries Research, QUASIMEME, and the Bromine Science and Environmental Forum [47,122]. All major PBDE congeners (BDE 28, 47, 99, 100, 153, 154, 183, and 209), as well as HBCDs, TBBP-A and dimethylated TBBP-A were targeted. The exercise included materials that are pertinent to food analysis, such as fish, fish oil, shellfish, and human milk. In parallel with the increasing number of participating laboratories in time, a general tendency for qualitative improvements of results and thus of analytical methods was observed. This was possible due to the guidance disseminated by the organizers after each exercise and to the increased availability of (labelled) standards. Although these interlaboratory studies have shown that most laboratories have improved their analytical methodology for PBDEs, several difficulties still persist for the analysis of BDE 209. Since no other interlaboratory studies have assessed higher BDE congeners, the reliability of the analysis of hepta- to nona-DEs is at present not clear. Recently, a first exercise on the determination of HBCDs in a standard solution, naturally contaminated fish oil and fish was organized by the Norwegian Institute of Public Health (Oslo, Norway) [160]. One of the conclusions of the study was that no significant differences were found between results obtained by GC-MS and LC-MS for total HBCDs. Although results for total HBCD were acceptable, improvement on the quality of isomer-specific data is needed.
3. OCCURRENCE IN FOOD 3.1 PBDE levels in food and dietary intake in North and South America Table 3 provides a summary of the levels of PBDEs that have been measured in food and edible fish in Canada and the USA and some recent data on farm-raised fish from Chile. Dietary intakes of PBDEs were estimated from the food levels in a few cases and are also given in Table 3. In Canada, PBDEs were first included in
Matrix type
Total diet study (n ¼ 49 composites)
Total diet study (n ¼ 46 composites)
Fish and shellfish (n ¼ 122)
Whitefish (n ¼ 41)
Fish (n ¼ 14)
Salmon (n ¼ 165 composites)
Location
Whitehorse, YT, Canada
Vancouver, BC, Canada
Vancouver, BC, Halifax, NS, and Toronto, ON, Canada Columbia River, Canada
Southern Chile
North and South America
Nd–0.02 mg/kg ww
11.5–24 mg/kg lw 0.9–2.0 mg/kg ww NA farmed: 1–6 mg/kg ww Chile farmed: 0.3–6 mg/kg ww NA wild: 0.05–6 mg/kg ww NA retail: 0.3–5 mg/kg ww NA
NA
NA
Unspecified
Near laboratory background
Concentrations BDE 209
Yearly averages: 4.3–71.8 mg/kg ww
Dairy: nd–0.07 mg/kg ww Meats: 0.03–1.2 mg/kg ww Fish: 0.1–0.37 mg/kg ww Other: 0.01–0.21 mg/kg ww Dairy: 0.00001–0.27 mg/kg ww Meats: 0.02–0.25 mg/kg ww Fish: 0.04–1.5 mg/kg ww Other: 0.0002–0.28 mg/kg ww Fish: 0.01–5.5 mg/kg ww Shellfish: 0.001–2.0 mg/kg ww
Range of total PBDEs (excluding BDE 209)
0.51 ngkg bw/d (all)
0.44 ng/kg bw/d (adult) 0.64 ng/kg bw/d (all)
[55]
[70]
[71]
www.hc-sc. gc.ca
[161], www.hc-sc. gc.ca
Reference
Farmed EU W [69] NA W Chilean W wild; Chinook W other salmon
Levels increased from 1998–2000 (W 10-fold) Farm-raised
Trout and salmon highest; domestic W imported
Fully prepared foods; intake: meat (41%), fish (27%), dairy (20%)
Fully prepared foods; intake: meat (76%), fish (3%), dairy (8%)
Dietary exposurea Comments
Table 3 North and South American levels of PBDEs in various retail foods and edible fish and estimated dietary exposures
Brominated Flame Retardants as Food Contaminants
543
Fish, meat, and fowl (n ¼ 22)
Beef, pork, and chicken (n ¼ 65)
USA: nine cities
Fish: 0.02–4.8 mg/kg ww Meat: 0.06–0.38 mg/kg ww Fowl: 0.07–2.3 mg/kg ww Beef: nd–2.5 mg/kg lw Pork: 0.1–16.3 mg/kg lw Chicken: 0.19–16.6 mg/kg lw
0.9–5.0 ng/kg bw/d (meat and fish only)
15–45 ng/kg bw/d (meat only)
Near laboratory background
Chicken and pork levels W beef
Dietary supplements Wild, farm-raised, and free-range; fish and fowl W meat
Highest levels in urbanized water sheds Levels correlated to age, not lipid content of fish Lake Ontario trout highest; Lake Erie lowest Wild; levels highest in most populated areas Wild and farm-raised
Dietary exposurea Comments
Nd–0.80 mg/kg ww
NA
7.6–19 mg/kg lw
Fish oils (n ¼ 4)
Northern CA, USA
Not generally detected
0.04–38 ppb ww
Fish (n ¼ 22)
Maryland, D.C., and North Carolina, USA Maryland, USA
NA
13.3–1,020 mg/kg lw 0.04–1,809 mg/kg ww
NA
773–8120 mg/kg lw 44.6–150 mg/kg ww
Fish (n ¼ 43 composites)
California, USA
NA
Nd–19,300 mg/kg lw Nd–1250 mg/kg ww
NA
Lake trout (n ¼ 40)
Great Lakes
Concentrations BDE 209
Range of total PBDEs (excluding BDE 209)
Lake averages: 27–95 mg/kg ww
Trout and whitefish (n ¼ 10) Salmon (n ¼ 21)
Washington, USA
Lake Michigan tributaries
Matrix type
Location
Table 3 (Continued )
[77]
[96]
[57]
[164]
[163]
[114]
[132]
[162]
Reference
544 Adrian Covaci et al.
Breast milk (n ¼ 59) Breast milk (n ¼ 98) Indoor dust (n ¼ 17)
Multi-media Urban Model data
Texas, USA
Urban Canada
162–8750 mg/kg dm
618–27 700 mg/kg dm
20 ng/kg bw/d (toddler)
307 ng/kg bw/d (nursing infant) 280 ng/kg bw/d (nursing infant) 3.3 ng/d (adult) 120–1180 ng/d (child) 2 ng/kg bw/d (adult)
Nd–8.24 mg/kg lw Nd–0.14 mg/kg ww NA
Indoor dust: 5,060 mg/kg Not included dm; indoor air: 445 pg/ m3; outdoor air: 81.8 pg/ m3; soil: 3,090 mg/kg dm Food from TDS (above)
0.9–1.2 ng/kg bw/d
nd–1.27 mg/kg ww
Meat/egg: nd–2.55 mg/kg ww Fish: 0.009–3.7 mg/kg ww Dairy: 0.004–0.42 mg/kg ww 6.2–419 mg/kg lw 0.08–21.3 mg/kg ww 0.8–956 mg/kg lw [167,168]
[165,166]
[165]
Dust ingestion: [169] 0.56 mg/d adult, 0.02–0.2 g/d child [168] Intake from dust/ soil: 60% for adults, 90% for children Dust ingestion: 0.02 g/d adult, 0.05 g/d child
Levels in fish W meat W dairy; Intake from meat 60–70%.
Notes: NA, not analyzed; nd, not detected; LOD, limit of detection; ww, wet weight; lw, lipid weight; dm, dry matter; LB, lower bound (valuesoLOD substituted with 0); MB, medium bound (valuesoLOD substituted with ½ LOD); and UB, upper bound (valuesoLOD substituted with LOD). a Dietary exposure for total PBDEs.
D.C., USA
Canada
Various animal products (n ¼ 62)
Dallas, TX, USA
Brominated Flame Retardants as Food Contaminants
545
546
Adrian Covaci et al.
the national total diet survey conducted by Health Canada in 1998 [161] (www.hc-sc.gc.ca/fn-an/surveill/total-diet/index_e.html). This survey analyses typical food from different major cities in Canada, usually one city per year. The food was prepared as they normally would be for consumption, composited, and then analysed for contaminants. The levels of contaminants are combined with consumption data to estimate dietary intake. Dietary intakes of PBDEs calculated from these studies show a typical average Canadian daily intake of about 50 ng. Meat and meat products were the largest contributor to dietary intake in Canada. However, the large variation of PBDE levels in the food types resulted in somewhat different dietary contributions from the two years studied; contribution from meats were 76% in 1998 and 41% in 2002. Canadian retail fish and shellfish collected from three Canadian cities and analysed for PBDEs showed that, on average, salmonid fish (salmon, trout, and char) had higher levels than other seafood (geometric means ¼ 1.6, 1.5, and 0.62 mg/kg wet weight (ww), respectively), and mussels, tilapia and shrimp had the lowest levels (geometric mean ¼ 0.26, 0.18, and 0.05 mg/kg ww, respectively) [71]. However, while tilapia had generally low levels, one tilapia fillet had PBDE levels similar to that of the highest salmon fillet: 5.0 and 5.5 mg/kg ww, respectively. These data again show a large range of contamination within any one type of product. Two factors that were positively associated with higher levels of PBDEs in the seafood were lipid content and domestic origin (produced in Canada as opposed to imported). No significant difference was observed between wild-caught and farm-raised products, although the authors noted that all of the high outliers were farm-raised samples and that the number of samples available for comparison was low and may have prevented observation of a significant difference. In a larger study of wild and farm-raised salmon from North America, South America, and Europe, Hites et al. [69] observed significant differences between the wild and farm-raised salmon. The levels of total PBDEs decreased in the order European farmed W North American farmed W Chilean farmed W wild salmon. One exception to the low levels in wild salmon were Chinook salmon from British Columbia (Canada) and Oregon (USA), which had an average 17times higher than other wild salmon (2.3 mg/kg ww vs. 0.13 mg/kg ww). The high levels of PBDEs in farmed salmon were explained by the contamination level of the feed sources and, in the case of Chinook salmon, by its top position in the food web. The low levels of PBDEs in Chilean farmed salmon have been confirmed by Montory and Barra [55] who found an average of 1.5 mg/kg ww from five farming areas in Southern Chile. No correlation with lipid content was observed, but a strong correlation was found between the contamination in the fish tissues and their feed. In addition to farmed and ocean-caught salmon, PBDE levels have been reported in other edible wild fish from various locations in North America including rivers in the state of Washington [162], the Columbia River in Canada [70], the Great Lakes [114,133], the California coastline [163], and the eastern coast of the USA [164]. Hayward et al. [164] found that Atlantic farmed and Alaskan
Brominated Flame Retardants as Food Contaminants
547
wild salmon had the lowest PBDEs levels of three classes of fish purchased in British Columbia (Canada), Maryland and North Carolina (USA), 0.04–1 .7 mg/kg ww. Striped bass and bluefish from the Atlantic coast, however, had average levels of 5.4 and 15.1 mg/kg ww, respectively. These higher levels probably reflected contamination in the highly populated and industrialized areas along the Atlantic coast such as the Chesapeake Bay which these fish inhabit. Cod and salmon oil dietary supplements purchased in Maryland (USA) had PBDE levels between 7.6 and 19 mg/kg lw [57]. Along the California coast, higher levels of PBDEs were found in edible fish caught in bays near highly populated areas such as San Francisco, Los Angeles, and San Diego [163]. The level of total PBDEs in all fish samples from along the Californian coast ranged from 0.04 to 17.9 mg/kg ww and averaged 4.8 mg/kg ww (data in manuscript converted from lw). Rainbow trout and mountain whitefish from rivers draining urban areas in the state of Washington (USA) had some of the highest PBDE levels reported in North American fish (up to 1,250 mg/kg ww) [162]. Mountain whitefish from the Columbia River showed average PBDE concentrations increasing from 1992 to 2000 by up to 12-fold in some areas (6.1– 71.8 mg/kg ww) [70]. The levels in fish from the more urbanized Columbia River watershed were 20–50 times higher than those found in nearby pristine waters. In tributaries of Lake Michigan, salmon ranged from 44 to 148 mg/kg ww [133], and lake trout from the four other Great Lakes ranged in average levels from 25 mg/kg ww in Lake Erie to 95 mg/kg ww in Lake Ontario [114]. In addition to industry and population along the Lakes, Luross et al. [114] suggested that water retention times and atmospheric deposition influenced contamination levels in the chain of lakes. Therefore, Lake Erie with the lowest water retention time (2.6 years) had the lowest contamination levels and Lake Superior may have received most of its contamination from atmospheric deposition. In the USA several market basket surveys have been conducted to measure PBDE levels in a variety of food products and estimate dietary intakes based on these levels. A survey of foods from markets in Northern California found fish and fowl had higher PBDE levels (0.2–5.0 mg/kg ww) than beef and deer meat (0.16–0.38 mg/kg ww) [96]. No difference was noted in contamination levels between chicken and beef raised under free-range conditions or typical industry conditions. In a survey that focused on meat products purchased at supermarkets across the country, Huwe and Larsen [97] found that chicken and pork products had higher PBDE levels than beef products (means ¼ 3.0, 1.7, and 0.46 mg/kg lw, respectively). The chicken and pork samples showed a large range of contamination (0.1–16.6 mg/kg lw) suggesting a source of PBDE contamination in the food production chain that could, consequently, be identified and eliminated. A wider market basket study including margarine, eggs, fish, meat, and dairy products was conducted on samples collected at large supermarkets in Texas, USA [165]. The results from this study were similar to the other two USA market basket surveys and showed that fish and poultry had higher PBDE levels than beef. The range of PBDE levels in meats was somewhat smaller than the range reported by Huwe and Larsen [97], but again showed large variations between samples (0.04–1.4 mg/kg ww or 0.09–5.8 mg/kg lw). One chicken liver
548
Adrian Covaci et al.
sample contained 44.3 mg/kg lw. Dairy products in this survey had a somewhat larger range of PBDE contamination than found in the Canadian total diet studies (0.008–0.68 mg/kg ww vs. nd – 0.27 mg/kg ww). Dietary intakes were estimated from each of the USA market baskets and showed a range of adult daily intakes: 0.9–5.0 ng/kg bw from fish and meat in northern California [94], 0.3–0.8 ng/kg bw from domestic meats [97], and 0.87– 1.3 ng/kg bw from a more complete diet [165]. Dietary intake estimates for children (ages 1–18 or 19) were higher than adults on a body weight basis: 1.1– 5.0 ng/kg bw [94] and 1.1–2.7 ng/kg bw [165]. Like the Canadian total diet survey, meat and meat products contributed the majority of the dietary intake in the USA (60–73%) for all age categories [165]. For nursing infants in North America dietary intake has been estimated at about 300 ng/kg bw/d, which is higher than for any other age group [165,168].
3.2 PBDE levels in food and dietary intake in Europe and Asia Table 4 provides a summary of the levels of PBDEs that have been measured in foodstuffs and fish oil dietary supplements in locations outside of the Americas. The table also summarizes the various estimates of dietary exposure derived from such studies. A recurrent message from both Europe and Asia is the important role played by the consumption of fish and seafood, with its ingestion typically comprising around 50% of overall dietary exposure. Related to this, there have been several studies that indicate the potential for exposure via ingestion of fish oil dietary supplements. Other important food groups with respect to dietary exposure to PBDEs include dairy products (including eggs) and meats. Interestingly, although some studies have specifically excluded plant-based comestibles on the assumption that their contribution to dietary exposure would be negligible, there are some indications that this may not be entirely accurate. Human exposure via a vegan diet was shown to be lower than that via an omnivorous diet but still appreciable [95]. Whereas available measurements support the idea that exposures via ingestion of fruit and vegetables are low, this is not the case for oils and fats of vegetable origin [93], and it would seem prudent to include such foodstuffs in future studies. D’Silva [149] also published similar findings when reporting results of the analysis of archived total diet survey samples from the United Kingdom; 70% of dietary exposure to PBDEs in the UK in 2000 came from non-meat sources — vegetables, fruit, bread, and dairy products. An important issue that emerges from this meta-analysis is the indications of contamination of foodstuffs with BDE 209. Whereas the difficulties in achieving reliable analysis of this congener have to date restricted severely the available data on this congener, there are several indications that it is present in human foodstuffs, with evidence from the UK suggesting that the magnitude of dietary exposure to this congener may exceed that arising from the sum of all other PBDEs. The origins of this contamination with BDE 209 (i.e., food chain transfer or direct contamination during processing, packaging, or storage), and whether it
Sample type
Retail foods and fast foods; no vegetables
Market basket study
Fresh and canned fish (n ¼ 70)
Retail samples of: meat, dairy produts, cereals; vegetables fruit, fats, and oils
Location(s)
Belgium
Finland
Ireland
Ireland
23 ng/d (LB) 48 ng/d (UB)
o LOQ (not defined)
0.17 (fruit/ vegetables)– 1.5 mg/kg lw (turkey); UB
0.05 (sardines)– 5.1 mg/kg ww (farmed salmon)
NA
NA
NA
NA
44 ng/d
Dietary exposure (total PBDEs)a
Concentrations BDE 209
NA 0.82 (liquid milk products)–850 ng/kg ww (fish)
Nd (beef)–1,570 ng/kg ww (salmon)
Concentrations of total PBDE (excluding BDE 209) Foods collected 2005; P BDE ¼ 28, 47, 99, 100, 153, 154, 183; fish accounts for 40%, meat 30%, and dairy/eggs 30% of total exposure Foods collected 1997–1999; P BDE ¼ 47, 99, 100, 153, 154; fish accounts for 53%, fats and oils 17%, and beverages, spices and sweets for 9% of exposure P BDE ¼ 17, 47, 66, 71, 77, 85, 99, 100, 126, 138, 153, 154, 183; concentrations in wild salmon 20% of those in farmed P BDE ¼ 17, 28, 47, 49, 66, 71, 77, 85, 99, 100, 119, 126, 138, 153, 154, 183
Comments
Table 4 Concentrations of PBDEs in various retail foods and edible fish and estimated dietary exposures in Europe and Asia
[171]
[170]
[94]
[99]
Reference
Brominated Flame Retardants as Food Contaminants
549
Sample type
Retail samples (n ¼ 33); fish, meat, dairy, and oils/fats
Retail food samples from 11 food groups
104 Food groups from retail outlets
Location(s)
Norway
Spain
Spain
Table 4 (Continued ) Concentrations BDE 209 NA
NA
o 0.06 (dairy)–2,480 ng/kg ww (oils)
Concentrations of total PBDE (excluding BDE 209) Nd (vegetable oil)– 3,850 ng/kg lw (eggs)
5.9 (fruits)–590 ng/kg ww (fats/oils)
3.2 (dairy products)– 2,960 ng/kg ww (oils); N.B. total PBDEs includes BDE 209
38.5 ng/d (UB)
48.6 (median), 29.4 (seafood) to 123 ng/d (including fish oil and higher fish consumption estimates) 81.9 ng/d (LB) 97.3 ng/d (MB)
Dietary exposure (total PBDEs)a Reference
[93] Foodstuffs collected P P 2000; BDE= tetrato octa-BDEs; exposure highest via fish, then fats and oils (margarine, olive and sunflower oils), and meats [82] Foods collected 2003–2005; P BDE ¼ 17, 28, 47, 66, 85, 99, 100, 153, 154, 183, 184, 191, 196, 197, 209; BDE 47 major congener in fish, dairy products and meats; BDE 209 in oils and eggs; exposure highest in fish W oils W meats
Samples collected [172] 2003–2004; P BDE ¼ 47, 99, 100, 153, 154
Comments
550 Adrian Covaci et al.
Market basket study; fish, meat, dairy, eggs, fats, and pastries
Cows’ milk from 70–1,040 Switzerland (n ¼ 55) (average ¼ 203) and Ireland (n ¼ 12) ng/kg lw (Switzerland); 221–723 (average ¼ 407) ng/kg lw (Ireland) Market basket Concentrations in samples individual food categories not given
Sweden
Switzerland and Ireland
The Netherlands
Retail foods, excluding fruit and vegetables
Sweden
Average ¼ 40.8 ng/d; median ¼ 28.2 ng/d
NA
NA
13 ng/d (LB) 213 ng/d (MB)
NA
NA
14 (dairy produce)– 775 ng/kg ww (fish)
NA
51 ng/d (MB)
NA
Average ¼ 27 ng/d (women); range ¼ 9.7–56.9 ng/d
51 ng/d
NA
NA
Concentrations in individual food categories not given
Foods of animal origin
Sweden
Concentrations in individual food categories not given
Market basket samples
Sweden
Did not include fruit and vegetables, but did include vegetable oils; P BDE ¼ 28, 47, 99, 100, 153, 154
Foodstuffs collected P 1999; BDE ¼ 47, 99, 100, 153, 154; half of intake from fish, with meat, dairy, and fats/oils each contributing about 15% of total exposure Foodstuffs collected 1998–1999; excluded fruit and vegetables; P BDE ¼ 47, 99, 100, 153, 154 P BDE ¼ 47, 99, 100, 153, 154; fish contributes 47% of exposure Foods collected 1999; P BDE ¼ 47, 99, 100, 153, 154; fish accounts for 53% of exposure Samples collected 2004 (Switzerland) and 2005 (Ireland); P P BDE= tri- to hepta-BDEs
[178]
[177]
[176]
[175]
[174]
[173]
Brominated Flame Retardants as Food Contaminants
551
Sample type
Retail food samples. All food groups
Omnivorous duplicate diet homogenates (n ¼ 10)
Vegan duplicate diet (n ¼ 5)
Archived Total Diet Study samples
Location(s)
The Netherlands
UK
UK
UK
Table 4 (Continued )
90.5 ng/d median (LB); 117 ng/d median (UB); range 37–235 ng/d
–
ca. 130 ng/d (1992); ca. 160 ng/d (1997); ca. 105 ng/d (2000); ca. 80 ng/d (2001) 76.2 ng/d (2003)
NA
NA
Dietary exposure for 2003 samples ¼ 265.6 ng /d
Median ¼ 180.6 ng/kg (dry weight)
Median ¼ 153.9 ng/kg (dry weight) Concentrations in individual food categories not given
Average ¼ 47.4 ng/d 97.5th percent ¼ 97.2 ng/d Both calculated assuming 60 kg body weight (MB)
Dietary exposure (total PBDEs)a
NA
Concentrations BDE 209
Concentrations in individual food categories not given
Concentrations of total PBDE (excluding BDE 209) Foodstuffs collected 2003–2004; concentrations in fruit and vegetables not measured but estimated; P BDE ¼ 47, 99, 100, 153, 154; dairy 39%, fish 28% of exposure Collected 1999–2000; concentrations significantly higher in omnivorous compared to vegan samples; P BDE ¼ 47, 99, 100, 153, 154 Collected 1999–2000; P BDE ¼ 47, 99, 100, 153, 154 All values for adults; BDE 209 determined only in 2003 samples; P BDE ¼ 28, 47, 49, 66, 77, 85, 99, 100, 119, 126, 138, 153, 154, 183
Comments
[180]
[95]
[95]
[179]
Reference
552 Adrian Covaci et al.
Fish oils (n ¼ 21); combined fish-vegetable oils (n ¼ 3); vegetable oils (n ¼ 4)
UK
Seafood (bivalves, fish, cephalopods, and crustaceans) (n ¼ 24)
Retail fish
China
Japan
Retail fish oil Belgium, (n ¼ 69) Ireland, The Netherlands, UK, South Africa, USA, France, Sweden, and Denmark
Salmon and fish oils
UK and Belgium NA
14.6–34.2 mg/kg lw NA (cod liver oil); 0.8–2.7 mg/kg w (fish oil); nd–1.9 mg/kg lw (fish/ vegetable oil); nd (vegetable oil) NA o 0.1–45 (median ¼ 0.4) mg/kg oil (Belgium); o 0.1–17 (median ¼ 0.5) mg/kg oil (The Netherlands);o 0.1–2.8 (median ¼ 0.2) mg/kg oil (UK); o 0.1–7.5 (median ¼ 0.4) mg/kg oil (other countries) NA 6.67–46.1 mg/kg lw (fish); 3.01–11.3 mg/kg lw (crab); 8.26–9.2 mg/kg lw (squid); 7.4–27.6 mg/kg lw (shrimp); 10.5–13.5 mg/kg lw (bivalves) 0.0057–0.08 0.01–0.75 mg/kg ww (average ¼ 0.35) ng/ kg ww (includes BDE 209)
1–85 mg/kg w (fish); nd–13 mg/kg lw (oils)
Samples collected [184] 2004–2005; congeners not specified but major congeners are BDEs 47, 99, 209 28.8 ng/d (based on fish consumption only)
[183]
[182]
[56]
[181]
Samples collected 2003–2004; congeners not specified; BDE 47 major contributor in fish; BDE 209 in all other samples.
Samples collected P 2006; BDE ¼ 28, 47, 66, 85, 99, 100, 153, 154, 183; BDE 47 is the predominant congener
Samples collected 1999–2001; P BDE ¼ 28, 47, 66, 71, 75, 99, 100, 153, 154 Samples collected 2001–2002; P BDE ¼ 28, 47, 99, 100, 153, 154, 183
NA
NA
NA
NA
Brominated Flame Retardants as Food Contaminants
553
Fish, meat, and vegetables
Retail fish (n ¼ 20) and shellfish (n ¼ 2)
Green mussels
Japan
Korea
Singapore
0.29–8.6 mg/kg ww
21–1,650 ng/kg ww (fish); 6.25–63.6 ng/kg ww (meat); 38.4–134 ng/kg ww (vegetables) 21.7 (pollack)–892 ng/kg lw (flatfish)
Concentrations of total PBDE (excluding BDE 209)
NA
NA
NA
NA
NA
NA
Dietary exposure (total PBDEs)a
Concentrations BDE 209 BDE ¼ 47, 99, 100, 153, 154
[83]
Reference
BDE ¼ 28, 47, 99, [185] 100, 153, 154, 183; BDE 47 the predominant congener Samples collected [186] P 2002; BDE ¼ 17, 28, 32, 35, 37, 47, 49, 66, 71, 75, 77, 85, 99, 100, 119, 138, 153, 154, 166, 181, 190
P
P
Comments
Notes: NA, not analysed; nd, not detected; LOD, limit of detection; ww, wet weight; lw, lipid weight; dm, dry matter; LB, lower bound (valuesoLOD substituted with 0); MB, medium bound (valuesoLOD substituted with ½ LOD); and UB, upper bound (valuesoLOD substituted with LOD). a Dietary exposure for total PBDEs.
Sample type
Location(s)
Table 4 (Continued )
554 Adrian Covaci et al.
Brominated Flame Retardants as Food Contaminants
555
is unique to the UK or more widespread, can only be answered by increased monitoring of this congener. In summary, dietary exposure for western Europeans over the last decade has P been estimated to range between 9.7 and 235 BDE ng/d, with typical values P falling within the range 40–100 BDE ng/d. By comparison, the only estimate of dietary exposure for Asia (specifically Japan) is limited to that arising P from the consumption of fish alone. However, this estimate (28.8 ng BDE/d) is P comparable to European estimates of BDE intake from fish, and it is therefore not unreasonable to speculate that exposures via other foodstuffs will be similar in Europe and Japan at least. Furthermore, exposures of Europeans via the diet also do not appear to be significantly different to those of North Americans; Canadian estimates falling at the lower end and US estimates at the higher end of those for Europe. Because levels in food and estimates of dietary intake in North America are not all that different than those found in Europe and Asia, the much higher human levels reported in North America [167,187] cannot be explained entirely by diet. The use and production of the penta- and octa-BDE formulations has only recently been curtailed in North America. It is therefore likely that another source of human exposure may be from household products and electronic goods that contain these flame retardants. One source that has been studied is the role of household dust in exposure scenarios. Stapleton et al. [169] measured PBDEs in US household dust and estimated an adult exposure of 3.3 ng/d, which is only 5–10% of the dietary intake estimates made by Ryan et al. [167] and Schecter et al. [165], assuming an average adult weight of 70 kg. Using a Monte Carlo method and reported PBDE levels, Webster et al. [188] estimated that dust via inhalation, ingestion, and dermal contact accounted for 37% of an average adult’s exposure to BDE 47. Jones-Otazo et al. [168] modeled exposure with the Multi-media Urban Model (MUM-Fate) and estimated 60% of an urban Canadian adult’s exposure to be from dust and soil ingestion. Taken alone, dietary surveys can therefore underestimate exposure in adults by as much as 60%. Furthermore, Harrad et al. [189] compared estimates of UK human exposure via dust ingestion with those obtained by Jones-Otazo et al. [168] for Canadians by using identical dust ingestion rates for both adults and toddlers. This comparison suggested UK exposure via dust ingestion to be — while appreciable — an order of magnitude below what was estimated for Canadians. For children in North America the underestimation of exposure from dietary intake alone can be even greater. Both models employed by Webster et al. [188] and Jones-Otazo et al. [168] predicted more than a 10-fold increase in the rate of exposure from dust in young children over that in adults, and therefore 70–90% of child’s exposure can come from dust and soil. Although indoor dust can be a potential source of PBDE exposure for humans, studies that confirm this theory are only now emerging [190], and it is clear that dietary exposure remains an important pathway. In light of the recent and possible future restrictions on the manufacture and new use of PBDEs, the extent to which our diet will remain a substantial source of
556
Adrian Covaci et al.
exposure to PBDEs is difficult to assess. In this context, the data on recent temporal trends in UK dietary exposure is informative, as it indicates a downward trend in such exposure to PBDE (excluding BDE 209 for which trend data is not available) since 1997 [180]. Although encouraging, it is too early to judge whether this downward trend can be sustained longer term, and to what extent it reflects an initial reaction to reduced fugitive emissions arising from manufacturing activities. Harrad and Diamond [191] hypothesized that a peak in dietary exposure may emerge some time after the peak in exposures via indoor air and dust, as a result of continuing emissions from the huge reservoir of PBDEtreated goods, both during use and as a result of their end-of-life disposal. Continued monitoring of PBDEs in food and consequent dietary exposure is therefore essential if the impact of recent and future efforts to limit their environmental distribution is to be evaluated.
3.3 Levels of HBCDs and TBBP-A in food and dietary intake Table 5 provides a summary of the levels of total HBCDs that have been measured in foodstuffs. Similar to PBDEs, the consumption of fish and seafood plays an important role in the dietary exposure to HBCDs. This is particularly true for fish caught in locations contaminated with HBCDs, such as the Western Scheldt estuary (The Netherlands), or point sources located along rivers Cinca (Spain), Viskan (Sweden) and Tees (UK) [142]. Concentrations of HBCDs in fish were mostly between 10 and 1 000 ng/g lw in urban/suburban regions of Europe, while levels in the North American Great Lakes were lower by approximately one order of magnitude [142]. Concentrations in fish from Swiss alpine lakes showed also lower concentrations than fish from lakes nearby urban areas [198,199]. However, the dietary exposure to HBCDs for other important food groups than fish has been investigated only in few studies. The few data available on the HBCD concentrations in commercially purchased Swedish food samples [18] suggest that fish is a major source of dietary HBCD intake. Considering the high proportion of fish in the Swedish diet, a median intake of 140 ng HBCDs/d was calculated (maximum 1,100 ng/d) [174]. In addition, HBCD intake through house dust inhalation may also contribute to the overall human exposure, but the relevance of human HBCD exposure originating from house dust vs. food-based HBCD exposure is still unknown. Only a limited number of studies have investigated the occurrence of TBBP-A in foodstuffs and have found that concentrations of TBBP-A were low (Table 5). Recently, 19 composite food group samples have been analysed in the UK. The study found limited presence of HBCDs in the samples and did not detect TBBP-A. Based on the results, UK’s Committee on Toxicity of Chemicals in Food, Consumer Products and the Environment concluded that the concentrations of HBCDs and TBBP-A detected in fish and shellfish do not raise toxicological concerns and that the estimated dietary exposure to HBCDs and TBBP-A seems to have limited implications for health [201].
Perch, whitefish, walleye, goldeye, sauger, and burbot Trout, smelt, sculpin, and alewife Trout, perch, and eel
Canada
Animal fat (pork, lamb, beef, chicken), eggs, milk, and fish Herring, salmon
Sweden
Sweden
Skipjack tuna
Pacific Ocean
Norway
Norway
Norway
Norway
Perch, pike, smelt, vendace, and trout Farmed salmon, herring, and mackerel Mussels
Eel muscle
Belgium
Canada
Sample type
1999–2002
1999–2002
1997–2001
2001
2004
2003
2003
2002
2003
1999–2001
Year
Range of means: 10–63 mg/kg lw
Range of means: 34 mg/kg lw Range:o0.1–45 mg/kg lw Range of means: 1–48 mg/kg lw
Range of means: 4.5–21 mg/kg lw Range of means: o3.4–28 mg/kg lw Range of means: 102–435 mg/kg lw Range of means: 1.0–1.3 mg/kg lw
Range of means: 3–78 mg/kg lw
177 (mean); 29–266 (range) mg/kg lw
Concentrations of P HBCDs
Baltic Sea
Only the a-HBCD isomer was detected
Drammensfjord, only a-HBCD detected Lake Mjøsa area, a-HBCD and g-HBCD isomer detected
Lake Ontario
a-HBCD isomer dominant, Scheldt basin Lake Winnipeg
Comments
[18]
[18]
[74]
[197]
[196]
[195]
[194]
[193]
[192]
[75]
Reference
Mean and range concentrations of total HBCDs and TBBP-A (mg/kg lw) in various foods and edible fish and estimated dietary exposures
Location(s)
Table 5
Brominated Flame Retardants as Food Contaminants
557
Whitefish muscle
Trout and char muscle
Shrimp and mussels
Eel muscle
Sole, plaice, bib, and whiting Eel muscle
Whiting muscle
Perch, pike, smelt, vendace, and trout Eel muscle
Switzerland
Switzerland
The Netherlands
The Netherlands
The Netherlands
North Sea
Norway
The Netherlands
Belgium
Sample type
Location(s)
Table 5 (Continued )
1999–2001
2003
1999–2001
1999–2001
2001
1999–2001
1998–2001
2004
2001
Year
94 (mean); 25–210 (range) mg/kg lw Range: 40–727 mg/kg lw 185 (mean); 6–690 (range) mg/kg lw 185 (mean); 6–690 (range) mg/kg lw Range of means: 38– 437 mg/kg lw 1.6 (mean); nd–13 (range) mg/kg lw 136 (mean); nd–245 (range) mg/kg lw 1.0–13.7 (range) mg/kg lw 0.3 (mean); nd–1.3 (range) mg/kg lw
Concentrations of P HBCDs
Lake Mjøsa area
a-HBCD isomer dominant a-HBCD isomer dominant a-HBCD isomer dominant and g-HBCD isomer also detected
Various lakes, only the a-HBCD isomer was detected
Comments
[75]
[195]
[75]
[75]
[140]
[75]
[75,200]
[199]
[198]
Reference
558 Adrian Covaci et al.
Brominated Flame Retardants as Food Contaminants
559
3.4 PBDD/Fs Generally the concentrations of PBDD/Fs in food and biota are very low. However, few research groups currently study these compounds, due in part to the difficult and often expensive analytical protocols required for their analysis in foodstuffs. Recent surveys of PBDD/Fs in food have yielded some interesting results. Kotz et al. [150] did not detect PBDD/Fs in a survey of 39 foodstuffs from Germany. Despite very low LODs of 0.0006–0.02 ng/kg lw, PBDD/Fs were not found even in fish samples that were highly contaminated with BFRs and chlorinated POPs. Similar results were found in food samples in a survey of archived total diet samples from the UK [149]. PBDD/Fs were seldom detected above LODs in food of animal origin, except perhaps offal, where lower brominated furans were detected. However, D’Silva found low, but above LOD, levels of PBDD/Fs in some food samples of vegetable origin. PBDFs dominated, while PBDDs were not detected in any samples [149]. Some foodstuffs were shown to have significantly higher levels of PBDFs than others; sugar and preserves (jam and jelly) were found to have relatively high levels of PBDFs in UK total diet survey samples in 2000 and 2003 [149,180]. The causes for this contamination are unknown and it is possible that PBDFs are introduced as process contaminants in the manufacture at elevated temperatures of these products. It was estimated that dietary exposure P to PBDD/Fs and dioxin-like PBBs was in the range WHO-TEQ 5.3–27.1 pg/d [180]. Recently, PBDD/Fs have been detected in composite and individual samples in a comprehensive survey of fish and fish products purchased in the UK [202]. These included farmed and wild oily fish and white fish, shellfish, canned fish, and fish paste, and supplements based on cod liver, halibut liver, shark liver, salmon and tuna oils. PBDD/Fs were detected in several of the samples. As previously seen, lower brominated furans, in particular tri-BDFs, dominated the congener profile, although overall levels were low. These results echoed those seen in a study of fish from Sweden, where significant levels of tri-BDFs were detected [203], and in fish and marine samples from Japan [80]. Consequently, at present it appears that PBDD/Fs are not ubiquitous contaminants in food, unlike PBDEs. However, their apparent absence is inconsistent with levels of PBDD/Fs detected in BFR products, incinerator outputs and environmental samples. A comprehensive survey of PBDD/Fs in environmental (air, soil, and sediment) and food samples from Japan reported that PBDD/Fs were detected in ambient air, settled soot and dust, soil, sediment, and aquatic life. However, these compounds were not found in groundwater, public water, terrestrial wildlife, or in food [204]. It is possible that these compounds were undetected due to the lack of laboratories capable of meeting the demands of their difficult analysis. It is also possible that they are only detected at low concentrations in biota due to their ability to be readily metabolized, although there is no biological evidence for this.
560
Adrian Covaci et al.
4. REGULATORY/SAFETY ASPECTS AND ON-GOING MONITORING PROGRAMMES Owing to the potential toxicity of numerous BFRs, their persistence in the environment, and their tendency to bioaccumulate in the food chain, regulations have been put into place or are pending for several of these compound classes. PBDEs: In the EU it is prohibited to market and use penta- and octa-BDE and products containing these substances including electrical and electronic equipment as of July 2006 [205,206]. Risk reduction measures are recommended for deca-BDE, and the exemption of deca-BDE from the regulation will be reviewed before 2010 [207]. Sweden adopted a limited ban on deca-BDE (25 August 2006, press release, www.sweden.gov.se; www.ebfrip.org), and other EU member states are considering similar proposals. In the USA, the sole producer of pentaBDE and octa-BDE (Great Lakes Chemical Corp.) voluntarily ceased manufacturing the compounds as of January 2005. The USA EPA issued a significant new use rule (SNUR) for tetra- through nona-BDEs that requires EPA to be notified of any future manufacturing or importing of these chemicals for the purpose of evaluating and limiting or restricting these activities [208]. Individual states (California, Hawaii, Maine, Michigan, New York, and Maryland) have enacted legislation to ban or restrict the manufacture and use of PBDEs, with the exception of deca-BDE, in most cases by 2006 (www.ncel.net). Massachusetts, Illinois, Minnesota, Oregon, and Washington all have similar legislation planned to follow shortly [209]. Canada added tetra- through decaBDEs to the list of toxic chemicals under Schedule 1 of the Canadian Environmental Protection Act, which is the first step towards regulation [210]. China plans to implement a regulatory plan similar to the EU restrictions by 2006, whereas Japan and South Korea may follow this lead [211]. Tetra- through heptaBDEs have been voluntarily banned from production or importation in Japan since 1995 [212]. The BFR industry has established two voluntary pacts aimed at reducing, monitoring, and managing BFRs [2]. The Voluntary Emission Control Action Programme (VECAP) initially focused on deca-BDE in Europe, but will eventually be expanded to global coverage with inclusion of TBBP-A in plastics and HBCDs in textiles. A Voluntary Industry Commitment (VIC) with the Organization for Economic Cooperation and Development (OECD) was signed in 1995 covering the production, handling, and disposal of PBDEs, PBBs, and TBBP-A. PBBs: PBBs are included in the VIC with OECD and in the EU and Chinese legislations on hazardous substances in electronics and electrical goods [205]. In Europe, PBBs have collectively been banned from textiles that come in contact with the skin since 1983 [213] and were not used or manufactured after 2000 [214]. However, even before the cessation of their manufacture, PBBs have not been a high demand product in Europe, due to the widespread use and production of PBDEs. During the 1990s, the demand for deca-BB treated products was limited to the Benelux, France and southern European countries at a level of less than 2,000 tonnes per year [215]. After an accidental contamination incident in Michigan in 1973, the major USA producer of hexa-BB voluntarily ceased
Brominated Flame Retardants as Food Contaminants
561
manufacturing in 1974 [9,216], whereas the USA manufacturing of deca-BB ceased in 1979. Canada has officially banned PBBs as toxic substances under CEPA 1999 since 2003 [217]. PBBs have not been manufactured in Japan and their importation ceased in 1978 [9]. TBBP-A and derivatives: TPPB-A is on the fourth list of priority chemicals in Europe [218] and has undergone a human health risk assessment [219]. An environmental risk assessment is pending. As a major BFR in electrical and electronic goods, TBBP-A is covered under the waste electrical and electronic equipment (WEEE) directive requiring the reduction, recycling, and reuse of these materials in the EU [205]. A similar reduction mandate was enacted in Japan in 2001 (Recycling of Specified Kinds of Home Appliances), and one is being established in China for electronic and electrical waste (Regulations on Recycling and Disposal of Waste and Used Household Electrical Appliances) [211]. Canada is in the process of assessing the human and environmental risks of TBBP-A and its ethoxyl and allyl ether derivatives [220]. HBCDs: HBCDs are undergoing risk assessments in Europe and Canada [220,221]. They are on the second list of priority substances in the EU [222]. In the USA, deca-BDE and HBCDs are included in an SNUR that is being developed by the US EPA for residential upholstered furniture which will allow reviewing by EPA of BFRs used in these fabrics (www.epa.gov/oppt/pbde) [223]. PBDD/Fs: As impurities in the waste electrical and electronic stream, PBDD/Fs are slated for reduction in the WEEE legislations of Europe, China, and Japan. A German Chemicals Banning Ordinance regulates PBDD/Fs in substances or articles at a limit of 5 mg/kg for the sum of eight 2,3,7,8-tetra- to hexa-BDD/Fs [224]. Until July 1999, the ordinance prohibited any product containing more than 10 mg/kg of the sum of four congeners: 2,3,7,8-T4BDD; 2,3,7,8-T4BDF; 1,2,3,7,8P5BDD, and 2,3,4,7,8-P5BDF, whereas the sum of eight other congeners was not to exceed 60 mg/kg, but was subsequently lowered [225]. At this point in time, PBDD/Fs are not included in regulations covering PCDD/Fs in food and feeds. A WHO report on PBDD/Fs discusses the concept of using TEFs for the assessment of these chemicals and suggests that the preliminary use of the same TEF values for the brominated congeners as described for the chlorinated analogues appears to be justified [5]. The UK Committee on Toxicity recommends that TEQs for PBDD/Fs should be combined with the WHO-TEQs for the PCDD/ Fs to provide an indication of the total intake of chemicals with dioxin-like properties [226]. The monitoring of BFRs throughout the food chain is conducted or sponsored by numerous entities including governments, industry, environmental groups, and academia and has occurred to some extent in most developed countries. BFRs have been analysed in several on-going biomonitoring programs including the third round of a WHO-coordinated human exposure study (2000–2003) [227] and the National Health and Nutrition Examination Survey (NHANES, 2001–2002) conducted in the USA [228]. Environmental non-profit organizations, such as the World Wide Fund for Nature (WWF, www.panda.org/detox) and Greenpeace (www.greenpeace.org.uk), have sponsored studies to investigate levels of BFRs (PBDEs, HBCDs, and TBBP-A) in humans, foods, wildlife, and
562
Adrian Covaci et al.
household dust. The BFR industry has sponsored monitoring studies in the workplace and the environment for several BFRs including PBDD/Fs [229]. In North America, where PBDE levels in humans appear to be among the highest, Health Canada has established an on-going monitoring program for PBDEs in foods (www.hc-sc.gc.ca) and the US Food and Drug Administration plans a large scale surveillance program for PBDEs in edible fish and total diet starting from 2006 [164]. Marine environments are also being monitored for BFRs. The Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR) listed PBDEs, PBBs, HBCD, and TBBP-A as chemicals for priority action, and the Commission has developed monitoring strategies for these chemicals in sediments and biota [214,230]. The Norwegian Feed Monitoring program has included PBDEs since 2003 [231]. The Ministry of Japan included TBBP-A in their environmental surveillance program beginning in 2003 [232]. The Great Lakes Fish Monitoring Program, a cooperative project between the USA and Canada, added PBDEs to the contaminant monitoring list in 2000 (www.epa.gov/glnpo/ monitor). Environment Canada and the Department of Fisheries and Oceans also monitor other Canadian waters for PBDEs [233] and HBCDs [192,193]. Japanese and Canadian government agencies and several Universities from Asian countries and Brazil recently cooperated in global monitoring studies of PBDEs and HBCDs in the marine environment using skipjack tuna as a biomonitor [73,74]. Only through continuous monitoring efforts, will the extent of contamination with BFRs and possible exposure routes be revealed. This will permit assessment of whether regulations that are enacted are effective at reducing levels in the environment and minimizing exposures.
5. FUTURE TRENDS IN THE BFR RESEARCH IN FOOD From the above a clear picture emerges, that notwithstanding recent actions to restrict their new manufacture and use, there will remain a need to monitor BFRs in human foodstuffs for the foreseeable future. In particular, continued monitoring of temporal trends in dietary contamination and resultant exposure is essential if the efficacy of these actions needs to be evaluated. Other key issues include: studies that better place the significance of dietary exposure into context against other exposure pathways and fundamental studies to enhance our currently limited understanding of the mechanisms via which BFRs enter the food chain and their efficiency. The current database of BFR levels in food is relatively detailed for the trithrough hexa-BDEs, but far less so for higher brominated DEs, including BDE 209, or other BFRs. Therefore, a rapid growth in the availability of data for these currently less well-characterized contaminants is needed. To generate these data, it is likely that researchers will investigate the utility of methods designed to increase sample throughput (e.g., PLE combined ‘‘on-line’’ with SPE to effect removal of interferences), as well as the potential of innovative instrumental techniques (e.g., GC GC-TOF-MS) to enhance data quality. In the latter context,
Brominated Flame Retardants as Food Contaminants
563
a marked increase in the number and range of available reference materials for the evaluation of BFR analyses is anticipated.
ACKNOWLEDGEMENT Adrian Covaci acknowledges a postdoctoral fellowship of the Funds for Scientific Research Flanders (FWO).
REFERENCES 1 WHO, Environmental Health Criteria 192: Flame Retardants: A General Introduction, World Health Organisation, Geneva, Switzerland, 1997. 2 BSEF. Bromine Science and Environmental Forum. Available at www.bsef.com. Last accessed November 2006. 3 European Commission, Directive 2000/60/EC of the European Parliament and of the Council of 23 October 2000 establishing a framework for Community action in the field of water policy, Off. J. Eur. Commun. L, L327 (2000) 1. 4 European Commission, Decision No 2455/2001/EC of the European Parliament and of the Council of 20 November 2001 Establishing the List of Priority Substances in the Field of Water Policy and Amending Directive 2000/60/EC, Off. J. Eur. Commun. L, 331 (2001) 1. 5 WHO, Environmental Health Criteria 205: Polybrominated dibenzo-p-dioxins and dibenzofurans, World Health Organization, Geneva, 1998. 6 L.S. Birnbaum, D.F. Staskal and J.J. Diliberto, Environ. Int., 29 (2003) 855. 7 N. Hanari, K. Kannan, Y. Miyake, T. Okazawa, P.R.S. Kodavanti, K.M. Aldous and N. Yamashita, Environ. Sci. Technol., 40 (2006) 4400. 8 F. Rahman, K.H. Langford, M.D. Scrimshaw and J.N. Lester, Sci.Total Environ., 275 (2001) 1. 9 WHO, Environmental Health Criteria 152: Polybrominated Biphenyls, World Health Organisation, Geneva, Switzerland, 1994. 10 E.J.C. Borojovich and Z. Aizenshtat, J. Anal. Appl. Pyrol., 63 (2002) 105. ˚ . Bergman, Environ. Sci. Technol., 38 (2004) 3119. 11 J. Eriksson, N. Green, G. Marsh and A 12 J. Bezares-Cruz, C.T. Jafvert and I. Hua, Environ. Sci. Technol., 38 (2004) 4149. 13 WHO, Environmental Health Criteria 162: Brominated Diphenyl Ethers, World Health Organization, Geneva, Switzerland, 1994. 14 R.H. Hill, D.G. Patterson, Jr., D.L. Orti, J.S. Holler, L.L. Needham, S.L. Sirmans and J.A. Liddle, J. Environ. Sci. Health B, 17 (1982) 19. 15 K. Ballschmiter and M. Zell, Fresenius J. Anal. Chem., 302 (1980) 20. 16 L.S. Birnbaum and D.F. Staskal, Environ. Health Perspect., 112 (2004) 9. 17 R.J. Law, M. Kohler, N.V. Heeb, A.C. Gerecke, P. Schmid, S. Voorspoels, A. Covaci, G. Becher, K. Janak and C. Thomsen, Environ. Sci. Technol., 39 (2005) 281A. 18 M. Remberger, J. Sternbeck, A. Palm, L. Kaj, K. Stro¨mberg and E. Brorstro¨m-Lunde´n, Chemosphere, 45 (2004) 9. 19 WHO, Environmental Health Criteria 172: Tetrabromobisphenol A and derivatives, World Health Organization, Geneva, Switzerland, 1995. 20 J.W. Voordeckers, D.E. Fennell, K. Jones and M.M. Haggblom, Environ. Sci Technol., 36 (2002) 696. 21 H. Buchert and K. Ballschmiter, Chemosphere, 15 (1986) 1923. 22 W. Chatkittikunwong and C.S. Creaser, Chemosphere, 29 (1994) 554. 23 M.L. Hardy, Chemosphere, 46 (2002) 757. 24 P.O. Darnerud, Environ. Int., 29 (2003) 841. 25 National Toxicology Program (NTP) 1986. Toxicology and carcinogenesis studies of decabromodiphenyl oxide in F344/N rats and B6C3F1 mice. Technical Report No. 309.
564
Adrian Covaci et al.
26 International Agency for Research on Cancer (IARC), Monographs: Some flame retardants and textile chemicals, and exposure in the textile manufacturing industry. Decabromodiphenyl Oxide, Vol. 48, Lyon, France, 1990. 27 H. Viberg, A. Fredriksson and P. Eriksson, Toxicol. Sci., 81 (2004) 344. 28 H. Viberg, N. Johansson, A. Fredriksson, J. Eriksson, G. Marsh and P. Eriksson, Toxicol. Sci., 92 (2006) 211. 29 P. Eriksson, H. Viberg, C. Fischer, M. Wallin and A. Fredriksson, Organohalogen Compd., 57 (2002) 389. 30 I. Branchi, F. Capone, E. Alleva and L.G. Costa, Neurotoxicology, 24 (2003) 449. 31 T. Zhou, D.G. Ross, M.J. DeVito and K.M. Crofton, Toxicol. Sci., 61 (2001) 76. 32 K.J. Fernie, G. Mayne, J.L. Shutt, C. Pekarik, K.A. Grasman, R.J. Letcher and K. Drouillard, Environ. Pollut., 138 (2005) 485. 33 K.J. Fernie, J.L. Shutt, G. Mayne, D. Hoffman, R.J. Letcher, K.G. Drouillard and I.J. Ritchie, Toxicol. Sci., 88 (2005) 375. 34 T. Hamers, J.H. Kamstra, E. Sonneveld, A.J. Murk, M.H.A. Kester, P.L. Andersson, J. Legler and A. Brouwer, Toxicol. Sci., 92 (2006) 157. 35 S. Germer, A.H. Piersma, L. van der Ven, A. Kamyschnikow, Y. Fery, H.J. Schmitz and D. Schrenk, Toxicology, 218 (2006) 229. 36 D. Ronisz, E.F. Finne, H. Karlsson and L. Forlin, Aquat. Toxicol., 69 (2004) 229. 37 T. Yamada-Okabe, H. Sakai, Y. Kashima and H. Yamada-Okabe, Toxicol. Lett., 155 (2005) 127. 38 E. Mariussen and F. Fonnum, Neurochem. Int., 43 (2003) 533. 39 S. Kitamura, N. Jinno, S. Ohta, H. Kuroki and N. Fujimoto, Biochem. Biophys. Res. Commun., 293 (2002) 554. 40 S. Kitamura, T. Suzuki, S. Sanoh, R. Kohta, N. Jinno, K. Sugihara, S. Yoshihara, N. Fujimoto, H. Watanabe and S. Ohta, Toxicol. Sci., 84 (2005) 249. ˚ . Bergman, J.G. Lemmen, B. van der Burg and 41 I.A.T.M. Meerts, R.J. Letcher, S. Hoving, G. Marsh, A A. Brouwer, Environ. Health Perspect., 109 (2001) 399. 42 A. Kristoffersen, O.A. Voie and F. Fonnum, Toxicol. Lett., 129 (2002) 161. 43 A. Covaci, S. Voorspoels and J. de Boer, Environ. Int., 29 (2003) 735. 44 H.M. Stapleton, Anal. Bioanal. Chem., 386 (2004) 807. 45 K. D’Silva, A. Fernandes and M. Rose, Crit. Rev. Environ. Sci. Technol., 34 (2004) 141. 46 J. de Boer, C. Allchin, R. Law, B. Zegers and J.P. Booij, Trends Anal. Chem., 20 (2001) 591. 47 J. de Boer and D.E. Wells, Trends Anal. Chem., 25 (2006) 364. 48 A. Fernandes, S. White, K. D’Silva and M. Rose, Talanta, 63 (2004) 1147. 49 M. Polo, G. Gomez-Noya, J.B. Quintana, M. Llompart, C. Garcia-Jares and R. Cela, Anal. Chem., 76 (2004) 1054. 50 M. Polo, M. Llompart, C. Garcia-Jares, G. Gomez-Noya, M.H. Bollain and R. Cela, J. Chromatogr. A, 1124 (2006) 11. 51 J. Llorca-Porcel, G. Martinez-Sanchez, B. Alvarez, M.A. Cobollo and I. Valor, Anal. Chim. Acta, 569 (2006) 113. 52 B.V. Pepich, B. Prakash, M.M. Domino, T.A. Dattilio, D.J. Munch and E.K. Price, Environ. Sci. Technol., 39 (2005) 4996. 53 A.M. Carro, R.A. Lorentzo, F. Ferna´ndez, R. Rodil and R. Cela, J. Chromatogr. A, 1071 (2005) 93. 54 R. Rodil, A.M. Carro, R.A. Lorenzo and R. Cela Torrijos, Anal. Chem., 77 (2005) 2259. 55 M. Montory and R. Barra, Chemosphere, 63 (2006) 1252. 56 M.N. Jacobs, A. Covaci, A. Gheorghe and P. Schepens, J. Agric. Food Chem., 52 (2004) 1780. 57 D.G. Hayward and T.S. Pisano, Organohalogen Compd., 68 (2006) 109. 58 D.R. Oros, D. Hoover, F. Rodigari, D. Crane and J. Sericano, Environ. Sci. Technol., 39 (2005) 33. 59 A. Martinez, M. Ramil, R. Montes, D. Hernanz, E. Rubi, I. Rodriguez and R. Cela, J. Chromatogr. A, 1072 (2005) 83. 60 P. Isosaari, A. Hallikainen, H. Kiviranta, P.J. Vuorinen, R. Parmanne, J. Koistinen and T. Vartiainen, Environ. Pollut., 141 (2006) 213. 61 C. Pirard, E. de Pauw and J.F. Focant, J. Chromatogr. A, 1115 (2006) 125. 62 H.M. Stapleton and J.E. Baker, Arch. Environ. Contam. Toxicol., 45 (2003) 227.
Brominated Flame Retardants as Food Contaminants
565
63 H.M. Stapleton, B. Brazil, R.D. Holbrook, C.L. Mitchelmore, R. Benedict, A. Konstantinov and D. Potter, Environ. Sci. Technol., 40 (2006) 4653. 64 E. Eljarrat, A. de la Cal, D. Raldua, C. Duran and D. Barcelo´, Environ. Sci. Technol., 38 (2004) 2603. 65 S. Bayen, H.K. Lee and J.P. Obbard, J. Chromatogr. A, 1035 (2004) 291. 66 M. Alaee, D.B. Sergeant, M.G. Ikonomou and J.M. Luross, Chemosphere, 44 (2001) 1489. 67 C.P. Rice, S.M. Chernyak, L. Begnoche, R. Quintal and J. Hickey, Chemosphere, 49 (2002) 731. 68 R.C. Hale, M.J. La Guardia, E.P. Harvey, T. Matteson Mainor, W.H. Duff and W.O. Gaylor, Environ. Sci. Technol., 35 (2001) 4585. 69 R.A. Hites, J.A. Foran, S.J. Schwager, B.A. Knuth, M.C. Hamilton and D.O. Carpenter, Environ. Sci. Technol., 38 (2004) 4945. 70 S. Rayne, M.G. Ikonomou and B. Antcliffe, Environ. Sci. Technol., 37 (2003) 2847. 71 S.A. Tittlemier, D. Forsyth, K. Breakell, V. Verigin, J.J. Ryan and S. Hayward, J. Agric. Food Chem., 52 (2004) 7740. 72 H. Liu, Z. Qinghua, C. Zongwei, L. An, W. Yawei and J. Guibin, Anal. Chim. Acta, 557 (2006) 314. 73 D. Ueno, N. Kajiwara, H. Tanaka, A. Subramanian, G. Fillmann, P.K.S. Lam, G.J. Zheng, M. Muchitar, H. Razak, M. Prudente, K.H. Chung and S. Tanabe, Environ. Sci. Technol., 38 (2004) 2312. 74 D. Ueno, M. Alaee, C. Marvin, D.C.G. Muir, G. Macinnis, E. Reiner, P. Crozier, V.I. Furdui, A. Subramanian, G. Fillmann, P.K.S. Lam, G.J. Zheng, M. Muchtar, H. Razak, M. Prudente, K.H. Chung and S. Tanabe, Environ. Pollut., 144 (2006) 238. 75 S. Morris, C.R. Allchin, B.N. Zegers, J.J.H. Haftka, J.P. Boon, C. Belpaire, P.E.G. Leonards, S.P.J. Van Leeuwen and J. de Boer, Environ. Sci. Technol., 38 (2004) 5497. 76 S. Morris, P. Bersuder, C.R. Allchin, B. Zegers, J.P. Boon, P.E.G. Leonards and J. de Boer, Trends Anal. Chem., 25 (2006) 343. 77 P.S. Haglund, D.R. Zook, H.R. Buser and J. Hu, Environ. Sci. Technol., 31 (1997) 3281. 78 H. Wolkers, B. van Bavel, A.E. Derocher, O. Wiig, K.M. Kovacs, C. Lydersen and G. Lindstro¨m, Environ. Sci. Technol., 38 (2004) 1667. 79 H. Wolkers, M.O. Hammill and B. van Bavel, Environ. Pollut., 142 (2006) 476. 80 Y. Ashizuka, R. Nakagawa, K. Tobiishi, T. Hori and T. Iida, J. Agric. Food Chem., 53 (2005) 3807. 81 B. van Bavel, I. Ericsson, H. Bjo¨rnfoth, J. Hagberg and G. Lindstro¨m, Organohalogen Compd., 66 (2004) 106. 82 B. Go´mara, L. Herrero and M.J. Gonza´lez, Environ. Sci. Technol., 40 (2006) 7541. 83 S. Ohta, D. Ishizuka, H. Nishimura, T. Nakao, O. Aozosa, Y. Shimidzu, F. Ochiai, T. Kida, M. Nishi and H. Miyata, Chemosphere, 46 (2002) 689. 84 O. Pa¨pke, P. Furst and T. Herrmann, Talanta, 63 (2004) 1203. 85 R. Cariou, J.P. Antignac, P. Marchand, A. Berrebi, D. Zalko, F. Andre and B. Le Bizec, J. Chromatogr. A, 1100 (2005) 144. 86 A. Sjo¨din, E.E. McGahee, III, J.F. Focant, R.S. Jones, C.R. Lapeza, Y. Zhang and D.G. Patterson, Jr., Anal. Chem., 76 (2004) 4508. 87 K. Saito, A. Sjo¨din, C.D. Sandau, M.D. Davis, H. Nakazawa, Y. Matsuki and D.G. Patterson, Jr, Chemosphere, 57 (2004) 373. 88 S. Voorspoels, A. Covaci and P. Schepens, Environ. Sci. Technol., 37 (2003) 4348. 89 U. Sellstro¨m, A. Bignert, A. Kierkegaard, L. Ha¨ggberg, C. de Wit, M. Olsson and B. Jansson, Environ. Sci. Technol., 37 (2003) 5496. ˚. 90 B. Fa¨ngstrom, M. Athanasiadou, I. Athanassiadis, A. Bignert, P. Grandjean, P. Weihe and A Bergman, Chemosphere, 60 (2005) 836. 91 U. Berger, D. Herzke and T.M. Sandanger, Anal. Chem., 76 (2004) 441. 92 A. Go¨tsch, E. Mariussen, R. von der Recke, D. Herzke, U. Berger and W. Vetter, J. Chromatogr. A, 1063 (2005) 193. 93 A. Bocio, J.M. Llobet, J.L. Domingo, J. Corbella, A. Teixido´ and C. Casas, J. Agric. Food Chem., 51 (2003) 3191. 94 H. Kiviranta, M.L. Ovaskainen and T. Vartiainen, Environ. Int., 30 (2004) 923. 95 S. Harrad, R. Wijesekera, S. Hunter, C. Halliwell and R. Baker, Environ. Sci. Technol., 38 (2004) 2345. 96 W.J. Luksemburg, R.J. Wenning, A. Patterson and M. Maier, Levels of polybrominated diphenyl ethers (PBDEs) in fish, beef, and fowl purchased in food markets in Northern California USA.
566
97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136
Adrian Covaci et al.
Third International Workshop on Brominated Flame Retardants, Toronto, ON, Canada, June 6–9, 2004, pp. 479–482. J.K. Huwe and G.L. Larsen, Environ. Sci. Technol., 39 (2005) 5606. EPA 1614, draft. Brominated diphenyl ethers in water, soil, sediment and tissue by HRGC/ HRMS, August 2003. S. Voorspoels, A. Covaci, H. Neels and P. Schepens, Environ. Int., 33 (2007) 93. D. Herzke, U. Berger, R. Kallenborn, T. Nyga˚rd and W. Vetter, Chemosphere, 61 (2005) 441. S. Suzuki and A. Hasegawa, Anal. Sci., 22 (2006) 469. N. Fontanals, T. Barri, S. Bergstrom and J.A. Jonsson, J. Chromatogr. A, 1133 (2006) 41. D.C.G. Muir, S. Backus, A.E. Derocher, R. Dietz, T.J. Evans, G.W. Gabrielsen, J. Nagy, R.J. Norstrom, C. Sonne, I. Stirling, M.K. Taylor and R.J. Letcher, Environ. Sci. Technol., 40 (2006) 449. B. Go´mara, C. Garcı´a-Ruiz, M.J. Gonza´lez and M.L. Marina, Anal. Chim. Acta, 565 (2006) 208. A. Covaci, J. de Boer, J.J. Ryan, S. Voorspoels and P. Schepens, Anal. Chem., 74 (2002) 790. ¨ stman, J. Chromatogr. A, 1041 (2004) 201. J. Bjo¨rklund, P. Tollba¨ck, C. Hiarne, E. Dyremarck and C. O P. Tollback, J. Bjorklund and C. Ostman, J. Chromatogr. A, 991 (2003) 241. ¨ stman, J. Sep. Sci., 26 (2003) 594. J. Bjo¨rklund, P. To¨llback, E. Dyremark and C. O ˚ . Bergman, A. Sjo¨din, L. Hagmar, E. Klasson-Wehler, K. Kronholm-Diab, E. Jakobsson and A Environ. Health Perspect., 107 (1999) 643. ¨ stman, J. Sep. Sci., 26 (2003) 1104. J. Bjo¨rklund, P. To¨llback and C. O C. de Wit, Chemosphere, 46 (2002) 583. R.J. Law, C.R. Allchin, J. de Boer, A. Covaci, D. Herzke, P. Lepom, S. Morris, J. Tronczynski and C.A. deWit, Chemosphere, 64 (2006) 187. M. Alaee, S. Backus and C. Cannon, J. Sep. Sci., 24 (2001) 465. J.M. Luross, M. Alaee, D.B. Sergeant, C.M. Cannon, D.M. Whittle, K.R. Solomon and D.C.G. Muir, Chemosphere, 46 (2002) 665. M.G. Ikonomou, S. Rayne, M. Fischer, M.P. Fernandez and W. Cretney, Chemosphere, 46 (2002) 649. W. Vetter, E. Stoll, M.J. Garson, S.J. Fahey, C. Gaus and J.F. Muller, Environ. Toxicol. Chem., 21 (2002) 2014. S. Voorspoels, Ph.D. Thesis: Environmental Distribution of Brominated Flame Retardants in Belgium, University of Antwerp, Belgium, 2006. P. Koryta´r, A. Covaci, J. de Boer, A. Gelbin and U.A. Th. Brinkman, J. Chromatogr. A, 1065 (2005) 239. P. Koryta´r, A. Covaci, P.E.G. Leonards, J. de Boer and U.A.Th. Brinkman, J. Chromatogr. A, 1100 (2005) 200. J.F. Focant, A. Sjo¨din, W.E. Turner and D.G. Patterson, Jr., Anal. Chem., 76 (2004) 6313. N. Dodder, B. Strandberg and R.A. Hites, Environ. Sci. Technol., 36 (2002) 146. J. de Boer and W.P. Cofino, Chemosphere, 46 (2002) 625. C. Thomsen, L.S. Haug, H. Leknes, E. Lundanes, G. Becher and G. Lindstro¨m, Chemosphere, 46 (2002) 641. ˇ ajka, J. Hajslova, R. Kazda and J. Poustka, J. Sep. Sci., 28 (2005) 601. T. C E. Eljarrat, A. de la Cal and D. Barcelo´, J. Chromatogr. A, 1008 (2003) 181. V.S. Ong and R.A. Hites, Mass Spectrom. Rev., 13 (1994) 259. C. Thomsen, E. Lundanes and G. Becher, J. Sep. Sci., 24 (2001) 282. W. Vetter, Anal. Chem., 73 (2001) 4951. U. Sellstro¨m, Ph.D. Thesis: Determination of Some Polybrominated Flame Retardants in Biota, Sediment and Sewage Sludge, University of Stockholm, Sweden, 1999. ¨ stman, J. Mass Spectrom., 38 (2003) 394. J. Bjo¨rklund, P. Tollba¨ck and C. O H.R. Buser, Anal. Chem., 58 (1986) 2913. ˚ . Bergman and L. Asplund, Environ. Sci. Technol., 38 (2004) 10. G. Marsh, M. Athanasiadou, A J.B. Manchester-Neesvig, K. Valters and W.C. Sonzogni, Environ. Sci. Technol., 35 (2001) 1072. C. Salgado-Petinal, M. Garcia-Chao, M. Llompart, C. Garcia-Jares and R. Cela, Anal. Bioanal. Chem., 385 (2006) 637. D. Wang, Z. Cai, G. Jiang, M.H. Wong and W.K. Wong, Rapid Commun. Mass Spectrom., 19 (2005) 83. V. Yusa, A. Pastro and M. de la Guardia, Anal. Chim. Acta, 565 (2006) 103.
Brominated Flame Retardants as Food Contaminants
567
137 D. Larraza´bal, M.A. Martı´nez, E. Eljarrat, D. Barcelo´ and B. Fabrellas, J. Mass Spectrom., 39 (2004) 1168. 138 QUASIMEME, Report Workshop Analysis Brominated Flame Retardants, Barcelona, Spain, 21–23 October 2002, FRS Marine Laboratory, Aberdeen, UK. 139 W. Budakowski and G. Tomy, Rapid Commun. Mass Spectrom., 17 (2003) 1399. 140 K. Jana´k, A. Covaci, S. Voorspoels and G. Becher, Environ. Sci. Technol., 39 (2005) 1987. 141 G.T. Tomy, T. Halldorson, R. Danell, K. Law, G. Arsenault, M. Alaee, G. MacInnis and C.H. Marvin, Rapid Commun. Mass Spectrom., 19 (2005) 2819. 142 A. Covaci, A.C. Gerecke, R.J. Law, S. Voorspoels, M. Kohler, N.V. Heeb, H. Leslie, C.R. Allchin and J. de Boer, Environ. Sci. Technol., 40 (2006) 3679. 143 T. Hayama, H. Yoshida, S. Onimaru, S. Yonekura, H. Kuroki, K. Todoroki, H. Nohta and M. Yamaguchi, J. Chromatogr. B, 809 (2004) 131. 144 J. Tollba¨ck, C. Crescenzi and E. Dyremark, Determination of the flame retardant tetrabromobisphenol-A in air samples by liquid chromatography-mass spectrometry, J. Chromatogr. A, 1104 (2006) 106. 145 R. Saint-Louis and E. Pelletier, Analyst, 129 (2004) 724. 146 L. Debrauwer, A. Riu, M. Jouahri, E. Rathahao, I. Jouanin, J.P. Antignac, R. Cariou, B. Le Bizec and D. Zalko, J. Chromatogr. A, 1082 (2005) 98. 147 K. Worral, A. Newton and C. Robinson, The analysis of dioxins and related POPs using GC-high resolution MS with the Autospec UltimaNT, Micromass, Waters Corporation, Conference Proceeding, Krakow, Poland, 2002. 148 M. Schlummer, F. Brandl, A. Ma¨urer, L. Gruber and G. Wolz, Organohalogen Compd., 66 (2004) 873. 149 K. D’Silva, Ph.D. Thesis: Brominated Organic Micro-pollutants in Food and Environmental Biota, University of Leeds, 2005. 150 A. Kotz, R. Malisch, K. Kypke and M. Oehme, Organohalogen Compd., 68 (2006) 1905. 151 A. Malmva¨rn, Y. Ze¨buhr, S. Jensen, L. Kautsky, E. Greyerz, T. Nakano and L. Asplund, Environ. Sci. Technol., 39 (2005) 8235. 152 A. Malmva¨rn, U. Eriksson, L. Kautsky and L. Asplund, Organohalogen Compd., 67 (2005) 1380. 153 A. Kierkegaard, J. Bjo¨rklund and U. Friden, Environ. Sci. Technol., 38 (2004) 3247. 154 A. Konstantinov, G. Arsenault, B. Chittim, T. Loic, K. MacPherson, A. McAlees, R. McCridle, D. Potter, E.J. Reiner, C. Tashiro and B. Yeo, Chemosphere, 64 (2006) 245. 155 E. Hoh, L.Y. Zhu and R.A. Hites, Environ. Sci. Technol., 39 (2005) 2472. 156 A. Sjo¨din, Ph.D. Thesis: Occupational and Dietary Exposure to Organohalogenated Substances with Special Emphasis on Polybrominated Flame Retardants, Stockholm University, Sweden, 2000. 157 C. Thomsen, H. Leknes, E. Lundanes and G. Becher, J. Anal. Toxicol., 26 (2002) 129. 158 N.G. Dodder, A.M. Peck, J.R. Kucklick and L.C. Sander, J. Chromatogr. A, 1135 (2006) 36. 159 G. Luthe, P.E.G. Leonards, H. Liu and J.E. Johansen, Organohalogen Compd., 66 (2004) 3715. 160 L.S. Haug, C. Thomsen and G. Becher, First Interlaboratory Comparison on HBCD in Biological Samples, Norwegian Institute of Public Health, Oslo, Norway, 2006. 161 J.J. Ryan and B. Patry, Organohalogen Compd., 51 (2001) 226. 162 A. Johnson and N. Olson, Arch. Environ. Contam. Toxicol., 41 (2001) 339. 163 R.F. Brown, J. Winkler, P. Visita, J. Dhaliwal and M. Petreas, Chemosphere, 64 (2006) 276. 164 D. Hayward, J. Wong and A.J. Krynitsky, Environ. Res., 103 (2007) 46. 165 A. Schecter, O. Papke, T.R. Harris, K.C. Tung, A. Musumba and J. Olson, Environ. Health Perspect., 114 (2006) 1515. 166 A. Schecter, O. Papke, K.C. Tung, J. Joseph, T.R. Harris and J. Dahlgren, J. Occup. Environ. Med., 47 (2005) 199. 167 J.J. Ryan, Polybrominated diphenyl ethers (PBDEs) in human milk; Occurrence worldwide. Proceedings of the 3rd International Workshop on Brominated Flame Retardants, Toronto, ON, Canada, June 6–9, 2004, pp. 17–22. 168 H.A. Jones-Otazo, J.P. Clarke, M.L. Diamond, J.A. Archbold, G. Ferguson, T. Harner, G.M. Richardson, J.J. Ryan and B. Wilford, Environ. Sci. Technol., 39 (2005) 5121. 169 H.M. Stapleton, N.G. Dodder, J.H. Offenberg, M.M. Schantz and S.A. Wise, Environ. Sci. Technol., 39 (2005) 925.
568
Adrian Covaci et al.
170 C. Tlustos, I. Pratt, B. McHugh, L. Tyrrell, H. Cooper, C. Duffy and E. McGovern, Organohalogen Compd., 67 (2005) 636. 171 C. Tlustos, I. Pratt, S. White, A. Fernandes and M. Rose, Organohalogen Compd., 67 (2005) 1474. 172 H. Knutsen, C. Bergsten, C. Thomsen, A. Sletta, G. Becher, J. Alexander and H.M. Meltzer, Organohalogen Compd., 67 (2005) 1624. 173 P.O. Darnerud, G.S. Eriksen, T. Jo´hannesson, P.B. Larsen and M. Viluksela, Environ. Health Perspect., 109 (2001) 49. 174 Y. Lind, M. Aune, S. Atuma, W. Becker, R. Bjerselius, A. Glynn and P.O. Darnerud, Organohalogen Compd., 58 (2002) 181. 175 Y. Lind, P.O. Darnerud, S. Atuma, M. Aune, W. Becker, R. Bjerselius, S. Cnattingius and A. Glynn, Environ. Res., 93 (2003) 186. 176 P.O. Darnerud, S. Atuma, M. Aune, R. Bjerselius, A. Glynn, K. Petersson Grawe´ and W. Becker, Food Chem. Toxicol., 44 (2006) 1597. 177 R. Gru¨mping, M. Petersen, A. Kuchen and C. Tlustos, Organohalogen Compd., 68 (2006) 2147. 178 R. De Winter-Sorkina, M.I. Bakker, G. van Donkersgoed and J.D. van Klaveren, Dietary intake of brominated flame retardants by the Dutch population, RIVM report 310305001/2003, 2003. 179 M.J. Zeilmaker, Organohalogen Compd., 68 (2006) 387. 180 K. D’Silva, A. Fernandes, S. White, M. Rose, D.N. Mortimer and M. Gem, Organohalogen Compd., 68 (2006) 770. 181 M.N. Jacobs, A. Covaci and P. Schepens, Environ. Sci. Technol., 36 (2002) 2797. 182 A. Covaci, S. Voorspoels, J. Wyckmans, A. Gelbin and H. Neels, Organohalogen Compd., 68 (2006) 5. 183 Q. Jiang, Y. Miyake, N. Hanari, T. Okazawa, N. Yamashita and P.K.S. Lam, Organohalogen Compd., 68 (2006) 1812. 184 R. Nakagawa, Y. Ashizuka, T. Hori, D. Yasutake, K. Tobiishi and K. Sasaki, Organohalogen Compd., 68 (2006) 2166. 185 S.J. Cha, Y.S. Kang and J.S. Park, Organohalogen Compd., 67 (2005) 1667–1670. 186 S. Bayen, G.O. Thomas, H.K. Lee and J.P. Obbard, Environ. Toxicol. Chem., 22 (2003) 2432. 187 R.A. Hites, Environ. Sci. Technol., 38 (2004) 945. 188 T. Webster, V. Vieria and A. Schecter, Organohalogen Compd., 67 (2005) 505. 189 S. Harrad, S. Hazrati and C. Ibarra, Environ. Sci. Technol., 40 (2006) 4633. 190 N. Wu, T. Webster, T. Herrmann, O. Paepke, J. Tickner, R. Hale, E. Harvey, M. La Guardia and E. Jacobs, Organohalogen Compd., 67 (2005) 654. 191 S. Harrad and M. Diamond, Atmos. Environ., 40 (2006) 1187. 192 G. Tomy, T. Halldorson, R. Danell, K. Law, G. Stern, S. Gerwutz, M. Whittle, M. Alaee and C. Marvin, Hexabromocyclododecane (HBCD) isomers and brominated diphenyl ether (BDE) congeners in fish from Lake Winnipeg, Manitoba (Canada). The Third International Workshop on Brominated Flame Retardants, Toronto, Canada, June 6–9, 2004, pp. 213–216. 193 G.T. Tomy, W. Budakowski, T. Halldorson, D.M. Whittle, M.J. Keir, C. Marvin, G. MacInnis and M. Alaee, Environ. Sci. Technol., 38 (2004) 2298. 194 M. Schlabach, E. Fjeld and A.R. Borgen, Brominated flame retardants in Drammen River and the Drammensfjord, Norway. Proceedings of the 3rd International Workshop on Brominated Flame Retardants, Toronto, Canada, June 6–9, 2004, pp. 147–150. 195 M. Schlabach, E. Fjeld, H. Gundersen, E. Mariussen, G. Kjellberg and E. Breivik, Organohalogen Compd., 66 (2004) 3730. 196 C. Bethune, J. Nielsen, A.K. Lundebye and K. Julshamm, Organohalogen Compd., 67 (2005) 619. 197 M. Schlabach, E. Mariussen, A. Borgen, C. Dye, E.K. Enge, E. Steinnes, N. Green and H. Mohn, Kartlegging av bromerte flammehemmere og klorerte parafiner. NILU Rapport 866/02, 2002. 198 A.C. Gerecke, M. Kohler, M. Zennegg, P. Schmid and N.V. Heeb, Organohalogen Compd., 61 (2003) 155. 199 P. Schmid, E. Gujer, M. Zennegg and M. Lanfranchi, Organohalogen Compd., 66 (2004) 1716. 200 T.A. Verslycke, A.D. Vethaak, K. Arijs and C.R. Janssen, Environ. Pollut., 136 (2005) 19. 201 UK Committee on Toxicity of Chemicals in Food, Consumer products and the Environment. Available at http://www.food.gov.uk/science/surveillance/fsisbranch2006/fsis1006
Brominated Flame Retardants as Food Contaminants
569
202 Food Standards Agency, Food safety information sheet 04/06-Brominated chemicals in farmed and wild fish, shellfish and fish oil dietary supplements, FSA, United Kingdom, 2006. Available at http://www.food.gov.uk/multimedia/pdfs/fsis0406.pdf 203 P. Haglund, K. Lindkvist, K. Wiberg, A. Malvarm, L. Asplund and A. Bignert, Organohalogen Compd., 67 (2005) 1267. 204 Ministry of the Environment, Findings of the Fiscal 2000 Survey on Brominated Dioxins Japan, 2001. Available at http://www.env.go.jp/en/chemi/dioxins/fiscal2000/brominated.pdf 205 European Commission, Directive 2002/95/EC of the European Parliament and of the Council of 27 January 2003 on the restriction of the use of certain hazardous substances in electrical and electronic equipment, Off. J. Eur. Commun. L, 37 (2003) 19. 206 European Commission, Directive 2003/11/EC of the European Parliament and of the Council of 6 February 2003 amending for the 24th time Council Directive 76/769/EEC relating to restrictions on the marketing and use of certain dangerous substances and preparations (pentabromodiphenyl ether, octabromodiphenyl ether), Off. J. Eur. Commun. L, 42 (2003) 45. 207 European Commission, Decision 2005/717/EC of the European Parliament and of the Council of 13 October 2005 amending for the purposes of adapting to the technical progress the Annex to Directive 2002/95/EC of the European Parliament and of the Council on the restriction of the use of certain hazardous substances in electrical and electronic equipment, Off. J. Eur. Commun. L, 271 (2005) 48. 208 Federal Register Vol. 71, No. 113, June 3, 2006, 40 CFR Part 721. 209 S. Janssen, Brominated Flame Retardants: Rising Levels of Concern. Health Care without harm, www.noharm.org, Arlington, VA, 2005. 210 Canada Gazette July 1, 2006. Order adding toxic substances to Schedule 1 to the Canadian Environmental Protection Act, 1999. 211 Pesticide & Toxic Chemical News, available at http://www.env.go.jp/en/, July 10, 2006. 212 K. Akutsu, M. Kitagawa, H. Nakazawa, T. Makino, K. Iwazaki, H. Oda and S. Hori, Chemosphere, 53 (2003) 645. 213 European Commission, Council Directive 83/264/EEC of 16 May 1983 amending for the fourth time Directive 76/769/EEC on the approximation of the laws, regulations and administrative provisions of the Member States relating to restrictions on the marketing and use of cetain dangerous substances and preparations, Off. J. Eur. Commun. L, 147 (1983) 9. 214 OSPAR Commission, Certain brominated flame retardants-Polybrominated diphenyl ethers, polybrominated biphenyls, hexabromocyclododecane, ISBN 0 946956 70 7, 2001. 215 C. Lassen, S. Lokke and L.I. Andersen, Brominated flame retardants; Substance flow analysis and assessment of alternatives. Danish Environmental Protection Agency, Ministry of Environment and Energy, Copenhagen, Denmark, 1999. 216 F.J. Di Carlo, J. Seifter and V.J. DeCarlo, Environ. Health Perspect., 23 (1978) 351. 217 Canada Gazette, Prohibition of Certain Toxic Substances Regulations, April 9, 2003. 218 European Commission, Regulation 2364/2000/EC of 25 October 2000 concerning the fourth list of priority substances as foreseen under Council Regulation (ECC) No 793/93, Off. J. Eur. Commun. L, 273 (2000) 5. 219 European Commission, Joint Research Center 2006a. EU Risk Assessment Report 2,2’,6,6’Tetrabromo-4,4’-isopropylidenediphenol (TBBP-A). Part II — Human Health. Available at http:// www.bsef.com/newsmanager/uploads/final_tbbpa_human_health_report.pdf 220 D. Gutzman, R. Chenier, J. Pasternak, L. Suffredine and K. Taylor, Environmental risk assessment of brominated flame retardants under the Canadian Protection Act, 1999. Proceedings of the 3rd International Workshop on Brominated Flame Retardants, Toronto, ON, Canada, 2004, pp. 11–14. 221 European Commission, Joint Research Center 2006b. Risk Assessment Hexabromocyclododecane, draft, 17. 222 European Commission, Regulation 2268/95/EC of 27 September 1995 concerning the second list of priority substances as foreseen under Council Regulation (ECC) No 793/93, Off. J. Eur. Commun. L, 237 (1995) 8. 223 K. Moss, BFR regulatory update. Proceedings of the 3rd International Workshop on Brominated Flame Retardants, Toronto, ON, Canada, June 6–9, 2004, pp. 7–9. 224 S. Hamm, M. Strikkeling, P.F. Ranken and K.P. Rothenbacher, Chemosphere, 44 (2001) 1353.
