Environmental and Agricultural Informatics: Concepts, Methodologies, Tools, and Applications 2019006765, 9781522596219, 9781522596226

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Environmental and Agricultural Informatics: Concepts, Methodologies, Tools, and Applications Information Resources Management Association USA

Published in the United States of America by IGI Global Engineering Science Reference (an imprint of IGI Global) 701 E. Chocolate Avenue Hershey PA, USA 17033 Tel: 717-533-8845 Fax: 717-533-8661 E-mail: [email protected] Web site: http://www.igi-global.com Copyright © 2020 by IGI Global. All rights reserved. No part of this publication may be reproduced, stored or distributed in any form or by any means, electronic or mechanical, including photocopying, without written permission from the publisher. Product or company names used in this set are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark. Library of Congress Cataloging-in-Publication Data Names: Information Resources Management Association, editor. Title: Environmental and agricultural informatics : concepts, methodologies, tools, and applications / Information Resources Management Association, editor. Description: Hershey, PA : Engineering Science Reference, an imprint of IGI Global, [2020] | Includes bibliographical references and index. | Summary: “This book examines the design, development, and implementation of complex agricultural and environmental information systems to quickly process and access environmental data in order to make informed decisions for the protection of the environment”-- Provided by publisher. Identifiers: LCCN 2019006765 | ISBN 9781522596219 (hardcover) | ISBN 9781522596226 (ebook) Subjects: LCSH: Environmental sciences--Data processing. | Environmental monitoring. | Agricultural informatics. Classification: LCC GE45.D37 E5384 2020 | DDC 333.70285--dc23 LC record available at https://lccn.loc.gov/2019006765 British Cataloguing in Publication Data A Cataloguing in Publication record for this book is available from the British Library. The views expressed in this book are those of the authors, but not necessarily of the publisher. For electronic access to this publication, please contact: [email protected].

Editor-in-Chief Mehdi Khosrow-Pour, DBA Information Resources Management Association, USA

Associate Editors Steve Clarke, University of Hull, UK Murray E. Jennex, San Diego State University, USA Ari-Veikko Anttiroiko, University of Tampere, Finland

Editorial Advisory Board Sherif Kamel, American University in Cairo, Egypt In Lee, Western Illinois University, USA Jerzy Kisielnicki, Warsaw University, Poland Amar Gupta, Arizona University, USA Craig van Slyke, University of Central Florida, USA John Wang, Montclair State University, USA Vishanth Weerakkody, Brunel University, UK



List of Contributors

Abbott, Eric / Iowa State University, USA......................................................................................... 716 Aderibigbe, Adekunle / Obafemi Awolowo University, Nigeria....................................................... 405 Adesoji, S. A. / Obafemi Awolowo University, Nigeria....................................................................... 133 Adewojo, Akinade Adebowale / Nigerian Stored Products Research Institute, Nigeria................. 1418 Adnan, Nadia / Universiti Teknologi Petronas, Malaysia............................................................... 1623 Ahmad, Noor Hazlina / Universiti Sains Malaysia, Malaysia........................................................... 157 Akande, Femi Titus / Librarian, Nigeria......................................................................................... 1418 Akroush, Samia Nadeem / National Center for Agricultural Research and Extension, Jordan..... 1709 Alarcon, Vladimir J. / Universidad Diego Portales, Chile.............................................................. 1469 Alecu, Alexandra / Petroleum-Gas University of Ploiesti, Romania................................................ 967 Alexandri, Cecilia / Institute of Agricultural Economics, Romania.................................................. 792 Anastasiadis, Foivos / Aristotle University of Thessaloniki, Greece................................................. 485 Antonaras, Alexandros / University of Nicosia, Cyprus................................................................... 258 Areendran, G. / WWF, India........................................................................................................... 1605 Arora, Rakhi / Jaipur National University, India........................................................................... 1335 Asoğlu, Veysel / Harran Unıversıty, Turkey......................................................................................... 17 Aw-Hassan, Aden / International Center for Agricultural Research in Dry Area, Jordan............. 1709 Ay, Sema / Uludag University, Turkey............................................................................................. 1649 Bakshi, Bhavik R. / The Ohio State University, USA......................................................................... 536 Bansode, Sheelratan S. / Solapur University, India........................................................................... 347 Bebeley, Jenneh F. / Sierra Leone Agricultural Research Institute, Sierra Leone............................. 855 Bekele, Frances / The University of the West Indies – St. Augustine, Trinidad and Tobago........... 1299 Bekele, Isaac / The University of the West Indies – St. Augustine, Trinidad and Tobago................ 1299 Bello, Julia / University of Illinois at Urbana-Champaign, USA....................................................... 716 Besalti, Metin / University of South Florida, USA............................................................................ 991 Bett, Bernard / International Livestock Research Institute, Kenya................................................. 1496 Bhaskar, Avantika / Care Earth Trust, India.................................................................................. 1536 Borràs, Susana / Rovira i Virgili University, Spain............................................................................. 38 Buyya, Rajkumar / University of Melbourne, Australia................................................................... 438 Caraiani, Chirața / Bucharest University of Economic Studies, Romania....................................... 562 Chachra, Kartik / Institute of Management Technology Ghaziabad, India........................................ 66 Chakraborty, Anusheema / TERI University, India......................................................................... 805 Chana, Inderveer / Thapar University, India.................................................................................... 438 Chelcea, Silvia / National Institute of Hydrology and Water Management, Romania...................... 590 Clouse, Carey / University of Massachusetts – Amherst, USA.......................................................... 388  



Coats, Cala / Stephen F. Austin State University, USA.................................................................... 1233 Colceag, Florian / Bucharest University of Economic Studies, Romania.......................................... 562 Confalonieri, Ulisses / René Rachou Research Center - Oswaldo Cruz Foundation, Brazil.......... 1395 Dascălu, Cornelia / Bucharest University of Economic Studies, Romania....................................... 562 Deshmukt, Preeti / Vasandada Sugar Institute, India..................................................................... 1040 Dhar, Anil / Regional Sericulture Research Station, Jammu, India.................................................. 687 Dhehibi, Boubaker / International Center for Agricultural Research in Dry Area, Jordan........... 1709 Dissanayeke, Uvasara / University of Peradeniya, Sri Lanka........................................................... 829 Doleček, Vlatko / Academy of Sciences and Arts, Bosnia and Herzegovina..................................... 630 Dua, V. K. / Central Potato Research Institute, India....................................................................... 1482 Ele, Ideba / University of Calabar, Nigeria..................................................................................... 1358 Essien, Essien D. / University of Uyo, Nigeria................................................................................. 1589 Famuyiwa, B. S. / Cocoa Research Institute of Nigeria (CRIN), Nigeria.......................................... 133 Feldman, Allan / University of South Florida, USA.......................................................................... 991 Furtado, André Tosi / University of Campinas, Brazil.................................................................... 1216 Garg, Shivani / Kurukshetra University, India................................................................................ 1517 Gboku, Matthew L. S. / Sierra Leone Agricultural Research Institute, Sierra Leone....................... 855 Ghafoor, Abdul / University of Agriculture Faisalabad, Pakistan.................................................. 1181 Ghanshyam, Chirravoori / CSIR-Central Scientific Instruments Organisation, India...................... 79 Gill, Sukhpal Singh / University of Melbourne, Australia................................................................. 438 Govindakrishnan, P. M. / Central Potato Research Institute, India................................................ 1482 Grace, Delia / International Livestock Research Institute, Kenya................................................... 1496 Halim, Hasliza Abdul / Universiti Sains Malaysia, Malaysia........................................................... 157 Hammas, Lamine / University of Sousse, Tunisia................................................................................. 1 Haug, Ruth / Norwegian University of Life Sciences (NMBU), Norway........................................... 661 Hiremath, Rahul / SCMHRD, Symbiosis International University, India........................................ 347 Hrestic, Maria Luiza / Valahia University of Târgovişte, Romania.................................................. 108 Inogwabini, Bila-Isia / Saint Pierre Canisius Institute of Agriculture and Veterinary Sciences (ISAV), Congo & Swedish University of Agricultural Sciences, Sweden..................................... 1452 Ionita, Monica / Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Germany........................................................................................................................................ 590 Ishaq, Muhammad / Pakistan Agricultural Research Council, Pakistan....................................... 1287 Ismyrlis, Vasileios / Greek Statistical Authority, Greece................................................................. 1127 Jain, Ankush / Institute of Management Technology Ghaziabad, India.............................................. 66 Jain, Anshul / Institute of Management Technology Ghaziabad, India............................................... 66 Jain, Lokesh / UIET, Panjab University, India.................................................................................. 516 Jain, Saloni / National Law University Delhi, India........................................................................ 1378 Jatav, M. K. / Central Institute for Arid Horticulture, India............................................................ 1482 Jean-Vasile, Andrei / Petroleum-Gas University of Ploiesti, Romania............................................. 967 Joshi, P K / Jawaharlal Nehru University, India................................................................................ 805 Joshi, Rohit / IIM Shillong, India.................................................................................................... 1570 Joshi, Sudhanshu / Doon University, India..................................................................................... 1570 Kaphaliya, Bhumija / Kurukshetra University, India..................................................................... 1724 Karabegović, Isak / University of Bihać, Bosnia and Herzegovina.................................................. 630 Kasemsap, Kijpokin / Suan Sunandha Rajabhat University, Thailand.......................................... 1669 Keser, Hilal Yildirir / Uludag University, Turkey............................................................................ 1649



Khaled, Rachida / University of Sousse, Tunisia........................................................................... 1, 316 Khan, Khalid / Higher Education Department Peshawar, Pakistan............................................... 1287 Khan, Zia Ullah / University of Swabi, Pakistan.............................................................................. 1287 Kiberiti, Boaz Stanslaus / Sokoine University of Agriculture, Tanzania........................................... 661 Kittilaksanawong, Wiboon / Saitama University, Japan................................................................ 1556 Kljajić, Nataša Ž. / Institute of Agricultural Economics, Serbia........................................................ 925 Kocadağlı, Aylin Yaman / Istanbul University, Turkey.................................................................... 1013 Kostopoulos, Alexandros / CSR Hellas, Greece............................................................................... 258 Kumar, Bimlesh / Indian Institute of Technology Guwahati, India.................................................. 347 Kumar, Harish / UIET, Panjab University, India.............................................................................. 516 Kumar, Mousumi / Aghorekamini Prakashchandra Mahavidyalaya, India..................................... 737 Kumar, Rajesh / Sharda University, India...................................................................................... 1605 Kurşun, Berrin / Marmara University, Turkey................................................................................. 536 Lindahl, Johanna / Swedish University of Agricultural Sciences, Sweden & International Livestock Research Institute, Kenya............................................................................................ 1496 Londhe, Sunil / World Agroforestry Centre (ICRAF), India........................................................... 1258 Luca, Lucian / Institute of Agricultural Economics, Romania.......................................................... 792 Lungu, Camelia I. / Bucharest University of Economic Studies, Romania........................................ 562 Lutomia, Anne Namatsi / University of Illinois at Urbana-Champaign, USA.................................. 716 Mabe, L. K. / North-West University – Mafikeng, South Africa......................................................... 182 Mamatha, D. M. / Sri Padmavathi Mahila Visvavidyalayam (Women’s University), India............... 366 Mamta / Jiwaji University, India........................................................................................................ 687 Manjunath Aradhya, V N / Sri Jayachamarajendra College of Engineering, India...................... 1078 Margonari, Carina / René Rachou Research Center - Oswaldo Cruz Foundation, Brazil............. 1395 Mattas, Konstadinos / Aristotle University of Thessaloniki, Greece................................................ 485 Mayer, Christina / Statistics Austria, Austria................................................................................... 875 Mazur, Robert / Iowa State University, USA..................................................................................... 716 Meehan, Kevin / University of Central Florida, USA..................................................................... 1053 Menezes, Júlia Alves / René Rachou Research Center – Oswaldo Cruz Foundation, Brazil........... 1395 Merdikawati, Nurina / National University of Singapore, Singapore............................................ 1146 Mlozi, Malongo R.S. / Sokoine University of Agriculture, Tanzania................................................. 661 Mocumbe, Sostino / Iowa State University, USA.............................................................................. 716 Modise, Oitshepile M. / University of Botswana, Botswana.............................................................. 855 Moharana, P. C. / National Bureau of Soil Survey and Land Use Planning, India......................... 1040 Moschidis, Odysseas / University of Macedonia, Greece............................................................... 1127 Mugwisi, Tinashe / University of South Africa, South Africa......................................................... 1106 Mukhopadhyay, Partha / National Institute of Technology Durgapur, India................................. 1163 Murali, J. / Environmental Solutions and Consultancy, UAE........................................................... 347 Murtaza, Ghulam / University of Agriculture Faisalabad, Pakistan.............................................. 1181 Musafiri, Ildephonse / University of Rwanda, Rwanda.................................................................... 618 Mussa, Mussa / Sokoine University of Agriculture, Tanzania........................................................... 661 Naitam, Ravindra Kashinath / National Bureau of Soil Survey and Land Use Planning, India............................................................................................................................................ 1040 Naraine, Leighton / Clarence Fitzroy Bryant College, Saint Kitts and Nevis................................. 1053 Nation, Molly / University of South Florida, USA............................................................................. 991 Naveed, Muhammad / University of Agriculture Faisalabad, Pakistan......................................... 1181