570
Adrian Covaci et al.
225 E. Hansen, Report: 570, Substance flow analysis for dioxins in Denmark, Danish Environmental Protection Agency, Ministry of Environment and Energy, Copenhagen, Denmark, 2000. 226 UK Committee on Toxicity (COT), Statement on chlorinated and brominated contaminants in shellfish, farmed and wild fish. Statement 2006/06, April 2006. Available at http://www.food. gov.uk/multimedia/pdfs/cotstatementfishsurveys.pdf 227 A. Kotz, R. Malisch, K. Kypke and M. Oehme, PBDE, PBDD/F and mixed chlorinatedbrominated PXDD/F in pooled human milk samples from different countries. Proceedings of the 3rd International Workshop on Brominated Flame Retardants, Toronto, ON, Canada, June 6–9, 2004, pp. 1540–1544. 228 L. Needham, D.G. Patterson, Jr., A.M. Calafat, A. Sjodin, W. Turner and Z. Kuklenyik, Organohalogen Compd., 68 (2006) 484. 229 M.L. Hardy, J. Biesmeier, O. Manor and W. Gentitm, Environ. Int., 29 (2003) 793. 230 OSPAR Commission, OSPAR background document on tetrabromobisphenol-A, ISBN 1-90442639-5, 2005. 231 A. Maage, K. Julshamm, H. Hove and M. Lorentzen, Organohalogen Compd., 68 (2006) 1924. 232 Y. Yoshida, T. Kawamura, K. Yamamoto, H. Sekii and S. Komoto, Organohalogen Compd., 67 (2005) 2127. 233 M.G. Ikonomou, M.P. Fernandez and Z.L. Hickmanm, Environ. Pollut., 140 (2006) 355.
CHAPT ER
16 Metals Clinio Locatelli
Contents
1. Introduction 1.1 Essential and non-essential elements 2. Analytical Procedure for Metal Determination 2.1 Sampling 2.2 Sample dissolution-destruction of organic matter 2.3 Separation and concentration methods 2.4 Laboratory contamination 2.5 Instrumental determination methods 3. Metals of Interest 3.1 Mercury 3.2 Platinum group metals 3.3 Miscellanea 4. Directive for Trace Metals in Food 5. Conclusions and Future Trends 5.1 Typology of the food samples 5.2 Instrumental techniques employed References
571 572 573 573 574 576 577 578 585 585 587 588 589 589 590 590 590
1. INTRODUCTION Metals are integral parts of the food chain, and, even if they have different origins (natural, artificial that includes criminal acts), they reach inexorably the last steps of such chains, so becoming in several cases very dangerous, also with irreversible effects, for animal and human life. In this sense, it is very important to have the possibility to determine these species at very low concentration levels in different organic matrices, food and feeding stuff in general. Many toxic trace elements may be present in such matrices at concentration levels below the limits of detection of the analytical methods. However, it is important to highlight that probably today the true problems are not the instrumentation, but the possibility of carrying out the determination in suitable Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00016-0
r 2008 Elsevier B.V. All rights reserved.
571
572
Clinio Locatelli
laboratories: the real risk is the external contamination. Food analyses must be carried out in clean rooms, using suitable reagents, glassware and laboratory materials.
1.1 Essential and non-essential elements It is impossible to establish a clear distinction between essential and non-essential (toxic) elements, since all metals are probably toxic if ingested in sufficient amounts. However, even if this aspect is beyond the aim of this discussion, some consideration may be given. In a very interesting work, Wolf [1] discussed, in a qualitative way, the relationship about the elements, their recommended dietary allowance, adequate intake and recommendations. The fundamental four points described in this work, and still valid [2–4], are:
to to to to
establish if a trace metal is or is not essential; determine the amount of metal required for proper nutrition; identify the inadequate or excessive levels of trace metals in diets; prevent, eventually, the non-optimal intakes of trace metals.
It is clear that the metal classification as essential or non-essential is strictly linked to the biological role that the elements play, precisely identifying either the biological parameters or the metal concentration levels involved. Only following such a way, it is possible to establish the optimum trace metal level for the diet and the concentration boundary line between essentiality and non-essentiality. It is also true that the concept essential/non-essential is applicable to several metals, but other elements, i.e., lead, cadmium, mercury, arsenic, antimony, are toxic at very low concentration levels of intake and there are no known deficiency symptoms showing also cumulative effects, and for this reason they are extremely harmful to health. As previously highlighted, the presence of metals in foods at a greater or lesser concentration level is linked to increasing industrialization and, consequently, to environmental pollution. For example, crops may contain toxic metals according to the nature of the soil, insecticide and fertiliser treatment and/or proximity of industrial zones [5,6]. Finally, trace metal contamination may frequently arise from a non-suitable conservation practice of foods. Even if several years ago, in the 1970s–1980s, the literature on the toxic metals in food, according to the law in force in that time, which generally provided for the determination of lead and cadmium, was prevalently addressed to the determination of these elements [7–14]. More recently, the literature has become very vast, including all metals, alkaline, alkaline-earth and transition metals [15–21]. However, the present discussion will be prevalently addressed to toxic metals with great attention to metals of particular interest, at least at the present time, for example, mercury(II) and platinum group metals (PGMs) [Pt(II), Pd(II) and Rh(III)], taking into account in all cases only the recent literature, that, inevitably, reports also all previous works.
Metals
573
Finally, the present discussion will be concerned with the total analytical procedure for the determination of metals in food, from sampling to final analytical concentration datum, passing through sample preparation before the analysis and instrumental method step. It is important also to highlight that biochemical [22,23], toxicological and nutritional aspects of trace metals, even if of interest to chemists, will not be discussed here.
2. ANALYTICAL PROCEDURE FOR METAL DETERMINATION The principal steps of the analytical procedure to give the final reliable concentration data relevant to trace metals in real matrices, as food matrices, are [24]: sampling, in order to obtain a representative sample; sample dissolution, i.e., destruction of organic matter, wet ashing or dry ashing; instrumental analysis and subsequent data interpretation processing.
2.1 Sampling Generally, sampling consists of removing a small portion from a matrix, in such a way that the same portion is the true representation of the properties of the original matrix. The great problem of the sampling procedure is relevant to the ‘‘homogeneity’’ of the final sample, which must be absolutely total, to have reproducible and representative concentration data [25–28]. Unfortunately, food matrices are, in general, heterogeneous and sampling errors could be frequent, so causing a high variability of concentration data among that determined in different laboratories, even if obtained employing the same analytical procedure. The object of a correct sampling scheme is to minimize, certainly not eliminate, such variations, which must be or better should be within the experimental errors. In my opinion, the sampling operation must be done by an analytical chemist for his feeling and evidence about the analytical way to obtain the final correct concentration datum. Sampling can be carried out following two distinct procedures: (1) (2)
Random selection. Portions of the matrix are taken in such a way that every part has statistically an equal chance of appearing in the sample. Representative or selective sampling. Each sample represents a partial and precise part of the whole matrix, but not the same matrix.
Probably, in food analysis, the random selection is the more frequently employed procedure, even if in some specific cases, the selective sampling is necessary. It is important to highlight that, in order to give a faithful situation of the metal concentration inside a sample, sometimes it is necessary to carry out
574
Clinio Locatelli
sub-samplings. In this case, the analytical chemist must also suggest the procedure. Strictly linked to sampling procedure, two other important steps must be considered: (a) sample homogenization and subsequently (b) storage.
2.1.1 Sample homogenization Liquids are ‘‘probably’’ the easiest samples to treat: easily mixed, filtered and sometimes immediately fit for the instrumental measurement. However, most foodstuffs are solid, non-homogeneous and their preparation for analysis may be difficult. The homogeneity may be obtained employing agate mortars, corundum ball mills or particular instrumentation that must assure the total absence of contamination by metals. The homogenization procedure involves sub-divisions by using either coning and quartering methods or riffling technique [29], and it may be followed, but more frequently preceded by liophilization treatment [30–34].
2.1.2 Sample storage If the analysis cannot be started immediately, suitable precautions to prevent changes in the sample composition are required. To avoid alteration in the sample, storage is generally carried out employing air-tight containers at low temperature, depending on the kind of the sample: liquid or solid.
2.2 Sample dissolution-destruction of organic matter The sample dissolution is a very important step of the analytical procedure in order to obtain a reliable final concentration datum. The sample dissolution is then strictly linked to the kind of analyte to determine. Generally, in the case of food matrices, inorganic contents, and metals in particular are the minor constituents; so it is absolutely necessary to remove the organic matter, the major constituent, before the final instrumental measurement to obtain the element concentration, since several interference problems may arise. Really, the direct determination of metals in food matrices without a sample pre-treatment has seldom been followed [35]. On the contrary, most procedures proposed for the determination of metals in food matrices require a preliminary destruction of organic matter, since this predominant component certainly interferes in the analytical procedure [36,37], altering significantly in positive or negative ways the metal concentration value. Several methods, aimed to solve the problem relevant to the destruction of the organic matter, have been proposed in the literature [24,38,39]. However, it is not possible to recommend a single particular procedure since, generally, all the proposed methods are strictly linked to personal surveys, convictions or preferences. In the 1970s, Gorsuch [39] published a very interesting and still now actual treatise, showing that, in all cases, the destruction of organic matter is the more suitable procedure for obtaining a correct metal concentration datum.
Metals
575
The two methods usually employed are: wet and dry ashing, and a third procedure, the fusion, is rarely followed [38]. Obviously, the choice of a particular procedure always represents a compromise in order to obtain the better concentration datum (good precision, accuracy, limits of detection and/or quantification, sensitivity of the analytical procedure, and so on). Both wet and dry ashing present advantages and disadvantages. Wet ashing involves reasonable times, small amounts of sample, but relatively large volume of reagents, and then contamination due to the reagent impurities may be a serious problem, especially in the case of very low element concentrations. Dry ashing also requires reasonable times, but a relatively large amount of sample is necessary. Such a procedure presents, however, also contamination problems. In dry ashing, because containers must be left open to the atmosphere, contamination caused by airborne particulate and/or by components of the ashing apparatus may be a problem. Besides, analyte losses may occur in the case of an element with very high volatility as Hg (see Section 3.1) or of hydrides of particular metals, such as As(III), Sb(III), Sn(IV), Te(II), Se(II), which have boiling points lower than 01C.
2.2.1 Wet ashing Wet ashing involves sample treatments with a mixture of acids. In literature, numerous compositions have been proposed for such mixtures, depending, in several cases, on the preference of the Analyst [24,38–43]. However, all have particular characteristics, strictly linked to the individual properties of the acids employed. Nitric and perchloric acids are very strong oxidizing agents. Generally, sulfuric acid is used with an additional substance such as hydrogen peroxide to yield a cleaner decomposition mixture. Combinations of the above acids are normally recommended for food analyses [24,38]. Nitric acid is recommended in the case of food samples with high chloride content. Nitric and sulfuric acid mixtures are widely used for the decomposition of samples with low organic matter content, while mixtures nitric–sulfuric–perchloric acids are employed for samples with high fat content. Nitric–perchloric acidic mixtures are generally used in the case of samples rich in proteins and carbohydrates, but in the absence of fat. Hydrofluoric acid has no oxidizing power and finds unique application in the decomposition of organic samples containing silicon or silica in varying amounts, such as corn leaves. Only in this case, because hydrofluoric acid attacks silicon bonds, it is essential to use non-glass apparatus for the sample treatment (generally Teflon apparatus is employed). The digestion and decomposition of food samples in acidic media are usually carried out employing commercial microwave oven, using polytetrafluoroethylene (PTFE)-lined stainless-steel vessels (the experimental conditions are generally recommended by the manufacturer), even if the literature reports several works, in which home-made apparatus are described [24,38,39,44]. Sometimes, the use of catalysts to speed up the rate of digestion was proposed, but after the first works [45], the procedure successively did not show a great success.
576
Clinio Locatelli
2.2.2 Dry ashing Although dry ashing generally requires a longer time, if compared with wet ashing, it may be interesting because larger sample amounts can be used and generally no reagent addition is necessary [46–48]. Then, elements at very low concentrations can be easily determined and contamination due to the reagents is low, even if strong contamination during dry ashing can be present and give serious problems [49]. In fact, the sample must be open to the air and dust particles in air can contaminate the sample. Therefore, dry ashing should be done in a clean area. Moreover, a final leaching step, carried out with acidic mixtures (usually nitric and hydrochloric acid) is required to bring the sample into solution. However, as in the case of wet ashing, also in this case blanks must always be done to obtain a correct analytical concentration datum. Finally, it is important also to highlight that the literature reports many papers regarding the critical comparison between wet and dry ashing, in order to suggest the better sample preparation procedure before the instrumental measurements [50–54].
2.2.3 Fusion Fusion [38], although very effective in decomposing organic samples, shows the disadvantage in trace element analysis of adding contaminants, and it is recommended only if other approaches are not satisfactory. A variety of fusing agents are available, the most common of which are sodium peroxide and hydroxide, potassium pirosulfate and metaborate. These compounds generally contain many impurities, and thus, considering that they may be purified with difficulty and that they must necessarily be mixed with the sample usually in excess, the risk of contamination from their use is very high. After the fusing step, the mixture is cooled at room temperature and then leached to bring the sample into solution. Leaching solution consists of dilute acids in mixture (usually nitric and hydrochloric acid, as in the case of dry ashing).
2.3 Separation and concentration methods Certainly, an optimum starting-point for the discussion about the separation and concentration methods in trace element analysis is the review published by Bachmann [55], who suggests solvent extraction and ion-exchange chromatography [56–59] as the most suitable approaches to trace element analysis. Separation and concentration methods are extra-steps in an analysis; they must be avoided if non-essential, since they are a possible cause of sample contamination. However, sometimes, separation is necessary to remove the analyte from an interfering matrix, and to bring the level of concentration of the analyte to a detectable level for the technique chosen, even if in both cases, the need for such a procedure is continually decreasing with improvements of the instrumentation.
Metals
577
2.4 Laboratory contamination This section, certainly not exhaustive, proposes only to alert the analytical chemists to the correct procedures to follow in the laboratories addressed to trace metal analysis, simply highlighting the critical points.
2.4.1 Water Water of high purity is essential in all steps of food sample preparation. The purity of water is normally expressed in terms of resistivity. In the case of trace element determination, the water must show to have resistivity better than 10–12 MO/cm, even if recent apparatus supply water at about 18 MO/cm resistivity.
2.4.2 Reagents In all cases (salts, acids, bases, and so on) they must be of Suprapur or Aristar grade, the latter to be used when the highest level of purity is required.
2.4.3 Containers The literature reports several works on the suitability of different container materials for storage of samples and standards in trace metal analyses. Really the fundamental problem is the ‘‘loss’’ of the analytes caused by sorption of the same analytes on the container walls. The intensity of the sorption phenomenon is strictly linked to some factors, for example: chemical form and/or chemical concentrations; composition and characteristics of the solution: dissolved salts, complexing agents, pH, and so on; composition and characteristics of the containers: chemical composition of the walls (generally sorption effects decrease according to the following order: borosilicate glass, pyrex, plastic and, in particular Teflon, quartz, even if the cost of the containers increases significantly following the same order [60]), surface cleanliness and roughness, and especially, surface area exposed to solution (in this case, particular attention must be paid to the ratio of inner container surface contacting the solution to solution volume); external factors, for example temperature, light exposure, length of the storage time. In this section, it is important to point out the work of Massee et al. [61] where the authors suggest different container materials taking into account the element, the matrix and the pH.
2.4.4 Laboratory requirements It may, probably, be an incorrect way to discuss, but in my opinion, the laboratory requirements for trace element determinations is prevalently assigned to the ‘‘analytical feeling’’ that chemists are shown to have. However, a fundamental precaution must be observed, i.e., the possibility of separating the laboratory into rooms dedicated to specific activities, e.g., balance room, instrument room,
578
Clinio Locatelli
chemical and/or sample preparation rooms. Only in this way is it possible to separate and solve the inevitable problems, and, in specific, contamination problems, that can occur in the different steps of the analytical procedure.
2.5 Instrumental determination methods Several instrumental techniques are addressed to the determination of metals in food matrices. The choice of the technique to be used, as well as scientific consideration, often depends on several factors, such as instrumental availability and cost, and number of samples to be analysed. No one technique, however, will solve all the problems likely to be encountered. For the determination of metals in food, voltammetric and spectroscopic methods were used almost exclusively up to 1980–1990. In recent years, several innovative techniques have been set up and proposed for element determination in complex matrices like food samples, even if the simultaneous multicomponent determination is largely privileged and encouraged.
2.5.1 Electroanalytical techniques Electroanalytical methods are characterized by some fundamental lines and survey fields: (a) ion-selective electrodes, (b) voltammetric and (c) potentiometric stripping analysis.
2.5.1.1 Ion-Selective electrodes. The technique is addressed to major elements such as alkaline, earth-alkaline metals [62], halogen anions [63–65] and organic acids [66], since measurements employing ion-selective electrodes are seldom possible at concentrations below mg/L level. For this reason, such a technique is not linked to the aim of the present discussion, even if some works relevant to the metal determinations in food [67–69] and very interesting reviews [70–72] have been published. Only anodic stripping voltammetry (ASV) and potentiometric stripping analysis (PSA) are the techniques employed in the case of trace metal determinations. Qualitative information is strictly linked, for each supporting electrolyte, to the peak potential, while the height of the signal gives the quantitative information. This is very important: conceptually ASV and PSA may be associated with chromatography, but they are certainly very complete techniques, which do not need complementary instrumental methods for a correct analytical determination, permitting either to quantify several metals carrying out single potential scans (possibly multicomponent determination) or to determine very low concentrations. Following these two important and fundamental starting points, Locatelli performed several works addressed to the sequential voltammetric determination of metals in food samples [73–80], taking into account also the matrices linked to environmental problems [73,74,79]. 2.5.1.2 Voltammetric stripping analysis. ASV is a powerful technique for the determination of metals at sub-ppb concentration level. Together with ASV,
Metals
579
cathodic stripping voltammetry (CSV) and adsorption stripping voltammetry (AdSV) are also employed in the metal determination. Evidently, the choice of the technique to employ is linked to the element to determine. After the metal ions have been pre-concentrated from the solution and amalgamated into stationary mercury electrode, using a potential more negative than the reduction potentials of the species to be determined, the process is reversed and the metals are oxidized and stripped anodically using a slowly increasing positive potential. The measured current recorded during the stripping step is a direct linear function of the bulk concentration of each metal [81,82]. Some years ago, stripping voltammetry in food and environmental analysis has been precisely and exactly reviewed by Brainina et al. [83]. The more recent works, addressed to metal determinations in food samples employing anodic and/or CSV, highlight especially the possibility of simultaneously determining several elements in the same food sample. Recently, Locatelli proposed several works regarding the simultaneous and/or sequential voltammetric determination of metals in food matrices: mussels, clams and fishes [44,78–80], meals [73–77] and vegetables [73]. In general, the fundamental problem in the case of multicomponent voltammetric determination regards the metal signal interference. In fact, the reduction peak potentials of each metal, in the commonly used supporting electrolytes, are sometimes very close and then, the simultaneous voltammetric determination of neighbouring elements should be hindered. So in the case of a large excess of one component, an increased overlapping of signals are observed in the measurements of neighbouring elements. Several works have dealt with this problem, solving it in two ways. (1)
(2)
The standard addition method [74,75], which allows one to establish the element concentration ratio within which the metal present at lower concentration can be determined. The employment of different solutions or complexing agents as supporting electrolytes, because the same element can present different peak potentials according to the composition of the medium used for the voltammetric determination. However, such a procedure is strictly linked to the reversibility of the electrodic processes, that allows to establish if, in a given supporting electrolyte, each metal shows to have a reversible, quasireversible or irreversible electrodic process, and, consequently well or bad defined peaks, but also, in the case of very irreversible electrodic processes, the absolute absence of the voltammetric signal [81,82,84,85]. Then, an analytical procedure that provides for the employment of two or more supporting electrolytes certainly may overcome and solve voltammetric metal interference problems.
However, the literature reports several papers regarding the voltammetric determination of metals in food matrices at ppb or sub-ppb concentration levels. Considering only the more recent papers describing the voltammetric analytical procedure for the determination of toxic metals in several kinds of food matrices,
580
Clinio Locatelli
the literature reports works relevant to vegetables [73,86–88], fish and sea food [89,90], vegetable sauce, pulp of sugar beet and wine [91–94], food for infants and milk [95,96], rice and tea leaves [97]. Even if all are addressed to very toxic metals in the different food matrices, among these, probably lead is certainly the more investigated but, in this context only few works [98,99] report or discuss its strong interference with tin, element largely used in the agricultural practice, and consequently present in food matrices of vegetable origin. Finally, it is worth highlighting the review by Cavicchioli et al. [100] relevant to analysis and speciation of arsenic traces in food samples by voltammetry. As it is well-known, arsenic is a very common element employed in agricultural practice and, for this reason, such a metal certainly shows to have considerable chances to enter the food chain.
2.5.1.3 Potentiometric stripping analysis. PSA, introduced and proposed by Jagner and Graneli [101], is similar to conventional voltammetric stripping analysis, since the metals are pre-concentrated as amalgams in a thin mercury film. It differs from voltammetric stripping modes in the approach used in reoxidizing the metals and generating the instrumental signal. PSA is concerned with the determination of metals accumulated on a mercury electrode by monitoring the change of potential with time, which occurs during chemical oxidation of the same accumulated metal (time vs. potential function) [81,82,84,85,102]. Even if the theoretical discussion about the PSA technique is certainly beyond the present discussion, it is important to highlight that, at least up to now, no surveys relevant to reciprocal signal interference problems in PSA have been published. The only one interference investigated and amply reported in literature is relevant to the formation of copper–zinc intermetallic compounds [103–106]. Notwithstanding this, many papers regarding the metal determination in food matrices are reported in literature, even if, unfortunately this technique seems to be limited only to copper, lead, cadmium and zinc determination [101–117]. Only in a few cases are elements like selenium, arsenic, tin, antimony and bismuth tentatively determined [100,118–122]. 2.5.1.4 Solid electrode: An opportunity? Finally, it is important to highlight a very interesting aspect that certainly will be fundamental in future years in the field of metal voltammetric determinations in food matrices: the employment of mercury-free electrodes. The rules which regulate the use of mercury in the voltammetric determination of trace metals in food matrices are very punctual and restrictive. The determination must be carried out in isolated areas, avoiding contact with food. For this reason the set-up and the possibility to carry out voltammetric determination directly on the spot may be a great chance for the voltammetry in food metal determination.
Metals
581
In the field of mercury-free electrodes, the literature is vast and reports a lot of papers. Among these, some reviews, reported here as examples, seem to be very interesting [123–127]. However, at the present time, the real problem of these electrodes regards the order of the analytical calibration function. Employing the ‘‘same electrode’’ for all the voltammetric scans following each standard addition necessary to determine the element analytical calibration functions, these functions are all of second order (memory effect, other questions? all arguments are today under discussion!). This may be a problem to correctly define the limits of detection (LOD) and/or the limits of quantification (LOQ). In our laboratory, the solution of such problems has shown very important progresses, in the course of publication, especially in the field of the statistical treatment of the data. Then, overcoming these difficulties will allow the use of such electrodes in food, as in the case of our surveys (i.e., the voltammetric determination of copper, lead, cadmium and zinc in beverages and meals), but also in the environmental field. Finally, it is very important also to highlight that stripping voltammetry and potentiometry allow one to carry out speciation studies, i.e., the possibility to identify and to determine in each matrix the different element oxidation states, the knowledge of which is fundamental for analytical, but also toxicological, nutritional and so on, aims. In this context, only as example, the review by Cavicchioli et al. [100], regarding the speciation of trace of arsenic in food matrices, is certainly a very interesting paper. It focuses on how the possibility to know qualitatively and quantitatively the different element oxidation states (in this case arsenic) allows a careful interpretation of the biological, nutritional and environmental phenomena.
2.5.2 Spectrometric methods This section deals with very powerful techniques, largely employed in food analysis. It provides the more possible extensive summary about the recent developments for the determination of trace metals in food, restricting the discussion to (a) atomic absorption spectroscopy (AAS) including cold vapour (CV-AAS) and hydride generation (HG-AAS) atomic absorption spectroscopy and to related techniques (b) atomic emission (AES) and (c) atomic fluorescence spectroscopy (AFS), even if it is important to highlight that in recent years some very interesting reviews have been published to give an atomic absorption [128] and emission [129] spectrometry update about their employment in trace metal determination in food.
2.5.2.1 Atomic absorption spectroscopy. Over 70 elements can be determined by the use of this technique, including most of those of interest in food analysis. Such a technique is divided substantially into four methods to employ according to analyte concentration and/or analyte kind. These methods are flame atomic absorption spectroscopy (FAAS), electrothermal atomic absorption spectroscopy (ET-AAS), CV-AAS and HG-AAS.
582
Clinio Locatelli
2.5.2.2 Flame atomic absorption spectroscopy and electrothermal atomic absorption spectroscopy. Following the analyte concentration criterion, FAAS is employed in the determination of major and minor elements (concentrations in the solution introduced in the flame higher than 0.5–1.0 mg/L), while ET-AAS is prevalently used if trace metals must be determined (concentrations lower than 0.1–0.5 mg/L in the solution to analyse by atomic absorption spectrometer and obtained in the sample preparation step). Without discussing the main methodological and instrumental performances of the techniques, i.e., lower analytical sensitivity for FAAS, the possibility of using the L’vov platform for a higher analytical sensitivity for ET-AAS, employment of the deuterium or Zeeman background corrector, and so on, and considering that between FAAS and ET-AAS the difference is not relevant to the atomization temperature (about 2,200–2,5001K for both techniques), the true problems of such spectroscopic techniques reside in the possible interference (chemical, spectral and of ionisation) [130] and in the dynamic linearity range of the analytical calibration function. Even if both seem to be solved, or partially solved, the latter may be considered perhaps the more important from the analytical point of view. In fact, the dynamic linearity range must be calculated close to the final metal concentration to determine; in other words, the determined final metal concentration must result in the middle of a very narrow linearity range. After the very excellent review of Taylor et al. [128] some significant works relevant to spectroscopic determination of trace metals in food have been published, all addressed to obtain very low limits of detection and of quantification through simple and quick analytical procedures. The literature here reported, certainly not exhaustive, can give useful information about the works published in previous years. FAAS employed especially in the major elements determination in food [131–133], recently is also employed in the determination of minor elements like Cd, Co and Ni using a new functionalized resin [134]. Obviously, graphite furnace atomic absorption spectroscopy (GF-AAS) is more utilized, considering also the very low element concentrations in food [135–142]. Some recent works have focused the interest on the preparation of the sample before the instrumental measurement [143–150]. In this section two very interesting works must be pointed out, the former for the kind of the sample: transgenic soybean oil [151] and the latter for the innovative spectroscopic technique: direct solid sampling AAS [152]. With reference to this latter subject, it is worth highlighting the possibility of determining trace metals directly in slurry samples. The literature relevant to slurry sampling in AAS is vast [153–166]. It is important also to point out that sampling of carbonaceous slurry may be carried out also when inductively coupled plasma atomic emission spectrometry (ICP-AES) is employed as the instrumental technique [164]. However, the literature previously reported shows that the AAS certainly does not present a secondary problem: it does not allow multicomponent analysis. Even if the introduction of hollow cathode lamps have deeply limited the spectral interference, they allow only the carrying out of mono-component
Metals
583
determinations. It is evident that, being compelled to carry out determinations of several trace metals in the same food sample, certainly the problem of long times of analysis and consequently of very high analysis costs is substantial. For this reason, even if in most public and private analytical laboratories a lot of atomic absorption spectrometers are present, today all the institutional structures aim at replacing them with ICP spectrometers, which, if a mass spectrometer is present as detector, allow to carry out multicomponent determinations. It is evident that, in this case, the problem may be the budget: an ICP instrumentation, equipped with mass spectrometer, may cost 10 times more than an atomic absorption spectrometer.
2.5.2.3 Cold vapour atomic absorption spectroscopy and hydride generation atomic absorption spectroscopy. The fundamental principles of these techniques are amply reported in literature [128–130]. Also in this case, the very important review of Taylor et al. [128] is certainly a reference point. The literature reports also some interesting works [167–175], even if none seems to present novelties or improvement of the analytical procedures. 2.5.2.4 Atomic emission spectroscopy. In recent years another spectroscopic technique has acquired great importance in the trace metal determination: the ICP-AES. Starting from two fundamental reviews [130,176], recently some papers have appeared in literature, especially considering the development in the detector field. In fact, the introduction of MS as detector for ICP instrumentation has allowed a high performance of this technique in the determination of metals not only in food matrices, but also in all the real matrices (environmental, industrial, and so on). If the very high instrument cost is not considered, the great advantages of this technique regard the possibility of carrying out multicomponent analysis, of obtaining very low limits of detection and of quantification and, finally, of employing a calibration function with a very wide theoretical linear dynamic range (also four, five or more orders of magnitude). Several authors nourish well-grounded perplexities about this last aspect. However, as previously reported, it is important to highlight that day-by-day, when possible, the laboratories aim at the replacement of FAAS and ET-AAS spectrometers with ICP-AES instrumentation, possibly coupled to a mass spectrometer detector. Such a trend is confirmed also by numerous and recent literature, which is addressed either to several metals or to different food matrices. In most cases, the analytical procedures suggest the employment of ICP instrumentation either coupled [2, 177–195] or not [51,196–198] with MS as detector. Also in the case of the present technique, some works highlight the importance of the sample preparation procedure [56,179,199]. 2.5.2.5 Atomic fluorescence spectroscopy. X-ray fluorescence (XRF) is a powerful qualitative and quantitative tool used in almost all industries, including food, pharmaceuticals, cosmetics, environmental, microelectronics, telecommunications and semiconductors.
584
Clinio Locatelli
Fluorescence is a process in which a material absorbs energy and almost instantaneously releases energy in a characteristic form. The different features of XRF tools include a source at high intensity X-rays, a collimation apparatus to define the X-ray beam size and algorithmic tools for determining the composition of the sample. Even if this technique, as well-known, is applicable only to all elements with atomic number greater than 11, it presents some very important advantages: the possibility to obtain both the analytical information, qualitative and quantitative data. Like voltammetry and ICP spectroscopy, this technique allows also a third fundamental advantage, the possibility of carrying out multicomponent analysis. However, the disadvantages are well known: the apparatus is very costly and certainly requires skilled operators. AFS has been reviewed several times. In fact, from the 1970s [176,200,201] the literature reports interesting papers about the ‘‘state of art’’ of such technique, even if the works relevant to trace metal determination in food matrices, in the meantime published [202–213], have substantially confirmed and again highlighted the evident and already described advantages of the technique. Among these are some interesting papers in which the performance of XRF for the determination of trace metals in food is compared with other spectroscopic methods [204,205,211].
2.5.3 Other techniques Finally, in this section, only one technique is pointed out, the neutron activation analysis (NAA), omitting other instrumental methods, certainly important, and sometimes still employed in routine analyses, but having too high LOD and LOQ (see, e.g., gravimetry or flame photometry), and then not addressed to trace metal concentration.
2.5.3.1 Neutron activation analysis. NAA is a sensitive analytical technique useful in performing both qualitative and quantitative multielement analysis of major, minor and trace elements in samples of scientific and technical interest. For many elements, this technique offers very high analytical sensitivities, i.e., sub-ppb concentration level. In addition, because of its accuracy and reliability, NAA is generally recognised, if possible, as the ‘‘Reference Method’’ of choice when new procedures are being developed or when other methods yield results that do not agree. In addition to the advantages previously reported (qualitative, quantitative, multicomponent analysis and very low LOD and LOQ), this technique shows to have certainly a fundamental advantage, i.e., the possibility of the analytical element determinations without destroying the sample, which is the fundamental condition for some kind of analyses in art and historical artifacts and, however, in all cases of small quantities of sample. Even if the method is ideally suited to multielement determination and small samples, the great disadvantage of this routine technique is the high capital cost and the necessity to utilize a nuclear reactor, so that analyses may take several days to complete. In the last few years several works regarding the employment
Metals
585
of NAA in food analysis have been published. The application field is relevant either to a lot of trace metals or to each kind of food matrix [214–227]. However, some papers are worth highlighting, as for example those relevant to the possibility of utilizing the concentration of several metals in fish to establish the environmental pollution degree of an ecosystem [217], to the possibility of using NAA for the determination of several metals in a lot of food kinds (cheese, egg, fish, fowl and meat) [222] and to the possibility of employing NAA as reference method in the U.S. Food and Drug Administration (FDA) Legislation [223]. Finally, in this section it must also be reported a very interesting paper regarding the possible simultaneous determination of trace metal in food samples by ion chromatography (IC), using a post-column derivatization and an UV-Vis detector [228].
3. METALS OF INTEREST Some comments on the analysis and occurrence in food of particular elements are given in this section. The choice of mercury and PGMs has been done owing to the high interest in recent years, the former, extremely toxic, present in large quantities in food, especially in fish matrices and the latter owing to increasing amounts of such metals in the environment and, consequently, in the food matrices because of the growing use of autocatalytic converters.
3.1 Mercury An estimated over 10,000 tons of mercury are released every year into the environment as a consequence of human activity [229,230]. The danger posed to human health by this form of contamination comes mainly from food and stems from the ability of this element to enter the natural alimentary chain, to accumulate in progressively larger quantities at each trophic stage and to reach highly toxic concentrations in the tissues of organisms that play a role in the human diet [231]. Concern over mercury contamination of the environment, and consequently of food, has promoted an intensive search for methods aimed at the determination of this metal, for example, inductively coupled plasma mass spectrometry (ICP-MS), gas chromatography (GC), NAA, nuclear magnetic resonance (NMR), electrothermal atomisation atomic absorption spectrometry (ETA-AAS), CV-AAS, cold vapour atomic fluorescence spectrometry (CV-AFS) and, not recently, also PSA. Considering also the sample preparation, very interesting were the works of Locatelli et al. [232,233], relevant to the critical comparison about the different procedures followed before the Hg determination by CV-AAS, especially regarding the eventual mercury loss. However, restricting the survey to the mercury determination in food matrices, it is important to highlight that mercury contamination may occur following different ways, so that mercury may be present also in refined beet sugar [234] or in fruit juices and beer [235].
586
Clinio Locatelli
For example, agricultural soils contain mercury levels in some cases also higher than 0.5 mg/g [236–239], and some edible plants, such as potatoes, mushrooms and carrots have been reported to take up mercury compounds at very high concentration levels [240–242]. Also fishes, especially those with high fat content, for example, swordfish and tuna, may show very high mercury content, resulting as dangerous for the human and/or animal diet. However, in order to give, if possible, the widest number of information, the discussion will be addressed to each food matrix of interest, highlighting only the more recent literature. In the case of foodstuff, several methods, employing different instrumental techniques, have been recently proposed. Grotti et al. [243] suggest the simultaneous determination of mercury, arsenic and selenium in foodstuff by chemical vapour generation inductively coupled plasma optical emission spectroscopy. ICP-MS is proposed as a powerful technique to determine not only mercury, but cadmium and arsenic too [244]. To optimize and validate the mercury determination in samples prepared with high-pressure asher or microwave digestion, Perring and Andrey [245] propose a critical comparison CV-AAS/ICP-MS technique. In the case of stripping voltammetry, the mercury determination gets into difficulties, especially in the sample preparation, that seems to be very time consuming [246]. Finally, Huang [247] suggests an interesting procedure employing reversedphase high-performance liquid chromatography, combined with on-line enrichment technique to quantify mercury, but also lead and cadmium in foodstuff at ng/L concentration level. Roughly subdividing the aquatic organism matrix kinds, the following discussion takes into account the mercury determination in fishes, mussels and clams. It is well known that mercury tends to accumulate in muscular tissues of high fat content. For this reason aquatic species, for example, tuna fish and swordfish, several times present in the human diet, may be the way, in the food chain, to transfer mercury to man [248]. The recent literature reports many papers addressed to the relation between mercury content in fish and its human consumption [249–256]. Determination of total and inorganic mercury in fish samples with on-line oxidation coupled to atomic fluorescence spectrometry is an interesting work regarding the mercury speciation in fish matrices [257]. Even if the determination of mercury concentration in fish has been amply reported in literature, considering either its toxicology [258], or its speciation and distribution [259–261], recently a very interesting work about the evaluation of reagent-less method for the determination of total mercury in aquatic life shows that reducing multiple treatment, i.e., drying, chemical digestion and/or oxidation steps, potentially sources of systematic, but also casual errors, it is possible to obtain an analytical concentration datum more precise and accurate [262]. Even if spectroscopic measurements are the most employed techniques in the mercury determination, recently, also electroanalytical methods, e.g., chronopotentiometric stripping analysis at gold film electrodes, are employed for the
Metals
587
determination of mercury in fishes and shrimps at ng/g, dry weight, concentration level [263]. Mussels and clams are constitutionally filtering organisms, but unlike zooplankton, they are not very mobile, justifying the heavy metal concentration in very limited spaces. The literature reports several works about the analytical procedure for the mercury determination in mussels and clams [80,264–272], even if, many times together with mercury, several other toxic metals are determined [78,273–279]. However, it is important also to highlight that mussels and clams may be useful as environmental pollution bio-monitors [280–282].
3.2 Platinum group metals The amount of heavy metals in the environment continuously increases and accumulates owing to the anthropogenic activities, of which vehicle emissions have attracted much interest and attention in recent years. The introduction and always compelling increasing use of autocatalytic converters containing PGMs has been the cause of the increasing amount of such metals in the environment that is parallel to the decrease of Pb(II) concentration. The use of autocatalytic converters, containing PGMs has resulted in a decrease of pollutants such as lead, carbon monoxide, nitrogen oxides and unburned hydrocarbons in exhaust gases from motor vehicles but, contemporaneously, it is the cause of a widespread distribution of fine particulate matter and dust originating from deterioration or abrasion of the bulk catalysts [283–285]. A considerable increase of Pt(II), Pd(II) and Rh(III) concentrations has consequently occurred in vegetation, soil surfaces and surface waters, especially in sites next to roadways with high traffic density, even if such concentrations are generally below 0.1 mg/L in liquid matrices (fresh and sea water) and below 50 mg/kg in solid matrices (soil, plant and particulate matter) [286,287]. Because of their toxicity [230,288–290] these elements can be dangerous to the health of the population, as a result of direct contact with the dust, by inhalation of fine particulate matter (aerodynamic diametero10 mm) and through food and water. In the last decade, some papers relevant to the determination of Pt(II), Pd(II) and Rh(III) in real samples, usually soil and air particulate matter, more rarely superficial water and foods, have been reported [291,292]. All these studies employed prevalently spectroscopic and voltammetric techniques. In the case of Pt(II), a very interesting work published by Desimoni et al. [293] is aimed at evaluating the capabilities of catalytic adsorptive stripping voltammetry in quantifying platinum at mg/kg level, or lower, under statistical control in some samples of food and beverage. Recently Bosch-Ojeda et al. [294] have proposed an automatic on-line FI-ETAAS (flow injection-electrothermal atomic absorption spectroscopy) method for the determination of trace amounts, using a chelating ion-exchange resin for the separation and pre-concentration of platinum from different food and beverages. In the spectroscopic field, ICP-MS was proposed to determine platinum concentration in food samples [295,296]. This instrumental technique allows to simultaneously determine several elements. Considering such a problem, an interesting work [297] shows that
588
Clinio Locatelli
also voltammetry is fit for multicomponent determination. However, in this case, interference problems may evidently occur (see Section 2.5.1.2). Some surveys show that such difficulties can be partially overcome and/or solved either employing standard addition method [298], or changing the supporting electrolyte, according to the reversibility of the electrodic process [299]. Pd(II) in food has been investigated only a few times. A flow injection (FI) system was used to develop an efficient on-line sorbent extraction preconcentration system for Pd(II) determination by graphite furnace AAS [300]. In the voltammetric field, the procedure proposed by Locatelli [297] allows the palladium determination in vegetable matrices and it is a good contribution to the possibility of carrying out multielement analysis, even in the presence of interferents. The literature relevant to Rh(III) determination in food samples is very scanty and recent, only regarding vegetable matrices. Brunetti et al. [301] have quantified the metal by catalytic adsorptive stripping voltammetry (CadSV) in lentils at sub mg/L levels. Its determination together with Pt(II) and Pd(II) is also proposed [297]. The suggested analytical procedure is appropriate to the sequential voltammetric determination of Pb(II), Pd(II), Pt(II) and Rh(III) in vegetable matrices using as supporting electrolyte 0.1 mol/L HCl [Pb(II)]; 0.1 mol/L HCl+1.8 104 mol/L dimethylglyoxime [Pd(II)]; 0.1 mol/L HCl+0.6 mmol/L formaldehyde+1.2 mmol/L hydrazine.
3.3 Miscellanea This section does not report the list of specific works for each metal in the different food matrices, considering also the very high number of metals and matrices of interest. For this reason the metal/matrix specific information can be drawn in the very wide reference section of this chapter. The choice to highlight and to privilege only two survey lines relevant to trace metal determination in food matrices (mercury and PGMs), is actually very important and of interest, confines the consideration and the information relevant to the remaining metals to the general discussion (see Section 2.5). In fact, a great variety of papers and books describe various traditional but also new methods of analysis in food addressed to a lot of elements. Evidently, being unable to discuss and/or to propose any studies concerned with the ranking of particular methods for each metal, here only three very interesting reviews are reported. The first one [83], regarding the electroanalytical techniques, reports accurately the studies carried out up to 2000. The second one [302], aimed at spectroscopic methods, provides an extensive summary of publication up to 2005. It reviews developments for the measurement of major, minor and trace elements in foods, beverages, whole diets and relates samples, such as food and herbal supplements. Finally, the third one [303], very general but undoubtedly exhaustive, describes the use and the developments of analytical techniques in food science up to 2001.
Metals
589
4. DIRECTIVE FOR TRACE METALS IN FOOD Even if the present topic may be beyond the more general discussion relevant to the determination of trace metals in food matrices, it is worth highlighting the relevance of rules addressed to fix the metal concentration limits in different foods. The problem is not simple to solve; the International Directives in force are continuously in progress: such specific legislation was initially applied to a strictly limited number of toxic elements, for example lead, cadmium, arsenic, and successively extended to an always increasing number of metals. It is important to highlight that the reference Tables relevant to the limit concentration levels are the result of crossed studies regarding chemical, biological, nutritional and medical surveys. As regards merely the chemical aspect, the rules have also followed, in the time, the performances of the instrumental techniques, which have allowed lowering considerably the metal concentrations to determine. In 2001, the European Community drew up a Directive binding on all E.U. Members. Such a Directive [304,305], together with the subsequent modifications (see e.g., that concerning food hygiene and health conditions for the production and placing on the market of products of animal origin intended for human consumption [306]) seems to be decidedly the more advanced point among the legislation today in force, especially taking into account the public health problems. The United States has also fixed the trace metal concentration limits in food, but each State of the American Union has the possibility to legislate and then to establish concentration limits for each metal and for each food matrix, so causing obvious confusion. However, the documents and reports published by Environmental Protection Agency (EPA) [307] and by U.S. FDA [308,309] aim to unify all the different rules, so to establish a common Directive. Several other Nations, for example Canada [310], propose its own rules. However, all food legislation is subject to continuing revision and, hence, each legislation detailed now is liable to be out of date in a short time. For this reason the Directives of the Nations should be unified. In this context, the work and the synthesis efforts carried out continuously by the World Health Organisation (WHO) of the United Nations [311] since the 1960s up to today are very important because they have the goal to obtain a unique and general Directive.
5. CONCLUSIONS AND FUTURE TRENDS This section highlights some important points. The International Directives (see Section 4) are continuously in progress, either increasing the number of metals to determine, or modifying their limits of detection and/or quantification in the different kinds of foods. Certainly, this is a positive occurrence, considering the biological implications of each metal, and especially, in most cases, their very high toxicity. However, this provides for the set up of suitable analytical
590
Clinio Locatelli
procedures, which must exclude, at a fixed confidence probability level, either casual or systematic errors. Such an aim is strictly linked to two parallel ways, the guidelines for future surveys in this research field: (1) (2)
typology of the food samples; instrumental techniques employed.
5.1 Typology of the food samples ‘‘Food’’ comprehends a great quantity of different matrices, and this entails the necessity to set up, for each metal, specific analytical procedures from sample dissolution to instrumental determination. Evidently it is impossible to propose an analytical procedure for each metal and for each kind of food. However, it is equally evident that this goal can be pursued, at least initially, classifying the foods in accordance with their typology, evidently linked to common chemical properties, and successively proposing, for each class, suitable analytical procedures for the determination of an always increasing number of metals.
5.2 Instrumental techniques employed The last comment regards the comparison among all the techniques employed for the metal determination in foods. The electroanalytical methods are very interesting and show to have several advantages. The most important is certainly relevant to the possibility of carrying out multicomponent analysis, also at very low concentration levels. Other techniques allow the simultaneous determination of several elements with comparable LOD and/or LOQ, but with instrumentation cost extremely higher, for example, spectroscopic instrumentation: ICP-AES with solid state (charge coupled device, CCD) detector or ICP-MS. Certainly, the employment of electroanalytical techniques for the metal determination in foods will be of fundamental importance in the next few years, since these methods allow coupling the advantages relevant to the multicomponent analysis and the very low instrumentation cost, previously reported, to the possibility of employing specific mercury-free sensors (see Section 2.5.1.4) with very high analytical sensitivity, even if, at least up to now, the set up of these sensors is a wide research field with many points under discussion to investigate and to explain.
REFERENCES 1 2 3 4 5 6
W.R. Wolf, Anal. Chem., 50 (1976) 190A. L. Noel, J.C. Leblanc and T. Guerin, Food Addit. Contam., 20(1) (2003) 44. J. Kottferova, B. Korenekova and M. Skalicka, Trace Elem. Electrolytes, 19 (2002) 91. M.T. Vidal, M.C. Pascual-Marti, A. Salvador and C. Llabata, Microchem. J., 72 (2002) 221. R.K. Sharma, M. Agrawal and F. Marshall, Ecotoxicol. Environ. Safe, 66 (2007) 258. D. De Souza, S.A.S. Machado and R.C. Pires, Talanta, 69 (2006) 1200.
Metals
7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
591
R. Duane Satzger, R.W. Kuennen and F.L. Fricke, J. Assoc. Off. Anal. Chem., 66 (1983) 985. S. Mannino, Analyst, 108 (1983) 1257. S. Mannino, Analyst, 107 (1982) 1466. R.J. Gajan, S.G. Capar, C.A. Subjoc and M. Sanders, J. Assoc. Off. Anal. Chem., 65 (1982) 970. S.G. Capar, R.J. Gajan, E. Madzsar, R.H. Albert, M. Sanders and J. Zyren, J. Assoc. Off. Anal. Chem., 65 (1982) 978. R.D. Satzger, C.S. Clow, E. Bonnin and F.D. Fricke, J. Assoc. Off. Anal. Chem., 65 (1982) 987. J.R. Preer, B.R. Stephens and C. Wilson Bland, J. Assoc. Off. Anal. Chem., 65 (1982) 1010. B. Krinitz and N. Tepedino, J. Assoc. Off. Anal. Chem., 64 (1981) 1014. S.K.C. Chang, E. Holm, J. Schwarz and P. Rayas-Duarte, Anal. Chem., 67 (1995) 127R. A.A. Farmer and A.M. Farmer, Sci. Total Environ., 257 (2000) 53. M. Aceto, O. Abollino, M.C. Bruzzoniti, E. Mentasti, C. Sarzanini and M. Malandrino, Food Addit. Contam., 19 (2002) 126. Z.K. Gaspic, T. Zvonaric, N. Vrgoc, N. Odzakand and A. Baric, Water Res., 36 (2002) 5023. R. Casanas Rivero, P. Suarez Hernandez, E.M. Rodriguez Rodriguez, J. Darias Martin and C. Diaz Romero, Food Chem., 83 (2003) 247. M. Soylak, S. Saracoglu, M. Tuzen and D. Mendil, Food Chem., 92 (2005) 649. L. Cocchi, L. Vescovi, L.E. Petrini and O. Petrini, Food Chem., 98 (2006) 277. J. Alonso, M.A. Garcia, M. Perez-Lopez and M.J. Melgar, Arch. Environ. Contam. Toxicol., 44 (2003) 180. S. Clemens, Biochimie, 88 (2006) 1707. E. Prichard, G.M. MacKay and J. Points, Trace Analysis: A Structured Approach to Obtaining Reliable Results, Laboratory of the Government Chemist, Royal Society of Chemistry, Cambridge, UK, 1996. M. Blanc, Mol. Nutr. Food Res., 50 (2006) 473. L. Jorhem, J. Engman, B. Sundstrom and A. Nillson, Accredit. Qual. Assur., 10(12) (2006) 647. T.B. Whitaker and A.S. Johansson, J. Food Prot., 68 (2005) 1306. R.Y. Wong, C.F. Clark and N.S. Ferguson, Int. J. Environ. Health Res., 14 (2004) 201. B.W. Woodget and D. Cooper, In: N.B. Chapman (Ed.), Samples and Standards, Wiley (On behalf of ACOL), London, Chichester, UK, 1987, pp. 60–91. L. Zheng and D.W. Sun, Trends Food Sci. Technol., 17 (2006) 16. R. Chakraborty, A.K. Saha and P. Bhattacharya, Sep. Purif. Technol., 49 (2006) 258. N. Benkerroum, A. Daoudi, T. Hamraoul, H. Ghalfi, C. Thiry, M. Duroy, P. Evrart, D. Roblain and P. Thonart, J. Appl. Microbiol., 98 (2005) 56. S. Khalloufi, J.L. Robert and C. Ratti, J. Food Process Eng., 28 (2005) 107. E. Wolff and H. Gibert, J. Food Eng., 8 (1988) 91. G.E. Baiulescu, P. Dumitrescu and P.Gh. Zugravescu. In: Ellis Horwood (Ed.), Sampling, Chichester, UK, 1991, pp. 61–79, Chapter 3. E.A. Zakharova, V.I. Deryabina and G.B. Slepchenko, J. Anal. Chem., 60 (2005) 503. N.T. Crosby, Proc. Inst. Food Sci. Technol. UK, 10 (1977) 65. J.C. Van Loon, Selected Methods of Trace Metal Analysis: Biological and Environmental Analysis, Wiley, New York, 1985. T.T. Gorsuch, The Destruction of Organic Matter, Pergamon Press, Oxford, UK, 1970. M. Yaman and N. Cokol, Atom. Spectrosc., 25 (2004) 185. A. Moeller, R.F. Ambrose and S.S. Que Hee, Food Addit. Contam., 18 (2001) 19. C. Blake and B. Bourqui, Atom. Spectrosc., 19 (1998) 207. P. Zbinden and D. Andrey, Atom. Spectrosc., 19 (1998) 214. C. Locatelli and G. Torsi, Ann. Chim. (Rome), 91 (2001) 65. W. Horwitz (Ed.), Official Methods of Analysis of the Association of Official Analytical Chemists, 12th ed., Association of Official Analytical Chemists, Washington, DC, 1975. L. Jorhem, J. AOAC Int., 83 (2000) 1204. P. Mader, J. Szakova and E. Curdova, Talanta, 43 (1996) 521. J.R. Bellanger, J. AOAC Int., 78 (1995) 477. P. Fecher and G. Ruhnke, Anal. Bioanal. Chem., 373 (2002) 787.
592
50 51 52 53 54 55 56 57 58
59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85
86 87 88 89
Clinio Locatelli
J.M. Anzano and M. Ruiz-Gil, Atom. Spectrosc., 26 (2005) 28. A.A. Momen, G.A. Zachariadis, A.N. Anthemidis and J.A. Stratis, J. AOAC Int., 88 (2005) 1797. H. Zeng-Yei, Bioresour. Technol., 95 (2004) 53. J.M. Jurado, A. Alcazar, F. Pablos, M.J. Martin and A.G. Gonzalez, Talanta, 63 (2004) 297. M. Yaman and S. Gucer, Ann. Chim. (Rome), 88 (1998) 555. K. Bachmann, Crit. Rev. Anal. Chem., 12 (1981) 1. A.K. Malik, V. Kaur and N. Verma, Talanta, 68 (2006) 842. P.C. Aleixo, D. Santos Junior, A.C. Tomazelli, I.A. Rufini, H. Berndt and F.J. Krug, Anal. Chim. Acta, 512 (2004) 329. J.L. Ezzell. In: Z. Mester and R. Sturgeon (Eds.), Comprehensive Analytical Chemistry, Volume XLI, Sample Preparation for Trace Element Analysis, Elsevier, Amsterdam, Netherlands, 2003, pp. 343–352, Chapter 11. E.C. Santiago and F.B.B. Bello, Food Addit. Contam., 20 (2003) 535. D.E. Robertson, In: M. Zeif and R. Speights (Eds.), Contamination Problems in Trace Element Analysis and Ultra-Purification, Ultra-Purity Methods and Techniques, Dekker Publications, New York, 1972. R. Massee, F.J.M.J. Maessen and J.J.M. De Goeij, Anal. Chim. Acta, 127 (1981) 181. J. Gallardo, S. Alegret and M. Del Valle, Talanta, 66 (2005) 1303. E. Sucman and J. Bednar, Can. J. Anal. Sci. Spectros., 47 (2002) 66. M.K. Malde, K. Bjorvatn and K. Julshamn, Food Chem., 73 (2001) 373. J.C.B. Fernandes, G. De Oliveira Neto, J.J.R. Rohwedder and L.T. Kubota, J. Braz. Chem. Soc., 11 (2000) 349. K. Buellens, D. Kirsanov, J. Irudayaraj, A. Rudnitskaya, A. Legin, B.M. Nicolai and J. Lammertyn, Sensor Actuators B-Chem., 116 (2006) 107. M. Mazloum Ardakani, M. Khayat Kashani, M. Salavati-Niasari and A.A. Ensafi, Sensor Actuators B-Chem., 107 (2005) 438. H. Karami, M. Fazlollah Mousavi and M. Shamsipur, Talanta, 60 (2003) 775. M.B. Gholivand and F. Sharifpour, Talanta, 60 (2003) 707. E. Pretsch, Trends Analyt. Chem., 26 (2007) 46. L.D. Mello and L.T. Kubota, Food Chem., 77 (2002) 237. J. Koryta, Anal. Chim. Acta, 206 (1988) 1. C. Locatelli, J. Sci. Food Agric., 87 (2007) 305. C. Locatelli, Anal. Bioanal. Chem., 381 (2005) 1073. C. Locatelli, Electroanalysis, 16 (2004) 1478. C. Locatelli and G. Torsi, Microchem. J., 78 (2004) 175. C. Locatelli and G. Torsi, Microchem. J., 75 (2003) 233. C. Locatelli, G. Torsi and F. Rossi, Fresenius Environ. Bull., 9 (2000) 813. C. Locatelli, Food Addit. Contam., 17(9) (2000) 769. C. Locatelli and F. Fagioli, Ann. Chim. (Rome), 87 (1997) 535. F. Vydra, K. Stulik and E. Julakova, Electrochemical Stripping Analysis, Ellis Horwood Limited Publisher, Chichester, UK, 1976. J. Wang, Stripping Analysis: Principles, Instrumentation and Applications, VCH Publishers, Deerfield Beach, 1985. Kh.Z. Brainina, N.A. Malakhova and N. Yu. Stojko, Fresenius J. Anal. Chem., 368 (2000) 307. A.J. Bard and L.R. Faulkner, Electrochemical Methods: Fundamentals and Applications, Wiley, New York, USA, 1980. Z. Galus. In: R.A. Chalmers and W.A.J. Bryce (Trans. Eds.), Fundamentals of Electrochemical Analysis, 2nd revised version, Ellis Horwood, Polish Scientific Publishers PWN, Warsaw, Poland, 1994. M. Intawongse and J.R. Dean, Food Addit. Contam., 23 (2006) 36. F. Queirolo, S. Stegen, M. Restovic, M. Paz, P. Ostapczuk, M.J. Schwuger and L. Munoz, Sci. Total Environ., 255 (2000) 75. S. Giroussi, A. Voulgaropoulos, A.K. Ayiannidis, J. Golimowski and M. Janicki, Sci. Total Environ., 176 (1995) 135. R. Inam and C. Toprak, Fresenius Environ. Bull., 14 (2005) 489.
Metals
593
90 I. De Gregori, D. Delgado, H. Pinochet, N. Gras, M. Thieck, L. Munoz, C. Bruhn and G. Navarrete, Sci. Total Environ., 111 (1992) 201. 91 M.A. Baldo and S. Daniele, Anal. Lett., 37 (2004) 995. 92 Kh.Z. Brainina, N. Yu. Stozhko, G.M. Belysheva, O.V. Inzhevatova, L.I. Kolyadina, C. Cremisini and M. Galletti, Anal. Chim. Acta, 514 (2004) 227. 93 D. Sancho, L. Deban, R. Pardo and D. Valladolid, J. Sci. Food Agric., 85 (2005) 1021. 94 P.L. Buldini, S. Cavalli and J.L. Sharma, J. Agric. Food Chem., 47 (1999) 1993. 95 I. Navarro-Blasco and J.I. Alvarez-Galindo, Food Addit. Contam., 22(8) (2005) 726. 96 R. Inam and G. Somer, Food Chem., 69 (2000) 345. 97 L. Qiong, W. Lirong, X. Danli and L. Guanghan, Food Chem., 97 (2006) 176. 98 Y.-H. Li, H.-Q. Xie, F.-Q. Zhou and H.-S. Guo, Electroanalysis, 18 (2006) 976. 99 Y.-H. Li, H. Long and F.-Q. Zhou, Anal. Chim. Acta, 554 (2005) 86. 100 A. Cavicchioli, M.A. La-Scalea and I.G.R. Gutz, Electroanalysis, 16 (2004) 697. 101 D. Jagner and A. Graneli, Anal. Chim. Acta, 83 (1976) 19. 102 A. Fogg and J. Wang, Pure Appl. Chem., 71 (1999) 891. 103 S.B. Adeloju, E. Sahara and D. Jagner, Anal. Lett., 29 (1996) 283. 104 S.V. Psaroudakis and C.E. Efstathiou, Analyst, 114 (1989) 25. 105 J. Obiols, R. Devesa and A. Malet, Analyst, 113 (1988) 1529. 106 S.V. Psaroudakis and C.E. Efstathiou, Analyst, 112 (1987) 1587. 107 E. Munoz and S. Palmero, Food Chem., 94 (2006) 478. 108 G. Dugo, L. La Pera, V. Lo Turco, R. Matarese Palmieri and M. Saitta, Food Chem., 93 (2005) 703. 109 G. Dugo, L. La Pera, G.L. La Torre and D. Giuffrida, Food Chem., 87 (2004) 639. 110 E. Munoz and S. Palmero, Food Control, 15 (2004) 635. 111 O. Mikkelsen, C. Nordhei, S.M. Skogvold and K.H. Schroder, Anal. Lett., 37 (2004) 2925. 112 L. La Pera, M. Saitta, G. Di Bella and G. Dugo, J. Agric. Food Chem., 51 (2003) 1125. 113 F. Salvo, L. La Pera, G. Di Bella, M. Nicotina and G. Dugo, J. Agric. Food Chem., 51 (2003) 1090. 114 F. Lo Coco, L. Ceccon, L. Ciraolo and V. Novelli, Food Control, 14 (2003) 55. 115 B.M. Kalicanin, N.J. Marjanovic and Z.J. Suturovic, J. Serb. Shem. Soc., 67 (2002) 213. 116 A.L. Da Rocha Nobre and L.H. Mazo, Quim. Nova, 20 (1997) 412. 117 S. Siegen, F. Queirolo, C. Marin, F. Vinagre, P. Ostapczuk and P. Valenta, Bol. Soc. Chil. Quim., 41 (1996) 137. 118 G. Dugo, L. La Pera, A. Bruzzese, T.M. Pellicano` and V. Lo Turco, Food Control, 17 (2006) 146. 119 L. La Pera, R. Lo Curto, G. Di Bella and G. Dugo, J. Agric. Food Chem., 53 (2005) 5084. 120 G. Dugo, L. La Pera, V. Lo Turco, D. Giuffrida and S. Restuccia, Food Addit. Contam., 21 (2004) 649. 121 R. Ratana-ohpas, P. Kanatharana, W. Ratana-ohpas and W. Kongsawasdi, Anal. Chim. Acta, 333 (1996) 115. 122 S. Mannino and J. Wang, Electroanalysis, 4 (1992) 835. 123 J. Wang, U. Anik Kirgoz, J.-W. Mo, J. Lu, A. Nasser Kawde and A. Muck, Electrochem. Commun., 3 (2001) 203. 124 A. Walcarius, Anal. Chim. Acta, 384 (1999) 1. 125 C. Agra-Gutierrez, J.L. Hardcastle, J.C. Ball and R.G. Compton, Analyst, 124 (1999) 1053. 126 K. Kalcher, J.-M. Kauffmann, J. Wang, I. Svancara, K. Vytras, C. Neuhold and Z. Yang, Electroanalysis, 7 (1995) 5. 127 L. Gorton, Electroanalysis, 7 (1995) 23. 128 A. Taylor, S. Branch, D. Halls, M. Patriarca and M. White, J. Anal. At. Spectrom., 18 (2003) 385. 129 F. Cubadda, J. AOAC Int., 87 (2004) 173. 130 B. Welz and M. Sperling, Atomic Absorption Spectrometry, 3rd ed., Wiley, Weinheim, Federal Republic of Germany, 1999. 131 D. Bellido-Milla, J.M. Moreno-Perez and M.P. Hernandez-Artiga, Spectrochim. Acta B, 55 (2000) 855. 132 A. Demirbas, Food Chem., 67 (1999) 27. 133 W.H. Evans, J.I. Read and B.E. Lucas, Analyst, 103 (1978) 580. 134 V. Azevedo Lemos, E. Moreira Gama and A. Da Silva Lima, Microchim. Acta, 153 (2006) 179. 135 A. Verdaguer, B. Gonzalez and J. Barcelo´, Afinidad, 62 (2005) 525.
594
136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177
Clinio Locatelli
M. Tuzen, Food Chem., 80 (2003) 119. M.S. Bratakos, E.S. Lazos and S.M. Bratakos, Sci. Total Environ., 290 (2002) 47. E. Lendinez, M.L. Lorenzo, C. Cabrera and M.C. Lopez, Sci. Total Environ., 278 (2001) 183. M. He, J. Yang and Y. Cha, Toxicol. Environ. Chem., 76 (2000) 137. P. Gallo, L. Serpe and G. Brambilla, J. AOAC Int., 80 (1997) 956. R. Tahvonen and J. Kumpulainen, J. Anal. At. Spectrom., 9 (1994) 1427. J.F. Vazquez-Gonzalez, P. Bermejo-Barrera and F. Bermejo-Martinez, Anal. Chim. Acta, 219 (1989) 79. M. das G. A. Korn, J.B. de Andrade, D.s. de Jesus, V.A. Lemos, M.L.S.F. Bandeira, W.N.L. dos Santos, M.A. Bazerra, F.A.C. Amorim, A.S. Souza and S.L.C. Ferreira, Talanta, 69 (2006) 16. K.S. Ferreira, J.C. Gomes and J.B.P. Chaves, Food Chem., 92 (2005) 29. D. Mandil, O. Dogan Uluozlu, M. Tuzen, E. Hasdemir and H. Sari, Food Chem., 91 (2005) 463. M.C. Yebra-Biurrun, S. Cancela-Perez and A. Moreno-Cid-Barinaga, Anal. Chim. Acta, 533 (2005) 51. M.C. Yebra-Biurrun, A. Moreno-Cid and S. Cancela-Perez, Talanta, 66 (2005) 691. M.C. Yebra, A. Moreno-Cid, R. Cespon and S. Cancela, Talanta, 62 (2004) 403. R.M. Garcia-Rey, R. Quiles-Zafra and M.D. Luque de Castro, Anal. Bioanal. Chem., 377(2) (2003) 316. R. Farre`, M.J. Lagarda and R. Montoro, J. Assoc. Off. Anal. Chem., 69 (1986) 876. R. Yukui, Z. Hongxing, G. Jing, H. Kunlun, Z. Benzhong and L. Yunbo, Agro Food Ind. Hi-Tech., 17 (2006) 35. A. Detcheva and K.H. Grobecker, Spectrochim. Acta B, 61 (2006) 454. R.G.O. Araujo, F. de S. Dias, S.M. Macedo, W.N.L. dos Santos and S.L.C. Ferreira, Food Chem., 101 (2007) 397. M. Yu Burylin, Z.A. Temerdashev and S. Yu Burylin, J. Anal. Chem., 63 (2006) 37. Md.N. Amin, S. Kaneco, T. Suzuki and K. Ohta, Int. J. Environ. Anal. Chem., 83 (2003) 1035. S. Chen, J. Anal. Chem., 60 (2005) 254. C. Shizhong, L. Dengbo and X. Qunying, Can. J. Anal. Sci. Spectrosc., 49 (2004) 290. P.-C. Li and S.-J. Jiang, Anal. Chim. Acta, 495 (2003) 143. F.D. Santos, A. Barbosa, F. Tomazelli, J.N. Krug and M. Arruda, Anal. Bioanal. Chem., 373 (2002) 183. I. Karadjova, S. Girousi, E. Iliadou and I. Stratis, Microchim. Acta, 134 (2000) 185. P. Vinas, M. Pardo-Martinez and M. Hernandez-Cordoba, J. Anal. At. Spectrom., 14 (1999) 1215. A. Carlosena, M. Gallego and M. Valcarcel, J. Anal. At. Spectrom., 12 (1997) 479. D.J. Butcher, R.L. Irwin, J. Takahashi, G. Su, G.-T. Wei and R.G. Michel, Appl. Spectrosc., 44 (1990) 1521. F. Fagioli, S. Landi, C. Locatelli, F. Righini, R. Settimo and R. Magarini, J. Anal. At. Spectrom., 5 (1990) 519. N.J. Miller-Ihli, Spectrochim. Acta B, 44 (1989) 1221. F. Fagioli and S. Landi, Anal. Lett., 16 (1983) 1435. S.C. Hight and J. Cheng, Food Chem., 91 (2005) 557. M. Plessi, D. Bertelli and A. Monzani, J. Food Compost. Anal., 14 (2001) 461. N. Ybanez, M.L. Cervera and R. Montoro, Anal. Chim. Acta, 258 (1992) 61. T.-M. Hsiung and C.W. Huang, J. Agric. Food Chem., 54 (2006) 2470. O. Muniz-Naveiro, R. Dominguez-Gonzalez, A. Bermejo-Barrera, J.A. Cocho, J.M. Fraga and P. Bermejo-Barrera, Anal. Bioanal. Chem., 381 (2005) 1145. I.R. Miksa, C.L. Buckley, N.P. Carpenter and R.H. Poppenga, J. Vet. Diagn. Invest., 17 (2005) 331. R. Font, D. Velez, M. Del Rio-Celestino, A. De Haro-Bailon and R. Montoro, Microchim. Acta, 151 (2005) 231. M. Korenovska, Chem. Pap., 57 (2003) 155. C.D. Freschi, G.P.G. Freschi, J.A. Gomes Neto, J.A. Nobrega and P.V. Oliveira, Spectrochim. Acta B, 60 (2005) 759. A. Taylor, S. Branch, D. Halls, M. Patriarca and M. White, J. Anal. At. Spectrom., 20 (2005) 323. K.D. CafferKy, D.D. Richardson and J.A. Caruso, Spectroscopy, 21 (2006) 18.
Metals
178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220
595
S. Nookabkaew, N. Rangkadilok and J. Satayavivad, J. Agric. Food Chem., 54 (2006) 6939. S.-H. Nam, J. Cheng, W.R. Mindak and S.G. Capar, Bull. Kor. Chem. Soc., 27 (2006) 903. K.C. Chan, Y.C. Yip, H.S. Chu and W.C. Sham, J. AOAC Int., 89(2) (2006) 469. Y. Wang, L. Liang, J. Shi and G. Jiang, Environ. Int., 31 (2005) 1103. N.L. Dufailly, V. Lemahieu, C. Vastel and T. Guerin, J. AOAC Int., 88 (2005) 1811. D. Hammer, M. Nicolas and D. Andrey, Atom. Spectrosc., 26 (2005) 203. M. Bettinelli, S. Spezia, C. Baffi, G.M. Beone, R. Rocchetta and A. Nassisi, Atom. Spectrosc., 26 (2005) 41. J. Falandysz, K. Szymczyk-Kobrzynska, A. Brzostowski, K. Zalewski and A. Zasadowski, Food Addit. Contam., 22 (2005) 141. F. Cubadda and A. Raggi, Microchem. J., 79 (2005) 91. F. Cubadda, A. Raggi and E. Marconi, Microchem. J., 79 (2005) 97. M. Ihnat, J. AOAC Int., 88 (2005) 341. H. Oshima, E. Ueno, I. Saito and H. Matsumoto, J. Food Hyg. Soc. Jpn, 45 (2004) 270. E. Vassileva and C.R. Que´tel, Anal. Chim. Acta, 519 (2004) 79. J. Entwisle, Am. Lab., 36 (2004) 11. E. Skrzydlewska, M. Balcerzak and F. Vanhaecke, Anal. Chim. Acta, 479 (2003) 191. L.G. Melnyk, J.N. Morgan, R. Fernando, E.D. Pellizzari and O. Akinbo, J. AOAC Int., 86 (2003) 439. F.J. Sanchez Lopez, M.D. Gil Garcia, N.P. Sanchez Morito and J.L. Martinez Vidal, Ecotoxicol. Environ. Safe, 54 (2003) 223. R.A. Schoof, L.J. Yost, J. Eickhoff, E.A. Crecelius, D.W. Cragin, D.M. Meacher and D.B. Menzel, Food Chem. Toxicol., 37 (1999) 839. M.D. Ioannidou, G.A. Zachariadis, A.N. Anthemidis and J.A. Stratis, Talanta, 65 (2005) 92. D.H. Sun, J.K. Waters and T.P. Mawhinney, J. AOAC Int., 83 (2000) 1218. M. Sadiq and I. Alam, J. Environ. Sci. Health A, 26 (1991) 607. E. Paredes, S.E. Maestre, S. Prats and J.L. Todolı`, Anal. Chem., 78 (2006) 6774. G.F. Kirkbright and M. Sargent, Atomic Absorption and Fluorescence Spectroscopy, Academic Press, London, UK, 1974. R.F. Browner, Analyst, 99 (1974) 617. H. D’souza Sunil, G. Menezes, S.C. Clark and V. Thuppil, Toxicol. Ind. Health, 22 (2006) 249. L. Perring, D. Andrey, M. Basic-Dvorzak and D. Hammer, J. Food Compost. Anal., 18 (2005) 655. C. Blake, Food Sci. Technol. Int., 18 (2004) 25. A. Jastrzebska, B. Brudka, T. Szymanski and E. Sziyk, Food Chem., 83 (2003) 463. P. Kump, M. Necemer and J. Snajder, Spectrochim. Acta B, 51 (1996) 499. E. Cernichiari, T.Y. Toribara, L. Liang, D.O. Marsh, M.W. Berlin, G.J. Myers, C. Cox, C.F. Shamlaye, O. Choisy, P. Davidson and T.W. Clarkson, Neurotoxicology, 16 (1995) 613. J. Omote, H. Kohno and K. Toda, Anal. Chim. Acta, 307 (1995) 117. K.K. Nielson, A.W. Mahoney, L.S. Williams and V.C. Rogers, J. Agric. Food Chem., 35 (1991) 887. A.H. Khan, S.A. Tarefdar, M. Ali, S.K. Biswas, S. Akhter, D.K. Saha, A. Islam, M. Billah, D.A. Hadi and F.B.A. Maroof, J. Radioanal. Nucl. Chem., 134 (1989) 367. K.K. Nielson, A.W. Mahoney and V.C. Rogers, J. Agric. Food Chem., 36 (1988) 1211. N.S. Saleh and K.A. Al-Saleh, Appl. Phys. Commun., 6 (1986) 195. K.K. Nielson, V.C. Rogers and A.W. Mahoney, Adv. X-ray Anal., 29 (1986) 551. M.B. Alamin, A.A. Mhapes, A.M. Bejey, A. Sadek, R.H. Atweer, K. Dubali and D.M. Saad, J. Radioanal. Nucl. Chem., 271 (2007) 247. M.B. Alamin, A.M. Bejey, J. Kucera and J. Mizera, J. Radioanal. Nucl. Chem., 270 (2006) 143. S.D. Kulkarni, R. Acharya, A.G.C. Nair, N.S. Rajurkar and A.V.R. Reddy, Food Chem., 95 (2006) 699. A.N. Garg and V.V.S. Ramakrishna, Toxicol. Environ. Chem., 88 (2006) 125. R. Jayasekera and M.C. Freitas, Biol. Trace Elem. Res., 103 (2005) 83. C.S. Sastri, V. Iyengar, S. Demirel-Gulen, M. Heck, P. Hoffmann, H.M. Ortner, G. Blondiaux, Y. Tessier, T. Sauvage and H. Petri, J. Radioanal. Nucl. Chem., 259 (2004) 515. S. Ribeiro Guevara, D. Bubach, P. Vigliano, G. Lippolt and M. Arribere, Biol. Trace Elem. Res., 102 (2004) 245.
596
221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240
241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261
Clinio Locatelli
S. Waheed, J.H. Zaidi and S. Ahmad, J. Radioanal. Nucl. Chem., 258 (2003) 73. L. Zikovsky and K. Soliman, J. Radioanal. Nucl. Chem., 251 (2002) 507. P. Mackill, J. Radioanal. Nucl. Chem., 249 (2001) 29. Y. Miyamoto, A. Kajikawa, J.H. Zaidi, T. Nakanishi and K. Sakamoto, J. Radioanal. Nucl. Chem., 243 (2000) 747. L. Gambelli, P. Belloni, G. Ingrao, L. Pizzoferrato and G.P. Santaroni, J. Food Compost. Anal., 12 (1999) 27. D.I.T. Favaro, M.L.T. Hui, S.M.F. Cozzolino, V.A. Maihara, M.J.A. Armelin, M.B.A. Vasconcellos, L.K. Yuyama, G.T. Boaventura and V.L. Tramonte, J. Trace Elem. Med. Bio., 11 (1997) 129. Y.S. Chung, Y.J. Chung, K.H. Cho and J.H. Lee, J. Radioanal. Nucl. Chem., 215 (1997) 129. M. Fredrikson, N.G. Carlsson, A. Almgren and A.S. Sandberg, J. Agric. Food Chem., 50 (2002) 59. R.D. Wilken and H. Hintelmann, In: J.A.C. Broekaert, S. Gucer and F. Adams (Eds.), Metal Speciation in the Environment, Springer-Verlag, Berlin, 1990, pp. 339–359. E. Merian, Metals and Their Compounds in the Environment — Occurrence, Analysis and Biological Relevance, VCH Publishers, Weinheim, Federal Republic of Germany, 1991. D. Purves, Trace Element Contamination of the Environment, Elsevier, Amsterdam, Netherlands, 1985. S. Landi, F. Fagioli and C. Locatelli, J. AOAC Int., 75 (1992) 1023. S. Landi, F. Fagioli, C. Locatelli and R. Vecchietti, Analyst, 115 (1990) 173. D. Sancho, L. Deban, F. Barbosa, R. Pardo and M. Vega, Food Chem., 74 (2001) 527. M. Rievaj, S. Mesaros, A. Brunova and D. Bustin, Chem. Pap., 51 (1997) 11. A. Bernaus, X. Gaona, D. Van Ree and M. Valiente, Anal. Chim. Acta, 565 (2006) 73. L. Zhang and M.H. Wong, Environ. Int., 33 (2007) 108. X. Feng, G. Li and G. Qiu, Sci. Total Environ., 368 (2006) 47. A.V. Gorbunov, M.V. Frontasyeva, A.A. Kistanov, S.M. Lyapunov, O.I. Okina and A.B. Ramadan, J. Environ. Sci. Heal. B, 38 (2003) 181. K. May, K. Reisinger, B. Torres, M. Stoeppler, Fresenius Z. Anal. Chem., 320 (1985/1987) 646; Proceedings International Conference Heavy Metals in the Environment, Athens, pp. 513–515; CEP Consultants Ltd, Edinburgh, Toxicol. Environ. Chem. 13 (153). J.K.C. Yoong, New Eng. J. Med., 354 (2006) 3. J.P. Frodello, M. Romeo and D. Viale, Environ. Pollut., 108 (2000) 447. M. Grotti, C. Lagomarsino and E. Magi, Ann. Chim. (Rome), 96 (2006) 751. L. Noel, V. Dufailly, N. Lemahieeu, C. Vastel and T. Guerin, J. AOAC Int., 88 (2005) 1811. L. Perring and D. Andrey, Atom. Spectrosc., 22 (2001) 371. V.N. Batalova, E.A. Zakharova, G.B. Slepchenko and M.V. Malygina, J. Anal. Chem., 59 (2004) 468. Z. Huang, G. Yang, Q. Hu and J. Yin, Anal. Sci., 19 (2003) 255. T. Endo, Y. Hotta, K. Haraguchi and M. Sakata, Environ. Sci. Technol., 37 (2003) 2681. J. Kojadinovic, M. Potier, M. Le Corre, R.P. Cosson and P. Bustamante, Sci. Total Environ., 366 (2006) 688. J. Burger and M. Gochfeld, Sci. Total Environ., 367 (2006) 1010. J.G. Wiener, B.C. Knights, M.B. Sandheinrich, J.D. Jeremiason, M.E. Brigham, D.R. Engstrom, L.G. Woodruff, W.F. Cannon and S.J. Balogh, Environ. Sci. Technol., 40 (2006) 6261. P. Krystek and R. Ritsema, Anal. Bioanal. Chem., 381 (2005) 354. T. Endo, K. Haraguchi, Y. Hotta, Y. Hisamichi, S. Lavery, M.L. Dalebout and C.S. Baker, Environ. Sci. Technol., 39 (2005) 5703. N. Cardellicchio, A. Di Leo, S. Giandomenico and S. Santoro, Ann. Chim. (Rome), 96 (2006) 159. E. Has-Schon, I. Bogut and I. Strelec, Arch. Environ. Contam. Toxicol., 50 (2006) 545. M.M. Storelli, R. Giacominelli-Stuffler and G.O. Marcotrigiano, J. Food Protect., 69 (2006) 1402. L.J. Shao, W.E. Gan and Q.D. Su, Anal. Chim. Acta, 562 (2006) 128. T.W. Clarkson and E. Magos, Crit. Rev. Toxicol., 36 (2006) 609. S.A. Peterson, J. Van Sickle, A.T. Herlihy and R.M. Hughes, Environ. Sci. Technol., 41 (2007) 58. M. Valega, S. Abreu, P. Pato, L. Rocha, A.R. Gomes, M.E. Pereira and A.C. Duarte, Water Air Soil Pollut., 174 (2006) 223. M.-B. Regine, D. Gilles, D. Yannick and B. Alain, Sci. Total Environ., 368 (2006) 262.
Metals
597
262 S. Haynes, R.D. Gragg, E. Johnson, L. Robinson and C.E. Orazio, Water Air Soil Pollut., 172 (2006) 359. 263 M.A. Augelli, R.A.A. Munoz, E.M. Richter, M.I. Cantagallo and L. Angnes, Food Chem., 101 (2007) 579. 264 A.J. Gutierrez, G. Lozano, T. Gonzalez, J.I. Reguera and A. Hardisson, J. Food Prot., 69 (2006) 2237. 265 A. Colaco, P. Bustamante, Y. Fouquet, P.M. Sarradin and R. Serrao-Santos, Chemosphere, 65 (2006) 2260. 266 H.A. Kehrig, M. Costa, I. Moreira and O. Malm, J. Braz. Chem. Soc., 17 (2006) 1409. 267 F.Z. Bouthir, S. Benbrahim, A. Chafik, S. Souabi and M. Sifeddine, J. Mar. Environ. Eng., 8 (2006) 215. 268 M. Kan, S.N. Willie, C. Scriver and R.E. Sturgeon, Talanta, 68 (2006) 1259. 269 J.L. Gomez-Ariza, F. Lorenzo and T. Garcia-Barrera, Chemosphere, 61 (2005) 1401. 270 C. Garron, F. Gagne`, W. Ernst, J. Julien, M. Bernier and C. Caldwell, Water Qual. Res. J. Can., 40 (2005) 1. 271 I. Ipolyi, P. Massanisso, S. Sposato, P. Fodor and R. Morabito, Anal. Chim. Acta, 505 (2004) 145. 272 C. Locatelli and G. Torsi, Environ. Monit. Assess., 75 (2002) 281. 273 D. Shi and W.X. Wang, Environ. Sci. Technol., 39 (2005) 9363. 274 Y. Saavedra, A. Gonzalez, P. Fernandez and J. Blanco, Sci. Total Environ., 318 (2004) 115. 275 M. Kim, Food Addit. Contam., 21 (2004) 763. 276 P. Szefer, B.S. Kim, C.K. Kim, E.H. Kim and C.B. Lee, Environ. Pollut., 129 (2004) 209. 277 G. Bhavani and S.D. Sharief, Ecol. Environ. Conserv., 9 (2003) 285. 278 R. Amodio-Cocchieri, S. Amoroso, A. Arnese, T. Cirillo, P. Montuori and M. Triassi, Bull. Environ. Contam. Toxicol., 71 (2003) 551. 279 D. Juresa and M. Blanusa, Food Addit. Contam., 20 (2003) 241. 280 Z. Kljakovic-Gaspic, N. Odzak, I. Ujevic, T. Zvonaric, M. Horvat and A. Baric, Sci. Total Environ., 368 (2006) 199. 281 C. Locatelli, D. Fabbri and G. Torsi, Ann. Chim. (Rome), 91 (2001) 425. 282 C. Locatelli, J. Phys. IV France, 107 (2003) 785. 283 K. Pyrzynska, J. Environ. Monit., 2 (2000) 99N. 284 J. Sternbeck, A. Sjodin and K. Andreasson, Atmos. Environ., 36 (2002) 4735. 285 B. Gomez, M.A. Palacios, M. Gomez, J.L. Sanchez, G. Morrison, S. Rauch, C. McLeod, R. Ma, S. Caroli, S. Alimonti, F. Petrucci, B. Bocca, P. Schramel, M. Zischka, C. Petterson and U. Wass, Sci. Total Environ., 299 (2002) 1. 286 T. Hess, B. Wenclawiak, S. Lustig, P. Schramel, M. Schwarzer, M. Schuster, D. Verstraete, R. Dams and E. Helmers, Environ. Sci. Pollut. Res., 5 (1998) 105. 287 M.A. Palacios, M. Gomez, M. Moldovan and B. Gomez, Microchem. J., 67 (2000) 105. 288 M. Moldovan, M.A. Palacios, M. Gomez, G. Morrison, S. Rauch, C. McLeod, R. Ma, S. Caroli, A. Alimenti, F. Petrucci, B. Bocca, P. Schramel, M. Zischhka, C. Petterson, U. Wass, M. Luna, J.C. Saenz and J. Santamaria, Sci. Total Environ., 296 (2002) 199. 289 K. Ravindra, L. Bencs and R. Van Grieken, Sci. Total Environ., 318 (2004) 1. 290 D.M. Wayne, J. Anal. At. Spectrom., 12 (1997) 1195. 291 K.H. Ek, S. Rauch, G.M. Morrison and P. Lindberg, Sci. Total Environ., 334/335 (2004) 149. 292 S. Zimmermann, J. Messerschmidt, A. Von Bohlen and B. Sures, Anal. Chim. Acta, 498 (2003) 93. 293 E. Desimoni, B. Brunetti and R. Bacchella, Electroanalysis, 14 (2002) 459. 294 C. Bosch Ojeda, F. Sanchez Rojas and J.M. Cano Pavon, Food Control., 17 (2006) 365. 295 C.A. Weeks, M. Croasdale, M.A. Osborne, L. Hewitt, P.F. Miller, P. Robb, M.J. Baxter, P.D. Warriss and T.G. Knowles, Food Addit. Contam., 23 (2006) 140. 296 C. Fragniere, M. Haldimann, A. Eastgate and U. Krahenbuhl, J. Anal. At. Spectrom., 20 (2005) 626. 297 C. Locatelli, D. Melucci and G. Torsi, Anal. Bioanal. Chem., 382 (2005) 1567. 298 C. Locatelli, Electrochim. Acta, 52 (2006) 614. 299 C. Locatelli, Anal. Chim. Acta, 557 (2006) 70. 300 F. Sanchez Rojas, C. Bosch Ojeda and J.M. Cano Pavon, Talanta, 70(5) (2006) 979. 301 B. Brunetti, R. Cattaneo and E. Desimoni, It. J. Food Sci., 17(4) (2005) 437. 302 A. Taylor, S. Branch, M.P. Day, M. Patriarca and M. White, J. Anal. At. Spectrom., 21 (2006) 439.
598
Clinio Locatelli
303 E. Ibanez and A. Cifuentes, Crit. Rev. Food Sci., 41(6) (2001) 413. 304 Commission of the European Communities 2001, EU Commission Decision 466/2001/EC of March 8, 2001, setting maximum levels for certain contaminants in foodstuff, G.U. EU-L 77/1, March 16, 2001. 305 L. Nasreddine and D. Parent-Massin, Toxicol. Lett., 127 (2002) 29–41. 306 Directive 2004/41/EC repealing certain Directives concerning food hygiene and health conditions for the production and placing on the market of certain products of animal origin intended for human consumption and amending Council Directives 89/662/EEC and 92/118/EEC and Council Decision 95/408/EC, April 21, 2004. 307 US Environmental Protection Agency. Available at http://www.epa.gov 308 US Food and Drug Administration. Available at http://www.fda.gov 309 S.G. Capar and N.J. Yess, Food Addit. Contam., 13(5) (1996) 553. 310 Canadian Food Inspection Agency. Available at http://www.inspection.gc.ca 311 FAO/WHO, ‘‘Sixteenth Report on the Joint Expert Committee on Food Additives’’, Tech. Rep. Ser. Wld Hlth Org., No. 505 (1972).
CHAPT ER
17 Polycyclic Aromatic Hydrocarbons Katsumi Tamakawa
Contents
1. Introduction 2. Physical and Chemical Properties 3. Health Effects 3.1 Effects on laboratory mammals in vitro 3.2 Effects on humans 4. Analytical Methods 4.1 Extraction 4.2 Cleanup 4.3 Determination 5. Occurrences of PAHs in Food 6. Future Trend Acknowledgements References
599 601 602 602 609 611 612 626 628 632 642 644 644
1. INTRODUCTION Polycyclic aromatic hydrocarbons (PAHs) are a large class of well-known carcinogenic compounds. These compounds are mainly formed by pyrolytic processes, especially the incomplete combustion of organic matter through natural and anthropogenic processes, such as forest fires, processing of coal and crude oil, vehicle traffic, residential heating, industrial power generating, cooking, smoking and so on. Some PAHs are commercially used as intermediates in industrial manufacturing. Naphthalene (Naph), anthracene (An) and phenanthrene (Phe) are used as raw materials in the production of dye, celluloid, lubricants, fibres, plastics and insecticides. However, the amounts of PAHs for commercial use are much less than those generated by incomplete combustion. Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00017-2
r 2008 Elsevier B.V. All rights reserved.
599
600
Katsumi Tamakawa
Owing to their widespread distribution in the environment, PAHs have been detected in air [1–5], sediment [6–9], soil [10–15], indoor air [16–18] and daily diet [19–24] and almost everywhere in the environment. PAHs contain two or more fused aromatic rings in their chemical structures, and have several hundred structural isomers. A number of PAHs and their related compounds have been detected in the environment. Among them, PAHs containing 24 or fewer ring carbon atoms (e.g., benz[a]anthracene, B[a]A; benzo[a]pyrene, B[a]P; dibenzo[ah]pyrene, DB[ah]P) have been chosen as target compounds for environmental monitoring owing to their biological effects. As a number of PAHs have proved to be mutagenic and/or carcinogenic and are considered to be major potential causes of cancer in humans, the occurrence of PAHs in the environment is of concern for public health in general. The fact that cancer could be due to exogenous causes was brought to light in 1775 by Sir Percival Pott [25]. He found that scrotal cancer in his patients, chimneysweepers, might be induced by professional exposure to soot and tar. The first experimental proof in animals to support this clinical impression was achieved by Yamagiwa and Ichikawa [26] in 1915. They succeeded in inducing neoplastic changes by patient application of coal tar to the ears of rabbits. The fact that pure chemical compounds might induce cancer in mammals was first demonstrated by Kennaway in 1930 [27], in seeking of carcinogens in highboiling fractions of coal tar distillates. A few years later, Cook et al. [28] identified B[a]P, which is nowadays one of the well-known PAHs, from two tons of coal tar pitch by monitoring its specific fluorescence. The primary routes of potential human exposure to PAHs are inhalation of polluted air and foods normally containing microgram quantities of PAHs. Emerole [29] reported that the presence of PAHs in smoked foods might be a contributory factor to the reported high stomach cancer within some Nigerian communities. In similar studies, Bally [30], Thorsteinsson [31] and Thorsteinsson and Thordanson [32] demonstrated the relationship between the presence of PAHs at high levels in Icelandic smoked fish and the prevalence of stomach cancer in Iceland. Roth et al. [33] studied the case in Linxian, China. They reported that high levels of PAHs present within food might contribute to that region’s high incidence of oesophageal cancer. Many published reports are available for estimation of multipathway exposure of PAHs. Among several routes, diet is estimated to be the major pathway for human exposure. Vyskocil et al. [34] investigated dietary intake and inhalation exposure of PAHs in small children living in Montreal, Canada. Estimated potential dose of pyrene (Py) from food was 167 and 186 ng, respectively, in ‘polluted’ and ‘non-polluted’ areas, and that from inhalation was 8.4 and 5.4 ng, respectively. Butler et al. [35] measured multimedia exposure to B[a]P in 15 adult individuals living in New Jersey. The proportional contribution of dietary intake in total exposure was calculated to be about 95%. Carcinogenic risk of B[a]P was estimated to be 4 107 in inhalation and 1 105 in dietary intake. This means that potential risk by dietary intake is about 25 times higher than the exposure by inhalation. Also Lodovici et al. [36] demonstrated in adult populations living in Italy that the inhalation of air is
Polycyclic Aromatic Hydrocarbons
601
not so important for PAHs intake accounting for 11% of the total intake. Cirillo et al. [37] studied multipathway exposure to PAHs among children aged 7–9. They showed that food appears to be most relevant source of exposure to PAHs. Most of research [34–40] showed that daily diet is estimated to be one of the major pathways among several routes for human exposure to PAHs. Doll [41] and Wynder and Gori [42] reported that most human cancer might be attributable to environmental carcinogens, especially through daily diet. Later, the Harvard Cancer Prevention Study [43], and the American Institute of Cancer Research/World Cancer Research Fund [44] separately affirmed that cancer is basically a preventable disease. A variety of carcinogenic substances have been detected in food so far. Among them, PAHs is one of the major components contributing to human cancer. It is, therefore, very important to develop simple and accurate analytical methods for routine screening of these harmful PAHs. In this chapter, the physicochemical properties, toxicological evaluation, analytical methods of PAHs and their occurrence in food are reviewed. In addition, promising analytical methods for PAHs are also criticized.
2. PHYSICAL AND CHEMICAL PROPERTIES The term ‘PAHs’ is generally used for aromatic compounds containing only carbon and hydrogen atoms (i.e., the unsubstituted parent PAH and their alkylsubstituted derivatives). These compounds consist of two or more fused aromatic rings made up of carbon and hydrogen atoms in their chemical structures. Consequently, they have many structural isomers. More than 100 PAHs have been detected in the atmospheric environment, and about 200 PAHs have been identified in tobacco smoke. In addition, 660 PAHs isomers can be retrieved in a database, ‘Polycyclic Aromatic Hydrocarbon Structure Index’ [45], which is presented as an aid in the identification of the chemical structures and nomenclature of PAHs. Among a variety of PAHs, 16 PAHs have been selected as priority substances for environmental monitoring by the United States Environmental Protection Agency (EPA). These PAHs include: Naph, acenaphthene (Ace), acenaphtylene (Acn), fluorene (Fl), Phe, An, fluoranthene (Flu), Py, B[a]A, chrysene (Chry), benzo[b]fluoranthene (B[b]F), benzo[k]fluoranthene (B[k]F), B[a]P, DB[ah]A, benzo[ghi]perylene (B[ghi]P) and indeno [1,2,3-cd]pyrene (In[cd]P). Eight of these PAHs, i.e., B[a]A, B[b]F, B[k]F, B[a]P, Chry, DB[ah]A, Flu and In[cd]P, are known to be carcinogenic and/or mutagenic. The Italian National Advisory Toxicological Committee [46] recommended seven PAHs, i.e., B[a]A, B[a]P, B[b]F, benzo[j]fluoranthene (B[j]F), B[k]F, DB[ah]A and In[cd]P, for health-related investigations. These PAHs were selected on the basis of their classification as having ‘probable’ or ‘ possible’ carcinogenicity to humans. The European Regulation 2065/ 2003/EC on smoke flavorings used or intended for use in or on food [47] requires the precursors to commercial smoke flavorings have to be registered as primary products in the European Union (EU). The application for registration has to be
602
Katsumi Tamakawa
accompanied by a dossier containing data on chemical composition, including a group of 15 PAHs which were recognized by the former Scientific Committee on Food in 2002 as being a concern for public health. These PAHs include: B[a]A, Cyclo[cd]P, Chry, 5-methylchrysene, B[b]F, B[j]F, B[k]F, B[a]P, In[cd]P, DB[ah]A, B[ghi]P, DB[al]P, DB[ae]P, DB[ai]P and DB[ah]P [48]. The structural formulae of selected PAHs isomers are shown in Figure 1. These were selected to be included in this chapter because they are suspected to be more harmful and there is a greater possibility that people may be exposed to these PAHs than to the others. The chemical and physical properties of these PAHs are also summarized in Table 1. Data are mainly retrieved from Interactive PhysProp Database Demo [49]. PAHs generally have planar structures as shown in Figure 1. As pure chemicals, they exist as a pale or greenish-yellow, white or colourless crystal and have a faint and aromatic odor. Among them, some PAHs such as B[a]A, DB[ai]P and In[cd]P show fluorescence ranging from greenish-yellow to brilliant bluishviolet to brown. At room temperature, most PAHs are usually solids, highly hydrophobic and are very soluble in organic solvents. The solubility of PAHs in water is inversely proportional to the numbers of aromatic rings contained. PAHs also have high melting and boiling points and low vapor pressures. Vapor pressure tends to decrease with increasing molecular mass, varying by more than 10 orders of magnitude. These physicochemical properties affect the distribution of PAHs in the environment. In aqueous environments, PAHs are generally found adsorbed on particulate matter, or solubilized in any oily matter, which may pollute water. Heavier molecular weight PAHs, which contain four or more aromatic rings, are almost exclusively bound to particulate matter, whereas lower molecular weight PAHs can also be found dissolved in water. In the atmospheric environment, the lighter PAHs are distributed between the gas phase and particles. The heavier PAHs are only associated with particles. PAHs are primarily rather inert compounds. However, in the presence of sunlight, they are easily decomposed to oxygenated PAHs. Photooxidation generally occurs much faster for particle-free PAHs than for particle-bound compounds. PAHs in atmospheric environments can also react easily with nitrogen oxides to form nitro-substituted PAHs. In the analysis of PAHs, it is, consequently, important to pay attention to the instability of these compounds at all stages to avoid their photodecomposition. To design and choose an analytical method for PAHs, it should be noted that their physical and chemical properties are an important consideration.
3. HEALTH EFFECTS 3.1 Effects on laboratory mammals in vitro The biological mechanisms to produce adverse effects of the majority of PAHs are not well understood yet. Except for Naph, there are only a limited number of studies available for the evaluation of acute oral toxicity. The values of oral LD50
Acenaphtylene (Acn)
Anthanthrene (Anth)
Anthracene (An)
Naphthalene (Naph)
Naphthacene (Naphth)
Figure 1
Structural formulae of PAHs.
Coronene (Cor)
Perylene (Per)
Dibenzo[a,l ]pyrene D[al ]P
*abbreviation in the parenthesis is used in this chapter
Dibenzo[ai ]pyrene (DB[ai ]P)
Chrysene (Chry)
Dibenzo[ah]pyrene (DB[ah]P)
Benzo[e]pyrene (B[e]P)
Benzo[c]phenanthrene (B[c]Phe)
Benz[a]anthracene3 (B[a]A)
Benzo[a ]pyrene (B[a]P)
Benzo[b]fluoranthene B[b]F
Phenanthrene (Phe)
Fluoranthene (Flu)
Pyrene (Py)
Fluorene (Fl)
Triphenylene (TriPhen)
Indeno[1,2,3-cd ]pyrene (In[cd ]P)
Cyclopenta[cd ]pyrene Dibenz[a,h]anthracene Dibenzo[ae]pyrene (Cyclo[cd ]P) (DB[a,h]A) (DB[a,e]P)
Benzo[ j ]fluoranthene Benzo[ k ]fluoranthene Benzo[ ghi ]fluoranthene Benzo[ghi ]perylene B[ j]F B[k]F (B[ghi ]Flu) (B[ ghi ]P)
Acenaphthene (Ace)
Polycyclic Aromatic Hydrocarbons
603
205-99-2
205-82-3
207-08-9
203-12-3 191-24-2 195-19-7 50-32-8
192-97-2
B[j]F
B[k]F
B[ghi]Flu
B[ghi]P
B[c]Phe
B[a]P
B[e]P
An
B[b]F
120-12-7
Anth
56-55-3
191-26-4
Acn
B[a]A
208-96-8
Ace
Acenaphthene 1,2-Dihydroacenaphthylene Acenaphtylene 1,2-Dihydroacenaphthalene Anthanthrene Dibenzo[def,mono]chrysene Anthracene Paranaphthalene
Benz[a]anthracene 1,2-Benzanthracene 2,3-Benzophenanthrene Benzo[b]fluoranthene 2,3-Benzofluoranthene 3,4-Benzofluoranthene Benzo[j]fluoranthene 10,11-Benzofluoranthene Benzo-12,13-fluoranthene Benzo[k]fluoranthene 11,12-Benzofluoranthene 11,12-Benzo[k]fluoranthene Benzo[ghi]fluoranthene 2,13-Benzofluoranthene Benzo[ghi]perylene 1,12-Benzoperylene Benzo[c]phenanthrene 3,4-Benzophenanthrene Benzo[a]pyrene 3,4-Benzopyrene 3,4-Benzpyrene Benzo[e]pyrene 4,5-Benzopyrene
83-32-9
(Abbreviation used in this chapter)
CAS no.
C22H12 276.34
177.5
176.5
yellow needles
Colourless crystals
68
226.28
No data
No data
C18H10 226.28 C22H12 276.34 C18H12 228.3 C22H12 252.32
217
278
Pale yellow needles
C20H12 252.32
166
168
No data
No data
215
White crystalline flakes, bluishviolet fluorescence Colourless leaflets or plates Needles 84
No data
264b
No data
311 (at 1E+ 01mmHg) 310–312
No data
W500
No data
480
No data
No data
437.6
339.9
280
92.5
No data
279
Boiling point (1C)
93.4
Melting point (1C)
White crystal
Crystal colourb
C20H12 252.32
C20H12 252.32
C18H12 228.3
C12H10 154.21 C12H8 152.2 C22H12 276.34 C14H10 178.24
Chemical formula, molecular weight
Physical and chemical properties of polycyclic aromatic hydrocarbonsa
IUPAC name Synonyms
Table 1
0.0063 (251C)
0.00162(251C)
0.00345 (251C)
0.00026
No data
0.0008
0.0025
0.0015
0.0094 (251C)
0.0434 (241C)
0.00127
16.1 (251C)
3.9 (251C)
Water solubility (mg/L)
6.44
6.13
5.25
6.63
No data
6.11
6.11
5.78
5.76
4.45
7.04
3.94
3.92
Octanolwater (log P)
5.7E-009 (251C)
5.49E-009 (251C)
6.66E-007 (251C)
1E-010 (251C)
No data
9.65E-010 (251C)
2.62E-008 (251C)
5E-007 (251C)
1.9E-006 (251C)
2.67E-006 (251C)
8.75E-010 (251C)
0.000912 (251C)
0.0025 (251C)
Vapor pressure (mm Hg)
604 Katsumi Tamakawa
191-30-0 206-44-0
86-73-7
193-39-5 92-24-0
91-20-3
DB[al]P
Flu
Fl
In[cd]P
Naphth
Naph
Py
TriPhen
Pyrene Benzo[def]phenanthrene
Triphenylene 9,10-Benzophenanthrene
Interactive PhysProp Database Demo. ChemFinder, http://chemfinder.cambridgesoft.com/
b
a
189-55-9
DB[ai]P
217-59-4
129-00-0
85-01-8
189-64-0
DB[ah]P
Phe
192-65-4
DB[ae]P
198-55-0
53-70-3
DB[ah]A
Per
27208-37-3
Cyclo[cd]P
Perylene Peri-dinaphthalene Phenanthrene
191-07-1
Cor
Coronene Hexabenzobenzene Cyclopenta[cd]pyrene Cyclopentano[cd]pyrene Dibenz[ah]anthracene 1,2:5,6-Dibenzanthracene Dibenz[ae]pyrene 1,2:5,6-Dibenzopyrene Dibenzo[ah]pyrene 3,4:8,9-Dibenzopyrene Dibenzo[ai]pyrene 3,4:9,9-Dibenzopyrene Dibenzo[al]pyrene 1,2:3,4-Dibenzopyrene Fluoranthene 1,2-Benzacenaphthene Benzo[jk]fluorene Fluorene 2,3-Benzindene 2,2’-Methylenebiphenyl Indeno[1,2,3-cd]pyrene 2,3-o-Phenylenpyrene Naphthacene 2,3-Benzanthracene Tetracene Naphthalene
218-01-9
Chry
Chrysene 1,2,5,6-Dibenzonaphthalene 1,2-Benzophenanthrene
C18H12 228.3
C16H10 202.26
C10H8 128.18 C20H12 252.32 C14H10 178.24
No data
C22H12 276.34 C18H12 228.3
Colourless solid or monoclinic crystals Colourless to light yellow solid No data
Colourless to brown solid No data
No data
White leaflets
Coloured needles
No data
425
404
151.2
199
340
274
217.9
No data
536
295
384
275 (at 5.00E02 mm Hg) No data
No data
No data
524
No data
525
448
99.2
252.32
80.2
No data
163.6
114.8
107.8
162.4
281.5
317
No data No data
233.5
269.5
White crystals No data
No data
437.3
258.2
No data
White crystals, orthorhombic bipyramidal plates from benzene
C13H10 166.22
C24H12 300.36 C18H12 228.29 C22H14 278.36 C24H14 302.38 C24H14 302.38 C24H14 302.38 C24H14 302.38 C16H10 202.26
C18H12 228.3
0.0411 (251C)
0.135 (251C)
1.15 (251C)
0.0004 (251C)
31 (251C)
No data
0.0019 (251C)
1.89 (251C)
0.26 (251C)
0.00036
0.000554
3.5E-005 (251C)
8.02E-005 (251C)
0.00249
No data
0.00014 (251C)
0.002
5.49
4.88
4.46
6.25
3.3
No data
6.7
4.18
5.16
7.71
7.28
7.28
7.28
6.75
No data
7.64
5.81
2.1E-008 (251C)
4.5E-006 (251C)
0.000112 (251C)
5.25E-009 (251C)
0.085 (251C)
No data
1.25E-010 (251C)
0.00842 (251C)
9.22E-006 (251C)
4.8E-010 (251C)
1.78E-011 (251C)
6.41E-012 (251C)
7.03E-011 (251C)
1E-010 (201C)
No data
2.17E-012 (251C)
6.23E-009 (251C)
Polycyclic Aromatic Hydrocarbons
605
606
Katsumi Tamakawa
reported are, B[a]P: W1,600 mg/kg body weight in mice [50], Phe: 700, 1,000 mg/kg in mice [48], Naph: 490—9,430 mg/kg in rats [51,52]. Oral toxicity of PAHs ranges from low to moderate. Adverse effects such as myelotoxicity, hemolymphatic changes and anemia were observed in the short-term studies of PAHs [53]. In long-term testing, many PAHs are known to be capable of inducing cancer in experimental animals [54]. Most studies to assess the carcinogenic potential of PAHs were carried by dermal, subcutaneous or inhalation exposure. There are only a limited number of studies that dealt with oral administration. When administrated in the diet, PAHs produced tumors in the gastrointestinal tract, liver, lungs and mammary glands of mice and rats. When administered by gavage, B[a]P induced malignant and benign forestomach tumors in mice and hamsters, and mammary tumors in female rats. Culp et al. [55] showed that papillomas and squamous cell carcinomas were observed in the forestomach of rodents. Besides these major target sites, B[a]P treatment also induced soft tissue sarcomas at various sites such as oesophagus, skin and mammary [56]. In a gavage study, B[a]A produced papillomas of the forestomach as well as lung adenomas and hepatomas in mice. When administered as an olive oil emulsion in drinking water, DB[ah]A induced alveologenic carcinomas of the lung and hemangioendotheliomas in mice [54]. As cancer is often linked to DNA damage, it is important to assess the genotoxicity of chemicals to estimate carcinogenic potency. To evaluate the genotoxicity of chemicals, a variety of short-term tests have been developed. Among them, the ‘Ames test’ is a well-known bacterial mutagenicity test. Mutagenicity of selected PAHs in the Ames test are summarized in Table 2. It is apparent that most of the PAHs, especially those containing four or more aromatic rings in their chemical structure, show positive responses in the Ames test. To examine the genotoxic profiles of PAHs, a bibliographic database, TOXNET (Toxicology Data Network), by the Environmental Mutagen Information Center (EMIC) is available. Users can search by subject terms, title words, chemical names, Chemical Abstracts Service Registry Numbers (CAS no.) and authors (EMIC) [57]. The overview of the genotoxicity of PAHs considered by the International Programme on Chemical Safety (IPCS) [58] is partly summarized in Table 3. Among 30 PAHs listed in Table 3, 16 PAHs are genotoxically positive and finally 3 PAHs, i.e., An, Fl and Naph, are totally or probably inactive in all shortterm tests. For the other PAHs, the evidence of genotoxicity is limited and based on results mainly obtained in in vitro systems. Therefore, they cannot be clearly classified as mutagenic. In the detoxification pathway of PAHs, they are initially oxidized to arene oxides and phenols by the mixed-function oxidase, which converts the non-polar PAHs into polar hydroxy and epoxy derivatives. For example, B[a]P is initially converted to several epoxides such as 7,8-epoxide, and then hydrolyzed to the diolepoxides such as 7,8-dihydrodiol-9,10-epoxide, which are considerably more mutagenic than the parent compounds. These so-called bay-region (e.g., stereochemically hindered, cup-shaped area between carbons 10 and 11 of
Polycyclic Aromatic Hydrocarbons
Table 2
607
Mutagenicity of polycyclic aromatic hydrocarbons in the Ames test TA98
Acenaphthene Acenaphtylene Anthanthrene Anthracene Benz[a]anthracene Benzo[b]fluoranthene Benzo[j]fluoranthene Benzo[k]fluoranthene Benzo[ghi]fluoranthene Benzo[ghi]perylene Benzo[c]phenanthrene Benzo[a]pyrene Benzo[e]pyrene Chrysene Coronene Cyclopenta[cd]pyrene Dibenz[ae]anthracene Dibenz[ah]anthracene Dibenzo[ah]pyrene Dibenzo[ai]pyrene Dibenzo[al]pyrene Fluoranthene Fluorene Indeno[1,2,3-cd]pyrene Naphthacene Naphthalene Perylene Phenanthrene Pyrene Triphenylene
TA100
+S9mix
Reference
+S9mix
Reference
+ + + No data + +,7 + + + 7 + + + +,7 + + + + + + + + + +
[59] [59] [60] [62,63] [60,62] [60] No data [60] [65,66] [67] [70] [62,71] [60,62,63] [59,62] [59] [70] [73] [60] [74] [60] [60,65] [67,75] [62] [76] [61] [52,63] [70,78] [59,62] [59,62] [67,75]
+ + + + + + + + + 7 + No data + + + + + + + + + + + No data +
[59] [59] [61] [62,63] [60,62] [64] [64] [64] [65] [68,69] [69,70] [62,71] [62,72] [60,62] No data [70] [73] [62] [74] [62] [65] [75] [62] [77] [61] [62,63] [78] [59,62] [59,62] [75]
B[a]P) diolepoxide are considered to be the ultimate mutagenic and/or carcinogenic species of PAHs [79]. It is well known that these metabolizing systems for PAHs are widely distributed in animal tissues. Among them, liver is the most active in metabolizing capacity, followed by lung, intestinal mucosa and kidneys. It is noteworthy that PAHs are generally potent inducers of mixedfunction oxidases and potentiate their own toxicity. These metabolic intermediates are then converted to water-soluble conjugates with glutathione and glucuronic acid, which enable excretion to occur via the kidney. Formation of these conjugates is regarded to be a true detoxification.
608
Table 3
Katsumi Tamakawa
Evaluations of genotoxicity and carcinogenicity of polycyclic aromatic hydrocarbons
IUPAC name
Genotoxicitya
Carcinogenicity IARCb
Acenaphthene Acenaphtylene Anthanthrene Anthracene Benz[a]anthracene Benzo[b]fluoranthene Benzo[j]fluoranthene Benzo[k]fluoranthene Benzo[ghi]fluoranthene Benzo[ghi]perylene Benzo[c]phenanthrene Benzo[a]pyrene Benzo[e]pyrene Chrysene Coronene Cyclopenta[cd]pyrene Dibenz[ah]anthracene Dibenzo[ae]pyrene Dibenzo[ah]pyrene Dibenzo[ai]pyrene Dibenzo[al]pyrene Fluoranthene Fluorene Indeno[1,2,3-cd]pyrene Naphthacene Naphthalene Perylene Phenanthrene Pyrene Triphenylene
(?) (?) (+) + + + + (+) + (+) + + + (+) + + + (+) + (+) + +
3 3 2A 2B 2B 2B 3 3 3 2A 3 3 3 3 2A 2B 2B 2B 2B 3 3 2B
+ (?) (?) +
2B 3 3 3 3
EPAc
3 D D B2 B2 B2 D
B2 B2
B2
D D B2
D D
a Ref. [78], pp. 47–96. Classification: +, positive; , negative and ?, questionable. Parentheses, result derived from small database. Short-term tests used for the evaluation are as follows: reverse mutation test in Salmonella typhimurium (Ames test), forward mutation test in S. typhimurium strain TM677, DNA binding in mammalian cells in vitro, DNA damage/repair in bacteria, DNA damage/repair in mammalian cells, mitotic gene conversion in yeast, mitotic recombination in yeast, forward mutation in yeast, host-mediated assay (bacteria), host-mediated assay (yeast), sexlinked recessive lethals (Drosophila), somatic mutation and recombination (Drosophila), DNA repair (Drosophila), HPRT system, thymidine kinase system, ouabain resistance, diphtheria toxic resistance, chromosomal aberrations, sister chromatid exchanges, micronucleus test, DNA damage/repair in vivo (various tissues), cytogenetic effects in somatic cells, cytogenetic effects in germ cells, sperm abnormalities and dominant lethals. b Ref. [80]. Classification: Group 1, carcinogenic to humans; Group 2A, probably carcinogenic to humans; Group 2B, possibly carcinogenic to humans; Group 3, not classifiable as to its carcinogenicity to humans and Group 4, probably not carcinogenic to humans. c EPA, US Environmental Protection Agency, Integrated Risk Information System (IRIS), Evidence for Human Carcinogenicity Weight of Evidence Characterization. Available at http://toxnet.nlm.nih.gov/cgi-bin/sis/htmlgen?IRIS. Classification: Group A, human carcinogen; Group B1, probable human carcinogen based on limited evidence of carcinogenicity in humans and sufficient evidence of carcinogenicity in animals; Group B2, probable human carcinogen based on sufficient evidence of carcinogenicity in animals; Group C, possible human carcinogen; Group D, not classifiable as to human carcinogenicity and Group E, evidence of non-carcinogenicity for humans.
Polycyclic Aromatic Hydrocarbons
609
3.2 Effects on humans There is inadequate evidence for the carcinogenicity of PAHs in humans [54]. However, there are a number of occupational epidemiologic studies that show increased incidence of cancer in humans exposed to mixtures of PAHs by inhalation or dermal contact. The first one was reported by Sir Percival Pott in 1775, as has already been mentioned, who reported the increased incidence of scrotal cancer among chimneysweepers. After this pioneer study, different epidemiological studies pointed out the high incidence of tumors in workers exposed to coke oven emissions [81,82], roofing-tar emissions [83] and cigarette smoke [84,85]. As for oral exposure of PAHs, there is a little information on the influences to human health. In the Van region of eastern Turkey, upper gastrointestinal (oesophageal and gastric) cancers are endemic and dietary factors are considered to play an essential role in carcinogenesis. Tu¨rkdog˘an et al. [86] studied B[a]P and B[a]A levels of cooked foods and revealed that traditional foods, which are baked or cooked using animal manure or fuel oil, are highly contaminated by PAHs, and that they may constitute a serious risk factor in this region. Lopez-Abente et al. [87] reported the relationship between the oral exposure of PAHs and health effects in rural areas in Spain. In these areas, wine has been traditionally stored in leather bottles sealed with a tar-like substance, which contain PAHs. By multivariate analysis, increased risk of colorectal adenomas was more strongly associated with B[a]P intake. Sinha et al. [88] estimated dietary intake of B[a]P to test its relationship with risk of colorectal adenomas in a case-control study. They developed a food frequency questionnaire on meat-cooking methods, doneness levels and B[a]P database based on the collection and analysis of a wide range of food samples. By multivariate analysis, increased risk of colorectal adenomas was regarded to be associated with dietary intake of B[a]P. These studies provide evidence that dietary intake of B[a]P plays a role in colorectal adenoma etiology. Evaluations on the carcinogenicity of selected PAHs by the International Agency for Research on Cancer (IARC) [80] and by the EPA are shown in Table 3. Both IARC and EPA classified PAHs into different categories according to the evidence available on their carcinogenicity. The criteria applied by each institution to classify carcinogenicity are shown in the footnote of the table. The main problem in evaluating carcinogenicity of PAHs in food and environment is that they are not present as individual compounds but as complex mixtures. The toxic equivalence is an approach proposed to assess the carcinogenic potency of complex mixtures. This concept requires that PAH concentrations are summed and also expressed as B[a]P equivalents, their relative concentrations are weighted in relation to the carcinogenic potential of individual PAH compounds using toxic equivalency factors (TEF). Toxic equivalents (TEQs) are defined as follows: TEQs ¼ SðCi TEFi Þ where Ci is the concentration of individual PAHs identified in a complex mixture and TEFi the relative potencies of PAHi in comparison with that of B[a]P.
610
Katsumi Tamakawa
The concept of TEQs was initially developed to estimate the potential toxicity of complex mixtures of polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs). Also in PAHs, there have been several studies on the estimation of the total carcinogenicity by TEFs of individual PAHs [89–96]. The TEFs reported are compared in Table 4. DB[ah]A appears to be equipotent or somewhat more potent than B[a]P. B[b]F, Ind[cd]P and B[a]A were about 10% and Naph, Phe and Fl were about 1% as potent as B[a]P. The greatest variation is observed for Chry. Most studies to assess the carcinogenic potency of PAHs were carried out following skin application, pulmonary instillation and intraperitoneal injection. There are only a limited number of studies available on acute oral toxicity. The oral toxicity of PAHs, therefore, has been speculated by these studies. There are some limitations in using the TEF approach in the risk assessment of PAHs in food. Application of the TEF approach to risk assessment is justifiable when all the chemicals in the mixture act in the same way, by the same mechanism. Dioxins bind directly to Ah receptor without biotransformation and this binding is considered to be responsible for their toxicity. Although PAHs generally bind to the Ah receptor, this is not the only one that determines the carcinogenic effect of PAHs. PAHs cannot express their carcinogenic potential until they have been metabolized to forms that can bind to DNA. PAHs are not necessarily activated through the same metabolism. Moreover, there is no Table 4 Estimations of carcinogenic potencies of various polycyclic aromatic hydrocarbons, relative to benzo[a]pyrene Compound
Anthracene Benz[a]anthracene Benzo[a]pyrene Benzo[b]fluoranthene Benzo[e]pyrene Benzo[ghi]perylene Benzo[j]fluoranthene Benzo[k]fluoranthene Chrysene Dibenz[ah]anthracene Dibenzo[ah]pyrene Fluoranthene Indeno[1,2,3-cd]pyrene Naphthalene Phenanthrene Pyrene
References [97]
[98]
[99]
0.1 1.0 0.1
0.1 1.0 0.1
0.145 1.0 0.167
0.1 0.1 0.1 1 1
0.1 0.1 0.01 10
0.1
0.1
0.020 0.0044 1.11
0.055
[100]
[101]
0.28 0.014 1.0 0.11 0 0.012 0.045 0.037 0.026 0.89 1.2
0.01 0.1 1.0 0.1
0.067 0.00064 0
0.01 0.1 0.01 5 0.001 0.1 0.001 0.001 0.001
Polycyclic Aromatic Hydrocarbons
611
corroboration that different PAHs induce the same type of mutations in the same organs or tissues [102]. The TEFs approach essentially relies on the additive theory, in which case there is no interaction (i.e., synergistic and/or antagonistic effects) between the components in the complex mixture. Some PAHs, however, have been reported to have greater interacting effects than other PAHs. For example, B[e]P, B[ghi]P, Flu and Py show the synergistic effects to B[a]P-induced tumor incidence [55]. B[e]P, Flu and Py have weak tumor-promoting activity following initiation by B[a]P [79]. Interactions between some PAHs and B[a]P are also reported to reduce the carcinogenic activity of B[a]P in animals [79]. Krewski et al. [103] analysed the published values and derived a new set of TEF values. Applications of their TEFs to the results of bioassays with PAH mixtures [104,105] indicated that their values would be unlikely to underestimate the carcinogenic risk posed by whole mixtures [55]. Schneider et al. [106] also examined the use of the TEF derived by Brown and Mittelman [107] and concluded that the TEFs approach may underestimate the carcinogenic potencies of PAHs mixtures in most cases. Because of some uncertainty in the TEF approach mentioned above, the Scientific Committee on Food, European Commission, does not find it necessarily appropriate to endorse the use of the TEF approach for the risk assessment of PAH in food [102].
4. ANALYTICAL METHODS Analysis of PAHs in food samples is problematic because of their extremely low concentrations and their affinity to be in the fatty fraction of food. As food samples naturally contain large quantities of fats and lipids, it is very important to extract and eliminate these fats before instrumental analysis, without losing the PAHs in any of the steps. In the analysis of PAHs, it is also necessary to pay attention to the chemical properties, i.e., especially instability and sublimation, of these compounds at all stages to achieve accurate analysis. Tamakawa et al. [108] showed photodecomposition of seven PAHs (i.e., An, Py, B[a]A, B[b]F, B[k]F, B[a]P and B[ghi]P) in acetonitrile under usual experimental conditions. PAHs, especially B[a]P and An, were easily decomposed within 5 h under these conditions. Takatsuki et al. [109] showed that B[a]P was decomposed by the coexistence of alkaline, light and oxygen; by peroxides in aged ethyl ether; and by oxygen when absorbed on silica gel. In the analysis of PAHs, therefore, it is recommended that samples be handled under ultraviolet (UV)-protected fluorescent lamps at all stages to achieve accurate results [110]. Moreover, low-molecular-weight PAHs, containing four or fewer aromatic rings such as An, Flu and Py, are easily sublimated during the drying-up processes in the preparation of PAHs (Figure 2). It is also critical to concentrate the extracting solvent carefully to ensure that the sample does not dry up completely.
612
Katsumi Tamakawa
120
100
Recoveries (%)
80
60
40
20
0
0
2 4 Time (min) of N2 blowing after drying-up
Anthracene Benz[a]anthracene Benzo[ghi ]perylene
Fluoranthene Benzo[b]fluoranthene
8
Pyrene Benzo[a]pyrene
Figure 2 Influences of N2 blowing on the recoveries of PAHs.
To correct the losses of PAHs during the analysis, the use of internal standards (surrogates) is recommended before the quantification by instrumental analysis such as high-performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS) [111–114]. Dunn and Armour [115] used tritium-labeled B[a]P as an internal standard in the HPLC determination to correct the losses of B[a]P during the purification procedure. In the United Kingdom (UK) Total Diet Study [116], 13C-labeled PAHs are also used as internal standards. Surrogates generally should be added to samples at a concentration similar to that expected for the analytes of interest [111]. A variety of analytical methods for multiresidue analysis of PAHs have been proposed since the 1970s. Typical methods include: extraction, cleanup and instrumental quantification using GC coupled with flame ionization detector (FID) or MS and HPLC with an UV detector or fluorescence detector. Typical analytical methods for PAHs in food are shown in Tables 5 and 6.
4.1 Extraction The PAHs extraction procedures most often used in water and beverages samples are liquid–liquid extraction (LLE) [117,118] and solid-phase extraction (SPE) [119]. These methods are applicable to food samples with comparatively low fat
Hexane extraction under alkaline condition
Liquid smoke flavor
Py, B[a]A, DB[ac]A, B[e]P, B[a]P, DB[ah]A
Mobile phase
AcCN/H2O gradient
AcCN/H2O (80:20, v/v)
AcCN/H2O (80:20, v/v)
Separon SGX C18 AcCN/H2O 300 mm (L) 3.0 mm (i.d.) (3:1, v/v)
Vydac 201 TP54 reverse-phase C18 250 mm (L) 4.6 mm (i.d)
Radial-Pak 5PAH10 Alkaline saponification with Na2S 100 mm (L) 5 mm (i.d.) as antioxidant, hexane extraction, Sep-Pak column purification (silica) Alkaline saponification, hexane Analytical HC-ODS extraction, Sep-Pak column 250 mm (L) 26 mm (i.d.) purification (silica)
Alkaline saponification, 1,1,2-trichlorotrifluoroethane extraction, SPE column purification (alumnina, silica, C18)
Daily diet
Stationary phase
[125]
[124]
[123]
[122]
[121]
UV 254 nm, fluorescence (Ex: 280 nm, Em: 389 nm)
Fluorescence An, Py, B[a]A (Ex: 334 nm, Em: 384 nm) B[b]F, B[k]F, B[a]P, B[g,h,i]P (Ex: 365 nm, Em: 430 nm) Fluorescence An, Py (Ex: 334 nm, Em: 384 nm) B[k]F, B[a]P, B[g,h,i]P (Ex: 384 nm, Em: 406 nm) Fluorescence Naph, Ace, Fl, Phe (Ex: 270 nm, Em: 350 nm) An, Flu, Py (Ex: 250 nm, Em: 420 nm) B[a]A, Chry (Ex: 270 nm, Em: 390 nm) B[b]F, B[k]F, B[a]P, DB[a,h]A (Ex: 290 nm, Em: 410 nm) B[g,h,i]P, In[c,d]P (Ex: 300 nm, Em: 465 nm) Fluorescence (Ex: 310 nm, Em: 410 nm)
[120]
Reference
Fluorescence (Ex: 370 nm, Em: 410 nm)
Detection
Quantitative HPLC
AcCN/H2O Radial-Pak PAH Alkaline saponification with Na2S analytical column as antioxidant, hexane extraction, (80:20, v/v) 300 mm (L) 15 mm (i.d.) silica gel column purification AcCN/H2O Vydac 201 TP54 Alkaline saponification, reverse-phase C18 trimethylpentane extraction, GPC gradient 150 mm (L) 4.6 mm (i.d.) purification
Sample preparation
Naph, Ace, Fl, Seafood Phe, An, Flu, Py, B[a]A, Chry, B[b]F, B[k]F, B[a]P, DB[ah]A, B[ghi]P, In[cd]P
An, Py, B[k]F, B[a]P, B[ghi]P
B[a]P, Chry, B[e]P, Fish, shellfish B[b]F, B[h]F, B[a]P, B[ghi]P Shellfish Flu, Py, B[a]A, Chry, B[e]P, B[b]F, B[k]F, B[a]P, DB[ah]A, B[ghi]P, In[cd]P Daily diet An, Py, B[a]A, B[b]F, B[k]F, B[a]P, B[ghi]P
Sample type
Methods used for polycyclic aromatic hydrocarbon detection: high-performance liquid chromatography (HPLC)
Analyte
Table 5
Phe, An, Flu, Py, Edible oils, fats B[a]A, Chry, B[a]F, B[k]F, B[e]P, B[a]P, DB[ah]A, Pery, B[ghi]P, In[cd]P, Cor, Anth
Smoked and broiled fish
LC-PAH column CH3OH/H2O Soxhlet extraction (methylene gradient 250 mm (L) 4.6 mm (i.d.) chloride) HPLC preparation, SPE column purification (cyanopropyl) AcCN/H2O Supercritical fluid extraction (SFE) LiChrospher 100 RP-18 column 125 mm with MeOH as modifier, stepwise (L) 4 mm (i.d.) SPE cleanup with bilayer mini gradient column (alumina+silica gel), octadecyl SPE-cartridge purification (Bond Elut C18) Chromspher 5PAH AcCN/H2O On-line donor–acceptor complex 250 mm(L) 4.6 mm (i.d.) chromatography (DACC) gradient cleanup (DACC column, Chromsher PI)
Oyster
Mobile phase
Phe, An, Flu, Py, B[a]A, Chry, B[b]F, B[k]F, B[a]P, B[ghi]P Naph, Fl, Phe, An, Flu, Py, B[a]A, Chry, B[a]P, Per
Stationary phase
Fluorescence Phe (Ex: 244 nm, Em: 375 nm) An (Ex: 244 nm, Em: 420 nm) Flu (Ex: 280 nm, Em: 460 nm) Py (Ex: 330 nm, Em: 388 nm) B[a]A (Ex: 280 nm, Em: 420 nm) Chry (Ex: 261 nm, Em: 400 nm) B[a]F (Ex: 250 nm, Em: 510 nm) B[k]F (Ex: 396 nm, Em: 430 nm) B[e]P (Ex: 324 nm, Em: 392 nm) B[a]P (Ex: 378 nm, Em: 403 nm) DB[a,h]A (Ex: 290 nm, Em: 440 nm) Pery (Ex: 430 nm, Em: 465 nm) In[c,d]P (Ex: 296 nm, Em: 500 nm) Cor (Ex: 298 nm, Em: 438 nm) Anth (Ex: 275 nm, Em: 330 nm)
UV 254 nm
Fluorescence
Detection
Quantitative HPLC
Sample preparation
Sample type
Analyte
Table 5 (Continued )
[128]
[127]
[126]
Reference
B[a]P
Soxhlet extraction (methylene chloride) SPE column purification (Florisil)
Vegetable oils Naph, Ace, Fl, Phe, An, Flu, Py, B[a]A, Chry, B[b]F, B[k]F, B[e]P, B[a]P, DB[ah]A, B[ghi]P, In[cd]P Tea infusion Phe, Flu, Py, samples B[a]A, B[e]P, B[a]P, DB[ah]A, B[ghi]P Nova-Pak C18 column AcCN/H2O 150 mm (L) 3.9 mm (i.d.) gradient
AcCN/H2O C18 column 125 mm (L) 4.6 mm (i.d.) gradient
Tracer PAH column AcCN/H2O Smoked products Lyophilization, extraction/ 150 mm (L) 4.6 mm (i.d.) sonication in hexane, SPE column (85:15, v/v) purification (silica) hexane/ DMSO partition, concentration by Sep-Pak C18 plus cartridge
Extraction and preconcentration by Sep-Pak vac tC-18 cartridge
Alkaline saponification, Sep-Pak column purification (Florisil)
Naph, Ace, Fl, Smoked food Phe, An, Flu, Py, B[a]A, B[b]F, B[k]F, B[a]P, DB[ah]A, B[ghi]P, In[cd]P
Fluorescence Phe (Ex: 250 nm, Em: 365 nm) Flu (Ex: 285 nm, Em: 465 nm) Py (Ex: 270 nm, Em: 390 nm) B[a]A (Ex: 287 nm, Em: 388 nm) B[e]P (Ex: 290 nm, Em: 390 nm) B[a]P (Ex: 295 nm, Em: 405 nm) DB[a,h]A, B[g,h,i]P (Ex: 290 nm, Em: 418 nm) Fluorescence (Ex: 294 nm, Em: 404 nm)
Fluorescence Naph, Ace, Fl (Ex: 270 nm, Em: 340 nm) Acn (Ex: 320 nm, Em: 533 nm) Phe (Ex: 254 nm, Em: 375 nm) An, Flu (Ex: 260 nm, Em: 420 nm) Py, B[a]A, Chry (Ex: 254 nm, Em: 390 nm) B[b]F, B[k]F, B[a]P, DB[a,h]A, B[g,h,i]P (Ex: 260 nm, Em: 420 nm) In[c,d]P (Ex: 293 nm, Em: 498 nm) Fluorescence
[131]
[119]
[130]
[129]
2nd LC: Supelcosil LC-PAH AcCN/H2O 130 mm (L) 4.6 mm (i.d.) gradient
On-line LC-LC system: (normal-phase LC-solvent evaporator-reversed-phase analytical LC) 1st LC: column; silica phase (250 mm 4.6 mm) solvent; pentane,10% dichloromethane Interface: solvent evaporator
B[b]F, B[k]F, B[a]P, Edible oils DB[ah]A, B[ghi]P
Gradient
Mobile phase
Ultrasonic extraction (acetone), Reversed-phase C-18 AcCN/H2O HPLC preparation (silica column, column gradient 250 4.6 mm i.d.) 130 mm (L) 4.6 mm (i.d.)
130 mm (L) 4.6 mm (i.d.)
Stationary phase
Reference
[132, 133] (Ex: 275 nm, Em: 330 nm) Phe (Ex: 250 nm, Em: 365 nm) An (Ex: 250 nm, Em: 402 nm) Flu (Ex: 240 nm, Em: 470 nm) Py (Ex: 240 nm, Em: 385 nm) B[a]A, Chry (Ex: 270 nm, Em: 390 nm) B[b]F (Ex: 260 nm, Em: 430 nm) B[k]F, B[a]P (Ex: 255 nm, Em: 410 nm) DB[a,h]A, B[g,h,i]P (Ex: 300 nm, Em: 418 nm) Fluorescence [134] Naph, Ace, Fl (Ex: 275 nm, Em: 330 nm) Phe (Ex: 250 nm, Em: 365 nm) An (Ex: 250 nm, Em: 402 nm) Flu (Ex: 240 nm, Em: 470 nm) Py (Ex: 240 nm, Em: 385 nm) B[a]A (Ex: 270 nm, Em: 390 nm) B[b]F, B[k]F, B[a]P, diB[a,h]A, B[g,h,i]P, In[c,d]P (Ex: 290 nm, Em: 410 nm) Fluorescence (Ex: 290 nm, Em: [135] 440 nm)
Detection
Quantitative HPLC
Grapeseed oil Naph, Ace, Fl, Phe, An, Flu, Py, B[a]A, B[b]F, B[k]F, B[a]P, DB[ah]A, B[ghi]P, In[cd]P
Sample preparation
(silica column, 250 4.6 mm i.d.)
Sample type
Lipidic extracts B[a]A, Chry, B[b]F, B[k]F, B[a]P, DB[ah]A, B[ghi]P
Analyte
Table 5 (Continued )
Extraction by sonication (ethyl ether–methylene chloride)
Homogenization with cold NaOH solution, tandem SPE with Extrelut, propylsulfonic acid (PRS) column and SiO2 column
Non-fatty food Naph, Ace, Fl, (mashed Phe, An, Flu, potato, toasted Py, B[a]A, Chry, bread, tomato) B[b]F, B[k]F, B[e]P, B[a]P, DB[ah]A, B[ghi]P, In[cd]P
Flu, B[a]A, B[k]F, B[a]P, B[ghi]P
Cooked meat
Supercritical-fluid extraction using AcCN and CO2 as modifier
Naph, Ace, Phe, Toasted bread An, Flu, Py, Chry, B[e]P, B[a]P, DB[ah]A, B[ghi]P
ChromSpher PAH column AcCN/H2O 250 mm (L) 4.6 mm (i.d.) (84:16, v/v)
Hypersil Green PAH column AcCN/H2O 100 mm (L) 4.6 mm (i.d.) gradient
Hypersil Green PAH column AcCN/H2O 100 mm (L) 4.6 mm (i.d.) gradient Fluorescence Naph (Ex: 270 nm, Em: 335 nm) Ace (Ex: 285 nm, Em: 330 nm) Phe (Ex: 250 nm, Em: 365 nm) An (Ex: 254 nm, Em: 402 nm) Flu (Ex: 285 nm, Em: 465 nm) Py (Ex: 270 nm, Em: 390 nm) Chry (Ex: 270 nm, Em: 384 nm) B[e]P (Ex: 290 nm, Em: 390 nm) B[a]P (Ex: 295 nm, Em: 405 nm) DB[ah]A (Ex: 290 nm, Em: 395 nm) B[ghi]P (Ex: 300 nm, Em: 420 nm) Fluorescence Naph, Ace, Fl (Ex: 275 nm, Em: 325 nm) Phe, An (Ex: 250 nm, Em: 375 nm) Flu (Ex: 285 nm, Em: 465 nm) Py (Ex: 270 nm, Em: 390 nm) B[a]A, Chry (Ex: 270 nm, Em: 384 nm) B[e]P, B[b]F (Ex: 300 nm, Em: 440 nm) B[k]F (Ex: 305 nm, Em: 410 nm) B[a]P (Ex: 290 nm, Em: 405 nm) DB[ah]A, B[ghi]P (Ex: 290 nm, Em: 418 nm) In[c,d]P (Ex: 290 nm, Em: 498 nm) Fluorescence (Ex: 360 nm, Em: 460 nm)
[138]
[137]
[136]
Lyophilization, extraction through chromatographic column using pentane:dichloromethane(1:1), silica cartridge
Liquid–liquid extraction, GPC purification
Fishery product
Olive oils
Coffee
B[a]A, B[b]F, B[k]F, B[a]P, DB[ah]A, In[cd]P
Phe, An, Flu, Py, 11H-B[b]F, B[a]A, Chry, B[e]P, B[b]F, DB[ac]A, B[k]F, B[a]P, B[ghi]P, In[cd]P
Flu, B[b]F, B[a]P
SPE purification (polystyrene– divinylbenzene)
Sample preparation
Sample type
Analyte
Table 5 (Continued )
Mobile phase
Supelcosil LC-PAH AcCN/H2O 250 mm (L) 4.6 mm (i.d.) (60:40, v/v)
C18 Vydac AcCN/H2O 250 mm (L) 2.1 mm (i.d.) gradient
ChromSpher PAH AcCN/H2O gradient 100 mm (L) 4.6 mm (i.d.)
Stationary phase
Reference
Fluorescence [139] B[a]A (Ex: 270 nm, Em: 390 nm) B[b]F (Ex: 260 nm, Em: 430 nm) B[k]F (Ex: 256 nm, Em: 410 nm) B[a]P (Ex: 256 nm,Em: 410 nm) DB[ah]A (Ex: 300 nm, Em: 418 nm) In[cd]P (Ex: 300 nm, Em: 418 nm) Fluorescence (Ex: 264 nm) [140] Phe (Em: 364 nm), An (Em: 402 nm), Flu (Em: 444 nm), Py (Em: 384 nm), 11H-B[b]F (Em: 352 nm), B[a]A (Em: 396 nm), Chry (Em: 368 nm), B[e]P (Em: 384 nm), B[b]F (Em: 444 nm), DB[ac]A (Em: 380 nm), B[k]F (Em: 420 nm), B[a]P (Em: 404 nm), B[ghi]P (Em: 420 nm), In[cd]P (Em: 500 nm) Fluorescence [141] Flu (Ex: 230 nm, Em: 410 nm) B[b]F, B[a]P (Ex: 250 nm, Em: 420 nm)
Detection
Quantitative HPLC
Method
Phe, An, 3-MePhe, 1-MePhe, GC/MSEI Flu, Py, 2-MePy, 1-MePy, B[ghi]F, CP[cd]P, B[a]A, Chry+TriP, B[k]F, B[e]P, B[a]P, Pery, In[cd]P, B[ghi]P, Cor 3,6-DMePhe, CP[cd]P, B[a]A, GC/MSNICI B[b]F, B[j]F, B[k]F, B[e]P, B[a]P, Pery, In[cd]P, DB[a,c]A, DB[ah]A, Pic, B[ghi]P, Cor
Phe, An, Flu, Py, B[a]A, GC/MS Chry/TriP, B[b;j;k]F, B[a]F, B[e]P, B[a]P, Pery, In[cd]P, DB[a,h;a,c]A, B[ghi]P
AcCN sonication, extraction, partition into pentane, micro silic acid column cleanup
Plant material (grain sorghums) DB-5 60 m (L) 0.21 mm (i.d.) 0.25 mm (D)
SE-54 30 m (L) 0.21 mm (i.d.) 0.25 mm (D)
Column
Vegetable oils, smoked fish (a) Vegetable oils: cyclohexane DB-5 50 m (L) fused-silica products, mussels,oysters, extraction column bream (b) Smoked meat, bacon, fish, eel, tea, herbs, vegetables:saponification, cyclohexane extraction Back-extraction by dimethylformamide-H2O, addition of Na2SO4 solution, re-extraction by cyclohexane, silica gel cleanup, GPC cleanup SE-54 capillary column Eider duck (liver) Freeze-dried, ground with activated sodium sulfate, Soxhlet extraction (toluene), alkaline saponification, dimethylformamide cleanup, silica column cleanup 25 m (L) 0.32 mm (i.d.) Duck eggs Alkaline saponification, n-hexane extraction, water and saturated NaCl washing, dimethylformamide extraction, deactivated silica cleanup preparative TLC
AcCN sonication, extraction, partition into pentane, micro silic acid column cleanup
Sample preparation
Plant material (grain sorghums)
Sample type
[46]
EI mode
[143]
[144]
[142]
Ref.
Column temperature: 701C (2 min)-(201C/min)1251C-(41C/min)-2901C (15 min) Column temperature: 701C (2 min)-(201C/min)1251C-(41C/min)-2901C (15 min) 701C-(51C/min)-2801C
Operating conditions
Methods used for polycyclic aromatic hydrocarbon detection: gas chromatography (GC) and gas chromatography/mass spectrometry (GC-MS)
Naph, Ace, Acn, Fl, Phe, An, GC/FID Flu, Py, B[a]A, Chry, B[b]F, B[k]F, B[a]P, In[cd]P, DB[ah]A, B[ghi]P GC/MSEI
Analyte
Table 6
Sheep and goat (livers, kidneys), chicken (livers, eggs), cow and sheep (milk) Fish edible muscle
GC/MS
Phe, An, Flu, Py, B[a]A, Chry, B[b]F, B[k]F, B[a]P, B[ghi]P, In[cd]P, DB[ah]A
Naph, Ace, Acn, Fl, Phe, An, GC/MS Flu, Py, B[a]A, Chry, B[b]F, (HPLC) B[k]F, B[a]P, In[cd]P, DB[ah]A, B[ghi]P
Roasted lamb
Eggs, chicken, duck
GC/MSEI
GC/MSEI (HPLC)
Fish tissue
GC/PID
Naph, 1-MeNaph, Fl, Phe, Ace, Acn, 2,3-DMNaph, An, Flu, Py, Chry, B[a]A, B[b]F, 2-MeAn, B[k]F, B[a]P, Pery, 1-MePhe, In[cd]P, DB[ah]A, B[ghi]P Phe, An, 1-MePhe, Flu, Py, 2-MePy, B[ghi]F, B[a]A, Chry+TriP, B[k]F, B[e]P, B[a]P, Pery, In[cd]P, B[ghi]P, Cor
An, Phe, 9-MeAn, Flu, Py, Chry, B[a]P, DB[ah]A
Olive oil
GC/FID
An, Flu, Py, 11-B[a]F, TriP, B[e]P, B[ghi]P
Sample type
Method
Analyte
Table 6 (Continued ) Column
[147]
Toluene extraction by shaking or SE-54 HP-1(methyl silicone) Soxhlet extraction (toluene), saponification, centrifugation, dimethyl formamide cleanup extraction, deactivated silica gel column cleanup (100 10 mm) Chloroform–MeOH extraction, CBP-1 25 m 0.33 mm 180 1C-(51C/min)-2701C silica gel column cleanup, ion source, monitor TLC cleanup separator temperature: 2501C EI mode, 70 eV voltage Alkaline saponification, silica DB-I Column temperature: 1501Cgel column chromatography (31C/min)-1801C-(51C/ min)-2301C-(101C/ min)-2901C (9 min) GC/MS: Column temperature: GC/MS:SE-54 Dichloromethane extraction, 601C-(121C/min)-2951C 30 m 0.32 mm, column chromatography (6 min) splitless mode (alumina:silica) HPLC purification (Phenogel 100 column, 250 22.5 mm)
[111]
[149]
[148]
[146]
Column temperature: 501C(51C/min)-2951C (10 min)
Ref. [145]
Operating conditions Column temperature: 851C (1 min)-(251C/min)1801C-(71C/min)-3001C FID detector: 3001C
Partition into DMSO, backFused-silica SPB-1 capillary partitioning into cyclohexane, column filtration on silica 30 m (L) 0.25 mm (i.d.) gel+anhydrous Na2SO4, TLC on silica gel DB-5 30 m (L) 0.25 mm Alkaline saponification, (i.d.) 0.25 mm (D) acidification, extraction, adsorption chromatography, GPC purification
Sample preparation
Smoked foods
Polished rice
Liquid smoke flavorings
Naph, Ace, Acn, Fl, Phe, An, GC/MS Flu, Py, B[a]A, Chry, B[k]F, B[j]F, B[a]P, In[cd]P, DB[ah]A, B[ghi]P
Phe, An, Flu, Py, B[a]A, GC/MS (HPLC) Chry/TriP, B[b;j;k]F, B[a]F, B[e]P, B[a]P, Pery, In[cd]P, DB[a,h;a,c]A, B[ghi]P
GC/MS Naph, 2-MeNaph, 1MeNaph, 2,6-DMeNaph, 1,7-DMeNaph, 1,6DMeNaph, Fl, Phe, An, 3-MePhe, 2-MePhe, 2-MeAn, 9-MePhe, 1-MePhe, 9MeAn, DMePhe/An, Flu, Py, m-Ter, p-Ter, MeFlu/Py, B[a]A, Chry+TriP, B[b]F, B[k]F, B[a]F, B[e]P, B[a]P, Pery, In[cd]P, DBA, B[ghi]P Naph, 2-MeNaph, 1GC/MS MeNaph, 2,6-DMeNaph, 1,7-DMeNaph, 1,6DMeNaph, Fl, Phe, An, 3-MePhe, 2-MePhe, 2-MeAn, 9-MePhe, 1-MePhe, DMePhe/An, Flu, Py, m-Ter, p-Ter,
Liquid smoke flavorings
Seafoods
2-MeNaph, 1-MeNaph, Phe, GC/MS Py, Chry, B[a]A, B[b]F, B[a]P
Alkaline saponification, extraction (cyclohexane), cleanup by two SPE (silica) tubes
5% Phenylmethyl siloxane 60 m (L) 0.25 mm (i.d.) 0.25 mm (D)
Alkaline saponification, hexane DB-5ms 30 m (L) 0.25 mm (i.d.) 0.25 mm (D) extraction, silica gel column chromatography (elution with hexane), partition into acetonitrile Accelerated solvent extraction, Cross-linked 5% sulfuric acid treatment, phenylmethyl siloxane Florisil column cleanup column 30 m (L) 0.25 mm (i.d.) 0.25 mm (D) Dichloromethane sonication DB-35MS extraction, Soxhlet extraction, 30 m (L) 0.25 mm (i.d.) activated silica gel column chromato graphy with acetone/hexane 5% Phenylmethyl siloxane Alkaline saponification, 60 m (L) 0.25 mm extraction (cyclohexane), SPE (i.d.) 0.25 mm (D) cleanup (Florisil, silica)
[114]
[112,113]
Column temperature: 501C (0.5 min)-(81C/min)1301C-(51C/min)-2901C (50 min) EI mode, 70 eV voltage
Column temperature: 501C (0.5 min)-(81C/min)1301C-(51C/min)-2901C (50 min)
[152]
[151]
[150]
Column temperature: 1001C (2 min)-(51C/min)2801C (15 min) EI mode, SIM mode
Column temperature: 401C (1 min)-(121C/min)2501C-(51C/min)-3101C (3 min)
Column temperature: 501C (1 min)-(251C/min)1201C-(101C/min)3201C (6.5 min)
Method
Naph, 2-MeNaph, 1MeNaph, 2,6-DMeNaph, 1,7-DMeNaph, 1,6DMeNaph, 1,4+2,3DMeNaph, 1,5DMeNaph, DM/ EthylNaph, Ace, Acn, Fl, Phe, An, o-Ter, 3-MePhe, 2-MePhe, 2-MeAn, 9MePhe, 1-MePhe,
GC/MS
11H-B[a]F, MeFlu/Py, B[a]A, Chry+TriP, B[b]F, B[k]F, B[e]P, B[a]P, Pery, B[ghi]P Naph, Ace, Acn, Fl, Phe, An, GC/MSEI Flu, Py, B[a]A, Chry, B[b]F, B[k]F, B[a]P, In[cd]P, DB[ah]A, B[ghi]P
Analyte
Table 6 (Continued )
Smoked cheese
Honey
Sample type
Matrix solid-phase dispersion (mixture of Florisil and anhydrous sodium sulfate) extraction with hexane–ethyl acetate Sonication extraction, alkaline saponification, extraction, cleanup by SPE (silica) tube
Sample preparation
HP-5MS (5% phenylmethyl siloxane) 30 m (L) 0.25 mm (i.d.) 0.25 mm (D)
5% Phenylmethyl siloxane 30 m (L) 0.25 mm (i.d.)
Column
[153]
[154]
Column temperature: 501C (0.5 min)-(81C/min)1301C-(51C/min)-2901C (50 min)
Ref.
Column temperature: 801C (0.5 min)-(81C/min)2301C-(51C/min)-2801C (17 min)
Operating conditions
B[a]A, B[a]P, B[b]F, B[ghi]P, GC/MS Chry, B[k]F, DB[ah]A, In[cd]P, B[j]F, Cyclo[cd]P, DB[ae]P, DB[ah]P, DB[ai]P, DB[al]P, 5-methylchrysene
DMePhe, Flu, Py, m-Ter, p-Ter, 2-MeFlu, MeFlu, 1MeFlu+11H-B[a]F, 11HB[b]F, 11H-B[c]F, 1-MePy, B[a]A, Chry+TriP, MeB[a]An, 3-MeChry, 2-MeChry, 1-MeChry, DMeB[a]A, B[b]F, B[j+k]F, B[a]F, B[e]P, B[a]P, Pery, In[cd]P, DB[ah/ac]A, B[b]Chry, Picene, B[ghi]P, Anth, DBP Naph, Ace, Acn, Fl, Phe, An, GC/MSEI Flu, Py, B[a]A, Chry, B[b]F, B[k]F, B[a]P, In[cd]P, DB[ah]A, B[ghi]P
Primary smoke condensate
Human milk
Alkaline saponification, extraction (cyclohexane), cleanup by two SPE (silica) tubes
Liquid–liquid extraction, cleanup by size exclusion chromatography (Bio-Beads S-X3)
Column temperature: Varian FactorFour VF-5ms 701C (2 min)-(201C/ (5% phenyl 95% dimethyl min)-1201C-(41C/ polysiloxane) min)-3001C (5 min) 30 m (L) 0.25 mm (i.d.) 0.25 mm (D) Column temperature: HP-5MS SV (5% 601C (1 min)-(401C/ phenylmethyl siloxane) min)-2401C-(121C/ 30 m (L) 0.25 mm min)-3001C (21.5 min) (i.d.) 0.5 mm (D)
[156]
[155]
624
Katsumi Tamakawa
content. The analysis of samples with high fat content, e.g., fats, vegetable and mineral oils, requires the elimination of the lipids using a further purification process such as liquid–liquid partition, column chromatography, alkaline saponification/solvent extraction and gel permeation chromatography (GPC). In the procedure of liquid–liquid partition [143,144], an edible oil sample is at first dissolved into a non-polar organic solvent such as cyclohexane or n-hexane. Following this, target PAHs in the organic solvent are extracted with a polar solvent such as DMSO or a mixture of dimethylformamide/water, while most of the lipids in samples remain in the organic phase. After dilution with water to change the coefficient of partition between the two phases, PAHs are backextracted into cyclohexane. With this method sample mass can be reduced to 10% of the starting value. LLE procedure is advantageous in the case of simultaneously analysing both PAHs and the other environmental contaminants such as pesticides and PCDDs, which are unstable under harsh conditions such as the alkaline digestion method mentioned later. The Soxhlet extraction [127,130] has been widely used for the extraction of PAHs from environmental samples such as soil, sewage sludge and airborne particulates. In comparison with the liquid–liquid extraction in food analysis, Soxhlet extraction has the advantage of enabling the preparation of the extract without emulsification. However, this method requires from 6 to 24 h for extraction, and is too timeconsuming. Birkholtz et al. [157] recommended the Soxhlet extraction method with dichloromethane because alkaline digestion commonly used in food analysis is messy and cumbersome. An alternative to Soxhlet extraction is ultrasonic extraction, which has a much faster extraction time. Alkaline saponification/solvent extraction is the most commonly used method for PAHs analysis in foods. This method is generally applied to eliminate fat, pigments and other organic contaminants [100,115], which may interfere with the further analytical determination. Alkaline digestion is adopted as an extraction procedure in the official method proposed by the United States Food and Drug Administration (FDA) [158] and the Pharmaceutical Society of Japan [159]. As mentioned in Section 2, PAHs are relatively unstable. Therefore, attention should be paid to the analytical condition in order to perform an accurate analysis, because some PAHs might be labile in the harsh saponification conditions [110,159]. Takatsuki et al. [109] proposed the used Na2S as an antioxidant during the alkaline digestion to avoid the decomposition and to obtain good recoveries. They also indicated that B[a]P was easily decomposed by the coexistence of light, peroxide in aged ethyl ether and oxygen when absorbed on silica gel. Therefore, the following precautions are recommended in the food analysis of PAHs: (1) protection from light during all steps of analysis, (2) addition of Na2S to the alkaline digestion mixture as an antioxidant, (3) complete removal of the peroxide in ethyl ether before use, (4) quick column chromatography on silica gel and (5) prevention of air from coming into contact with the adsorbent [105,110].
Polycyclic Aromatic Hydrocarbons
625
Caffeine complexation is another extraction procedure using a caffeine–PAHs complex formation. Food samples are dissolved into cyclohexane, and mixed with a caffeine-formic acid solution to form caffeine–PAHs complex. The caffeine–PAHs complex is destroyed by addition of an aqueous sodium chloride solution. PAHs are, then, back-extracted with cyclohexane [160,161]. Moret et al. [161] evaluated the three extraction procedures for PAHs analysis — i.e., saponification, caffeine complexation and liquid–liquid partition with cyclohexane and dimethylformamide/water — on an olive oil sample. Squalene, which is one of the main components in olive oils containing 50% of the unsaponified fraction, interferes with the chromatographic detection of PAHs. A significant amount of squalene remained after the saponification method, whereas no appreciable amount of squalene was detected after the liquid–liquid partition. Among these methods, the liquid–liquid partition appeared to be the most applicable concerning time consumption, recoveries and repeatability. The caffeine complexation method presented the advantage of reducing the extraction time; however, the recovery of PAHs was comparatively low. Some promising methods for the extraction of PAHs from food were developed years ago. Supercritical fluid extraction (SFE) is an effective procedure to shorten extraction times with higher efficiency and lower consumption of organic solvents compared with traditional extraction procedures. As an extraction fluid, carbon dioxide is commonly used in SFE, mainly because of its mild supercritical condition (tc ¼ 31.11C, pc ¼ 7.38 MPa). SFE has found an extensive use in the field of PAHs analysis for environmental samples, such as soil, sediments and airborne particulates. However, there are a few applications for PAHs determination in food analysis. Vo-Dinh [162] determined PAHs in smoked and broiled fish. Kayali-Sayadi et al. [163] studied PAHs determination in toasted bread samples by SFE, using carbon dioxide and acetonitrile as modifier. Jarvenpaa et al. [127] applied SFE for the extraction of PAHs from smoked and broiled fish. Methanol was used as a modifier, because extraction of larger PAHs molecules by using carbon dioxide were insufficient. By using methanol, however, lipids were coeluted in greater amounts and interfered with the followed analysis of HPLC/UV detection. They adopted an SPE before HPLC determination. The overall extraction procedure was completed in 20 min. SFE has great potential in offering shorter extraction times with higher recoveries and lower consumption of organic solvents. Accelerated solvent extraction (ASE) is another promising procedure for extracting solid and semisolid samples. ASE uses conventional organic solvent at elevated temperatures and pressures to enhance the efficiency of the extraction procedure under closed conditions. ASE offers a lower cost per sample than the other conventional techniques such as Soxhlet and sonication by reducing solvent consumption by up to 90%. Wang et al. [151] showed that ASE reduced solvent consumption for extraction to 20–30 mL/aliquot and the time taken for extraction procedure was reduced to 10–20 min. Yusa et al. [163] evaluated the possibility of ASE as a fast alternative to saponification for the extraction of 12 PAHs from mussel tissue. The performance characteristics of the ASE (trueness: 70–110%;
626
Katsumi Tamakawa
precision: 4–14% and limit of quantification (LOQ): 0.1–0.25 mg/kg) meet the criteria by the European Union for quantitative methods of analysis for official control of organic residues and contaminants. Guille´n et al. [164] tried headspace solid-phase microextraction (HS-SPME) as a tool to estimate the contamination of smoked cheeses by PAHs. SPME is a quick and simple technique, based on the use of a fused-silica fibre coated with a phase where analytes can be retained. Sample amounts required for the analysis are very small and the use of solvents is not required. HS-SPME method has an advantage that the life expectancy of the fibre is longer because the fibre is not in contact with the sample directly. However, the selectivity and sensitivity of this method is strongly affected by the distribution equilibrium of analytes between air and the sample matrix. They showed that only PAHs with four aromatic rings or less were detected by this method. Compared with the results obtained by a conventional solvent extraction method, HS-SPME was found to be useful as a rapid screening method to distinguish among samples with different degrees of PAHs contamination.
4.2 Cleanup The extracts obtained by any of the procedures previously reported contain a considerable amount of substances that can interfere with the subsequent determination. Cleanup of the extracts is required to separate target PAHs from other components. So far, several cleanup methods for PAHs analysis, such as thin layer chromatography (TLC), column chromatography and an SPE cleanup, have been studied. Most of these processes, however, were not necessarily suitable for routine screening purposes, because chromatography usually requires column packing and large quantities of organic solvent as an eluant, and is consequently time-consuming. For routine analyses, a simplified, rapid and accurate process is essentially desirable. For this purpose, conventional chromatographic methods have been substituted by commercial SPE cartridges [122,165]. SPE cartridges have been commonly used for the purification of PAHs in environmental samples such as water [166,169] and airborne particulates [170– 172] and food samples [122,124,166,167,173,174]. Tsuji et al. [174] reported the use of Sep-Pak silica cartridges (Waters Assoc. Ltd.) for a simplified analysis of PAHs in sediment and shellfish. Tamakawa et al. [122] developed a simplified method for the analysis of the daily diet, sampled by the duplicate portion method, using a Sep-Pak silica cartridge. The procedure involves alkaline digestion with Na2S as an antioxidant, extraction with n-hexane, purification by Sep-Pak silica cartridge and HPLC with fluorometric detection. Recovery efficiencies and coefficients of variation (CV) were from 90.2% for An to 102.6% for Py and from 2.97% for B[a]A to 7.56% for B[a]P, respectively. Perfetti et al. [124] reported the determination of 12 PAHs (Ace, An, Flu, Py, B[a]A, Chry, B[b]F, B[k]F, B[a]P, DB[ah]P, B[ghi]P, In[cd]P) in seafood using an SPE cleanup (modified FAD method). After alkaline digestion, PAHs were partitioned into 1,1,2-trichloro-trifluoroethane, and then was cleaned up by SPE (alumina, silica and C18) cartridges before reversed-phase HPLC.