Nikolaou, Kallirroi / Aristotle University of Thessaloniki, Greece................................................... 485 Niranjan, S K / Sri Jayachamarajendra College of Engineering, India.......................................... 1078 Noor, Amir Noor / London Metropolitan University, UK................................................................ 1623 Nordin, Shahrina Md / Universiti Teknologi Petronas, Malaysia................................................... 1623 Nulkar, Gurudas / SCMHRD, Symbiosis International University, India & Trustee Ecological Society, India................................................................................................................................. 347 Ogbeide, Osadebamwen Anthony / Agribusiness Services, Australia............................................ 1358 Okegbile, Samuel Dayo / Obafemi Awolowo University, Nigeria...................................................... 405 Oladele, O. I. / North-West University – Mafikeng, South Africa....................................................... 182 Olaniyi, O. A. / Ladoke Akintola University of Technology, Nigeria................................................. 133 Oluwaranti, Adeniran Ishola / Obafemi Awolowo University, Nigeria............................................ 405 Ortner, Karl Michael / Federal Institute of Agricultural Economics, Austria................................... 875 Pal, Bijay Baran / University of Kalyani, India.................................................................................. 737 Paliwal, Rashmi / Kurukshetra University, India............................................................................ 1724 Patel, Manoj Kumar / Academy of Scientific and Innovative Research, India & CSIR-Central Scientific Instruments Organisation, India...................................................................................... 79 Patil, Sharmila S. / Walchand Institute of Technology, India............................................................. 347 Pǎuna, Bianca / National Institute of Economic Research, Romania................................................ 792 Pittendrigh, Barry R. / Michigan State University, USA................................................................... 716 Popescu, Constanţa / Valahia University of Târgovişte, Romania.................................................... 108 Popescu, Constantin / Valahia University of Târgovişte, Romania.................................................. 108 Popović, Vesna Ž. / Institute of Agricultural Economics, Serbia........................................................ 925 Prasad, Shitala / GREYC – Imaging Lab, CNRS, France................................................................. 773 Quendler, Erika / Federal Institute of Agricultural Economics, Austria.......................................... 875 Raghupathi, Viju / Brooklyn College (CUNY), USA........................................................................ 906 Raghupathi, Wullianallur / Fordham University, USA.................................................................... 906 Rajan, Ramkishen S. / George Mason University, USA.................................................................. 1146 Raju, P. J. / Andhra Pradesh State Sericulture Research and Development Institute, India.............. 366 Ramachandran, Nira / Independent Researcher, India.................................................................. 1688 Ramteke, Indal K. / Maharashtra Remote Sensing Applications Centre, India.............................. 1040 Rao, G. Babu / Care Earth Trust, India............................................................................................ 1536 Rao, Prakash / Symbiosis International University, India.............................................................. 1605 Rao, Rayavarapu Jaganadha / Jiwaji University, India.................................................................... 687 Rao, Roopesh / Shri Ramdeobaba College of Engineering and Management, India...................... 1199 Robinson, Timothy / International Livestock Research Institute, Kenya........................................ 1496 Roy, Sankhajit / Bidhan Chandra Krishi Viswavidyalaya, India...................................................... 737 Ruch, Cathleen Brandi / Lake Region State College, USA............................................................... 298 S, Siddesha / Sri Jayachamarajendra College of Engineering, India.............................................. 1078 Saifullah / University of Dammam, Saudi Arabia............................................................................. 1181 Sanga, Camilius Aloyce / Sokoine University of Agriculture, Tanzania............................................ 661 Saqib, Muhammad / University of Agriculture Faisalabad, Pakistan............................................ 1181 Saravanan, Raj / National Institute of Agricultural Extension Management (MANAGE), India...... 462 Sarkar, Mayukh / Institute of Management Technology Ghaziabad, India........................................ 66 Sassenrath, Gretchen F. / Kansas State University, USA................................................................ 1469 Seelam, Gowtham / Institute of Management Technology Ghaziabad, India..................................... 66 Şengün, Halil İbrahim / Dicle University, Turkey............................................................................... 17



Sengupta, Partha Pratim / National Institute of Technology Durgapur, India............................... 1163 Seshagiri, S. V. / Andhra Pradesh State Sericulture Research and Development Institute, India...... 366 Sharma, R. K. / Banaras Hindu University, India........................................................................... 1724 Sharma, R. P. / National Bureau of Soil Survey and Land Use Planning, India............................. 1482 Sidibe, Hamadoun / Université de Moncton, Canada....................................................................... 233 Simbeye, Daudi Samson / Dar es Salaam Institute of Technology, Tanzania.................................... 332 Simonovic, Zoran / Institute of Agricultural Economics, Serbia...................................................... 948 Singh, Harshit / Institute of Management Technology Ghaziabad, India........................................... 66 Singh, R. S. / National Bureau of Soil Survey and Land Use Planning, India................................. 1040 Singh, S. K. / National Bureau of Soil Survey and Land Use Planning, India................................. 1040 Sinha, Madhabendra / National Institute of Technology Durgapur, India..................................... 1163 Smith, Glenn Gordon / University of South Florida, USA................................................................ 991 Subić, Jonel V. / Institute of Agricultural Economics, Serbia............................................................ 925 Suchiradipta, Bhattacharjee / Independent Researcher, India........................................................ 462 Sukhwani, Khushboo / National Law University Delhi, India....................................................... 1378 Sun, Jun / Dalian Polytechnic University, China.............................................................................. 419 Tan, Khee Giap / National University of Singapore, Singapore...................................................... 1146 Tladi, Flora M. / University of Botswana, Botswana......................................................................... 282 Tsakiridou, Efthimia / Aristotle University of Thessaloniki, Greece................................................ 485 Tumbo, S. D. / Centre for Agric. Mechanization and Rural Technologies, Tanzania......................... 661 ul Haq, Zahoor / Abdul Wali Khan University Mardan, Pakistan.................................................. 1287 Uniyal, Shivani / Banaras Hindu University, India......................................................................... 1724 Vencatesan, Jayshree / Care Earth Trust, India.............................................................................. 1536 Vukovic, Predrag / Institute of Agricultural Economics, Serbia....................................................... 948 Wahid, Fazli / University of Waterloo, Canada............................................................................... 1287 Wani, Khursheed Ahmad / ITM University Gwalior, India.............................................................. 687 Wickramasuriya, H.V.A. / University of Peradeniya, Sri Lanka...................................................... 829 Xing, Ruben / Montclair State University, USA................................................................................ 419 Yusoff, Asliza / Universiti Sains Malaysia, Malaysia........................................................................ 157 Zia-ur-Rehman, Muhammad / University of Agriculture Faisalabad, Pakistan........................... 1181

Table of Contents

Preface.................................................................................................................................................. xxi

Volume I Section 1 Fundamental Concepts and Theories Chapter 1 Technological Innovation and the Agricultural Sustainability: What Compatibility for the Mechanization?........................................................................................................................................ 1 Rachida Khaled, University of Sousse, Tunisia Lamine Hammas, University of Sousse, Tunisia Chapter 2 Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey......................... 17 Veysel Asoğlu, Harran Unıversıty, Turkey Halil İbrahim Şengün, Dicle University, Turkey Chapter 3 Rights of Nature to Protect Human Rights in Times of Environmental Crisis...................................... 38 Susana Borràs, Rovira i Virgili University, Spain Chapter 4 The Impact of Kisan Call Centers on the Farming Sector..................................................................... 66 Kartik Chachra, Institute of Management Technology Ghaziabad, India Gowtham Seelam, Institute of Management Technology Ghaziabad, India Harshit Singh, Institute of Management Technology Ghaziabad, India Mayukh Sarkar, Institute of Management Technology Ghaziabad, India Anshul Jain, Institute of Management Technology Ghaziabad, India Ankush Jain, Institute of Management Technology Ghaziabad, India Chapter 5 Fundamentals of Electrostatic Spraying: Basic Concepts and Engineering Practices........................... 79 Manoj Kumar Patel, Academy of Scientific and Innovative Research, India & CSIR-Central Scientific Instruments Organisation, India Chirravoori Ghanshyam, CSIR-Central Scientific Instruments Organisation, India 



Chapter 6 Aggressions of the Socio-Economic System on the Natural Capital................................................... 108 Constanţa Popescu, Valahia University of Târgovişte, Romania Constantin Popescu, Valahia University of Târgovişte, Romania Maria Luiza Hrestic, Valahia University of Târgovişte, Romania Section 2 Development and Design Methodologies Chapter 7 Appropriate Extension Methodologies for Agricultural Development in Emerging Economies........ 133 B. S. Famuyiwa, Cocoa Research Institute of Nigeria (CRIN), Nigeria O. A. Olaniyi, Ladoke Akintola University of Technology, Nigeria S. A. Adesoji, Obafemi Awolowo University, Nigeria Chapter 8 Agropreneurship Among Gen Y in Malaysia: The Role of Academic Institutions............................. 157 Asliza Yusoff, Universiti Sains Malaysia, Malaysia Noor Hazlina Ahmad, Universiti Sains Malaysia, Malaysia Hasliza Abdul Halim, Universiti Sains Malaysia, Malaysia Chapter 9 Application of Information Communication Technologies for Agricultural Development Through Extension Services: A Review............................................................................................................. 182 L. K. Mabe, North-West University – Mafikeng, South Africa O. I. Oladele, North-West University – Mafikeng, South Africa Chapter 10 Strategic Positioning of Turkey Agricultural Products on the Agricultural World Market................. 233 Hamadoun Sidibe, Université de Moncton, Canada Chapter 11 Stakeholder Agriculture: Innovation From Farm to Store................................................................... 258 Alexandros Antonaras, University of Nicosia, Cyprus Alexandros Kostopoulos, CSR Hellas, Greece Chapter 12 Striking a Perfect Fit in Leadership Style for Effective Farmer Training in Botswana....................... 282 Flora M. Tladi, University of Botswana, Botswana Chapter 13 Rebirth of a Program via Community, Industry, and Philanthropic Support...................................... 298 Cathleen Brandi Ruch, Lake Region State College, USA



Chapter 14 Impact on Agricultural Sustainability of Maghreb Countries: An Empirical Analysis by 3SLS........ 316 Rachida Khaled, University of Sousse, Tunisia Chapter 15 Deployment of Wireless Sensor Networks for Soil Macronutrients Measurements in Farms............ 332 Daudi Samson Simbeye, Dar es Salaam Institute of Technology, Tanzania Chapter 16 Industrial Wastewater Management in the Context of Climate Change Adaptation in Selected Cities of India: A Business Approach.................................................................................................. 347 Rahul Hiremath, SCMHRD, Symbiosis International University, India Bimlesh Kumar, Indian Institute of Technology Guwahati, India Sheelratan S. Bansode, Solapur University, India Gurudas Nulkar, SCMHRD, Symbiosis International University, India & Trustee Ecological Society, India Sharmila S. Patil, Walchand Institute of Technology, India J. Murali, Environmental Solutions and Consultancy, UAE Chapter 17 Sericulture Industry: A Bonanza to Strengthen Rural Population in India.......................................... 366 P. J. Raju, Andhra Pradesh State Sericulture Research and Development Institute, India D. M. Mamatha, Sri Padmavathi Mahila Visvavidyalayam (Women’s University), India S. V. Seshagiri, Andhra Pradesh State Sericulture Research and Development Institute, India Chapter 18 Design for Autonomy: Water Resources in Ladakh............................................................................. 388 Carey Clouse, University of Massachusetts – Amherst, USA Section 3 Tools and Technologies Chapter 19 Web Based Automatic Soil Chemical Contents Monitoring System................................................... 405 Samuel Dayo Okegbile, Obafemi Awolowo University, Nigeria Adeniran Ishola Oluwaranti, Obafemi Awolowo University, Nigeria Adekunle Aderibigbe, Obafemi Awolowo University, Nigeria Chapter 20 The Empirical Study on the Evolutionary Game Based Agricultural Products Supply Chain............ 419 Jun Sun, Dalian Polytechnic University, China Ruben Xing, Montclair State University, USA



Chapter 21 IoT Based Agriculture as a Cloud and Big Data Service: The Beginning of Digital India................. 438 Sukhpal Singh Gill, University of Melbourne, Australia Inderveer Chana, Thapar University, India Rajkumar Buyya, University of Melbourne, Australia Chapter 22 ICTs for Agricultural Development and Food Security in Developing Nations.................................. 462 Bhattacharjee Suchiradipta, Independent Researcher, India Raj Saravanan, National Institute of Agricultural Extension Management (MANAGE), India Chapter 23 Exploring Alternative Distribution Channels of Agricultural Products.............................................. 485 Kallirroi Nikolaou, Aristotle University of Thessaloniki, Greece Efthimia Tsakiridou, Aristotle University of Thessaloniki, Greece Foivos Anastasiadis, Aristotle University of Thessaloniki, Greece Konstadinos Mattas, Aristotle University of Thessaloniki, Greece Chapter 24 Mobile Networks and Indian Agricultural Sector................................................................................ 516 Lokesh Jain, UIET, Panjab University, India Harish Kumar, UIET, Panjab University, India Chapter 25 Sustainability Assessment in a Geographical Region and of the Activities Performed...................... 536 Berrin Kurşun, Marmara University, Turkey Bhavik R. Bakshi, The Ohio State University, USA

Volume II Chapter 26 Environmental Audit in Integrated Audit System................................................................................ 562 Chirața Caraiani, Bucharest University of Economic Studies, Romania Camelia I. Lungu, Bucharest University of Economic Studies, Romania Cornelia Dascălu, Bucharest University of Economic Studies, Romania Florian Colceag, Bucharest University of Economic Studies, Romania Chapter 27 Spatio-Temporal Variability of Seasonal Drought Over the Dobrogea Region................................... 590 Monica Ionita, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Germany Silvia Chelcea, National Institute of Hydrology and Water Management, Romania



Chapter 28 The Role of Mobile Phones Use on Agricultural Output and Household Income in Rural  Rwanda................................................................................................................................................ 618 Ildephonse Musafiri, University of Rwanda, Rwanda Chapter 29 Mobile Robotics................................................................................................................................... 630 Isak Karabegović, University of Bihać, Bosnia and Herzegovina Vlatko Doleček, Academy of Sciences and Arts, Bosnia and Herzegovina Chapter 30 Farmers’ Access and Use of Mobile Phones for Improving the Coverage of Agricultural Extension Service: A Case of Kilosa District, Tanzania..................................................................... 661 Boaz Stanslaus Kiberiti, Sokoine University of Agriculture, Tanzania Camilius Aloyce Sanga, Sokoine University of Agriculture, Tanzania Mussa Mussa, Sokoine University of Agriculture, Tanzania S. D. Tumbo, Centre for Agric. Mechanization and Rural Technologies, Tanzania Malongo R.S. Mlozi, Sokoine University of Agriculture, Tanzania Ruth Haug, Norwegian University of Life Sciences (NMBU), Norway Chapter 31 Biological Alchemy: Gold From Garbage or Garbage Into Gold........................................................ 687 Mamta, Jiwaji University, India Rayavarapu Jaganadha Rao, Jiwaji University, India Anil Dhar, Regional Sericulture Research Station, Jammu, India Khursheed Ahmad Wani, ITM University Gwalior, India Chapter 32 Making Agricultural Learning Accessible: Examining Gender in the Use of Animations via Mobile Phones..................................................................................................................................... 716 Julia Bello, University of Illinois at Urbana-Champaign, USA Anne Namatsi Lutomia, University of Illinois at Urbana-Champaign, USA Eric Abbott, Iowa State University, USA Robert Mazur, Iowa State University, USA Sostino Mocumbe, Iowa State University, USA Barry R. Pittendrigh, Michigan State University, USA Chapter 33 A Genetic Algorithm to Goal Programming Model for Crop Production With Interval Data Uncertainty........................................................................................................................................... 737 Bijay Baran Pal, University of Kalyani, India Sankhajit Roy, Bidhan Chandra Krishi Viswavidyalaya, India Mousumi Kumar, Aghorekamini Prakashchandra Mahavidyalaya, India



Chapter 34 Mobile Vision for Plant Biometric System.......................................................................................... 773 Shitala Prasad, GREYC – Imaging Lab, CNRS, France Chapter 35 Demand for Food Diversity in Romania.............................................................................................. 792 Lucian Luca, Institute of Agricultural Economics, Romania Cecilia Alexandri, Institute of Agricultural Economics, Romania Bianca Pǎuna, National Institute of Economic Research, Romania Chapter 36 Simulation-Based Approaches for Ecological Niche Modelling: A Geospatial Reference................. 805 Anusheema Chakraborty, TERI University, India P K Joshi, Jawaharlal Nehru University, India Section 4 Utilization and Applications Chapter 37 Information Societies to Interactive Societies: ICT Adoptions in the Agriculture Sector in Sri Lanka................................................................................................................................................... 829 Uvasara Dissanayeke, University of Peradeniya, Sri Lanka H.V.A. Wickramasuriya, University of Peradeniya, Sri Lanka Chapter 38 A Case Study of Innovation Platforms for Agricultural Research, Extension, and Development: Implications for Non-Formal Leadership and Adult Learning............................................................ 855 Matthew L. S. Gboku, Sierra Leone Agricultural Research Institute, Sierra Leone Oitshepile M. Modise, University of Botswana, Botswana Jenneh F. Bebeley, Sierra Leone Agricultural Research Institute, Sierra Leone Chapter 39 Economic Transformation of Austrian Agriculture Since EU Accession........................................... 875 Erika Quendler, Federal Institute of Agricultural Economics, Austria Christina Mayer, Statistics Austria, Austria Karl Michael Ortner, Federal Institute of Agricultural Economics, Austria Chapter 40 Economic Growth and Climate Change: An Exploratory Country-Level Analytics Study................ 906 Wullianallur Raghupathi, Fordham University, USA Viju Raghupathi, Brooklyn College (CUNY), USA Chapter 41 The Role of Irrigation in the Development of Agriculture: Srem District (Serbia)............................. 925 Vesna Ž. Popović, Institute of Agricultural Economics, Serbia Jonel V. Subić, Institute of Agricultural Economics, Serbia Nataša Ž. Kljajić, Institute of Agricultural Economics, Serbia



Chapter 42 Characteristics Development of Agriculture and Agricultural Policy Southeast European Countries.............................................................................................................................................. 948 Zoran Simonovic, Institute of Agricultural Economics, Serbia Predrag Vukovic, Institute of Agricultural Economics, Serbia Chapter 43 Trends and Transformations in European Agricultural Economy, Rural Communities and Food Sustainability in Context of New Common Agricultural Policy (CAP) Reforms............................... 967 Andrei Jean-Vasile, Petroleum-Gas University of Ploiesti, Romania Alexandra Alecu, Petroleum-Gas University of Ploiesti, Romania Chapter 44 The Use of Complementary Virtual and Real Scientific Models to Engage Students in Inquiry: Teaching and Learning Climate Change Science................................................................................ 991 Allan Feldman, University of South Florida, USA Molly Nation, University of South Florida, USA Glenn Gordon Smith, University of South Florida, USA Metin Besalti, University of South Florida, USA Chapter 45 The Temporal and Spatial Development of Organic Agriculture in Turkey...................................... 1013 Aylin Yaman Kocadağlı, Istanbul University, Turkey Chapter 46 Climate Change and Land Suitability for Potato Cultivation in India............................................... 1040 Ravindra Kashinath Naitam, National Bureau of Soil Survey and Land Use Planning, India Preeti Deshmukt, Vasandada Sugar Institute, India P. C. Moharana, National Bureau of Soil Survey and Land Use Planning, India Indal K. Ramteke, Maharashtra Remote Sensing Applications Centre, India R. S. Singh, National Bureau of Soil Survey and Land Use Planning, India S. K. Singh, National Bureau of Soil Survey and Land Use Planning, India Chapter 47 Strengthening Food Security With Sustainable Practices by Smallholder Farmers in Lesser Developed Economies........................................................................................................................ 1053 Leighton Naraine, Clarence Fitzroy Bryant College, Saint Kitts and Nevis Kevin Meehan, University of Central Florida, USA Chapter 48 A Study of Different Color Segmentation Techniques for Crop Bunch in Arecanut......................... 1078 Siddesha S, Sri Jayachamarajendra College of Engineering, India S K Niranjan, Sri Jayachamarajendra College of Engineering, India V N Manjunath Aradhya, Sri Jayachamarajendra College of Engineering, India



Chapter 49 Applying Indigenous Knowledge in Agricultural Extension in Zimbabwe....................................... 1106 Tinashe Mugwisi, University of South Africa, South Africa Chapter 50 Multiple Exploration of Entrepreneurs’ Suggestions for Agricultural Development of Local Regional Units in Greece................................................................................................................... 1127 Odysseas Moschidis, University of Macedonia, Greece Vasileios Ismyrlis, Greek Statistical Authority, Greece

Volume III Chapter 51 Agricultural Productivity in Indonesian Provinces............................................................................ 1146 Khee Giap Tan, National University of Singapore, Singapore Nurina Merdikawati, National University of Singapore, Singapore Ramkishen S. Rajan, George Mason University, USA Chapter 52 Importance of Sustainable Rural Development Through Agrarian Reforms: An Indian  Scenario............................................................................................................................................. 1163 Partha Mukhopadhyay, National Institute of Technology Durgapur, India Madhabendra Sinha, National Institute of Technology Durgapur, India Partha Pratim Sengupta, National Institute of Technology Durgapur, India Chapter 53 Mitigation of Climate Change Impacts Through Treatment and Management of Low Quality Water for Irrigation in Pakistan.......................................................................................................... 1181 Ghulam Murtaza, University of Agriculture Faisalabad, Pakistan Muhammad Saqib, University of Agriculture Faisalabad, Pakistan Saifullah, University of Dammam, Saudi Arabia Muhammad Zia-ur-Rehman, University of Agriculture Faisalabad, Pakistan Muhammad Naveed, University of Agriculture Faisalabad, Pakistan Abdul Ghafoor, University of Agriculture Faisalabad, Pakistan Chapter 54 Rural Innovations: Text and Cases..................................................................................................... 1199 Roopesh Rao, Shri Ramdeobaba College of Engineering and Management, India Chapter 55 Low Carbon Energy Innovations Systems in Natural Resource Rich Developing Countries: The Case of Brazil..................................................................................................................................... 1216 André Tosi Furtado, University of Campinas, Brazil



Section 5 Organizational and Social Implications Chapter 56 The Collective Aestheticization of Farming as Participatory Civic Engagement............................. 1233 Cala Coats, Stephen F. Austin State University, USA Chapter 57 Inter Linkages of Water, Climate, and Agriculture............................................................................ 1258 Sunil Londhe, World Agroforestry Centre (ICRAF), India Chapter 58 Does Nonfarm Income Affect Agricultural Income and Investment in Pakistan?............................. 1287 Zia Ullah Khan, University of Swabi, Pakistan Zahoor ul Haq, Abdul Wali Khan University Mardan, Pakistan Khalid Khan, Higher Education Department Peshawar, Pakistan Muhammad Ishaq, Pakistan Agricultural Research Council, Pakistan Fazli Wahid, University of Waterloo, Canada Chapter 59 Social and Environmental Impacts on Agricultural Development.................................................... 1299 Frances Bekele, The University of the West Indies – St. Augustine, Trinidad and Tobago Isaac Bekele, The University of the West Indies – St. Augustine, Trinidad and Tobago Chapter 60 Marketing of Agricultural Commodities in India.............................................................................. 1335 Rakhi Arora, Jaipur National University, India Chapter 61 An Analysis of Mobile Phone Use in Nigerian Agricultural Development....................................... 1358 Osadebamwen Anthony Ogbeide, Agribusiness Services, Australia Ideba Ele, University of Calabar, Nigeria Chapter 62 Farmer Suicides in India: A Case of Globalisation Compromising on Human Rights..................... 1378 Saloni Jain, National Law University Delhi, India Khushboo Sukhwani, National Law University Delhi, India Chapter 63 Environmental Change and the Emergence of Infectious Diseases: A Regional Perspective From South America................................................................................................................................... 1395 Ulisses Confalonieri, René Rachou Research Center - Oswaldo Cruz Foundation, Brazil Júlia Alves Menezes, René Rachou Research Center – Oswaldo Cruz Foundation, Brazil Carina Margonari, René Rachou Research Center - Oswaldo Cruz Foundation, Brazil



Chapter 64 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State,  Nigeria............................................................................................................................................... 1418 Femi Titus Akande, Librarian, Nigeria Akinade Adebowale Adewojo, Nigerian Stored Products Research Institute, Nigeria Chapter 65 Congo Basin’s Shrinking Watersheds: Potential Consequences on Local Communities.................. 1452 Bila-Isia Inogwabini, Saint Pierre Canisius Institute of Agriculture and Veterinary Sciences (ISAV), Congo & Swedish University of Agricultural Sciences, Sweden Chapter 66 Nitrate, Total Ammonia, and Total Suspended Sediments Modeling for the Mobile River Watershed........................................................................................................................................... 1469 Vladimir J. Alarcon, Universidad Diego Portales, Chile Gretchen F. Sassenrath, Kansas State University, USA Chapter 67 Impact of Climate Change on Potato Production in India................................................................. 1482 M. K. Jatav, Central Institute for Arid Horticulture, India V. K. Dua, Central Potato Research Institute, India P. M. Govindakrishnan, Central Potato Research Institute, India R. P. Sharma, National Bureau of Soil Survey and Land Use Planning, India Chapter 68 Rift Valley Fever and the Changing Environment: A Case Study in East Africa.............................. 1496 Johanna Lindahl, Swedish University of Agricultural Sciences, Sweden & International Livestock Research Institute, Kenya Bernard Bett, International Livestock Research Institute, Kenya Timothy Robinson, International Livestock Research Institute, Kenya Delia Grace, International Livestock Research Institute, Kenya Chapter 69 Impact of Overpopulation on Land Use Pattern................................................................................ 1517 Shivani Garg, Kurukshetra University, India Section 6 Managerial Impact Chapter 70 Characterization and Management Concerns of Water Resources Around Pallikaranai Marsh, South Chennai.................................................................................................................................... 1536 Avantika Bhaskar, Care Earth Trust, India G. Babu Rao, Care Earth Trust, India Jayshree Vencatesan, Care Earth Trust, India



Chapter 71 Managerial Reactions to Ambiguous Environmental Changes: Attention, Reasoning, and Erratic Decisions............................................................................................................................................ 1556 Wiboon Kittilaksanawong, Saitama University, Japan Chapter 72 Assessing the Readiness of Farmers Towards Cold Chain Management: Evidences From India..... 1570 Rohit Joshi, IIM Shillong, India Sudhanshu Joshi, Doon University, India Section 7 Critical Issues and Challenges Chapter 73 The Loss and Damage of Environmental Ethics in the Threshold of African Culture: Environmental Ethics and African Culture........................................................................................ 1589 Essien D. Essien, University of Uyo, Nigeria Chapter 74 Understanding Glacial Retreat in the Indian Himalaya: Historical Trends and Field Studies From a Large Glacier................................................................................................................................... 1605 Rajesh Kumar, Sharda University, India Prakash Rao, Symbiosis International University, India G. Areendran, WWF, India Chapter 75 Segmenting Paddy Farmer’s Attitude and Behavior: A Study Towards the Green Fertilizer Technology Adoption Among Malaysian Paddy Farmers – Adoption of GFT................................. 1623 Nadia Adnan, Universiti Teknologi Petronas, Malaysia Shahrina Md Nordin, Universiti Teknologi Petronas, Malaysia Amir Noor Noor, London Metropolitan University, UK Chapter 76 Competitiveness of Turkey in the Sectoral Transformation Process: A Comparative Analysis With the BRIC Countries............................................................................................................................ 1649 Sema Ay, Uludag University, Turkey Hilal Yildirir Keser, Uludag University, Turkey Chapter 77 Sustainability, Environmental Sustainability, and Sustainable Tourism: Advanced Issues and Implications........................................................................................................................................ 1669 Kijpokin Kasemsap, Suan Sunandha Rajabhat University, Thailand



Chapter 78 Are GM Crops the Answer to Africa’s Critical Food Security Status? Learning From the Experiences of Developing Countries............................................................................................... 1688 Nira Ramachandran, Independent Researcher, India Chapter 79 Agricultural Growth Accounting and Total Factor Productivity in Jordan: Trends, Determinants, and Future Challenges........................................................................................................................ 1709 Samia Nadeem Akroush, National Center for Agricultural Research and Extension, Jordan Boubaker Dhehibi, International Center for Agricultural Research in Dry Area, Jordan Aden Aw-Hassan, International Center for Agricultural Research in Dry Area, Jordan Chapter 80 Human Overpopulation: Impact on Environment.............................................................................. 1724 Shivani Uniyal, Banaras Hindu University, India Rashmi Paliwal, Kurukshetra University, India Bhumija Kaphaliya, Kurukshetra University, India R. K. Sharma, Banaras Hindu University, India Index................................................................................................................................................... xxiv

xxi

Preface

Due to continual advancements in technological applications, contemporary society has the ability to rapidly process large amounts of information and data in a variety of fields in order to solve complex problems and issues. In the field of environmental science, informatics can be used to quickly process and access environmental data in order to plan preventive measures and solve current environmental problems for the protection of the environment. These advancements are providing assistance, tools, applications, and solutions for agriculturalists and environmentalists on a number of issues such as the sustainable use of water and land, crop growth and maintenance, climate change, water pollution, deforestation, etc. The constantly changing landscape of environmental and agricultural informatics makes it challenging for experts and practitioners to stay informed of the field’s most up-to-date research. That is why IGI Global is pleased to offer this three-volume reference collection that will empower environmentalists, agriculturalists, researchers, professionals, academics, students, and scientists with a strong understanding of critical issues surrounding environmental and agricultural informatics by providing both broad and detailed perspectives on cutting-edge theories and developments. This reference is designed to act as a single reference source on conceptual, methodological, technical, and managerial issues, as well as to provide insight into emerging trends and future opportunities within the field. Environmental and Agricultural Informatics: Concepts, Methodologies, Tools, and Applications is organized into seven distinct sections that provide comprehensive coverage of important topics. The sections are: 1. 2. 3. 4. 5. 6. 7.