Polycyclic Aromatic Hydrocarbons
627
Average recoveries of PAHs from five matrices such as mussels and oysters ranged from 76% to 94%. Concerning beverages, Kayali-Sayadi et al. [136,173] reported a rapid determination of PAHs in tea infusion samples and coffee brew samples by HPLC based on SPE using Sep-Pak vac tC-18 cartridges. Reversed-phase cartridge is recommended for extraction of non-polar compounds in polar eluants such as water or water-containing solvent. Bishnoi et al. [174] reported a method for quantification of 16 PAHs in tea and coffee samples by HPLC. This method is based on LLE followed by cleanup with C-18 cartridge. Recoveries at different concentration levels were higher than 68%, and detection limit was found to be low (0.0006 ng) for An and highest (0.174 ng) for Naph with relative standard deviation between 0.4% and 7%. As the application of SPE enables the isolation of specific compounds by only the extraction process, this process is considered to be ideal for routine work. Size exclusion chromatography (SEC or GPC) is also applicable for the partial purification of PAHs. This is a method that is capable of separating substances by molecular size. SEC has been widely used for the purification and analysis of synthetic and biological polymers, such as proteins, polysaccharides, nucleic acids and lipids. This method, therefore, is often used to separate PAHs from lipids in different fatty matrixes. Purification of PAHs from biogenic interferences by SEC was first reported by Winkler et al. [168] in 1977 by using Sephadex and mStyragel as SEC phase. Bubba et al. [155] determined 16 PAHs in human milk by LLE, SEC packed with Bio-Beads S-X3 and GC-MS analysis. These laboratorypacked columns are unquestionably robust and of low cost, while rigid-bead commercial columns have some advantages in speed and resolution. Automated GPC systems recover a wide range of compounds with high reproducibility and reliably remove higher molecular weight interferences such as proteins, pigments and lipids. The SEC also seems to be ideal as a screening method for the quick estimation of the extent of PAHs contamination. Nyman et al. [166] compared the cleanups from the modified FDA method [124] mentioned earlier and the National Marine Fisheries Service (NMFS) method [173], followed by GC-MS determination of PAHs at levels from 1 to 5 ppb in seafood. In the modified FDA method, seafood extracts were purified by three types of SPE cartridges (silica, alumina and C18) after LLE. In the NMFS method, seafood extracts were purified using silica gel/alumina column chromatography followed by gel permeation HPLC. Average recoveries ranged from 73% to 144% for the modified FDA method and 63% to 106% for the NMFS method. Years ago, donor–acceptor complex chromatography (DACC) gained popularity for PAHs analysis [175–179]. Perrin et al. [175] developed a new cleanup procedure for the analysis of PAHs in edible oils and fats using DACC. PAHs are generally electron donors and strongly interact with DACC stationary phases while the other matrix components is not retained and washed to waste. The cleanup step is achieved by DACC with a tetrachlorophthalimidopropyl (TCPI) modified silica. Neutral lipid and the other interferents in PAH analysis are eluted with a mixture of hexane/methyl-tert-butylether. Then, PAHs are eluted
628
Katsumi Tamakawa
by methylene chloride and analysed by HPLC with fluorescence detection. The strength of PAHs–DACC complex formations increases with the number of aromatic rings. The entire procedure required 2 h for a determination, and was estimated to be 5–10 times faster than those of typical LLE procedures. Off-line methods for cleanup are generally laborious and time-consuming. Van Stijin et al. [128] proposed an automated on-line method using LC-LC coupling of a cleanup DACC column to an analytical column for the determination of PAHs in edible oils and fats. The limitations of quantification are o0.1 mg/kg for individual PAHs. Total anlysis time per sample is approximately 80 min, compared to 8–10 h with traditional methods.
4.3 Determination Analytical methods for PAHs in food previously reported are summarized in Tables 5 and 6. There have been many methods reported on the determination of PAH concentrations in food samples, mostly based on a variety of chromatographies, such as TLC [180,181], column chromatography [182–185], GC [145] coupled with MS [111–113,149,150,152] and HPLC [127] with a fluorescence detector [110,119,123,124,126,128,131–136,186]. In the past, TLC was commonly used for the detection of some PAHs such as B[a]P. This method has the advantage of being inexpensive, and is a quick analytical technique. However, the separation efficiency is not high enough to carry out the simultaneous determination of many PAHs. Borneff et al. [187] improved this weak point by using two-dimensional processes. As an alternative to TLC, HPLC and GC are superior because of their separation efficiency and reproducibility. As most PAHs have strong fluorescence, HPLC coupled with fluorescence spectrometry is a promising method for the routine screening purpose of PAHs, because of its sensitivity and selectivity. HPLC has some advantages in detecting PAHs in routine analysis. This technique is generally carried out under a normal temperature (room temperature B701C), there is, therefore, no concern about thermal decomposition, which takes place in GC analysis, or about vaporization, as in the TLC procedure. Moreover, even high-molecular-weight PAHs, which cannot be detected by the GC method, can be identified by the HPLC method. Resolution efficiency of HPLC is generally superior to that of TLC and column chromatography and inferior to that of the GC method, especially in the analysis of low-molecular-weight PAHs. Nevertheless, in the separation of some PAHs such as B[a]P and B[e]P, HPLC shows excellent resolution, compared with the GC analysis. The linearity of calibration curves of HPLC with the fluorescence detector is satisfactory, ranging from nanograms to the order of micrograms. The sensitivity and specificity are also sufficient to detect PAHs in the environment. Wavelength-programmed detection system, which changes the excitation and emission wavelength to the optimal values automatically in the time preset during a chromatographic run, has been currently used for the analysis of PAHs. A chromatogram of a standard PAHs mixture by HPLC with the fluorescence
629
Polycyclic Aromatic Hydrocarbons
detector is shown in Figure 3 [188]. This automated system is a powerful technique for routine analysis of food samples [125,128,129]. A variety of separation columns for HPLC have been commercially available. Among them, reverse-phase column such as the octadecyl-bonded column is the most frequently used, because of its high-resolution efficiency for the target compounds. By using a reverse-phase column, the molecular sizes of the PAHs can be estimated from their retention times on the HPLC chart.
11 5
Fluorescence
60.00
12
40.00
3
9 8
20.00 2
1
4
6
7
13
10
14 15
0.00 0.00
4.00
2.00
6.00
8.00
10.00
(A) Gradient of the mobile phase
Time (min) 0 12 28
40
60
b
40
40
60
c
b
a 60 (B) Gradient profile 50
10 12
c
20
30
14.00
16.00
18.00
20.00
22.00
24.00
26.00
28.00 min.
(C) Program of excitation and emission wavelength pairs
Water Acetonitrile Gradient (%) (%) Profile 40 60 100 a 0
%100
12.00
40 min.
Retention time
Ex (nm)
Em (nm)
1 Naphthalene
6.9
224
330
2 3 4 5 6 7 8 9
10.1 10.8 12.2 13.4 14.2 14.7 15.9 16.5
280
320
250 249 281 270
350 380 436 378
270
385
290
410
297
473
No.
PAHs
Acenaphthene Fluorene Phenanthrene Anthracene Fluoranthene Pyrene Benz[a]anthracene Chrysene
10 Benzo[b]fluorantheneb
18.0
11 Benzo[k]fluoranthene Benzo a]pyrene 12 Benzo[ 13 Dibebz[ah]anthracene
19.1 20.6 22.3
14 Benzo[ghi]perylene
24.3
15 Indeno[1,2,3-cd ] pyrene
25.8
28
Figure 3 Chromatogram of standard mixture of PAHs by HPLC with wavelength-programmed fluorescence detection system. Conditions: SUPELCOSIL LC-PAH column (4.6 250 mm, 3 mm); temperature, 271C; mobile-phase condition (A); gradient profile (B) and pairs program for fluorimetric detection (C). Reproduced with permission from Ref. [188].
630
Katsumi Tamakawa
A variety of GC techniques coupled with various detection methods have been developed for PAHs analysis. Poster et al. [189] critically reviewed GC techniques used for the determination of PAHs in environmental samples and foodstuffs. A high-resolution GC with capillary column is commonly used for PAHs analysis. Typical detectors equipped in GC apparatus are an FID, a photoionization detector (PID) and a quadrupole electron impact mass spectrometry (EI-MS). FID has broad linearity, and is generally non-selective to chemicals. As the response of FID is proportional to the number of carbons, one can quantify compounds in the same group even if calibrant for matching is not available. PID is more selective for aromatic hydrocarbons or organo-heteroatom species but is not sufficiently responsive to some alkylbenzenes [146]. As the selectivity of these detector is not necessarily enough, further purification is required for obtaining the best chromatographic conditions. Detection of PAHs is most commonly accomplished by EI-MS in the selected ion monitoring (SIM) mode. GC/EI-MS is probably the most used for its selectivity, and sensitivity. The identification of PAHs by GC/MS in SIM mode is based on main ions of the characteristic mass spectrum of each compound with the relative abundance of the other ions selected for each PAHs. Typical GC/MS (EI-SIM) chromatogram is shown in Figure 4. Nemoto et al. [150] developed a process to determine petroleum-related contaminants in seafoods using GC-MS (EI-SIM). The detection limits were 2B3 ppb for n-alkane, 0.1B0.2 ppb for PAHs. Albero et al. [153] developed multiresidue method for the determination of 16 PAHs in honey by matrix solidphase dispersion (MSPD) and GC-MS (EI-SIM). Average recoveries for all the PAHs studied were in the range 80–101%, with relative standard deviations of 6–15%. Negative ion chemical ionization mass spectrometry (NCI-MS) is known as a sensitive and selective method for the determination of some kinds of PAHs and alkylated PAHs [125]. Hilpert [190] reported that the molecular anion for B[a]P
MCounts 125 100 75 50 25 0
4 3
10
78 5 6
11
9
13
2
1
12
14 5.0
7.5
10.0
12.5
15.0
15
16
17.5 minutes
Figure 4 Typical GC/MS (EI-SIM) chromatograms of standard solution containing 16 PAHs with corresponding peaks labeled as 1, benzo[k]fluoranthene; 2, acenaphtylene; 3, acenaphthene; 4, fluorene; 5, phenanthrene; 6, anthracene; 7, fluoranthene; 8, pyrene; 9, benz[a]anthracene; 10, chrysene; 11, benzo[b]fluoranthene; 12, benzo[k]fluoranthene; 13, benzo[a]pyrene; 14, indeno[1,2,3-cd]pyrene; 15, dibenz[a,h]anthracene and 16, benzo[ghi]perylene.
Polycyclic Aromatic Hydrocarbons
631
was approximately 1,000 times more abundant than that of B[e]P and that of Flu was 100 times more abundant than that of Py. Time-of-flight mass spectrometry in combination with capillary gas chromatography (GC-TOF-MS) is another powerful technique with limits of detection in the low picogram range. Vreuls et al. [191] evaluated the spectrum storage rate, linearity of response and detection limits of GC-TOF-MS for organic microcontaminants, including PAHs, in a sediment and boiled tea [192]. For these analytes, GC-TOF-MS provided good linearity in the range 2 pg–1 ng [192]. Because of its higher mass resolving power, TOF-MS can enable better signal-tonoise ratios than quadrupole analyses. As the stationary phases of separation column, the methylpolysiloxanes, in particular SE-52 (5% phenyl-substituted) and SE-54 (5% phenyl-, 1% vinyl-substituted), are commonly used for PAHs analysis. SE-30, OV-101 (unsubstituted) and OV-17 (50% phenyl-substituted) are also used. Fused silica capillary columns, which have an excellent resolution (eq. 3,000 plates per meter) and can separate more than 100 PAHs in complex mixtures, are commercially available. Concerning the comparison among food analysis of PAHs, Simko and Bruncova [125] reported that there were statistically no differences in analytical data of B[a]P in the liquid smoke preparations between HPLC with fluorescence detection and GC-MS (EI-SIM) method. However, Chiu et al. [129] demonstrated the differences between analytical data using HPLC with UV, fluorescence detection and those by GC-MS using ion-trap detection (ITD). Limits of detection of fluorescence detection were 20–320 times lower than that of UV detection, and 1–50 times lower than that of ITD. They showed that PAHs concentration detected by HPLC were generally lower than those by GC-MS/ITD, and that the presence of impurities, such as aliphatic hydrocarbons and fatty acid esters, may interfere with the identification and quantification of PAHs by HPLC. Simon et al. [192] reported the result of an intercomparison of 15 Europeanpriority PAHs analysis among 17 laboratories to validate an analytical method for monitoring use. The methods tested were based on GC-MS/SIM of cyclohexane extract with SPE through silica gel. The recoveries varied between 50% and 85%, except those for cyclo[cd]P, DB[ai]P and DB[ah]P. For B[a]P, the validated analytical range covered 5–20 mg/kg, and for B[a]A 10–25 mg/kg. This method, therefore, was recognized to be suitable for monitoring B[a]P and B[a]A at their maximum permitted levels of 10 and 20 mg/kg, respectively. Three analytes, B[b]F, B[j]F and B[k]F could not be separated by all of the participants. To simplify the analysis, an on-line combination of LC, GC and MS has been used. The first on-line LC-capillary GC system was developed by Majors in 1980 [193], who determined athrazine in sorghum by using a conventional LC connected to a GC autosampler used as the interface. Some reviews have been reported about the various LC-GC transfer systems and their applications [194–197]. The direct introduction of a large amount of solvent into GC requires the use of special techniques to remove the solvent from the sample, leaving the solute in a sharp band at the entrance of the separation column. Several interfaces have
632
Katsumi Tamakawa
been proposed for the LC-GC coupling. Among them, on-column interface based on retention gap technique [198,199], loop-type interface by concurrent eluant evaporation [198–202] and vaporizer interface [203,204] are commonly used today. Normal-phase chromatography (NPLC) and SEC are more easily coupled with GC than reversed-phase liquid chromatography (RPLC). Concerning PAHs in edible oils, Moret et al. [205–207] reported an on-line LC-LC and LC-LC-GC system for the analysis of PAHs. The system involves coupled NP-RP HPLC and an interface. The main difficulty in coupled HPLC is the necessity to perform a mobile phase exchange between immiscible different solvent systems. They developed an on-line solvent evaporator, which work on the principles of concurrent eluant evaporation and vapor overflow with two additional 10-port valves. Recoveries and repeatability of heavy PAHs, such as B[b]F, B[k]F, B[a]P, DB[ah]A and B[ghi]P, were reported to be above 80% and 2.4–5.7%, respectively. Van der Wielen et al. [208] applied LC-LC with fluorescence detection system for the quantification of B[a]P in edible oils and food supplements. According to the author, the system has good performance characteristics and produced good results in proficiency tests. From 2002 to 2004, about 1,350 samples of oils and food supplements were analysed using this method to test the level of B[a]P. Vreuls et al. [209] reported the on-line coupling of HPLC, capillary GC and MS for the determination and identification of PAHs in vegetable oils. The LC fraction, containing PAHs, was transferred to the GC using a loop-type interface. After solvent evaporation through the solvent vapor exit, the compounds were introduced into the GC-MS for detection and identification. The total setup allowed the direct analysis of oil samples after dilution in n-pentane without any purification. Detection limits are about 40 pg (20 ppb) in the full-scan mode and about 1 pg (0.5 ppb) with SIM. Hyphenated techniques, such as LC-GC and LC-LC-GC for PAHs determination in oils, are dealt with in a review by Moret et al. [210]. Shimmo et al. [211,212] reviewed the LC-GC/MS coupled with on-line SFE as the extraction technique in atmospheric particles. On-line procedures have many advantages of being automated and minimizing sampling losses and contaminations, besides simplifying the sample purification. The NPLC-GC methods already available are fairly simple to use [196]. However, on-line RPLC-GC system, which is essential for PAHs analysis, is complicated and has not necessarily become a routine method despite many encouraging developments [196].
5. OCCURRENCES OF PAHS IN FOOD Reports on the concentrations of individual PAHs in food are summarized in Table 7. Many PAHs are detected in substantial quantities in a variety of food. Occurrence of PAHs in vegetables is influenced by the fallout of airborne particulates. In contrast, uptake of PAHs from soils via the root system appears to be negligible. Spinach and lettuce, which have large and rough leaf surfaces, are
7.9
70 [214]
0.3–8.3
1.8–7.5 3.4–10.4
[213]
Reference
2.8–9.1
7.7 4.2 62 1 117
0.5–10.8 0.3–6.2
15
Netherlands (1984)
Sweden (1982)
o0.1–0.3 0.7–4.6 0.5–7.3
Kale
Lettuce
[215]
0.8
0.4 0.2 0.1 0.1
Netherlands (1990)
Potatoes
[182]
2.22 0.28
nd 1.26 nd
[182]
4.5 1.0
nr 1.1 nd
0.3
0.1
0.02 0.09
0.1 0.2
1.4
0.11 0.05
0.10
Grilled vegetable (average)
Japan (1990)
Vegetable (average)
Fruit and vegetables (mg/kg)
Polycyclic aromatic hydrocarbon concentrations in foods
Acenaphthene Acenaphtylene Anthracene Benz[a]anthracene Benzo[b]fluoranthene Benzo[k]fluoranthene Benzo[ghi]perylene Benzo[a]pyrene Chrysene Dibenz[ah]anthracene Fluoranthene Fluorene Indeno[1,2,3-cd]pyrene Naphthalene Phenanthrene Pyrene
Table 7
[216]
0.9–18
0.14–0.72
0.13–2.1 0.05–1.4
0.09–0.19
Finland (1986)
Lettuce
[130]
0.08–0.75
Greek (1998)
Lettuce
[217]
0.630 0.280 0.150 1.380 1.600
0.810 0.070 1.050 0.520 0.240 0.198 0.200 0.610 0.110 0.550
Egypt (2006)
Lettuce (average, ppb)
Polycyclic Aromatic Hydrocarbons
633
White flour
nr nr 0.04–0.19 0.02–0.06 0.03–0.08 0.06–0.19 0.02–0.09 nr o0.01–0.01 0.07–0.40 nr 0.06–0.24
0.04–0.88 [218]
nr
nr 0.06–0.15 0.02–0.05 0.02–0.07 0.06–0.08 0.03–0.05 nr o0.01 0.22–0.60 nr 0.08–0.15
nr 0.26–1.18
[218]
Reference
United Kingdom (1983)
Breakfast cereal
Acenaphthene Acenaphtylene Anthracene Benz[a]anthracene Benzo[b]fluoranthene Benzo[k]fluoranthene Benzo[ghi]perylene Benzo[a]pyrene Chrysene Dibenz[ah]anthracene Fluoranthene Fluorene Indeno[1,2,3-cd]pyrene Naphthalene Phenanthrene Pyrene
Table 7 (Continued)
[219]
2.6–8.5
3.0
[219]
2.8
[219]
1.1–48
nd–0.4
nd–1.2 0.8–26
2.9
3.0 1.5–7.4
0.1–4.2 0.1–0.5
Barley malt
nd–0.3
0.4
Canada (1984)
Whole grain oats
0.1
0.3–0.8 0.1/0.2
Wheat
Cereals (mg/kg)
[220]
0.38–0.62
0.01–0.02 0.58–0.69 nr 0.24–0.33 nr
nr 0.11–0.21 0.07–0.09 0.1–0.14 0.13–0.20 0.10–0.12
United Kingdom (1987)
High bran and granary bread
[221]
1.6/5.4
1.5/13 2.3/2.7
0.3/0.4
1.3 o0.1/0.2
0.7
Finland (1988)
Oats
[215]
o2.0
1.0
o0.3 0.2 0/2 0.1 o0.7 0.1 o0.4
United Kingdom (1990)
Bread
634 Katsumi Tamakawa
[218]
[222]
[222]
nd–0.33
nd–37
Reference
tr–0.39 tr–0.35
nd–25 nd–18
0.79
tr–0.09
nd–86
0.14 0.13 0.04 0.12 0.13 0.65 0.03 0.1
United Kingdom (1983)
Acenaphthene Acenaphtylene Anthracene Benz[a]anthracene Benzo[b]fluoranthene Benzo[k]fluoranthene Benzo[ghi]perylene Benzo[a]pyrene Chrysene Dibenz[ah]anthracene Fluoranthene Fluorene Indeno[1,2,3-cd]pyrene Naphthalene Phenanthrene Pyrene
United Kingdom (1982)
Fish (smoked) Fish Fish (unsmoked)
[143]
2.1–5.1 2.6–12.4
1.9–19.6 3.2–11.2 [143]
0.3–0.6
5.1–17.5
4.5–13.5 0.2–1.2
0.3–0.8 0.2–1.0
nd–0.6 0.8–3.0
0.3–1.5 0.3–1.7
nd–1.9 0.8–5.7
Germany (1990)
[223]
65.3 20.5
1.1
21.0 2.5 1.2 0.5 0.7 1.2 2.5 o0.1 26.0
Germany (1996)
[111]
1.1, 1.2 1.0, 1.0 0.7, 0.8 0.3, 0.4 0.3, 0.5 0.3, 0.5 0.2, 0.5 0.7, 0.9 1.6, 1.9 0.1, 0.1 1.5, 1.5 5.0, 5.5 0.1, 0.1 19.6, 20.4 13.0, 14.0 1.7, 1.8
Yemen (1997)
Sea mussels Oysters Fish (smoked) Fish (canned) (fresh and canned)
Fish and marine products(mg/kg)
[149]
3.5
1.6
1.8
0.9 1.3 2 0.7 0.9 1.4 2.9
Netherlands (1997)
Fish
Polycyclic Aromatic Hydrocarbons
635
1.7 0.3–0.9
[158]
Reference
0.2–0.7
0.1
0.5 0.1–0.2
United States (1984)
Smoked sausage
Acenaphthene Acenaphtylene Anthracene Benz[a]anthracene Benzo[b]fluoranthene Benzo[k]fluoranthene Benzo[ghi]perylene Benzo[a]pyrene Chrysene Dibenz[ah]anthracene Fluoranthene Fluorene Indeno[1,2,3-cd]pyrene Naphthalene Phenanthrene Pyrene
Table 7 (Continued)
Meat and meat product
[215]
0.04–0.38
0.03–0.31 0.02–0.45
0.02–0.64
[215]
0.7
1.1
0.9 0.5 1 0.2 0.6 0.6 0.6
Netherlands (1990)
Smoked beef
Sheep milk
[149]
10.0 139.3
47.43 14.5 [149]
nd
nd 3.0 2.1 nd nd 1.6 21.5 nd 14.2
nd
100 3.63 6 2 nd 3.25 6.36 nd 10.5
Kuwait (1997)
Chichen liver
Meat and dairy products (mg/kg)
[183]
0.06 0.37
0.15 0.07
0.01
0.01
Japan (1999)
Milk (raw)
[217]
0.28–10.37 0.36–44.48 0.12–7.04 1.17 0.09–0.54 1.57(j+k) 0.49 0.52 0.11(+TriPhen) 0.34(+DB[ac]A) 0.44–5.22 0.75–37.86 0.44 9.32–175.74 1.93–42.90 0.54–4.83
Spain (2004)
Smoked cheese
[154]
0–2.34
0–1.58 0–1.26 0–3.93
0–11.90
Poland (2005)
Heat-treated meat
636 Katsumi Tamakawa
nd–4.2 nd–4.1
0.2–16.1 nd–4.3 nd–69.4 0.1–13.6
0.5 0.7
3.1
0.4
3.8 2.6
[224]
Reference [143]
nd–4.8 nd–6.1
0.3 0.9
[225]
0.29–6.03
0.49–9.14
0.16–3.0 0.20–3.40 0.38–5.21 0.19–6.0 0.26–7.36 0.05–1.02 0.09–4.50
0.22–3.98
[46]
4–41 2–14
3–15 nd
nd–4
Italy (1991)
United Kingdom (1991)
Germany (1990)
Germany (1988)
Acenaphthene Acenaphtylene Anthracene Benz[a]anthracene Benzo[e]pyrene Benzo[b]fluoranthene Benzo[k]fluoranthene Benzo[ghi]perylene Benzo[a]pyrene Chrysene Dibenz[ah]anthracene Fluoranthene Fluorene Indeno[1,2,3-cd]pyrene Naphthalene Phenanthrene Pyrene
Olive Oliz
Margarine
Vegetable oils (olive, saffower, wheat germ)
Sunflower
[206]
tr–1.330 tr–0.476 tr–0.735 tr–1.210 tr–9.35 tr–0.258 tr–52.70 0.56–4.57 tr–0.63 tr–22.4 1.7–35.0 0.4–27.9
tr–3.01 tr–10.30
Olive oil (refine+virgin) (ppb)
[206]
0.618–1.398 0.229–0.458 0.648–1.853 0.460–1.335 0.66–1.47 o0.01–0.104 o0.01–4.38 o0.01–0.57 0.288–1.960 o0.01–6.4 0.4–6.7 o0.01–4.2
o0.01–0.46 0.355–0.565
Italy (1997)
Extra virgin olive oil (ppb)
Vegetable oils (mg/kg)
[140]
o0.5–6.7
o0.3–1.9
o0.2–0.46 o0.5–13.0 o0.1–5.2 o0.05–1.6 o0.08–1.9 o0.09–6.2
Spain (2005)
Olive oils
[226]
0.8 1.0 0.2 1.4 0.5 1.2 1.3 0.9 0.1 7.1 2.5 1.2 7.9 9.4 8.2
0.4
Italy (2005)
Vegetable oils from canned vegetables and oil-based sause
Polycyclic Aromatic Hydrocarbons
637
[215]
0.4
0.05 0.08
United Kingdom (1991)
Netherlands (1990)
[225]
0.02–0.24
o0.08
0.01–0.02 o0.01 o0.01–0.01 o0.01–0.02 o0.01 0.02–0.03 o0.01–0.01 0.03–0.19
Whisky
Soup
Notes: nd, not detected; nr, not reported and tr, trace.
Reference
Acenaphthene Acenaphtylene Anthracene Benz[a]anthracene Benzo[b]fluoranthene Benzo[k]fluoranthene Benzo[ghi]perylene Benzo[a]pyrene Chrysene Dibenz[ah]anthracene Fluoranthene Fluorene Indeno[1,2,3-cd]pyrene Naphthalene Phenanthrene Pyrene
Table 7 (Continued)
[119]
0.119–0.658 0.0184–0.168
0.0023–0.0237 0.0042–0.0301
0.0056–0.0273 0.0021–0.0238
0.0028–0.0434
Spain (1998)
Tea infusion (mg/L)
[184]
nd–3.79 nd–0.28
nd–0.03 nd–2.09 nd–0.49
nd–0.68
nd–0.01
nd–0.10 nd–0.03
nd
Japan (2000)
Soy sauce (ppb)
Others (mg/kg)
[114]
5.21–172.77 0.58–6.07 0.17–0.62
0.15–0.60 0.72–15.07
0.41–1.75 0.05–0.24 0.07 0.05–0.07 0.02–0.08 0.04–0.06
Smoke flavoring
[113]
43.4 336.9 1.6 678.8 627 33.5
113.7 4.1 1.6 1.7 1.9 2.8 3.3
Spain (2000)
Smoke flavoring
[112]
0.20–43.26 0.62–380.45 0.38–1.57 9.74–677.55 0.94–664.92 0.16–33.50
8.81–118.36 0.07–4.41 0.60–1.48 0.78–1.72 0.63–1.94 0.27–0.62
Smoke flavoring
[155]
nd nd nd 0.25 1.06 nd 4.7 0.553 0.620
2.72 6.95 0.616 0.974 0.560 0.114
Italy (2005)
Human milk
638 Katsumi Tamakawa
Polycyclic Aromatic Hydrocarbons
639
often highly contaminated by PAHs, maybe due to deposition from the ambient air [227]. In the neighborhood of industrial areas or close to an emission source such as highway, concentrations of PAHs detected in soil and plant surfaces are higher. As shown in Table 7, high-level contaminations of PAHs were detected in lettuce grown close to a highway in Sweden [213]. Kale, studied by Vaessen et al. [214] in Netherlands, contained high concentrations of Flu (117 mg/kg), Py (70 mg/kg), Chry (62 mg /kg) and B[a]P (15 mg/kg). Predominant differences of the contamination level of PAHs in vegetables may be attributed to variation in the growing location and seasons. Tateno [182] examined PAHs produced from grilled vegetables, i.e., small sweet pepper, green pepper, pumpkin, eggplant, Welsh onion, onion, corn, sweet potato, potato, shiitake mushroom, shimeji mushrooms and matsutake mushroom (Table 7). Higher amounts of carcinogenic PAHs were detected after grilling than in raw vegetables. Zohair [217] reported the effect of different oxidants to eliminate PAHs from naturally contaminated carrots. Midribs of cabbage leaves solution were the most efficient way to remove PAHs, followed by H2O2 and KMnO4 solution. The removal efficiencies of the total PAHs ranged from 65.5% to 97.8% and from 79.4% to 99.9% at 4% and 8% concentrations of oxidative materials, respectively. The data of individual PAHs in fish, meat and dairy products are shown in Table 7. A high concentration was observed in sheep milk studied in Kuwait [149]. Comparatively high-level contaminations of PAHs were detected in smoked cheese [222]. The levels of PAHs found in vegetable oils are also listed in Table 7. Vegetable oils and fats are another major source of PAHs in the diet. Moret et al. [228] reported the concentration of 14 PAHs in olive oil samples. According to the author, the amount of B[a]P and total PAHs in olive oils ranges from trace to 1.210 mg/kg and from 2.946 to 143.124 mg/kg, respectively. Menichini et al. [145] reported the concentrations of 28 PAHs in olive oils and virgin olive oils found on the Italian markets. Data showed that the 3- and 4-ring PAHs, which are the most abundant in the environment, were present in all samples, no significant differences were observed between two kinds of olive oils. The amounts of Phe, Py and Flu ranged from 4 to 41 mg/kg, 2 to 14 mg/kg and 3 to 15 mg/kg, respectively. Moret et al. [226] investigated 16 PAHs in 62 samples of vegetable oils from canned vegetables and fish and oil-based sauces. The contribution of B[a]P to the total genotoxic heavy PAH content ranges from 8.2% to 27.2% and from 10.3% to 26.7% in oil samples from vegetable and fish products, respectively. The percentage of B[a]P to TEQs varies between 45.5% and 85.4% for the oil samples from vegetable products and between 48.1% and 86.0% for the oil samples from canned fish. Despite the objection to the TEF approach from the toxicological point of view, this model is commonly used for the estimation of contribution of some target PAHs, especially B[a]P or B[a]A, to carcinogenic potentials of sample foods [229,230]. Recently, Spain, Italy, Portugal and Greece have produced legislation limiting the concentration of the following eight heavy PAHs: B[a]A, B[e]P, B[b]F, B[k]F, DB[ah]A, B[a]P, B[ghi]P and In[cd]P. A maximum limit value of 2 ppb for each
640
Katsumi Tamakawa
single PAH and 5 ppb for the sum of these eight PAHs were established. LopezAbente et al. [86] reported PAHs in pomace oil samples obtained from different producers in Spain. Five of the 25 samples analysed were outside of the tolerated limits. A close relationship was observed between B[b]F and B[a]P, which were simultaneously under or over the 2 ng/g limit regulated for single PAH. Speer and Montag [224] showed that PAHs contamination in vegetable oils is mainly attributed to the drying processes of the seeds by using combustion gases, because vegetable oils were naturally free of PAHs. The oil refining process is very useful for reducing the amount of these contaminants. Heavy PAHs with more than four aromatic rings are mainly removed by charcoal treatment, whereas light PAHs are generally reduced by the deodorization process [231]. Guillen et al. [112–114] reported the 34 PAHs levels of commercial liquid flavorings, used in the European food industry. The concentrations of lower molecular weight PAHs were much higher than those of the higher molecular weight PAHs. B[a]P levels detected in these samples did not exceed the limit concentration (10 mg/kg) fixed by the FAO/WHO [220]. As for the generation of PAHs in liquid smoke flavorings, Guillen et al. [112] showed that poplar wood generated a large amount of PAHs rather than oak, cherry tree and beech samples. Human milk is a paramount biomarker for assessing the individual exposure to pollution, because PAHs have lipophilic nature and accordingly are liable to be accumulated in fat globules of milk. Bubba et al. [155] studied PAHs concentration in 10 human milk samples collected from health, non-smoking, Italian primiparae, living in rural or low-traffic zones (Table 7). A great variability in the qualitative and quantitative PAHs composition was observed. PAHs having the greatest volatilities (Naph, Ace, Acn and Fl) were detected at the highest mean concentration (1.06–6.95 mg/kg milk). PAHs with more than three aromatic rings showed lower mean concentrations (0.114–0.974 mg/kg milk) and B[a]P was never detected. Cooking (such as grilling, roasting and frying) and processing (such as smoking and drying) are recognized as the major sources of PAHs in food. PAH formation is dependent upon the fat content of the meat, cooking time and heating temperature. Chen and Lin [232] detected the highest amounts of carcinogenic PAH in smoked duck breast sample (53 mg/kg). Mottier et al. [233] reported high concentrations of carcinogenic PAHs (14 mg/kg) in heavily barbecued lamb sausage. Doremire et al. [234] reported the highest concentration of B[a]P (130 mg/kg) in cooked fatty beef. The significantly higher level of PAHs contamination may play a carcinogenic role. Sinha et al. [87] showed the relationship between dietary intake of B[a]P and colorectal adenoma risk by a clinic-based case-control study. Using multivariate analysis, increased risk of colorectal adenomas seemed to be strongly associated with B[a]P intake estimated from all foods. Tu¨rkdog˘an et al. [235] showed the carcinogenic role of traditional foods baked or cooked using animal manure or fuel oil in eastern Turkey (Van region) because of high B[a]P and B[a]A levels. The most important factor affecting human risk is, however, not the concentration itself but the daily intake of these compounds. Table 8 shows a comparison of the daily intake of PAHs from different studies.
a
[218]
Reference
Lower- and upper-bound values.
1.1
0.21 0.18 0.06 0.21 0.25 0.50 0.03 0.99
Market basket method
Sampling method
Acenaphtylene Acenaphthene Anthracene Benz[a]anthracene Benzo[b]fluoranthene Benzo[k]fluoranthene Benzo[ghi]perylene Benzo[a]pyrene Chrysene Dibenz[ah]anthracene Fluoranthene Fluorene Indeno[1,2,3-cd]pyrene Naphthalene Phenanthrene Pyrene
1983
Published year
[236]
0.620
0.148 0.061 0.103 0.039 0.070 0.050
Market basket method
1984
United Japan Kingdom
Country
[186]
0.98
0.23 0.041 0.088 0.084
0.23
0.08–0.46a
2.7 0.16
[215]
0.99–1.66a
0.16 0.08 1.2
[214]
0.20–0.36a 0.31–0.36a 0.10–0.14a 0.20–0.36a 0.12–0.29a 0.86–1.53a
0.16
[123]
0.029–0.085 0.039–0.108 0.045–0.109
[39]
1.00
0.17 0.065 0.100 0.064
0.34
[116]
0.5
0.3 0.8 1.5 1.3 0.9 1.6
[237]
0.051
0.128 0.640 0.055
0.355 0.216 0.107
[238]
0.006
0.006 0.009 0.005
0.007 0.011 0.007
Market (Through edible basket method marine species) Total diet study (ng/ kg/day)
Duplicate portion method
Duplicate portion method
Market basket method
Duplicate portion method
Duplicate portion method
2006
2003
2002
Spain
1992
Spain
1991
United Kingdom
1990
Japan
1988
Netherlands Netherlands Japan
1987
Japan
Table 8 Daily dietary intake of polycyclic aromatic hydrocarbons (mg/kg)
Polycyclic Aromatic Hydrocarbons
641
642
Katsumi Tamakawa
Tamakawa et al. [39] reported that daily dietary intake of B[a]P for 117 meal samples was 0.0017–1.6 mg/day (geometric mean: 0.032 mg/day) by the duplicate portion method. In this case, wakame seaweed, broiled fish and meat were appeared frequently in the heavily polluted sample meals. Shiraishi and Shiratori estimated daily intake of B[a]P to be 0.06 mg/day, ranging from 0.025 to 0.131 mg/day in dormitory students [239]. De Vos et al. [215] studied the PAH intake from the total diet of the Dutch by testing 221 different food items from a market basket method. The B[a]P intake estimated was 0.12–0.29 mg/day. According to ‘PAHs in the UK diet: 2000 TOTAL DIET STUDY SAMPLES’, daily intakes of B[a]P and B[a]A are estimated to be two- to five-fold lower in 2000 compared with 1979 for average and high-level intakes [116]. Average daily dietary intakes of B[a]P estimated in the UK survey have fallen from 2.4 ng/kg/day in 1979 to 1.6 ng/kg/day in 2000. Despite the differences in protocols for these survey and the dietary habits among each country, the reported PAHs levels are surprisingly quite similar. Concerning main contributors in B[a]P intake, Dennis et al. [218,225] estimated that most B[a]P came from oils and fats (50%) and cereals (30%) in the UK. In the oils and fats total diet group, margarine was the major dietary source of PAHs. De Vos et al. [215] carried out a similar survey in the Netherlands. The major contributors to the B[a]P intake are oils and fats (47%), cereal products (36%), sugar and sweets (14%). Although the PAHs contamination levels of cereals were quite low, they made a significant contribution to the dietary intake of PAHs by total weight occupied in the diet.
6. FUTURE TREND As mentioned earlier, purification was simplified by SPE procedure instead of conventional packed column chromatography. This preparation, however, is troublesome and still time-consuming because SPE procedure requires some steps, such as elution by organic solvent from cartridges and concentration not to dry up before instrumental analysis. For the routine screening purpose, a simplified, rapid, cost-effective and accurate process is essential. MSPD maybe as a simultaneous extraction and cleanup technique. This method is based on dispersion of the sample on adsorbent such as Florisil or C18. Pigments and lipids, which may interfere with the further analytical determination, are retained on the surface of the adsorbent; consequently a further purification is not necessary. MSPD method requires less time and solvent than liquid–liquid or Soxhlet extraction, and is a good alternative to these conventional methods [240]. To reduce solvent consumption and cut down the sample preparation to a minimum, stir-bar sorptive extraction (SBSE) is also useful. In SBSE, an analyte is extracted into organic phase coated on stir bar, based on octanol–water partitioning coefficient. Therefore, optimization for extraction condition (i.e., salt saturation, solvent addition, temperature and pH, etc.) is required for each sample. SBSE is very popular as an extraction procedure for organic
Polycyclic Aromatic Hydrocarbons
643
micropollutants in environmental water samples [237,240]. However, this technique has hardly been applied to the study of PAHs in food. SBSE may be useful for the analysis of drink. The on-line LC-GC systems have many advantages of being automated and minimizing sampling losses and contaminations. Moreover, the automated systems are generally important to prevent manual intervention-related errors. The LC-GC systems are not simply a coupling of two well-established techniques [196]. Some optimizations of condition, adaptation and underlying new principles are still required. Although LC-GC systems are a little complicated and not so robust, these on-line systems seem to be ideal for routine analysis [194–197,210]. Nowadays, sample throughput is another important aspect when choosing an analytical method in routine analytical applications. For this purpose, the socalled fast GC is promising method. Recently, interest for very fast separations using GC has increased significantly. Fast GC is designed to minimize analysis time without influencing chromatographic resolution. For example, analysis of EPA 16 PAHs can be carried out in 3 min in fast GC. This is a 10-fold improvement in analysis time as compared to the U.S. EPA procedure for PAHs. This is owing to the many improvements in technology, such as high-speed injection systems, low-pressure (LP) outlet conditions (LP-GC), rapid oven heating/cooling, reduction of column length, diameter and stationary phase thickness (narrow-bore capillaries), fast detection system and improvement of software. Among them, the narrow-bore column, and LP-GC and resistive heating have been the main approaches for faster food analysis. Several
Figure 5 PAH analysis in boiled tea using miniaturized LLE. The trace shows the reconstructed ion chromatogram using the quantification masses of PAHs. Peak assignment: 1, methyl salicate; 2, dihydroactinidiolide; 3, anthracene; 4, caffeine; 5, hexanoic acid; 6, fluoranthene; 7, phytol; 8, pyrene; 9, benz[a]anthracene; 10, chrysene; 11, benzo[b]fluoranthene; 12, benzo[k]fluoranthene; 13, benzo[a]pyrene; 14, indeno[1,2,3-cd]pyrene; 15, dibenz[ah]anthracene and 16, benzo-[ghi]perylene. Reprinted from Ref. [151] with permission of Wiley.
644
Katsumi Tamakawa
reviews have been reported describing the concepts and the application of fast GC [237,238,241]. The main limitation of fast GC is the speed of detector response. Fast GC is, therefore, limited mainly to GC-FID, GC-ECD (ECD, electron capture detection) and GC-TOF-MS [169]. The combination of high sensitivity of TOF-MS and narrow peaks of fast GC enables analyte detection at the trace level [191]. Moreover, GC-TOF-MS is successfully used for the fast (3–5 min) analysis of organophosphorus pesticides, triazine herbicides and PAHs in several types of samples [177]. In the case of boiled tea, 11 PAHs from among EPA 16 PAHs were detected at a level of less than 10 mg/L in just over 300 s (Figure 5). GC-TOF-MS may create new possibilities in the field of PAHs analysis in food.
ACKNOWLEDGEMENTS The author is grateful to the editor and reviewers for their valuable comments and suggestions, and would like to express his appreciation to Ms. Ajet Blondy for the English language amendments.
REFERENCES 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
S.P. Wu, S. Tao, F.L. Xu, R. Dawson, T. Lan, B.G. Li and J. Cao, Sci. Total Environ., 345 (2005) 115. H.B. Moon, K. Kannan, S.J. Lee and G. Ok, Arch. Environ. Contam. Toxicol., 51 (2006) 494. K.F. Chang, G.C. Fang, J.C. Chen and Y.S. Wu, Environ. Pollut., 142 (2006) 388. H. Sharma, V. Kain and Z.H. Khan, Chemosphere, 66 (2007) 302. Ch. Vasilakos, N. Levi, T. Maggos, J. Hatzianestis, J. Michopoulos and C. Helmis, J. Hazard Mate., 140 (2007) 45. L. Tolun, D. Martens, O.S. Okay and K.W. Schramm, Environ. Int., 32 (2006) 758. T. Agarwal, P.S. Khillare and V. Shridhar, Environ. Monit. Assess., 123 (2006) 151. S.B. Hawthorne, C.B. Grabanski and D.J. Miller, Environ. Toxicol. Chem., 25 (2006) 2901. S.Y. Yuan and B.V. Chang, J. Environ. Sci. Health B, 42 (2007) 63. B. Maliszewska-Kordybach, Polycycl. Arom. Compds., 21 (2000) 287. W. Wilcke, M. Krauss, G. Safronov, A.D. Fokin and M. Kaupenjohann, J. Environ. Qual., 34 (2005) 1581. H.B. Zhang, Y.M. Luo, M.H. Wong, Q.G. Zhao and G.L. Zhang, Environ. Pollut., 141 (2006) 107. E. Heywood, J. Wright, C.L. Wienburg, H.I. Black, S.M. Long, D. Osborn and D.J. Spurgeon, Environ. Sci. Technol., 40 (2006) 7629. H. Jensen, C. Reimann, T.E. Finne, R.T. Ottesen and A. Arnoldussen, Environ. Pollut., 145 (2007) 829. Z. Wang, J. Chen, P. Yang and F. Tian, Environ. Monit., 9 (2007) 199. T. Ohura, T. Sugiyama, T. Amagai, M. Fusaya and H. Matsushita, J. Assoc. Off. Anal. Chem., 85(1) (2002) 188. S.C. Lung, M.C. Kao and S.C. Hu, Indoor Air, 13 (2003) 194. T. Ohura, T. Amagai, M. Fusaya and H. Matsushita, Environ. Sci. Technol., 38 (2004) 77. A. Barranco, R.M. Alonso-Salces, I. Crespo, L.A. Berrueta, B. Gallo, F. Vicente and M. Sarobe, J. Food Prot., 67 (2004) 2786. D. Lin and L. Zhu, J. Agric. Food Chem., 52 (2004) 8268. M.S. Garcia-Falcon and J. Simal-Gandara, Food Addit. Contam., 22 (2005) 791. R. Ibanez, A. Agudo, A. Berenguer, P. Jakszyn, M.J. Tormo, M.J. Sanchez, J.R. Quiros, G. Pera, C. Navarro, C. Martinez, N. Larranaga, M. Dorronsoro, M.D. Chirlaque, A. Barricarte, E. Ardanaz, P. Amiano and C.A. Gonzalezi, J. Food Prot., 68 (2005) 2190.
Polycyclic Aromatic Hydrocarbons
645
23 S. Tao, X.C. Jiao, S.H. Chen, W.X. Liu, R.M. Coneney, Jr., L.Z. Zhu and Y.M. Luo, Environ. Pollut., 140 (2006) 406. 24 C.A. Galinaro, D.R. Cardoso and D.W. Franco, J. Agric. Food Chem., 55 (2007) 3141. 25 M. Potter, Natl. Cancer Inst. Monogr., 10 (1963) 1. 26 K. Yamagiwa and K. Ichikawa, Mitt. Med. Facultat, Kaiser Univ. Tokyo, 15 (1915) 295. 27 E.L. Kennaway, Biochem. J., 24 (1930) 497. 28 J.W. Cook, C.L. Hewett and I. Hieger, J. Chem. Soc., 1933 (1977) 395. 29 G.O. Emerole, Bull. Environ. Contam. Toxicol., 24 (1980) 641. 30 E.J. Bally and N. Dunga, Br. J. Cancer, 12 (1958) 348. 31 T. Thorsteinsson, Cancer, 23 (1969) 455. 32 T. Thorsteinsson and G. Thordanson, Cancer, 21 (1968) 390. 33 M.J. Roth, K.L. Strickland, G.Q. Wang, N. Rothman, A. Greenberg and S.M. Dawsey, Eur. J. Cancer, 34(5) (1998) 757. 34 A. Vyskocil, Z. Fiala, V. Chenier, L. Krajak, E. Ettlerova, J. Bukac, C. Viau and S. Emminger, Environ. Toxicol. Pharm., 8 (2000) 111. 35 J.P. Butler, G.B. Post, P.L. Joy and J.M. Waldman, J. Air Waste Manage. Assoc., 43 (1993) 970. 36 M. Lodovici, P. Dolara, C. Casalini, S. Ciappellano and G. Testolin, Food Addit. Contam., 31 (1995) 703. 37 T. Cirillo, P. Montuori, P. Mainardi, I. Russo, M. Triassi and R. Amodio-Cocchieri, J. Environ. Sci. Health A, 41(10) (2006) 2089. 38 G. Schere, S. Frank, K. Riedel, I. Meger-Kossien and T. Renner, Cancer Epidemiol. Biomarkers Prev., 9 (2000) 373. 39 K. Tamakawa, T. Seki and A. Tsunoda, HPLC detection of polycyclic aromatic hydrocarbons. In: L.M.L. Nollet (Ed.), Food Analysis by HPLC, Marcel Dekker, New York, 1992, pp. 697–711. 40 C.A. Menzie, B.B. Potocki and J. Santodonato, Environ. Sci. Technol., 26 (1992) 1278. 41 R. Doll, Nature, 265 (1977) 589. 42 E.L. Wynder and G.B. Gori, J. Natl. Cancer Inst., 58 (1977) 825. 43 Harvard Center for Cancer Prevention, Harvard Report on Cancer Prevention, Vol. 1: Causes of Human Cancer, Cancer Causes Control; 7(Suppl. 1) (1996) S1–S59. 44 World Cancer Research Fund/American Institute for Cancer Research., Food, Nutrition, and the Prevention of Cancer: A Global Perspective, American Institute for Cancer Research, Washington, DC, 1997. 45 L.C. Sander and S.A. Wise, Special Publication 922, Polycyclic Aromatic Hydrocarbon Structure Index, US National Institute of Standards and Technology (NIST), 1997. Available at http:// ois.nist.gov/pah/ 46 E. Menichini, A. Bocca, F. Merli, D. Ianni and F. Monfredini, Food Addit. Contam., 8 (1991) 363. 47 Regulation (EC) No 2065/2003 of the European Parliament and of the Council of 10 November 2003 on smoke flavourings used or intended for use in or on foods. 48 http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexapi!prod!CELEXnumdoc&lg ¼ EN& numdoc ¼ 32003R2065&model ¼ guichett 49 Interactive PhysProp Database Demo. Available at http://esc.syrres.com/interkow/physdemo. html 50 T. Awogi and T. Sato, Mutat. Res., 223 (1989) 353. 51 G.K. Montizaan, P.G.N. Kramers, J.A. Janus and R. Posthumus, Integrated criteria document polynuclear aromatic hydrocarbons (PAH): Effects of 10 selected compounds. Appendix to RIVM Report no. 758474007, National Institute of Public Health and Environmental Protection, RIVM, Bilthoven, 1989. 52 US Environmental Protection Agency, Ambient water quality criteria: Naphthalene, Washington, DC, 1978, p B/6 (PB-296 786). 53 C. Legraverend, D.E. Harrison, F.W. Ruscetti and D.W. Nebert, Toxicol. Appl. Pharm., 70 (1983) 390. 54 IARC, Certain Polycyclic Aromatic Hydrocarbons and Heterocyclic Compounds, International Agency for Research on Cancer (IARC Monographs on the Evaluation of the Carcinogenic Risk of Chemicals to Man, Vol. 13), Lyon, 1973. 55 S.J. Culp, D.W. Gaylor, W.G. Sheldon, L.S. Goldstein and F.A. Beland, Carcinogenesis, 19 (1998) 117.
646
Katsumi Tamakawa
56 E.D. Kroese, J.J.A. Muller, G.R. Mohn, P.M. Dortant and P.W. Wester, National Institute of Public Health and the Environment, RIVM Report no. 658603 010, Bilthoven, 2001. 57 TOXNET (Toxicology Data Network), by the Environmental Mutagen Information Center (EMIC). Available at http://toxnet.nlm.nih.gov/ 58 Environmental Health Criteria (EHC), Monographs 202: Selected non-heterocyclic aromatic hydrocarbons, International Programme on Chemical Safety, WHO, Geneva, 1998. Available at http://www.inchem.org/documents/ehc/ehc/ehc202.htm 59 I. Florin, L. Rutberg, M. Curvall and C.R. Enzell, Toxicology, 18 (1980) 219. 60 M. Hermann, Mutat. Res., 90 (1981) 399. 61 A.W. Andrew, L.H. Thibault and W. Lijinsky, Mutat. Res., 51 (1978) 311. 62 J. McCann, E. Choi, E. Yamasaki and B.N. Ames, Proc. Natl. Acad. Sci. USA, 72(12) (1975) 5135. 63 I.F.H. Purchase, E. Longstaff, J. Ashby, J.A. Styles, D. Anderson, P.A. Lefevre and F.R. Westwood, Nature, 264 (1976) 624. 64 S.S. Hecht, E. LaVoie, S. Amin, V. Bedenko and D. Hoffmann, In: A. Bjorseth and A.J. Dennis (Eds.), Polynuclear Aromatic Hydrocarbons: Chemistry and Biological Effects, Battelle Press, Columbus, OH, 1980, pp. 417–433. 65 W. Karcher, J. Dubois, R.J. Fordham, P. Glaude, R. Barale and D. Zucconi, In: M. Cooke and A.J. Dennis (Eds.), Polynuclear Aromatic Hydrocarbons: Mechanisms, Methods and Metabolism, Battelle Press, Columbus, OH, 1984, pp. 685–696. 66 E.J. LaVoie, L. Tulley, V. Bedenko and D.A. Hoffmann, In: A. Bjorseth and A.J. Dennis (Eds.), Polynuclear Aromatic Hydrocarbons: Chemistry and Biological Effects, Battelle Press, Columbus, OH, 1980, pp. 1041–1057. 67 H. Tokiwa, K. Morita, H. Takeyoshi, K. Takahashi and Y. Ohnishi, Mutat. Res., 48 (1977) 237. 68 M. Katz, J.A. Heddle and M.F. Salamone, Mutagenic Activity of Polycyclic Aromatic Hydrocarbons and Other Environmental Pollutants, Battelle Press, Columbus, OH, 1981, pp. 519–528. 69 J.H. Carver, M.L. Machado and J.A. MacGregor, Mutat. Res., 174 (1986) 247. 70 A.L. Wood, D.C. Bouchard, M.L. Brusseau and P.S.C. Rao, Chemosphere, 21 (1990) 575. 71 V.F. Simmon, H.S. Rosenkranz, E. Zeiger and L.A. Poirier, J. Natl. Cancer Inst., 62 (1979) 911. 72 V.C. Dunkel, E. Zeiger, D. Brusick, E. McCoy, D. McGregor, K. Mortelmans, H.S. Rosenkranz and V.F. Simmon, Environ. Mutagen., 6(Suppl. 2) (1984) 1. 73 P.D. Devanesan, P. Cremonesi, J.E. Nunnally, E.G. Rogan and E.L. Cavalieri, Chem. Res. Toxicol., 3 (1990) 580. 74 A.W. Wood, R.L. Chang, W. Levin, D.E. Ryan, P.E. Thomas, R.E. Lehr, S. Kumar, D.J. Sardella, E. Boger, H. Yagi, J.M. Sayer, D.M. Jerina and A.H. Conney, Cancer Res., 41 (1981) 2589. 75 R.P. Bos, J.T.G. Theuws, F.J. Jongeneelen and P.T. Henderson, Mutat. Res., 204 (1988) 203. 76 M. Hermann, J.P. Durand, J.M. Charpentier, O. Chaude, M. Hofnung, N. Petroff, J.P. Vandecasteele and N. Weill, In: A. Bjorseth and A.J. Dennis (Eds.), Polynuclear Aromatic Hydrocarbons: Chemistry and Biological Effects, 4th Int. Symp., Battelle Press, Columbus, OH, 1980, pp. 899–916. 77 J.E. Rice, D.T. Coleman, T.J. Hosted, E.J. LaVoie, D.J. McCaustland and J.C. Wiley, Cancer Res., 45 (1985) 5421. 78 G. Lofroth, R. Toftgard, L. Nilsson, E. Agurell and J.A. Gustafsson, Carcinogenesis, 5 (1984) 925. 79 ATSDR, Polycyclic Aromatic Hydrocarbons (PAHs), ATSDR Toxicological Profiles, US Department of Health and Human Services, Public Health Service, Agency for Toxic Substances and Disease Registry, CRC Press LLC, 1995. Available at http://www.atsdr.cdc.gov/toxprofiles/ tp69.html 80 IARC, Overall Evaluation of Carcinogenicity, IARC Monographs on the Evaluation of the Carcinogenic Risk of Chemicals to Humans: An Updating of IARC Monographs, Vols 1–42, Supplement 7, 1987. Partly available at http://monographs.iarc.fr/ENG/Monographs/vol32/ volume32.pdf and http://monographs.iarc.fr/ENG/Classification/Listagentsalphorder.pdf 81 J.W. Lloyd, J. Occup. Med., 13 (1971) 53. 82 S. Mazumdar, C.K. Redmond and W. Sollecito, J. Air Pollut. Control Assoc., 25 (1975) 382. 83 E.D. Hammond, I.J. Selikoff and P.O. Lawther, Ann. N. Y. Acad. Sci., 271 (1976) 116.
Polycyclic Aromatic Hydrocarbons
647
84 E.L. Wynder and D. Hoffmann, Tobacco and Tobacco Smoke, Academic Press, New York, NY, 1967. 85 K.M. Maclure and B. MacMahon, Epidemiol. Rev., 2 (1980) 19. 86 M.K. Tu¨rkdog˘an, G. Dag˘og˘lu, A. Nevzat, A. Mustafa, T. Ilyas and I. Uygan, J. Nutr. Environ. Med., 13 (2003) 103. 87 G. Lopez-Abente, J.M. Sanz-Anquela and C.A. Gonzalez, Arch. Environ. Health, 56 (2001) 559. 88 R. Sinha, M. Kulldorff, H.C. Wong, P. Strickland, N. Kazerouni and N. Rothman, Proc. Am. Assoc. Cancer Res., 42 (2001), Abstract no. 4106. 89 I.C.T. Nisbet and P.K. LaGoy, Regul. Toxicol. Pharmacol., 16 (1992) 290. 90 H.M. Malcolm and S. Dobson, The calculation of an environmental assessment level (EAL) for atmospheric PAHs using relative potencies, Department of the Environment, London, Report no. DoE/HMIP/RR/94/041, 1994, p. 34. 91 US EPA, Provisional guidance for quantitative risk assessment of polycyclic aromatic hydrocarbons, US Environmental Protection Agency, Office of Health and Environmental Assessment, Environmental Criteria and Assessment Office, Cincinnati, OH, EPA/600/R-93/089 PB94-116571, 1993. 92 P. McClure and R. Schoeny, Fifteen international symposium on polycyclic aromatic compounds: Chemistry, biology and environmental impact. Ispara, Joint Research Centre European Commission, Belgirate, Italy, 1995, p. 161. 93 J.C. Larsen and P.B. Larsen, In: R.E. Hester and R.M. Harrison (Eds.), Air Pollution and Health, issues in Environmental Sciences and Technology, The Royal Society of Chemical, Cambridge, 1998. 94 N. Poonsup, C. Voravit, N. Ito and K. Tanaka, J. Health Sci., 51 (2005) 437. 95 V. Variet, T. Serot, C. Knocaert, J. Comet, M. Cardinal, F. Monteau, B. Le Bizec and C. Prost, J. Sci. Food Agric., 87 (2007) 847. 96 C.Y. Kuo, Y.W. Hsu and H.S. Lee, Arch. Environ. Contam. Toxicol., 44 (2003) 454. 97 P. McClure and R. Schoeny, Evaluation and a component-based relative potency approach to cancer risk assessment for exposure to PAH, In: Fifteenth International Symposium on Polycyclic Aromatic Hydrocarbons: Chemistry, Biology and Environmental Impact. Ispra, Joint Research Centre European Commission, Belgirate, Italy, 1995, p.161. 98 California Environmental Protection Agency, Air Toxics Hot Spots Program Risk Assessment Guidelines, Part II Technical Support Document for Describin Available Cancer Potency Factors. Office of Environmental Health Hazar Assessment, December 2002. Available at http://www.oehha. ca.gov/air/hot_spots/pdf/TSDNov2002.pdf 99 U. S. E. P. A., Provisional Guidance for Quantitative Risk Assessment of Polycyclic Aromatic Hydrocarbons, EPA/600/R-93/089, July 1993. 100 MOE (Ministry of the Environment), Scientific Criteria Document for Multimedia Standards Development. Polycyclic Aromatic Hydrocarbons (PAHs), Part 1: Hazard Identification and Dose-Response Assessment, Ministry of the Environment, Toronto, Ontario, Canada, 1997. 101 I.C.T. Nisbet and P.K. LaGoy, Regul. Toxicol. Pharmacol., 16 (1992) 290. 102 European Commission, Opinion of the Scientific Committee on the risks to human health of Polycyclic Aromatic Hydrocarbons in food occurrence in foods, 2002. Available at http:// ec.europa.eu/food/food/chemicalsafety/contaminants/out153_en.pdf 103 D. Krewski, T. Thorslund and J. Withey, Toxicol. Ind. Health, 5 (1989) 851. 104 E.H. Pfeiffer, In: V. Mohr, D. Schma¨hl and L. Tomatis (Eds.), Air Pollution and Cancer in Man (IARC Scientific Publications No. 16), International Agency for Research on Cancer, Lyon, 1977, pp. 69–77. 105 D. Schma¨hl, K.G. Schmidt and M. Habs, In: V. Mohr, D. Schma¨hl, and L. Tomatis (Eds.), Air Pollution and Cancer in Man (IARC Scientific Publications No. 16), International Agency for Research on Cancer, Lyon, 1977, pp. 53–59. 106 K. Schneider, R. Roller, F. Kalberlah and U. Schuhmacher-Wolz, J. Appl. Toxicol., 22 (2002) 73. 107 R. Brown and A. Mittelman, Evaluation of existing methods to rank the relative carcinogenicity of polycyclic aromatic compounds (PAH), Draft. Technical Resources, Inc. Contract No. 68-01-0022, for Office of Emergency and Remedial Response, Office of Solid Waste and Emergency Response,
648
108 109 110
111 112 113 114 115 116
117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143
Katsumi Tamakawa
U.S. Environmental Protection Agency, Office of Pesticides, Pollution Prevention and Toxic Substances (OPPTS), 1993. K. Tamakawa, T. Seki and A. Tsunoda, In: L.M.L. Nollet (Ed.), Food Analysis by HPLC, Marcel Dekker, New York, 1992, pp. 697–711. K. Takatsuki, S. Suzuki, N. Sato and I. Ushizawa, J. Assoc. Off. Anal. Chem., 68(9) (1985) 45. US EPA, Determination of benzo(a)pyrene and other polynuclear aromatic hydrocarbons in indoor air. In: W.T. Winbery, Jr., L. Forehand, N.T. Murphy, A. Ceroli, B. Phinney and A. Evans (Eds.), Compendium of Methods for the Determination of Air Pollutants in Indoor Air, US Environmental Protection Agency, Method IP-7, Research Triangle Park, North Carolina, 1990, pp. 550–639. A.-Z. DouAbul Ali, M.A. Heba Hassan and K.H. Fareed, Hydrobiologia, 352 (1997) 251. M.D. Guillen, P. Sopelana and M.A. Partearroyo, J. Agric. Food Chem., 48 (2000) 126. M.D. Guillen, P. Sopelana and M.A. Partearroyo, Food Addit. Contam., 17(1) (2000) 27. M.D. Guillen, P. Sopelana and M.A. Partearroyo, J. Agric. Food Chem., 48 (2000) 5083. B.P. Dunn and R.J. Armour, Anal. Chem., 52 (1980) 2027. UK, PAHs in the UK diet: 2000 total diet study samples (Number 31/02), Food Survey Information Sheet, The United Kingdom Food Standard Agency, 2002. Available at http:// www.foodstandards.gov.uk/multimedia/pdfs/31pah.pdf M.D. Nunez and F. Centrich, Anal. Chim. Acta, 234 (1990) 269. Y. Mori, S. Goto, S. Onodera, S. Naito, S. Takitani and H. Matsushita, Fresenius J. Anal. Chem., 345 (1993) 63. M.N. Kayali-Sayadi, S. Rubio-Barroso, M.P. Cuesta-Jimenez and L.M. Polo-Diez, Analyst, 123 (1998) 2145. K. Tatatsuki, S. Suzuki, N. Sato and I. Ushizawa, J. Assoc. Off. Anal. Chem., 68 (1985) 945. C.J. Musial and J.F. Uthe, J. Assoc. Off. Anal. Chem., 69 (1986) 462. K. Tamakawa, Y. Ohgane, Y. Katoh, Y. Mishima and T. Seki, Eisei Kagaku (J. Hyg. Chem.), 32 (1986) 475. T. Nakagawa, A. Seshimo, C. Yamamoto, Y. Sato and T. Kawamura, Ann. Rep. Yokohama Inst. Health, 30 (1991) 113. G.A. Perfetti, P.J. Nyman, S. Fisher, F.J. Joe, Jr. and G.W. Diachenko, J. Assoc. Off. Anal. Chem., 75 (1992) 872. P. Simko and B. Bruncova, Food Addit. Contam., 10 (1993) 257. M. Sanders, Arch. Environ. Contam. Toxicol., 28 (1995) 397. E. Jarvenpaa, R. Huopalahti and L. Tapanainen, J. Liq. Chromatogr. Relat. Technol., 19 (1996) 1473. F. van Stijin, M.A.T. Kerkhoff and B.G.M. Vandeginste, J. Chromatogr. A, 750 (1996) 263. C.P. Chiu, Y.S. Lin and B.H. Chen, Chromatographia, 44 (1997) 497. D. Voutsa and C. Samara, Sci. Total Environ., 218 (1998) 203. M.S.G. Falcon, S.G. Amigo, M.A.L. Yusty and J.S. Lozano, Food Addit. Contam., 16 (1999) 9. S. Moret and L.S. Conte, J. High Resolut. Chromatogr., 21 (1998) 253. S. Moret, L.S. Conte and D. Dean, J. Agric. Food Chem., 47 (1999) 1367. S. Moret, A. Dudine and L.S. Conte, J. Assoc. Off. Anal. Chem., 77 (2000) 1289. S. Moret, V. Cericco and L.S. Conte, J. Microcolumn Sep., 13 (2001) 13. M.N. Kayali-Sayadi, S. Rubio-Barroso and R. Garcia-Iranzo, J. Liq. Chromatogr. Relat. Technol., 23 (2000) 1913. M.J. Nieva-Cano, S. Rubio-Barroso and M.J. Santos-Delgado, Analyst, 126 (2001) 1326. B. Janoszka, L. Warzecha, U. B"aszczy and D. Bodzek, Acta Chromatogr., 14 (2004) 115. C. Sobrado, M.C. Quintela, J.C. Gonza´lez and J.M. Vieites, J. Aquatic Food Product Tech., 13 (2004) 93. S. Martinez-Lopez, A. Morales-Noe, A. Pastor-Garcia, A. Morales-Rubio and M. de la Guardia, J. Assoc. Off. Anal. Chem., 88 (2005) 1247. J.K. Houessou, C. Benac, C. Delteil and V. Camel, J. Agric. Food Chem., 53 (2005) 87. J.T. Coates and A.W. Elzerman, J. Assoc. Off. Anal. Chem., 69 (1986) 110. K. Speer, H. Steeg, P. Horstmann, Th. Kuhn and A. Montag, J. High Resolut. Chromatogr., 13 (1990) 104.
Polycyclic Aromatic Hydrocarbons
649
144 D. Broman, C. Naf, I. Lundbergh and Y. Zebuhr, Environ. Toxicol. Chem., 9 (1990) 429. 145 E. Menichini, A. Domenico and L. di Bonanni, J. Chromatogr., 555 (1991) 211. 146 J.A. Lebo, J.L. Zajicek, T.R. Schwartz, L.M. Smith and M.P. Beasley, J. Assoc. Off. Anal. Chem., 74 (1991) 538. 147 C. Naf, D. Broman and B. Brunstrom, Environ. Toxicol. Chem., 11 (1992) 1653. 148 M. Nakano and M. Fukushima, Syoku-Hin Eiseigaku Zasshi (J. Food Hyg. Soc. Japan), 35 (1994) 41. 149 A. Husain, E. Naeemi, B. Dashti, H. Ai-Omirah and S. Al-Zenki, Food Addit. Contam., 14 (1997) 295. 150 S. Nemoto, S. Takatsuki, R. Matsuda, K. Sakai and M. Toyoda, Syokuhin Eiseigaku Zasshi (J. Food Hyg. Soc. Japan), 39 (1998) 31. 151 G. Wang, A.S. Lee, M. Lewis, B. Kamath and R.K. Archer, J. Agric. Food Chem., 47 (1999) 1062. 152 T. Korenaga, T. Kajihara and Y. Tsukiyama, Bunseki Kagaku (Anal. Sci.), 48 (1999) 631. 153 B. Albero, C. Sa´nchez-Brunete and J.L. Tadeo, J. Assoc. Off. Anal. Chem., 86 (2003) 576. 154 M.D. Guille´n and P. Sopelana, J. Dairy Sci., 87 (2004) 556. 155 M. del Bubba, L. Zanieri, P. Galvan, G.P. Donzelli, L. Checchini and L. Lepri, Ann. Chim., 95 (2005) 629. 156 R. Simon, S. Palma and E. Anklam, J. Chromatogr. A, 110 (2006) 307. 157 D.A. Birkholtz, R.T. Cout and S.E. Hrudey, J. Chromatogr., 449 (1988) 251. 158 F.L. Joe, Jr., J. Salemme and T. Fazio, J. Assoc. Off. Anal. Chem., 67 (1984) 1076. 159 Pharmaceutical Society of Japan, Analytical Methods for Food Contaminants’ in Method of Analysis in Health Science, Pharmaceutical Society of Japan, Tokyo, 2000, pp. 489–491. 160 P. Welling and B. Kaanorp, Z. Lebensm. Torsch., 183(2) (1986) 111. 161 S. Moret, R. Bortolomeazzi, S. Rebecca and L.S. Conte, Riv. Ital. Sostanze Grasse, 73 (1996) 141. 162 T. Vo-Dinh, Chemical Analysis of Polycyclic Aromatic Compounds, Wiley, New York, 1989, p. 487. 163 V. Yusa`, O. Pardo, P. Martı´ and A. Pastor, Food Addit. Contam., 22 (2005) 482. 164 M.D. Guille´n and P. Sopelana, J. Dairy Sci., 88 (2005) 13. 165 J.E. France, J.W. King and J.M. Snyder, J. Agric. Food Chem., 39 (1991) 1871. 166 P.J. Nyman, G.A. Perfetti, F.L. Joe, Jr. and G.W. Diachenko, Food Addit. Contam., 10 (1993) 489. 167 I. Tsuji, K. Koide, H. Moriyama, K. Tanabe and H. Matsushita, Syokuhin Eiseigaku Zasshi (J. Food Hyg. Soc. Japan), 26 (1985) 50. 168 E. Winkler, A. Buchele and O. Mueller, J. Chromatogr., 138 (1977) 151. 169 J.P. Hanus, H. Guerrero, E. Biehl and C.T. Kenner, J. Assoc. Off. Anal. Chem., 62 (1979) 29. 170 E. Mochizuki, H. Kobayashi and A. Nakayama, Yamanashi-ken Eisei Kogai Kenkyusho Nenpo (Ann. Rep. Yamanashi Pref. Inst. Public Health), 31 (1987) 8. 171 P.F. Landrum, S.R. Nihart, B.J. Eadie and L.R. Herche, Environ. Toxicol. Chem., 6 (1987) 11. 172 L. Xia, M. Zhu, F. Tao and Z. Hu, Fenxi Huaxue (Anal. Chem.), 16 (1988) 147. 173 M.N. Kayali-Sayadi, S. Rubio-Barroso, M.P. Cuesta-Jimenez and L.M. Polo-Diez, J. Liq. Chromatogr. Relat. Technol., 22 (1999) 615. 174 N. Bishnoi, U. Mehta, U. Sain and G. Pandit, Environ. Monit. Assess., 107 (2005) 399. 175 ].J.L. Perrin, N. Poirot, P. Liska, A. Thienpont and G. Felix, Fat Sci. Technol., 95 (1993) 46. 176 K. Kimata, K. Hosoya, T. Araki, N. Tanaka, E.R. Barnhart, L.R. Alexander, S. Sirimanne, P.C. McClure, J. Grainger and D.G. Patterson, Jr., Anal. Chem., 65 (1993) 2502. 177 M. Funk, H. Frank, F. Oesch and K.L. Platt, J. Chromatogr. A, 659 (1994) 57. 178 M. Liu, A. Thienpont, M.H. Delville, G. Fe´lix and C. Netter, J. High Resolut. Chromatogr., 17(2) (2005) 104. 179 F. Holger and M. Giovanni, HPLC analysis of PAHs in edible oils using on-line donor-acceptor complex chromatography sample, LC GC North America (LC GC N. Am.), Vol. FEV (2005), p. 37. 180 International Union of Pure and Applied Chemistry, Pure Appl. Chem., 59, (1987) 1735. 181 WHO, International Drinking-Water Standards, 3rd ed., p. 55. 182 T. Tateno, Syokuhin Eiseigaku Zasshi (J. Food Hyg. Soc. Japan), 32(3) (1990) 271. 183 T. Tateno and Y. Kageyama, Syokuhin Eiseigaku Zasshi (J. Food Hyg. Soc. Japan), 40(1) (1999) 90. 184 T. Tateno, Bull. Tokyo Kasei Univ., 40 (2000) 91. 185 T. Tateno, Bull. Tokyo Kasei Univ., 42(2) (2002) 83.
650
Katsumi Tamakawa
186 K. Tamakawa, Y. Katoh, Y. Ohgane, Y. Mishima, T. Seki and A. Tsunoda, Eisei Kagaku (J. Hyg. Chem.), 33(1) (1987) 66. 187 J. Borneff and H. Kunte, In: H. Egan, M. Castegnaro, P. Bogovski, H. Kunte and E.A. Walker (Eds.), Environmental Carcinogens: Selected Methods of Analysis, Volume 3: Analysis of polycyclic aromatic hydrocarbons in environmental samples, International Agency for Research on Cancer (IARC Scientific Publications No. 29), Lyon, 1979, pp. 129–139. 188 M. Maita, T. Toba, K. Yamada, N. Yamada, T. Kanno, T. Osawa, T. Ishii and K. Tamakawa, Rep. Sendai Munic. Inst. Public Health, 35 (2005) 129. 189 D.L. Poster, M.M. Schantz, L.C. Sander and S.A. Wise, Anal. Bioanal. Chem., 386 (2006) 859. 190 L.R. Hilpert, Biomed. Environ. Mass Spectrom., 14 (1987) 383–394. 191 R.J.J. Vreuls, J. Dalluge and U.A.Th. Brinkman, J. Microcolumn Sep., 11(9) (1999) 663. 192 R. Simon, S. Palma and E. Anklam, J. Assoc. Off. Anal. Chem., 89(3) (2006) 772. 193 R. Majors, J. Chromatogr. Sci., 18 (1980) 571. 194 H.J. Cortes, In: H.J. Cortes (Ed.), Multidimensional Chromatography, Techniques and Applications, Chromatographic Science Series, Vol. 50, Marcel Dekker, Inc., New York, 1990. 195 L. Mondello, In: L. Mondello, A.C. Lewis and K.D. Bartle (Eds.), Multidimensional Chromatography, Wiley, London, 2001. 196 T. Hyo¨tyla¨inen and M. -L. Riekkola, J. Chromatogr. A, 1000 (2003) 357. 197 P. Dugo, G. Dugo and L. Mondello, On-line coupled LC–GC: Theory and applications, Recent Applications in Multidimensional Chromatography, 2003. Available at http://www.lcgceurope. com/lcgceurope/data/articlestandard/lcgceurope/482003/77606/article.pdf 198 E. Boselli, K. Grob and G. Lercker, J. Agric. Food Chem., 48 (2000) 2868. 199 T. Hyotylainen, T. Andersson, K. Hartonen, K. Kuosmanen and M.L. Riekkola, Anal. Chem., 72 (2000) 3070. 200 A. Miller, Th. Frenzel, H.-G. Schmarr and K.-H. Engel, J. Chromatogr. A, 985 (2003) 403. 201 W. Kamm, F. Dionisi, L.B. Fay, C. Hischenhuber, H.G. Schmarr and K.H. Engel, J. Chromatogr. A, 918 (2001) 341. 202 R. Magnusson, C. Nilsson, K. Andersson, B. Andersson, R. Gieling, K. Wiberg, C. Ostman and U. Rannug, Environ. Technol., 21 (2000) 819. 203 K. Grob, M. Vass, M. Biedermann and H.P. Neukom, Food Addit. Contam., 18(1) (2001) 1. 204 M.L. Ruiz del Castillo, M. Herraiz and G.P. Blanch, J. Agric. Food Chem., 48 (2000) 1186. 205 S. Moret, K. Grob and L.S. Conte, J. High Resolut. Chromatogr., 19 (1996) 434. 206 S. Moret, K. Grob and L.S. Conte, Z. Lebensm. Unters. Forsch., 204 (1997) 241. 207 S. Moret, K. Grob and L.S. Conte, J. Chromatogr. A, 750 (1996) 361. 208 J.C.A. van der Wielen, J.T.A. Jansen, M.J. Martena, H.N. De Groot and P.H. In’t Veld, Food Addit. Contam., 23(7) (2006) 709. 209 J.J. Vreuls, G.D.E. Jong and U.A. Brinkman, Chromatographia, 31 (1991) 113. 210 S. Moret and L.S. Conte, J. Chromatogr. A, 882(1–2) (2000) 245. 211 M. Shimmo, P. Anttila, K. Hartonen, T. Hyotylainen, J. Paateo, M. Kulmala and M.L. Riekkola, J. Chromatogr. A, 1022 (2004) 151. 212 M. Shimmo, J. Jantti, P. Anttila, K. Hartonen, T. Hyotylainen, J. Paateo, M. Kulmala and M.L. Riekkola, Anal. Bioanal. Chem., 378 (2004) 1982. 213 B. Larsson and G. Sahberg, In: M. Cooke and A.J. Fisher (Eds.), Polynuclear Aromatic Hydrocarbons: Physical and Biological Chemistry, Battelle Press, Columbus, OH, 1982, pp. 417–426. 214 H.A.M.G. Vaessen, P.L. Schuller, A.A. Jekel and A.A.M.M. Wilber, Toxicol. Environ. Chem., 7 (1984) 297. 215 R.H. de Vos, W. van Dokkum, A. Schouten and P. de Jong-Berkhout, Food Chem. Toxicol., 28 (1990) 263. 216 K. Wickstrom, H. Pyysalo, S. Plaami-Heikkil and J. Tuominen, Z. Lebensmittelunters Forsch, 183 (1986) 182. 217 A. Zohair, World J. Agric. Sci., 2(1) (2006) 90. 218 M.J. Dennis, R.C. Massey, D.J. McWeeny, M.E. Knowles and D. Whatson, Food Chem. Toxicol., 21 (1983) 569. 219 J.F. Lawrence and D.F. Weber, J. Agric. Food Chem., 32 (1984) 794.
Polycyclic Aromatic Hydrocarbons
651
220 FAO/WHO, 31st Report of the Joint Committee on Food Additives, WHO, Geneva, Switzerland, 1987, p. 759. 221 J.P. Tuominen, H.S. Pyysao and M. Sauri, J. Agric. Food Chem., 36 (1988) 118. 222 A.S. McGill, P.R. Mackie, E. Parsons, C. Bruce and R. Hardy, In: M. Cooke, A.J. Dennis and G.L. Fisher (Eds.), Polynuclear Aromatic Hydrocarbons: Physical and Biological Chemistry, Battelle Press, Columbus, OH, 1982, pp. 491–499. 223 H. Karl and M.Z. Leinemann, Z. Lebensm. Unters. Forsch., 202 (1996) 458. 224 K. Speer and A. Montag, Fat Sci. Technol., 90 (1988) 163. 225 M.J. Dennis, R.C. Massey, G. Cripps, I. Venn, N. Howarth and G. Lee, Food Addit. Contam., 8 (1991) 517. 226 S. Moret, G. Purcaro and L.S. Conte, Eur. J. Lipid Sci. Technol., 107 (2005) 488. 227 G. Crossmann and M. Wy¨stemann, Loadings in Domestic Gardens and Allotments by Inorganic and Organic Substances with Damaging Potential: Actual Documentation, Part I: Soils and Garden Wastes and Part II: Vegetables and Fruits. Ministry of Environment, Berlin, 1992, pp. 40–42, 108–124. 228 S. Moret, B. Piani and R. Bortolomeazzi, Z. Lebensm. Unters. Forsch., 205 (1997) 116. 229 R.J. Law, C. Kelly, K. Baker, J. Jones, A.D. McIntosh and C.F. Moffat, J. Environ. Monit., 4 (2002) 383. 230 W. Jira, Eur. Food Res. Technol., 218 (2004) 208. 231 B.K. Larsson, A.T. Eriksson and M. Cervenka, J. Am. Oil Chem. Soc., 64 (1987) 365. 232 B.H. Chen and Y.S. Lin, J. Agric. Food Chem., 45 (1997) 1394. 233 P. Mottier, V. Parisod and R.J. Turesky, J. Agric. Food Chem., 48 (2000) 1160. 234 M.E. Doremire, G.E. Harmon and D.E. Pratt, J. Food Sci., 44 (1979) 622. 235 M. Ku¨rs- ad Tu¨rkdog˘an, D. Gu¨rdal, A. Nevzat, A. Mustafa, T. Ilyas, U. Ismail, J. Nutr. Environ. Med., 13 (2003) 103. 236 H. Obana, S. Hori, R. Tanaka and T. Kashimoto, Syokuhin Eiseigaku Zasshi (J. Food Hyg. Soc. Japan), 25 (1984) 35. 237 G. Falco´, J.L. Doming, J.M. Llobet, A. Teixido´, C. Casas and L. Mu¨ller, J. Food Prot., 66 (2003) 2325. 238 J.M. Llobet, G. Falco´, A. Bocio and J.L. Doming, J. Food Prot., 69 (2006) 249. 239 Y. Shiraishi and T. Shiratori, Syokuhin Eiseigaku Zasshi (J. Food Hyg. Soc. Japan), 22 (1981) 436. 240 A.C. Heiden, A. Hoffmann and B. Kolahgar, Comparison of the Sensitivity of Solid Phase MicroExtraction (SPME) and Stir Bar Sorptive Extraction (SBSE) for the Determination of Polycyclic Aromatic Hydrocarbons (PAHs) in water and soil samples. Available at http:// www.gerstel.com/an-2001-08.pdf 241 M.S. Garcia-Falcon, B. Cancho-Grande and J. Simal-Gandara, Water Res., 38(7) (2007) 1679.
CHAPT ER
18 Methods for the Determination of N-Nitroso Compounds in Food and Biological Fluids Sidney S. Mirvish
Contents
1. Introduction 2. Physical and Chemical Properties of NOC 2.1 UV, nuclear magnetic resonance (NMR) and mass spectrometry (MS) 2.2 Synthesis, formation and decomposition of NOC 3. Health Effects 3.1 Human studies 3.2 Animal studies 4. Analytical Methods 4.1 Safety 4.2 Nomenclature 4.3 General considerations in NOC analysis 4.4 Determination of volatile nitrosamines 4.5 HPLC-TEA of nitrosamino acids 4.6 GC-TEA of methyl esters of nitrosamino acids 4.7 GC-TEA of hydroxyalkylnitrosamines 4.8 HPLC-photolysis-TEA of non-volatile NOC 4.9 Havery’s HPLC-TEA method for all types of NOC 4.10 Determination of total ANC 4.11 Determination of nitrosamides as ANC 4.12 Determination of alkylureas 4.13 HPLC-photolysis-TEA of nitrosamides 5. Occurrence of NOC in Foods 5.1 Occurrence of volatile nitrosamines 5.2 Occurrence of nitrosamino acids 5.3 Occurrence and identity of total ANC 5.4 Occurrence of alkylureas and alkylnitrosoureas 6. Conclusions and Future Trends
Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00018-4
654 656 656 657 657 657 659 659 659 660 660 661 665 665 667 669 669 669 673 673 675 676 676 677 678 678 679
r 2008 Elsevier B.V. All rights reserved.