Fundamental Concepts and Theories; Development and Design Methodologies; Tools and Technologies; Utilization and Applications; Organizational and Social Implications; Managerial Impact; and Critical Issues and Challenges.

The following paragraphs provide a summary of what to expect from this invaluable reference tool. Section 1, “Fundamental Concepts and Theories,” serves as a foundation for this extensive reference tool by addressing crucial theories essential to the understanding of Environmental and Agricultural Informatics. Introducing the book is “Technological Innovation and the Agricultural Sustainability: What Compatibility for the Mechanization?” by Rachida Khaled (Faculty of Economics and Management of Sousse, Department of Economics, University of Sousse, Sousse, Tunisia) and Lamine Hammas (Faculty 

Preface

of Economics and Management of Sousse, Department of Economics, University of Sousse, Sousse, Tunisia): a great foundation laying the groundwork for the basic concepts and theories that will be discussed throughout the rest of the book. Section 1 concludes and leads into the following portion of the book with a nice segue chapter, “Aggressions of the Socio-Economic System on the Natural Capital,” by Constanţa Popescu (Valahia University of Târgovişte, Romania), Constantin Popescu (Valahia University of Târgovişte, Romania), and Maria Luiza Hrestic (Valahia University of Târgovişte, Romania). Section 2, “Development and Design Methodologies,” presents in-depth coverage of the conceptual design and architecture of Environmental and Agricultural Informatics. Opening this section is “Appropriate Extension Methodologies for Agricultural Development in Emerging Economies,” by B. S. Famuyiwa (Cocoa Research Institute of Nigeria [CRIN], Nigeria), O. A. Olaniyi (Ladoke Akintola University of Technology, Nigeria), and S. A. Adesoji (Obafemi Awolowo University, Nigeria). Through case studies, this section lays excellent groundwork for later sections that will get into present and future applications for Environmental and Agricultural Informatics. This section concludes with an excellent work by Carey Clouse (University of Massachusetts – Amherst, USA), “Design for Autonomy: Water Resources in Ladakh.” Section 3, “Tools and Technologies,” presents extensive coverage of the various tools and technologies used in the implementation of Environmental and Agricultural Informatics. The first chapter, “Web Based Automatic Soil Chemical Contents Monitoring System,” by Samuel Dayo Okegbile (Obafemi Awolowo University, Ile-Ife, Nigeria), Adeniran Ishola Oluwaranti (Obafemi Awolowo University, Ile-Ife, Nigeria), and Adekunle Aderibigbe (Obafemi Awolowo University, Ile-Ife, Nigeria) lays a framework for the types of works that can be found in this section. This section concludes with “Simulation-Based Approaches for Ecological Niche Modelling: A Geospatial Reference” by Anusheema Chakraborty (TERI University, India) and P K. Joshi (Jawaharlal Nehru University, India). Where Section 3 described specific tools and technologies at the disposal of practitioners, Section 4 describes the use and applications of the tools and frameworks discussed in previous sections. Section 4, “Utilization and Applications,” describes how the broad range of Environmental and Agricultural Informatics efforts has been utilized and offers insight on and important lessons for their applications and impact. The first chapter in this section is “Information Societies to Interactive Societies: ICT Adoptions in the Agriculture Sector in Sri Lanka,” written by Uvasara Dissanayeke (University of Peradeniya, Sri Lanka) and H.V.A. Wickramasuriya (University of Peradeniya, Sri Lanka). This section includes the widest range of topics because it describes case studies, research, methodologies, frameworks, architectures, theory, analysis, and guides for implementation. The breadth of topics covered in this section is also reflected in the diversity of its authors from countries all over the globe. This section concludes with “Low Carbon Energy Innovations Systems in Natural Resource Rich Developing Countries: The Case of Brazil” by André Tosi Furtado (University of Campinas, Brazil), a great transition chapter into the next section. Section 5, “Organizational and Social Implications,” includes chapters discussing the organizational and social impact of Environmental and Agricultural Informatics. This section opens with “The Collective Aestheticization of Farming as Participatory Civic Engagement” by Cala Coats (Stephen F. Austin State University, USA). This section focuses exclusively on how these technologies affect human lives, either through the way they interact with each other or through how they affect behavioral/workplace situations. This section concludes with “Impact of Overpopulation on Land Use Pattern” by Shivani Garg (Kurukshetra University, India).

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Preface

Section 6, “Managerial Impact,” presents focused coverage of Environmental and Agricultural Informatics in a managerial perspective. This section begins with “Characterization and Management Concerns of Water Resources around Pallikaranai Marsh, South Chennai” by Avantika Bhaskar (Care Earth Trust, India), G. Babu Rao (Care Earth Trust, India), and Jayshree Vencatesan (Care Earth Trust, India). This section serves as a vital resource for developers who want to utilize the latest research to bolster the capabilities and functionalities of their processes. The chapters in this section offer unmistakable value to managers looking to implement new strategies that work at larger bureaucratic levels. This section concludes with “Assessing the Readiness of Farmers towards Cold Chain Management: Evidences from India” by Rohit Joshi (IIM Shillong, India) and Sudhanshu Joshi (Doon University, India). Section 7, “Critical Issues and Challenges,” presents coverage of academic and research perspectives on Environmental and Agricultural Informatics tools and applications. This section begins with “The Loss and Damage of Environmental Ethics in the Threshold of African Culture: Environmental Ethics and African Culture” by Essien D. Essien (University of Uyo, Uyo, Nigeria). Chapters in this section look into theoretical approaches and offer alternatives to crucial questions on the subject of Environmental and Agricultural Informatics. This section concludes with “Human Overpopulation: Impact on Environment” by Shivani Uniyal (Banaras Hindu University, India), Rashmi Paliwal (Kurukshetra University, India), Bhumija Kaphaliya (Kurukshetra University, India), and R. K. Sharma (Banaras Hindu University, India). Although the primary organization of the contents in this multi-volume work is based on its seven sections, offering a progression of coverage of the important concepts, methodologies, technologies, applications, social issues, and emerging trends, the reader can also identify specific contents by utilizing the extensive indexing system listed at the end of each volume. As a comprehensive collection of research on the latest findings related to using technology to providing various services, Environmental and Agricultural Informatics: Concepts, Methodologies, Tools, and Applications provides researchers, administrators, and all audiences with a complete understanding of the development of applications and concepts in Environmental and Agricultural Informatics. Given the vast number of issues concerning usage, failure, success, policies, strategies, and applications of Environmental and Agricultural Informatics in countries around the world, Environmental and Agricultural Informatics: Concepts, Methodologies, Tools, and Applications addresses the demand for a resource that encompasses the most pertinent research in technologies being employed to globally bolster the knowledge and applications of Environmental and Agricultural Informatics.

xxiii

Section 1

Fundamental Concepts and Theories

1

Chapter 1

Technological Innovation and the Agricultural Sustainability:

What Compatibility for the Mechanization? Rachida Khaled University of Sousse, Tunisia Lamine Hammas University of Sousse, Tunisia

ABSTRACT The diffusion of the technological innovation can affect the agricultural sector in the three-sided (social, economic and environmental), a hand, it can contribute to solve problems of the agricultural sector: the effects of the climatic changes, the farming exodus and the migration and the problems of poverty and it can improve the agricultural productivity. But on the other hand, he can lead to new problems, such as depletion of energy resources caused by excessive use of energizing technologies, pollution of air and water and the destruction of soil by industrial waste. This paper aims to theoretically and empirically analyze the role of technological innovation in improving agricultural sustainability through the impact of mechanization on agricultural productivity, energy production and net income per capita for a panel of three Maghreb countries (Algeria, Morocco and Tunisia) during the period 1997-2012. By using simultaneous equations, the authors’ finding that technological innovation cannot achieve the purpose of sustainable development in the agriculture sector in the Maghreb countries through the negative impact of mechanization and research and development on agricultural productivity.

1. INTRODUCTION The world today endures some several economic, social, political and environmental problems, as the climatic change, the reduction of biodiversity, the destruction of soils, the shortcomings of production and consumption, poverty, the transferable illness development, the problems of unemployment, etc. A new approach has emerged in development economics for solving these problems, which incorporates the concept of sustainability is «sustainable development». DOI: 10.4018/978-1-5225-9621-9.ch001

Copyright © 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Technological Innovation and the Agricultural Sustainability

On this new basis, a sustainable development was defined by the Brundtland Report (1987) as: Sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet in their generations. (Franck-Dominique, 2003; Karen Delchet, 2004; Olivier Godard, 2002) In 1992, have Rio politicians negotiated during a summit of the earth, the development situation and environment, their issues and constraints (Franck-Dominique, 2003; Karen Delchet; Olivier Godard, 2002). In this summit was also attended by men of science and technology, recognizing that environmental issues should be a major concern in all areas of humanity. The innovation is indispensable to the sustainable development and reciprocally the sustainable development determines the orientation of the innovation. These two principles are complementary and their convergence can constitute a big advantage for the economy of tomorrow. While the question of whether technological innovation, particularly the mechanization improves or prevents the agricultural sustainability opens the door to the birth of several economic and political debates, there are little theoretical and empirical studies on the factors of development and economic durability of irrigation system in Maghreb countries. The objective of this paper is to make up the void in the literature and make an in-depth analysis the agriculture sector of the Maghreb countries in order to identify their main factors. To better understand what leads the mechanization effect on the Maghreb agriculture sustainability, we browse in this paper three types of factors, social, economic and environmental. The scope of our study covered 3 Maghreb countries during the 1997-2012 periods. We utilized an econometric methodology based on the simultaneous equations. Our results show that the technological innovation such as mechanization, research and development cannot achieve the sustainable development purpose in the agricultural sector of the Maghreb country in particular economic efficiency. The rest of the paper is organized as follows. Section 2 furnishes a brief literature review of the impact of technological innovation in the agricultural sustainability. Section 3 presents the trend of agriculture and mechanization in the Maghreb countries. Section 4 shows the data and the adopted econometric methodology. The empirical results are obtained and interpreted in section 5. Finally, section 6 presents some conclusions and policy implications.

2. TECHNOLOGICAL INNOVATION AND SUSTAINABLE DEVELOPMENT IN AGRICULTURE: A BRIEF LITERATURE REVIEW Major prior studies related to the present paper include Jimmy Alani (2012), Jean - Marc Blazy, Alain carpentier and Alban Thomas (2011), Roberto Esposti (2002),Fédes van Rijn, Erwin Bulte and Adewale Adekunle (2012), Graeme J. Doole (2012),Gershon Feder and Dina L. Umali (1993),Vernon W. Ruttan (1977), Khaled et Hammas (2014). These studies focus on the effects of technological innovation on the development of agricultural sustainability in developed and developing countries. Jimmy Alani (2012) shows that improving agricultural productivity is linked with technical progress, he argues their work by a theoretical model derived from a production function type Cobb - Douglas.

2

 Technological Innovation and the Agricultural Sustainability

Jean - Marc Blazy Alain Carpentier and Alban Thomas (2011) indicate that improvement in agricultural production based on the reduction of pesticide use and renovation of soil fertility in the fight against weed, provide the nitrogen to the soil without insecticides increases in numbers, each of this way has led to technological innovation. According to the authors the innovations also have different effects on the net operating income and the productivity. The implementation of some innovating method in the sectors agricultural based on conditions environmental, social and economic. Recent research shows that agricultural development is improving by the technological innovation, but whereas the durability can affect positively or negatively by the mechanization as it explains Colin Thirtle, Robert Townsend and Joban van Zyl (1995) in his empirical analysis that is founded on the OLS modelling. The innovation in agriculture and rural enterprise comes from whatever source (formal or informal) of new modes in the production and organization of agricultural activity. The rural populations have a human capital integrating essential sources of knowledge and new procedures through their knowledge and modes of organization. Good solutions found by small farmers themselves are a necessary source for enhancing agricultural productivity of developing countries. Nigel Poole (2006) shows that the mechanism and the level of research and innovation in the formal agricultural system have increased in the eighteenth and/or nineteenth century later has the use of scientific methods in relatively advanced economies. The R&D preferences in agriculture were encouraged during the last century by the government, which led to the birth of the formal national research systems in advanced and developing countries and the creation of organism’s international research. The green revolution is represented as a result of public research or as a classic example of a method giving land ownership to the farmer. At this point, we can say that innovation is constituted by various researches and it can be spread through different distribution procedures by economic historical, political, institutional and climate contexts. In recent years, the increasing advances in technology led to the creation of technology platforms such as information and communication technology (ICT) and biotechnology.

3. EVALUATION OF ENVIRONMENTAL, ECONOMIC AND SOCIAL FACTORS 3.1. Energy The farming surroundings and the agricultural sectors endure mediocrity of the infrastructure and the lack of information. These two difficulties cause the reduction of the outputs of the agricultural production and the decrease of the level of employment in this sector, what conducted to the apparition of poverty in these surroundings. For solving these problems, it is necessary to encourage the investment in the energy since he/it is considered like means of enhancing the life quality for rural populations, while being based on the technologies, in particular of information and the communication. The lack of infrastructure and high costs are often explained by the lack of rural energy associated with various social, economic and political difficulties.

3

 Technological Innovation and the Agricultural Sustainability

The energy is necessary to reinforce the non-agricultural farming economy directly and the agricultural farming economy indirectly. The current price of oil and its derivatives can release hazardous effects that affect various areas such as air pollution, sea pollution that led to the decline the marine resources and soil pollution and thus to reduce the fertility of agricultural land and subsequently to lower yields and lower employment in this sector, Which encourages migration from rural to industrial or other services. Energy supply associated with conventional technologies in rural areas can be more expensive. The social and environmental benefits of the development of services based on energy sources other than oil are viable. We must invest in the energy sectors other than oil for environmental and economic reasons, such as wind and solar energy, which are technically feasible for local markets in rural areas.

3.2. Poverty Reduction The project ” objectives of the millennium for the development ” (OMD) defined real strategies to avoid poverty while improving the investments in the infrastructure and the human capital in the farming surroundings, what permits to improve the agricultural sector by a qualified manpower, as well as the increase of production following the increase of the transportation means and thereafter a growth of the outputs and a reduction of poverty in the background farming, while motivating the equality between the sexes and the protection of the environment. The project of the OMD includes the science, the technology and the innovation and permits to apply the knowledge to the development. The difficulties faced by developing countries in innovation are not related to the creation of new knowledge, but the effective use of existing techniques.

3.3. The System of Supermarkets The impact of the international proliferation of large series on food retail sectors was generally analysed for developing countries and also in several other regions such as Latin America, Central and Eastern Europe, sub-Saharan Africa and Asia. In developing countries, to reason at a time of demand bound to the tendency of the local life forms and to the big international business entry, the food systems are quickly going to be complex. In Tunisia the international supermarket entry is increasing with the time the sample Carrefour Market that has developed in most regions of Tunisia. However, the international supermarket is a novelty that ensures the sale of food products, such as fresh produce, namely fruits, vegetables, meat and fish, which promotes the growth of production in the two sectors agriculture and fisheries. So the international supermarket is an innovation that improves several areas such as fisheries and agriculture, and for industry. The international supermarket system offers the advantages that are the development of the employment in these stores and in their specific supply chains, an overall increase in the quality of food coming from the technology transfer and commercial uses of farmers.

4

 Technological Innovation and the Agricultural Sustainability

National supermarkets are represented as major suppliers and demanders of local products, in the less advanced countries. These companies run into relationship marketing and ensure the root of supply series. This new business model is distinguished by low margins and high quality, creating new opportunities and new challenges for providers, such as self-service sales, healthy environments, indicating prices, the aggressive marketing and the promotions are henceforth the strategic norm (Cadilhom et al, 2006). The development of monopsony system and economies of scale associated with the production, the basis of the standards and the organization rule and multiplication of knowledge to make, transmission of the markets that explains the situation of the small agriculturists of the difficult zones that is outside of these markets.

3.4. The Lack of Information Because of the lack for a communication system that includes not only the technology, but also information there for smallholders a significant information deficit (Poole et al, 2000). Small farmers do not inform about the price, on the situation of effective demand, or the quality of favourite products, in this situation the producers cannot negotiate traders. The information available in the rural area may not be equally distributed, and producers who are excluded from markets are the most disadvantaged. Other factors act on the commercial efficiency and can form difficulties of horizontal nature to the orientation of the markets and the fluxes of information as the sex, the family, the level of education.

4. AGRICULTURAL EVOLUATION IN THE MAGHREB COUNTRY The Maghreb region includes richest country in oil and gas (Libya, Algeria) and countries whose resources are very limited compared to their populations (Tunisia, Morocco and especially Mauritania) throughout the region of Africa north (Houssem Eooine Chebbi, Lassao Lachaal, 2004). To solve this problem of limited natural resources, many economic and political leaders put agriculture in question. For all the Maghreb countries, the agricultural sector remains of major importance in the economic, social and political level. Table 1. Summarize the number of exploitation, cultivated surface, number of mechanization and spending in R&D in the three Maghreb countries in 2005 Agriculture Productivity

Country

Energy Production

Number of Mechanization

Net income per capita

Algeria

8.221

166662.44

1693.00

10270.00

Morocco

14.677

610.282

1397.00

4710.00

Tunisia

10.127

6681.4

1700.00

7360.00

Legend: the agriculture productivity is the value added (% of GDP), energy production includes forms of primary energy, or oil, natural gas, other solid fuels and renewable and waste-derived fuels and primary electricity, all converted into oil, number of mechanization measured by the number of tractors per 100 square km of arable land, net income per capita based on rate parity purchasing power (PPP). Source: WDI, 2011

5

 Technological Innovation and the Agricultural Sustainability

The sector must continue to achieve two strategic objectives: the protection of the development of basic agricultural products so-called strategic (cereals, milk, potatoes and sugar) and compensation for producers in the event of agricultural disasters. Globally, on the basis of the green revolution goal, the success of these R&D should result increased the production volume of basic agricultural products, by increasing yields and agricultural productivity and lower the level of agricultural imports expensive and rarely by the degree of respect and apply the principles of sustainable development. So the use of new technologies such as cultural diversity or animal genetic material shows very contradictory results, with rising environmental costs (protection of forest areas and backgrounds, the use of mechanization on fragile soils with increased erosion, ...) and the social costs (loss of a genetic heritage applied to the arid conditions, deterioration of the collective actions with the individual production motivations). In some difficult areas, these new technologies do not find their place because of the lack of infrastructure for production and transport, and low participation in services such credits to finance the costly inputs. Also applied research, partly in experimental research institutions overlooked the local expertise of the actors and the spread of this research was done at the expense of local knowledge which ensured a balance between the medium and the community. In the arid media, the options distribution difficulties are in intensive systems, which have been frequently reduced for social reasons, such as non-rationality of producers or low level of education in marginal and disadvantaged areas, etc. The basic consequence is the reduction of the actions to the destructive technical applications of the nature to restrict the environmental risks, in particular the risks of drought. However, facing the demographic increase of the Maghreb countries, and in light of the urbanization and unemployment increases rates attached to the emigration from the marginal surroundings, of the pastoral zones deterioration, the increasing desertification problem, and the weak technological transfer of research in the difficult zones that correspond to more of 85% of the territory, the agricultural research was interested again controlled in the small and medium agricultural farmers of the arid and semi-arid zones, but this new orientation made itself it in a setting of liberalization, from the years 80, named pre – adjustment period.

5. ECONOMETRIC METHODOLOGY AND DATA The approach selected in this paper was to model the mechanization impact on the agriculture sustainability in the Maghreb countries. Our initial intention was to cover all countries in the Maghreb, but given that some countries have not yet data of agricultural productivity (for example, Libya, Mauritania), the samples are included only 3 Maghreb countries: over the period of 1997-2010.

5.1. Data Data were extracted from two sources, the data will be used for the measurement of variables are taken from the database of the World Development Indicators (WDI 2010) and food agriculture organization (FAO 2010).

6

 Technological Innovation and the Agricultural Sustainability

Information related the expenses in research and development “R&D” (ERD), the expenses in information and communication technology “ICT” (EICT), the energy production (EP) and the net income per capita (NI) are collected from Worlds Development Indicators (World Bank, 2010). Other information related to agricultural productivity (AP), the mechanization, the Labor (L), the farming population (FP) is collected from food agriculture organization (FAO, 2010). The dependent variables of interest are agriculture productivity, energy production and net income per capita.

5.2. The Variables Our analysis founded on macroeconomic factors: •

•

Agricultural Productivity (AP): is agriculture in value added by the worker (% of GDP) (WDI, 2009). V. Ruttan (1977) indicates that the agricultural growth, improvement begins with the apparition of one sustained increase period in the total productivity via the use of new factors and new technologies; our technology is the system of irrigation (Rachida Khaled and Lamine Hammas, 2014). The Expenses in Research and Development (ERD): Clark and Youngblood (1992) showed that the variable ” technology “, as the expenses of the R&D changes the supple utilitarian shape with time is included in the specification of the function of profit, this variable permits to solve the problem of tendency of time (Colin Thirtle, Robert Townsend et Joban van Zyl, 1995). The R&D is the key of development and modernization of the agricultural sector.

Even in the developed country, the agricultural systems of research meaningful are dedicated to testing and refined the innovations of the agriculturists and to test the adaptation of exotic exploitation varieties and the species of the animal (Vernon W. Ruttan, 1977). •

The Expenses in Information and Communication Technology (EICT): permits to improve the sector by the diffusion of innovation to the world level and the diffusion of the R&D toward the producers and the consumers.

The ICT decreases the uncertainty of the producers concerning the bought input and of the consumers concerning the consumed product (Gershon Feder and Dina L. Umali, 1993). • • • •

The Mechanization (M): it is a very important technology to improve the outputs of producers. (E.J.Clay, 1982). The Labor (L): Jimmy Alani (2012) proved that the labor is considered as a technology that permits of replaced the machinery in some cases to keep the durability of the sector. The Farming Population (FP): is himself the producers, the consumers and the manpower. The farming sociologist research has contributed to the diffusion efficiency of technology (Vernon W. Ruttan, 1977). The Energy Production (EP): energy production includes forms of primary energy, or oil (crude oil, natural gas liquids, and oil from unconventional sources), natural gas, other solid fuels (coal,

7

 Technological Innovation and the Agricultural Sustainability

•

lignite, and other derived fuels) and renewable and waste-derived fuels and primary electricity, all converted into oil equivalent (WDI, 2011). Net Income Per Capita (NI): net income per capita based on rate parity purchasing power (PPP). Net income per capita in PPP is gross national income converted to international dollars using the rate parity purchasing power (PPP). An international dollar has the same purchasing power over net income per capita stating that a US dollar in the United States. The net income per capita is the sum of value added produced by all residents, most all tax revenues (less subsidies) not included in the value of production plus net receipts of income (compensation of employees and property income) from the abroad. The data are in current dollars International (WDI, 2014).

5.3. Econometric Methodology From a methodological viewpoint, we chose to value the involvement of the innovations technological to the durability and the growth of the agricultural sector based on the standard production function of Cobb - Douglas type (1928) improves by Dowricks and Rogers (2002) respecting the properties traditional neoclassical (Teheni El Ghak, 2009). Y = AK k H h Lβ or α

α

β = 1 − (α k + α h )

(1)

where, Y is a dependent variable which is defined by agricultural productivity, energy production and net income per capita. K, H, L and A are, respectively, the physical capital, the human capital, the labor that grows to the rate exogenous and constant ” n “, the technical progress is neutral in the sense of Hicks (1932) and αk, αh, β are the production elasticity’s (Teheni el Ghak, 2009). However to evaluate the participation of technological innovation, we decomposed the stock of physical capital in two parts: the material, physical capital is the mechanization (M) and the immaterial physical capital is the expenses in the information and communication technology ICT (EICT). The ERD is the investment in human capital, according to the theory of human capital (Malam Mom Nafiou, 2009). The expenses in R&D (ERD) and the expenses in the technology of information and communication, ICT (EICT) are considered like an investment in the innovation (OECD, 1999). The stock of the labor is decomposed into two parts: the labor in the agricultural sector (L) and the farming population (FP). The goal of this paper is to examine the relationship between technological innovation and agricultural sustainability through the impact of mechanization on agricultural productivity, energy production and net income per capita. This relationship is measured by a simultaneous equations model (3SLS) extended as follows: APit = α + β1 (EICT ) + β2 (M ) + β3 (ERD ) i ,t

i ,t

i ,t

+β4 (L ) + β5 (FP ) + β6 (EP ) + β7 (NI ) + ξi,t i ,t

8

i ,t

i ,t

i ,t



(2)

 Technological Innovation and the Agricultural Sustainability

EPit = α + β1 ( EICT )i ,t + β 2 ( M )i ,t + β3 ( ERD )i ,t + β 4 ( L )i ,t + β5 ( FP )i ,t + β 6 ( AP )i ,t + β 7 ( NI )i ,t + ξi ,t

NI i,t = α + β1 (EICT ) + β2 (M ) + β3 (ERD ) i ,t

i ,t

i ,t

+β4 (L ) + β5 (FP ) + β6 (AP ) + β7 (EP ) + ξi,t i ,t

i ,t

i ,t





(3)

(4)

i ,t

i = 1, 2,…N, t = 1,2,…Ti where AP, EP and NI are the dependent variables, are defined respectively as agricultural productivity, energy production and net income per capita. The Independent variables are the expenses in research and development (ERD), the expenses in information and communication technology (EICT), the mechanization (M), the labor (L), and the farming population (FP). Equation (2), allows measure the impact of technological innovation on economic sustainability through the effect of the mechanization (M) on the agriculture productivity (AP), as well as the spending of research and development (ERD) and spending of information and communication technology (EICT) impact. Equation (3), allows examine the impact of technological innovation on environmental sustainability through the effect of the mechanization (M) on the energy production (EP), as well as the spending of research and development (ERD) and spending of information and communication technology (EICT) impact. Equation (4), examines the impact of technological innovation on social sustainability through the effect of the mechanization (M) on the net income per capita (NI), as well as the spending of research and development (ERD) and spending of information and communication technology (EICT) impact. Our methodology is based on an estimate of the simultaneous equations model (3SLS), a sample of 3 Maghreb countries (Algeria, Morocco, Tunisia) and a measurement of the variables from the data for the countries will of 1997 until to 2010. This simultaneous equations model is estimated by the generalized method of moments (GMM). Since generally, the results of GMM are robust.

6. RESULTS AND INTERPRETATION Table 2 provides summary statistics on the variables. Table 2 shows that the average agricultural productivity, the entire sample is 2.437398%. The interindividual variance (between) 0.0908%, while the intra individual variance (time) is equal to 0.0172%, in our case the inter-individual dimension (3 countries) is very important that the intra-individual dimension (17 years country) (0.0908%> 0.0172%). The same for the regression (3) and (4). Table 3 summarized the results of three least squares (3SLS) models for the sample of the 3 Maghreb countries from 1997 to 2013.

9

 Technological Innovation and the Agricultural Sustainability

Table 2. Descriptive statistics Variable AP

Mean

Std. Dev

2.437398

.2811494

Min

Max

1.899224

3.006836

ERD

-.8185559

.7113078

-2.65926

.4054651

EICT

1.316085

.5931466

.4054651

2.674149

L

1.743967

.5446175

.8329091

2.388763

FP

3.669752

.1182476

3.510638

3.863899

M

4.495038

.4879865

3.805239

5.002106

AEP

9.090681

2.234337

6.346817

12.02373

NI

8.847955

.3956486

8.02617

9.478075

N 51 N 17 T3 Note. — N, total number of observation; n, number of observation for only one country; T, number of country.