653
654
Sidney S. Mirvish
Acknowledgements References
680 680
1. INTRODUCTION N-Nitroso compounds (NOC) comprise nitrosamines [R1N(NO)R2] and nitrosamides [R1N(NO)COR2]. Nitrosamines include dialkylnitrosamines, e.g., N-nitrosodimethylamine (NDMA), and cyclic nitrosamines, e.g., N-nitrosopyrrolidine (NPYR) (Figure 1). In 1937 Freund [1] reported two cases of acute liver toxicity caused by exposure to NDMA in a laboratory. In one of these cases, the individual had cleaned up a spill in the open laboratory from a broken bottle of NDMA, became sick soon thereafter and later died from acute liver toxicity. NDMA is no longer synthesized on a large scale for reduction to the rocket fuel 1, 1-dimethnylhydrazine (Figure 2) [2]. In 1956, Magee and Barnes [3] reported that NDMA (50 mg/kg diet) induced liver cancer in rats. The first indication that nitrosamines were an environmental hazard was the discovery in 1965 when the presence of NDMA in spoiled herring was responsible for an outbreak of acute liver toxicity in Norwegian sheep [4]. NDMA still occurs in some fish products [5], where it could arise from the fish constituents trimethylamine and trimethylamine N-oxide. Because even low doses of NOC could induce cancer in humans [6], it is vital to minimize NOC levels in foods. This chapter will review the determination of the various types of NOC in foods, with some attention also to NOC in biological materials. This is a widely studied area, e.g., the Scifnder database contained over 900 references to ‘‘nitrosamine determination,’’ most of which involved food analysis. References are generally not discussed if the detection limits were relatively high, e.g., greater than 1–2 mg of volatile nitrosamines/kg food. Nitrosamines are carcinogenic because they are activated by cytochrome P450 isozymes that insert a hydroxy group on a carbon atom adjacent to the N-nitroso
Figure 1 Some common nitrosamines. NMOR, N-nitrosomorpholine; NPIP, N-nitrosopiperidine; NSAR, N-nitrososarcosine; NPRO, N-nitrosoproline; and NTCA, N-nitrosothiazolidine-4-carboxylic acid.
Methods for the Determination of N-Nitroso Compounds
655
Figure 2 Reduction of NDMA to 1,1-dimethylhydrazine.
Figure 3 Metabolic activation of NDMA by cytochrome P450 2E1 and conversion of NMU to alkylating agents. R1R2NH and R3OH ¼ DNA bases, e.g., guanine.
(NNO) group. The hydroxyalkyl group in the product is split off by hydrolysis. The resulting alkyldiazonium cation can alkylate DNA bases and thereby induce mutations and, eventually, cancer (Figure 3) [7,8]. Nitrosamides, e.g., N-nitrosomethylurea (NMU), do not require enzymic activation as they are converted directly to alkyldiazonium ion (Figure 3). People are exposed to exogenous NOC ingested in the diet or inhaled in cigarette smoke, and are also exposed to endogenous NOC. These are produced in vivo by acid-catalyzed nitrosation of amines and amides in the stomach (perhaps the major in vivo route), by bacteriacatalyzed nitrosation in the colon and achlorhydric (high pH) stomach, and by nitrosation by the nitrogen oxides N2O3 and N2O4 (which also produce nitramines) and peroxynitrite (ONOO) (Equations (1)–(4)). These agents arise from the oxidation of endogenous nitric oxide (NO) or, in the case of peroxynitrite (OONO), by the reaction of NO with superoxide (O 2 ) during inflammation (Equations (3) and (4)) [8,9]. 2R1 NHR2 þ N2 O3 ! 2R1 NðNOÞR2 þ H2 O
(1)
2R1 NHR2 þ N2 O4 ! R1 NðNOÞR2 þ R1 NðNO2 ÞR2 þ H2 O
(2)
NO þ O 2 ! ONOO
(3)
R1 NHR2 þ OONO ! R1 NðNOÞR2 þ HOO
(4)
As increasingly sensitive analytical methods are developed for NOC, an important question is to decide what level of NOC in foods should be considered
656
Sidney S. Mirvish
harmful. This may eventually be decided by epidemiological studies correlating cancer incidence with the intake of individual foods with known NOC contents. Meanwhile, a conservative approach is to ensure that NOC intake in specific foods should not increase much the current daily intake of NOC, e.g., of about 1 mg/day for volatile nitrosamines [6]. For more details, including many of the original references, readers are referred to previous reviews on health effects of nitrate, nitrite and NOC by the National Academy of Sciences in 1981 [6] and by the author in 1995 [8]; and to reviews on NOC determination by Scanlan in 1973 [10], Tricker et al. in 1984 [11], Scanlan and Reyes in 1985 [12], Sen and Kubacki in 1987 [13], Massey in 1988 [14], Tricker and Kubacki in 1992 [15], Yeh and Ebeler in 1998 [16] and Biaudet et al. in 2000 [17].
2. PHYSICAL AND CHEMICAL PROPERTIES OF NOC 2.1 UV, nuclear magnetic resonance (NMR) spectrometry and mass spectrometry (MS) NOC can be determined in simple solutions by their UV absorption [18]. NDMA shows absorption maxima at 225 (7,100) and 331 (91) nm in water, 227 (5,900) and 343 (98) nm in 95% ethanol and 349 (97), 359 (117) and 370 (96) nm in ether (parentheses here and below give molar extinction coefficients). NMU shows absorption maxima in water at 235 (6,700), 390 (95) and 417 (64) nm; and in ether at 230 (7,700), 378 (87), 391 (136) and 410 (131) nm. UV absorption can detect 50 mg NOC/ml when the maximum at greater than 320 nm is used and 0.5 mg NOC/ml when the maximum below 240 nm is used. This method of determining NOC has been employed to study the kinetics of NOC formation from nitrite in simple solutions and effects of inhibitors and enhancers of this formation [19]. NMR spectrometry of nitrosamines [20] usually reveals the presence of syn and anti isomers, which occur because of the partial double-bond character of the N–N bond (Figure 4). These isomers can be separated by high pressure liquid chromatography (HPLC), but interconvert at raised temperatures [20]. MS is used to detect and determine NOC and to confirm the identity of NOC detected by other means. The mass spectra of aliphatic dialkylnitrosamines show prominent molecular ions with relative intensities exceeding 25% of the base peak [21]. An ion at m/z 30 due to NO is common. Peaks at M–17 (loss of OH) and M–31 (loss of NOH) are prominent, whereas peaks at M–30 (loss of NO) are rare.
Figure 4 Syn and anti forms of nitrosamines.
Methods for the Determination of N-Nitroso Compounds
657
2.2 Synthesis, formation and decomposition of NOC NDMA and other simple nitrosamines are volatile liquids, whereas nitrosamides and more complex nitrosamines are solids. NOC are synthesized by the reaction of secondary amines (Equations (5)–(7)) or N-alkylamides (Equation (8)) with nitrous acid (HNO2, i.e., acidified nitrite, Equations (5) and (8)), with the gasses N2O3 and N2O4 (Equations (6) and (7)) and with peroxynitrite (OONO) (Equation (4)) [9]. Nitrosamine solutions in water decompose slowly in the presence of acid by the reverse of Equation (5) [22] and are best stored under alkaline conditions. In contrast, nitrosamides are rapidly decomposed by alkali. R1 NHR2 þ HNO2 Ð R1 NðNOÞR2 þ H2 O
(5)
R1 NHR2 þ N2 O3 Ð R1 NðNOÞR2 þ HNO2
(6)
R1 NHR2 þ N2 O4 Ð R1 NðNOÞR2 þ HNO3
(7)
R1 NHCOR2 þ HNO2 Ð R1 NðNOÞCONHR2 þ H2 O
(8)
The kinetics of NOC formation from nitrite [23] are relevant here because the ease of NOC formation increases with decreasing pH (down to pH 3.0–3.3 for secondary amines and with no pH limit for N-alkylamides), varies enormously for different NOC and may be an important factor in determining NOC concentration in foods, e.g., acidic foods are more likely to generate NOC than neutral foods. For secondary amines, the rate of nitrosation is proportional to nitrite concentration squared (Equation (9)). Most but not all tertiary amines, e.g., nicotine, are nitrosated far more slowly than secondary amines. The rate of nitrosation of N-alkylamides is proportional to the concentration of nitrite multiplied by that of hydrogen ion (Equation (10)). The rate constants, which determine the ease of nitrosation, vary by factors of more than 105 between different amines and between different amides. For secondary amines, nitrosation rate is largely governed by the acidic dissociation constant (pKa) of the amine, with the rate increasing as the pKa decreases. Rate ¼ k1 ½amine½nitrite2
(9)
Rate ¼ k2 ½amide½nitrite½Hþ
(10)
3. HEALTH EFFECTS 3.1 Human studies After the initial report of the toxicity of NDMA (see Section 1) [1], several other cases were reported of acute liver toxicity due to exposure to NDMA vapor
658
Sidney S. Mirvish
[24,25]. In a 1967 review on NOC, Magee and Barnes proposed that NOC may be significant causes of human cancer [26]. More recent laboratory and epidemiologic studies indicate that dietary NOC are etiological agents for human cancer of the oesophagus, nasopharynx, stomach, colon, brain and urinary bladder [8,27]. Salted dried fish and fish sauce are established risk factors for gastric cancer [28], perhaps due in part to NMU produced by the nitrosation of creatinine (CRN) and methylguanidine (see Section 4.12). The occurrence of polymorphic forms of enzymes that activate nitrosamines show correlations with the incidences of certain cancers. For example, increased incidences of nasopharyngeal cancer were observed in individuals with certain polymorphic forms of a DNA repair enzyme and of cytochrome P450s 2E1 and 2B6, which are known or suspected of being involved in nitrosamine metabolism [29]. In addition to dietary NOC, nitrosamines in cigarette smoke are a probable cause of cancer of the lung, oesophagus, nasal cavity and pancreas induced by smoking [30]. Certain meat and fish products are ‘‘processed,’’ which generally means preserved with sodium nitrite and, in some cases, sodium chloride. Fresh and processed red meat products are reported risk factors for colon cancer, and the risk for processed meat appeared greater than that for fresh meat [31,32]. Associations have been reported of processed meat with gastric and oesophageal cancer [27], and of preserved fish and vegetable products and smoked foods with gastric cancer [27,28]. These associations may be due to NOC present in or produced from nitrite in these foods, though a high sodium chloride level in fish products is probably an additional risk factor for gastric cancer. NOC in processed meat and fish products have often been measured as total apparent NOC (ANC, see Section 4.10) [33]. Hot dogs (frankfurters, a nitritepreserved meat product) contain ANC and, when fed to mice, increased ANC levels in the faeces [34]. Red meat had a similar effect in humans [35] and mice [34], but in mice the effect of red meat was weaker than that of hot dogs. In an epidemiological study in Europe, estimated faecal ANC excretion after the ingestion of meat was significantly (hazard ration, 1.42) correlated with the incidence of non-cardiac gastric cancer [36]. The estimated intake of NDMA showed no such correlation. Because nitrosoureas induce brain tumours in the offspring of pregnant rats treated with these compounds, it was proposed [37] that childhood brain cancer can be induced by in utero exposure to nitrosoureas (see Section 3.2). Childhood brain cancer was associated [38] with the consumption by pregnant women or their children of nitrite-preserved meat, which could produce NOC that, like nitrosoureas, are direct-acting mutagens [39]. Processed meat is also a risk factor (in addition to smoking) for pancreatic cancer [40] and chronic obstructive lung disease [41]. Processed meat is not a risk factor for prostate cancer [42]. Partly because exposure to ingested nitrate and nitrite can produce NOC, an International Agency for Research on Cancer Working Group concluded in 2006 that ‘‘ingested nitrate or nitrite under conditions that result in endogenous nitrosation is probably carcinogenic to humans’’ [43].
Methods for the Determination of N-Nitroso Compounds
659
3.2 Animal studies NDMA produced acute liver necrosis in rats and other animal species [1,7,25,26], and the acute toxicities in animals of many NOC have been recorded [18,44]. The dose of NDMA causing 50% lethality in rats is 40 mg/kg. After the initial report of the carcinogenicity of NDMA [3], it was found that most NOC are carcinogenic, inducing tumours in different organs of many rodent and other species, with organ specificity depending on the particular NOC and its dose schedule and mode of administration [7,18,26]. Nitrosamines often induce tumours at sites distant from the site of administration, probably because the sensitive tissues contain cytochrome P450 isozymes that can activate the nitrosamines. In rats and mice, most volatile nitrosamines are potent carcinogens, frequently inducing tumours of the liver and oesophagus in rats. Particular nitrosamines also induce tumours of the nasal cavity, kidney, pancreas and urinary bladder [7,18]. Dimethylnitramine (Me2NNO2) is also carcinogenic, but less so than NDMA [45]. The toxicology of non-volatile nitrosamines has hardly been investigated, except for tests showing that N-nitrosoproline (NPRO) was not carcinogenic in rats [45]. The only reported carcinogen among these compounds is N-nitrososarcosine (NSAR), which was a weak oesophageal carcinogen in rats [18]. Nitrosamines with high ether–water partition coefficients and high volatilities were more carcinogenic than related nitrosamines with the opposite characteristics [46], probably because carcinogens need to cross the lipidic plasma membrane of cells before they can alkylate DNA bases. This suggests that nitrosamino acids, which are expected to have low ether–water partition coefficients, are at most only weak carcinogens. Probably because alkylnitrosoureas are direct-acting mutagens (not requiring metabolic activation), they often, but not always, induce tumours at the site where exposure occurs [7]. After oral administration, NMU induced gastric cancer in guinea pigs [47], Nu-acetyl-N-methyl-N-nitrosourea induced glandular stomach cancer in rats [48] and NMU induced gastric cancer in Mongolian gerbils when their stomachs were infected with the bacterium Helicobacter pylori, a cofactor for human gastric carcinogenesis [49]. Alkylnitrosoureas can be readily produced by the acid-catalyzed nitrosation of alkylureas in the stomach [23,50]. Therefore, as first proposed by the author in 1972 [28,51], nitrosoureas could be factors in the etiology of human gastric cancer. When alkylnitrosoureas were injected into pregnant rats, the offspring developed high incidences of brain tumours [18].
4. ANALYTICAL METHODS 4.1 Safety Because of the carcinogenicity of NOC and the volatility of many nitrosamines [46], NOC should always be worked with in a fume hood while wearing gloves.
660
Sidney S. Mirvish
Because fat-soluble nitrosamines readily penetrate most types of gloves [52,53], gloves should be removed and placed in the hood immediately after contact with nitrosamine solutions. Excess nitrosamines should be destroyed by reduction with aluminium–nickel alloy in alkaline solutions [54]. This reduces nitrosamines to hydrazines, which are further reduced to amines. Potassium ferroate (K3FeO4), a potent oxidant, has also been used to destroy nitrosamines [55]. Nitrosamides should be decomposed by treatment with aqueous alkali. The resulting mixture should be kept overnight in a chemical hood because volatile carcinogenic diazoalkanes are produced.
4.2 Nomenclature The most widely used nomenclature for NOC, which has been adopted by the International Agency for Research on Cancer, is to add the prefix ‘‘N-nitroso’’ to the name of the parent amine or amide. This system is used here. An alternative, simpler system is to name NOC as derivatives of nitrosamines or nitrosamides, e.g., as dimethylnitrosamine rather than as NDMA, but this system is hard to use with more complex NOC. One should refer to ‘‘nitrosamines,’’ not ‘‘N-nitrosamines,’’ because the ‘‘N’’ is superfluous.
4.3 General considerations in NOC analysis To detect contamination during the analysis, reagent blanks should be included with each series of analyses. Contamination with nitrosamines can occur by contact with rubber tubing and stoppers, and from solvents. Artifact formation due to nitrosation by nitrite (present in the sample or formed from atmospheric nitrogen oxides) is best avoided by adding sulfamic acid (SA) or, less commonly, ascorbic acid under acidic conditions before the work-up. Solvents containing alcohols should be avoided in case they form nitrite esters, even though such esters are destroyed by SA [33]. Nitrite reacts with SA to produce nitrogen and reacts with ascorbic acid to produce NO. A 50-fold excess of SA reacts completely with nitrite within 2–3 min at room temperature [56]. Artifactual nitrosamines could also occur by transnitrosation from nitrosothiols (RSNO) directly or due to nitrosation by nitrogen oxides produced by decomposition of the nitrosothiols [57]. Because both nitrosamines [58,59] and nitrosamides [60] undergo photolysis fairly readily, bright lights in the laboratory should be avoided or replaced by yellow lights. Loss of volatile nitrosamines by evaporation should be minimized. An NOC that is not present in the sample should be included as an internal standard wherever possible. An amine, e.g., dibutylamine, can be added that yields a nitrosamine not present in the sample. The appearance of this nitrosamine indicates artifactual nitrosation [61]. Low results can occur due to decomposition of NOC during the analysis, e.g., by slow acid hydrolysis back to nitrite and amines or amides (the reverse of Equations (5) and (8)) [22]. Nitrosamine (but not nitrosamide!) solutions are best stored by making them alkaline and then keeping them at 151C.
Methods for the Determination of N-Nitroso Compounds
661
Several of the preliminary clean-up methods used for secondary amines that are NOC precursors (NOCP) and for nitrosamines that also contain amino groups involve adsorption of the protonated amines from acidic solution by the acidic form of cation exchange resin and elution of the free amines from the resin under basic conditions.
4.4 Determination of volatile nitrosamines Volatile nitrosamines are usually determined by gas chromatography (GC) with detection by thermal energy analysis (TEA). A review by Hotchkiss in 1981 [62] summarizes early methods of analysis and should be consulted for the relevant references. The analytical strategy includes the addition of di-n-propyl nitrosamine, which does not occur naturally, as an internal standard and of SA and a mineral acid (the ‘‘stopping solution’’) to prevent artifactual nitrosation. The first step in an early method was atmospheric or vacuum distillation from slurries, or from slurries with added mineral oil and aqueous alkali, followed by vacuum distillation. The distillate was extracted with dichloromethane. The extract was dried over sodium sulfate and concentrated to about 4 ml with a Kuderna–Danish evaporative concentrator. Final concentration of 0.25–1.0 ml was achieved with a gentle stream of nitrogen. The food matrix can also be extracted directly with dichloromethane by adsorption on a column of Celite and elution with the same solvent. This avoids the distillation step but can rapidly contaminate the GC column with fats. In early studies, the final step for determining volatile nitrosamines was GC-MS [63,64]. After Fine et al. [63] introduced the TEA in 1975, GC-MS was mostly replaced by GC-TEA, but has been re-introduced in several recent studies. Packed (rather than capillary) column GC is adequate for many purposes. GC conditions have included the use of 10% Carbowax 1540 plus 5% KOH as column packing, with the GC programmed from 80 to 1801C (perhaps the most widely used system), 25% Carbowax 20M plus 2% NaOH with the GC run at 1701C (for NDMA), and of Carbowax 20M-terephthalic acid. Capillary column GC can provide improved separations [65]. In GC-TEA, the nitrosamine is passed after the GC through a pyrolyzer at 4501C to decompose the nitrosamine to NO, which is passed into a Thermal Energy Analyser (Thermo-Orion, Beverly, MA, USA). A common practice is to mount the pyrolyzer on top of the GC apparatus. An oil pump maintains the pressure of the system below 0.7 torr (mm Hg). In the TEA, NO reacts with ozone to form NO2 in an excited state. This decomposes to give NO2 and photons of infrared light, which are determined with a photomultiplier. This method (often called ‘‘determination of NOC by chemiluminescence’’) readily detects 25 pmol of nitrosamine. Nitrosamines can also be assayed with the ‘‘Sievers purge system and NO chemiluminescence detector’’ (General Electric Analytical, Boulder, CO), which determines NO by the same method as that used in the TEA and has been widely employed to follow NO formation in biological systems. This system includes a compact one-piece reaction vessel, which contains a single sodium hydroxide trap to remove acids. The sensitivity of this system appears similar to that of the TEA.
662
Sidney S. Mirvish
The GC-TEA peaks are identified by comparing their retention times with those for nitrosamine standards run on the same day. Identity should be confirmed by GC-MS. The TEA system usually provides clear well-defined peaks because it only detects compounds that yield NO. Hence this system can be used without elaborate prior purification, whereas classical MS detects all volatile compounds. Compounds other than nitrosamines that are detected by GC-TEA include nitramines, some pyrroles and some aliphatic, but not aromatic, C-nitro compounds [62,66]. Nitrosamines can be distinguished from nitramines by UV irradiation, which destroys nitrosamines far more readily than it does nitramines [67]. The decomposition of nitrosamines by HBr in acetic acid [68] has been used to help identify them [67]. The presence of NDMA and NPYR has been confirmed by their oxidation to the corresponding nitramines with pentafluoroperoxybenzoic acid, a clean-up with Celite and acid alumina, and GC-TEA or GC-electron capture detection [66]. Use of this method confirmed the identity of NDMA and NPYR peaks derived from bacon, malt, non-fat dried milk powder and beer [66]. Collaborative studies with a reproducibility of, generally, less than 15% were performed for the analysis by the same method of volatile nitrosamines in cheese, cured meat, malt and beer [62]. In 1990 a collaborative study [69] was carried out by 10 laboratories on a method for determining nitrosamines in hot dogs containing minced fish or meat spiked with 0, 3 or 5 mg/kg each of NDMA, NPYR and N-nitrosomorpholine (NMOR). Instead of distillation, this method involved adsorption on a mixture of Celite and anhydrous sodium sulfate with elution by dichloromethane, passage of the eluate through a second column containing acidified Celite (to remove amines), with elution by pentane–dichloromethane 95:5 (to remove fats) and then by pure dichloromethane, concentration of the latter eluate to about 4 ml in a Kuderna–Danish apparatus and then to 1 ml on a microSnyder column, and analysis by GC-TEA. The results showed good agreement between the different laboratories. A similar method has been used to determine NDMA in beer [70]. The Pensabene group [71,72] reported a similar method for determining N-nitrosodibenzylamine, a contaminant derived from rubber and found in hams processed in elastic rubber netting. Ham samples were ground in a mortar and pestle with anhydrous sodium sulfate, Celite, propyl gallate and an internal standard. The mixtures were packed in columns and eluted with dichloromethane, which was passed through silica gel columns with elution by ether– dichloromethane 3:7 or through a Sep-Pak column (solid phase extraction (SPE)), and were analysed by GC-TEA [69]. Because of the poor volatility of Nnitrosodibenzylamine, the GC apparatus was linked to the TEA by a line heated to 2751C. N-Nitrosodibenzylamine (3–130 mg/kg) occurred in 12 of 18 hams. The detection limit was 1 mg/kg. Identity was confirmed by GC-MS. The method could be used to analyse 10 volatile nitrosamines in addition to the test compound. Pensabene et al. [73] also reported the analysis of nitrosamines in hams using supercritical fluid extraction (SFE) with CO2 instead of SPE. Results were similar of the two methods, but the supercritical fluid method enabled 20–24 samples/day to be analysed compared to 8–12 samples/day for SPE.
Methods for the Determination of N-Nitroso Compounds
663
Several recent studies determined volatile nitrosamine levels in foods and cigarettes by GC-MS rather than GC-TEA, presumably because analytical laboratories are more likely to have MS than chemiluminescence facilities, MS instruments are simpler to use and cheaper than earlier, and MS can both measure the amount of nitrosamine and confirm its identity. MS is now fast, accurate, specific, sensitive and quantitative. However, TEA usually requires less elaborate clean-up of samples than MS because of the high specificity for compounds that yield NO. As an example of the use of MS, the tobacco-specific nitrosamines 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and Nu-nitrosonornicotine were determined in cigarettes by adding 13C-NNK as an internal standard and using automated extraction with ethyl acetate in a Dionex ASE 200 accelerated solvent extractor [74]. The extracts were washed with aqueous sodium hydroxide, passed through extraction columns and analysed by GC-MS. Two fragment ions were measured for each nitrosamine. Other examples of this approach induce studies on NDMA levels in human faeces [75] and on NDMA and N-nitrosodiethylamine (NDEA) levels in meat after the addition of sodium chloride and sodium ascorbate, which lowered the nitrosamine levels, or after baking the product, which increased these levels [76]. The latter study was performed using a clean-up by combined distillation-solvent extraction [77], followed by capillary GC at 50–1501C coupled to MS. This study is discussed in Section 5.1. Reverse-phase HPLC-TEA methods are generally unsuitable because cold traps are needed to remove organic solvents after the HPLC and they become blocked with ice. However, Eerola et al. [78] used HPLC-MS to determine volatile nitrosamines in dry sausages. Homogenized sausages (10 g) were minced with 300 mg of propyl gallate, 10 ng of N-nitrosodipropylamine (as internal standard), sodium sulfate, Celite and dichloromethane. The filtered extract was applied to a silica column, which was developed with dichloromethane–pentane 1:3 and then with dichloromethane–ether 7:3. The latter eluate was subjected to HPLC on a Spherisorb-ODS column, which was eluted with a water–methanol gradient, with monitoring by UV absorption at 230 and 254 nm. The eluate was passed continuously into a mass spectrometer with a HPLC interface operated in the positive ionization mode. Analysis was carried out by tandem MS using atmospheric pressure chemical ionization in the selected reaction monitoring (SRM) mode. This soft ionization method is a less energetic process than electron ionization. The MH+ ions were used to determine NDMA, NPYR, NDEA, N-nitrosopiperidine and N-nitrosodipropylamine. Monitored product ions were formed by loss of the nitroso or the alkyl group from the parent ion. In 1989 Belardi and Pawliszyn [79] described a solid phase microextraction (SPME) technique that has become widely used for concentrating organic compounds from water and foods. An advantage of this method is that no environmentally damaging organic solvents are used. In 1997 Sen et al. [80] applied this method to the semi-quantitative analysis of N-nitrosodibutylamine and N-nitrosodibenzylamine in smoked hams packed in elastic rubber netting. The hams were steam-distilled and SPME fused silica fibres coated with a liquid
664
Sidney S. Mirvish
phase 75 m thick of poly(dimethylsiloxane) or polyacrylate were equilibrated with the head-space (HS) over the distillate. The fibres were inserted into needles and injected into the injector port (maintained at 2201C) of a GC-TEA apparatus to desorb the nitrosamines. A glass lining in the injector port guided the SPME fibre needle into a capillary column, which was coated with Supelcowax-10. The GC was run with a temperature gradient of up to 2201C. Recoveries of the test nitrosamines were 41–112%. Detection limits were 1–3 mg/kg. In 2001, Ruiz et al. [81] described an SPME method for the analysis of volatile compounds in foods. The SPME fibre was injected directly into a food using a specially designed extraction device. The fibre was equilibrated for 30 min and desorbed in the GC injector port at 2801C. The gas in the injector port was then passed rapidly via a valve into the GC apparatus [82]. The transfer line from the GC to the MS instruments was maintained at 2801C. Ventanas et al. [83] applied this method to the analysis of volatile nitrosamines in gelatin gels. GC was performed on a capillary column lined with 5% phenylmethylsilicone (HP-5) bonded-phase fused silica. Analysis was carried out by MS using the selected ion-monitoring mode. In a study of Andrade et al. [84], volatile nitrosamines in sausages were determined by HS analysis using SPME (HS-SPME) on fused silica fibres coated with polyacrylate or polydimethylsiloxane-divinylbenzene, followed by GC-TEA. The method was stated to be simple, rapid and of adequate accuracy and sensitivity. Volatile nitrosamines in sausages were determined by vacuum steam distillation followed by extraction with active carbon and micellar electrokinetic chromatography, with confirmation by MS [85]. NDMA was detected in 17% of Chilean fish-meal samples, even though the detection limit of 11 mg/kg was relatively high. The method included extraction with ethyl acetate, column chromatography on silica gel and GC linked to a nitrogen–phosphorus-specific detector [5]. In 2003 Sanches-Filho et al. [86] described the analysis of volatile nitrosamines in sausages by vacuum steam distillation, adsorption from the distillate onto activated carbon, elution with acetone–dichloromethane and capillary electrophoresis (micellar electrophoretic chromatography) using a fused silica capillary and a potential of 10 kV. The method separated and detected several added nitrosamines, but was only applied to two unspiked samples. These contained peaks with the retention times of NDMA, NMOR, NPYR and NDEA. Cardenes et al. [87] recently described a sensitive method for determining volatile nitrosamines after dichloromethane extraction from aqueous extracts at neutral pH and denitrosation by heating with HBr–HOAc–water for 10 min at 1001C to give the corresponding secondary amines. Conversion to dansyl derivatives (Figure 5) was achieved by reacting the amines for 30 min at 401C with dansyl chloride in bicarbonate buffer or by a fast microwave-assisted procedure that took less than 5 min and would be especially useful for an automated system. The dansyl derivatives were separated by HPLC on a C-18 column. Cigarette smoke condensate contained 20–80 ng NMOR and 0–5 ng NPYR–cigarette. However, this method would determine the corresponding secondary amines in addition to the nitrosamines. Perhaps prior extraction of the
Methods for the Determination of N-Nitroso Compounds
Figure 5
665
Formation of dansyl derivatives of secondary amines.
nitrosamines from acidified solutions would prevent interference from the amines. Eerola et al. [78] reviewed several earlier papers that used the dansylation method to determine nitrosamines and noted that the corresponding amines would have been determined as nitrosamines.
4.5 HPLC-TEA of nitrosamino acids In 1984, Tricker et al. [11] described an HPLC-TEA method for determining nonvolatile nitrosamines in cured meats. Cured meat (5 g samples) was blended with ammonium sulfamate and sodium sulfate in 2 M phosphoric acid. Pipecolic acid and a test nitrosamine were added to detect artifact formation (indicated by the appearance of N-nitrosopipecolic acid) and measure recoveries. The resulting slurry was extracted with hexane (to remove fats), which was discarded, and then with ethyl acetate, which was concentrated. Nitrosamino acids in the concentrate were passed through a Bond-Elut aminopropyl column and subjected to HPLC on a cyano-based column with hexane–acetone–acetic acid (81:18:1) as the mobile phase. The HPLC eluate was passed successively through (a) the TEA pyrolyzer run at 4801C to liberate NO, (b) cold traps of dry ice-isopropanol and liquid nitrogen to freeze out the solvents and (c) the TEA apparatus. Recoveries were 59–88% for 250 mg/kg each of the added nitrosamines NSAR, NPRO, N-nitrosothiazolidine-4-carboxylic acid (NTCA), N-nitrosohydroxyproline, N-nirosothiazolidine and three N-nitroso derivatives of dipeptides with N-terminal proline. The detection limit for each nitrosamine was 5–10 mg/kg. To prevent ice formation in the cold traps, which blocked the gas flow, Sen et al. [13] used an organic buffer containing 2% water as the HPLC solvent. By this means they could separate the syn and anti isomers of NSAR and NPRO on a silica column. However, this method sometimes showed high responses in blank runs and seems not to have been pursued.
4.6 GC-TEA of methyl esters of nitrosamino acids This is now the preferred method for determining nitrosamino acids such as NPRO, because it is more rugged, more sensitive and simpler to use than HPLCTEA [13]. The analysis of poorly volatile nitrosamines, including nitrosamino acids, was reviewed by Massey [14], Sen and Kubacki [13] and Tricker et al. [11].
666
Sidney S. Mirvish
In 1981, Ohshima and Bartsch [88] reported that NPRO occurred in the urine of a subject who ingested nitrate and the amino acid l-proline. NPRO formation is a useful test because it may indicate the propensity for the in vivo (probably gastric) formation of carcinogenic nitrosamines. Gastric NPRO formation should depend on the gastric concentrations of proline, nitrite and inhibitors and promoters of nitrosation, and on gastric pH. The test is considered safe because NPRO was not carcinogenic in tests on rats using doses of up to 36 g NPRO/kg body weight [45,89,90]. Since 1981 many studies, including those from the Ohshima–Bartsch group [91] and the author’s group [92–94], have reported on nitrosamino acid levels in human urine. In such studies, N-nitrosopipecolic acid (NPIC) is added to urine sample as an internal standard, as well as SA and HCl. The nitrosamino acids are converted to their methyl esters with diazomethane (CH2N2) [88] or by heating for 75 min at 701C with boron trifluoride in methanol [95], and are then analysed by GC-TEA. Packed GC columns that have been used in the author’s laboratory include 10% Carbowax 20M on 60–80 mesh Chromosorb W [88] and 3% OV-225 on base-washed 80/100 Supelcoport. Figure 6 shows the separation of NPRO from NPIC on the latter column. NSAR is often detected in human urine in addition to NPRO [93,96]. When diazomethane is used as the methylating agent, NTCA and 2-methyl-NTCA are also detected [97,98]. These nitrosamines arise by nitrosation of the product
NPIC
NPRO
millivolts
300
200
100
2
4
6
8
minutes
Figure 6 GC-TEA tracing of TMS derivatives of NPRO extracted from human saliva and of the internal standard NPIC.
Methods for the Determination of N-Nitroso Compounds
667
Figure 7 Formation of NTCA and 2-methyl-NTCA.
formed by the condensation of formaldehyde (in the case of NTCA) or acetaldehyde (in the case of 2-methyl-NTCA) with cysteine (Figure 7). Their level in urine is about twice that of NPRO and their formation proceeds up to 500 times faster than that of NPRO. NTCA and 2-methyl-NTCA are not detected when BF3–methanol is used for the methylation, apparently because they are hydrolyzed by this reagent [99]. Nevertheless, BF3–methanol is easier to use and safer than diazomethane. Also, NTCA and 3-methyl-NTCA are unlikely to be good predictors of the in vivo formation of carcinogenic nitrosamines, because their gastric formation presumably depends on the levels of their precursors, formaldehyde, acetaldehyde and cysteine, in addition to those of nitrite, other nitrosating agents and nitrosation promoters and inhibitors. Therefore, the author’s group used BF3–methanol in their studies. Outram and Pollock [100–102] reported that N-nitrosodialkanoic acids (free and bound as amides to amino acids and peptides) were formed during the nitrosation of gastric juice and of dipeptides [101]. These products were detected by GC-TEA after methylation with diazomethane and probably arose via the genesis of carboxyalkylating agents from nitrosated amino acids and peptides (Figure 8) [100]. The structures of representative compounds were confirmed by elemental analysis [102] and by NMR spectrometry [102] and MS [100]. The authors estimated that 80% of the total nitrosamines detected in nitrosated gastric juice by their GC-TEA method were N-nitrosodialkanoic acids.
4.7 GC-TEA of hydroxyalkylnitrosamines Volatile hydroxyalkylnitrosamines can be determined directly by GC-TEA if the molecular weight is not too large and high temperatures are used for the GC. Thus the author’s group used GC-TEA with a column of 10% Carbowax-20MTPA on Chromosorb GHP heated to 1901C to separate and determine underivatized N-nitroso-2-, 3-, 4- and 5-hydroxymethylpentylamine, which are metabolites of N-nitrosomethylpentylamine, a potent oesophageal carcinogen in the rat [103]. Most studies have determined hydroxyalkylnitrosamines by GC-TEA of their trimethylsilyl (TMS) derivatives. For example, there is evidence that the inductions of lung cancer by cigarette smoke is in part due to the lung
668
Sidney S. Mirvish
Figure 8 Proposed origin of N-nitrosodialkanoic acids.
Figure 9 Tobacco-specific nitrosamines 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and Nu-nitrosonornicotine (NNN), NNK metabolite 4-(methylnitrosamino-1-(3-pyridyl)-1-butanol (NNAL) and two internal standards, iso-NNAL and NPPA, used for NNAL analysis.
carcinogen NNK [30]. NNK is metabolized to give 4-(methylnitrosamino)-1-(3pyridyl)-1-butanol (NNAL), which is excreted in the urine together with its b-Oglucuronide (Figure 9). The urinary level of NNAL plus its glucuronide has been determined in many studies. A standard method [65,104] involves hydrolysis of the glucuronide with b-glucuronidase, adsorption of the NNAL on Celite columns, elution with dichloromethane, transfer to methanol–HCl, passage through cation exchange cartridges with elution by a water–methanol–NH4OH mixture, evaporation to dryness, conversion to TMS derivatives by treatment with N,O-bis-TMS-trifluoroacetamide and capillary GC-TEA. An internal standard, 4-(methylnitrosamino)-4-(3-pyridyl)-1-butanol (iso-NNAL), is added before b-glucuronidase treatment and a second nitrosamine, N-nitroso-3picolylamine, is added before the silylation step as an injection standard. A recent method for NNAL in urine involved HPLC on a molecularly imprinted polymer (MIP) specific for NNAL [105,106]. To prepare this maternal, highly cross-linked polymer is synthesized in the presence of a template molecule that mimics the analyte and forms cavities that are sterically and chemically
Methods for the Determination of N-Nitroso Compounds
669
complementary to the analyte. The HPLC eluate is then analysed for NNAL by electrospray ionization MS-MS. This system requires a less elaborate clean-up than previous methods.
4.8 HPLC-photolysis-TEA of non-volatile NOC Photolysis has been used to detect non-volatile NOC after their separation by HPLC. The resulting NO is determined by TEA. This system has been applied to nitrosamides (see Section 4.13). A 1989 study by Conboy and Hotchkiss [107] used an ion-suppression system (10 mM trifluoracetic acid at pH less than 2) or an ion-pair system (tetrabutylammonium dihydrogen phosphate at pH 7) with water–acetonitrile gradients. The HPLC eluate was passed through a borosilicate coil into which was bubbled a stream of helium while the column was irradiated with a mercury-vapor UV lamp. NO produced from the NOC was swept thorough a series of cold traps and determined by TEA. Peak widths of 30–60 s were achieved for mixtures containing 2.4–14 ng each of eight NOC, including NPRO, hydroxy-NPRO, NTCA and four nitrosamides. The method was applied to the analysis of human urine and gastric juice. The detection limit was 2–5 mg/L.
4.9 Havery’s HPLC-TEA method for all types of NOC In 1990 Havery described an analytical system in which aqueous NOC solutions were separated by HPLC and then decomposed to form NO, which was determined by TEA ([108] and D.C. Havery, personal communication). The HPLC used a Zorbax-ODS column and different water–acetonitrile gradients depending on the NOC. The HPLC eluate was mixed with HI, which reacted with the NOC in a post-column reactor to liberate NO, which was analysed by TEA. Oxygen flow rate in the TEA was set to give a pressure of 0.35 torr when the HPLC was disconnected. After connecting the HPLC system, the TEA pump pulled the HPLC eluate and the reagents through the post-column reactor. In this reactor (a glass coil heated to 701C), the HPLC eluate was mixed with helium carrier gas, 10% KI in water (delivered with a separate pump) and 10% H2SO4 in acetic acid (drawn in by the TEA pump). The TEA vacuum gauge then read 0.9–1.0 torr. NOC reacted with HI formed from the KI to generate NO. The NO was swept by the helium through several cold traps to remove acids and water, and then passed into the TEA. Although the system is complicated, it could detect all the principal types of NOC. This method was used by Sen et al. [109,110] to determine nitrosoureas (see Section 4.13).
4.10 Determination of total ANC The method generally used for total ANC depends on the finding that HBr, but not HCl, reacts with NOC to produce NO (Equations (11) and (12)) [68]. The ANC method was introduced in 1976–1978 by the Walters group [111,112]. Solutions of ANC, generally but not necessarily in water, are treated with SA under acidic
670
Sidney S. Mirvish
conditions to destroy any nitrite present. SA also eliminates a slight response due to nitrate [13]. The resulting solution is injected into a mixture containing HBr, which reacts with NOC to liberate NO, which is determined by TEA. If SA is not added, the method can be used to determine nitrite (which apparently is also reduced to NO by HBr), preferably after separating the nitrite by HPLC [113]. R1 NðNOÞR2 þ HBr ! R1 NHR2 þ NOBr
(11)
2NOBr ! 2NO þ Br2
(12)
In the U.K. Massey et al. reported ANC levels in beer, cured meat and other foods [114–116]. Beer was treated with SA and passed through an anion exchange column to remove nitrite and nitrate before the ANC determination [115]. For cured meat and other foods [114], 0.1–1.0 g minced food was shaken for 30 s with ethyl acetate, the mixture was treated with acetic acid and HBr, and NO evolution was monitored by TEA to measure ANC. This method is similar to the ANC method described below. ANC levels in ethyl acetate extracts of human gastric juice were positively correlated with gastric pH [117]. In 1993 Xu and Reed [118] examined the relationship between gastric ANC levels in un-extracted fasting gastric juice and gastric pH. They obtained two peaks of ANC concentration, at pH 1.2–2.5 and at pH 6.2–8.3. Mean ANC levels for the two pH ranges were 1.45 and 3.37 mM. This result suggests that both acid-catalyzed nitrosation at pH 1.2–2.5 and bacteria-mediated nitrosation at pH 6.2–8.3 produce gastric ANC. Volatile nitrosamines and nitrosamino acids generally constitute about 1–2% and 20% of the ANC in foods and biological fluids [117]. The remaining 80% of the ANC could be the most important fraction for carcinogenesis. It is not certain that all these ANC, which have mostly not been separated and identified (for an exception where an NOCP was identified, see Ref. [39]) truly are NOC. The various studies on ANC analysis used different solvents to extract the ANC from foods. The ANC method used but the author’s group [33,34] is based on similar but more complicated methods for the analysis of ANC in human gastric juice developed by Xu and Reed [119] and Pignatelli et al. [120]. Samples of diet or mouse faeces are dried to constant weight for 36 h at 1 torr and 01C. The samples (up to 1 g) are soaked for 30 min in water, vortexed and centrifuged. Aliquots of the supernatant are incubated with SA and HCl for 15 min and injected into a mixture of ethyl acetate, acetic acid, HCl and HBr that is refluxing in a four-neck round-bottom flask at less than 0.7 torr and 281C. The oil pump in the TEA maintains the vacuum. A stream of argon sweeps the liberated NO through six wash-bottles containing agents that remove acids and water, and then into the TEA. The method accurately measures ANC, even in crude extracts, but does not separate individual compounds. NPRO (0.1 nmol) is injected periodically as a standard. To determine ANC precursors (ANCP), aliquots are nitrosated with 110 mM nitrite at pH 1.5–2.0, SA is added and dilutions (usually 1/100) are analysed for ANC. Dilutions are made in 1% SA to remove nitrite derived from atmospheric nitrogen oxides.
Methods for the Determination of N-Nitroso Compounds
671
Relative to the response for NPRO, the ANC method gave yields of close to 100% for simple nitrosamines, including NDMA and NMOR, 77% for 1-methyl-3nitro-1-nitrosoguanidine (a carcinogen and direct-acting mutagen) and only 16% for NMU [33]. The specificity of the ANCP method was tested by treating various nitrogen compounds with nitrite under the conditions used to assay ANCP [33]. ANC yields were less than 1% for peptides with nitrogen only in the peptide (–NHCO–) bond and for diethylamine, 6–12% for alkylureas, 45–97% for the readily nitrosated [23] secondary amines proline, morpholine and piperazine, 67% for 1-deoxy-N-1-fructosylvaline, 27–88% for tryptophan, up to 31% for tryptophanyl alanine, up to 5% for alanyl tryptophan and less than 2% for histidine [33,39]. The low ANC yield for simple peptides not containing tryptophan and for diethylamine is attributed to their slow rate of nitrosation [23]. These results indicate that most of the hot dog ANCP are nitrosamines derived from readily nitrosated amines. The ANCP in hot dogs did not include significant amounts of tryptophan because the concentration of free tryptophan in hot dogs was far less than that of the ANCP and because ANC produced from tryptophan were far less stable than ANC derived from hot dog ANCP [39]. The ANCP in hot dogs were purified by adsorption from aqueous extracts onto silica gel, elution with acetonitrile and then methanol, adsorption of the methanol eluate on cation exchange resin in its protonated form, desorption with 1N NH4OH and HPLC on a lead (Pb++) carbohydrate column run at 901C [39]. After nitrosation, addition of SA, and neutralization, the material eluted from the resin with ammonium hydroxide (the ‘‘ammonia eluate’’) was directly mutagenic in the Ames test with Salmonella typhimurium TA-100, producing four times the number of background mutations [39]. Ammonia eluate that was not nitrosated showed twice the background mutations. These results suggest that the hot dog ANCP-derived ANC might indeed be carcinogenic. This might be especially relevant for the colon because feeding red meat and hot dogs, which contain both ANC and ANCP, increased the faecal excretion of ANC in humans [35] and mice [34], and colonic ANC levels are similar to those in the faeces [34]. ANCP-rich fractions from the HPLC of hot dog extract were converted to TMS derivatives and examined by GC-MS. One fraction was identified as the TMS derivative of 1-deoxy-N-1-glucosyl glycine (Figure 10) [39]. This suggests that N-1glucosyl amino acids and peptides are significant ANCP in meat products. Such compounds are very weak bases [121] and hence [23] would be rapidly nitrosated, as was the case for the hot dog ANCP [33]. Facile nitrosation of N-glycerylamines was indicated by the ready conversion of N-2-deoxy-2-fructosyl valine to NOC
Figure 10 1-Deoxy-N-1-glucosyl glycine.
672
Sidney S. Mirvish
[33] and the low pKa predicted for these compounds. In fact, one N-glucosyl dipeptide had a pKa of only 5.6 [121], relevant because a low pKa for secondary amines is generally associated with a high rate of nitrosation [23]. HI has been used instead of HBr to produce NO from NOC. Thus Havery’s method for determining NOC used HI to generate NO [108] (see Section 4.9). Fiddler et al. [122] employed HI to assay ANC in acetonitrile extracts of cured meat products by a modification of Havery’s procedure. Also, Cox et al. [123] used HI in a method for determining ANC in human urine. After removal of nitrate and nitrite by treatment with anion exchange resin and sulfanilamide, urine extracts were mixed with HI–sulfuric acid and the liberated NO was determined by TEA. In 1932 cuprous chloride (CuCl) was reported to react with nitrosamines to give NO and the parent amines [124]. This reaction was later recommended as a means of purifying secondary amines [125]. In 2005, Wang et al. [126] described a method for determining ANC using cuprous chloride to produce NO from the ANC. As in the HBr method, SA was added before the TEA. ANC formation from NPRO was linear from 4 pmol to 2 nmol. The cuprous chloride method could be used with aqueous or organic solvents, except for dichloromethane and chloroform, and was applied successfully to the analysis of ANC in meat products and sauces. Excessive foaming interfered in the analysis of beer, shampoos and lotions. Equations (13)–(15) show the proposed reactions. Nitrite esters (RONO), oximes (RCH¼NOH) and C-nitro and C-nitroso compounds gave negative responses. Inorganic nitrite and nitrite esters were determined if SA was omitted. S-Nitroso-N-acetylpenicillamine and S-nitrosoglutathione were determined in yields of 3.3% and 32%, respectively, after SA was added. Nitrate increased the baseline, probably due to a very slow release of NO. Interference by nitrate could be prevented by absorbing the nitrate on anion exchange resin before the NOC analysis. CuCl þ HCL $ ½CuCl2 þ Hþ
(13)
R1 R2 NNO þ Hþ $ ½R1 R2 NHNOþ
(14)
½R1 R2 NHNOþ þ ½CuCl2 ! R1 R2 NH þ NO þ CuCl2
(15)
The author’s group (M.P. Lisowyj and S.S. Mirvish, unpublished results) used the HBr method to confirm and extend the findings of Wang et al. [126] that nitrosothiols could be determined as ANC. Solutions (1.0 nmol/mL) of glutathione and dithiothreitol were nitrosated and treated with SA as in the NOCP method [33] and then analysed for ANCP. After the solutions were stored in ice for 0–10, 60–70 and 90–100 min, percent ANC yields based on the response for NPRO were 47%, 32% and 18% for glutathione, and 42%, 20% and 20% for dithiothreitol. Analysis of S-nitroso-N-acetylpenicillamine as ANC after addition of SA gave apparent yields of 180% compared to that for NPRO. In contrast to the instability of these S-nitroso compounds, the ANCP in hot dogs were stable when stored for several hours in ice (unpublished results), indicating that the ANCP in hot dogs could include at most only a small proportion of nitrosothiols.
Methods for the Determination of N-Nitroso Compounds
673
4.11 Determination of nitrosamides as ANC Pignatelli et al. [120] reported only a 25% yield for NMU compared to that for NPRO when NMU was determined as ANC. Xu and Reed [119] reported a broad peak for NMU when HBr alone was used for denitrosation, but a sharp peak when both HBr and HCl were employed. In our study on ANC determined by the HBr method [33], 1-methyl-3-nitro-1-nitrosoguanidine showed a narrow peak (a short elution time), whereas NMU gave broad peaks 13–15 min wide, with molar yields less than 20% of those for NPRO. When the temperature of the refluxing ethyl acetate was raised from the standard 281C, the width of the NMU peaks was reduced to 3.5–4.0 min and the response rose to 32% (at 331C) and 39% (at 361C) of that for NPRO [33]. In contrast, Sen et al. [127] obtained nearly quantitative recoveries by the Havery method [108] when NMU was denitrosated with HI at 701C (see Section 4.13). Sen et al. [128] also reported that inorganic nitrite could be determined by the method for ANC if SA was omitted.
4.12 Determination of alkylureas Krull et al. [129] used an HPLC method with detection by UV absorption to determine 1-nitroso-1,3-bis-(2-chloroethyl)-urea in blood with a detection limit of 100–200 mg/L). Conboy and Hotchkiss [107] later used a similar method, but with detection by TEA. The detection limit was 2–5 mg/L when this method was applied to the analysis of N-nitrosotrimethylurea in porcine gastric fluid. Dried fish and nitrite-preserved meat products are likely risk factors for the etiology of gastric cancer [28] and alkylnitrosoureas and related NOC can induce gastric cancer in laboratory animals (see Section 3.2). Because alkylureas could readily be converted to alkylnitrosoureas in the stomach, the author’s group studied the occurrence of alkylureas in aqueous extracts of marine animal products and fried bacon [130]. Methylurea was not detected in the absence of nitrosation, but was detected after the aqueous extracts were ‘‘nitrosated– denitrosated,’’ i.e., were treated with very large amounts of nitrite at pH 1 to convert precursors to alkylnitrosoureas, and were then stored at pH 0 to convert the alkylnitrosoureas to alklylureas. This treatment destroys urea itself, which reacts with nitrite to give CO2 and nitrogen (the van Slyke reaction) [131,132]. The resultant alkylureas were extracted with n-butanol. Because alkylureas show pKa values of about 0.7 (the value for methylurea [133]), they were further purified by adsorption of the protonated alkylureas on columns of cation exchange resin at pH 1 and elution of the deprotonated ureas at pH 4. Purification was followed by a colorimetric method involving the addition of semidine (N-phenyl-pphenylenediamine), ferric chloride and HCl, which gives a purple colour with alklylureas and alkylnitrosoureas, with a detection limit of 10 nmol/sample [134,135]. Subsequent purification by paper chromatography and HPLC followed by MS enabled us to identify and determine alkylureas in the nitrosated– denitrosated products. n-Propylurea, 3-butenylurea and a hydroxybutylurea (not fully identified) were detected after nitrosation–denitrosation of extracts of certain crab and lobster species.
674
Sidney S. Mirvish
Figure 11 Nitrosation of CRN and methylguanidine to give methylurea and NMU.
Large amounts of creatine and phosphocreatine (which converts adenosine diphosphate to adenosine triphosphate in vivo) occur in muscle tissues of vertebrates, including fishes. When foods containing creatine are dehydrated or heated, the creatine loses water to give CRN, which is also the urinary metabolite of creatine. In 1971, Archer et al. [136] discovered that nitrosation of CRN produces CRN-5-oxime and 1-methylhydrantoin-5-oxime (Figure 11) [136]. In 1982 the author’s group discovered that the precursor of methylurea in dried bonito fish was CRN [137]. Yields of methylurea after nitrosation–denitrosation of CRN, CRN-5-oxme and 1-methylhydantoin-5-oxime were 0.04%, 0.04% and 7.0%. On this basis it was proposed that CRN produces methylurea by the sequence shown in Figure 11 and that the first two of these nitrosations were the ratelimiting steps. A later study of these reactions included the separate determination by HPLC of the syn and anti isomers of the two intermediate oximes [138]. Reaction rates were proportional to nitrite concentration squared as in Equation (9). Nitrosation of creatine produced NSAR [136] but not methylurea [137]. The extremely high CRN concentration of 4 g/kg in both dried fish and fried bacon, the lengthy storage time at ambient temperature for dried fish and the high temperature and low water content during the frying of bacon could make methylurea formation in these products significant, despite the slow nitrosation of CRN. Nitrosation of methylguanidine gave a 35% yield of NMU at a rate less than 1% of that for NMU formation from methylurea (Figure 11) [51,139]. This is relevant here because methylguanidine occurs at levels of 60–1,900 mg/kg in fresh beef and in various species of fish [140]. Bredereck et al. [141] reported in 1964 that urea reacts with the diethylacetal of dimethylformamide to form its dimethylaminomethylene derivative (Figure 12). In 1979, Kawabata et al. [142,143] applied this method to the detection of alklylureas in foods. For this purpose, they used successive chromatography on Dowex 50 (H+ form), cation exchange resin, Dowex IX anion exchange resin (OH form) and basic alumna, conversion of alkylureas to
Methods for the Determination of N-Nitroso Compounds
675
Figure 12 Formation of dimethylaminomethylene derivatives of alkylureas.
their dimethylaminomethylene derivatives (Figure 12) and GC of the derivatives on an OV-17 column with flame ionization detection. GC-MS using the same GC conditions confirmed the identities of the alkylurea derivatives. Mean recoveries of eight alkylureas, added to salted dried fish samples, were 71–90%. The detection limit for these alkylureas was 10–100 mg/kg food.
4.13 HPLC-photolysis-TEA of nitrosamides Nitrosamides cannot be determined by pyrolysis to give NO because most nitrosamides are poorly volatile and decompose on heating to produce nitrogen [144]. Shuker and Tannenbaum [145] reported in 1983 on a method for determining nitrosamides based on their photochemical decomposition to give nitrite. Because nitrosamides yield NO as the primary product of photolysis [60], nitrite is presumably produced by oxidation of NO to N2O3 and N2O4, which react with water to give nitrite. In the method of Shuker and Tannenbaum, nitrosamides were separated by HPLC on a C-18 cartridge eluted with pH-6 buffer-acetonitrile mixtures. The HPLC eluate was passed through 15 m of 0.25 mm Teflon tubing wound round the outside of a water-cooled cylindrical glass jacket, which surrounded a high-intensity-discharge metal halide lamp, that emits light at 380–420 nm and is used in light-houses. Teflon tubing is transparent to visible light and hence is suitable for studies on nitrosamides, which absorb light and therefore are decomposed at 380–430 nm. The apparatus was enclosed in a box lined with aluminum foil. Nitrosamides were completely decomposed to give nitrite after exposure to the light for 2 min. Nitrite in the eluate was analysed colorimetrically with the Griess reagent [146]. The method was used to determine methylnitronitrosoguanidine, NMU, N-nitroso derivatives of bile salts such as taurocholic acid, N-methyl-N-nitrosoacetamide and N-nitrosocimetidine, all of which are or are related to nitrosamides. Deng et al. [147–149] reported the occurrence of NMU when Oriental fish sauces were nitrosated under mild conditions (1 h, 5 mM nitrite, pH 2, 371C), followed by addition of SA. Under these conditions, most methylurea, but very little CRN, would be converted to NMU. Aqueous extracts of nitrosated fish sauce were mixed with sodium chloride, deproteinized with tungstophosphoric acid and extracted with acetone–dichloromethane 1:5. The extracts were subjected to HPLC on various columns with elution by aqueous trifluoroacetate–acetonitrile mixtures. NMU in the eluates was determined by photolysis to liberate NO, which was converted to and measured as nitrite [107]. Maximum NMU yields were obtained after nitrosation at pH 1 (the lowest pH tested) and
676
Sidney S. Mirvish
pH 2 [148], as expected if the NMU precursor was methylurea [23,51], but NMU yields were not reported. NMU was not detected in the fish sauce in the absence of nitrosation. After nitrosated fish sauce extracts were subjected to HPLC, MS analysis of the eluates confirmed that NMU was present [150]. NMU was also detected in the stomachs of pigs that were intubated with fish sauce and nitrite and of humans who ingested these materials [151]. Sen et al. [109,110] detected NMU after CRN, Oriental fish sauce and other marine products were incubated with up to 1.6 mM nitrite. Aqueous extracts were incubated with ascorbic acid and SA at pH 1.0–1.5 to prevent artifactual nitrosation, saturated with sodium chloride and kept at pH less than 6–7. The workers avoided exposing samples to strong light and raised temperatures, and avoided delays in processing. The extracts were subjected to a series of additional extractions and clean-ups on C-18 and silica Sep-Pak columns, and were then analysed for NMU by HPLC with post-column chemical denitrosation followed by TEA according to Havery’s method (Section 4.9) [108], or were analysed by GC-MS. The HPLC-TEA method could detect 0.1–1.0 ng and GC-MS could detect 2.5 pg of NMU. In nitrosated cured meat, the authors could detect 0.5 mg/kg of NMU by HPLC-TEA and 0.03 mg/kg of NMU by GC-MS. NMU was not detected in un-nitrosated samples. Because methylurea is very readily converted to NMU [23,51], the procedures of Deng et al. [148] and Sen et al. [109,110], both of which involved nitrosation under mild conditions followed by analysis for NMU, in reality probably are methods for determining methylurea.
5. OCCURRENCE OF NOC IN FOODS 5.1 Occurrence of volatile nitrosamines Figure 1 shows the structures of many of the nitrosamines that can occur in foods. In general, NOC appear to accumulate in foods that are fermented and/or stored for long periods at ambient temperatures, e.g., beer and fish sauce. In the late 1960s, fried bacon was found to contain up to 100 mg/kg (ppb) of volatile nitrosamines, especially NDMA and NPYR [152,153]. In 1972 a group that included the author found that ascorbic acid (vitamin C) inhibited nitrosamine formation in chemical systems [19]. It was then shown that ascorbate inhibits the production of volatile nitrosamines in fried bacon [152]. As a result, the U.S. Food and Drug Administration and, later, government agencies in other countries mandated that nitrite levels in bacon be dropped from 150 to 120 mg/kg and that 500 mg/kg of ascorbate or its non-vitamin isomer, erythorbate, be added to bacon [154]. The effect of this mandate was to lower volatile nitrosamine levels in fried bacon to below 20 mg/kg [152,153]. These levels are considered safe because they do not add much to the total dietary burden of volatile nitrosamines. In 1979, German beer was found to contain a mean NDMA level of 2.7 mg/kg (maximum, 68 mg/kg) [155]. This probably arose from a reaction of dimethylamine, which occurs in malt (germinated barley) and beer [156], with nitrogen oxides in spent gas from the natural gas kilns in which the malted barley was
Methods for the Determination of N-Nitroso Compounds
677
dried. After 1979, NDMA levels in beer were lowered by reducing the flame temperature, by adding elemental sulfur to the flames and especially by the use of indirect heating, in which the heated gasses travel through pipes and are only in indirect contact with the malted barley. The heated gases contain nitrogen oxides that are derived from the reaction of nitrogen with oxygen in the flames and can nitrosate amine. These techniques lowered NDMA levels in beer to less than 0.4 mg/L [70,156,157]. In 1981, the U.S. National Academy of Sciences [6] listed the following values for NOC concentration in foods. In England, fried bacon contained 1–20 (occasionally up to 200), 0.1–0.5 and 0.1–0.25 mg/kg of NPYR, NDMA and N-nitrosopiperidine. Cured meat in the United States and United Kingdom contained less than 1 mg/kg of volatile nitrosamines. In the U.K., 80% of uncooked and fried fish samples contained detectable NDMA, with about onethird of the samples showing 1–10 mg/kg of NDMA and the rest showing lower levels. Japanese broiled salted dried fish and shellfish showed up to 310 and up to 13 mg/kg of NDMA and NPYR, with the highest values in dried squid. In 1986, levels in mg/kg of home-cooked fried bacon were reported to be 17, 4, 9 and 0.7 for NPYR, NDMA, N-nitrosothiazolidine and N-nitrosopiperidine [158]. The fried-out fat contained somewhat higher levels of these nitrosamines. In the United States, in 1981, the mean daily intake of volatile nitrosamines in mg/person was estimated to be 17 from cigarettes (due largely to NNK and Nu-nitrosonornicotine), up to 1.0 in beer, 0.41 in cosmetics and 0.17 in cured meat [6]. The nitrosamines in the last three items were mostly NDMA and NPYR. In Germany, before corrective measures were adopted for beer, the percentages of dietary intake of NDMA due to beer, meat and meat products, cheese and other items were 24, 9, 1 and 66 [159]. In the U.K., the total intakes of volatile nitrosamines in cured meat, fish, cheese and all other foods were 0.43, less than 0.01, less than 0.01 and 0.08 mg/person/day [160]. In Chinese foods, most nitrosamine levels were similar to those in the U.K. but NDMA levels were 5–130 mg/kg in dried shrimp and 3–26 mg/kg in shrimp meat. In Spain, the mean dietary intake of NDMA was estimated in 2006 to be only 0.11 mg/day, mostly derived from processed meat and cured cheese [161]. Rywotycki [76] recently reported mean nitrosamine levels for raw beef of 8 mg/kg (range, 6–11) each for NDMA and NDEA. These results are much higher than those listed above for fried bacon and cured meat. NDEA has not usually been detected in meat products. Most analyses have reported more NPYR than NDMA, whereas here NPYR was not mentioned. However, few results have been reported previously for raw meat. A problem with this study may have been that, apparently, few of the checks listed in Section 4.3 were performed.
5.2 Occurrence of nitrosamino acids Tricker et al. [11] reported the occurrence of nitrosamino acids in smoked cured meat from Germany. The detection limit was 5–10 mg/kg. The principal nitrosamino acids detected and their highest observed concentrations in mg/kg
678
Sidney S. Mirvish
were NSAR, 410; NPRO, 360; N-nitrosohydroxyproline, 560 and NTCA, 1,620. The highest nitrosamino acid levels were found in Icelandic smoked mutton.
5.3 Occurrence and identity of total ANC In the U.K., Massey et al. [114–116] reported ANC levels in mmol/kg of 0.2–1.0 for dried milk, dried soups, coffee, tea and cocoa/chocolate; 0.2–18 for beer; 14–32 for canned cured meat; 11–136 for raw bacon and 8–55 for fried bacon. (The British groups recorded their results as mg of NNO group/kg of food. These results are re-expressed here as mmol/kg by dividing mg NNO by 44.) In a U.S. study by Haorah et al. [33], mean NOC and NOCP values in mmol/kg were 5.5 and 2,700 for hot dogs, 0.5 and 660 for fresh meat, 3.7 and 1,300 for summer sausage, 6 and 1,100 for canned corned beef; 5.8 and 5,800 for salted, dried fish, 2.7 and 6,600 for all sauces (mostly soy sauces), 0.7 and 950 for ketchup, and 29.6 (a very high value) and 7,800 for a Chinese ground bean sauce [33]. In the study by Fiddler et al. [122] on acetonitrile extracts of cured meat, mean results for hot dogs, bacon, fermented salami, dried beef, canned corned beef, canned ham and netted ham were 1.9, 3.5, 9.0, 8.1, 54.6, 5.5 and 6.4 mmol/kg of ANC (these results were presented as mg NPRO/kg and are recalculated here). Note the high results for canned corned beef. In this study, 10 g comminuted meat was mixed with 15 ml acetonitrile to prepare the extracts. In contrast, the Haorah study [33] reported results for water extracts and stated that acetonitrile extracts contained very little ANC. Unlike the Fiddler et al. [122] study, Haorah et al. [33] evaporated the meat samples to dryness before adding acetonitrile, so that the acetonitrile extracts contained little water. Hence the two sets of results are probably comparable. Mean total ANC excretion by healthy subjects was 1.3 mmol/day in the urine and 1.3–3.2 mmol/day in the faeces [117]. The total ANC level in normal gastric juice was 1.3–1.6 mmol/L [117]. Nitrosamino acids and volatile nitrosamines constituted 16% and 0.03% of the ANC in human urine. N-Nitroso derivatives of proline and peptides with N-terminal proline, together with other similar derivatives, constituted 15–20% of the total ANC in meat products [117]. The remaining 80% of the ANC in hot dogs remain to be identified, though the identification of 1-deoxoy-N-1-glucosylglycine in hot dog extracts (Section 4.10) suggests that it and similar glycosyl amino acids and peptides are the major components of these ANC.
5.4 Occurrence of alkylureas and alkylnitrosoureas In the study of methylurea levels in nitrosated–denitrosated dried fish and fried bacon [130] (Section 4.12), methylurea levels after nitrosation–denitrosation were 350 mmol (25 mg) per kg for both foods. In the study on NMU determination in nitrosated food extracts [109] (Section 4.13), NMU levels were up to 140 ng/kg for fish sauces, up to 34 mg/kg for crab and lobster paste, and somewhat lower for other marine animal products. I emphasize that these figures do not indicate actual occurrences, but rather show yields in the foods after nitrosation– denitrosation (for methylurea) or after nitrosation alone (for NMU).
Methods for the Determination of N-Nitroso Compounds
679
6. CONCLUSIONS AND FUTURE TRENDS In most of the principal methods for determining NOC, the NOC are converted to NO, which is measured by TEA. Decomposition of NOC to give NO is achieved by heating volatile nitrosamines to 4501C (pyrolysis) after GC, by treatment of NOC or ANC with HBr [33], HI [108] or cuprous chloride [126], or by photochemical methods [107,145,147–149]. Analyses of volatile nitrosamines were mostly performed by MS until the TEA was introduced in 1978. TEA has since been adopted as the detection step for most methods of NOC analysis. Because TEA is relatively specific for NOC, it generally gives simpler results (clearer tracings) than MS. However, MS has been a useful method for confirming the identity of GC-TEA peaks. Also, many recent studies have used MS rather than TEA to determine nitrosamines, partly because of the greater availability of MS compared to chemiluminescence (TEA and Sievers) instruments in analytical laboratories. In the author’s opinion, the most likely classes of NOC to be causes of human cancer are the simple volatile dialkyl and cyclic nitrosamines (‘‘simple’’ ¼ without other functional groups), which may be causes of oesophageal, nasopharyngeal, laryngeal and bladder cancer [8]; NMU formed by the nitrosation of CRN and, possibly, methylguanidine, which may be causes of stomach and brain cancer; and (with less evidence) N-nitrosoglucosyl amino acids and related compounds, which might be causes of colon cancer. Future analysis of food should focus on these classes of NOC. Following NPRO excretion in urine may continue to be a valuable method for monitoring in vivo nitrosation. The carcinogenicity of non-volatile nitrosamines, including nitrosamines derived from amino acids with secondary amino groups, has mostly not been investigated, except that NPRO is clearly not carcinogenic. Therefore, some of these nitrosamines should at least be tested for bacterial mutagenicity in the Ames test. This would be useful because the Ames test for mutagenicity is relatively cheap and its results are fairly well correlated with carcinogenicity [162]. Individual ANC in crude food extracts have mostly not been identified. This raises the question of whether ANC truly measures NOC, especially since it was reported [126] and confirmed here (see Section 4.10) that some nitrosothiols can also be determined as ANC. It may not matter much if the ANC include small properties of nitrosothiols, if ANC levels are used mainly to indicate the potential for NOC formation, i.e., to indicate the presence of nitrosating agents that could react with NOCP to form NOC. Nevertheless, research is urgently needed to identify the major ANC in foods. The author recommends that, for uniformity, future ANC results should be reported as mmol ANC/kg as in reference [33] and not as mg NNO group/kg [114,115] or as mg NPRO/kg [122]. Most of the results for NOC analysis were published in the early 1980s, e.g., those referred to in [6], and it appears that the monitoring of foods and beverages for their NOC content has slackened off in recent years. However, it is clearly vital to continue this effort by periodic analysis, probably in most cases by government agencies, in case NOC levels rise due to changes in agricultural or
680
Sidney S. Mirvish
manufacturing practices. These analyses should be preformed with at least some of the precautions listed in Section 4.3.
ACKNOWLEDGEMENTS I thank the Editor of this book (Yolanda Pico) and the Reviewer of this article for their advice and encouragement, Donald C. Havery (U.S. Food and Drug Administration) for information about his studies and Nilesh W. Gaikwad (Eppley Institute for Research in Cancer) for advice about MS techniques. This review was written while the author’s research was funded by grant RO3-CA-11753 from the National Cancer Institute, a contract with the Division of Cancer Prevention, National Cancer Institute and a grant to Stephen I. Rennard from the Institute for Science and Health. Several of the techniques used in these projects are summarized here. I thank Michal P. Lisowyj and Michael E. Davis for laboratory assistance with these projects, Michal P. Lisowyj for help in finding references and preparing the figures, and Darcy C. Jackson and Diane C. Torrey for help in typing and arranging the manuscript.
REFERENCES 1 H.A. Freund, Ann. Intern. Med., 10 (1937) 1144. 2 W. McQuiston, R.E. Bowen, G.A. Carpenter and G.B. Wilmot, Basic Studies Related to the Synthesis of 1,1-Dimethylhydrazine by Chloramination, Air Force Off. Sci. Res., Washington, DC, 1979. 3 P.N. Magee and J.M. Barnes, Br. J. Cancer, 10 (1956) 114. 4 J. Sakshaug, E. Sognen, M.A. Hansen and N. Koppang, Nature, 206 (1965) 1261. 5 N. Mendoza, R. Villegas and M. Leon, Informacion Technol., 12 (2001) 15. 6 National Academy of Sciences., The Health Effects of Nitrate, Nitrite, and N-Nitroso Compounds, National Academy Press, Washington DC, 1981. 7 R. Preussmann and B.W. Stewart. In: C.E. Searle (Ed.), Chemical Carcinogens, ACS Monograph 182, Am. Chem. Soc., Washington, DC, 1984, p. 643. 8 S.S. Mirvish, Cancer Lett., 93 (1995) 17. 9 M. Masuda, H.F. Mower, B. Pignatelli, I. Celan, M.D. Friesen, H. Nishino and H. Ohshima, Chem. Res. Toxicol., 13 (2000) 301. 10 R.A. Scanlan, CRC Crit. Rev. Food Technol., 5 (1973) 357. 11 A.R. Tricker, M.J. Perkins, R.C. Massey, C. Bishop, P.E. Key and D.J. McWeeny, Food Addit. Contam., 1 (1984) 245. 12 R.A. Scanlan and F.G. Reyes, Food Technol., 39 (1985) 95. 13 N.P. Sen and S.J. Kubacki, Food Addit. Contam., 4 (1987) 357. 14 R.C. Massey. In: M.J. Hill (Ed.), Nitrosamines: Toxicology and Microbiology, Ellis Horwood, Chichester, 1988, p. 16. 15 A.R. Tricker and S.J. Kubacki, Food Addit. Contam., 9 (1992) 39. 16 G. Yeh and J.D. Ebeler, Chromatogr. Sci., 77 (1998) 77. 17 H. Biaudet, B. Pignatelli and G. Debry. In: L.M.L. Nollet (Ed.), Handbook of Food Analysis, Vol. 2, Marcel Dekker, New York, 2000, p. 1603, Chapter 38. 18 H. Druckrey, R. Preussmann, S. Ivankovic and D. Schmahl, Z. Krebsforsch, 69 (1967) 103. 19 S.S. Mirvish, L. Wallcave, M. Eagen and P. Shubik, Science, 177 (1972) 65. 20 G.J. Karabatsos and R.A. Taller, J. Am. Chem. Soc., 86 (1964) 4373. 21 W.T. Rainey, W.H. Christie and W. Lijinsky, Biomed. Mass Spectrom., 5 (1978) 395. 22 T.A. Turney and G.A. Wright, Chem. Rev., 59 (1959) 497. 23 S.S. Mirvish, Toxicol. Appl. Pharmacol., 31 (1975) 325. 24 K.H. Jacobson, H.J. Wheelwright, J.H. Clem and R.M. Harmon, AMA Arch. Ind. Health, 12 (1955) 617. 25 J.M. Barnes and P.N. Magee, Br. J. Ind. Med., 11 (1954) 167.
Methods for the Determination of N-Nitroso Compounds
26 27 28 29
30 31 32 33 34 35 36
37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64
681
P.N. Magee and J.M. Barnes, Adv. Cancer Res., 10 (1967) 163. P. Jakszyn and C.A. Gonzalez, World J. Gastroenterol., 12 (2006) 4296. S.S. Mirvish, J. Natl. Cancer Inst., 71 (1983) 629. L.E. Dodd, S. Sengupta, I.H. Chen, J.A. den Boon, Y.J. Cheng, W. Westra, M.A. Newton, B.F. Mittl, L. McShane, C.J. Chen, P. Ahlquist and A. Hildesheim, Cancer Epidemiol. Biomarkers Prev., 15 (2006) 2216. S.S. Hecht and D. Hoffmann, Cancer Surv., 8 (1989) 273. M.S. Sandhu, I.R. White and K. McPherson, Cancer Epidemiol. Biomarkers Prev., 10 (2001) 439. M.H. Ward, A.J. Cross, H. Divan, M. Kulldorff, S. Nowell-Kadlubar, F.F. Kadlubar and R. Sinha, Carcinogenesis, 28 (2007) 1210. J. Haorah, L. Zhou, X. Wang, G. Xu and S.S. Mirvish, J. Agric. Food Chem., 49 (2001) 6068. S.S. Mirvish, J. Haorah, L. Zhou, M. Hartman, C.R. Morris and M.L. Clapper, Carcinogenesis, 24 (2003) 595. R. Hughes, A.J. Cross, J.R.A. Pollock and S. Bingham, Carcinogenesis, 22 (2001) 199. P. Jakszyn, S. Bingham, G. Pera, A. Agudo, R. Luben, A. Welch, H. Boeing, G. Del Giudice, D. Palli, C. Saieva, V. Krogh, C. Sacerdote, R. Tumino, S. Panico, G. Berglund, H. Siman, G. Hallmans, M.J. Sanchez, N. Larranaga, A. Barricarte, M.D. Chirlaque, J.R. Quiros, T.J. Key, N. Allen, E. Lund, F. Carneiro, J. Linseisen, G. Nagel, K. Overvad, A. Tjonneland, A. Olsen, H.B. Bueno-de-Mesquita, M.O. Ocke, P.H. Peeters, M.E. Numans, F. Clavel-Chapelon, A. Trichopoulou, C. Fenger, R. Stenling, P. Ferrari, M. Jenab, T. Norat, E. Riboli and C.A. Gonzalez, Carcinogenesis, 27 (2006) 1497. G.R. Bunin, R.R. Kuijten, C.P. Boesel, J.D. Buckley and A.T. Meadows, Cancer Causes Control, 5 (1994) 177. S. Preston-Martin, J.M. Pogoda, B.A. Mueller, E.A. Holly, W. Lijinsky and R.L. Davis, Cancer Epidemiol. Biomarkers Prev., 5 (1996) 599. L. Zhou, J. Haorah, F. Perini, S.G. Carmella, T. Shibamoto and S.S. Mirvish, J. Agric. Food Chem., 54 (2006) 5679. H.A. Risch, J. Natl. Cancer Inst., 95 (2003) 948. R. Jiang, D.C. Paik, J.L. Hankinson and R.G. Barr, Am. J. Respir. Crit. Care Med., 175 (2007) 798. L.N. Kolonel, Epid. Rev., 23 (2001) 72. Y. Grosse, R. Baan, K. Straif, B. Secretan, F. El Ghissassi and V. Cogliano, Lancet Oncol., 7 (2006) 628. R.C. Shank, Toxicol. Appl. Pharmacol., 31 (1975) 361. S.S. Mirvish, O. Bulay, R.G. Runge and K. Patil, J. Natl. Cancer Inst., 64 (1980) 1435. S.S. Mirvish, P. Issenberg and H.C. Sornson, J. Natl. Cancer Inst., 56 (1976) 1125. H. Druckrey, S. Ivankovic, J. Bucheler, R. Preussmann and C. Thomas, Z. Krebsforsch, 72 (1968) 167. H. Druckrey, S. Ivankovic and R. Preussmann, Z. Krebsforsch, 74 (1970) 23. F. Maruta, H. Ota, R.M. Genta, A. Sugiyama, M. Tatematsu, T. Katsuyama and S. Kawasaki, Scand. J. Gastroenterol., 36 (2001) 283. S.S. Mirvish, K. Karlowski, D.F. Birt and J.P. Sams, IARC Sci. Pub., 31 (1980) 271. S.S. Mirvish, J. Natl. Cancer Inst., 46 (1971) 1183. E.A. Walker, M. Castegnaro, L. Garren and B. Pignatelli, IARC Sci. Publ., 19 (1978) 535. E.B. Sansone and Y.B. Tewari, IARC Sci. Publ., 19 (1978) 517. G. Lunn, E.B. Sansone and L.K. Keefer, Carcinogenesis, 4 (1983) 315. R. Bartzatt and D. Nagel, Arch. Environ. Health, 46 (1991) 313. Y.M. Kostrikin and O.V. Tetrauna, Energetik, 10 (1987) 22. M.J. Dennis, R. Davies and D.J. McWeeny, J. Sci. Food Agric., 30 (1979) 639. C.J. Michejda and T. Rydstrom, IARC Sci. Pub., 57 (1984) 365. J. Polo and Y.L. Chow, J. Natl. Cancer Inst., 56 (1976) 997. Y.L. Chow. In: P. Ansleme (Ed.), N-Nitrosamines, ACS Symposium Series 101, Am. Chem. Soc., Washington, DC, 1979, p. 13, Chapter 2. N.P. Sen, S. Seaman and L. Tessier, J. Food Safety, 4 (1982) 242. J.H. Hotchkiss, J. Assoc. Off. Anal. Chem., 64 (1981) 1037. D.H. Fine, F. Rufeh, D. Lieb and D.P. Rounbehler, Anal. Chem., 47 (1975) 1188. A.E. Wasserman, W. Fiddler, R.C. Doerr, S.F. Osman and C.J. Dooley, Food Cosmet. Toxicol., 10 (1972) 681.
682
Sidney S. Mirvish
65 S.G. Carmella, S. Han, A. Fristad, Y. Yang and S.S. Hecht, Cancer Epidemiol. Biomarkers Prev., 12 (2003) 1257. 66 W.I. Kimoto, L.S. Silbert and W. Fiddler, J. Assoc. Off. Anal. Chem., 67 (1984) 751. 67 I.S. Krull, E.U. Goff, G.G. Hoffman and D.H. Fine, Anal. Chem., 51 (1979) 1706. 68 G. Eisenbrand and R. Preussmann, Arzneim.-Forsch., 20 (1970) 1513. 69 J.W. Pensabene, W. Fiddler and J.G. Phillips, J. Assoc. Off. Anal. Chem., 73 (1990) 947. 70 N.P. Sen, S. Seamam and L. Tessier, J. Food Safety, 4 (1982) 243. 71 J.W. Pensabene, W. Fiddler and R.A. Gates, J. Assoc. Off. Anal. Chem., 75 (1992) 438. 72 J.W. Pensabene and W. Fiddler, J. Assoc. Off. Anal. Chem., 77 (1994) 981. 73 J.W. Pensabene, W. Fiddler, R.J. Maxwell, A.R. Lightfield and J.W. Hampson, J. Assoc. Off. Anal. Chem., 78 (1995) 744. 74 D.L. Ashley, M.D. Beeson, D.R. Johnson, J.M. McCraw, P. Richter, J.L. Pirkle, T.F. Pechacek, S. Song and C.H. Watson, Nicotine Tob. Res., 5 (2003) 323. 75 T.M.C.M. De Kok, L.G.J. Engels, E.J. Moonen and J.C.S. Kleinjans, Lancet Oncol., 1 (2005) 731. 76 R. Rywotycki, Food Chem., 101 (2007) 540. 77 S.K. Pancholy, Soil Biol. Biochem., 8 (1976) 75. 78 S. Eerola, I. Otegui, L. Saari and A. Rizzo, Food Addit. Contam., 15 (1998) 270. 79 R.P. Belardi and J.B. Pawliszyn, Water Pollut. Res. J. Canada, 24 (1989) 179. 80 N.P. Sen, S.W. Seaman and B.D. Page, J. Chromatogr., 788 (1997) 131. 81 J. Ruiz, J. Ventanas and R. Cava, J. Agric. Food Chem., 49 (2001) 5115. 82 A.I. Andres, R. Cava and J. Ruiz, J. Chromatogr., 963 (2002) 83. 83 S. Ventanas, D. Martin, M. Estevez and J. Ruiz, Food Chem., 99 (2006) 842. 84 R. Andrade, F.G.R. Reyes and S. Rath, Food Chem., 91 (2004) 173. 85 F. Sanches, A. Rios, M. Valcarcel, K. Zanin and E. Caramao, J. Chromatogr., 985 (2003) 503. 86 P.J. Sanches-Filho, A. Rios, M. Valcarcel, K.D. Zanin and E.B. Caramao, J. Chromatogr., 985 (2003) 503. 87 L. Cardenes, J.H. Ayala, V. Gonzalez and A.M. Afonso, J. Chromatogr., 946 (2002) 133. 88 H. Ohshima and H. Bartsch, Cancer Res., 41 (1981) 3658. 89 H. Garcia and W. Lijinsky, Z. Krebsforsch Klin. Onkol., 79 (1973) 141. 90 J.E. Nixon, J.H. Wales, R.A. Scanlan, D.D. Bills and R.O. Sinnhuber, Food Cosmet. Toxicol., 14 (1976) 133. 91 H. Bartsch, H. Ohshima, B. Pignatelli and S. Calmels, Pharmacogenetics, 2 (1992) 272. 92 S.S. Mirvish, A.C. Grandjean, H. Moller, S. Fike, T. Maynard, L. Jones, S. Rosinsky and G. Nie, Cancer Epidemiol. Biomarkers Prev., 1 (1992) 455. 93 S.S. Mirvish, A.C. Gandjean, K.J. Reimers, B.J. Connelly, S.C. Chen, J. Gallagher, S. Rosinsky, G. Nie, H. Tuatoo, S. Payne, C. Hinman and E.I. Ruby, Cancer Epidemiol. Biomarkers Prev., 4 (1995) 775. 94 S.S. Mirvish, A.C. Granjean, R.E. Reimers, E.J. Connely, S.C. Chen, C.R. Morris, X. Wang, J. Haorah and E.R. Lyden, Nutr. Cancer, 31 (1998) 106. 95 W.G. Stillwell, J. Glogowski, H.-X. Xu, J.S. Wishnok, D. Zavala, G. Montes, P. Correa and S.R. Tannenbaum, Cancer Res., 51 (1991) 190. 96 Y. Zeng, H. Ohshima, G. Bouvier, P. Roy, Z. Jianming, B. Li, I. Brouet, G. de The and H. Bartsch, Cancer Epidemiol. Biomarkers Prev., 2 (1993) 195. 97 H. Ohshima, I.K. O’Neill, M. Friesen, J.C. Bereziat and H. Bartsch, J. Cancer Res. Clin. Oncol., 108 (1984) 121. 98 M. Tsuda, T. Hirayama and T. Sugimura, Gann, 74 (1983) 331. 99 N.P. Sen, S.W. Seaman and P.A. Baddoo, Food Technol., 39 (1985) 84. 100 J.R.A. Pollock, IARC Sci. Publ., 41 (1982) 81. 101 J.R. Outram and J.R.A. Pollock, IARC Sci. Publ., 57 (1984) 71. 102 J.R. Pollock, Food Chem. Toxicol., 23 (1985) 701. 103 S.S. Mirvish, M.Y. Wang, J.W. Smith, A.D. Deshpande, M. Makary and P. Issenberg, Cancer Res., 45 (1985) 577. 104 S.G. Carmella, S. Han, P.W. Villalta and S.S. Hecht, Cancer Epidemiol. Biomarkers Prev., 14 (2005) 2669. 105 Y. Xia, J.E. McGuffey, S. Bhattacharyya, B. Sellergren, E. Yilmaz, L. Wang and J.T. Bernert, Anal. Chem., 77 (2005) 7639.
Methods for the Determination of N-Nitroso Compounds
106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143
144 145 146 147 148 149 150
683
O. Shimells, A.K. Wihlborg, C. Aurand and A. Trinh, The Reporter (Supelco-Aldrich), 24 (2007) 3. J.J. Conboy and J.H. Hotchkiss, Analyst, 114 (1989) 155. D.C. Havery, J. Anal. Toxicol., 14 (1990) 181. N.P. Sen, S.W. Seaman, C. Burgess, P.A. Baddoo and D. Weber, J. Agric. Food Chem., 48 (2000) 5088. N. Sen, S. Seaman, P. Baddoo, C. Burgess and D. Weber, J. Agric. Food Chem., 49 (2001) 2096. M.J. Downes, M.W. Edwards, T.S. Elsey and C.L. Walters, Analyst, 101 (1976) 742. C.L. Walters, M.J. Downes, M.W. Edwards and P.L.R. Smith, Analyst, 103 (1978) 1127. N.P. Sen, P.A. Baddoo and S.W. Seaman, J. Chromatogr., 673 (1994) 77. R.C. Massey, P.E. Key, D.J. McWeeny and M.E. Knowles, Food Addit. Contam., 1 (1984) 11. R.C. Massey, P.E. Key, D.J. McWeeny and M.E. Knowles, IARC Sci. Publ., 84 (1987) 219. R.C. Massey, P.E. Key, R.A. Jones and G.L. Logan, Food Addit. Contam., 8 (1991) 585. A.R. Tricker, Eur. J. Cancer Prev., 6 (1997) 226. G.P. Xu and P.I. Reed, Carcinogenesis, 14 (1993) 2547. G. Xu and P.I. Reed, Analyst, 118 (1993) 877. B. Pignatelli, I. Richard, M. Bourgade and H. Bartsch, Analyst, 112 (1987) 945. H.B.F. Dixon, Biochem. J., 129 (1972) 203. W. Fiddler, J.W. Pensabene, R.C. Doerr and R.A. Gates, J. Assoc. Off. Anal. Chem., 78 (1995) 1435. R.D. Cox, C.W. Frank, L.D. Nikolaisen and R.E. Caputo, Anal. Chem., 54 (1982) 253. E.C.S. Jones and J. Kenner, J. Chem. Soc., 1932 (1932) 711. W. Woelter, Chemiker-Zeitung, 98 (1974) 4938. J. Wang, W.G. Chan, S.A. Haut, M.R. Krauss, R.R. Izac and W.P. Hempfling, J. Agric. Food Chem., 53 (2005) 4686. N.P. Sen, S.W. Seaman, P.A. Baddoo, C. Burgess and D. Weber, J Agric. Food Chem., 49 (2001) 2096. N.P. Sen, P.A. Baddoo and S.W. Eaman, J. Chromatogr., 673 (1994) 77. I.S. Krull, J. Strauss, F. Hochberg and N.T. Zervas, J. Anal. Toxicol., 5 (1981) 42. S.S. Mirvish, K. Karlowski, D.A. Cairnes, J.P. Sams, R. Abraham and J. Nielsen, J. Agric. Food Chem., 28 (1980) 1175. R.W. Lamson, J. Bacteriol., 9 (1924) 307. P.A.S. Smith, The Chemistry of Open-Chain Nitrogen Compounds, W.A. Benjamin, New York, 1965. D.D. Perrin, Dissociation Constants of Organic Bases in Aqueous Solution, Butterworths, London, 1965. D. Hunninghake and S. Grisolia, Anal. Biochem., 16 (1966) 200. S.S. Mirvish, J.P. Sams and S.D. Arnold, Anal. Chem., 298 (1979) 408. M.C. Archer, S.D. Clark, J.E. Thilly and S.R. Tannenbaum, Science, 174 (1971) 1341. S.S. Mirvish, D.A. Cairnes, N.H. Hermes and C.R. Raha, J. Agric. Food Chem., 30 (1982) 824. S.S. Mirvish, A. Deshpande, R. Haight, J. Nickols, N. McWilliams, D.M. Babcook and C.R. Morris, J. Agric. Food Chem., 41 (1993) 2051. S.S. Mirvish, D.L. Nagel and J. Sams, J. Org. Chem., 38 (1973) 1325. S.S. Mirvish. In: W. Nakahara, S. Takayama, T. Sugimuara and S. Odashima (Eds.), Topics in Chemical Carcinogenesis, Tokyo Press, Tokyo, 1972, p. 279. H. Bredereck, F. Effenberger and A. Hofmann, Chem. Ber., 97 (1964) 61. T. Kawabata, J. Uibu, H. Ohshima, M. Matsui, M. Hamano and H. Tokiwa, IARC Sci. Publi., 31 (1980) 481. T. Kawabata, H. Ohshima, J. Uibu, M. Nakamura, M. Matsui and M. Hamano, In: E.C. Miller, J.A. Miller, I. Hirono, T. Sugikuara and S. Takayama (Eds.), Naturally Occurring Carcinogens-Mutagens and Modulators of Carcinogenesis, University Park Press, Baltimore, 1979, p. 195. E.H. White and D.J. Woodcock, Chemistry of the Amino Group, Wiley, New York, 1968. D.E.G. Shuker and S.R. Tannenbaum, Ann. Chem., 55 (1983) 2152. S.S. Mirvish, K.J. Reimers, B. Kutler, S.C. Chen, J. Haorah, C.R. Morris, A.C. Grandjean and E.R. Lyden, Eur. J. Cancer Prev., 9 (2000) 335. R.F. Zhang, D.J. Deng, Y. Chen, H.Y. Wu and C.S. Chen, IARC Sci. Publ., 105 (1991) 152. D.J. Deng, T. Li, H. Ma, R.M. Wang, L.K. Gu and J. Zhou, J. Agric. Food Chem., 46 (1998) 202. D.J. Deng, World J. Gastroenterol., 6 (2000) 613. D.J. Deng, S.M. Yang, T. Li and H.J. Xin, Biomed. Environ. Sci., 12 (1999) 54.
684
151 152 153 154 155 156 157 158 159 160 161
162
Sidney S. Mirvish
D.J. Deng and H.J. Xin, J. Agric. Food Chem., 48 (2000) 2495. D.C. Havery, T. Fazio and H.W. Howard, J. Assoc. Off. Anal. Chem., 61 (1978) 1379. N.P. Sen, B. Donaldson, S. Seaman, B. Collins and J.Y. Iyengar, Food Sci. Technol. J., 10 (1977) A13. R.G. Cassens, Nitrie-Cured Meat: A Food Safety Issue in Perspective, Food and Nutriton Press, Trumbull, CT, U.S.A., 1990. B. Spiegelhalder, G. Eisenbrand and R. Preussmann, Food Cosmet. Toxicol., 17 (1979) 29. L.J. Yoo, J.F. Barbour, L.M. Libbey and R.A. Scanlan, J. Agric. Food Chem., 40 (1992) 2222. M. Izquierdo-Pulido, J.F. Barbour and R.A. Scanlan, Food Chem. Toxicol., 34 (1996) 297. A.J. Vecchio, J.H. Hotchkiss and C.A. Bisogni, J. Food Sci., 51 (1986) 754. B. Spiegelhalder, G. Eisenbrand and R. Preussmann, Oncology, 37 (1980) 211. T.A. Gough, K.S. Webb and R.F. Coleman, Nature, 272 (1978) 161. P. Jakszyn, A. Agudo, A. Berenguer, R. Ibanez, P. Amiano, G. Pera, E. Ardanaz, A. Barricarte, M.D. Chirlaque, M. Dorronsoro, N. Larranaga, C. Martinez, C. Navarro, J.R. Quiros, M.J. Sanchez, M.J. Tormo and C.A. Gonzalez, Public Health Nutr., 9 (2006) 785. D.M. Maron and B.N. Ames, Mutat. Res., 113 (1983) 173.
CHAPT ER
19 Heterocyclic Amines Mark G. Knize and James S. Felton
Contents
1. 2. 3. 4.
Introduction Physical and Chemical Properties Health Effects Formation of Heterocyclic Amines 4.1 Model systems 4.2 Conditions for formation in meats 5. Food Sample Analysis 5.1 Sample extraction 5.2 Chromatography and detection 5.3 Mass spectrometry 5.4 GC-MS 5.5 LC-MS 5.6 Ultra-high performance LC-MS/MS 5.7 Capillary electrophoresis 6. Occurrence in Food 6.1 Pan residues and food flavors 6.2 Modifying cooking practices to reduce the formation of heterocyclic amines 7. Exposure Assessment 8. Regulations and Future Trends Acknowledgements References
685 686 687 688 688 689 689 690 691 692 692 694 696 697 697 697 699 700 701 701 701
1. INTRODUCTION Heterocyclic amines (HAs) are important because of their potent biological activity causing mutation in laboratory tests and in initiating tumours in rodents. Coupled with their presence in human food at varying levels, these compounds may have an impact on human health. A description of the occurrence of HAs in food and methods for their analysis are the primary focus of this chapter. We also describe methods to prevent their formation and some of the health effects research Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00019-6
r 2008 Elsevier B.V. All rights reserved.
685
686
Mark G. Knize and James S. Felton
underway on these interesting compounds. The risks of exposure in humans have been evaluated in many laboratories and are the subject of ongoing research. Lifestyle and the accompanying diet have been implicated as important factors in the observation that cancer rates differ worldwide [1,2]. A biologically plausible hypothesis for at least part of this association was the discovery in the 1970s of mutagenic activity, as detected by bacterial test systems, in meats cooked for human consumption [3,4]. Finding substances derived from cooked meats to be mutagenic in bacterial tests paralleled the well-known presence of mutagens in the smoke collected from cigarettes at that time [5]. In the late 1970s it was discovered that there were mutagenic substances in cooked meats. This observation was followed by demonstrations in many laboratories worldwide that the mutagens were formed during high temperature cooking and that the formation process was both time- and temperaturedependent. A large range of food was analysed and it was determined that the cooked muscle meats from any vertebrate species were the major sources of extractable mutagenic activity in the human diet [6]. The precursors responsible for the mutagens were proposed when the chemical structures of the first compounds from cooked fish [7,8] and beef [9,10] were determined to be aromatic amines. These newly discovered mutagenic chemicals were primarily of an amino-imidazo structure suggesting that creatine or creatinine was a component of the muscle meat reactions. An early work in adding creatine to meat before cooking showed that its addition increased mutagenic activity [11]. A later study of cooked meat from 17 animal species also showed that creatine or creatinine levels do not entirely explain differences in mutagenic activity. These results suggested that other components were also important for determining the mutagen levels in cooked meats. Other work showed free amino acids to be involved in the formation of mutagenic activity [12], but not amino acids included in the polypeptide chain of proteins [11]. Analysis of the specific mutagenic compounds formed during cooking shows that amino acids are important and changes in these can affect the amount and types of HAs found in the cooked meat. Importantly, knowledge of the formation conditions does suggest ways to cook meat (lower temperatures, among others) that greatly inhibit the formation and, thus, the human intake of HAs.
2. PHYSICAL AND CHEMICAL PROPERTIES The HAs under discussion are formed from natural precursors during the cooking of muscle meats. They have the common property of potent mutagenic activity in bacterial mutation tests. These are primary aromatic amines containing two or more fused aromatic rings. All have two or more heterocyclic nitrogen atoms, and most have an imidazo ring that has the exocyclic amino group and an N-methyl substituent. Molecular weights of relevant HAs are from 162 to 227. These compounds were isolated because they are potent mutagens, and these properties (primary aromatic amines with heterocyclic nitrogen atoms and methyl constituents) also define potent mutagenic compounds.
687
Heterocyclic Amines
These HAs are formed during heating and are stable chemical products. The amine structure can be exploited in liquid/liquid and solid-phase sample extraction and for chemical derivatization to enhance analysis and detection. The aromatic ring structure confers a strong UV absorbance and in some cases, fluorescence, to enable sensitive detection. Their aromatic structure fosters detection of molecular ions and fragments by mass spectrometry (MS).
3. HEALTH EFFECTS The HAs were discovered because of their potent mutagenic effect in bacterial tests, and subsequent assays in cultured mammalian cells also showed HAs to be potent mutagens. Interestingly, the more active bacterial mutagens, like MeIQx and IQ (Figure 1) were less potent in mammalian cells than PhIP, which is 50-fold
N
CH3 N N
N
N
N
H3 C
NH2
NH2 CH3
H3C
N
PhIP
MeIQx (2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline)
(2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine)
NH2
N N
N
N
CH3
CH3
DiMeIQx (2-amino-3,4,8-trimethylimidazo[4,5-f ]quinoxaline)
NH2 CH3 H3 C N H
NH2
N
N N
AαC (2-amino-9H-pyrido[2,3-b]indole)
N
CH3 N NH2 N
7,9-DiMeIgQx (2-amino-1,7,9-trimethylimidazo[4,5-g]quinoxaline)
H3C
N
H3C
N
N
CH3
7,8-DiMeIQx (2-amino-3,7,8-trimethylimidazo[4,5-f]quinoxaline)
NH2 N
NH2
NH2
H3C N
N IQ (2-amino-3-methylimidazo[4,5-f]quinoline)
N
N
O
CH3
N
N
IFP (2-amino-1,6-dimethylfuro[3,2-e ]imidazo[4,5-b]pyridine)
NH2
H3C
N N
CH3
CH3
N
IQ[4,5-b] (2-amino-3-methylimidazo[4,5-b]quinoline)
H3C
NH2
N
CH3
N
N
H3C
N
N
N
N
IQx (2-amino-3-methylimidazo[4,5-f]quinoxaline)
NH2 N
N N
N
Iso-IQx (2-amino-1-methylimidazo[4,5-f]quinoxaline)
Iso-MeIQx (2-amino-1,8-dimethylimidazo[4,5-f]quinoxaline)
CH3 N
CH3 N H
N
NH2
MeAαC 2-amino-3-methyl-9H-pyrido[2,3-b]indole
N H
NH2 CH3
Trp-P-1 3-amino-1,4-dimethyl-5H-pyrido[2,3-b]indole
Figure 1 Structures, common names and chemical names of HAs found in cooked meats.
688
Mark G. Knize and James S. Felton
less potent in bacterial systems. This observed difference has important implications in predicting health effects, and many studies have been done to investigate the metabolic transformations and predict the outcome in humans. The relationship between consumption of HAs and cancer is under very active investigation. Epidemiological studies relating cancer outcome and meat cooking doneness (as a surrogate for dietary HA content) suggest effects in the breast, colon and prostate, plus oesophagus, larynx, lung, lymphocytes, stomach and pancreas. There were 31 of such studies compiled by 2005 [13]. Most of these studies show positive associations, but some are negative, as would be expected given the variety of cancer sites evaluated. Improved classification of exposure levels, however, would tend to elevate odds ratios and improve statistical significance if the hypothesis of HA involvement is true. Thus, improved determination of exposures would refine the risk assessment considerably.
4. FORMATION OF HETEROCYCLIC AMINES Figure 1 shows the structure, common name and chemical name of 14 HAs found in cooked meats. All but three of these structures (AaC, MeAaC, Trp-P-1) contain the 5-membered imidazo ring with an exocyclic amino group and N-methyl group. Other HAs have been isolated from model systems based on heated or pyrolyzed protein and can occasionally be found in foods, but this report focuses on the commonly reported HAs and some newly-found structural isomers that occur in food cooked for human consumption. HA exposures are a mixture of biologically active compounds, and this mixture of compounds is the challenge for food analysts. The common imidazo ring feature, shown in Figure 1, was determined to be a derivative of creatine, including the amino and N-methyl groups. Modeling experiments demonstrate that most of the HA mutagens shown can be pyrosynthesized in laboratory experiments from creatine and other small molecules, such as amino acids and glucose. It is easy to see that the N-methyl-amino-imidazo moiety could form intact from creatine, but the ring constituents are derived from other small molecules, and their sources are not apparent from the reactants. These HAs were isolated by following their mutagenic activity in Salmonella-based mutation tests during extraction and chromatographic purification [7–9,14–16]. Interestingly, in determining exact chemical structure for the naturally produced HAs, many structural features were shown to greatly affect mutagenic potency. Such structure/activity relationships have been the subject of many research efforts worldwide [17–21].
4.1 Model systems Model systems to understand the formation of the mutagenic/carcinogenic HAs were developed to help identifying the foods and cooking conditions favoring their formation and to develop strategies to reduce their formation and, thus, human intake. Defined model systems composed of creatine or creatinine, amino acids and sugars have been a good model for the trace level formation of these
Heterocyclic Amines
689
HAs. Jagerstad et al. [22] developed a system for heating components in diethylene glycol and the work was followed by many studies investigating HA precursors [23–25] and kinetics [26] in a sealed-tube aqueous model. It was shown that 371C is warm enough to produce PhIP from a mixture of phenylalanine with creatinine and glucose or MeIQx from glycine with creatinine and glucose in aqueous buffers [27,28]. But, no PhIP was found in a similar model system kept at room temperature for two weeks in another study [29]. Simple dry-heating of HA precursors forms the relative amounts and types of HAs one detects in cooked meats. Pais et al. [30] showed that heating the amino acids, creatine and glucose for 30 min at 2251C, in ratios mimicking their content in beef muscle, chicken breast, or codfish, produces a family of HAs. Analysis methods for model systems are similar to those for the foods themselves. Even simple model systems generate thousands of products when heated.
4.2 Conditions for HAs formation in meats Along with the discovery of mutagenic activity in cooked meats was the determination that their activity was temperature dependent. Cooking time and temperature studies showed that uncooked meat had no activity, and formation of mutagens was time and temperature dependent. The HAs were first detected using a biological assay for mutagenic potency that performed well using complex mixtures. This Ames/Salmonella assay was developed in 1974 [31], and mutagenic chemicals were reported in the extracts of cooked beef shortly thereafter by Sugimura et al. [3,32]. Cooking experiments showed that muscle meats were the major source in the diet and the results could be repeated in many laboratories [6,33–39]. Comparing various cooking methods showed that higher temperature processes, like frying, broiling and flame grilling, produced more of the activity than lower temperature processes like baking and boiling. Surface-insulating practices like breading also reduced the temperature at the meat surface, and, thus, the HAs formed. These results were confirmed when the HAs were known, and analysis methods were developed. The temperature dependence of the formation of HAs in beef patties was computationally modeled by Tran et al. [40].
5. FOOD SAMPLE ANALYSIS The relatively quick and inexpensive biological assay guided the chemical fractionation of extracts of cooked meats to reveal pure compounds whose structure could be determined. This work revealed the structures of IQ [7], MeIQx [9] and PhIP [10]. The determination of the chemical structures of the mutagens enabled large quantities of pure HAs to be synthesized as reference material for chemical analysis, with or without isotopic labels. Synthetic HAs were, and still are, essential for biological experiments investigating the relationship between mutagenic and carcinogenic potency, and for studying the metabolism of HAs in biological model systems, rodents and people.
690
Mark G. Knize and James S. Felton
The HAs isolated from cooked foods have stable multi-ring aromatic structures, and all have an exocyclic amino group. They all also have characteristic UV spectra and high extinction coefficients, some of the compounds fluoresce (i.e., PhIP), and all can be electrochemically oxidized making electrochemical detection a suitable method. The aromatic structures of these HAs give little fragmentation and therefore show large base peaks, making MS a good detection method [41]. With each of these detection methods confirmation of peaks, for instance, by mass or UV spectra, is important to prevent false positives in the complex sample extracts. There are several factors that make the analysis of HAs from food a difficult problem. HAs are present in food at very low part-per-billion (ppb) levels. Because of these low levels, chromatographic efficiency, detector sensitivity and detector selectivity must be optimized. Several of the HAs are formed under the same reaction conditions, so the number of compounds to be quantified requires that the extraction, chromatographic separation and detection be general enough to detect several of the HAs per sample. The complexity and diversity of food samples needing to be analysed requires a rugged method not affected by the sample matrix. Several extraction and analysis methods were developed over the past 20 years, including solid-phase extraction, high pressure liquid chromatography (HPLC)-UV, derivatization-gas chromatography-mass spectrometry (GC-MS) and liquid chromatography tandem mass spectrometry (LC-MS/MS). These methods have made analysis cheaper and more accurate, enabling hundreds of samples from cooked meats and model systems to be investigated for HAs content.
5.1 Sample extraction The detection of bacterial mutagens in cooked meats led to efforts to optimize the recovery of the mutagenic chemicals using a variety of extraction methods. Samples were liquified in a solvent using a probe homogenizer (which is still the standard practice) and extracted with organic solvents [3,35,42]. The purity of the extracts obtained at this point was generally not sufficient to measure specific HAs, and typically mutagenic potency was measured using the Ames/Salmonella test, an assay that performs well with crude mixtures. Murray et al. [43] devised an analysis method specific enough to be used on samples dissolved in acid and extracted with dichloromethane. These extracts were then derivatized and analysed by GC-MS as described below. The most widely used HA sample preparation scheme is the solid-phase extraction method that uses liquid/liquid extraction on a solid support of diatomaceous earth as the first step. This method can easily be coupled to further extraction steps, a practice that revolutionized the approach to HA analysis of food samples. Another HA extraction method uses a solid support containing blue copper phthalocyanine trisulfonate linked to cotton and was developed for its ability to adsorb planar aromatic compounds having three or more fused rings. HAs can be adsorbed to the blue cotton from saline solutions and eluted with a methanol/ ammonia solution [44], and this scheme has been successfully used in many food
Heterocyclic Amines
691
analysis studies [45,46]. Further developments linking the phthalocyanine trisulfonate to rayon or chitin for use in HA analysis was reviewed by Skog [47]. A single solid-phase extraction scheme was used to isolate three classes of genotoxic compounds from charcoal-grilled meat: HAs, polycyclic aromatic hydrocarbons (PAH) and nitrogen-containing PAHs [48]. The method gave detection limits from 0.3 to 8.4 ng/g in a charcoal-grilled meat sample for the 12 compounds assessed. Very few studies have analysed the same meat sample for more than one class of mutagen/carcinogen. We showed pan-fried hamburgers to have only HAs, and flame-grilled meat had both PAH and HAs, with a total of 37 ng/g of six PAH, and 17.2 ng/g for combined PhIP and MeIQx [49]. Most commonly these days, disposable cartridges containing a solid, often silica-based, sorbent are used for extraction of HAs from cooked meats. Gross simplified and improved extraction methods, with the goal of high sample throughput and high analytical sensitivity [50]. The key to solid-phase extraction is the coupling of liquid/liquid extraction to a cation exchange resin column (propylsulfonic acid silica), concentrating the sample diluted from the large volume of organic solvent resulting from the first step in the extraction. Using the cation exchange properties of the column allows selective washing and elution to further purify the sample. This extraction method, followed by various detection schemes, was evaluated in inter-laboratory comparisons in Europe and included extraction details and modifications [51]. The search-improved methods continues, with a report of metastable atom bombardment ionization MS of extracts prepared simply by pyrolysis [52]. A simplification of solid-phase extraction enabling the detection of 15 HAs with a tandem mass spectrometer was recently reported [53].
5.2 Chromatography and detection Baseline separation of all HAs is a prerequisite for the multi-compound analysis method. Chromatographic conditions were optimized by Gross and Gru¨ter [54] for the separation of 12 HAs in 1992. A more recent study evaluated HPLC columns for the separation of HAs for LC/MS, and the same column material favored by Gross, containing ODS-80, was found to be optimal for HAs in the newer study [55]. Peak confirmation is a crucial problem when working with such low levels of HAs, since co-elution with other co-extracted compounds can occur. The most convenient and accessible instrument to identify HAs in-line during an HPLC separation is the UV photodiode array detector. Most instruments allow the recording of UV spectra even at a 0.1-ng level. A photodiode array detection system efficiently prevents most false peak identifications and is essential to prevent false positive results. Even with modern photodiode array detection with spectral library matching by computer, human interpretation is still needed for confirmation in many cases. Changes in separation selectivity were shown to further improve peak identification for complex samples [56]. In addition, fluorescence detection is typically used in-line as a complement to photodiodearray detection. Not all HAs fluoresce, however, but PhIP, a common HA in foods,
692
Mark G. Knize and James S. Felton
shows about a 9-fold greater peak signal with fluorescence than with the photodiode-array UV detection method. Figure 2 shows an example of the UV and fluorescence chromatograms recorded from the extraction of a cooked chicken sample as well as the corresponding UV spectra of the HAs seen, with an overlay of a reference spectrum obtained from a pure compound. The fluorescence of IFP and PhIP add support for the presence of those compounds, since the UV spectra are weak in this example. Gross [50] determined the standard error of repeated extractions to range from 6 to 11% for cooked fish, very acceptable for low-level analysis. Reproducibility of the solid-phase extraction and HPLC method over time was determined in a blind study. Two hamburger samples, one cooked rare and one cooked well-done, were repeatedly sent in separate aliquots for quality control determination. For the two samples analysed repeatedly during the 24 months, MeIQx, PhIP and DiMeIQx were consistently detected in the sample cooked well-done, but not in the sample cooked rare. Relative standard deviations (coefficients of variation) for the amounts determined were 34 for MeIQx, 22 for PhIP and 38 for DiMeIQx for the well-done cooked samples [58]. No sample degradation was seen in the samples stored frozen at 41C.
5.3 Mass spectrometry MS has many desirable features as a detector of HAs. It offers the selectivity of mass detection with the possibility of adding heavy-isotope-labeled internal standards to determine extraction recovery and act as chromatographic standards simultaneously.
5.4 GC-MS A very sensitive approach for HA analysis was devised using GC-MS. Most of the HAs exhibit poor chromatographic behavior for GC, and thus require derivatization prior to injection. For this method, extracts of food from a liquid/liquid extraction scheme were derivatized with 3,5-bistrifluoromethylbenzyl bromide at room temperature, washed with hexane and extracted with ethyl acetate. The total yield for these extraction steps was reported to be about 40% as determined by [14C]MeIQx tracer [43]. PhIP can give multiple products upon derivatization with this method, and another derivatizing agent, pentafluorobenzyl bromide, was reported to give a single product [59]. Additional derivatization methods for GC analysis of HAs were also reported [60,61]. With MS, recovery for extraction and derivatization can be calculated by the use of heavy-isotope-labeled internal standards, as mentioned above. The chemical ionization and negative-ion detection gave a reported 1 pg detection limit using selected-ion monitoring [43]. GC-MS methods have not been optimized for as many different HAs as HPLC-UV methods, and IQ reportedly could not be detected by one GC-MS method [62]. Several groups reported GC-MS analysis gave limits of detection at least 20-fold lower than HPLC-UV methods [62,63].
Heterocyclic Amines
Figure 2 HPLC chromatograms of the extract of a cooked chicken sample. Upper chromatogram is plotted fluorescence at excitation of 307 nm, emission of 370 nm, lower chromatogram is absorbance at 262 nm. Insert are overlayed UV spectra from sample and reference compounds plotted from 250 to 350 nm. Adapted from Salmon et al. [57].
693
694
Mark G. Knize and James S. Felton
More recently, a larger number of HA derivatives were made by the reaction with N,N,-dimethylformamide di-tert-butylacetal to develop a more general meat analysis method [64], or by silylation with N-methyl-N-(tert-butyldimethylsilyl)trifluoroacetamide [65]. Figure 3 shows chromatograms of the extract of a bacon sample and the resultant HA peaks. With these complex food samples, many peaks are seen and isotopically labeled internal standards would be a good addition to monitor analyte recovery during extraction, the HA derivatization reaction yield and chromatographic retention times.
5.5 LC-MS The HAs are more easily separated by LC and there are many more examples of groups successfully using LC-MS for food analysis. Gross et al. [66] reported
Figure 3 Selected ion monitoring GC-MS analysis of derivatized HAs from a fried bacon sample. Reprinted with permission from Casal et al. [65].
Heterocyclic Amines
695
LC-MS single ion plots for 11 HAs and showed extracts of bacon to be free of interfering peaks at the masses monitored for the HAs. Pais et al. [67] separated 14 HAs and related compounds using LC-MS, reporting instrument detection limits of 10–600 pg depending on the HA. Toribio et al. [53] developed a low-time consuming solid-phase extraction procedure to purify the meat samples using LC-MS/MS with an ion trap mass analyser as determination technique. Figure 4 shows the chromatograms obtained. Three LC-MS systems with electrospray interfaces, an ion trap, a single quadrupole and a triple quadrupole, were compared for the analysis of HAs. The results clearly showed that the ion trap was the least sensitive instrument for detection of HAs spiked into meat extracts; the single quadrupole instrument was usually 2–7-fold better; and the triple quadrupole instrument, operated in the multiple reaction monitoring mode, was typically 10-fold more sensitive than the single
Figure 4 HPLC-MS/MS plots of masses indicated for HAs from a griddle-fried beef sample. Reprinted with permission from Toribio et al. [53].
696
Mark G. Knize and James S. Felton
Figure 5 HPLC-MS/MS plots of HAs from barbecued chicken showing the mass transitions using isotopically labeled standards for some HAs. HAs isomeric to known compounds are indicated by numbers 1–3 and 5. Reprinted with permission from Turesky et al. [70].
quadrupole instrument, with levels of detection of 0.5–5 pg, depending on the HA [68]. Multiple reaction monitoring with a triple quadrupole mass spectrometer was used to evaluate food samples by Klassen et al. [69] and Turesky et al. [70]. These three studies, in three separate laboratories, confirm that triple quadrupole LC-MS/MS can detect multiple HAs concurrently at the picogram level. Using LC-MS/MS enabled the detection of HA isomers along with the known compounds. Figure 5 shows analysis of a cooked chicken sample, and along with the known HAs, isomers are seen that have the same molecular weight and mass transitions, and the identity shown by chemical synthesis and co-chromatography. For instance, for ‘‘8-MeIQx’’ (middle panel on the left of the Figure), there are several peaks that have the transition from mass 214 to mass 199, only one co-eluted with the isotopically labeled standard at 11.13 min (shown in the panel above). The peak numbered ‘‘1’’ was shown to be the ‘‘iso-MeIQx’’ [70]. The health significance of these isomeric HAs needs to be further investigated.
5.6 Ultra-high performance LC-MS/MS A promising new LC system, using higher than normal pressure to provide high efficiency and resolution, was optimized for the mass spectral analysis of HAs.
Heterocyclic Amines
697
Sixteen HAs were separated and limits of detection were determined, showing this system to be sensitive and reproducible for routine analysis of meat extracts [71].
5.7 Capillary electrophoresis Capillary electrophoresis with photodiode-array detection was developed for the analysis of 12 HAs in foods [72] and meat extracts [73,74]. Capillary electrophoresis with field-amplified sample injection, coupled to a mass spectrometer used in either the MS or MS/MS mode, was evaluated for 16 HA by Sentellas et al. [75]. They showed extraction of the amines from spiked urine, however, rather than the more difficult food analysis. Levels of detection are in the range of LC-UV for this separation method.
6. OCCURRENCE IN FOOD Table 1 shows representative amounts of 14 HAs for cooked beef, chicken and fish. Cooking in the laboratory setting allows for determination of temperature and time, yet commercially cooked or home-cooked meats (labeled ‘‘commercial’’ or ‘‘home’’ in Table 1) are perhaps a better sample of foods from which to determine human intake, since these reflect meats cooked specifically for human consumption, and cooking is such an important determinant for HAs formation. PhIP, MeIQx and DiMeIQx are found in all samples shown and represent the most abundant HAs. PhIP is generally the most abundant HA in these samples. Few studies look for all known HAs, as Table 1, compiled from three recent articles, shows. It should be noted that all samples did not have detectable HAs. The average for the HAs in many foods is shown in the last three rows, and the low amounts represent many samples below the level of detection. These averages are useful for population exposures, but individual exposures (indicated in rows 1–10) can be much greater than the population average. Studies of the amounts of HAs produced in foods as a result of regional cooking practices are reported for Great Britain [76], Sweden [77,78], Switzerland [79], Spain [80], Japan [81] and the United States [82,83]. In most cases, PhIP and MeIQx tend to be the most mass-abundant HAs. Their concentrations in cooked meats typically range from nearly undetectable levels (typically 0.1 ng/g) to tens of ng/g for MeIQx and up to a few hundreds of ng/g for PhIP, depending on the cooking method. Research on the toxic effects of HAs has rightly focused on these two compounds.
6.1 Pan residues and food flavors Sources of HAs related to the meats themselves are pan residues and process flavors. Pan residues are sometimes consumed after being made into gravy and can be a source of HAs equivalent to or greater than that of the meat itself [30,77,78].
0.75
0.10
1.35
1.37
0.03
0.24
0.588 1.43 0.175 0.119 0.431 0.276 1.27 0.72 0.66 0.28 0.11
–
–
o0.03 3.32 o0.03 2.80 7.75 8.70 0.33 0.18 ND NQ –
–
–
0.549 1.02 0.084 0.063 0.569 0.09 – – – – –
0.001
0.015
– – – – 0.003
–
–
0.04 0.26 o0.03 0.036 0.129 0.118 ND ND ND ND –
7,97,8IQ DiMeIgQx DiMeIQx
0.07
0.12
– – – – – – – – – – 0.09
IFP
–
–
0.031 0.21 NA 0.046 0.172 – – – – – –
–
–
0.257 0.390 0.115 o0.03 0.20 o0.03 – – – – –
IQ[4,5-b] IQx
Source: Rows 1–6, from Turesky et al. [70]; rows 7–10, from Toribio et al. [53]; rows 11–13, from Salmon et al. [57] Note: , Not assayed; ND, below limit of detection; NQ, below limit of quantification.
3.72 5.31 1.45 0.527 1.60 0.335 2.86 1.17 1.70 0.78 0.18
0.426 15.2 0.161 2.190 13.9 10.0 6.99 3.49 3.26 1.73 2.37
Beef, pan fried 1 Beef, pan fried 2 Beef, pan fried 3 Beef, barbecued 1 Beef, barbecued 2 Chicken barbecued Beef griddle, lab Beef B commercial Beef C commercial Beef D commercial Chicken, home, n ¼ 38 Chicken, marinated, home, n ¼ 39 Fish, home, n ¼ 37
MeIQx DiMeIQx AaC
PhIP
Examples of heterocyclic amine content in beef chicken and fish
Meat
Table 1
–
–
0.349 1.420 NA 0.154 1.070 – – – – – –
–
–
3.79 13.8 NA 1.18 6.49 – – – – – –
–
–
o0.03 0.143 o0.03 0.088 0.285 0.225 0.15 NQ ND NQ –
– – – – – – 0.35 0.35 ND ND
Iso-IQx IsoMeAaC Trp-P-1 MeIQx
698 Mark G. Knize and James S. Felton
Heterocyclic Amines
699
Process flavors are commercially produced flavors derived from heated mixtures of proteins, fats and carbohydrates. These are added to foods in amounts up to a few percent by weight to improve the food’s taste and colour, and they can also be used as a base for soups. Because of their chemical complexity, specific sample preparation methods for HA analysis have been developed for these types of samples [67,84,85]. Although most process flavors have undetectable levels of HAs, some samples contain as much as 20 ng HAs per gram of solid or liquid flavor [86–88]. However, since process flavors are greatly diluted and then consumed as only a tiny percentage in the food, we believe the bulk of HA exposure is not from process flavors, but is from well-cooked meats. Process flavors are added to food commercially and thus regulation of the content of ‘‘HA carcinogens’’ by government agencies may, in the future, impact these food additives.
6.2 Modifying cooking practices to reduce the formation of heterocyclic amines Since HAs are formed during cooking, food preparation can be modified before or during cooking to minimize human exposure. Minor changes in recipes for preparing different meat dishes may provide another way to reduce the HAs formed. Schemes for reducing mutagenic activity or HAs by adding substances to ground meat have been reported. Additives such as soy flour or antioxidants [89], or glucose or lactose [90], were shown to lower mutagenic activity when added to ground meat prior to frying. The heat flow and mass transport in meat during frying is very complex. Water is important for the transport of water-soluble precursors for formation of HAs within the food. The transport of precursors from the inner parts of the food to the surface can be restricted by the addition of water-binding compounds, such as salt, soy protein, or starch to ground meat, thus reducing the formation of HAs. Persson et al. showed a significant effect with the addition of sodium chloride/ sodium tripolyphosphate [91]. Enzyme treatment with creatinase was also used to reduce the available creatine in meat [92]. A microwave pre-treatment method reduced the amount of HAs formed during the frying of ground beef [93]. Beef patties received microwave pretreatment for various times before frying. Microwave pre-treating for 2 min, then pouring off the resulting liquid and frying at either 2001C or 2501C for 6 min per side, reduced HAs. The liquid released by the microwave pre-treatment contained creatine, creatinine, amino acids, glucose, water and fat, and discarding these precursors presumably reduced the concentration of reactants resulting in less HAs formation. The sum of the HAs present decreased 3-fold following microwaving (1.5 min) and frying at 2001C (6 min per side) or 9-fold following microwaving and then frying at 2501C, compared to controls (non-microwave pre-treated beef patties fried under identical conditions). HAs formation can also be affected by meat surface treatment. The application of a 7-component marinade to chicken breast meat before grilling can greatly decrease PhIP, although MeIQx is increased at the longest cooking time. This
700
Mark G. Knize and James S. Felton
increase is probably due to sucrose in the marinade [94]. No change in HAs was seen after marinating chicken in another study [95], possibly due to differences in marinating or cooking conditions. Conversely, a HA reducing effect was seen when sugar was mixed with ground meat formed into patties before frying [90]. Experiments with eggs, bean cake and pork show that added sugar and soy sauce increases most of the HAs [96]. During cooking, the formation of HAs is related to pan temperature, even when meat is cooked to the same final internal temperature. Surprisingly, the time needed to reach the 701C USDA recommended internal temperature is nearly the same at 2501C (7 min) as it is at 1601C (9 min) [97]. This is due to the slow heat transfer through the meat, suggesting that simply using lower pan temperatures is a practical way to reduce HA formation, without greatly increasing cooking time. Related to pan temperature, turning beef patties over every minute during cooking, compared to turning the meat over once during the cooking period, seems to be the most effective way to reduce HA content when frying [97]. Monitoring the temperature during cooking avoids under-cooking, which is defined as cooking to a final temperature below 701C, the internal temperature needed to kill harmful bacteria in the meat, so combining known pan temperature and turning the meat over are practical ways to fry beef patties to minimize HA formation.
7. EXPOSURE ASSESSMENT The primary use of food analysis described in this chapter is for assessing HA intake in epidemiology studies for determination of any health consequences from HA exposure. Exposures to HAs have been assessed using questionnaires for frequency of meat consumption, estimates of amounts consumed and meat doneness preference, often using photographs to aid in assessing doneness [98–101]. Worrisome is that validation of the doneness classification by analysing foods consumed by the study population is typically not done, yet exposure estimates derived from these questionnaires and reported with great certainty often fail to consider meat preparation and cooking factors discussed in Section 6.2 that are known to be important in HAs formation. Nevertheless, numerous studies have used this questionnaire data to correlate HA exposure with risk of cancers at many sites. There are other ways to determine the exposure to HAs that use many of the same methods of HA analysis in food detailed above. Human urine was analysed for the presence of specific HAs after individuals ate a cooked-meat meal by using GC-MS detection [102]. They showed that only a few percent of the parent compound was in the urine. Other studies detect metabolites of the HAs using LC-MS; PhIP and MeIQx conjugates were detected in urine [103]. Another study showed that PhIP metabolites were detected in a racially diverse population [104]. One drawback of the analysis of urine for HAs and their metabolites is the short duration of the detectable exposure signal. It has been shown in many studies in humans and rodents that most of the dose is excreted within 12 h, so detecting
Heterocyclic Amines
701
urinary HAs or their metabolites is not the desired long-term marker of dose or bioavailable dose, but only really useful for studying exposure after a single meal. In 1992 it was discovered that PhIP has a high binding to pigmented tissues [105]. This finding led to detection of PhIP bound to human hair as a marker of dietary exposure and bioavailability [106]. Interestingly, PhIP incorporation appears to vary with hair colour and be dependent upon the eumelanin concentration in hair [107]. Because a hair sample may provide a record of exposure over a period of several months or longer, hair analysis may be a promising avenue for determining human exposure and internal dose.
8. REGULATIONS AND FUTURE TRENDS There are no laws regulating the HA content in foods or process flavors. In the U.S., the state of California, using its Proposition 65 law to warn consumers about carcinogens, has listed PhIP as a carcinogen, but a No Significant Risk Level (NSRL) has not yet been established for PhIP. High priority for future needs in HA analysis is the determination of the complete set of HAs. As noted, few studies try to detect all known compounds. The current methodologies are adequate for the sub-part per billion analysis of HAs, but improvements in automation to cut costs through higher throughput, as more samples are examined from commercial cooking, would be helpful. Coupled with this need is a determination of which compounds are the most important in inducing health effects. Risk may be based largely on one HA, or a subset of HAs, based on their abundance or carcinogenic activity. Interactions with other dietary components may be important in evaluating the risk of consuming HAs. A further challenge is determining the HA intake over a lifetime of exposure. The compelling part of HA research for population studies is that there are more than 100-fold variations in human exposure, and, therefore, most studied populations have enough range in variation to test the hypothesis that HA exposures are involved in human cancer etiology. Large cohort studies would be best for these types of studies. Also compelling is the fact that these exposures can be modified through changes in cooking practices, if changes are warranted from risk assessment, without having to abstain from meat intake. Association of diet and cancer is still with us, and there is no evidence to show that HAs are not important.
ACKNOWLEDGEMENTS The authors thank Cynthia Salmon for review of this manuscript. This work was performed under the auspices of the U.S. Department of Energy by the University of California, Lawrence Livermore National Laboratory under Contract No. W-7405-Eng-48 and supported by NCI grant CA55861.
REFERENCES 1 D. Doll and R. Peto, J. Nat. Cancer Inst., 66 (1981) 1191. 2 S. Holmes, Health Policy, 45 (1998) 169.
702
Mark G. Knize and James S. Felton
3 T. Sugimura, M. Nagao, T. Kawachi, M. Honda, T. Yahagi, Y. Seino, S. Sato, N. Matsukura, T. Matsushima, A. Shirai, M. Sawamura and H. Matsumoto, Mutagen-carcinogens in foods with special reference to highly mutagenic pyrolytic products in broiled foods. In: H.H. Hiatt, J.D. Watson and J.A. Winsten (Eds.), Origins of Human Cancer, Cold Spring Harbor, New York, 1977, pp. 1561–1577. 4 B. Commoner, A.J. Vithayathil, P. Dolara, S. Nair, P. Madyastha and G.C. Cuca, Science, 201 (1978) 913. 5 T. Sugimura, T. Kawachi, M. Nagao, T. Yahagi, T. Okamoto, K. Shudo, T. Kosuge, K. Tsuki, K. Wakabayashi, Y. Litaka and A. Itai, Proc. Jpn. Acad., 53 (1977) 58. 6 L.F. Bjeldanes, M.M. Morris, J.S. Felton, S.K. Healy, D.H. Stuermer, P. Berry, H. Timourian and F. T Hatch, Food Chem. Toxic., 20 (1982) 57. 7 H. Kasai, Z. Yamaizumi, S. Nishimura, K. Wakabayashi, M. Nagao, T. Sugimura, N.E. Spingarn, J.H. Weisburger, S. Yokoyama and T. Miyazawa, J. Chem. Soc., (1981) 2290. 8 H. Kasai, Z. Yamaizumi, K. Wakabayashi, M. Nagao, T. Sugimura, S. Yokoyama, T. Miyazawa, N.E. Springarn and J.H. Weisburger, Proc. Jpn. Acad., 56 (1980) 278. 9 H. Kasai, Z. Yamaizumi, T. Shiomi, S. Yokoyama, T. Miyazawa, K. Wakabayashi, M. Nagao, T. Sugimura and S. Nishimura, Chem. Lett., (1981) 485. 10 J.S. Felton, M.G. Knize, N.H. Shen, P.R. Lewis, B.D. Andresen, J. Happe and F.T. Hatch, Carcinogenesis, 7 (1986) 1081. 11 M. Ja¨gerstad, A. Laser-Reuterswa¨rd, R. Oste, A. Dahlqvist, S. Grivas, K. Olsson and T. Nyhammer, Creatinine and Malliard reaction products as precursors of mutagenic compounds formed in fried beef. In: G.R. Waller and M.S. Feather (Eds.), The Maillard Reaction in Foods and Nutrition, American Chemical Society, 1983, pp. 507–519. ¨ vervik, M. Kleman, I. Berg and J.A. Gustafsson, Carcinogenesis, 10 (1989) 2293. 12 E. O 13 M.G. Knize and J.S. Felton, Nut. Rev., 63 (2005) 158. 14 H. Hayatsu, S. Arimoto and K. Wakabayshi, Methods for separation and detection of heterocyclic amines. In: H. Hayatsu (Ed.), Mutagens in Food: Detection and Prevention, CRC Press, Boca Ratan, 1991, pp. 101–112. 15 J.S. Felton, M.G. Knize, C. Wood, B.J. Wuebbles, S.K. Healy, D. H Stuermer, L.F. Bjeldanes, B.J. Kimble and F.T. Hatch, Carcinogenesis, 5 (1984) 95. 16 M.G. Knize, M. Roper, N.H. Shen and J.S. Felton, Carcinogenesis, 11 (1990) 2259. 17 F.T. Hatch and M.E. Colvin, Mut. Res.-Fun. Mol. Mech. Mutagen., 376 (1997) 8. 18 F.T. Hatch, M.G. Knize and M.E. Colvin, Environ. Mol. Mutagen., 38 (2001) 268. 19 M. Jagerstad and S. Grivas, Mut. Res., 144 (1985) 131. 20 M.G. Knize, F.T. Hatch, M.J. Tanga, E.Y. Lau and M.E. Colvin, Environ. Mol. Mutagen., 47 (2006) 132. 21 M. Nagao, Y. Fujita, K. Wakabayashi and T. Sugimura, Biochem. Biophys. Res. Commun., 114 (1983) 626. 22 M. Jagerstad, A.L. Reutersward, R. Olsson, S. Grivas, T. Nyhammar, K. Olsson and A. Dahlqvist, Food Chem., 12 (1983) 255. 23 C. Negishi, M. Tsuda, K. Wakabayashi, S. Sato, T. Sugimura and M. Jargerstad, Mutat. Res., 130 (1984) 378. 24 K. Skog and M. Ja¨gerstad, Carcinogenesis, 14 (1993) 2027. 25 M.A.E. Johansson, L.B. Fay, G.A. Gross, K. Olsson and M. Ja¨gerstad, Carcinogenesis, 16 (1995) 2553. 26 P. Arvidsson, M.A.J.S. vanBoekel, K. Skog and M. Jagerstad, J. Food Sci., 62 (1997) 911. 27 N. Kinae, K. Kujirai, C. Kajimoto, M. Furugori, S. Masuda and K. Shimoi, Int. Congr. Ser., 1245 (2002) 341. 28 S. Manabe, N. Kurihara, O. Wada, K. Tohyama and T. Aramaki, Carcinogenesis, 13 (1992) 827. 29 S. Zochling and M. Murkovic, Food Chem., 79 (2002) 125. 30 P. Pais, C.P. Salmon, M.G. Knize and J.S. Felton, J. Agric. Food Chem., 47 (1999) 1098. 31 B.N. Ames, J. McCann and E. Yamasaki, Mutat. Res., 31 (1975) 347. 32 T. Sugimura, M. Nagao and K. Wakabayashi, Mutagenic heterocyclic amines in cooked food. In: L. Fishbein, I.K. O’Neill, M. Castegnaro and H. Bartsch (Eds.), Environmental Carcinogens: Selected Methods of Analysis IV, IARC Scientific Publications, Lyon, 1981, pp. 251–267. 33 G. Becher, M.G. Knize and J.S. Felton, Va˚r Fo¨da, 42 (1989) 85. 34 P.J. Barrington, R.S.U. Baker, A.S. Truswell, A.M. Bonin, A.J. Ryan and A.P. Paulin, Food Chem. Toxicol., 28 (1990) 141.
Heterocyclic Amines
703
35 J.S. Felton, S.K. Healy, D.H. Stuermer, C. Berry, H. Timourian, F.T. Hatch, M. Morris and L.F. Bjeldanes, Mutat. Res., 88 (1981) 33. 36 M.G. Knize, B.D. Andresen, S.K. Healy, N.H. Shen, P.R. Lewis, L.F. Bjeldanes, F.T. Hatch and J.S. Felton, Food Chem. Toxicol., 23 (1985) 1035. 37 M. Nagao, M. Honda, Y. Seino, T. Yahagi and T. Sugimura, Cancer Lett., 2 (1977) 221. ¨ vervik, L. Nilsson, L. Fredholm, O. Levin, C.E. Nord and J.A. Gustafsson, Mutat. Res., 187 38 E. O (1987) 47. 39 M. Vahl, J. Gry and P.A. Nielsen, Proceedings of the XVII Annual Meeting of the European Environmental Mutagen Society (EEMS), Zurich, (1987) 99. 40 N.L. Tran, C.P. Salmon, M.G. Knize and M.E. Colvin, Food Chem. Toxicol., 40 (2002) 673. 41 M.G. Knize, J.S. Felton and G.A. Gross, J. Chromatogr., 624 (1992) 253. 42 C.A. Krone and W.T. Iwaoka, Cancer Lett., 14 (1981) 93. 43 S. Murray, N.J. Gooderham, A.R. Boobis and D.S. Davies, Carcinogenesis, 9 (1988) 321. 44 H. Hayatsu, Y. Matsui, Y. Ohara, T. Oka and T. Hayatsu, Gann, 74 (1983) 472. 45 R.J. Turesky, H. Bur, T. Huynh-Ba, H.U. Aeschbacher and H. Milon, Food Chem. Toxicol., 26 (1988) 501. 46 K. Wakabayashi, M. Nagao, H. Esumi and T. Sugimura, Cancer Res. (Suppl.), 52 (1992) 2092s. 47 K. Skog, J. Chromatogr. B Analyt. Technol. Biomed. Life Sci., 802 (2004) 39. 48 L. Rivera, M.J.C. Curto, P. Pais, M.T. Galceran and L. Puignou, J. Chromatogr. A, 731 (1996) 85. 49 M.G. Knize, C.P. Salmon, P. Pais and J.S. Felton, Adv. Exp. Med. Biol., 459 (1999) 179. 50 G.A. Gross, Carcinogenesis, 11 (1990) 1597. 51 F.J. Santos, E. Barcelo-Barrachina, E. Toribio, L. Puignou, M.T. Galceran, E. Persson, K. Skog, C. Messner, M. Murkovic, U. Nabinger and A. Ristic, J. Chromatogr. B Analyt. Technol. Biomed. Life Sci., 802 (2004) 69. 52 E. Jamin, S. Chevolleau, C. Touzet, J. Tulliez and L. Debrauwer, Anal. Bioanal. Chem., 387 (2007) 2931. 53 F. Toribio, R. Busquets, L. Puignou and M.T. Galceran, Food Chem. Toxicol., 45 (2007) 667. 54 C.A. Gross and A. Gru¨ter, J. Chromatogr., 592 (1992) 271. 55 E. Barcelo-Barrachina, E. Moyano, L. Puignou and M.T. Galceran, J. Chromatogr. B Analyt. Technol. Biomed. Life Sci., 802 (2004) 45. 56 P. Pais and M.G. Knize, LC/GC, 16 (1998) 378. 57 C.P. Salmon, M.G. Knize, J.S. Felton, B. Zhao and A. Seow, Food Chem. Toxicol., 44 (2006) 484. 58 M.G. Knize, R. Sinha, N. Rothman, E.D. Brown, C.P. Salmon, O.A. Levander, P.L. Cunningham and J.S. Felton, Food Chem. Toxicol., 33 (1995) 545. 59 M.D. Friesen, K. Kaderlik, D.X. Lin, L. Garren, H. Bartsch, N.P. Lang and F.F. Kadlubar, Chem. Res. Toxicol., 7 (1994) 733. 60 H. Kataoka and K. Kijima, J. Chromatogr. A, 767 (1997) 187. 61 J. Alexander, R. Reistad, H. Frandsen and S. Grivas, Mutat. Res., 376 (1997) 7. 62 S. Vainiotalo, K. Matveinen and A. Reunanen, Fresenius J. Anal. Chem., 345 (1993) 462. 63 S. Murray, N.J. Gooderham, A.R. Boobis and D.S. Davies, Carcinogenesis, 10 (1989) 763. 64 E. Barcelo-Barrachina, F.J. Santos, L. Puignou and M.T. Galceran, Anal. Chim. Acta, 545 (2005) 209. 65 S. Casal, E. Mendes, J. O Fernandes, M.B.P.P. Oliveira and M.A. Ferreira, J. Chromatogr. A, 1040 (2004) 105. 66 G.A. Gross, R.J. Turesky, L.B. Fay, W.G. Stillwell, P.L. Skipper and S.R. Tannenbaum, Carcinogenesis, 14 (1993) 2313. 67 P. Pais, E. Moyano, L. Puignou and M.T. Galceran, J. Chromatogr. A, 778 (1997) 207. 68 E. Barcelo-Barrachina, E. Moyano, L. Puignou and M.T. Galceran, J. Chromatogr. A, 1023 (2004) 67. 69 R.D. Klassen, D. Lewis, B.P.Y. Lau and N.P. Sen, Food Res. Int., 35 (2002) 837. 70 R.J. Turesky, J. Taylor, L. Schnackenberg, J.P. Freeman and R.D. Holland, J. Agric. Food Chem., 53 (2005) 3248. 71 E. Barcelo-Barrachina, E. Moyano, M.T. Galceran, J.L. Lliberia, B. Bago and M.A. Cortes, J. Chromatogr. A, 1125 (2006) 195. 72 J. Wu, M.K. Wong, H.K. Lee, B.L. Lee, C.Y. Shi and C.N. Ong, Food Addit. Contam., 13 (1996) 851. 73 L. Puignou, J. Casal, F.J. Santos and M.T. Galceran, J. Chromatogr. A, 769 (1997) 293. 74 J.C. Olsson, A. Dyremark and B. Karlberg, J. Chromatogr. A, 765 (1997) 329. 75 S. Sentellas, E. Moyano, L. Puignou and M.T. Galceran, Electrophoresis, 24 (2003) 3075.
704
Mark G. Knize and James S. Felton
76 S. Murray, A. Lynch, M.G. Knize and N.J. Gooderham, J. Chromatogr. B Biomed. Appl., 616 (1993) 211. 77 K. Skog, K. Augustsson, G. Steineck, M. Stenberg and M. Ja¨gerstad, Food Chem. Toxicol., 35 (1997) 555. 78 M.A.E. Johansson and M.I. Ja¨gerstad, Carcinogenesis, 15 (1994) 1511. 79 B. Zimmerli, P. Rhyn, O. Zoller and J. Schlatter, Food Addit. Contam., 18 (2001) 533. 80 R. Busquets, M. Bordas, F. Torbino, L. Puignou and M.T. Galceran, J. Chromatogr. B, 802 (2003) 79. 81 K. Wakabayashi, H.M.T. Ushiyama, H. Nukaya, S.B. Kim, M. Hirose, M. Ochiai, T. Sugimura and M. Nagao, Environ. Health Perspec., 99 (1993) 129. 82 M.G. Knize, R. Sinha, C.P. Salmon, S.S. Mehta, K.P. Dewhirst and J.S. Felton, J. Muscle Foods, 59 (1995) 999. 83 M.G. Knize, R. Sinha, E.D. Brown, C.P. Salmon, O.A. Levander, J.S. Felton and N. Rothman, J. Agric. Food Chem., 46 (1998) 4648. 84 G.A. Gross, A. Gru¨ter and S. Heyland, Food Chem. Toxicol., 30 (1992) 491. 85 G.A. Perfetti, J. AOAC Int., 97 (1996) 813. 86 A. Solyakov, K. Skog and M. Ja¨gerstad, Food Chem. Toxicol., 37 (1999) 1. 87 L.S. Jackson, W.A. Hargraves, W.H. Stroup and G.W. Diachenko, Mutat. Res., 320 (1994) 113. 88 B. Stavric, B.P.Y. Lau, T.I. Matula, R. Klassen, D. Lewis and R.H. Downie, Food Chem. Toxicol., 35 (1997) 185. 89 Y.Y. Wang, L.L. Vuolo, N.E. Springarn and J.H. Weisburger, Cancer Lett., 16 (1982) 179. 90 K. Skog, A. Laser-Reuterswa¨rd and M. Ja¨gerstad, Food Chem. Toxicol., 30 (1992) 681. 91 E. Persson, I. Sjoholm and K. Skog, J. Agric. Food Chem., 51 (2003) 4472. 92 R. Vikse and J.P. Joner, Acta Vet. Scand., 34 (1993) 1. 93 J.S. Felton, E. Fultz, F.A. Dolbeare and M.G. Knize, Food Chem. Toxicol., 32 (1994) 897. 94 C.P. Salmon, M.G. Knize and J.S. Felton, Food Chem. Toxicol., 35 (1997) 433. 95 L.M. Tikkanen, K.J. Latva-kala and R.L. Heinio¨, Food Chem. Toxicol., 34 (1997) 725. 96 C.M. Lan and B.H. Chen, Food Chem. Toxicol., 40 (2002) 989. 97 C.P. Salmon, M.G. Knize, D.N. Panteleakos, R.W. Wu, D.O. Nelson and J.S. Felton, J. Nat. Cancer Inst., 92 (2000) 1773. 98 R. Sinha, Mutat. Res.-Fundam. Mol. Mech. Mutagen., 506 (2002) 197. 99 R. Sinha, M. Kulldorff, J. Curtin, C.C. Brown, M.C. Alavanja and C.A. Swanson, Cancer Causes Control, 9 (1998) 621. 100 K. Augustsson, K. Skog, M. Jagerstad, P.W. Dickman and G. Steineck, Lancet, 353 (1999) 703. 101 G.A. Keating, R. Sinha, D. Layton, C.P. Salmon, M.G. Knize, K.T. Bogen, C.F. Lynch and M. Alavanj, Cancer Causes Control, 11 (2000) 731. 102 L. Le Marchand, J.H. Hankin, L.M. Pierce, R. Sinha, P.V. Nerurkar, A.A. Franke, L.R. Wilkens, L.N. Kolonel, T. Donlon, A. Seifried, L.J. Custer, A. Lum-Jones and W. Chang, Mutat. Res.-Fundam. Mol. Mech. Mutagen., 506 (2002) 205. 103 W.G. Stillwell, L.C.R. Kidd, J.S. Wishnok, S.R. Tannenbaum and R. Sinha, Cancer Res., 57 (1997) 3457. 104 L. Kidd, W. Stillwell, M. Yu, J. Wishnock, P. Skipper, R. Ross, B. Henderson and S. Tannenbaum, Cancer Epidemiol. Biomarkers Prev., 8 (1999) 439. 105 E.B. Brittebo, K. I Skog and I.M. Jagerstad, Carcinogenesis, 13 (1992) 2263. 106 R. Reistad, S. Nyholm, L. Haug, G. Becher and J. Alexander, Biomarkers, 4 (1999) 263. 107 S. Hegstad, R. Reistad, L.S. Haug and J. Alexander, Pharmacol. Toxicol., 90 (2002) 333.
20
CHAPT ER
Acrylamide, Chloropropanols and Chloropropanol Esters, Furan Richard H. Stadler and Till Goldmann
Contents
1. Acrylamide 1.1 Background 1.2 Analytical considerations 1.3 Proficiency tests 2. Chloropropanols and Chloroesters 2.1 Background 2.2 Analytical considerations 2.3 General considerations on MCPD-esters 2.4 Proficiency tests and collaborative studies 3. Furan 3.1 Background 3.2 Analytical considerations 3.3 Proficiency tests and monitoring exercises 4. Conclusion and Future Trends References
705 705 707 714 714 714 716 721 722 722 722 723 727 728 728
1. ACRYLAMIDE 1.1 Background Acrylamide (2-propenamide, CH2 ¼ CHCONH2, CAS Registry Number 79-06-01, M.W. 71.08) is a colourless, odourless, and highly water soluble (215 g/L at 251C) crystalline compound with a melting point of 84.51C. Acrylamide is an important industrial chemical used since the mid-1950s to produce water-soluble polyacrylamides employed as flocculents for clarifying drinking water, for treating municipal and industrial waste waters and as flow control agents in
Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00020-2
r 2008 Elsevier B.V. All rights reserved.
705
706
Richard H. Stadler and Till Goldmann
oil-well operations. Other salient applications are in soil stabilization, as a grouting agent for repairing sewers and in acrylamide gels used in biotechnology-related practices. Acrylamide has been classified as ‘‘probably carcinogenic to humans’’ (class 2A) by the International Agency for Research on Cancer [1] and exposure at high levels causes damage to the nervous system [2,3]. Acrylamide is also considered a reproductive toxin [4,5], with mutagenic and carcinogenic properties in experimental mammalian in vitro and in vivo systems [6]. Early in 2002, the Swedish National Food Authority and the University of Stockholm jointly announced that they had found considerable levels of acrylamide in starch-based foods [7,8]. The Swedish findings were very rapidly confirmed by several governments, and subsequently all available data on acrylamide was reviewed at an international level. Consequently, intensive investigations on a global scale were launched into acrylamide, encompassing the analysis, occurrence, chemistry, toxicology, and potential health risk of this contaminant in the human diet. It is now highly probable that for the most part of acrylamide is formed during the Maillard reaction, i.e., from reducing sugars or reactive carbonyls that condense with the amino acid asparagine, the latter forming the backbone of the acrylamide molecule [9,10]. As sugars are equally important in the formation of acrylamide, their concentration may be rate limiting, and in some foods increasing carbohydrate content equally increases the rate of formation of acrylamide under thermal conditions (CIAA, ‘‘Acrylamide Toolbox’’ at www.ciaa.be). Considering this, most of the analytical methods were targeted towards the relevant matrices that are potato-based products, bakery wares, cereal-based products such as bread and breakfast cereals, and coffee. The first results published by Tareke and co-workers [8] were based on a method encompassing bromination of acrylamide and determination by gas chromatography-mass spectrometry (GC-MS), initially employed for the determination of the analyte in hydroponically grown tomatoes [11] and proposed by the U.S. Environmental Protection Agency for acrylamide analysis in water [12]. The authors, however, also presented a liquid chromatography tandem MS (LC-MS/MS) method that was cross-validated with results obtained by GC-MS [8]. Initial method development by LC-MS proved challenging, due to the high polarity (and consequently poor retention) of acrylamide and its low molecular weight. Today, the majority of the laboratories are using LC-MS/MS or GC-MS based methods, and since the initial announcement in 2002 many different methods applicable to food have been proposed. Several excellent reviews have been published on the different methods employed for acrylamide determination in foodstuffs [13,14]. Therefore, this chapter will only elaborate the most common approaches that have been applied and highlight the most relevant analytical parameters — following the experiences of these authors — that need attention when performing acrylamide analysis on cooked foods.
Acrylamide, Chloropropanols and Chloropropanol Esters, Furan
707
1.2 Analytical considerations The analytical procedure for the determination of acrylamide broadly speaking encompasses (i) extraction (ii) clean-up and (iii) the instrumental technique. In all method developments, the extraction and clean-up steps are optimized/adapted to the corresponding instrumental tool, to which the protocol invariably refers. LC-MS/MS is considered to be the more appropriate instrument for that purpose as it is adapted for hydro-soluble analytes while achieving the adequate performance. The use of a mass detector is a major advantage in terms of analyte confirmation and quantitation when using stable isotope-labelled internal standards. However, the relatively high cost of this instrument may explain why the use of ‘‘cheaper’’ GC-based methods are also frequently described. A selection (non-exhaustive list) of the different instrumental techniques so far used to measure acrylamide in food are shown in Table 1, corroborating the widespread use of MS detectors that are either coupled to LC or GC separation techniques. The sensitivity of the method depends on several factors, i.e., (i) the final extract concentration (x g sample in x mL), (ii) the extractability, (iii) the signal quality (e.g., ion suppression by LC-MS/MS may impair the overall sensitivity), (iv) the selectivity of the method (e.g., presence of interferences may hamper peak integration or reduce the signal to noise (S/N) ratio) and (v) the sensitivity of the detector. Table 1 Selection of LC- and GC-based methods employed to measure acrylamide in food (non-exhaustive list) Technique
Reference
GC-ECD after derivatization with bromine GC-NPD GC-MS/PCIa GC-MS/NCI GC-MS/EIb GC-TOF-HRMS/EI GC-MS/MS/PCI with ammonia GC-MS/EI after derivatization with bromine SPME-GC-MS/EI Ion chromatography/UV or MS LC-UV or LC-DAD LC-MS LC-MS with 2-mercapobenzoic acid derivatization LC-MS/MS
[49] [130] [15,18,45] [47] [19,47] [26] [46] [16,23,24,27,45,48,131] [17,22] [38] [20,56] [29,36,40,132] [50] [16,21,30], [32–35], [39,48,52,54,55,57] [53]
LC-electrochemical detector a
With methane or methanol or ammonia, with and without bromination. Without derivatization or after derivatization with N,O-bis(trimethylsilyl)fluoroacetamide.
b
708
Richard H. Stadler and Till Goldmann
Today it is possible to state — based on all available publications in the scientific literature pertaining to acrylamide determination in food — that a limit of quantification (LOQ) of ca. 0.01 mg/kg is achievable for all concerned matrices. A clear advantage of GC versus LC could not be determined. However, a better GC separation in complex matrices like cocoa has been reported by Mastovska and Lehotay [15], although most laboratories favour the use of the latter.
1.2.1 Sample preparation, extraction and clean-up As a first step, i.e., prior to sample preparation and extraction, a stable isotopelabelled standard is added to the food sample. The employment of an isotopelabelled surrogate is common practice for quantitative MS analysis, and allows correcting for losses during the analytical procedure and compensates for ion suppression by co-extractives in the MS analyser. For this purpose, the 2,3,3-d3 acrylamide was first used, but due to potential deuterium/proton exchange on the double bond, the more stable 13C3-labelled acrylamide is preferred. However, other standards have been reported, especially in the case of methods without MS detection. These are typically methylacrylamide, N,N-dimethylacrylamide or butyramide for either the control of bromination [8,16,17] or for the correction of the final volume [18]. It is worthwhile to note that the use of non-isotope-labelled internal standard is controversial, as their behaviour through the analytical procedure may differ from that of the target analyte (bromination rate, extraction yield, ionization). Many different approaches to sample preparation and extraction have been proposed. Due to its polarity acrylamide is easily solubilized in food samples using water. The food matrix can be suspended either at room temperature or at higher temperature, which may increase the extraction rate [16,18], or facilitate the solubilization of fatty samples [14]. The use of organic solvents, e.g., methanol [19,20] or acetonitrile [21,22] has also been described. The ratio between sample and extraction solvent is typically between 3 and 10 [18,23], but up to 20 for complex matrices such as green tea [24]. Increasing the swell time or the swell temperature (up to 120 min at 801C in [16]) impacts the extractability of acrylamide in some cases, but usually a 20–30 min extraction time at room temperature will suffice [18]. An enzymatic hydrolysis step using, for example, a thermostable amyloglucosidase may be helpful in the case of cereal-based products to facilitate further work-up of aqueous sample extracts [25]. Some authors have proposed the addition of 1-propanol to the aqueous extract [18,26], which limits the co-extraction of potentially interfering compounds while allowing an azeotropic evaporation. Furthermore, the addition of ethanol greatly reduced foaming of coffee samples by promoting the precipitation of polysaccharides [27]. After reconstitution with water, the aqueous extract is usually defatted using an apolar solvent, e.g., petroleum ether [28] or dichloromethane [29] and clarified by centrifugation, filtration, or protein precipitation by freezing [30,31] or Carrez solutions [23]. These approaches afford ‘‘cleaner’’ extracts, facilitating the
Acrylamide, Chloropropanols and Chloropropanol Esters, Furan
709
bromination of acrylamide or subsequent clean-up by solid phase extraction (SPE). The aqueous extracts may then be further treated by passage over an SPE cartridge or re-extracted with an organic solvent such as 2-butanone [18] or ethyl acetate [28], usually in the presence of salts (ammonium sulphate, sodium chloride) to enhance the extractability (salting-out effect). At least for LC-MS/MS, the use of SPE is an interesting clean-up step as it is selective with small solvent volumes, mainly water-based, that depending on the sensitivity of the instrument can be directly injected into the LC system. Different SPE sorbents have been applied to eliminate interfering compounds. Apolar (C8 or C18), strong anion exchanger (SAX) or strong cation exchanger (SCX) cartridges can be used alone or coupled consecutively [32–34]. Acrylamide in aqueous solution is only partially retained on apolar phases (e.g., C18, described in [35]) or on mixed apolar–polar phases (e.g., Oasis HLB [28,36]). Both require optimization of the clean-up and solvent elution steps. Acrylamide is, however, not retained on SAX or SCX sorbents. The use of mix-mode cartridges combining the aforementioned characteristics may be the most effective approach in terms of providing a ‘‘clean’’ extract, e.g., Isolute Multimode from IST [30] or Oasis MCX [37]. Alternative extraction techniques have been proposed, such as accelerated solvent extraction (ASE) with water [38], ethyl acetate [25], acetonitrile [21] or with dichloromethane-ethanol 98:2 (v/v) [39]. In this later case acrylamide extracted into dichloromethane is re-extracted into water, followed by direct LC-MS/MS analysis. A clean-up step using deactivated Florisil — placed directly into the ASE extraction cell — is an elegant way to combine extraction and purification, and has been shown to be effective for a complex matrix such as coffee [25]. Another possibility is the QUECHERS approach (QUECHERS for Quick, Easy, Cheap, Effective, Rugged, Safe), used for pesticide screening and adapted to acrylamide determination. In principle, QUECHERS is based on similar steps, i.e., liquid–liquid extraction with acetonitrile via salting-out and dispersive SPE [15]. Inoue and co-workers proposed an on-line GPC-LC-MS allowing the centrifuged aqueous extract to be cleaned on the gel permeation column and subsequently analysed by LC-MS without further treatment [40]. However, any extraction technique must be carefully validated by the analyst. In this context, Soxhlet extraction of potato fries in methanol over prolonged periods of time (up to 10 days) resulted in very high amounts of acrylamide [41]. Our laboratory used similar dry methanolic conditions to synthesize the N-glycoside of asparagine and glucose, an important early precursor of acrylamide. Therefore, free asparagine and reducing sugars present in the food matrix could contribute to the formation of acrylamide via the Maillard route during the essentially dry extraction conditions. In a second study, Eriksson and Karlsson [42] extracted cereal and potato products at a pH of 12, finding 2–3-fold higher amounts of acrylamide after such treatment and thus suggesting that not all available acrylamide is extracted from the matrix under conventional conditions. It could be shown that in both the studies acrylamide is generated artefactually, i.e., harsh extraction conditions should definitely be avoided [43,44].
710
Richard H. Stadler and Till Goldmann
Clearly, instrumental detection capability depends directly on the cleanliness of the extract. However, the extraction and clean-up steps should be as fast and as effective as possible while being affordable and as pollution-free as possible. For this purpose the use of SPE is a well-engrained approach.
1.2.2 GC-MS The direct analysis of acrylamide using GC-MS in the electron impact (EI) mode without derivatization may be problematic, due to the fact that acrylamide is polar and not so volatile. Furthermore, a major potential pitfall of analysing native acrylamide by GC is the risk of generating acrylamide in situ in the heated GC injector, particularly if acrylamide precursors should be present in the final extract. This may be avoided by selecting the appropriate extraction solvent that does not co-extract potential precursors, e.g., 1-propanol [18,26]. Finally, the fragmentation in EI mode leads to ions that are commonly observed for small molecules, e.g., hexanoic acid [18]. To solve this latter problem, procedures have been proposed that analyse acrylamide as such using a polar column (e.g., Carbowax, FFAP) in positive chemical ionization (+CI) using methane [18], methanol [15] or ammonia [45]. The use of +CI significantly increases the selectivity as less fragmentation takes place compared to EI. Positive CI has also been proposed for GC-MS/MS analysis [46]. The use of high resolution MS has also been reported, but cannot be considered as a ‘‘routine’’ tool in analytical testing operations [26]. However, most of the GC methods are based on a derivatization of the molecule by bromination [8,16,23], i.e., addition of bromine to the olefine moiety. This approach ensures a better volatility of acrylamide, concomitantly leading to higher molecular weight and hence more selective ions (Figure 1). The derivative can be analysed in the +CI mode with methane [45] or with ammonia as reaction gases, or in negative CI [47]. In more detail, the method encompasses bromination of the filtered, clarified or even SPE-treated [48] aqueous extract using a bromine–water solution with HBr and KBr, or the safer KBr + KBrO3 mixture [49]. After derivatization — typically at 0–41C — from 30 min [49] to 15 h at 41C [16], the excess bromine is neutralized by addition of a sodium thiosulfate solution, and the apolar derivative is extracted by liquid–liquid extraction into an organic solvent, e.g., ethyl acetate or ethyl acetate:cyclohexane (50:50, v/v) as described by Pittet and co-workers in Ref. [23]. This organic extract may be subjected to further clean-up steps over a Florisil column [23] or diatomeous earth [50]. The final derivative 2,3dibromopropionamide is, however, rather unstable and may decompose in the GC injector to furnish 2-bromopropenamide. To avoid possible loss of the analyte, and hence irreproducible results, a small amount of triethylamine is added to catalyse its conversion into 2-bromopropenamide, which then represents the target analyte [51]. The GC columns most commonly employed for the analysis of the bromo-derivative are mid-polar to polar columns, e.g., DB-17 [16] or ZB-Wax [23]. Zhang and co-workers [49] demonstrated that a few phases could be preferably used based on the theoretical plate number i.e.,
711
Acrylamide, Chloropropanols and Chloropropanol Esters, Furan
A) Abundance
O
70
280000
H2C
240000
C C
200000
NH
2
Br 106
160000
149
120000 80000 40000 0 m/z-->
53 79 50
60
70
80
133 122
93 90
100
110
120
130
B) Abundance
150
160
170
160
170
O
73
320000
140
H13 C 2
280000
13
C
13
240000
NH2
C
Br
200000
108
160000
152
120000 80000
56
136
40000 0 m/z-->
79 50
60
70
80
94 90
123 100
110
120
130
140
150 13
Figure 1 GC-MS (full scan) spectra of (A) 2-bromopropenamide and (B) [ C3]-2bromopropenamide.
polyethylene glycol (e.g., DB-WAX or HP-INNOWax) and nitroterephthalic acid modified polyethylene glycol (HP-FFAP). Acrylamide can also be derivatized by silylation of the amide function, as proposed by Lagalante and Felter [22]. The bistrimethylsilyl derivatives were adsorbed from the headspace (HS) onto a poly(dimethylsiloxane) solid phase microextraction (SPME) fibre and analysed with a CP Sil 8 CB column. This method obviates the time-consuming bromination step while procuring a more stable derivative, but is only applicable to dry matrices as BSTFA is highly moisture sensitive. In summary, the GC-MS methods after bromination of acrylamide are fit for purpose, despite relatively more lengthy analysis time and to some extent higher consumption of reagents. The method also allows the detection and quantitation of acrylamide in complex food matrices such as baby food in the low part-perbillion amount, exemplified in Figure 2. Thus, for laboratories that do not have access to a LC-MS/MS apparatus, GC-MS after bromination is the best choice.
712
Richard H. Stadler and Till Goldmann
Abundance 4000
Ion 105.00
2000 0 4000
Ion 149.00
2000 0 4000
Ion 151.00
2000 0 10000
Ion 154.00
Internal standard
6000 2000 Time -->
10.8
10.9
11.0
11.1
11.2
11.3
11.4
11.5
11.6
11.7
11.8
11.9
Figure 2 GC-MS extracted chromatograms (SIM) of a baby food sample spiked with acrylamide at 0.005 mg/kg.