Table 3. Estimation of the model by the method 3SLS models

(2)

(3)

(4)

Variables

AP

EP

NI

AP

---

.0443973 (0.324)

.0053343 (0.448)

EP

2.66 (0.074)*

---

3.25 (0.000)***

NI

-.0000302 (0.293)

-.0000361 (0.676)

---

M

-.0075109 (0.007)***

.0752307 (0.000)***

.0032048 (0.047)**

ERD

.2154256 (0.144)

-2.626171 (0.000)***

.1818109 (0.012)**

EICT

.0140135 (0.127)

.0401492 (0.175)

.0365969 (0.000)***

L

-.0595136 (0.002)***

.2157 (0.000)***

.0197317 (0.076)*

FP

.0148279 (0.324)

.1443269 (0.000)***

-.037439 (0.000)***

Constante

2.894438 (0.001)

-4.792734 (0.006)

9.310632 (0.000)

Observations

37

37

37

R

0.9243

0.9867

0.9879

2

Note. — Panel estimations of the 3 Maghreb countries. The dependent variable is the agriculture productivity (AP), energy production (EP) and the net income per capita (NI). Variables in parentheses are at the significance level of 1% *, 5%** and 10%***.

10

 Technological Innovation and the Agricultural Sustainability

The first column presents the effect of mechanization on economic sustainability through her impact on agricultural productivity. The second column indicates the effect of the mechanization on environmental sustainability through her effect in energy production. The third column shows the impact of mechanization on social sustainability through her effect on net income per capita. According to the regression (2), we show that where agricultural productivity (AP) increases by 1 percentage points, mechanization (M) decreases by 0.0075109 percentage points, labor (L) decreases by 0.0595136 percentage points, net income per capita (NI) drops by 0.0000302 percentage points, R&D expenditure (ERD) and communication and information technology expenditure (EICT) increase respectively by 0.2154256 percentage point and 0.0140135 percentage point, farming population (FP) raises by .0148279 percentage points, and energy production (EP) increases by 2.66 percentage points. This negative impact of mechanization on the sustainability economic explains that the mechanization cannot achieve economic efficiency in the Maghreb countries due to the intensive use of mechanization in the sector, allowing deteriorate soil fertility over time and eventually lowers productivity and performance in the agricultural sector. In the regression (3), we mark that wen energy production rises by 1 percentage points, mechanization (M) increases by 0.0752307 percentage points, labor (L) increases by 0.2157 percentage points, net income per capita (NI) drops by 0.0000361 percentage points, R&D expenditure (ERD) drops by 2.626171 percentage points, communication and information technology expenditure (EICT) increase by 0.0401492 percentage points, farming population (FP) raises by .1443269 percentage points, and agriculture productivity (AP) increases by 0.0443973 percentage points. According to the study of L. Kallivroussis; A. Natsis; G. Papadakis (2002), the mechanization ensures the transportation of the oleaginous plant energy to processing for the production of biodiesel. The use of mechanization in agriculture increases the energy work by reducing the working hours of each employer. So the mechanization increases energy production. Regression (4), indicate that when net income per capita (NI) increases by 1 percentage points mechanization (M) increases by 0.0032048 percentage points, labor (L) increases by 0.0197317 percentage points, energy production (EP) rises by 3.25 percentage points, R&D expenditure (ERD) increases by 0.1818109 percentage points, communication and information technology expenditure (ECIT) increase by 0.0365969 percentage points, farming population (FP) decreases by 0.037439 percentage points, and agriculture productivity (AP) increases by 0.0053343 percentage points. Usually technological innovation affects positively the social aspect, mechanization is produced by innovative societies and eventually allows increased wages of companies and their purchasing power that leads as the decline in poverty. Mechanization improves the purchasing power of Employers in the industrial sector such as an equipment manufacturing society, for against the rural population suffers from very high level of poverty. As he explains C.P.Timmer (1992), the agricultural sector is like a black box, it provides power to all the other sectors against it is not growing. In the Maghreb countries, the mechanization affects positively the sustainability’s environmental and social but it affects negatively the sustainability economic. According to the results of the simultaneous equations model (3SLS) estimation, we noticed that the workforce has an important role in the functioning of agricultural machines. The three regressions (2), (3) and (4) show that the relationship between mechanization and labor is positive. The impact of mechanization on economic, social and environmental aspects is explained by the effect of labor on the three durabilities. The workforce in agriculture of the Maghreb countries is unqualified. 11

 Technological Innovation and the Agricultural Sustainability

The lack of learning by doing in the agricultural sector prevents increasing performance and productivity through step full of ecological, poor use of fertilizers, spreading pollution and over-exploitation of water resources (Feder and Umali, 1993). The result of the estimated regression No. 3 shows that the level of research and development to a negative impact on the environmental aspect through their impact on energy production, this result can be interpreted by the novelty of the sustainable agriculture in the Maghreb countries, such as organic farming. Biological research and development remains until today in the laboratories and has not yet applied to a field. The information and communication technology (ICT) has a positive effect on all three aspects (economic, social and environmental), this result is explained by the introduction of new technology (mobile, internet, etc.) in rural areas and their participation in the agricultural sector through improved marketing of agricultural product line, development and definition of sustainable agriculture concept and organic products in the Maghreb countries. The result of the estimated regression No. 4 indicates the farming population affects the affects negatively the social aspect through their impact on the net income per capita. The population increase in rural areas increases the pollution in the zone and increases the use of water resources, leading to over-exploitation of natural resources. Despite the positive effect of mechanization on the social and environmental aspect, mechanization used by Maghreb countries is not sustainable since it cannot achieve economic efficiency.

7. CONCLUSION AND POLICY RECOMMENDATIONS The concept of sustainable development has spread during the 90s in scientific research both locally and planetary. All this research agrees that the achievement of sustainable development depends on the respect of four essential principles: equity between nations and generations, the equilibrium of the economic situation and the protection of the environment. On this basis, several economists and scientists believe that the diffusion of technological innovation is a basic means to ensure sustainable development in the agricultural sector. To verify this effectiveness, we tested the effects of technological innovation on the agricultural sector in the three Maghreb countries (Tunisia, Morocco and Algeria) for a period from 1997 to 2010 by a model of simultaneous equations, as well as their ability or non to achieving the objectives of sustainable development in agriculture sector. The estimation results show that mechanization used by Maghrebin farmers is unsustainable. For this it’s unable to achieve the sustainable development objectives in the agricultural sector of Maghreb countries. The mechanized agricultural land use may lead to reduced fertility and increased pollution. A recent study done by CEMA (2014) indicates that there are 12 types of agricultural mechanization in the world. The weak type is used by developing countries, particularly Africa. It can be concluded that the poor quality of mechanization used by Maghreb countries to impact the agricultural sector sustainability. Our findings have important policy recommendations for Maghreb countries. First, the government support for funding and Development: the Maghreb Farmers need for state subsidies to buy sustainable agricultural machines with good quality. They also need the development of their rural areas by building infrastructure to attract investors to invest in the agriculture sector.

12

 Technological Innovation and the Agricultural Sustainability

Secondly, improve training in the rural middle, especially how to operate farm machinery: the workforce in the agricultural sector of the Maghreb countries is not qualified because of their limited education level. The majority of labor worked in agriculture is the farming population. Third, the development of environmental protection strategy and implementation in the rural middle, for example, the payment of fees for people that generate negative externalities in the rural areas.

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This research was previously published in the International Journal of Innovation in the Digital Economy (IJIDE), 7(2); edited by Ionica Oncioiu, pages 1-14, copyright year 2016 by IGI Publishing (an imprint of IGI Global).

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Chapter 2

Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey Veysel Asoğlu Harran Unıversıty, Turkey Halil İbrahim Şengün Dicle University, Turkey

ABSTRACT Requests and needs are not static in a growing and changing world. On the contrary, they can develop and change with the effect of both environmental and internal factors. Green marketing is the request of social civilization. One of the effects of this growing interest in environmental markets in Turkey and the rest of the world can be seen in the move towards organic agriculture. The main purposes of this study are to define organic agriculture as described by environmental marketers and as practised in the agricultural sector, and to explore the current condition of organic agriculture in Turkey and the rest of the world. Subsequently, organic agriculture and the main problems in its related sectors will be discussed and suggestions for solutions will be given. Suggestions will be given that include political, as well as research and development and training programs that are related to improving organic agriculture and increasing organic exports.

INTRODUCTION Sustainable agriculture involves the production of food products with sufficient and quality amounts and with appropriate costs. Besides, economic vitality of world agriculture involves protection of environment and natural agriculture resources and systems and practice that will develop welfare of population of the World. The most important fact which should be examined about sustainability in Turkey is agricultural activities and the subject of organic agriculture. Because, agriculture is the starting point which we define as prime production of food chain. Therefore, organic agricultural activities in Turkey will be tried to be examined in the study and problems faced will be put forward and solution ways will be discussed. DOI: 10.4018/978-1-5225-9621-9.ch002

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 Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey

GREEN MARKETING Although environmental issues affect human activities and whole human health, the number of science fields dealing with environmental issues are pretty few. The more the interest of society towards natural environment increases, the more businesses should review their internal policies in order for them to be able to fulfill the requests of society. Green Marketing takes places in the literature with different names such as ecological marketing, environmental marketing, sustainable marketing and conservationist marketing and etc. All of these concepts take reviewing marketing programs to be applied in meeting requests and needs of consumer with conservationist approach as a basis (Shehu, 2010). Marketers haandcompiled process of change of green marketing definitions in time. According to this, development process of green marketing in time can be stated as below; At firstly, Henion and Wilson (1976) emphasized the necessity of that all marketing activities in environmentalist marketing should become remedy for the causes of environmental problems and should bring awareness. Recently, İslamoğlu (2013) defined green marketing as “businesses’ determining their marketing strategies, programs in a way that will protect and develop natural environment and applying them.” It is stated by financial communities that green marketing involved in marketing literature in a seminar, the subject of which was ecological marketing, American Marketing Union organized in the USA in 1975 for the first time (Erbaşlar, 2007; Ay & Ecevit, 2005). As Ottman (1993) informed, green marketing is a work strategy which examines positive and negative sides of pollution, energy consumption and consumption of exhaustible resources, which aims at longterm profitability within the perception of responsibility in meeting the needs of society and consumers (Alagöz, 2008). It may be stated that green marketing has arisen from societal marketing with its one aspect. Societal Marketing is a marketing approach which aims at not only satisfying only its customers but also considering the expectations of society (Pezikoğlu, 2012). Green Marketing is an approach which has been advancing by becoming more and more powerful since 1980s as a new marketing strategy which has double-sided (producer-consumer) interaction and compulsivity. Besides, green marketing means a process which renews itself continuously. It is observed that green marketing has become different conceptually in time. According to this, “ecological marketing, which involves all marketing activities which causes environmental problems and which will become solution to these environmental problems, and which showed up with phrases of recycling, ozone-friend and etc.” comprises the first stage. The second stage is “green-environmentalist marketing”. The third stage is stated as “sustainable-green marketing”. Undoubtedly, development of environmental marketing has had some effects on marketing in the last 10 years. It is known that giant companies such as IBM, McDonalds and BT and etc. force their suppliers to show higher eco-performance by using their purchasing power in their hands. And it is seen that they control these works with green supervising. (Pezikoğlu, 2008).

SUSTAINABLE AGRICULTURE AND ORGANIC AGRICULTURE: TRADES AND SUBSIDIES Sustainable agriculture is related to agricultural dimension of sustainable development. In sustainable agriculture, it is essential that in addition to that natural resources should be protected in the long run,

18

 Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey

agricultural structure where agricultural technologies which do not harm environment should be formed. Synthetic production inputs are used without supervision in a number of countries in the world. And at the same time, intense (conventional or intensive) agricultural production are being carried out without thinking negative results that cultivation techniques and technologies form. Nowadays, these practices has started to get attention as much as waste industry or urban pollutions with their characteristic of creating danger of life which may reach human via their effects on deformation of natural balance and also all creatures. Because of this, in sustainable agriculture, techniques that have not lost their naturality yet have had necessity. Here, using inputs which are not natural such as pesticides, synthetic fertilizers and etc. should be avoided and organic agricultural techniques meeting with health and environmental standards play a key role. Organic agriculture which bear importance in terms of reflection of sustainable agriculture to practice has started to constitute a necessity together with the development of environment awareness especially in recent years. In addition to this, products chosen in order to know and protect some agricultural products in especially European Union (EU) countries are registered in sustainable agriculture perception (Turhan, 2005). Sustainable agriculture are being tried to be carried out with different systems in a number of countries round the World. Products produced by using this method and system are among the green products. HACCP (Hazard Analysis and Critical Control Point), ISO (International Organization for Standardization) series, organic and good agricultural practices confront us as green marketing products. (Albayrak et al., 2010). Organic Agriculture is one of the systems of sustainable agriculture. However, Organic Agriculture has specific principles and practices in the process from the production of products on the field to their marketing (Demiryürek, 2011). Sustainable aspects of organic agriculture within sustainable agriculture concept can be summarized as below: • • • • • •

Avoiding earth and water pollution, even if it is low, as a result of choice and application of natural chemicals applied compatible with ecological environment and designing an agricultural production system which may be within ecological environment, Having formed a new system in terms of economic sectors, actors within conventional system being able to be within this commercial system. Producer’s Adopting production methods protecting environment in rural areas, Distributing risk by having activity which has any other market network and price within agricultural activities carried out on the basis of businesses, Because work power need is higher, preventing unemployment and, being positive for businesses whose work power is intense, Being in the market as a new product which is just in the beginning of product life cycle, having become a trademark, and being able to form organic label at the national level.

As against the aspects mentioned above, criteria which should be taken into consideration in order to examine organic agriculture with regard to sustainability of agriculture can be classified as: • •

Food safety and guarantee, Sufficiency and continuity in business income,

19

 Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey

• •

Continuity of employment in rural areas, Rural welfare (Pezikoğlu & Yavuz, 2006).