1.2.3 LC-MS/MS Analytical methods based on LC-MS/MS entail shorter analysis time and in broad terms the protocols can be considered ‘‘simpler’’ than those of the GC-MS bromination methods. The drawback of LC-MS/MS are well known, i.e., potential interferences and ion suppression. To avoid these problems — particularly in complex matrices such as cocoa and coffee — emphasis has been placed on the preparation of adequately ‘‘clean’’ extracts [52], the method of choice being SPE clean-up that has consequently been extensively evaluated. The clean-up step can be considered even more critical when only single quadrupole MS instruments are used. The separation of acrylamide on LC columns is an additional challenge. Octadecyl bounded silica (C18 or ODS) are often used [15,20,29,53], but the retention behaviour may differ depending on their endcapping. In this context, a hydrophilic endcapping apparently favours the retention of acrylamide when using an aqueous elution system [15]. Graphite carbon columns (Hypercarb) have also been employed successfully for the determination of acrylamide [21,54], despite the fact that some analysts have noticed that it may lead to unstable responses within an analytical batch [55]. The use of a polymethacrylate gel column has also been reported [32,52] as well as a normal phase column [56]. In the later case, an acidic elution system (H2SO4 0.01 M) was combined with UV detection. Regarding MS/MS detection, the use of multiple reaction monitoring (MRM) significantly enhances the selectivity of the method. One quantifier transition is chosen (usually that leading to the highest signal) and two qualifier mass transitions among the following typical transitions: m/z 72-55; 72-54; 72-44; 72-27, exemplified with a breakfast cereal sample in Figure 3. In Figure 3 the transition m/z 72-55 has been used as quantifier, whereas the transitions m/z
713
Acrylamide, Chloropropanols and Chloropropanol Esters, Furan
5.92 %
71.9 > 54 2.17e3
%
71.9 > 27 2.39e3
%
%
%
71.9 > 54.9 8.44e4
Time 5.0
5.2
Internal standard
74.9 > 30 6.27e3
Internal standard
74.9 > 57.9 1.67e5
5.4
5.6
5.8
6.0
6.2
6.4
6.6
6.8
7.0
7.2
Figure 3 LC-MS/MS chromatograms (MRM) of a breakfast cereal (approximately 0.25 mg/kg) using a Shodex RSpak DE-613 column (150 mm 6 mm i.d.). The LC mobile phase was composed of 0.01% formic acid in water and methanol (6:4, v/v) at flow rate of 0.75 mL/min.
72-54 and 72-27, corresponding respectively to 20–25% of the quantifier, were used as qualifier. Furthermore, two transitions have been considered for the internal standard, i.e., m/z 75-58 as quantifier and 75-30 as qualifier. However, the optimization of each MS parameter should be carefully defined, and Yusa and co-workers even proposed central composite design to obtain a more accurate optimization [21]. Most of the proposed LC-MS/MS methods describe electrospray ionization (ESI), and a few have reported good experience with atmospheric pressure chemical ionization (APCI), e.g., for coffee and cocoa [54], potato- and cereal-based products [37], or for more general matrices [31]. The advantage of APCI over ESI is that it is considered as less prone to ionsuppression. The use of LC-MS/MS also offers the advantage of multiple chemical analysis; Nielsen and co-workers [57] developed a method for the simultaneous analysis of acrylamide, and its precursors asparagine and reducing sugars in bread. In summary, the determination of acrylamide in foodstuffs using isotope dilution coupled to LC-MS/MS represents an ideal combination that provides highly performant methods in terms of analyte selectivity, sensitivity, precision and accuracy, fully tailored to the physico-chemical properties of the analyte.
714
Richard H. Stadler and Till Goldmann
1.3 Proficiency tests When acrylamide was first announced in 2002, there was a lack of suitable methods that could reliably measure the analyte in the pertinent range of foods. Laboratories around the world immediately began developing and validating their own internal test methods, and consequently today there exist a plethora of different approaches, i.e., no ‘‘standard’’ method valid for all matrices. The urgent need of inter-laboratory comparison studies became evident, particularly for those food matrices of most concern (potato-based products, bakery wares, coffee). Thus, already in 2002 several inter-laboratory tests were organized at national (e.g., Germany [58]) or international level [59] (Table 2). The matrices that were covered by these two tests were respectively mashed potatoes, cocoa, crisp bread and butter biscuit for the first one, and crisp bread for the second (Table 2). These first tests showed no statistically significant differences between GC and LC methods, but extraction conditions did, however, directly influence the recovery of the analyte. In the past years several proficiency tests for acryamide in foods have been conducted [60–64]. Depending on the matrices, certain of the above-mentioned analytical methods could lead to an over-estimation of the results, e.g., GC-MS without derivatization. Furthermore, the variation between GC-MS methods (with or without bromination, addition of triethylamine, etc.) led to more variability in the results versus LC-MS/MS-based methods. Overall, the data obtained using GC-MS (with bromination) and LC-MS/MS can be considered comparable, without apparent bias of either technique. Judging from the participants of proficiency tests, it seems though that the use of LC-MS/MS is more widespread. Finally, laboratories are urged to participate on a frequent basis to these tests that are important to demonstrate performance and a functional quality control system.
2. CHLOROPROPANOLS AND CHLOROESTERS 2.1 Background The research group of Prof. Jan Velı´sˇek [65–68] in Prague was the first to demonstrate that chloropropanols could be formed in hydrolyzed vegetable proteins (HVP) produced by hydrochloric acid hydrolysis of proteinaceous by-products from edible oil extraction such as soybean meal, rapeseed meal and maize gluten. It was shown that hydrochloric acid could react with residual glycerol and lipids associated with the proteinaceous materials to yield a range of chloropropanols and their isomers. Generally, 3-chloropropane-1,2-diol (3-MCPD) is the most widely occurring chloropropanol in acid-HVPs together with lesser amounts of 2-chloropropane-1,3-diol (2-MCPD), 1,3-dichloropropanol (1,3-DCP), 2,3-dichloropropanol (2,3-DCP) and 3-chloropropan-1-ol. Studies published in the 1980s showed that the relative proportions of the major chloropropanols (3-MCPD, 2-MCPD, 1,3-DCP and 2,3-DCP) occurring in HVPs manufactured by the conventional technological procedures were
Acrylamide, Chloropropanols and Chloropropanol Esters, Furan
715
Table 2 Examples of inter-laboratory-trials on acrylamide conducted in the period 2002–2003 (non-exhaustive list) Matrix
Contamination level (mg/kg)
Number of laboratories reporting results
Year
Reference
Mashed potato Cocoa Crisp bread Butter biscuit Crisp bread Crisp bread Butter cookies Bread crumb Crisp bread Crisp bread Potato crisps Breakfast cereal Breakfast cereal Coffee Crisp bread 1 Crisp bread 2 Crisp bread 3
10,679 329 206 630 1,200 57 150 116 1,213 707 167 109 95 312 46 498 414
34
2002
[58]
55 62
2002 2003
[59] [60]
37 45 40 35 29 31 42
2002–2003 (pool of 6 tests)
[62]
2003
[63]
approximately in the ratio of 1,000:100:10:1 [69]. Typically, HVPs contained 100–800 mg/kg of 3-MCPD, 10–90 mg/kg of 2-MCPD, 0.1–6 mg/kg of 1,3-DCP and 0.01–0.5 mg/kg of 2,3-DCP, respectively [70]. Concentrations in HVPs depended on the lipid content in the raw material, concentration and amount of HCl, temperature and pressure used and duration of the hydrolysis process. These findings led to intensive investigations into the potential toxicity and possible health effects of chloropropanols, and in 1994 and 1997 the EU Scientific Committee for Food concluded that 3-MCPD should be regarded as a genotoxic carcinogen. Since a safe threshold dose could not be determined, residues in food should be undetectable by the most sensitive analytical method [71]. However, re-evaluation of 3-MCPD by the Joint FAO/WHO Expert Committee on Food Additives (JECFA) in 2001 [72] considered more recent toxicology, mutagenicity and carcinogenicity data, and provided reassurance that the mutagenic activity seen in vitro was not expressed in vivo [73]. Thus, 3-MCPD is classified as a non-genotic carcinogen, for which a toxicological threshold can be defined, and consequently a provisional maximum tolerable daily intake of 2 mg/kg body weight for 3-MCPD was recommended by the EU Scientific Committee on Food [74]. The European Union (EU) has set a regulatory limit of 0.02 mg/kg for 3-MCPD in HVP and soy sauce [75]. Initial concern was focused on acid-HVP, and so the food industry introduced major changes to their
716
Richard H. Stadler and Till Goldmann
manufacturing process to ensure low levels of this undesired compound in the aforementioned products. In this context, the Codex Alimentarius is developing a Code of Practice as a means of disseminating best practice to assist food manufacturers — particularly in developing countries — to take action to reduce the levels of 3-MCPD in their products. However, in recent years several studies have shown that 3-MCPD is also present in foods such as bread, other cereal-based products and meat [76–78]. This has led to further studies on the occurrence and formation pathways of 3-MCPD in heat-processed foods [78,79], as well as some work on potential mitigation strategies (UK Food Standards Agency Stakeholder Meeting, London, 2006). Earlier work has also shown that fatty acid esters of 1,3-DCP and 3-MCPD (mono- and diesters) are formed in acid-HVP [67], but that only traces remained in the final commercial product since the majority were effectively removed during filtration of the hydrolysate (Figure 4). Chloroesters can be intermediates in the formation of DCPs and MCPDs from lipids and the relative amounts of each chloropropanol formed in acid-HVP were dependent on the composition of the lipid in the raw materials used [80]. Newer work has broadened the knowledge on chloroesters and related their formation to thermal treatment of foods, extended to a wide range of processed food products [81,82]. However, further work is needed on the formation occurrence, and toxicity of these compounds and only the fundamental approach to quantifying them in foods will be presented.
2.2 Analytical considerations Several methods for the determination of chloropropanols at trace amounts in foodstuffs such as acid-HVP, soy sauces and related products, processed foods have been published in the literature [83–85]. The absence of suitable chromophores has made approaches based on high performance liquid chromatography (HPLC) with ultraviolet or fluorescence detection unsuitable. Thus, procedures based on GC have been the methods of choice and in the earlier stages of method development the native compound was determined without derivatization using an MS detector [83] or electrolytic conductivity detection [86]. However, the low volatility and high polarity of MCPDs give rise to R R
OH
O
O O
O
HO Cl 3-MCPD
R O
R
O
OH
3-MCPD diesters
R = alkyl
HO
O Cl
O
Cl 3-MCPD monoesters
Figure 4 Chemical structures of 3-MCPD mono- and diesters.
Cl
Acrylamide, Chloropropanols and Chloropropanol Esters, Furan
717
unfavourable interactions with components of GC systems that result in poor peak shape and low sensitivity. Furthermore, the low molecular weight of both MCPDs and DCPs makes mass detection difficult since diagnostic ions cannot be reliably distinguished from background chemical noise. Hence, the earlier methods report limit of detections (LODs) in the range 0.1–0.25 mg/kg in seasonings and related foodstuffs. More recent GC-MS methods have been adapted to afford stable volatile derivatives that can be readily characterized by selective MS detection. In addition, the commercial availability of stable isotope-labelled 3-MCPD has contributed significantly to the reliability of the data. This review will now summarize the main approaches used to quantify chloropropanols and their esters at low concentrations in a wide variety of foodstuffs.
2.2.1 Sample preparation and GC-MS analysis of heptafluorobutyryl (HFB) ester derivatives Methods based on the reaction of 3-MCPD with heptafluorobutyrates and subsequent GC analysis with electron capture detection of the 3-MCPD diheptafluorobutyrate ester were developed in the early 1990s [84], focusing on acid-HVP as the food matrix. Hamlet and Sutton [87] reported on a modified GC-MS procedure for the determination of 3-MCPD in acid-HVP and seasonings. The employment of an isotope-labelled internal standard (3-MCPD-d7) was added to the sample prior to extraction and enabled an LOD of o0.005 mg/kg. In fact, procedures based on the GC/MS detection of HFB esters (heptafluorobutyryl imidazole (HFBI) and heptafluorobutyric acid anhydride (HFBA)) of chloropropanols have been universally applied to the analysis of a wide range of foodstuffs and have subsequently become the normative reference methods [88,89]. The heptafluorobutyric acid reacts with nucleophilic constituents and is therefore suitable for the analysis of all chloropropanols. Since HFBI and HFBA are sensitive to moisture, derivatization must be carried out under anhydrous conditions, which constitutes a critical point. The MS fragmentation pattern of the diheptafluorobutyrate ester of 3-MCPD is depicted in Figure 5. The principle method for the determination of MCPDs by HFBI derivatization is rather straightforward. A deuterated internal standard, 3-MCPD-d5, is added to the test portion, followed by a salt solution, and the mixture is homogenized (e.g., blended with a Polytron homogenizer). Then the contents of an Extrelutt refill pack are added and mixed thoroughly. The mixture is transferred to a glass chromatography column and the non-polar and semi-polar constituents are eluted respectively with diethyl ether/hexane (10+90) and diethyl ether/hexane (40+60). The compounds 2-MCPD and 3-MCPD are eluted with pure diethyl ether through a small column filled with Florisil (deactivated at 3%) and the extract is concentrated to a small volume. A portion of the concentrated extract is derivatized with HFBI to convert 3-MCPD to the corresponding HFB di-ester prior to analysis by GC-MS. Typical ion extract chromatograms of HVP containing ca. 0.015 mg/kg of 3-MCPD and standard compounds are shown in Figure 6.
718
Richard H. Stadler and Till Goldmann
O
O O
OH Cl
+2 OH
C3F7
O
N
O
N HFBI
3-MCPD d5-3-MCPD
C3F7
Cl
O
-ClCH2
C3F7
O
C3F7
m/z 502 m/z 507 O
C3F7
m/z 453 m/z 456 O
HFBI fragments m/z 197
C4OF7
m/z 169
C3F7
m/z 147
C3OF5
m/z 119
C2F5
m/z 69
-C4O2F7
Cl
-C5O2H2F7 O
C3F7
O m/z 289/291 m/z 294/296 O
O
O -HCl
C3F7
O
C3F7
Cl m/z 275/277 m/z 278/280
CF3 -C4O2F7
m/z 239 m/z 241
-HCl
Cl m/z 75/77 m/z 79/81 O m/z 253 m/z 257
C3F7 O
-C2H3 O
C3F7
m/z 225 O
Figure 5 The MS fragmentation pattern of the diheptafluorobutyrate esters of 3-MCPD and d5-3-MCPD showing the key quantitative and qualitative ions in EI-MS.
Brereton and co-workers [88] validated by collaborative trial the procedures developed by the Hamlet group [87,90] for the determination of 3-MCPD at the low mg/kg level in a wide range of foods and ingredients. The approach is analogous to that described above, i.e., the water-soluble 3-MCPD was extracted into saline solution and then partitioned into diethyl ether using a SPE technique based on diatomaceous earth. Dried and concentrated extracts were treated with HFBI in 2,2,4-trimethylpentane and quantification was by a stable isotope internal standard method using 3-MCPD-d5 added to the sample prior to extraction. The method was suitable for the quantification of 3-MCPD at levels of Z0.010 mg/kg and was adopted as an AOAC First Action Official Method. The three main advantages of this approach were (1) (2) (3)
high sensitivity resulting from the formation of a volatile 3-MCPD derivative; high specificity associated with MS detection at higher mass; accurate quantification from the use of a isotope-labelled internal standard.
Judging from the number of recent publications on the subject, method optimization is still a topic that receives attention. The changes are, however,
719
Acrylamide, Chloropropanols and Chloropropanol Esters, Furan
A Abundance
11.04 Ion 257.00 (IS)
13000 11000 9000 Ion 75.00 Ion 253.00 Ion 289.00 Ion 453.00
7000 11.15
5000 3000
11.28 1000 0 Time-->
10.00
10.20
10.40
10.60
10.80
11.00
11.20
11.40
11.60
11.80
B Abundance
11.05 Ion 257.00 (IS)
13000 11000 9000 11.16 7000 5000
11.29 Ion 75.00 Ion 253.00 Ion 289.00 Ion 453.00
3000 1000 0 Time--> 10.00
10.20
10.40
10.60
10.80
11.00
11.20
11.40
11.60
11.80
Figure 6 The extract ion chromatograms showing the qualitative and quantitative ions of 3-MCPD in (A) HVP containing ca. 15 ng/g of 3-MCPD, (B) 2-MCPD and 3-MCPD pooled calibration solution (25 pg/ml).
mainly related to sample extraction conditions, the clean-up stage, or minor modifications of the derivatization step. These have led to some improvements in the LOD/LOQ and precision of the methods. For example, Xu and co-workers [91] employed HFBA modified with catalytic amounts of triethylamine as an alternative reagent that was shown to be more stable, lower the cost of analysis, and maintain the same sensitivity, albeit using negative chemical ionization MS. The method of Brereton [88] was recently modified by Chung et al. [92] using
720
Richard H. Stadler and Till Goldmann
silica gel as 3-MCPD sorbent and ethyl acetate as the elution solvent instead of diethyl ether in the analysis of soy sauces. The LOQ for this method, suitable also for the quantitation of other chloropropanols, was reported at approximately 0.005 mg/kg. Precision of the method was satisfactory at about 5% and the recovery of 3-MCPD from soy sauce spiked at 0.025 mg/kg was 98%.
2.2.2 Sample preparation and GC-MS analysis of dioxaborolane/ dioxaborinane derivatives Boronic acids react specifically with diols to afford cyclic dioxaborolane/ dioxaborinane derivatives. The selective reactivity obviates the need of tedious purification over diatomaceous earth as described before with HFBI as reagent. The derivatization reagent used most frequently is phenylboronic acid (PBA), that yields 4-chloromethyl-2-phenyl-1,3,2-dioxaborolane when reacting with 3-MCPD. The resulting derivatives can be detected by either flame ionization [85] or preferably MS detection [93]. An advantage of the PBA method is that the non-polar cyclic derivatives can be extracted into an apolar solvent such as hexane. A disadvantage, however, is that the DCPs cannot be determined by this method. The derivatization can be conducted either under anhydrous conditions [94] or aqueous conditions [95]. Hence, this approach has been adopted for the analysis of liquid seasonings such as HVP and soy sauces [76,85]. The use of boronic acid derivatives for the determination of MCPDs has been extended to a wide range of different foodstuffs [76,96]. When employed with a stable isotope internal standard and GC-MS operating in selected ion monitoring (SIM) mode, LOQs ranging from 0.010 mg/kg (e.g., soy sauce) to 0.050 mg/kg (e.g., toasted bread) can be achieved. The typical procedure as described by Divinova´ and co-workers entails (1) (2) (3) (4) (5) (6) (7) (8) (9)
suspension of the food sample in hexane/acetone (1:1, v/v); addition of the internal standard; homogenization; filtration; extraction of the organic layer with water; evaporation of the combined extracts in vacuo at 551C to dryness; reaction with PBA (901C for 20 min) after reconstitution in saline solution; extraction of the derivative into hexane; GC-MS analysis of the hexane layer.
The removal of fat was effective and eliminated sample matrix interferences. The method performance was comparable to that of the HFBI method with a repeatability o5% for acid-HVP and coffee.
2.2.3 Sample preparation and GC-MS analysis of dioxolane/dioxane derivatives The reaction of diols with aldehydes and ketones to form cyclic acetals and ketals in an acidic medium is well known [97]. The group of Meierhans [98] were the first to report a quantitative method for 2- and 3-MCPD in soy sauce seasoning
Acrylamide, Chloropropanols and Chloropropanol Esters, Furan
721
and bouillon, using dry acetone as the derivatizing reagent — and reaction solvent at the same time — in the presence of toluene-4-sulphonic acid (TsOH) as catalyst. The resulting 1,3-dioxolane and 1,3-dioxane derivatives are usually characterised by GC-MS, that shows an intense and diagnostic ion isotope pattern. MCPDs were partitioned from aqueous samples/extracts using SPE on diatomaceous earth and diethyl ether elution. In keeping with the HFB reagents, anhydrous conditions are required for derivatization. The procedure proposed by Meierhans [98] gives good results for the determination of 3-MCPD by GC-MS in soy sauce and seasonings provided that an internal standard is added to the sample. However, the protocol cannot be applied directly to other foodstuffs such as bread, cheese, soups or salami, due to matrix interferences and subsequently poor detection and quantification limits. Therefore, several modifications beyond the addition of an internal standard to the procedure of Meierhans [98] have been reported [99,100]. A recent approach applicable to a wide range of foods describes the use of ethyl acetate for the solid phase partition step and additional clean-up after derivatization using basic aluminium oxide cartridges [100]. A further advantage of the cartridges is that they ensure fast removal of the TsOH catalyst, an important step as cyclic ketals are not stable in acidic medium. The LOQs for these methods are in the range 0.001–0.005 mg/kg.
2.3 General considerations on MCPD-esters The occurrence of chloroesters in food was first reported in HVP by Prof. Velisek’s group [67]. Since then, several heat-processed foods [79,101], as well as vegetable oils [102] were added to the list. MCPD-esters have also been detected in goat’s milk [103], milk powders manufactured from cow’s milk and human breast milk (Velı´sˇek, 2006, Presentation at the UK Food Standards Agency Stakeholder meeting, London, 2006). Due to their structural similarity to monoand diacylglycerols, MCPD-monoesters and -diesters represent potential substrates for lipases and can thus be converted into MCPD in the gastrointestinal tract. Consequently, methods have been devised to measure the total amount of chloropropanol, i.e., free and ester derived. There are only a few methods reported for the analysis of MCPD-esters. Hamlet et al. [78], Hamlet and Sadd [79] and Zelinkova et al. [102], developed methods for the direct analysis of esters of 3-MCPD in cereal products and edible oils based on an adaptation of the earlier procedure of Davı´dek et al. (1980) [104]. The isolation and measurement of all chloroesters is a lengthy process due to the many species arising from the different fatty acid combinations associated with each chloropropanol moiety.
2.3.1 Sample preparation and GC-MS analysis of MCPD-Esters Divinova´ et al. [96] developed a method to measure total 3-MCPD in a wide range of foodstuffs. Free and esterified 3-MCPD was isolated from samples as fat using diethyl ether as the extraction solvent. The solvent-free fat extract was then subjected to methanolysis using methanolic sulphuric acid and the 3-MCPD
722
Richard H. Stadler and Till Goldmann
generated was quantified as the PBA derivative using GC-MS as described before. The LOD and LOQ were determined to be 1.1 and 3.3 mg/kg, respectively on the extracted fat basis. Alternatively, chloroesters can be hydrolyzed enzymatically. The group of Colin Hamlet measured total MCPDs in dried cereal products, i.e., free and esterified with fatty acids [78,81]. The MCPDs esterified with fatty acids were released under neutral pH conditions by incubation with a commercial lipase from Aspergillus oryzae for 24 h. Total MCPDs were determined as the HFB-esters by GC/MS as described before. The recovery of 3-MCPD from 3-MCPDdipalmitate reference standard was 106% and 91% at 0.250 and 0.750 mg/kg (sample basis), respectively. The repeatability of the method, expressed as a coefficient of variation, was 3.7% and the LOQ was o0.010 mg/kg. The quantification and ratio of 3-MCPD mono to -diesters are important to assess the contribution of foods to the bioavailability of 3-MCPD. Seefelder and co-workers at the Nestle´ Research Centre [105] were the first to develop a simple and rapid method for the determination of the 3-MCPD mono and -diesters separately using mono-palmitoyl-3-MCPD-d5 as an internal standard. An aminopropyl column was employed to fractionate the di- and mono-esters, eluted respectively with a mixture of hexane/dichloromethane/diethyl ether (89:10:1), followed by hexane/ethyl acetate (85:15). Samples were analysed after hydrolysis and derivatization with PBA as described by Divinova´ et al. [96]. No recent methods for the analysis of monoesters of 1,3- and 2,3-DCP have been reported.
2.4 Proficiency tests and collaborative studies Several proficiency tests have been conducted over the past years on 3-MCPD in a wide range of different foods, organized for example by Food Analysis and Performance Scheme (FAPAS) of the Central Science Laboratory of the UK (http://www.fapas.com/dosearch.cfm). Specific methods for the determination of 3-MCPD in food are not prescribed, but laboratories within the EC must ensure that they employ validated methods that fulfill the performance criteria as stipulated in Commission Directive 2001/22/EC (8 March 2001). A specific method for the determination of 3-MCPD in a wide range of food and food ingredients has been validated by collaborative trial (88, CSL Report FD 97/95). After a pre-trial study, 12 laboratories were asked to analyse 12 test materials by using a prescribed procedure. The study demonstrated the satisfactory validation of the method for quantifying 3-MCPD at levels of Z0.010 mg/kg. The LOD derived from separate in-house studies was estimated to be 0.005 mg/kg.
3. FURAN 3.1 Background Furan (CAS 110-00-9, C4H4O, M.W. 68.07) is a cyclic dienyl ether with a low boiling point (bp760 311C) and is poorly soluble in water. Its industrial uses are
Acrylamide, Chloropropanols and Chloropropanol Esters, Furan
723
mainly focused on synthetic purposes. Furan shows carcinogenic properties in rodents and has thus been classified by IARC as class 2B, i.e., as possibly carcinogenic to humans [106]. The European Food Safety Authority (EFSA) has recently reviewed the toxicity data on furan and found that the weight of evidence indicates that furan-induced toxicity is probably attributable to a genotoxic mechanism; its metabolism to cis-2-butene-1,4-dial is thought to be the main genotoxic route [107], although the results of a recent publication question this evidence [108], hence warranting further studies in this field. In 2004, the US Food and Drug Administration (FDA) reported a comprehensive study on the presence of furan in numerous heat-processed foods, with contamination levels reaching up to 0.122 mg/kg [109], raising the question of the significance of furan in food to human health. The majority of the samples that were analysed were canned and jarred foods, including baby foods, infant formulae, canned vegetables, fruit, meat, fish, pasta sauces, beers and coffee. At the same time, the FDA published the method that was used to gather the data for this study [110,111], with an LOQ of ca. 0.005 mg/kg for most foods. As for acrylamide, the widespread contamination of foods with traces of furan led to global effort to increase the surveillance data, and EFSA reported provisional findings, which included concentration data for some European samples [112]. EFSA has subsequently issued a call for more information on the occurrence of furan in food that will be used in a database to estimate consumer’s exposure [113]. It is important to note, however, that the presence of furan in foodstuffs has been known for several decades, and early reports were collated by Maga [114]. Furan and its derivatives contribute to the flavour profile of many foods such as coffee [115,116], canned meat, cooked meat and baked bread [114,117]. It has now been firmly established that furan in food can be formed by several different pathways, including the thermal degradation of carbohydrates, amino acids, ascorbic acid, and the oxidation of polyunsaturated fatty acids (PUFAS) and carotenoids [114,118–121]. As mentioned before, contamination has been highest in closed food systems due to the impossibility for the volatile furan to escape (e.g., canned and jarred foods, bottled products).
3.2 Analytical considerations The US FDA published the first quantitative method for the determination of furan in different foodstuffs and beverages [110]. Because of its volatility, HS sampling coupled to GC-MS is the method of choice for furan. Consequently, this has been the main approach proposed by the methods published in the literature, with differences mainly linked to the sample preparation and extraction conditions. To ensure method performance, isotope dilution is highly recommended to correct for the air/water differential partition of furan that is dependent on the food matrix. For this purpose, the deuterated isotopomer d4-furan is normally employed and of course the use of the highly selective MS is recommended that enables differentiation between the two isotopes and allows detection down to the low ng/g level in the concerned foods. The most important
724
Richard H. Stadler and Till Goldmann
analytical parameters and method performance characteristics published till date are summarized in Table 3.
3.2.1 Preparation of standard solutions The first step to achieve a reliable furan determination is the correct preparation of standard solutions. In almost all of the proposed methods, the procedures are comparable, i.e., concentrated methanolic furan and d4-furan standard solutions are prepared (typically from 2 to 10 mg/mL) and then diluted in water to attain working solutions of furan and d4-furan on a daily basis. The stock solution is stable for a period of 1–4 weeks at temperatures from 41C to 18 1C. However, due to the high volatility of furan, the preparation of the concentrated methanolic stock solution requires special care. One approach is to fill a HS vial with a known volume of methanol, seal it with septum cap and weigh it. A definite volume of refrigerated furan is then added (injected) and the vial again weighed. The concentration of the solution can be deduced from the weight difference. The vial should be completely filled to avoid furan losses/ partition in the HS.
3.2.2 Sample preparation To avoid losses of the analyte, food samples should be chilled (ca.+41C) before handling. Furthermore, a representative sample should be taken that has been homogenized and the components adequately dispersed, as furan may be ‘‘trapped’’ in the fatty part of sample. Due to the risk of losses of the volatile analyte during sample handling, all operations should be conducted as quickly as possible. In this context, Becalski et al. [122] have shown losses of about 10% when blending the sample for 1 min. A good approach is to chill the sample in its original container before commencing with the work-up, e.g., 4 h at 41C as suggested in the FDA method [110]. Further precautions include preparation in a cold environment, i.e., the use of cryogenic milling, pre-chilled glassware and refrigerated water for sample dilution/solubilization/reconstitution. This step is then immediately followed by the rapid transfer of a sample aliquot into a HS vial. The sample size transferred is usually adapted according to the volume of the HS vial but also to the concentration of furan in the sample, as well as the defined working range. The absolute sample weight reported in the different methods typically ranges from 0.05 g (e.g., coffee powder) to 10 g (e.g., liquid food).
3.2.3 GC-MS analysis of the headspace The partitioning of furan from the food sample into the HS in the vial is affected by time, temperature, ionic strength and the mobility of the sample. Two main HS sampling techniques for the analysis of furan are proposed in the literature: static HS using direct injection, e.g., using pneumatic pressure balance sampling [110,123] or syringe sampling [124], or static HS using SPME. The later technique necessitates the use of a fibre coated with a polymeric sorbent. A 75-mm Carboxent/polydimethylsiloxane fibre is the preferred choice judging by the methods reported so far [125–128]. Volatiles are absorbed for a predefined period
[128]a,b,c
[123]a
c
b
Standard addition. External calibration. SPME method. d Ranges given depends on the matrix.
a
Undiluted to 10–12 1:11 Undiluted to 5–10 1:1 1:2 to 0.01:2 15
[111]a
8
1:1
[127]b,c
[125]b,c
Undiluted to 0.7–1.2 1:10 1:6 10
Undiluted to 10–12 1:11 Undiluted to 14 1:1 1:1 1
15 and 30
30
30
10
20
20
60
10
30
Approximate Equilibration total weight time/SPME incubation (g) (min)
[126]b,c
[122]b
[124]b
[110]a
Reference Sample preparation
25
80
60
30
30
50
30
80
80
Incubation temperature (1C)
HP-PlotQ (15, 0.32, 20) HP-PlotQ (30, 0.25, 20) CP-Pora Bond Q (25, 0.25, 3) HP-PlotQ (15, 0.32, 20) CP-Pora Bond U (25, 0.32, 7) HP-INNOWAX (60, 0.25, 0.5) HP-PlotQ (15, 0.32, 20) HP-PlotQ (15, 0.32, 20) BPX-volatiles (60, 0.25, 1.4)
Column type and dimensions (m, mm, mm)
SIM 68,39/72, 42 SIM 68,69,39/ 72,44 SIM 68,39, 38/72,42,40 SIM 68,39/72, 42 FS 35-150 (68,39/72) FS 35-150 (68,39/72) FS 35-150 (68,39/72,42)
FS 25-150 (68,39/72) SIM 68/72
Ions furan/ d4-furan
LOQ (mg/kg)
0.042
0.8
Information not given 0.086
0.5–2d
0.008– 0.07d
0.2–0.9d
0.03–0.25d
0.6–2.9d
See [123] See [123]
0.026
0.3
0.10– 4.85d 0.034
–
See [123] See [123]
LOD (mg/kg)
Table 3 Summary of key method parameters and performance characteristics reported by different laboratories in the analysis of furan in food
Acrylamide, Chloropropanols and Chloropropanol Esters, Furan
725
726
Richard H. Stadler and Till Goldmann
(10–60 min) and then desorbed thermally (1–5 min, 90–3001C) in the injection port of the GC to drive off the volatiles onto the GC column. SPME allows sample concentration and consequently affords better sensitivity in the low ng/g range [126]. A pivotal step in HS analysis is optimization of the incubation conditions, i.e., the ionic strength of the solution, the incubation temperature and the incubation time. The addition of salts allows an optimal furan transfer from the sample to the HS gas phase and increases the furan concentration in the HS. Altaki and co-workers [128] report an optimal concentration of 20% NaCl for their method, although some analysts tend to work with saturated solutions [110,126], whereas others are using only pure water [123]. Nyman et al. recommend, however, the use of sodium chloride for the analysis of peanut butter as the salt prevents fermentation, and the formed ethanol may lead to interferences. The incubation temperature employed by most analysts is typically at 501C or below, giving adequate sensitivity of ca. 1 mg/kg. In fact, lower incubation temperatures at 251C give a higher sensitivity for SPME [128]. On the other hand, incubation temperatures around 801C or above are disadvantageous as they may lead to the formation of furan in some foodstuffs [129]. Becalski and co-workers showed that an increase in the HS incubation temperature from 30 to 501C afforded only a 50% increase in the furan peak area of an aqueous standard [122]. In some special cases, the incubation temperature may need to be adapted to the food matrix, e.g., when the fat content of the sample hinders the extraction of the analyte; by slightly increasing the incubation temperature this problem may be overcome [122]. In most methods, an incubation time of 20–30 min was found adequate to reach an equilibrium of furan between the gas phase and liquid [123,128]. Bianchi et al. [127] employed a 10 min period that afforded a good signal while shortening the HS-GC-MS run time. Many different GC-MS conditions have been reported and most are variations of the US FDA method. Several GC columns provide adequate retention of furan and separation from other volatiles, such as CP-Pora Bond U [125], HP-INNOWAX [127] and BPX-volatiles [128]. Moreover, the more frequently used column is that proposed in the FDA method, i.e., the porous-layer open tubular PLOT-Q from Agilent dedicated to targeted volatile compounds. Mass detection is usually in the EI-mode, either in full scan or in SIM. Furan is identified by its retention time and the correct ratio between the molecular ion for furan at m/z 68 (quantifier) and one or two qualifier ions; the considered ratio are typically m/z 39/68, 38/68 or 69/68. An accurate quantitation is done by measuring the ratio between the furan quantifier and the d4-furan one. The isotopomer d4-furan can also be confirmed by checking ion ratios, such as m/z 42/72 or 40/72 [125]. Typical mass spectra of furan and d4-furan are depicted in Figure 7. Quantification of furan is based on standard additions or external calibration graphs, both employing an isotope-labelled internal standard. The FDA method is rather tedious as it proposed both standard addition as well as the use of an isotope-labelled standard, equating to seven determinations for the analysis of a
727
Acrylamide, Chloropropanols and Chloropropanol Esters, Furan
A)
Abundance
68
280000
H
H C
C
240000
39
C
200000
H
O
C H
160000 120000 80000 40000
37
0 m/z-->
28
32
36
42 40
44
48
52
56
60
64
68
B) Abundance
72
72
900000
D
D C
C 700000
C D
O
C D
42
500000 300000 100000 0 m/z-->
28
32
36
40
44
40
44
48
52
56
60
64
68
72
Figure 7 GC-MS (full scan) spectra of (A) furan and (B) d4-furan.
single food sample. However, the isotopomer corrects for combined extraction, partition and matrix effects. In fact, no significant difference was observed between the FDA method and the more facile isotope dilution approach with external calibration [124,128]. Recoveries of the analyte for the major foodstuffs are reported better than 90%. The sensitivity of the methods for furan in foods depends on the matrix and on the sample size. However, very low detection limits are achievable and typically range from 0.008 to 1.0 mg/kg, and 0.03 to 2.0 mg/kg for the LOQ in the foodstuffs of concern.
3.3 Proficiency tests and monitoring exercises So far, no proficiency test has been conducted for furan in food, probably attributable to the difficulty in obtaining homogeneous and conservable samples. However, a proficiency test on baby food has been planned by FAPAS tentatively in June 2007. Despite progress in terms of furan analysis, several projects at EU level are ongoing or have just commenced, e.g., the EU monitoring programme of
728
Richard H. Stadler and Till Goldmann
furan in foods following the Commission Recommendation 2007/196/EC, and the EFSA call for furan data.
4. CONCLUSION AND FUTURE TRENDS The analytical tools at the disposal of food analysts and chemists today have evolved considerably over the past 2–3 decades. Progress in particular has been made in the development of confirmatory techniques based mainly on mass spectrometry, that enable detection limits in complex food matrices of basically any single compound (polar, non-polar) in the low part-per-billion range. Extraction and clean-up techniques have also improved, but are clearly adapted to the performance of the analytical detection system. The harmonization of validation approaches, establishment of inter-laboratory performance schemes, availability of centralized databases that allow comparison of data, have all contributed positively to better and more reliable methods being developed and published at an exponential rate. For food-borne chemicals that are considered as ‘‘undesired’’ in foods that comprise our daily diets, these rapid analytical developments with spurious detection limits have led to issues in terms of assessing the true health risk to humans of certain chemicals. The compounds highlighted in this chapter are exemplary of such challenges, particularly from a toxicological/risk assessment viewpoint as experimental data is essentially based on compounds tested in their isolated state and employing animal models usually at exposures of several orders of magnitude above those amounts typically found in food. However, the rapid pace of research in this field will continue, and more compounds with potential health concerns in foods will be discovered albeit at very low amounts. Consequently, there is an urgent need of reliable mechanisms whereby the compounds can be prioritized based upon the margin of safety (effect/exposure relationship), as well as future guidance toward the toxicological evaluation of food within a holistic frame, i.e., avoid testing individual compounds but rather the complete foods.
REFERENCES 1 IARC Monographs on the evaluation of carcinogenic risks to humans, Lyon, France, 1994, Vol. 60, p. 389. 2 H.A. Tilson, Neurobehav. Toxicol. Teratol., 3 (1981) 445. 3 R.M. Lopachin, J. Ellen and E.J. Lehning, Neurotoxicology, 15 (1994) 247. 4 L.G. Costa, H. Deng, C. Gregotti, L. Manzo, E.M. Faustman, E. Bergmark and C.J. Calleman, Neurotoxicology, 13 (1992) 219. 5 K.L. Dearfield, C.O. Abernathy, M.S. Ottley, J.H. Brantner and P.F. Hayes, Mutat. Res., 195 (1988) 45. 6 K.L. Dearfield, G.R. Douglas, U.H. Ehling, M.M. Moore, G.A. Sega and D.J. Brusick, Mutat. Res., 330 (1995) 71. 7 SNFA, 2002. Acrylamide is formed during the preparation of food. Press release. 8 E. Tareke, P. Rydberg, P. Karlsson, S. Eriksson and M. To¨rnqvist, J. Agric. Food Chem., 50 (2002) 4998.
Acrylamide, Chloropropanols and Chloropropanol Esters, Furan
729
9 R.H. Stadler, I. Blank, N. Varga, F. Robert, J. Hau, Ph. Guy, M.-C Robert and S. Riediker, Nature, 419 (2002) 449. 10 D.S. Mottram, B.L. Wedzicha and A.T. Dodson, Nature, 419 (2002) 448. 11 L. Castle, M.J. Campos and J. Gilbert, J. Sci. Food Agric., 54 (1993) 549. 12 U.S. EPA, 1996, SW 846. Test methods for evaluating solid waste, acrylamide by gas chromatography, Method 8032A. U.S. Environmental Protection Agency, Washington, DC. 13 T. Wenzl, M. Beatriz de la Calle and E. Anklam, Food Addit. Contam., 20 (2003) 885. 14 L. Castle and S. Eriksson, J. AOAC Int., 88 (2005) 274. 15 K. Mastovska and S. Lehotay, J. Agric. Food Chem., 54 (2006) 7001. 16 J.S. Ahn, L. Castle, D.B. Clarke, A.S. Llyod, M.R. Philo and D.R. Speck, Food Addit. Contam., 19 (2002) 1116. 17 El-Ghorab, K. Fujioka and T. Shibamoto, J. AOAC Int., 89 (2006) 149. 18 M. Biedermann, S. Biedermann-Brem, A. Noti and K. Grob, Mitt. Lebensm. Hyg., 93 (2002) 638. 19 E. Tateo and M. Bonomi, Int. J. Food Sci., 15 (2003) 149. 20 V. Go¨kmen, H. Senyuva, J. Acar and K. Sarioglu, J. Chromatogr. A, 1088 (2005) 193. 21 V. Yusa, G. Quintas, O. Pardo, P. Marti and A. Pastor, Food Addit. Contam., 23 (2006) 237. 22 A.F. Lagalante and M.A. Felter, J. Agric. Food Chem., 52 (2004) 3744. 23 Pittet, A. Pe´risset and J.M. Oberson, J. Chromatogr. A, 1035 (2004) 123. 24 Y. Mizukami, K. Kohata, Y. Yamaguchi, N. Hayashi, Y. Sawai, Y. Chuda, H. Ono, H. Yada and M. Yoshida, J. Agric. Food Chem., 54 (2006) 7370. 25 S.A. Nestec, Acrylamide by LC-ESIMS/MS in Simple and Complex Matrices, Internal Nestle´ Laboratory, 2004. 26 L. Dunovska, T. Cajka, J. Haslova and K. Holadova, Anal. Chim. Acta, 578 (2006) 234. 27 C. Soares, S. Cunha and J. Fernandes, Food Addit. Contam., 23 (2006) 1276. 28 J. Jiao, Y. Zhang, Y. Ren, X. Wu and Y. Zhang, J. Chromatogr. A, 1099 (2005) 198. 29 B. Eberhart, D. Ewald, A. Sanders, D. Tallmadge, D. Zyzac and M. Strothers, J. AOAC Int., 88 (2005) 1205. 30 J. Rosen and K.-E. Hellenas, Analyst, 127 (2002) 880. 31 H. Senyuva and V. Go¨kmen, Food Addit. Contam., 22 (2005) 204. 32 S. Riediker and R.H. Stadler, J. Chromatogr. A, 1020 (2003) 121. 33 J. Roach, D. Andrzejewski, M. Gay, D. Nortrup and S. Musser, J. Agric. Food Chem., 51 (2003) 7547. 34 D. Andrzejewski, J. Roach, M. Gay and S. Musser, J. Agric. Food Chem., 52 (2004) 1996. 35 F. Calbiani F, M. Careri, L. Elviri, A. Mangia and I. Zagoni, J. AOAC Int., 87 (2004) 107. 36 M. Youg, K. Jenkins and C. Mallet, J. AOAC Int., 87 (2004) 961. 37 H. Senyuva and V. Go¨kmen, Food Chem., 97 (2006) 539. 38 S. Cavalli, R. Maurer and F. Ho¨fler, Fast determination of acrylamide in food samples using accelerated solvent extraction followed by ion chromatography with UV or MS detection. Dionex Applications Book, 2003. 39 F. Brandl, S. Demiani, J. Ewender, R. Franz, M. Gmeiner, L. Gruber, A. Gruner, M. Schlummer, A. Sto¨rmer and G. Wolz, Electron. J. Environ. Agric. Food Chem., 1 (2002) 137. 40 K. Inoue, Y. Yoshimura and H. Nakazawa, J. Liq. Chromatogr. Rel. Tech., 26 (2003) 1877. 41 J. Pedersen and J. Olsson, Analyst, 128 (2003) 332. 42 S. Eriksson and P. Karlsson, LWT, 39 (2006) 392. 43 J. DeVries and B. Post, Analyst, 129 (2004) 93. 44 T. Goldmann, A. Perisset, M.-C. Bertholet, R. Stadler, E. Petersson and K.-E. Hellenas, Food Addit. Contam., 23 (2006) 437. 45 B. Rothweiler, E. Kuhn and H. Prest, Gas chromatography/mass spectrometry approaches to the analysis of acrylamide in food. Agilent Application Note no 5989-0602EN, 2004. 46 K. Hoenicke, R. Gatermann, W. Harder and L. Hartig, Anal. Chim. Acta, 520 (2004) 207. 47 T. Robarge, E. Philips and M. Conoley, Optimizing the analysis of acrylamide in food by quadrupole GC-MS, Application Note #9195, Thermo Electron Corporation, Austin, TX, http://www.thermo.com/ eThermo/CMA/PDFs/Articles/articlesFile_18995.pdf 48 H. Ono, Y. Chuda, M. Ohnishi-Kameyama, H. Yada, M. Ishizaka, H. Kobayashi and M. Yoshida, Food Addit. Contam., 20 (2003) 215.
730
49 50 51 52 53 54 55 56 57 58
59 60 61 62 63 64 65 66 67 68 69 70 71
72
73
74 75
76 77
78 79
Richard H. Stadler and Till Goldmann
Y. Zhang, Y. Dong, Y. Ren and Y. Zhang, J. Chromatogr. A, 1116 (2006) 209. M. Jezussek and P. Schieberle, J. Agric. Food Chem., 51 (2003) 7866. F. Andrawes, S. Greenhause and D. Draney, J. Chromatogr. A, 399 (1987) 269. T. Delatour, A. Perisset, T. Goldmann, S. Riediker and R.H. Stadler, J. Agric. Food Chem., 52 (2004) 4625. Casella, M. Pierri and M. Contursi, J. Chromatogr. A, 1107 (2006) 198–203. P. Aguas, M. Fitzhenry, G. Giannikopoulos and P. Varelis, Anal. Bioanal. Chem., 385 (2006) 1526. Y. Govaert, A. Arisso, J. Van Loco, E. Scheers, S. Fraselle, J.M. Degroodt and L. Goeyens, Anal. Chim. Acta, 556 (2006) 275. E. Paleogolos and M. Kontominas, J. Chromatogr. A, 1077 (2005) 128. N. Nielsen, K. Granby, R. Hedegaard and L. Skibsted, Anal. Chim. Acta, 557 (2006) 211. C. Fauhl, H. Klaffke, W. Mathar, R. Palavinskas and R. Wittkowski, Acrylamide interlaboratory study 2002. Available at http://www.bfr.bund.de/cm/208/acrylamide___interlaboratory_ study_2002.pdf D. Clarke, J. Kelly and L. Wilson, J. AOAC Int., 85 (2002) 1370. T. Wenzl, B. de la Calle, R. Gatermann, K. Hoenicke, F. Ulberth and E. Anklam, Anal. Bioanal. Chem., 379 (2004) 449. H. Klaffke, C. Fauhl, W. Mathar, R. Palavinskas and R. Wittkowski, J. AOAC Int., 88 (2005) 292. L. Owen, L. Castle, J. Kelly, L. Wilson and A. Lloyd, J. AOAC Int., 88 (2005) 285. T. Wenzl and E. Anklam, J. AOAC Int., 88 (2005) 1413. T. Wenzl, L. Karasek, J. Rosen, K.-E. Hellenas, C. Crews, L. Castle and E. Anklam, J. Chromatogr. A, 1132 (2006) 211. J. Velı´sˇek, J. Davı´dek, J. Hajsˇlova´, V. Kubelka, G. Janı´e`ek and B. Ma´nkova´, Zeitschrift fu¨r Lebensmittel-Untersuchung und-Forschung, 167 (1978) 241. J. Velı´sˇek, J. Davı´dek, V. Kubelka, J. Bartosˇova´, A. Tue`kova´, J. Hajsˇlova´ and G. Janı´cˇek, LebensmittelWissenschaft und-Technologie — Food Sci. Technol., 12 (1979) 234. J. Velı´sˇek, J. Davı´dek, V. Kubelka, G. Janı´cˇek, Z. Svobodova´ and Z. Sˇimicova´, J. Agric. Food Chem., 28 (1980) 1142. J. Velı´sˇek, J. Davı´dek, Z. Sˇimicova´ and Z. Svobodova´, Scientific Papers of the Prague Institute of Chemical Technology, E 53 (1982) 55. ´ VTIZ-Potravina´rˇske´ Veˇdy, 3 (1985) 84. J. Velı´sˇek, J. Davı´dek, V. Kubelka and J. Pa´nek, Sbornı´k U J. Velı´sˇek and K. Ledahudcova´, Potravina´rˇske´ Veˇdy, 11 (1993) 149. EC, 1997, Opinion on 3-monochloro-propane-1,2-diol (3-MCPD), expressed on 16 December 1994. In: Food Science and Techniques: Reports of the Scientific Committee for Food (36th series), European Commission, Brussels, pp. 31–33. J. Schlatter, A.J. Baars, M. DiNovi, S. Lawrie and R. Lorentzen, 3-Chloro-1,2-propanediol. In: WHO Food Additives Series 48. Safety Evaluation of Certain Food Additives and Contaminants, Prepared by the Fifty-seventh meeting of the Joint FAO/WHO Rome 2001. Available at http://www.inchem.org/ documents/jecfa/jecmono/v48je18.htm Committee on Mutagenicity of Chemicals in Food, Consumer Products and the Environment (COM) 2000, Mutagenicity of 3-monochloro propane 1,2-diol (3-MCPD), COM statement COM/ 00/S4-October 2000. Available at http://www.advisorybodies.doh.gov.uk/com/mcpd2.htm SCF, 2001, Opinion of the Scientific Committee on food on 3-monochloro-propane-1,2-diol (3-MCPD) updating the SCF opinion of 1994. Adopted on 30 May 2001. EC (2001) Regulation No. 466/2001, Setting maximum levels for certain contaminants in foodstuffs. Official Journal of the European Communities L77/1, 16 March, Office for Official Publications of the European Communities, Luxembourg. C.M. Breitling-Utzmann, H. Kobler, D. Herbolzheimer and A. Maier, Deutsche LebensmittelRundschau, 99 (2003) 280. T. Kuballa and W. Ruge, Analysis and detection of 3-monochloropropane-1,2-diol (3-MCPD) in food by GC/MS/MS, 2004. Available at http://www.varianinc.com/cgi-bin/nav?applications/ gcms&cid ¼ JLQOILQPFJ C.G. Hamlet, P.A. Sadd, C. Crews, J. Velisek and D.E. Baxter, Food Addit. Contam., 19 (2002) 619. C.G. Hamlet and P.A. Sadd, Czech J. Food Sci., 22 (2004) 259.
Acrylamide, Chloropropanols and Chloropropanol Esters, Furan
731
80 P.D. Collier, D.D.O. Cromie and A.P. Davies, J. Am. Oil Chem. Soc., 68 (1991) 785. 81 C.G. Hamlet, P.A. Sadd, D.A. Gray, Chloropropanols and their esters in baked cereal products, In: W. Yokoyama (Eds.), Abstracts of the Division of Agricultural and Food Chemistry, 227th Annual Meeting, Anaheim, California, March 28–April 1, 2004, American Chemical Society, Anaheim 82 R.H. Stadler, V. Theurillat, A. Studer, F. Scanlan and W. Seefelder. The formation of 3-MCPD in food and potential measures of control. In: DFG Symposium Thermal Processing of Food: Potential Health Benefits and Risks, Wiley-VCH, Weinheim, 2007, p. 141. 83 R. Wittmann, Z. fu¨r Lebensmittel-Unters. und-Forsch., 193 (1991) 224. 84 C.A. Van Bergen, P.D. Collier, D.D.O. Cromie, R.A. Lucas, H.D. Preston and D.J. Sissons, J. Chromatogr. A, 589 (1992) 109. 85 W.J. Plantinga, W.G. Van Toorn and G.H.D. Van Der Stegen, J. Chromatogr. A, 555 (1991) 311. 86 G. Spyres, J. Chromatogr. A, 638 (1993) 71. 87 C.G. Hamlet and P.G. Sutton, Rapid Commun. Mass Spectrom., 11 (1997) 1417. 88 P. Brereton, J. Kelly, C. Crews, S. Honour, R. Wood and A. Davies, J. AOAC Int., 84 (2001) 455. 89 British Standards Institution, 2004, BS EN 14573: 2004 Foodstuffs. Determination of 3-monochloropropane-1,2-diol by GC/MS. 90 C.G. Hamlet, Food Addit. Contam., 15 (1998) 451. 91 X. Xu, Y. Ren, P. Wu, J. Han and X. Shen, Food Addit. Contam., 23 (2006) 110. 92 W.C. Chung, K.Y. Hui and S.C. Cheng, J. Chromatogr. A, 952 (2002) 185. 93 H. Wu and G. Zhang, Fenxi Ceshi Xuebao (Journal of Instrumental Analysis), 18 (1999) 64. 94 L.E. Rodman and R.D. Ross, J. Chromatogr. A, 369 (1986) 97. 95 R.L. Pesselman and M.J. Feit, J. Chromatogr. A, 439 (1988) 448. 96 M. Divinova´, B. Svejkovska´, M. Dolezˇal and J. Velı´sˇek, Czech J. Food Sci., 22 (2004) 182. 97 J. March, Advanced Organic Chemistry: Reactions Mechanisms, and Structure, 2nd ed, McGraw-Hill, Tokyo, 1983, 810. 98 D.C. Meierhans, S. Bruehlmann, J. Meili and C. Taeschler, J. Chromatogr. A, 802 (1998) 325. 99 F.M. Dayritt and M.R. Ninonuevo, Food Addit. Contam., 21 (2004) 204. 100 C. Re´tho and F. Blanchard, Food Addit. Contam., 22 (2005) 1189. 101 B. Svejkovska, O. Novotny, V. Divinova, Z. Reblova, M. Dolezal and J. Velisek, Czech J. Food Sci., 22 (2004) 190. 102 Z. Zelinkova, B. Svejkovska, J. Velisek and M. Dolezal, Food Addit. Contam., 23 (2006) 1290. 103 J. Cerbulis, O.W. Parks, R.H. Liu, E.G. Piotrowski and H.M. Farrell, Jr., J. Agric. Food Chem., 32 (1984) 474. 104 J. Davı´dek, J. Velı´sˇek, V. Kubelka, G. Janı´e`ek and Z. Sˇimicova´, Lebensmittel-Untersuchung undForschung, 171 (1980) 14. 105 W. Seefelder, N. Varga, A. Studer, G. Williamson, F. Scanlan and R.H. Stadler, Food Addit. Contam., 25 (2008) 391. 106 IARC Monographs on the evaluation of carcinogenic risks to humans and their supplements, 1995, Vol. 63, p. 393. 107 L. Chen, S. Hecht and L. Peterson, Chem. Res. Toxicol., 8 (1995) 903. 108 L. Durling, K. Svensson and L. Abramsson-Zetterberg, Toxicol. Lett., 169 (2007) 43. 109 FDA, 2004, Exploratory data on furan in food, data through April 28, 2004. Available at http:// www.fda.gov/Bdms/furandat.html 110 FDA, 2004b, Determination of furan in food. Available at http://www.fda.gov/Bdms/ furandat.html 111 FDA, 2006, Determination of furan in food. Available at http://www.fda.gov/Bdms/ furandat.html 112 EFSA Journal, Vol. 137, 2004, pp. 1–20. 113 EFSA, 2006, Invitation to submit data on furan in food and beverages. Available at http:// www.efsa.europa.eu/en/science/data_collection/furan.htmle` 114 J. Maga, CRC Crit. Rev. Food Sci. Nutr., 11 (1979) 355. 115 M. Shimoda and T. Shibamoto, J. Agric. Food Chem., 38 (1990) 802. 116 K. Yanagimoto, L. Kwang-Geun, O. Hirotomo and T. Shibamoto, J. Agric. Food Chem., 50 (2002) 5480.
732
117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132
Richard H. Stadler and Till Goldmann
T. Persson and E. Von Sydow, J. Food Sci., 38 (1973) 377. C. Perez Locas and V. Yaylayan, J. Agric. Food Chem., 52 (2004) 6830. V. Yaylayan, J. Verbr. Lebensm., 1 (2006) 5. Becalski and S. Seaman, J. AOAC Int., 88 (2005) 102. J. Ma¨rk, P. Pollien, C. Lindinger, I. Blank and T. Ma¨rk, J. Agric. Food Chem., 54 (2006) 2786. Becalski, D. Forsyth, V. Casey, B. Lau, K. Pepper and S. Seaman, Food Addit. Contam., 22 (2005) 535. P. Nyman, K. Morehouse, T. McNeal, G. Perfetti and G. Diachenko, J. AOAC Int., 89 (2006) 1417. H. Reinhard, F. Sager, H. Zimmermann and O. Zoller, Mitt. Lebensm. Hyg., 95 (2004) 532. Ho, S. Yoo and S. Tefera, J. AOAC Int., 88 (2005) 574. T. Goldmann, A. Pe´risset, F. Scanlan and R.H. Stadler, Analyst, 130 (2005) 878. F. Bianchi, M. Careri, A. Mangia and M. Musci, J. Chromatogr. A, 1102 (2006) 268. M. Altaki, F. Santos and M. Galceran, J. Chromatogr. A, 1146 (2007) 103. S. Hasnip, C. Crews and L. Castle, Food Addit. Contam., 23 (2006) 219. Yashura, Y. Tanaka, M. Hengel and T. Shibamoto, J. Agric. Food Chem., 51 (2003) 3999. J. Elmore, G. Koutsidis, A. Dodson, D. Mottram and B. Wedzicha, J. Agric. Food Chem., 53 (2005) 1286. J. Rufian-Henares and F. Morales, Food Chem., 97 (2006) 555.
CHAPT ER
21 Food Contact Materials Catherine Simoneau
Contents
1. Introduction 1.1 Potential for migration and migration processes 2. Physical and Chemical Properties 2.1 Substances used in the formulation of materials 2.2 Other substances 3. Analytical Methods 3.1 General analytical considerations regarding compliance of migrants 3.2 Screening methods 3.3 Overall migration testing — plastics 3.4 Specific migration testing and analytical determination of migrants 3.5 Content in the material 3.6 Quality measures and context of official controls 4. Health Effects 4.1 Basis for risk assessment 5. Occurrence in Foods 6. Future Trends References
733 734 736 736 736 741 744 746 747 747 761 763 765 765 768 768 771
1. INTRODUCTION The supply of safe and high-quality foodstuffs relies on the efficient protection of food from deterioration. This can often be achieved simply by food packaging, which can offer mechanical, chemical and biological protection against contamination and extends shelf life of the product. This protection must extend from abuse from macro- or microorganisms, to the control of the transfer of gas/ vapour, moisture, radiation and chemical interaction such as migration. The term ‘‘food contact materials’’ (FCMs) refers to all materials and articles intended to come into contact with foodstuffs, including not only packaging Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00021-4
r 2008 Elsevier B.V. All rights reserved.
733
734
Catherine Simoneau
materials but also cutlery, dishes, processing machines, containers, etc. The term also includes materials and articles that are in contact with water intended for human consumption but it does not cover fixed public or private water supply equipment. Many types of materials can be used for food packaging ranging from plastics, regenerated cellulose, paper and board (P&B), glass and ceramics, elastomers (natural and synthetic rubbers), metals, wood, textile, waxes, etc. Recent years have seen the appearance and evolution of new materials such as biobased or active and intelligent packaging. The prevention of contamination of food by the packaging intended to protect is the object of constant research and regulations in the European Union (EU) and such FCMs are the objects of specific legislations. Various chemical ingredients can be used for the manufacture of FCMs. Those chemicals must comply with many chemical criteria to ensure that packaged foods are safe to consumers. Substances used in the manufacture of FCMs are regulated with maximum limits that may migrate into foodstuffs without causing any health concerns. The harmonization and implementation of food legislation is a major task, which requires scientific and technical consensus among Member States, such as on validated reference methods and materials for quality and safety controls. FCMs need to be tested for compliance with migration limits. Appropriate methodologies are crucial for both industrial and enforcement testing of compliance with the law. Testing compliance in anticipation, conception and implementation of policies for consumer protection also requires adequate reference materials and substances to be used as calibrants in the development of performant methods. Finally, the integration of new Member States also highlights an increasing need for mutual recognition and comparability between laboratories to facilitate a single market and for fostering free trade. The purpose of this chapter is to review the nature of the various potential migrants from FCMs and the implications on their extraction, identification and quantification.
1.1 Potential for migration and migration processes All materials can release small amounts of their chemical constituents when they touch certain types of food. This transfer, from the packaging to the food, is called chemical migration. Any substance that migrates from the packaging into the food is of concern if it could pose health problems to the consumer. The complex composition of plastics (that can have additives to modify their properties), multilayers and coatings for cans enhances this problem. The substances that are used and can migrate depend on the nature of the material. They are most often ingredients employed in the formulation of the packaging that are supposed to fulfil a specific function. These can be monomers and starting substances, catalysts, solvents and suspension media and additives (including for example antioxidants, antistatic, antifogging, slip additives, plasticizers, heat stabilizers, dyes and pigments, etc.). Other substances that
Food Contact Materials
Table 1
735
Important types of materials used in food contact materials
Material
Common starting materials
Typical area of use
Plastics
Natural or, more commonly, synthetic monomers converted to polymers Pulp obtained from plant fibres or recycled paper and cardboard Steel, aluminium, tin Silica from sand or quartz Cross-linked natural rubber and polymers A diverse group including waxes polymers, additives and silicones
All types of food contact materials
Paper/cardboard Metals Glass Rubbers Lacquers and coatings
Bags, cartons, paper, kitchen rolls Cans, tubes, tanks Bottles Stoppers, tubes Surface treatment of many materials
may migrate can be known or unknown isomers, impurities, reaction products and breakdown products of these ingredients. The magnitude of a potential health risk depends on how extensively the typical food intake and diet contacts a wide variety of packaging materials, the extent of use of chemicals in the material to give it its functionality (number of chemicals and concentrations) and the physical factors determining migration. The range of materials in contact with food is varied, but some are used more than others, such as P&B, plastics, coatings (e.g., cans), glass, ceramics; the other categories are lesser used. Some of the more important types of materials are listed in Table 1. Migration is ‘‘the mass transfer from an external source into food by submicroscopic processes’’. Migration produced from the deliberate contact between food and a non-food material during production, processing, transport, storage, cooking and eating. There are several factors and parameters that dictate whether migration might occur and to what extent. These are the nature of the material itself and its composition, the extent of physical conditions favouring migration (duration of contact, temperature) and the capability of the food to extract substances contained in the material considered. It should be noted that materials are formulated in composition to provide certain physico-chemical characteristics to best protect the food. The formulation is therefore a function of the functionality desired. The main mechanism that underlies migration is diffusion, i.e., the macroscopic movement of molecules from high to low concentration or between gases of different compositions. The phenomenon has been extensively studied for plastic polymers [1]. The migration process is governed by diffusion and is controlled by the concentration gradient across the polymer. The diffusion coefficient is determined by the nature of the polymer, the original concentration of the migrant in the packaging before contact with food, the solubility of the migrant in the contacting phase or the
736
Catherine Simoneau
partition coefficient between the polymer and the contacting phase, the temperature of the system and the contact time. Following diffusion through the polymer, migrants move via solvation into food. This is facilitated if the migrant is more soluble in the food than in the polymer, which explains why concern of contamination is higher for fatty foods, as the majority of additives and possible contaminants are more likely to be fat-soluble. In the case of P&B, migration has been studied to a lesser extent than that from polymers and the mechanisms are less defined in part due to the heterogeneity of fibre-based materials, which makes modelling difficult. In addition, these materials serve to pack mainly dry foodstuffs, which represent a less homogeneous contact. Migration can, however, occur due to the presence of large number of pores in the matrix, where, in this case, moisture or fats from foods may penetrate the paper and act in turn as extractants for contaminants.
2. PHYSICAL AND CHEMICAL PROPERTIES Because of the existence of a wide range of materials, there is an even wider range of substances used in their manufacture. There are likely more than 3,000 substances that could be used and more than 400 that are allowed for use. Appropriate methodologies to identify and quantify all these substances must be developed in order to verify their compliance with the limits imposed by the EU legislation.
2.1 Substances used in the formulation of materials Some materials, their typical ingredients in formulation, their functions and the associated potential migrating substances are illustrated in Table 2.
2.2 Other substances Two current examples are highlighted: Inks applied to food packaging materials are not covered by specific European legislation. However, materials and articles intended to come in contact with foods should comply with the general criteria laid down in Art. 3 of Regulation (EC) No. 1935/2004 [2], i.e., should not transfer their constituents to food in quantities which could endanger human health or bring about unacceptable changes in composition or characteristics of foodstuffs. These criteria are also found in the Council of Europe Resolution AP (2005)2 [3] on printed materials and articles intended to come in contact with food. In 2005, an alarm was raised regarding the detection of the ink photoinitiator 2-isopropyl thioxanthone (ITX) in food samples packed with cartons printed with ultraviolet (UV)-cured inks. Although the photoinitiator has not shown to be harmful to human health, its presence should not occur in the food. Isocyanates: The migration and presence of primary aromatic amines (PAAs) in FCMs can come from a variety of sources, as for example rubber, epoxy
Cellulosic fibres
Additives
Paper and board
Paper and board
Printing inks and varnishes
Monomers
Plastics
Additives
Class of substance
Material
Adhesives and coatings Fillers
Chlorine bleaches
Solvent varnishes
Inks
Other
Light stabilizers (UV absorbers) Antistatic agent Slip agents Optical brightners
Antioxidants
Plasticizers
Medium volatile
Volatile
Type of substance
Optical properties and printability
Chemical pulping
Printing (primary or secondary packaging) Shiny appearance
Whitening agent
Against attraction of dirt or dust
Light resistance of polymers
Monomer polystyrene and other Co-monomer in polyethylene (modifier) Monomer of polyamide (e.g., Nylon 12) Monomer of polycarbonate Softness, flexibility, elasticity, processibility PVDC (microwavable) cling film Protection against UV
Example of function
Monomers of styrene/butadiene or styrene/acrylate co-polymers Clay, talc calcium carbonate and titanium dioxide
Fatty acid diethanolmides Silicone oils and stearate of calcium or magnesium 4,4u-Diamino-2,2u-stillbene-disulfonic acid or 2,5-bis-[5u-tertbutylbenzoxazoly(2u)thiophene Residual quantities of polymerization catalysts, cross-linking agent emulsifiers, etc. Volatiles (taint) — solvents used to dissolve pigments and resins, catalysts or initiators of UV curing, hydrocarbons or aldehydes and ketones from alkyd resins (litho-inks), esters (e.g., for flexo and gravure inks), reaction products with foods components (e.g., adduct of mercaptoketones mesityl oxide and hydrogen sulfide for solvent varnishes) Chlorophenols can be formed via a reaction with lignin
Stearyl 3-(3,5-di-tert-butyl-4-hydroxyphenyl)propionate (e.g., Iragnox 1076), or 2,6-di-tert-butyl-4-methylphenol (BHT) Bisphenol A in PVC Benzophenone, derivatives of benzophenone
Acetyl tributyl citrate (ATBC)
Bisphenol A Phthalates, adipates, acetates, oligomers (e.g., polyadipates)
Laurolactam
Styrene 1-Octene
Example of chemical(s)
Table 2 Materials, their typical ingredients in formulation, their functions and associated potential migrating substances
Food Contact Materials
737
Elastomers
Additives
Paper and board
Rubbers, silicone, etc.
Other
Class of substance
Material
Table 2 (Continued )
Inks Solvents Paraffinic substances Volatiles Natural rubber (cispolyisoprene), nitrile rubber (butadiene
Polymer coatings
Other additives
Pigments or mineral coatings Binders
Fluorescent whitening agents
Foam-control agents
Slimicides
Sizing agents, surface sizing agents, wet strength sizing agents Fat repellents Retention aids
Type of substance
Dispersing agents, lubricants (e.g., emulsions of waxes) and preservatives Extrusion of packaging board for liquid foods or as multilayer multimaterial Printing/labelling Carbonless process Waxed paper (Taint) Food processing and preparation: seals, gaskets, pumps parts, belts (e.g., conveyors), some gloves,
Adhesiveness
Aldehydes and ketones Low-molecular-mass substances such as monomers, vulcanizing agents, plasticizers, waxes and antidegradants Volatiles such as butadiene or acrylonitrile
High-molecular-mass polymers and extrusions (e.g., polyethylene) several polymers and potentially a high barrier (e.g., aluminium), plasticizer and volatiles Heavy metals, diisopropylnapthalenes (DIPN)
Water-soluble colloids, or aqueous solutions of synthetic polymers such as styrene butadiene and styrene acrylate butadiene
Polyglycol-fatty acid mixtures, phosphates esters and polyglycol esters Derivatives of 4,4u diaminostillbene-2,2-sulfonic acid, in trans form, e.g., organic sulfur and nitrogen compounds with at least four conjugated double bonds Kaolin
Tall oil rosin, alkyl-ketene dimmers, paraffin waxes starch and starch derivatives (e.g., carboxymethyl cellulose) melamine-formaldehyde, urea-formaldehyde and polyamide resins Fluoroalkyl polymers Polyacrylamides, polyethylenimines with functional groups such as amino or sulfonics Organic bromine, sulfur or nitrogen compounds
Increased hydrophobicity and wet strength of paper
Grease proofing Retain fibres on the wire on paper machine Prevent microbial growth (use of warm/hot water) Avoid foam in paper-making process Fluorescence for increased whiteness Dyes Printability and appearance
Example of chemical(s)
Example of function
738 Catherine Simoneau
Lids
Glass
Cans and metals
Lacquers
Tin
Plastisols of poly(vinyl chloride) (PVC) usually containing 25–45% by weight of plasticizers and additives
Vinyl systems on lower epoxy coating
Epoxy and epoxyphenolics
acrylonitrile copolymer) and blends (e.g., styrene butadiene rubber), elastomers, etc., silicone polymers and thermoplastics elastomers
Thermal stabilizers
Plastisols for ensuring good seal of the closure against the glass rim Plasticizers are used for plasticizing of PVC gasket seals
Products with milder thermal treatments (e.g., pasteurization), e.g., top coating on a lower epoxybased one for beer and beverage cans Glass, crystal glass
Tinplate used for cans, steel kitchen utensils Applications in which flexibility is a requirement
tubing, soothers, moulds (e.g., silicone baking moulds)
Phthalates: di-(2-ethylhexyl) phthalate (DEHP), diisononyl phthalate (DINP), diisodecyl phthalate (DIDP). Also dibutyl sebacate (DBS) and di-(2-ethylhexyl) sebacate (DEHS), di-(2-ethylhexyl) adipate (DEHA), ATBC, Citroflex), epoxidized linseed oil (ELO), acetylated mono/ diglycerides, slip agents (most frequently oleamide and erucamide), lubricants such as silicon or paraffin oil Pigments (titanium oxide) Thermal stabilizers (salts of 2-ethylhexanoic acid) Novel plasticizers: diisononylcyclohexane-1,2-dicarboxylate (DINCH), 2-ethylhexyl palmitate and stearate
Silicon oxide, aluminium, calcium, magnesium, sodium, potassium and fluoride, lead Epoxidized soy bean oil (ESBO)
Tin Chromium Bisphenol A diglycidyl ether (BADGE) and bisphenol F diglycidyl ether (BFDGE) from the epoxy resin. Hydroxy or chloro adducts Vinyl chloride and vinyl acetate
Phthalate plasticizers, phenolic antioxidants and phenylene diamine antiozonants nitrosamines from rubber vulcanization
Food Contact Materials
739
740
Catherine Simoneau
polymers, azo-dyes and aromatic polyurethane products. As such, PAAs are not intended to be present in the final products but could be found as residuals from incomplete reactions, impurities (unreacted), by-products or degradation products from intermediate chemicals or from final products. According to Directive 2002/72/EC [4], FCMs may not release PAAs (expressed as aniline) in a detectable quantity using an analytical method with a detection limit of 20 mg aniline equivalents per kilogram food per food simulant (included the analytical tolerance). A source of migration of PAAs is from multilayered plastics (laminates), which can contain residual quantities of unpolymerized aromatic isocyanates from polyurethane-based adhesives, where the aromatic isocyanates can react with water and form PAAs. Other sources of migration of PAAs in food from FCM are azo-colours, epoxies and plastics.
2.2.1 Innovative materials Recent years have seen the appearance and evolution of new materials, such as biobased ones, which are produced from renewable sources. Examples are polylactic acid (from corn fermentation) or thermoplastic amides. Recent innovations also include active and intelligent packaging. Active packaging refers to the ability to interact with the internal environment of the packed food via the release or scavenging of substances. These materials are commercialized in some countries such as the United States, Japan and Australia, but not yet in the EU, since the current legislation requires an inertness of the packaging versus the food products. Examples of released substances are antioxidants or antimicrobial agents, whereas scavenging can be directed to oxygen, ethylene, moisture or taint. Intelligent packagings include elements that allow a better traceability of the packed foodstuffs by monitoring its history and quality by external or internal indicators. It can, in particular, indicate threats to the quality of the packed food during its shelf life from the manufacturing plant to the consumer’s table. As an example, colorimetric time–temperature indicators point out breaks in the cold chain for refrigerated packed fresh products. These are used in some EU Member States. There are a variety of factors that influence the instrumental techniques that can be applied to the identification and the quantification of migrants from FCMs. Among these factors, physical and chemical properties of the migrants themselves are very important. Substances used in FCMs can range from nonpolar (more often) to polar, most volatile to non-volatile. As a common scientific consensus, substances concerned range generally from molecular weight 50 to 1,000 Da. Above this molecular weight, from a metabolic standpoint, substances are excreted rather than metabolized and therefore are of less toxicological concern. Table 3 outlines the characteristics of several migrating substances from plastic that have been used as reference for their breadth of physical and chemical properties. These migrants have been used in several EU projects such as CRM on Certified Reference Materials (G6RD-CT2000-0411) and FOODMIGROSURE (QLK1-CT2002-2390). Both projects were aimed to develop methods
Food Contact Materials
741
and reference materials for systematic migration kinetics studies either on simulants (CRM) or foodstuffs (FOODMIGROSURE). These substances cover a wide range of different technical applications in the plastic materials as monomers (styrene, bisphenol A, 1-octene, laurolactam) and additives (triacetin, ATBC, BHT). Some of them are already regulated with a limit, some are only subjected to a tolerable daily intake (TDI) and some are substances that could be authorized in the future due to their functionality in other applications (e.g., triclosan) and some need further data (limonene). This table exemplifies the variety of molecular structures, weights, solubility, polarity and volatility.
3. ANALYTICAL METHODS In the context of FCMs, a difference must be established between testing migration, testing in the context of compliance and quantifying in foods themselves. The methodology to verify compliance of FCMs with the limits imposed by law are not only the determination of a substance in a food or in liquids simulating foods (called simulants), but also include a ‘‘migration’’ part, i.e., an exposure of the FCMs to a food or to a food simulant. In that respect, there is an added source of measurement uncertainty, which is unique to FCMs and comes from this step where the performance of the migration test or its interpretation are a well-recognized source of error. As mentioned in the previous section, the nature of the chemical substances present in various FCMs is a driver for determining their propensity to migrate from a particular FCM into a specific food, or into a food simulant. The propensity of the substances to migrate to a lesser or greater extent in various food matrices, and therefore have to be quantified in such matrices, is also a function of the chemical nature of the food matrix. For FCMs, foodstuffs have been classified into four categories: aqueous, acidic, alcoholic and fatty. A fifth one — dry foods — is now also considered. Thus, the legislation in the EU allows in some cases the verification of compliance with limits in simulants themselves, although recent trends for enforcement purposes have further and adequately focused on compliance and, therefore, determination in foodstuffs with their inherent complexities of extraction and quantification. The potential of the constituents from a non-food matrix (the FCM) to be attracted into a particular food matrix must be taken into account when developing adequate analytical protocols. This depends on the nature of the migrant and the nature of the food. Another factor is whether the substance or its limits are in higher or lower concentrations. The difficulty of extraction, identification and quantification from the food matrix is also to consider, i.e., in the number of potential interferences from the matrix. For example, the extraction of non-polar substances presents challenges from oily matrices (with interferences from the matrix during extraction and low selectivity in the separation of the peak of interest from the food matrix). Similar problems can arise to extract polar substances from aqueous foodstuffs or volatiles from dry ones.
742
Catherine Simoneau
Table 3 Examples of migrants and their physical and chemical properties (source project FOODMIGROSURE QLK1-CT2002-2390) Ref. No.
CAS
24610
Synonyms
Molecular weight
Appearance
Solubility
000100-42-5 Styrene
Cinnamol; vinyl benzene
104.15
Liquid, clear, inhibited with 10–15 mg/kg, tertiary butyl catechol
Alcohol, acetone, benzene
22660
000111-66-0
Caprylene
112.22
Liquid, colourless
–
14200
000105-60-2 Caprolactam
2-Oxohexamethyleneimine; hexanolactam
113.16
Crystals, white
Water, alcohol, benzene, chloroform
57760
000102-76-1 Glycerol triacetate
1,2,3-Triacetoxypropane (1,2,3-triacetylglycerol)
218.2
Liquid, colourless
Most of organic solvent
46640
000128-37-0 2,6-Di-tert-butyl-p-cresol
Butylated hydroxytoluene; BHT
220
Crystalline solid, white
13480
000080-05-7 2,2-Bis(4-hydroxyphenyl) propane
Bisphenol A; 4,4isopropylidene-diphenol; 2,2-di-hydroxy-phenyl propane
228.29
Powder, white
Most of organic solvent Alkaline solution, alcohol, acetone
61600
001843-05-6 2-Hydroxy-4-noctyloxybenzophenone 000103-23-1 Adipic acid, bis(2ethylhexyl) ester
326.44
Powder, pale yellow
370
Liquid, colourless
402.5
Liquid, clear, odourless
430
Powder, yellow
Acetone, toluene
530.9
Powder or flakes, white
Acetone, acetic acid, benzene, chloroform, hexane
31920
Synoptic name
1-Octene
93760
000077-90-7 Tri-n-butyl acetyl citrate
38560
007128-64-5 2,5-Bis(5-tert-butyl-2benzoxazolyl) thiophene 002082-79-3 Octadecyl 2-(3,5-di-tertbutyl-4-hydroxyphenyl) propionate
68320
Hexanedioic acid, bis (2-ethylhexyl)ester; di (2-ethylexyl)adipate; dioctyl adipate (DEHA) 1,2,3,-Propanetricarboxylic acid, 2-(acetyloxy)-, tributyl ester; ATBC; EINECS 201-067-0 2,2u-(2,5-Thiophenediyl)bis(5tert-butylbenzoxazole) Benzenepropanoic acid-3,5bis(1,1-dimethylethyl)-4hydroxyoctadecyl ester (Irganox 1076)
Alcohol, benzene
743
Food Contact Materials
Boiling point
Melting point
Formula
Current uses
Applications
145
30.6
C8H8
Styrene polymers, co-polymers (high-impact polystyrene and terpolymers (ABS, SAN). Used in methacrylate-butadienestyrene (MBS) co-polymer added to PVC formulations as an impact modifier. Polyesters
121
102
C8H16
A co-monomer for linear lowdensity polyethylene
269
69
C6H11NO
Synthesis of Nylon-6, blocking agent for isocyanates
258–260
78
C9H14O6
Lubricant, carrier
Diverse applications including packaging materials, kitchenware, household appliances, adhesives, can sealants, and cargo and bulk storage containers. Crystal polystyrene plates, drinking cups, dessert tubs; expanded polystyrene trays (frozen and chill) Film for pre-packed fresh and frozen foods. Part of laminate with paper or aluminium. In bags, and blow moulded for storage containers Used for both-in-the-bag products, 41480 vacuum-packed meat and cheese and food processing equipment. Tubing. Polyurethane coatings used for baking enamels, etc. General use 93695
265
69–70
C15H24O
Antioxidant
General use
250–252 (1.73)
150–155
C15H16O2
45–46
C21H26O3
Cookware articles. Packaging of Polycarbonates, Blends with ABS, fruit juices, beer, coffee and tea. co-polymer with epichlorohydrin to give BADGE Containers for automatic used in epoxy resins. Codispensers, baby bottles. Steam sterilizable food processing polymer with styrene and maleic equipment. Coatings for cans anhydride. Polysulfones and bulk storage containers. Lacquers and varnishes. Pot lids and microwave UV stabilizers General use
67.8
C22H42O4
Plasticizers
PVC, PVDC, coatings, paper
360
C20H34O8
327
196–203
C26H26N2O2S
UV stabilizer, optical brightner
General use
51.5–52.5
C35H62O3
Antioxidant
General use
Same as (Ref. No.)
13607; 39680; 62540; 40060; 19255
744
Table 4
Catherine Simoneau
Nature of foods and nature of migrants prone to migrate into them [5]
Nature of the foodstuffs in contact
Nature of the chemicals in food contact materials likely to be attracted
Aqueous, acidic and low alcoholic food or beverages Fatty foods, distilled spirits
Polar organic chemicals, salts, metals On-polar, lipophilic (highly soluble in fat) organic substances Low molecular weight, volatile substances
Dry foods
Table 4 illustrates the likeliness of attraction of various migrants to various natures of food matrices. In some cases, the compliance with the established limits can also be demonstrated by extracting the substances directly from the FCM itself. This quantity in the material (QM or QMA) can be expressed either as weight of substance per weight of material (QM) or weight per surface area of material (QMA).
3.1 General analytical considerations regarding compliance of migrants In the field of compliance of FCMs, the EU legislation is governed by Regulation 1935/2004 [2]. This regulation gives the general principles for the use of substances in the formulation of FCMs. The substances are evaluated based on toxicological as well as exposure data (i.e., the propensity of the substance to be in the food and ingested). All materials’ constituents have to be effectively authorized for food contact use, which can be demonstrated by screening tests. For parts of the composition that are not covered by the EU Directives (such as colourants, catalysts), the Regulation also applies (Article 3) in the sense that further testing should demonstrate that they are safe. Testing for migration can be aimed at testing towards the total or global amount that could migrate (overall migration, OM), or testing for specific target substances subjected to specific limits (specific migration, SM). In certain cases, it can be also a residual content in the polymer. Because of the complexity and variety of foodstuffs, testing for migration itself can be performed on simpler liquids, the so-called food simulants. There are four simulants described in the legislation for plastics: distilled water or water of equivalent quality (simulant A), 3% acetic acid (w/v) in aqueous solution (simulant B), 10% ethanol (v/v) in aqueous solution (simulant C) and rectified olive oil (simulant D). These simulants mimic under worst-case conditions aqueous foods, acidic foods, slightly alcoholic foods and fatty foods. Olive oil can be replaced by other equivalent non-volatile fatty food simulants in cases of technological impossibility to carry out the determination, as long as the results ensure worst-case scenario as with olive oil. The correspondence between foodstuffs and the
Food Contact Materials
745
Figure 1 Example of a support type on which specimen of films can be held for a total immersion test into a liquid food stimulant.
required simulant can be found in the Directive (85/572/EC) [6] with a focus on plastics materials. Similarly, with respect to the time–temperature exposure between a food/food simulant and material, the Directive (97/48/EC) [7] provides the test conditions (food simulants, contact times and temperatures, etc.) for testing migration of the constituents of plastic materials. The mode of contact between the material and the simulant also aims to correspond to real-case scenarios. A material that comes in contact with the food by both faces (e.g., cling film) will be tested by total immersion, in which the material is plunged in the simulant. A material that contacts by single face will be tested using a metallic cell holding that exposes only one side of the material to the simulant, or by a pouch if the material can be sealed, or for rigid containers by article filling. Figure 1 illustrates a specific device to attach strips of plastics materials whereas Figure 2 shows a device composed of a metallic cell to determine single-face contact. Different methodologies mainly for plastics and, in lesser extent, also for papers have been developed to test migration within the frame of the European Committee for Standardisation (CEN, http://www.cen.eu/cenorm/homepage. htm) to determine either overall or SM. These methods are validated and constitute CEN standards. Methods for the determination of OM correspond to the CEN standard EN 1186 series, whereas those for SM correspond to the CEN standard EN 13130 series. The method descriptions give details related to the performance of migration experiments and the analytical procedures (apparatus, reagents, samples, etc.). Another source of analytical methods is in the Community Reference Laboratory for Food Contact Materials (CRL-FCM, http://crl-fcm.jrc.it/).
746
Catherine Simoneau
Figure 2 Illustration of a specific device to be able to determine single-face contact.
3.2 Screening methods 3.2.1 Characterization of materials The characterization of a material such as plastics can give valuable information on its components, such as – types of monomers or specific additives, also giving some directions into what migration tests could be performed. Similarly, for other materials such as P&B, additives as for example wet strength or grease proofing agents can be individuated. The qualitative characterization of a material is most commonly performed by Fourier Transform Infrared Spectrometer (FT-IR). The samples are scanned through a wavelength range, typically from 600 to 4,000 cm1. Both the polymeric base itself (of materials such as plastics, paper, rubbers elastomers, etc.) and specific functional groups will give out specific characteristics and absorbances that are indicators of their respective identities. A common and user-friendly technique is now the use of attenuated total reflectance (ATR). The characterization can also be extended to several layers by either peeling off or using thin perpendicular slices across layers (which will have been microtomed). However the correct identification depends on the interpretation and, therefore, on the use of spectral libraries. The quality of the libraries (either commercial or produced in-house) thus greatly influences the quality and confidence of the identification.
3.2.2 Identification of constituents and additives in the material This is achieved by a generic extraction procedure that aims at extracting as much as possible from the materials (also termed non-targeted extraction). Therefore, the techniques used for the determination of residual content or quantity in materials are, to some extent, quite similar to those used for screening. For volatiles, a common screening technique can be achieved by headspace gas chromatography mass spectrometry (GC-MS), whereas for lesser volatiles, the screening will take place with a solvent extraction and possibly associated techniques such as fractionation or derivatization. The extract is then analysed with GC-MS either in full scan or in SIM (single ion monitoring) modes to verify the presence of additives eventually used. The scan mode is generically chosen to identify the largest number of substances extracted, whereas the SIM mode
Food Contact Materials
747
targets specific ion fragments to check the presence of specific substances. An example is an ion selection at 530 and 515 amu to check the presence of Irganox1076. For some non-volatile substances, liquid chromatography mass spectrometry (LC-MS) can be a good alternative to GC-MS. Further explanations can be found in Section 3.5 for quantitative analysis and in Chapter 22, for techniques developed for non-target multicomponent analysis.
3.3 Overall migration testing — plastics The reason of determining OM is that the FCMs can produce unacceptable changes in the composition of food (Article 3 of the framework Regulation (EC) 1935/2004) [2]. The EU limit of the OM is 10 mg/dm2 or 60 mg/kg. Because olive oil (simulant D) is a severe solvent compared with most fatty foods, a reduction factor ranging from 2 to 5 may be applied depending on the food. Chocolate has, for example, a reduction factor of 5, which means that the value obtained for the OM into simulant D must be divided by 5 before checking it against the limit (Directive 85/572/EEC) [6]. The time/temperature conditions applied also correspond to specifications set in Directive 97/48/EC [7]. Furthermore, the analytical error in the determination of the OM is 2 mg/dm2 or 12 mg/kg for the aqueous food simulants (A, B and C) and 3 mg/dm2 or 20 mg/kg for the fatty food simulant (D). These methods are described in detail in official CEN or ISO methods (Table 5).
3.4 Specific migration testing and analytical determination of migrants SM is the quantification of the amount of a specific component or substance that migrates from the FCM to the food simulant or food during contact. There are several ways to demonstrate compliance of specific migration limits (SMLs) set in EU food contact legislation. Upon migration, the substances(s) in question must be extracted from the food simulant or the food and then identified and quantified using a suitable technique. The analytical approach that will be chosen depends on – – – –
the the the the
volatility of the substance, its polarity; nature of the food or food simulant (aqueous, fatty); level of determination (high or low); and functional groups of the substance (towards a mode of detection).
The sensitivity for FCMs limits in food has its lowest level (non-detectable) at 10 mg substances per kilogram food. So many detectors can achieve this level, even if some concentration of the samples might be necessary. The most crucial steps in the case of the contaminants from FCMs is their extraction from the foodstuffs or food simulant and their quantification free of interferences.
748
Catherine Simoneau
Table 5
ISO CEN methods of generic nature and for overall migration
Standard reference
Title
Plastics EN 1186-1:2002
Materials and articles in contact with foodstuffs — Plastics — Part 1: Guide to the selection of conditions and test methods for overall migration Part 2: Test methods for overall migration into olive oil by total immersion Part 3: Test methods for overall migration into aqueous food simulants by total immersion Part 4: Test methods for overall migration into olive oil by cell Part 5: Test methods for overall migration into aqueous food simulants by cell Part 6: Test methods for overall migration into olive oil using a pouch Part 7: Test methods for overall migration into aqueous food simulants using a pouch Part 8: Test methods for overall migration into olive oil by article filling Part 9: Test methods for overall migration into aqueous food simulants by article filling Part 10: Test methods for overall migration into olive oil (modified method for use in cases where incomplete extraction of olive oil occurs) Part 11: Test methods for overall migration into mixtures of C-labelled synthetic triglycerides Part 12: Test methods for overall migration at low temperatures Part 13: Test methods for overall migration at high temperatures Part 14: Test methods for ‘substitute tests’ for overall migration from plastics intended to come into contact with fatty foodstuffs using test media iso-octane and 95% ethanol Part 15: Alternative test methods to migration into fatty food simulants by rapid extraction into iso-octane and/ or 95% ethanol
EN 1186-2:2002 EN 1186-3:2002 EN 1186-4:2002 EN 1186-5:2002 EN 1186-6:2002 EN 1186-7:2002 EN 1186-8:2002 EN 1186-9:2002 EN 1186-10:2002
EN 1186-11:2002 EN 1186-12:2002 EN 1186-13:2002 EN 1186-14:2002
EN 1186-15:2002
Paper and board EN EN EN EN
1104:2005 1230-1:2001 1230-2:2001 13676:2001
Paper and board intended to come into contact with foodstuffs — Determination of the transfer of antimicrobial constituents Sensory analysis — Part 1: Odour Sensory analysis — Part 2: Off-flavour (taint) Polymer coated paper and board intended for food contact — Detection of pinholes
Food Contact Materials
749
Table 5 (Continued ) Standard reference
Title
EN 14338:2003
Conditions for determination of migration from paper and board using modified polyphenylene oxide (MPPO) as a simulant Standard atmosphere for conditioning and testing and procedure for monitoring the atmosphere and conditioning of samples (ISO 187:1990) Preparation of a cold water extract Determination of colour fastness of dyed paper and board Preparation of a hot water extract Determination of the fastness of fluorescent whitened paper and board Determination of dry matter content in an aqueous extract
EN 20187:1993
EN EN EN EN
645:1993 646:2006 647:1993 648:2006
EN 920:2000 Other CEN/TS 14234:2002 CEN/TS 14235:2002 CEN/TS 14577:2003 EN 14481:2003 EN 14233:2002
Cookware CEN/TS 129832:2005 Tableware EN ISO 8442-1:1997 EN ISO 8442-2:1997 EN ISO 8442-2:1997 EN ISO 8442-3:1997 EN ISO 8442-4:1997
(Materials and articles in contact with foodstuffs) Polymeric coatings on paper and board — Guide to the selection of conditions and test methods for overall migration Polymeric coatings on metal substrates — Guide to the selection of conditions and test methods for overall migration Plastics — Polymeric additives — Test method for the determination of the mass fraction of a polymeric additive that lies below 1000 Daltons Test methods for the determination of fatty contact Determination of temperature of plastics materials and articles at the plastics/food interface during microwave and conventional oven heating in order to select the appropriate temperature for migration testing Cookware — Domestic cookware for use on top of a stove, cooker or hob — Part 2: Further general requirements and specific requirements for ceramic, glass and glass ceramic cookware Materials and articles in contact with foodstuffs — Cutlery and table holloware — Part 1: Requirements for cutlery for the preparation of food Part 2: Requirements for gold-plated cutlery Part 2: Requirements for stainless steel and silver-plated cutlery Part 3: Requirements for silver-plated table and decorative holloware Part 4: Requirements for gold-plated cutlery
750
Catherine Simoneau
Table 5 (Continued ) Standard reference
Title
EN ISO 8442-5:2004
Part 5: Specification for sharpness and edge retention test of cutlery Part 6: Lightly silver plated table holloware protected by lacquer Part 7: Specification for table cutlery made of silver, other precious metals and their alloys Part 8: Specification for silver table and decorative holloware
EN ISO 8442-6:2000 EN ISO 8442-7:2000 EN ISO 8442-8:2000
Table 6
Application of various chromatographic approaches for various molecules
Type of substance
Example
Predominant chromatographic technique
Volatiles (bpo1501C)
Monomers and solvent residues (e.g., styrene)
Semi-volatiles (substance with a vapour pressure at temperatures up to 3001C) Non-volatiles
Plasticizers, glycols, additives, MWo400– 500 Da (e.g., phthalates)
Headspace, SPME, purge and trap and GC, with mostly FID or MS Liquid injection (split, splitless, PTV, oncolumn, etc.) and GC with mostly FID or MS
Antioxidants, polymeric plasticizers, additives with MW W 400–500 Da (e.g., perfluorotelomers)
LC in majority reverse phase, with diode array, fluorescence or MS detection
Table 6 gives a generic classification of what FCM components are more adequately analysed by one or another technique. The analytical determination of migrants includes three main steps: extraction, sample clean-up (if necessary) and determination (mainly by chromatographic techniques). The extraction and sample clean-up depend on how much substance is expected and its characteristics with respect to those of the matrix. The aim of the clean-up is to remove and discard any substance of the food that could interfere or obscure the signal of the analytes investigated. Another purpose is to remove major food components such as protein, carbohydrates or fats, which may burden and spoil the analytical equipment. The elimination of these compounds allows to maintain the sample throughput, thus, improves the quantification. General information about how to determine SM is available in CEN document ‘‘EN 13130-1:2004 Materials and articles in contact with foodstuffs — Plastics substances subject to limitation — Part 1: Guide to test methods for the specific
Food Contact Materials
751
migration of substances from plastics to foods and food simulants and the determination of substances in plastics and the selection of conditions of exposure to food simulants’’. CEN has also established methods for the determination of some SMs. Table 7 shows a list of components for which CEN methods have been established. A source of analytical methods covering more than 450 of them can be found on the website of the CRL-FCM (http://crl-fcm.jrc.it/). In addition the project Foodmigrosure has produced a number of reviews focused on the analytical methods for a number of migrants,1 and can be used as specific references.
3.4.1 Volatile organic substances Clean-up from most food matrices can be achieved effectively by headspace (static or dynamic), or purge and trap sampling techniques (e.g., Tenax). The food sample is heated and the volatile components are partitioned into the headspace gas leaving the main food components behind. An aliquot of the headspace is then injected into the GC column. In some cases solid-phase microextraction (SPME) has been applied. GC-MS is often preferred due to the possibility to monitor specific ions which lead to an unequivocal identification of the target substances. Heating time and temperature are the major variables. The major drawback of headspace GC-MS is quantification, since headspace is based on a partitioning mechanism between the gas phase and the liquid phase. Each molecule almost has its own partitioning characteristic. Therefore if internal standards are used they must be very close to the target molecule, so close in fact that the standard addition of the same molecule has been suggested as a better option for quantification.
3.4.1.1 Examples: styrene, 1-octene, limonene. Typical volatiles from FCMs include styrene, a monomer of polystyrene, 1-octene and limonene. These migrants are analysed by volatilization (headspace) or distillation GC-MS, or SPME GC-MS. From food matrices, the first two techniques are preferred for the greater efficiency of removal of other food components. Analysis by static or dynamic headspace-GC (FID, flame ionization detector or MS) constitutes an efficient and common determination for the three compounds. In a number of EU projects, model migrants of different chemical structures, polarities, lipophilicity and molecular weights have been extensively studied and several analytical procedures were suggested; some of the examples given here are, therefore, based on the representative substances of the range of physicochemical characteristic encountered in food contact plastics. Examples of other materials that have substances of interest are also included. Static or dynamic headspace GC has been applied to the determination of styrene in coffee and tea [8]. Extraction from foods using this technique have also included determination in sliced potatoes with grated cheese and minced beef fried with tomato sauce [9]. In some cases, limits to the extraction can be reached, 1
Such reviews include non exhaustively two articles published in Trends in Food Science and Technology, 17 (2006) by Silva et al. (p. 535) and Garcı´a et al. (p. 354).
752
Table 7
Catherine Simoneau
CEN/ISO methods for specific substances
Standard reference
Title
Plastics
Materials and articles in contact with foodstuffs — Plastics substances subject to limitation — Part 1: Guide to test methods for the specific migration of substances from plastics to foods and food simulants and the determination of substances in plastics and the selection of conditions of exposure to food simulants Part 2: Determination of terephthalic acid in food simulants Part 3: Determination of acrylonitrile in food and food simulants Part 4: Determination of 1,3-butadiene in plastics Part 5: Determination of vinylidene chloride in food simulants Part 6: Determination of vinylidene chloride in plastics Part 7: Determination of monoethylene glycol and diethylene glycol in food simulants Part 8: Determination of isocyanates in plastics Part 9: Determination of acetic acid, vinyl ester in food simulants Part 10: Determination of acrylamide in food simulants Part 11: Determination of 11-aminoundecanoic acid in food simulants Part 12: Determination of 1,3-benzenedimethanamine in food simulants Part 13: Determination of 2,2-bis(4-hydroxyphenyl)propane (Bisphenol A) in food simulants Part 14: Determination of 3,3-bis(3-methyl-4hydroxyphenyl)-2-indoline in food simulants Part 15: Determination of 1,3-butadiene in food simulants Part 16: Determination of caprolactam and caprolactam salt in food simulants Part 17: Determination of carbonyl chloride in plastics Part 18: Determination of 1,2-dihydroxybenzene, 1,3dihydroxybenzene, 1,4-dihydroxybenzene, 4,4udihydroxybenzophenone and 4,4udihydroxybiphenyl in food simulants Part 19: Determination of dimethylaminoethanol in food simulants Part 20: Determination of epichlorohydrin in plastics Part 21: Determination of ethylenediamine and hexamethylenediamine in food simulants Part 22: Determination of ethylene oxide and propylene oxide in plastics Part 23: Determination of formaldehyde and hexamethylenetetramine in food simulants
EN 13130-1:2004
EN 13130-2:2004 EN 13130-3:2004 EN 13130-4:2004 EN 13130-5:2004 EN 13130-6:2004 EN 13130-7:2004 EN 13130-8:2004 CEN/TS 13130-9:2005 CEN/TS 13130-10:2005 CEN/TS 13130-11:2005 CEN/TS 13130-12:2005 CEN/TS 13130-13:2005 CEN/TS 13130-14:2005 CEN/TS 13130-15:2005 CEN/TS 13130-16:2005 CEN/TS 13130-17:2005 CEN/TS 13130-18:2005
CEN/TS 13130-19:2005 CEN/TS 13130-20:2005 CEN/TS 13130-21:2005 CEN/TS 13130-22:2005 CEN/TS 13130-23:2005
Food Contact Materials
753
Table 7 (Continued ) Standard reference
Title
CEN/TS 13130-24:2005
Part 24: Determination of maleic acid and maleic anhydride in food simulants Part 25: Determination of 4-methyl-1-pentene in food simulants Part 26: Determination of 1-octene and tetrahydrofuran in food simulants Part 27: Determination of 2,4,6-triamino-1,3,5-triazine in food simulants Part 28: Determination of 1,1,1-trimethylolpropane in food simulants
CEN/TS 13130-25:2005 CEN/TS 13130-26:2005 CEN/TS 13130-27:2005 CEN/TS 13130-28:2005 Paper and board EN 12497:2005 EN 12498:2005 EN 14719:2005 EN 1541:2001 EN ISO 15318:1999 EN ISO 15320:2003 Lacquers EN 15136:2006 EN 15137:2006 Ceramics ISO 6486-1:1999 ISO 6486-2:1999 ISO 8391-1:2002 ISO 8391-2:2002 Cook and table ware EN 1388-1:1995 EN 1388-2:1995
Paper and board Determination of mercury in an aqueous extract Determination of cadmium and lead in an aqueous extract Determination of the Diisopropylnaphthalene (DIPN) content by solvent extraction Determination of formaldehyde in an aqueous extract Determination of 7 specified polychlorinated biphenyls (PCB) (ISO 15318:1999) Determination of pentachlorophenol in an aqueous extract (ISO 15320:2003) Materials and articles in contact with foodstuffs — Certain epoxy derivatives subject to limitation Determination of BADGE, BFDGE and their hydroxy and chlorinated derivatives in food simulants Determination of novolac glycidyl ether (NOGE) and its hydroxy and chlorinated derivatives Ceramic ware, glass-ceramic ware and glass dinnerware in contact with food Ware: Release of lead and cadmium — Part 1: Test method Ware: Release of lead and cadmium — Part 2: Permissible limits Cookware: Release of lead and cadmium — Part 1: Method of test Cookware: Release of lead and cadmium — Part 2: Permissible limits Materials and articles in contact with foodstuffs — Silicate surfaces — Part 1: Determination of the release of lead and cadmium from ceramic ware Part 2: Determination of the release of lead and cadmium from silicate surfaces other than ceramic ware
754
Catherine Simoneau
Table 7 (Continued ) Standard reference
Title
Glass ISO 7086-1:2005 ISO 7086-2:2005
Glass hollowware in contact with food Release of lead and cadmium — Part 1: Test method Release of lead and cadmium — Part 2: Permissible limits
Enamel ISO 4531-1:2003
Vitreous and porcelain enamels Release of lead and cadmium contact with food — Part 1: Release of lead and cadmium contact with food — Part 2:
ISO 4531-2:2003
from enamelled ware in Method of test from enamelled ware in Permissible limits
for example in meat by dynamic headspace due to the water present in the meat condensing in the trap [10]. Headspace GC has also been used for 1-octene and in the analysis of limonene in light density polyethylene (LDPE), polycarbonate (PC) and polyethylene terephthalate (PET) absorbed from orange juices [11–13]. A dynamic procedure was applied for the determination of 1-octene from pure beef fat and menhaden fish oil [14,15]. SPME has also been applied for volatile contaminants from FCMs such as styrene in drinking water with a polyacrylate fibre [16] and for 1-octene in ham with carboxen-poly(dimethylsiloxane) [17]. Other procedures are possible, such as extraction from non-fatty foods with weakly polar solvents immiscible with water, or from fatty foods using polar solvents immiscible with fat. Styrene migration into olive oil was determined extracting the sample with hexane, using a Likens–Nikerson distillation apparatus [9]. Styrene shows a very good response by fluorescence and UV and could also be determined by high-performance liquid chromatography (HPLC) using those detectors.
3.4.2 Medium volatiles and non-volatiles organic substances Clean-up from the food matrix can be attempted in a variety of ways: Selective solvent extraction: the food sample is extracted with a solvent selected to dissolve the target substance but not the main food matrix. Solvent–solvent partitioning: the food extract is partitioned (washed) with a second solvent to remove potential interferences. Size exclusion chromatography (SEC) or gel permeation chromatography (GPC) can be used to determine and isolate fraction of target substances that have a molecular weight typically below 1,000 Da; in the case of SEC/GPC, the food extract is passed through a bed of gel with a controlled pore size. The separation takes place on the basis of molecular size. The fraction containing the target substance is collected and the remainder is discarded. The partition is based on molecular size and therefore, the shape of the molecule sought has an influence beyond its molecular mass.
Food Contact Materials
755
Solid-phase extraction (SPE) uses disposable cartridges in miniaturized form of LC. The target substances are absorbed effectively on a cartridge packaged with an active support and the unwanted materials washed off. The target substance(s) is/are then eluted with a change in solvent. The analysis of the extract containing the target migrant(s) can then be done by GC-MS or LC-MS. The choice of GC-MS is indicated for medium volatile migrants, i.e., migrants with a vapour pressure at temperature up to 3001C (e.g., molecules below 1,000 Da). As the majority of the target analytes are non-polar and consequently the extraction solvents are organic and of low polarity, these are amenable to direct GC-MS injection. The start temperature, temperature ramp and holding and injection type are the major variables. The limit of the use of GC-MS is for higher weight molecules (e.g., W500 Da). In this case, the molecules can also often be antioxidants and, therefore, the use of high-temperature columns may also degrade them during their elution. The choice of LC or LC-MS depends on the characteristics of the substance. UV, diode array and fluorescence can be sufficient when the target analytes are known and when they have functional groups that allow them to be detected by these types of detectors. The choice of LC will be based on finding a mobile phase in which the target migrants will be soluble and can be separated unequivocally from other components in the matrix. Separation is then based on either polarity, solubility or molecular mass. The conditions that have influence and improve separations are the nature of the mobile phase, the temperature, the pH (when buffers are used), the stationary phase of the column, the diameter of the column and length, the flow of the elution solvent or mixture and the gradient of binary or ternary mixture elution solvent. The type of mass analyser also has an influence, such as ion trap, triple quadrupole (see Chapter 7). Most often, due to the non-polar nature of most migrants, C18 columns can be used with a medium polarity solvent such as acetonitrile or methanol.
3.4.2.1 Example for monomer from plastics: bisphenol A. For aqueous simulants, the simulant itself can be directly injected in reversed-phase HPLC (RP-HPLC). Examples include the analysis of bisphenol A in water and different concentrations of ethanol in water [18] and in acetic acid [19]. If the concentration is low, a concentration step and/or a change of solvent is necessary prior to the chromatographic analysis. For fatty foods the extraction is a necessity and often conducted with liquid– liquid solvent extraction. For example in the case of bisphenol A using acetonitrile or methanol followed by HPLC, or a dissolution in chloroform [20–23]. The most common technique is RP-HPLC using either fluorescence or UV depending on the limit of detection one is seeking and using C18 columns. 3.4.2.2 Example for additives from plastics: plasticizers such as phthalates, adipates, etc. The section will focus on the analyses from lids due to their current importance as they have been recently specifically regulated in Regulation
756
Catherine Simoneau
No. EC/2007/19 [24]. Several analytical methods are described for the analysis of plasticizers and additives in PVC gaskets and food. In foodstuffs, the pioneering work done by Castle et al. [25] on epoxidized soybean oil (ESBO) employed two derivatization steps of epoxy triglycerides and further determination of the derivates by GC-MS. For oily food samples, Fankhauser-Noti et al. [26] proposed a method in which after transesterification of epoxidized triglycerides, the methyl esters of diepoxy linoleic acid and two internal standards were isolated by HPLC and transferred on-line to GC/FID using on-column interface with concurrent eluent evaporation. Suman et al. [27] developed a method for analysis of ESBO in foodstuffs, which was based on RP-HPLC interfaced with electrospray ion-trap tandem MS and, which included simple sample preparation procedure with extraction step without any further purification prior to the analysis. For the analysis of PVC plasticizers (other than ESBO) in foodstuffs several authors used GPC clean-up prior the analysis with GC-MS [28–31], while others proposed GC-MS or FID with an injector-internal thermal desorption approach in order to avoid GPC clean-up [32,33]. For polyadipates and otherwise systematic determination of plasticizers and additives in representative PVC gasket seal samples and in oily foodstuffs, methods using derivatizations and concurrent determinations using GC-MS were used [32,34–38]. The schemes are represented in Figures 3 and 4.
3.4.2.3 Examples for additives from plastics: antioxidants such as ATBC. From non-fatty foods, ATBC has been extracted from aqueous food extracts by solvents such as cyclohexane–dichloromethane [39,40]. ATBC has been also extracted by SPE with a Tenax adsorption column with hexane from fatty simulants and the same authors have extracted from fatty foods using Soxhlet 7 h with diethylether [41]. For this fairly big molecule, SEC or GPC is often used as means to separate the target from the fatty food matrices. Examples include Castle et al. [42,43] from a large variety of foods, using Biobeads S-X3 and a dichloromethane-cyclohexane. The food had previously been homogenized with acetone–hexane. It should be noted that similar considerations would be made and similar approaches would be used for the other well known and used antioxidant Irganox 1076. 3.4.2.4 Example for coatings: BADGE and derivatives, multianalytes. The extraction and analysis of BAGDE depends on whether the searching is for BADGE alone or BADGE and derivatives. In general, the methodology is based on a solvent extraction procedure to liberate the analytes from the homogenized food matrix, the can coating or food simulant and a successive liquid chromatographic separation and quantification of the extract. Several approaches are currently used for the confirmation of identity, of which MS is the most widely employed. Most often, the analysis is carried out by RP-HPLC and thus requires a preliminary removal of fat and oil (e.g., by partitioning between solvents of different polarity which are not
Figure 3
Solution of the analytes for GC-MS SIM analysis
1. Evaporation to dryness 2. Dissolution in 1.5 ml of THF
Solution of the analytes
2. Water solution of NaCl.
1. Cyclopentanone + boron trifluoride;
Methyl esters of transesterified ESBO components
3. Transesterification (NaOMe/MeOH)
2. Extraction (Acetone: Hexane = 1:1)
1. Adding IS – Ethyl 11,14-diepoxyeicosanoa
Food for ESBO Analysis
The Concentration of ESBO in Food
Analysis by GC-MS in SIM mode
1,3-dioxolane derivatives of transesterified ESBO and IS
Scheme for methodology for plasticizers (left) and (right) ESBO in foods [38].
Fatty components (mono-, di-, triglycerides, etc.
1. Biobeads S-X3 (Bio-Rad) 2. CH2Cl2 : Cycloxehane = 1:1
THF solution for GPC clean-up
1. Adding IS – BBP; 2. Extraction (THF: Hexane = 1:1) 3. Evaporation to dryness 4. Residue dissolving in THF (1 ml)
Fatty Food for Analysis of Phthalates, Adipates, Sebacates, ATBC and Slip Agents
Food Contact Materials
757
758
Catherine Simoneau
Polyadipates in PVC gaskets for the identification of PA type 1. Dissolving in THF 2. Adding of EtOH 3. Centrifugation PVC Residue
Solution of polyadipates 1. Silylation 2. GC-MS analysis The identification data on the type of polyadipate
Fatty Food Analysis of Total Polyadipates 1. Adding IS – Dimethylpimelate; 2. Extraction (THF: Hexane =1:1); 3. Evaporation to dryness; 4. Transesterification (NaOBu/EtOH, 1 min). Dibutyl adipate in butanol solution for GC-MS SIM analysis Concentration of dibutyl adipate
CF Applying of Conversion Factor (CF)
Concentration of Total Polyadipate in Food
Figure 4 Scheme for methodology for polyadipates.
miscible). In aqueous extracts, the extraction solvent can be simply hexane or acetonitrile without further sample preparation [44–47]. For fatty food and food in oily liquid or oil, procedures for RP-HPLC often homogenize the whole can content and only the liquid part of the food is analysed and extracted with a solvent such as hexane/acetonitrile [48–51]. Nonwater-miscible solvents are re-extracted into a water-miscible solvent, mostly acetonitrile. Additional clean-up procedures (SPE) before analysis of the final extract can also been employed. Direct extraction of coatings from cans can also be done when analysed for their release of BADGE, BFDGE and NOGE. The procedure applied consists of a simple extraction with an organic solvent. Most often acetonitrile is applied for RP-HPLC. An extract is prepared by filling the can to a part or completely with the solvent and the maceration process is carried out either by active extraction (stirring) or passively (allowed to stand at ambient temperature for 24 h) [50]. With regard to the quantification, a further explanation is necessary since such limits are now representing multianalytes limits; the solvent extracts containing the analytes obtained from various food matrices are separated from co-extracted matrix compounds on either normal phase or RP-HPLC systems. Quantification is based on external standard calibration. Standards for BADGE and BFDGE and their derivatives are mostly commercially available. Substances not commercially available are calculated on the base of their molecular fluorescence response. In a proposed CEN standard for BAGE and derivatives, a confirmation by hydrolysis of the epoxy groups and the hydrochlorinated adducts was performed. A part of the extract was analysed using RP-HPLC. The remaining extract was hydrolyzed in alkaline medium to produce the di-derivative of BADGE and BFDGE. The second hydrolyzed extract was also analysed and the disappearing of signals were used to confirm the presence of epoxy-containing substances in the first not hydrolyzed extract.
Food Contact Materials
759
3.4.2.5 Example for multilayers and paper and board: ink substance such as photoinitiators. The presence of ink substances, such as photoinitiators, has been the subject of a recent surge of investigations. The methods employed are often targeted to specific liquid food products typically packaged in rigid multimaterial multilayers (e.g., bricks). Such foodstuffs are most often liquid. Determination has been reported by accelerated solvent extraction (ASE) with high-performance thin-layer chromatography (HPTLC) coupled with MS detection of ITX down to levels of 1 mg/kg in fatty food [52]. The sample preparation for HPTLC determination is simple and rapid; however, the mean recovery rates of ITX could be further improved. Other methods available in the literature included the use of GC-MS for the determination of ITX in aqueous simulants [53] and the use of pressurized liquid extraction with LC-MS for its determination in fruit juices, which also offered validation data and potential applications for a wide variety of foods [54]. 3.4.2.6 Example for multilayers and adhesives: primary aromatic amines from isocyanates. There are a number of options for the analysis of PAAs. In Directive 2002/72/EC [4], the migration of PAAs is expressed in aniline equivalents. The reason is that the analytical methodology used is based on a spectrophotometric method, which is the traditional one. Aromatic amines, which may be present in the sample, are diazotized in hydrochloric acid solution and subsequently coupled with N-(1-naphtyl)-ethylene-diamine dihydrochloride to produce a violet-coloured solution. The colour can be enriched using SPE columns and other columns can be used to remove some background interferences if required. The PAA content, calculated as aniline hydrochloride, is determined photometrically at a wavelength of 550 nm. This analytical approach can test collectively all substances that have the PAA moiety, which is the unit that gives the toxicological alert. The method can be used to test the stimulant distilled water, 3% acetic acid solution and 10% ethanol solution. The method cannot be used to test most foodstuffs because they present too much background interferences. Another complication is that some aromatic amines are not carcinogenic but have an individual restriction (e.g., SML in EU Directives). In addition, some non-PAAs substances used for plastics may also give rise to a similar colour reaction. Thus the colorimetric test can be used to pass a material, it should not be used to fail a material. Therefore, a number of approaches have been proposed for confirmation that include GC-MS [55] and LC-MS [56]. CEN is investigating a test system which is presented in Figure 5. The test combines traditional spectrophotometry with LC analysis.
3.4.3 Inorganic substances A number of inorganic substances are severely regulated for migration due to their inherent toxicity. Among them, lead, mercury and cadmium are typical examples. Some additives that are also organometallic in nature as well as catalyst residues are also commonly regulated by the amount of the inorganic
760
Catherine Simoneau
Rules on sampling and storage pf specimens.
Migration test (CEN rules)
Colourimetric assay
If PASS
UV-Vis scan of the coloured solution to check for any interferences
If PASS
HPLC analysis of the colored derivatives
Identification of permitted amines by their retention times
Measure all the other coloured
Determine level of all non-listed PAAs (using response factor =1 vs. aniline)
Figure 5
If PASS If >0.02 mg/kg = > FAIL
Flow chart of the approach of CEN being developed for PAAs.
moiety permitted to migrate. Most methods for elements are similar to those used in food safety, i.e., atomic absorption spectrometry, atomic emission spectrometry with varied extraction and/or digestion techniques for sample pre-treatment. If the target analytes include several elements, inductively coupled plasma MS (ICP-MS) is a method of choice, where digestion can be microwave assisted and performed in sealed containers. A definite advantage of ICP-MS is the capacity to generate multielement data. One aspect in the generation of semi-quantitative multielement data for samples of unknown composition is the plot as smooth curve of element mass against sensitivity yields (as long as isotopic abundance and degree of ionization have been taken into account). A set of elements can be used across the mass range for the response curve with an internal standard to allow back cross-reference to the stored curve and correct instrumental drift. The variations of the technique from a ‘‘true’’ value can fluctuate by a factor of 3, which is why the technique is considered semi-quantitative and therefore more as screening technique.
Food Contact Materials
761
3.5 Content in the material In some cases, the limits imposed are on the quantity in a material (QM, QMA) rather than a migration limit into foods. The reason can be that the substance is volatile and so migration testing would have large uncertainties and measurement difficulties, or that the substance readily reacts with foodstuffs and thus, cannot be measured as such upon migration.
3.5.1 General considerations The measurement of residual content requires the complete extraction of the target substance from the polymer. This can be achieved by headspace or by dissolving the polymer with a strong effective solvent and re-precipitating the polymer with a solvent that would not risk entrapping again the substance. It is widely accepted that the solvent used should both dissolve the target compound well and also swell or dissolve the polymer matrix. Polymer swelling data are readily available in the literature, but the solubilities of the selected substances in potential extraction solvents are not always available and sometimes have to be estimated as a function of the analyte and of the extraction solvent. Several combinations solvent/analyte/polymer have been used. Tetrahydrofuran (THF) has been used to dissolve PVC, as well, other extraction procedures are Soxhlet and reflux. The polymeric material is extracted with a solvent, for example it can be isooctane for 4 h at 601C (conventional conditions for tests — Directive 82/711/EEC) [57]. The sample preparation involves usually pre-cutting the polymer or materials in small pieces or grinding to facilitate the extraction process.
3.5.2 Approaches In some cases, for volatiles where lack of interferences are not suspected, the extraction could be directly in headspace, or the dissolution could be followed by headspace. However attention should be paid to matrix effects that can occur for presence of the polymer in the solvent, which may result in another equilibrium of the solvent/vapour distribution of the analyte. This is the case for substances such as styrene and limonene. It should be noted that for styrene, polystyrene can be swelled by a solvent such as THF and then followed by a separation method such as GPC and LC. Limonene has been extracted with hexane, dichloromethane or ethanol, toluene or a mixture of toluene and m-cresol or methanol [13,58]. BHT was extracted with acetonitrile or with a double extraction with heptane [59–61]. In many cases, the extraction process can be accelerated by shaking or ultrasound [62]. For bisphenol A and related compounds, a typical dissolution–precipitation is commonly used, for example, extraction with dichloromethane followed by methanol or propan-2-ol precipitation [18,63]. Another approach is with chloroform followed by an extraction with a 0.01 M sodium hydroxide solution [23].
762
Catherine Simoneau
For plasticizers the scheme is illustrated in Figure 6. A multianalytical GC-MS method was used for the determination of plastisols in PVC gasket seals. The pioneering work done by Castle et al. [25,34,38] on ESBO employed two derivatization steps of epoxy triglycerides and further determination of the derivates by GC-MS. For substances of higher molecular weight, such as ATBC, for example from sealing resins, hexane is commonly used as extracting solvent. Continuous extraction such as Soxhlet has also been used to extract BHT from HDPE with acetonitrile, DIPN from P&B using dichloromethane and ethanol and ATBC from PVC with cyclohexane [41,64,65]. CEN has also generated standardized test methods that are summarized in Table 8. PVC gasket seal Dissolution(THF) Solution of PVC gasket seal Centrifugation PVC residue
Supernatant
Dilution in MTBE
MTBE solution for GC-MS analysis
1. Transesterification (NaOEt/EtOH, 6 min); 2. Addition of MTBE/hexane; 3. Addition of aqueous Na citrate. MTBE/hexane solution for GC-MS analysis
Figure 6 Scheme of method for extraction of plasticizers from gaskets or PVC in general. Table 8
CEN methods to determine the content in the material
CEN method
Materials and articles in contact with foodstuffs — Plastics substances subject to limitation
CEN/TS 13130-17:2005 CEN/TS 13130-22:2005
Part 17: Determination of carbonyl chloride in plastics Part 22: Determination of ethylene oxide and propylene oxide in plastics Part 4: Determination of 1,3-butadiene in plastics Part 6: Determination of vinylidene chloride in plastics Part 8: Determination of isocyanates in plastics Part 20: Determination of epichlorohydrin in plastics
EN 13130-4:2004 EN 13130-6:2004 EN 13130-8:2004 CEN/TS 13130-20:2005
Food Contact Materials
763
In the case of inorganic compounds, the dissolution of the polymer is followed by a technique adapted to the elements.
3.5.3 Special considerations regarding the application of limits based on materials content A QM limit is difficult to enforce in case of multilayer materials. For thin multilayer materials, the whole film can be extracted and if the QM limit is not exceeded the material is in compliance. However, in case of thick materials (e.g., W0.17 mm) the QM limit should be determined in the layer containing that substance. This is generally not possible. This restriction called QMA is a limit for the substance expressed in 6 mg/dm2 surface area. There are various reasons to establish a QMA, e.g.: No analytical method for the determination of the migration of the substance is provided. The substance is not stable under conditions of migration or the substance is very volatile. The QMA assumes 100% migration from the polymer into the food simulant, therefore it represents the worst-case situation compared for example to an SML. The QMA limit can be applicable to multilayer materials as the expression (6 mg/dm2) is independent from the other layers. Only in case of thick materials the assumption of 100% migration may be unrealistically severe. A QMA limit can also be enforced in the same way as a QM limit. In most cases the polymer can be extracted and the extracted substance can be determined by means of a suitable method.
3.6 Quality measures and context of official controls As with any food analysis, blank internal standards at best or external at worst must be ensured and care must be taken in avoiding either loss of target volatile migrants or contamination, which can occur with ubiquitous molecules such as phthalates. The determination of quantities such as SML, OML, QM and QMA implies various procedural steps e.g., sampling, migration tests with different experimental conditions (OML, SML) or extraction (QM, QMA), as well as the usual multistep analytical determination. Each of these steps is subjected to a certain variability and an overall variability will affect the value found by one laboratory (repeatability) or by more than one laboratory (reproducibility). The analytical difficulty and hence the intrinsic uncertainty of measurements, will vary according to the nature of the limitation in the Directive. Rather than expressing variability as ‘‘reproducibility’’ or ‘‘repeatability’’ the field of food contact has used the term ‘‘analytical tolerance’’, which comprises the variability due to all the above-mentioned procedural steps. In the expression legal limits, the restrictions can be expressed either (1) affected by a specified analytical tolerance; (2) affected by an unspecified analytical tolerance and (3) restrictions not affected by any analytical tolerance.
764
Catherine Simoneau
Restriction with a specified analytical tolerance can be the case of the overall migration limit (OML), since the value of the OML in fatty simulants (60 ppm or 10 mg/dm2) is accompanied by an analytical tolerance of 20 ppm (or 3 mg/dm2). In this case, the variability should be added to the limit value and, only if the value found is greater than 80 ppm ( ¼ 60+20) or 13 mg/dm2 ( ¼ 10+3), the article is considered not in compliance with the Directive. The choice to increase the OML by the value of the tolerance was due to the variability of the analysis. It should be noted that this approach has the disadvantage that as the variability of sampling and analytical procedures becomes less, the overall limit becomes effectively greater. For ‘‘Low’’ SML values (e.g., 0.05 mg/kg or less) the uncertainty of measurement may become a significant problem when establishing compliance or, otherwise, with the limit. This problem is exacerbated when the substance is volatile or of limited stability, or when interfering substances are present in the plastics. These cases often represent substances such as carcinogens or highlytoxic substances, which should ‘‘not be detectable in foodstuffs (when measured by a method with a limit of detection of 0.01 mg/kg)’’, for example acrylamide, or ‘‘not detectable (when measured by a method with a limit of detection of 0.02 mg/kg, analytical tolerance included)’’, for example acrylonitrile. The definition of what constitutes ‘‘not detectable’’ and the low limits gives rise to significant problems when establishing the uncertainty of any method and in this case an SML restriction which includes non-specified analytical tolerance has often been used. The detection limit is fixed, but is subjected to a variability in its determination and therefore is expressed as ‘‘not detectable (detection limit ¼ 20 ppb analytical tolerance included)’’ and was adopted mostly to have a transitional concept until the validation of specific methods of analysis would be completed for such substances. Recent revisions have now showed a trend to express directly as a 10 ppb limit without tolerance included. An SML restriction without any reference to analytical tolerance (thus no indication of the variability) are applied to substances which have SMLs of 50 ppb or greater or to the substances affected by QM or QMA restrictions. This is even truer for high SMLs (above 10–15 mg/kg), where the uncertainty of measurement is likely to be low compared to the limit. A number of substances are subjected to group limits, i.e., QM(T) or SML(T) limitations. The imposition of group limits causes particular difficulties. Except for the epoxy moiety, there is usually no obvious derivatization route to determine the functional group quantitatively. This means that each member of the group must be determined individually and the total amount of the migrating moiety has to be derived by calculation, i.e., by summing the levels of each individual member of the group multiplied by the appropriate conversion factor. Many of the group restrictions cover substances that differ considerably from each other in molecular weight, boiling point, polarity, etc. and so they cannot all be determined by a single analytical procedure. This could lead to greater analytical errors when summing the total amount of the individual substances present. Determination of the total of a group of substances requires that for each
Food Contact Materials
765
member of the group a value must be given, which is either the level actually determined, together with the tolerance on this determination, or the limit of detection for that member of the group. The total is then the sum of these values. This means that if a limit for a group was 0.05 mg/kg and there were more than five substances in the group, each of which was subject to a detection limit of 0.01 mg/kg, even if none of the substances were in fact present it would not be possible to prove that the group limit was not exceeded. It also means that, even for a small group of 2 or 3 substances, if 2 were present at, for example, the 0.02 mg/kg level but with an analytical tolerance of +0.01 mg/kg for the group total, then it would not be possible to prove that a group limit of 0.05 mg/kg had not been exceeded. The relevant parts of the CEN Standard EN 13130 give advice and instructions upon the analytical methods for these groups and how to report the results. In addition, a specific CEN guide addressed this issue: CEN/TR 15356-1:2006 ‘‘Validation and interpretation of analytical methods, migration testing and analytical data for materials and articles in contact with food — Part 1: General considerations’’.
4. HEALTH EFFECTS A potential risk from the use of FCMs derives from their content of substances that might migrate in the foodstuffs in contact. Therefore, to protect the consumer, an assessment of the potential hazards of oral exposure to those potential migrants must be made. To establish the safety of ingestion of migrating substances, both toxicological data and the likely human exposure data need to be combined. From an exposure standpoint, the issues to take into account to evaluate the potential risks for the consumer are
the type of chemical(s) that migrates, the quantity or concentration that migrates, the different packaging for FCMs in which the substances can be found and the different types of food packing with these FCMs and the extent of their consumption.
4.1 Basis for risk assessment 4.1.1 Hazard characterization New substances or substances under re-evaluation are submitted or petitioned with a dossier containing relevant information as well as toxicological and migration data according to the document ‘‘note for guidance’’. These were formerly submitted to the Scientific Committee for Food (SCF) and are now
766
Catherine Simoneau
submitted to the European Food Safety Authority (EFSA, http://www.efsa. europa.eu/). A dossier contains two categories of information: one is directed towards chemistry and migration and the other is toxicological in nature. The chemical dossier contributes data to the identity of the substance, its physical and chemical properties, the intended use, microbiological properties, eventual authorizations in Member States or other countries, data on migration in worst-case scenarios and residual content in the material. The toxicological dossier contains the various toxicological tests that have been performed. As a general principle, the greater the exposure through migration, the more toxicological information will be required in order to establish the safety. For example, in case of low migration (i.e., o0.05 mg/kg food) testing may be limited to three tests of mutagenicity in vitro, whereas for intermediate migration (e.g., 0.05–5 mg/kg food) testing must also include a 90-day oral toxicity studies, normally in two species as well as data to demonstrate the absence of potential for accumulation in man. In the case of high migration (i.e., 5–60 mg/kg/food), an extensive data set is needed which further include studies on absorption, distribution, metabolism and excretion, studies on reproduction in one species and developmental toxicity (normally in two species), as well as studies on long-term toxicity/carcinogenicity, normally in two species. The substances are then classified in categories (0–9) of increasing restrictions according to their increasing toxicity or the lack of adequate data. The OM limit of 60 mg/kg of food applies and SMLs are imposed in accordance with toxicity and exposure.
4.1.2 Exposure assessment To estimate dietary exposure to a substance migrating from food packaging material, information is needed on the types of foods packaged, the nature of the packaging material, migration data, packaging usage factors and food consumption. Two extensive reviews of exposure assessment for food contact have been published by ILSI in 2001 and 2007, respectively, and were extensively used as basis here. They constitute key publication for more specific and thorough reference in the domain, in particular the new extensive guidelines. They can be found at http:// europe.ilsi.org/activities/taskforces/foodchain/PackagingMaterials.htm.
4.1.3 Food consumption data To a large extent food consumption data are available for EU consumers but are not accessible in a uniform way because different methods for collecting the data and different time frames have been used. The reason is that food surveys have been historically carried out for different purposes, often primarily to assess nutrient or energy intake, or have been taken from export/import statistics, or collected to study acute or chronic health effects.
Food Contact Materials
767
At present, several methods are used in Europe to assess food consumption. In addition to household surveys, the most commonly used method is dietary assessment which can take a number of forms as follows
twenty-four-hour recalls (retrospective); food frequency questionnaires (retrospective); dietary history (retrospective) and dietary records of 1, 2, 3 and 7 or more days (prospective).
All these methods are based on different time frames, ranging from 24 h up to 1 year (e.g., food frequency questionnaire). A short time frame usually tends to give an overestimation of the lifetime food intake. Other differences in these methods result from the varying aggregation level (national, household and individual). To assess intake figures, various approximations and/or calculation methods can be used as cost-effective shortcuts.
4.1.4 Food packaging usage One of the key elements in the exposure assessment of FCMs is to link the use of a specific food packaging to a specific food item. For food packaging materials, numerous data of high quality are available when considering the total amount of packaging material used. Sources are well known, units are few and definitions are more consistent than those at the level of the individual packaged product. At the packaged product (consumer) level, data are few and of low quality, definitions are inconsistent, units are diverse and sources of information are disparate. Changes in packaging trends, such as replacement of glass by PET replacement of PVC, emergence of active and intelligent packaging and replacement of rigid packs by flexible laminates, make an estimation of packaging use more difficult. Over time, however, trends are easily identified. The same is true for global packaging markets and global brands. Packaging size also has an impact on exposure. More ready-made foods are now available, often in small packages, which implies a higher surface area to volume exposure.
4.1.5 Migration aspects Limits such as SML or QM are usually based on a TDI or an ADI accounting for a lifetime exposure of a substance present in a foodstuff. However, the daily ingested amount of a specific food item will vary considerably during an approximate lifetime of 70 years. Food packaging will also vary and the level of the substance will vary. The consumer’s total food consumption will vary, depending on gender, age and other factors. However, legislative restrictions in foods are not currently expressed in exposure terms. Migration limits expressed as milligrams of substance per kilogram of food have been chosen as a model for the exposure, historically due to a lack of a better alternative. However, recent efforts have been made to make better use of available food consumption data to obtain estimates of intake of food packaging substances. These data could be used to set more scientifically based migration limits where appropriate.
768
Catherine Simoneau
Migration testing in contact with a food simulant is the normal procedure for checking a food packaging material (plastics) either for compliance testing or at the level of enforcement laboratories. A very modern tool to facilitate compliance testing of plastic materials is to take advantage of mathematical migration modelling, using validated diffusion models for establishing the relationship between the quantity of a substance in the polymer and its SM value to be compared with the SML. Probabilistic modelling (e.g., Monte Carlo) is commonly used to generate distributions and calculate the exposure based on single point data drawn from individual distribution repeatedly (e.g., food consumption, residue levels of contaminant and body weight of the consumer). Assessing numerous combinations of input data leads to a frequency distribution of exposure over a specified time period. The approach is under increased investigations for FCMs for estimating more realistic lifetime exposure assessments. Another tool to measure the exposure is biomarkers. Biomarkers, such as urinary metabolites or haemoglobin adducts, can give a more direct measure of exposure to a substance and may be used either to assess that exposure or to validate and improve other indirect dietary exposure models such as probabilistic models. However, for biomarkers to be useful, the metabolite should be uniquely associated with the substance of interest, the relationship between dietary exposure and excretion should be established, any variation in excretion between individuals should be known and it should be clear that no other sources of the chemical in question (endogenous or exogenous) are present to contribute to that metabolite.
5. OCCURRENCE IN FOODS The human exposure to FCMs contaminants is dictated by how much is ingested via the diet and, therefore, one key element is the levels of concentration of the substances in food, coming from FCMs. An indicative table (Table 9) is presented for a number of substances. The SML is the limit which does not pose a risk if ingested chronically. For most substances, with the exception of plasticizers, the SML should not be and, in practice, is not exceeded (Table 9). One exception is plasticizers for PVC films or lids in contact with fatty foods. In this case, a number of surveys conducted, have shown that maximum permitted levels were exceeded in a significant number of cases (Table 10).
6. FUTURE TRENDS Currently, a strong trend is the screening of non-target migrants. The occurrence of migrants in food that are unforeseen or unexpected, such as degradation products, reaction products or non-intentionally added substances, as for example inks, highlights the necessity to develop techniques adapted to more effective screening.
Food Contact Materials
Table 9
769
Substances and their maximum permitted levels (usually respected)
Ref. No.
CAS
Synoptic name
Restriction
24610
000100-42-5
Styrene
22660 14200 57760 46640 13480
000111-66-0 000105-60-2 000102-76-1 000128-37-0 000080-05-7
61600
001843-05-6
31920
000103-23-1
93760 38560
000077-90-7 007128-64-5
68320
002082-79-3
1-Octene Caprolactam Glycerol triacetate 2,6-Di-tert-butyl-p-cresol 2,2-Bis(4-hydroxphenyl) propane 2-Hydroxy-4-noctyloxybenzophenone Adipic acid, bis(2-ethylhexyl) ester Tri-n-butyl acetyl citrate 2,5-Bis(5-tert-butyl-2benzoxazolyl) thiophene Octadecyl 3-(3,5-di-tert-butyl-4hydroxyphenyl)propionate
SML ¼ 0.6 mg/kg (under review) SML ¼ 15 mg/kg SML(T) ¼ 15 mg/kg – SML ¼ 3 mg/kg SML(T) ¼ 0.6 mg/kg SML(T) ¼ 6 mg/kg SML ¼ 18 mg/kg – SML ¼ 0.6 mg/kg SML ¼ 6 mg/kg
The validation of methods that cover a range of target migrants is also an important issue. The hurdle in this case when several classes of substances are involved is to have a method that needs to be compromising of performance and robustness among the different target migrants. In some case it can be an arduous job that hinders a full validation for all substances, especially if their characteristics lead to different response factors. An example is PAAs either from isocyanates. A confirmation method above a certain threshold is necessary. However, out of the 20 proposed amines for validation, the methods currently proposed using SPE and either GC-MS or HPLC or LC-MS are amenable for validation only for a subset of such substances due to their different response factor. Other areas of strong interest are the refinement of exposure assessment. The legislation on FCMs aims at the protection of the consumer and, therefore, based on health effects of substances combined with how much the consumer might be exposed to the substances via the diet. The exposure assessment is becoming the focal point of the development of future legislation rather than the most conservative approach and assumptions taken until now. EU projects such as FOODMIGROSURE have tackled systematic studies of actual migration of target substances into real foods, as well as tackling mathematical modelling aimed towards exposure assessment. In this sense, modelling is used to predict migration data, which can then be combined with stochastic modelling for food consumption. Finally, the significance of developing methodologies or novel approaches for migrants and materials for which the conventional analytical approaches have limited use has to be highlighted. For example, P&B cannot be tested by the
770
Table 10
Catherine Simoneau
Examples of occurrence of plasticizers causing current issues
Plasticizer
Food type
No samples analysed
Concentration (mg/kg)
SML/TDI
Author
ESBO
Baby food Food wrapped in PVC film Baby food
n/a n/a
o0.1–7.6 1.0–85
30 60
Castle et al. [66]
81
1.5–50.8
30
Various Baby food
66 out of 87 153 95 out of 248 56 86
7–105 o1.5 1.5–135.2 o5–86 47–580
60 30
Hammarling et al. [67] Anonymous [68] Fantoni and Simoneau [69]
10–100 W60 W200 0.09–0.19
60 (300) 60
Diet food
70 91 34 29
Diet food Food (fat W3%)
29 15
DEHA
Diet food
29
0.13–0.14
18
DINP
Food (fat W3%) Food (fat W3%) Food (fat W3%)
DINCH
Food (fat W3%)
22–180 W9 W120 W9 150–740 180, 710
18 9
DIDP
8 13 9 out of 13 12 5 out of 12 2
Oily food Pesto and sauces Food fat W3% DBP BBP DEHP
0.17–0.019 0.11–0.18
60 (300)
TDI 0.1 mg/ kg bw Re-evaluation 3
FankhauserNoti et al. [26] Suman et al. [27] FankhauserNoti et al. [70] Petersen and Breindhal [29]
FankhauserNoti et al. [70] Petersen and Breindhal [29] FankhauserNoti et al. [70]
n/a
conventional techniques (as it is a porous material whose structure would be damaged) and therefore research through EU projects such as BIOSAFE have tackled the development of cytotoxicity approaches for the testing of migrants from P&B, especially in view that much P&B is recycled. Nanotechnology is also an emerging science and a field of growing applications. Nanosciences and nanotechnologies are new approaches to research and development related to phenomena and manipulation of materials at atomic, molecular and macromolecular scales, where material properties differ significantly from those at a larger scale. New materials that are manufactured with small particles in the size range up to 100 nm may exhibit novel properties and nanotechnology can be applied in the production, processing, safety and packaging of food. However, understanding, observing and controlling the properties of matter with lengths of between 1 and 100 nm is a new challenge for the research community and industry. An on-going project financed by the Food Standard Agency (UK) and performed by the Central Science Laboratory (CSL), will gather and collate
Food Contact Materials
771
information related to nanomaterials, with regard to their current and projected uses in FCMs. Based on this information, if a need is identified, experimental work will be conducted to determine the potential migration of nanoparticles from selected materials. Laboratory work will also be undertaken to determine if the incorporation of nanocomponents (an arrangement of nanoparticles) has any significant effect on the migration of other substances.
REFERENCES 1 O. Piringer, Mathematical modelling of chemical migration from food contact materials. In: K.A. Barnes, C.R. Sinclair and D.H. Watson (Eds.), Chemical Migration and Food Contact Materials, Woodhead Publishing, Ltd, Cambridge, 2006, p. 180. 2 Regulation (EC) No. 1935/2004 of the European Parliament and of the Council of 27 October 2004 on materials and articles intended to come into contact with food and repealing Directives 80/590/ EEC and 89/109/EEC, 2004. 3 Resolution ResAP (2005) 2 on packaging inks applied to the non-food contact surface of food packaging materials and articles intended to come into contact with foodstuffs (Adopted by the Committee of Ministers on 14 September 2005 at the 937th meeting of the Ministers’ Deputies). www.coe.int 4 Commission Directive of 6 August 2002 relating to plastic materials and articles intended to come into contact 2002/72/EC. 5 L. Castle, Chemical migration into food, an overview. In: K.A. Barnes, C.R. Sinclair and D.H. Watson (Eds.), Chemical Migration and Food Contact Materials, Woodhead Publishing, Ltd, Cambridge, 2006, p. 1. 6 Council Directive 85/572/EEC of 19 December 1985 laying down the list of simulants to be used for testing migration of constituents of plastic materials and articles intended to come into contact with foodstuffs. 7 Commission Directive 97/48/EC of 29 July 1997 amending for second time Council Directive 82/711/EEC laying down the basic rules necessary for testing migration of the constituents of plastics materials and articles intended to come into contact with foodstuffs. 8 S.L. Varner and C.V. Breder, J. Assoc. Off. Anal. Chem., 67 (1984) 516. 9 S.M. Jickells, P. Gancedo, C. Nerin, L. Castle and J. Gilbert, Food Addit. Contam., 10 (1993) 567. 10 J.W. Gramshaw and H.J. Vandenburg, Food Addit. Contam., 12 (1995) 223. 11 J. Simal-Gandara, M. Sarria-Vidal, A. Koorevaar and R. Rijk, Food Addit. Contam., 17 (2000) 703. 12 R.W.G. van Willige, J.P.H. Linssen, M.B.J. Meinders, H.J. Van der Stege and A.G.J. Voragen, Food Addit. Contam., 19 (2002) 303. 13 R.W.G. van Willige, J.P.H. Linssen, A. Legger-Huysman and A.G.J. Voragen, Food Addit. Contam., 20 (2003) 84. 14 K. Umano and T. Shibamoto, J. Agric. Food Chem., 35 (1987) 14. 15 M. Horiuchi, K. Umano and T. Shibamoto, J. Agric. Food Chem., 46 (1998) 5232. 16 F.C. Silva, C.R. De Carvalho and Z.D.L. Cardeal, J. Chromatogr. Sci., 38 (2000) 315. 17 A.I. Andre´s, R. Cava and J. Ruiz, J. Chromatogr. A, 963 (2002) 83. 18 J.E. Biles, T.P. McNeal, T.H. Begley and H.C. Hollifield, J. Agric. Food Chem., 45 (1997) 3541. 19 J. Lo´pez-Cervantes, D.I. Sanchez-Machado, P. Paseiro-Losada and J. Simal-Lozano, Chromatographia, 58 (2003) 327. 20 J. Lo´pez-Cervantes and P. Paseiro-Losada, Food Addit. Contam., 20 (2003) 596. 21 E.M. Munguia-Lopez and H. Soto-Valdez, J. Agric. Food Chem., 49 (2001) 3666. 22 J.E. Biles, T.P. McNeal and T.H. Begley, J. Agric. Food Chem., 45 (1997) 4697. 23 S.R. Howe and L. Borodinsky, Food Addit. Contam., 15 (1998) 370. 24 Commission Directive EC/2007/19 of 2 April 2007 amending Directive 2002/72/EC relating to plastic materials and articles intended to come into contact with food and Council Directive
772
25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57
58 59 60 61
Catherine Simoneau
85/572/EEC laying down the list of simulants to be used for testing migration of constituents of plastic materials and articles intended to come into contact with foodstuffs. L. Castle, M. Sharman and J. Gilbert, J. Assoc. Off. Anal. Chem., 71 (1988) 1183. A. Fankhauser-Noti, K. Fiselier, S. Biedermann, M. Biedermann, K. Grob, F. Armellini, K. Rieger and I. Skjevrak, Eur. Food Res. Technol., 221 (2005) 416. M. Suman, S. La Tegola, D. Catellani and U. Bersellini, J. Agric. Food Chem., 53 (2005) 9879. J.H. Petersen, P. Togeskov, J. Hallas, M.B. Olsen, B. Jorgensen and M. Jakobsen, Pack. Technol. Sci., 17 (2004) 53. J.H. Petersen and T. Breindahl, Food Addit. Contam., 15 (1998) 600. J.H. Petersen, L. Lillemark and L. Lund, Food Addit. Contam., 14 (1997) 345. M. Sharman, W.A. Read, L. Castle and J. Gilbert, Food Addit. Contam., 11 (1994) 375. K. Fiselier, M. Biedermann and K. Grob, J. Sep. Sci., 28 (2005) 2144. M. Biedermann, K. Fiselier and K. Grob, J. Sep. Sci., 28 (2005) 1550. S. Biedermann-Brem, M. Biedermann, K. Fiselier and K. Grob, Food Addit. Contam., 22 (2005) 1274. M. Biedermann and K. Grob, Chromatographia, 64 (2006) 543. M. Biedermann and K. Grob, Pack. Technol. Sci., 19 (2006) 159. M. Biedermann and K. Grob, J. Sep. Sci., 29 (2006) 114. Z. Ezerskis, V. Morku¯nas, M. Suman and C. Simoneau, Anal. Chim. Acta., 604 (2007) 29. P.D. Zygoura, E.K. Paleologos, K.A. Riganakos and M.G. Kontominas, J. Chromatogr. A, 1093 (2005) 29. Y. Tsumura, S. Ishimitsu, A. Kaihara, K. Yoshii and Y. Tonogai, J. Health Sci., 48 (2002) 493. R.S. Garcı´a, A.S. Silva, I. Cooper, R. Franz and P.P. Losada, Trends Food Sci. Technol., 17 (2006) 354. L. Castle, S.M. Jickells, M. Sharman, J.W. Gramshaw and J. Gilbert, J. Food Prot., 51 (1988) 916. L. Castle, J. Gilbert, S.M. Jickells and J.W. Gramshaw, J. Chromatogr., 437 (1988) 281. P. Paseiro Losada, C. Pe´rez Lamela, M.F. Lo´pez Fabal, P. Fenollera and J. Simal Lozano, J. Agric. Food Chem., 45 (1997) 3493. P. Paseiro Losada, M. Lo´pez, O. Va´zquez, J. Simal Lozano and G. Simal, J. Assoc. Off. Anal. Chem., 74 (1991) 925. J. Simal-Gandara, S. Paz-Abuin, P. Paseiro-Losada and J. Simal-Lozano, J. Chromatogr. Sci., 31 (1993) 450. J. Simal Gandara, P. Lopez Mahia, P. Paseiro Losada, J. Simal Lozano and S. Paz Abuin, Food Addit. Contam., 10 (1993) 555. J.E. Biles, K.D. White, T.P. McNeal and T.H. Begley, Determination of the diglycidyl ether of bisphenol A and its derivatives in canned foods, J. Agric. Food Chem., 47 (1999) 1965. A. Theobald, C. Simoneau, P. Roncari, A. Roncari and E. Anklam, Dtsch. Lebensmitt. Rundsch., 95 (1999) 362. A. Theobald, C. Simoneau, P. Roncari, A. Roncari and E. Anklam, Dtsch. Lebensmitt. Rundsch., 95 (1999) 186. C. Simoneau, A. Theobald, P. Hannaert, P. Roncari, A. Roncari, T. Rudolph and E. Anklam, Food Addit. Contam., 16 (1999) 189. G. Morlock and W. Schwack, Anal. Bioanal. Chem., 385 (2006) 586. S. Papilloud and D. Baudraz, Prog. Org. Coat., 45 (2002) 231. G. Sagratini, J. Man˜es, D. Giardina and Y. Pico´, J. Agric. Food Chem., 54 (2006) 7947. C. Brede, I. Skjevrak and H. Herikstad, J. Chromatogr. A, 983 (2003) 35. S.K. Mortensen, X. Thorsager Trier, A. Foverskov and J.H. Petersen, J. Chromatogr. A, 1091 (2005) 40. Council Directive of 18 October 1982 laying down the basic rules necessary for testing migration of the constituents of plastic materials and articles intended to come into contact with foodstuffs, 82/711/EEC. C. Caner, R.J. Hernandez, M. Pascall, V.M. Balasubramaniam and B.R. Horte, Pack. Technol. Sci., 17 (2004) 139. M. Monteiro, C. Nerı´n, C. Rubio and F.G.R. Reyes, HRC-J. High Resolut. Chromatogr., 21(5) (1998) 317. J.D. Vargo and K.L. Olson, Anal. Chem., 57 (1985) 672. C. Wessling, T. Nielsen, A. Leufve´n and M. Gerstad, Food Addit. Contam., 15 (1998) 709.
Food Contact Materials
773
D. Marque, A. Feigenbaum, D. Dainelli and A.M. Riquet, Food Addit. Contam., 15 (1998) 831. K.A. Mountfort, J. Kelly, S.M. Jickells and L. Castle, Food Addit. Contam., 14 (1997) 737. Y.S. Lee, H.S. Shin, J.K. Han, M. Lee and J.R. Giacin, J. Sci. Food Agric., 84 (2004) 993. W. Summerfield and I. Cooper, Food Addit. Contam., 18 (2001) 77. L. Castle, A. Mayo and J. Gilbert, Food Addit. Contam., 7 (1990) 29. L. Hammarling, H. Gustavsson, K. Svensson, S. Karlsson and A. Oskarsson, Food Addit. Contam., 15 (1998) 203. 68 Anonymous, Epoxidised soya bean oil migration from plasticised gaskets, Food Surveillance Information Sheet, 1999. 69 L. Fantoni and C. Simoneau, Food Addit. Contam., 20 (2003) 1087. 70 A. Fankhauser-Noti, S. Biedermann-Brem and K. Grob, Eur. Food Res. Technol., 223 (2006) 447. 62 63 64 65 66 67
CHAPT ER
22 Non-Target Multi-Component Analytical Surveillance of Food Contact Materials Leon Coulier, Sander Koster, Bas Muilwijk, Leo van Stee, Ruud Peters, Esther Zondervan-van den Beuken, Rinus Rijk, Monique Rennen, Winfried Leeman, Geert Houben and William D. van Dongen
Contents
1. Introduction 2. Legislation on Food Contact Materials 2.1 Current status of legislation on food contact materials 2.2 Future developments in legislation on FCMs 3. Non-Target Analysis 3.1 Migration experiments 3.2 Sample work-up/pre-treatment 3.3 Separation of the migrants 3.4 Characterization and/or identification of migrating compounds 3.5 Quantification of migrating compounds 3.6 Evaluation of analytical data 4. Examples of Non-Target Analysis from the Recent Literature 4.1 Paper and board 4.2 Polymers 4.3 Cans 5. Safety Assessment of Migrants from FCM 5.1 TTC principle 5.2 Safety assessment of unlisted migrants 6. Conclusions and Future Trends References
Comprehensive Analytical Chemistry, Volume 51 ISSN: 0166-526X, DOI 10.1016/S0166-526X(08)00022-6
776 776 776 777 778 778 779 779 780 780 780 782 782 783 784 785 786 788 791 792
r 2008 Elsevier B.V. All rights reserved.
775
776
Leon Coulier et al.
1. INTRODUCTION To ensure that food does not contain unacceptable levels of migrants from food contact materials (FCMs), resulting in unwanted changes of the composition of the food, all kind of analytical tests are required to ensure whether food complies with the relevant legislation and, of course, in the first place, if it is safe to consume. In principle, two approaches of testing can be distinguished: conventional compliance testing which is a target analysis of migrants, based on knowledge of the composition of the FCM, and a non-target approach for the non-intentionally added substances (NIASs). The main difference between conventional compliance testing and non-target compliance testing is that in conventional compliance testing the investigation is focussed on the ingredients (monomers, additives, etc.) used to make the FCM and on how much of these ingredients are present and can potentially migrate to the food. In non-target compliance tests, all possible components that can migrate to the food are included (with the focus to components that were included in the polymer without the intention to be added, which are components like oligomers, by-products, reaction products, impurities, etc.). Though, non-target compounds may be toxic, analysing such compounds is often a search for the needle in a haystack. The name, non-target, is mostly synonym for unknown. Since millions of different molecules exist that may appear in food from several origins and each class of compound may require a different analysis strategy, it is, at present, almost impossible to obtain a full picture of the total composition of the non-target compounds, i.e., no analytical technique or strategy exists with which all possible components can be detected, identified and quantified. Grob [1] presented a good overview of all flaws involved in non-target analysis and showed that the human perception of healthy food is mainly focused on pesticides and environmental pollutants despite the fact that the amount of material migrating from food packaging into food may well be 100 times higher. However, progress in the detection of non-target compounds has been made in recent years and much more progress is required to ensure safe food. This chapter is focussed on the present non-targeted compliance testing strategies of FCM migrants and an overview of the legislation involved on FCMs, including an overview of recent literature. A novel concept to investigate the presence of potential toxic compounds and to rate their health relevance is based on the Threshold of Toxicological Concern (TTC) principle and will be discussed at the end of this chapter.
2. LEGISLATION ON FOOD CONTACT MATERIALS 2.1 Current status of legislation on food contact materials The basis of the European legislation on FCMs is the recently published Framework Regulation EC 1935/2004 [2]. Article 3 of this Framework Regulation
Non-Target Multi-Component Analytical Surveillance of Food Contact Materials
777
[2] states that producers of FCMs have to guarantee that their products do not endanger human health or bring about an unacceptable change in the composition of the foodstuff or a deterioration of the organoleptic characteristics. More specifically, plastic FCMs are currently regulated in Directive 2002/72/EC [3] as last amended by Directive 2007/19/EC [4]. This directive contains positive lists of substances that may be used in FCMs, albeit sometimes under certain restrictions. These substances can be monomers, starting materials or additives. For certain substances, specific migration limits (SML), based on their toxicological properties or the available toxicological data, are established. In some cases, a limit for the residual content (QM) is set, which relates to the maximum quantity (mg/kg) in a final article. In other cases, a maximum residual quantity per surface area (QMA, expressed as mg/6 dm2) is used as safety criteria. Restrictions expressed as QM and QMA are so-called worst-case restrictions as it assumes that 100% of the residual amount present in the FCM will migrate into the food. The QM and QMA restriction are mainly established when the substance is not stable in food or food simulants or when they are very difficult to determine in those media. For a limited number of substances, purity requirements have been published as well. To prevent migration of an unacceptable level of compounds from a FCM into the foodstuff, an overall migration limit (OML) of 60 mg/kg food is given. The SML, QMA and OML are based on chronic exposure and depart from the assumption that an adult person weighs 60 kg and consumes every day, during its lifetime, 1 kg of the food packaged in a material that contains or releases the substance of interest at the maximum level of the restriction. Another assumption is that 6 dm2 of packaging material is used to pack 1 kg of food. Compliance testing is currently being carried out for plastic FCMs that contain starting substances that are on the positive list. This includes verification of the composition of the packaging material to judge whether all starting substances, i.e., monomers and additives are on the positive list. If one or more substances have a SML, QM or QMA, the residual content of the specific substance in the packaging materials or the migration of the specific substance from the packaging material into food simulants is determined.
2.2 Future developments in legislation on FCMs Although FCMs are profoundly regulated, there is a constant need for fine-tuning of the current EU legislation on FCMs. In the last amendment to Directive 2002/ 72/EC (Directive 2007/19/EC) [4] some new issues are addressed, including introduction of the concept of the functional barrier, introduction of the fat (consumption) reduction factor and clarification of the declaration of compliance and obligation to have available supporting documents. Issues like threshold of regulation (ToR) and extension of the rules to plastic multi-material multi-layers may be regulated in subsequent amendments to the plastics Directive. Perhaps more important is the renewed attention to the assessment of unlisted substances migrating from the FCM into the food. In principle, this is already regulated in Article 3 of the Framework Regulation EC 1935/2004 [2],
778
Leon Coulier et al.
i.e., FCMs should not endanger human health. Unlisted substances include impurities in starting substances, reaction intermediates, decomposition products and reaction products. However, non-harmonized substances should not be excluded although they may be subject to national regulation or simple rely on a risk assessment of the plastic manufacturer. The idea behind the renewed attention to unlisted substances is, of course, enhancing consumer protection. A recent example of unlisted substances originating from packaging materials is the migration of semicarbazide formed as a decomposition product of azodicarbonamide used as a blowing agent for plastics [5] which use is now definitively prohibited by Directive 2007/19/EC [4]. Also the formation of chlorohydrins and cyclic reaction products from epoxidized soybean oil used as a stabilizer [6–8] has been reason for concern and as a result Regulation (EC) No 372/2007 [9] has been published. In these cases migrants from food packaging, with possible toxicological properties, were found in food although these substances were not intentionally added or used for the food packaging but were formed during preparation and/or use of the food packaging. These examples clearly show that compliance testing of authorized substances is useful but incomplete. For safe FCMs it is necessary to pay attention to the unlisted substances. This chapter provides an overview of analytical methodologies and concepts that are capable of addressing the issue of unlisted substances.
3. NON-TARGET ANALYSIS Besides the starting materials such as monomers and additives (target analysis) also impurities, oligomers, reaction and degradation products of monomers and additives have to be considered as compounds that may leak from the FCM (non-target analysis). Determination of non-target compounds promotes the development of new analytical strategies that are pragmatic and cost-efficient. A non-target analysis generally consists of the following steps, as also described by Feigenbaum et al. [10], that will be discussed in the following sections: (1) (2) (3) (4) (5) (6)
Migration experiment Sample work-up/pre-treatment Separation of the migrants Characterization and/or identification of migrated compounds Quantification of migrated compounds Evaluation of analytical data.
3.1 Migration experiments In migration experiments, migrants released from the FCM into food need to be analysed. Since food is a complex matrix and requires a high demand from the analytical chemist, food simulants are used instead. Commonly used food
Non-Target Multi-Component Analytical Surveillance of Food Contact Materials
779
simulants, depending on the physicochemical properties of the packed food, are water, 10% ethanol, olive oil and 3% acetic acid. These food simulants present a worst-case scenario for aqueous, alcoholic, fat-containing and acidic foodstuffs, respectively. Iso-octane and 95% ethanol are simulants alternatively used for olive oil as this is, with respect to the analysis, a troublesome liquid to work with. The food simulant is brought in contact with the food-contact-side of the packaging material for defined time and temperature to extract components which are able to migrate from the FCM. This process presents a worst-case scenario of the storage time and temperature the foodstuff may experience.
3.2 Sample work-up/pre-treatment After the sample has been in contact with the food simulant at elevated temperature for a give time, the simulant is evaporated if necessary, to preconcentrate the extracted migrants. This depends on the analytical procedure followed and detection limits of the instrumentation. For many classes of compounds that can migrate from the packing material, derivatization strategies are required as the commonly used separation and detection systems in analytical chemistry may not be specific enough. Additionally, the liquid matrix may need to be modified (e.g., buffered solution for LC analysis). Special care needs to be taken when working with volatile compounds, which may be released from the system during each of the pre-treatment steps performed. Similarly, compounds may react (e.g., oxidize) or contaminants may enter the simulant from the laboratory environment. Of course, the ideal chemical analysis is the one where a pre-treatment is obsolete. This is unfortunately not very common as the current state-of-the-art of the analytical instruments are not capable of handling the complexity of the untreated samples.
3.3 Separation of the migrants Separation of a mixture of migrants is challenging especially when the composition and identity of the migrants is unknown, as is the case in nontarget analysis. Frequently, a combination of headspace gas chromatography (GC), liquid chromatography (LC) and inductively coupled plasma (ICP)/atomic absorption spectrometry (AAS) is used. These techniques cover volatile/nonvolatile, polar/non-polar and organic/inorganic compounds. Depending on the packing material, the number of migrants released can be too large to be sufficiently separated in a single chromatographic run. For such examples, two-dimensional separation techniques such as GC GC and LC LC can be considered. In conventional one-dimensional chromatography, the separation is based on one mechanism, e.g., the volatility of the compounds. In two-dimensional chromatography, the compounds are separated on volatility in the first dimension followed by an additional separation on, e.g., polarity in the second dimension. This increases the separation efficiency considerably. An overview of GC GC [11–14] and LC LC [15] can be found elsewhere.
780
Leon Coulier et al.
3.4 Characterization and/or identification of migrating compounds Mass spectrometry (MS) is one of the most commonly used detection techniques to obtain structural information of migrants. In combination with GC, mostly electron ionization (EI) is used to fragment the molecules eluting from the GC column, which can be considered as a fingerprinting technique for molecules. The molecular mass of the migrants can be obtained by using chemical ionization (CI) instead of EI. Coupling MS with LC requires a different approach. The mobile phase eluting from the column can often be directly nebulized and guided to the mass spectrometer inlet. Before entering the mass spectrometer, ionization is performed in a gentle manner using electrospray ionization (ESI) [16,17], atmospheric pressure chemical ionization (APCI) [18] or atmospheric pressure photoionization (APPI) [19]. Mainly intact molecules are generated of which the elemental composition of the molecule can be deduced when using a highresolution mass spectrometer, such as a Fourier transform mass spectrometer [20] or an orbitrap [21]. The elemental composition can give hints about the molecular structure for especially small molecules. However, frequently an additional fragmentation experiment, using, e.g., collisionally activated dissociation (CAD), leads to the formation of structure-specific fragments required to deduce the molecular structure [22].
3.5 Quantification of migrating compounds Quantification of migrants is easily performed when the pure compound that can be used as a calibration standard is available. Such a standard is unfortunately expensive or not commercially available for many compounds. For those cases, a compound that has close chemical/physical properties compared to the compound of interest is chosen. The main problem following this approach is that the intensity of the peak in a mass spectrum strongly depends on structural features of the molecule, the so-called ionization efficiency. Therefore, a calibration standard should be chosen that is structurally similar enough to avoid differences in the ionization efficiency.
3.6 Evaluation of analytical data The concentration of the migrant in the extract, matrix composition and the detection limit of the instrument used, determines whether the migrant is detected. If a component is not visibly present in the chromatograms it cannot be further addressed. However, this does not mean that the component is not of toxicological relevance. The toxicological properties of a specific compound and the extent of its consumption via food determine what concentration is acceptable in the migration extract, using the assumptions made in food contact legislation. As a result the acceptable concentration of specific compounds in migration extracts might differ by orders of magnitude. Therefore, analytical methods should be sensitive enough to detect the most toxic compounds above
Non-Target Multi-Component Analytical Surveillance of Food Contact Materials
781
certain toxicological thresholds. An example of such a threshold is the ToR of 1.5 mg/day as proposed by Begley [23]. This means that every compound is allowed if the consumption does not exceed 1.5 mg/person/day, provided that the substance migrating is not a potential genotoxic carcinogen. At first instance this seems an adequate rule of thumb for the screening of migrants. However, using the current assumptions in EU Directive 2002/72/EC [24] this means that 1.5 mg/day corresponds to 1.5 mg/kg food ¼ 1.5 mg/6 dm2 packaging. Assuming standard migration conditions of 2.34 dm2 packaging in contact with 100 mL simulant, this would result in a concentration of 1.5/62.34/100 ¼ 0.00585 mg/mL ¼ 5.85 ng/mL. Hence a detection limit of 5.85 ng/mL is necessary to meet the ToR. For most components this is not feasible using the analytical techniques discussed earlier. Possible solutions to this problem are concentration of the migration extract, e.g., by evaporation, also as discussed earlier. It should be noted that a concentration by at least a factor of 10–100 is necessary for the majority of components. Another option might be to apply actual exposure data to focus on compounds which might be present in the FCM migrant and toxicity data to focus on compounds which have potential toxicological relevance. This is explained in some more detail in a later section. At this moment, no analytical technique or strategy exists by which all possible components can be detected, identified and quantified at (toxicologically) relevant concentrations. Despite this, the current status of analytical techniques is able to at least give an indication of the presence of migrants in food simulants. Figure 1 shows a commonly used procedure to determine migrating compounds from FCMs. The procedure covers analytes with different polarities, volatility and molecular weight.
Packaging material
Migration extract/ mild extract
SEC Fraction