When the literature is examined, there are a number of definitions about the concept of organic agriculture. However, because there is no common definition which is agreed generally, it brings together some discussions and differences of opinion. Here will be given a definition whose framework has been drawn up technically by USA Agriculture Department (USDA). According to this “organic agriculture is a production system which forbids use of fertilizers with synthetic content, pesticides, growth regulators or which avoids them to a large extent. Organic agriculture systems depend on processes of product alternation, plant residues, animal fertilizer, legume, green fertilizing, organic farm waste and control of biological pests in so far as possible in order to cultivate the soil, protect the productivity, to provide plant foodstuff, to control pests, weeds and diseases (Anonymous, 1980). Lampkin (1990) emphasized sustainability advantages of organic agriculture and defined organic agriculture as an agricultural approach aiming at the purpose of forming an integrated agricultural system which is environmentally, socially and economically sustainable. He emphasized that dependence on out-of-farm inputs should be reduced whether they have chemical or organic roots. As a result of long-term studies, the definition of organic agriculture was approved by International Organic Agricultural Movement Federation (IFOAM) in Italy in 2008. According to this; “Organic Agriculture is a production system which sustains soil, ecosystem and human health. The system depends on ecological processes, biological diversity and cycles which have been adapted local conditions. Organic agriculture brings traditions, innovations and science together in order to be beneficial to the environment in which it is lived, to generalize fair relation and a better life quality for all related parties” (Anonymous, 2009). In the efforts of increasing especially agricultural lands and water resources in the world in recent years, more and more difficulties are being met. Environmental effects such as oil erosion and air pollution have slowed down the increase of agricultural lands in the world, even they have brought it just to the point of stop. Not being able to cultivate the lands which have suffered from erosion seriously, and the lands’ being used in out-of-agriculture areas such as buildings and factories cause millions of hectares of lands to be lost every year. While some countries such as Brazil, Israel and etc. are forming new agricultural lands by rehabilitating deprived lands in terms of productivity, other countries such as Turkey, China etc. convert 1. class agricultural lands into other usage areas. As a result of all of these, the amount of agricultural lands per person reduces in both Turkey and the World (Rehber and Çetin, 1999). On one side, the world population is increasing and on the other side decrease in cultivated lands is seen as an important problem. Developed and developing countries began to try to take precautions against all of these threats and started studies related to this subject in 1950s (Turhan, 2005). Studies, which continued separately until 1970s, gathered movements of organic agriculture all round the world under a common roof in 1972. With the foundation of IFOAM which aims at directing development of the movement healthily, protecting required standards and methods, conveying all developments to its members and farmers, this gathering gained a different dimension. Really, practices of production standards which have been combined and/or have become adapted, aiming at production of organic foodstuff all round the world, are quite important for growing organic agricultural land and organic product markets to develop more. Harmonizing rules and every country’s organizing its own regulations commonly is necessary in order to remove the difficulties of trade of organic products (İpek & Çil, 2010). 20

 Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey

It is known that organic agriculture started for the first time in EU and USA and then spread to other countries. There are total 37.2 million hectares of organic agriculture land (including transition process areas) in the world. In today’s world, 1,2% of agricultural land cultivated in the world is organic agricultural land. (Eryılmaz et al.,2015; Emir & Demiryürek, 2015; Willer & Klicher, 2011). Nowadays, organic agriculture is becoming a sector whose market volume and consumption demand are increasing more and more all round the world. It gets attention that developed countries start to be in the position of consumer and developing countries start to be in the position of producer. One of the most important driving power at the back of organic agriculture is that organic products are more reliable than conventionals with regard to chemical use and residue problem and that the number of consumers believing this is increasing. It is a fact that organic agriculture reduces toxic chemicals, prevents the use of Genetically Modified Organisms (GMO) definitely, reduces food additives and colorant use, on the other hand, increases beneficial minerals and foodstuff, beneficial oil acids and antioxidants. In addition to this, organic products it is mentioned that organic products have the potential to reduce the risk of formation of cancer, coronary heart diseases, allergy and hypermobility problem in children. A number of studies showing comparative benefits of organic food and forage in terms of health have been conducted. There are claims that organic products are more superior than products produced with other alternatives in terms of safety nutrition content and value. Especially, expectation that vegetables and fruit produced via organic way will be more beneficial than conventionals in terms of health is common (Rehber & Pezikoğlu, 2013). While up to 500 additives are permitted in conventional food production, the number of additives permitted in organic production is only about 30 (Heaton, 2002). Countries making organic agricultural production preferred starting from usually conventional products of their countries in the transition towards production all round the world. For example, the first products produced organically are tea in India, milk and dairies in Denmark, meat and meat products in Argentina, banana in central America and Africa countries, date palm, olive oil in Tunisia, dried and fruit with hard shell (İpek & Çil, 2010). While a fast production decrease is the point in question at first in the transition towards organic agriculture when compared to conventional agriculture, production level approaches to the previous level with precautions taken afterwards. While giving up using synthetic inputs causes productivity decrease, it provides important cost savings. In an evaluation made, while gross yield with the rate of 6-17% is the point in question in transition towards organic agriculture in plant production, because of decrease in costs, net income loss is said to be about 13% at most. Even if organic agriculture seems to be financially less advantageous than conventional agriculture, especially in the long run, it is actually more superior with economic contributions in the way of protecting environment and natural balance. Consumer income in the long run is very important in sustainable agriculture and so in organic agriculture (Turhan, 2005). In World Trade Organization (WTO) organizations, agriculture has been involved within globalization. In WTO agreement, opinion of market mechanisms’ directing agricultural production and change by purging agricultural policies of state intervention and social dimension has been agreed. However, because of welfare differences between rural communities, some privileges have been granted in certain subjects in agriculture. According to this, internal supports are examined in 3 parts, Red Box, Blue Box and Green Box. Green Box includes supports from which any discount is not requested in internal supports. Organic agriculture is assessed within this box. By the same token, direct income support payments are within this scope and direct income support payments made to organic agriculture does not get limited by WTO. FAO grants supports to organic agriculture and similar environment-focused

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 Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey

agricultural systems. Principles and standards of organic agriculture was defined by Codex Allimentarius (Pezikoğlu & Yavuz, 2006). Before mentioning supports given to organic agriculture in Turkey, it is beneficial to mention their examples in the world briefly; Organic agriculture have been conducted under the control of the state in the USA. Organic Agricultural Producers are supported with advance payments or payment conveniences for especially certification. In Latin America, organic action generally has developed with its own effort. There is no state which provide support or economic help directly. As an exception, the state has published interministy organic plan in order to encourage organic production, research, marketing and trade in Brazil. In Bolivia, an action plan has been created in order to support development of organic production and to establish national control system. EU Countries, which own more than 50% of organic food market, is also in the position of the biggest foreign purchaser of the world. Organic agriculture has located in the center of agricultural policy of the Union with Common Agricultural Policy (CAP), which took effect on 1 January 2005. With reforms made in common agricultural policy, agricultural subsidy policy has changed completely. According to this, protection of environment, food safety, animal and plant health and sustainable use of agricultural land are predicted with new regulations. In addition, both regulations related to agricultureenvironment relations and various regulations dealt with within the scope of environment policies, and national programs which each country member of EU has developed according to their own conditions contributes for organic agriculture to be directed. Farmers in all EU countries gets support within the scope of agricultural environment programs. State supports aimed at organic agriculture in different EU countries are as follows; The United Kingdom (UK) has given the biggest environmental priority to sensitive regions. Depending on the structure of land, farmers are granted previous period supports paid in the last 5 years in this country. In Germany, development of organic agriculture was supported by forbidding chemicals from 1989 to 1992. There are a number of different applications about the support granted to organic agriculture resulting from federal structure. Different programs are applied in each one of states in order to support farmers dealing with organic agriculture and participation conditions to these programs show differences. Annual subsidies are granted to farmers dealing with organic agriculture in vegetable production per hectare in Belgium and finance of two research centers which have been established for organic agriculture is provided. In Denmark, the government supports organic agriculture projects and grants subsidies per hectare. Although Danish Farmers are involuntary about transition towards organic agriculture, transition towards organic agriculture has been considerably enabled as a result of government policies and market pressures. In Italy, supports granted to organic agriculture are used like direct income support in some regions. Tax applications to pesticides are started in order to create financial resources in order to be used in development of organic market. In addition, campaigns of awarenessraising of the population are being carried out. In Netherlands, various precautions have been taken in order to increase production and consumption of organic agriculture according to policy called “Organic Market in order to Win”. The purpose of legal regulations aimed at farmers making organic production in Netherlands is to increase sustainable investments in agriculture (Anonymous, 2012). Because of fewness of studies in which organic agricultural trade and state supports are told together in developing states before in the literature, current condition in Turkey, insufficiencies, support elements which are and should be provided to organic agriculture will be examined in the study afterwards.

22

 Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey

BACKGROUND In a study that Eryılmaz et al. (2015) conducted, according to results of the research made in certain provinces of Turkey, among the reasons that consumption of organic agriculture and food products is low are highness of prices and knowledge insufficiency. Increasing demand for organic agriculture and food products is important with regard to sustainability of production. Therefore, organic producers who want to continue their existence in the sector and who want to follow the development in the world should turn towards the perception of consumer-focused marketing. According to Armağan and Özdoğan (2015), in Aydın province consumers prefer organic food products which they qualify as healthy and delicious more as their income level and education level increases. 30,4% of consumers stated that they could pay more to organic chicken and 30,4% of those to organic eggs. According to results of researches that Akgüngör and et al. (2010) conducted on the people living in urban areas of İstanbul and İzmir provinces, the reasons for consumers to prefer organic products are that their nutrition values are higher and their health risks are lower. Consumers do not perceive organic food products more expensive than conventional equals and they are voluntary to pay up to 36% more to organic labeled and certificated products. According to Akın et al. (2010), in Niğde province, families under the age of 40, whose income levels are over 1000, with one or two children and especially women consumers within this group are more sensitive about organic food subject than the groups having other socio-demographic characteristics. According to a research that Dağıstan and et al. (2010) made on consumers living in the center of Hatay Province, 57% of consumers consumed at least one organic agriculture and food product. Knowledge deficit and price highness (70%) are among the leading reasons for consumers’ not consuming organic products. Sarıkaya (2007) determined in his research that the organic product groups which consumers, living in Ankara and İstanbul where organic agriculture and food product market intensifies, buy most are vegetables, fruit and drinks because they are easily found and their product ranges are wide. Aydın (2011) found out that 7,81% of consumers living in urban areas of Samsun province regularly consume organic products and that knowledge deficit, with 43,22%, is in the first place. According to Gündüz and Bayramoğlu (2011), 81% of families living in Samsun province agree to pay more for organic chicken. It was determined that monthly family income, education level of family head, monthly chicken consumption, organic food consumption and opinion of consumers related to risks conventional chicken bear in terms of health have effect on payment desire. Ergin and Özsaçmacı (2011) found out in their study where he researched main reasons for consumers’ buying organic product in İstanbul and Ankara provinces that thoughts that organic foods are more healthy, tasty, fresh and environment-friendly are dominant when compared to their conventional alternatives according to findings obtained. As Erılmaz et al. (2015) stated in their compilation study they conducted, It was determined that markets of organic agriculture and food products intensifies in different parts of Turkey especially in big provinces such as İstanbul, Ankara and İzmir. It was seen that consumers’ habit of purchasing organic agriculture and food products is not common in Turkey in general. Among the main reasons for this condition are that consumers do not have sufficient knowledge about organic production and they regard prices as high.

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 Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey

In a study Hassan et al. (2009) conducted, education was found to be the first of effective factors in the formation of consumer attitude and behavior in EU countries against organic food and agricultural products. Because, it is seen that organic agriculture and food products are preferred more by those whose education levels are higher. In a study Urena et al. (2008) conducted, it was found out that another effective factor in the consumption of organic agriculture and food products is gender. According to findings, although tendencies of women consumers towards buying organic products are higher than men, their wills to pay to these products are lower. In a research Kızılaslan and Olgun (2012) made, they found out that organic agriculture land and the number of producers are increasing more and more and on the other hand, Turkey cannot use the potential it has about organic agriculture sufficiently. Gülse Bal et al. (2006) determined in a study conducted in Tokat province that 90% of consumers may pay more to reliable food. In an organic product demand research conducted by Koç et al. (2001) in the center of Ankara, the rate of voluntary consumers to pay 50% and %100 price difference without reducing their consumption was determined to be 24,2 for tomatoes and 16% for cucumbers (Koç et al., 2001). In a study Karahan Uysal et al. (2010) conducted, although the most important fact defining organic product is “logo”, it is thought that Turkish consumers do not have sufficient information about it. In a study conducted on organic product consumers in İzmir and Ankara, it was determined that knowledge levels of consumers about organic product logos and standards are low and on the other hand, trust in logos is above average. In a research made by Pezikoğlu (2004), price difference Turkish consumers are ready to pay for organic product was found to be about 2%. In a research made by Demiryürek (2004), economic factors (especially premium price and market guarantee) were found out to be the most effective motivation element in transition of producers towards organic production in Turkey. In another research made by Demiryürek (2011), a number of suggestions were made aimed at policies, research and development and training programs related to developing organic agriculture in Turkey and increasing our organic product export. In a research Bahrs(2004) made, he stated that subsidies should be also supported with tax incentives. According to findings they obtained in a research Azak and Miran (2015) made in İzmir province, Turkey, they stated that if supports that will increase the number of organic producers are made, the number of producers and consumers will increase, this will increase supply and may be able to balance product prices. State and municipalities should give supports that will reduce the costs of especially sellers, for example, paying transportation costs may prevent product prices from increasing. By increasing market places, opportunity of marketing their products easily should be given to producers, and it should be targeted to reach more consumers. In a study Lotter (2003) conducted, the aspect of organic agriculture’s being a system which provide important benefits to public about reducing environmental costs was emphasized. In the study was also stated the necessity of transferring high costs in transition towards organic agriculture from farmer and organic product customer to public.

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 Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey

ORGANIC AGRICULTURE TRADES AND SUBSIDIES IN TURKEY Issues, Controversies, Problems One of agricultural effects of sustainable and green marketing is seen in the shape of turning towards organic agriculture in Turkey and in the world. Organic agriculture practices is becoming widespread not only in developed countries but also in developing countries. This condition has become clear with increasing importance the consumers especially in developed countries give to their health and protecting environment. In parallel with this, organic food market is developing especially in Europe, America and Oceania. Demand for organic products which are not produced in developed countries has caused international trade to develop. So, developing countries whose ecology is suitable for organic agriculture have become organic product producers and exporters in order to be able to meet demands coming from developed countries. With this aspect, organic agriculture is a very valuable element whose importance in Turkish trade is increasing fast (Rehber & Turhan, 2001; Demiryürek, 2011; İpek & Çil, 2010) Organic agriculture in Turkey started in the direction of demand of European importers and with export of sultanas and dried figs in Aegean Region for the first time in mid-80s and spread all round Turkey from here. Although farmers led the development of organic agriculture in the countries where organic agriculture started, European private organic agriculture companies played an active role in promotion of organic agriculture and adopting it to farmers in Turkey. That is, whereas Europe and in the USA realized bottom-up starting from producer (supply-based), top-bottom structuring of organic agriculture from companies dealing with organic agriculture towards producer (demand-based) is the point in Turkey (Kizilaslan & Olgun, 2012; Demiryürek, 2004; 2011). Organic products started to gain importance commercially all round the world in 1990s. It became necessity for a national legislation on organic product which came to the fore in those years in Turkey which organizes all stages of organic agricultural activities from production to marketing to be created. In this direction, “Legislation on Production of Herbal and Animal Products” was enacted in 1994. With this legislation, organic agricultural activities were started to be carried out in Turkey for the first time under the supervision of Food, Agriculture and Livestock Ministry (FALM) and within rules determined. Later years, the legislation mentioned was modified in order to comply with changes in EU legislation together with developments lived in the sector and “Legislation on Principles and Practice of Organic Agriculture” was published in 2002. By considering increasing importance of Organic Agriculture, “Organic Agriculture Law” No:5262 involving provisions of production, consumption and supervision of organic products was published in order to form a ground to penal sanctions and duties and responsibilities of the parties and to strengthen legal regulations made with the legislation in this field. “Legislation on Principles and Practice of Organic Agriculture” which was prepared by depending on this law took effect in 2005. In the direction of demands and needs coming from the sector, changes were made 3 times. At last, Council Regulation No:834/2007 and Council Directive No: 889/2008 were put into practice instead of Council regulation No: 2092/91, and national legislation was brought into conformity with European Union Legislation and was published in 2010. Besides, organic Agriculture Units were formed within 81 Province directorates of the Ministry in order to carry out activities related to organic agriculture. Duties and authorities of those to work in this unit were determined with Communique No: 2005/1. The Communique mentioned was revised as communiques, No: 2009/1 and 2011/4 (Anonymous, 2012).

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 Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey

There are 42 accredited institutions for certification procedures of organic agricultural producers in Turkey as of 2016. The number of producer businesses having legal entity authorized by these institutions is 1106 (Anonymous, 2016b). As specified in Table 1, organic agriculture has shown important developments year by year in every sense from the number of products to the number of producers, from total production land to total production amount. As specified in Table 2, Turkey exported organic fig and fig products the most in 2014 (21.626.691 $). Afterwards nut and nut products (17.046.378 $) and sultanas (13.557.823 $) come. As seen in Table 3, Turkey exported the most to Germany (19.248.646 $), the USA (19.053.760 $) and France (8.507.402 $) respectively. It is seen that the countries mentioned are developed countries as stated in previous sections. As specified in Table 4, the first three of organic product import of Turkey the most in the basis of amount are baby food and drink, sultanas and composte (Plum, fig, apricot, peach, cherry) In addition to general agricultural supports to producers performing organic agriculture, supports of 70 TL/da for vegetable-fruit, 10 TL/da for field crops will be granted in Turkey in 2015 with the decision of Board of Ministers No: 2015/7495 published in Official Gazette on 8 April 2015 and No: 29320. Support payments to be made to producers who practice ranching, to beekepers and to those who produce water products based on kinds are shown in Table 5. Official documents from which supports related to organic agriculture in Turkey are taken as a reference are as follows; • •

Communique on making payment of herbal production support (Communique No: 2015/21). Communique on making payment of support to organic ranching and organic water product cultivation (Communique No: 2015/31).

Table 1. Organic agricultural production data in Turkey in terms of years (including transition period) Years

The number of products

The number of farmers

Land cultivated (ha)

Natural gathering land (ha)

Total Production land (ha)

Production Amount (ton)

2002

150

12.428

57.365

32.462

89.827

310.125

2003

179

14.798

73.368

40.253

113.621

323.981

2004

174

12.751

108.598

100.975

209.573

377.616

2005

205

14.401

93.134

110.677

203.811

421.934

2006

203

14.256

100.275

92.514

192.789

458.095

2007

201

16.276

124.263

50.020

174.283

568.128

2008

247

14.926

109.387

57.496

166.883

530.224

2009

212

35.565

325.831

175.810

501.641

983.715

2010

216

42.097

383.782

126.251

510.033

1.343.737

2011

225

42.460

442.581

172.037

614.618

1.659.543

2012

204

54.635

523.627

179.282

702.909

1.750.127

2013

213

60.797

461.395

307.619

769.014

1.620.387

2014

208

71.472

491.977

350.239

842.216

1.642.235

Source: Anonymous, 2015a

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 Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey

Table 2. Organic products which were exported the most in Turkey in 2014 Product

Amount(Kg)

Sum ($)

% Kg

%$

Fig and fig products

4.523.936

21.626.691

29,09

27,5

Nut and Nut products

1.642.488

17.046.378

10,56

21,6

Sultanas

4.118.835

13.557.823

26,48

17,2

Apricot and apricot products

1.975.009

11.102.466

12,70

14,1

Fruit and Fruit products

1.292.370

8.595.480

8,31

10,9

Cotton and textile products

132.447

1.814.432

0,85

2,3

Pistachio

21.807

854.089

0,14

1,1

Lentil and kinds

365.123

709.020

2,35

0,9

Caper

76.125

604.698

0,49

0,8

Wheat and Wheat Products

845.340

364.871

5,44

0,5

Vegetables and vegetable products

56.256

347.835

0,36

0,4

Walnut

22.258

343.069

0,14

0,4

Total

15.071.994

76.966.852

96,9

97,7

General Sum (including others)

15.552.638

78.779.537

100

100

Source: Anonymous,2015b

Table 3. Countries to which organic product export was made the most in 2004 by Turkey Country

Amount (Kg)

Sum ($)

% Value

Germany

3.335.466

19.248.646

24,4

United States

3.782.712

19.053.760

24,2

France

1.488.675

8.507.402

10,8

Netherlands

1.254.091

7.075.308

9,0

Switzerland

1.190.599

6.217.360

7,9

The UK

998.137

4.446.227

5,6

Sweden

808.811

4.360.203

5,5

Italy

389.770

2.775.607

3,5

Japan

296.571

1.910.147

2,4

Denmark

250.452

1.201.498

1,5

Australia

211.130

1.038.758

1,3

Belgium

136.720

471.784

0,6

total

14.143.134

76.306.700

96,9

General sum (including others)

15.552.638

78.779.537

100

Source: Anonymous, 2015b

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 Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey

Table 4. Organic food import in 2014 Product Name Baby food and drink

Amount (Kg)

Country from which it is imported

1.532.148

Germany, Austria, Czech Republic, Poland

Sultanas

268.000

America, Netherlands, The UK

Composte (Plum, fig, apricot, peach, cherry)

178.592

Germany

Fruit kinds (Pear, strawberry, plum, Mandarin, Grapefruit)

122.502

Germany, Denmark, France, Netherlands

Dried fruit (Berry, Fig, Plum,date palm)

53.118

Afghanistan, Germany, Moldova, Poland, Tunisia)

Vegetables

24.120

Afghanistan, Germany

Medical smelly herbs(Daphne, thyme, locust Gum, Stevia)

23.612

America, Netherlands, The UK, Italy

Nigella and Nigella products

12.850

Germany, India

Ageve Syrup

8.500

The UK, Mexico

Nut

7.000

Germany

Coconut milk and oil

6.083

Sri lanka

Bread Mixture

4.300

Germany

Coffee and Coffee kinds

4.050

America, Belgium, Netherlands

Spreadable chocolate

2.548

Belgium

Kidney bean

2.322

France

Sunflower oil

1.824

Germany, Italy

Fruit tea and tea kinds

1.739

Netherlands

Fruit jam kinds

1.076

Belgium

Organic cookie with ginger

122

Afghanistan

Beemilk honey

116

Afghanistan

Sumach

20

Denmark

Source: Anonymous, 2015b

Table 5. Organic agriculture supports Product Fruit, Vegetable

Price 70 TL/decare

Farm crops

10 TL/decare

Mature cattle, water buffalo

150 TL/a head

Calf

50 TL/a head

Mature sheep, goat

10 TL/a head

Hive with bees

5 TL/a hive

Trout

0,35 TL/kg

Seabream, sea bass

0,45 TL/kg

Source: Anonymous, 2016a

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 Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey

• •

Investment management credit with low interest Decision of Board of Minsters (2014/7201 published in official gazette dated 21.01.2015 and No: 29244). Decision of Board of Minsters No:2015/8299 published in official gazette dated 16.12.2015 and no: 29564 on Having Investment and Management Credit with low interest for agricultural production used by TR Ziraat Bankası A.Ş. and Agricultural Credit Cooperatives.

Briefly, under the light of documents above, supports granted to organic agriculture in Turkey can be summarized in four main items. • • •

•

Land based support payment. Product based supports in Organic ranching. Having Investment and Management Credit with low interest for agricultural production used by TR Ziraat Bankası A.Ş. and Agricultural Credit Cooperatives (In 2016, the opportunity of credit use with 5.000.000 TL credit top limit with 50% discount from the rate of current interest rate has been provided). Support payments which are made to farmers who sign grant agreement and who participate in Protection of Agricultural Land with Environmental Purpose by FALM in order to protect soil and water quality in agricultural land, for the sustainability of renewable natural resources and taking required cultural precautions aimed at reducing negative effects of intensive agricultural activities are being made. Within this scope, 135 TL/da payment is being made to 3.category environmentfriendly agricultural techniques and cultural practices (Anonymous, 2012). In addition to these supports:

• • •

•

Vegetable market tax are being taken within the scope of “The law on Regulating trade of vegetables and Fruit from raw, semi-products or products and other goods which have sufficient supply and demand depth having organic agriculture certificates”. Within the scope of Communique on Supporting Environmental Costs, costs of certificate and analysis of organic products aimed at export. Expenditures of Certification and lab analysis (per certificate and/or analysis) are supported with the rate of 50% and up to 25.000 USD. Treasure lands are leased for 49 years to investments who undertake to make organic agriculture investment with the amount in TL equals to 10 million USD at least and employ 10 people at least for 10 years within the scope of the project. Entrepreneurs making organic product export benefit from export refund payments within the limits predicted. In addition, 600 TL support payment are being made to producers utilizing agricultural publishing and consultancy services. In order to agricultural entrepreneurs to be able to benefit from this support, they should be registered to farmer’s registry and/or greenhouse, water products, beekeeping, sheep-goad registry system (Anonymous, 2012).

SOLUTIONS AND RECOMMENDATIONS In order to create a difference in the market and enlarging marketing opportunities of countries in terms of global competition, first of all strategies about green marketing, developing conventional and organic

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 Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey

product potential, e-trade’s, which has various advantages, becoming widespread and supports’, given aimed at e-trade and marketing, becoming widespread in the dimension of farmers are needed. Using values and products especially specific to Turkey is important on the point of view of Turkey. When organic product production and export data of Turkey are examined, it is seen that it has not used the potential it has sufficiently and efficiently. But Turkey, whose climate and soil conditions are already suitable for agriculture, is an appropriate country for organic agriculture system because it has lots of biological and genetic diversity. In this case, organic production level should be increased much more and in addition to this it should be encouraged more. In order for environment-friendly organic agriculture to settle as a sustainable and preferred agricultural system, producers should be motivated, encouraged to this system, and in addition they should be enabled to get more profit than conventional agriculture. Otherwise, producers will not adopt and continue this system especially, when it is considered that income is low in organic agriculture, producers need to be supported especially in transition period. In addition, supports granted to organic agriculture by the state should be increased and conversion of producers to organic agriculture should be encouraged. Research, training and publishings related to organic agriculture should be generalized by the state, private sector and NGOs. As a result of this, it is thought that both the incomes of producers increase and important amount of contribution will be provided to the economy of the country. In developed and especially developing countries, some problems in both technical and economic sense are faced in transition towards organic agriculture. One of the most important of these is deficiency of technical knowledge and personnel related to the subject. Organic product raising techniques are a system which needs special knowledge and technology at each stage from production of product, even from preparing soil to collecting, processing, and packaging and distribution stages and which bring a number of rules together with it. Provided that Farmers and industrialist advance their technical knowledge and skills continuously, organic agriculture will be able to develop. Because of this, if expert personnel is added to support items to be granted by the state, it should be enlarged in a way that it will include salary and insurance Premium. There are some differences in two items within production cost in organic agriculture when compared to other systems. One of these is the cost of certification and the other is the need of increasing work power. This additional work power need may be thought to be employment booster from the point of businesses whose family work power is high. But, it causes foreign work power need to increase in other businesses and to cause work power cost to increase. On the other hand, certification cost causes negativeness for both types of businesses. This condition does not leave any other choice other than contracted production for small businesses. In order to remove problems showing up at the marketing stage of organic products produced, contracted cultivation concept comes to the forefront here. Thanks to this, both producers market their products they have produced easily and industrialists gain the guarantee of obtaining raw material required with the quality and amount they request. Target for the next a couple of years should be determined and market share and growth rates should be followed according to this. Contact offices that will give consumers information about it should be formed. Questions and problems of producers should be removed via these offices, required applications for incentives should be able to be made. Because it is known that Province directorates of Food, Agriculture and Livestock ministry are dealing with intensive bureaucracy and personnel problems, it is obligatory for a separate organization structure for organic agriculture to be established. In addition

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 Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey

to this, agricultural engineers who will carry out consultancy for organic agriculture should be trained and assessed separately. It is targeted for the energy used in transportation by consuming products produced in organic agriculture domestically. Nevertheless, products are sent to different parts of the world and it is observed that it has a similar structuring to conventional product trade. Therefore, classic supports as well as logistic supports should be provided. Certification and branding in organic products’ opening to world market are among indispensable works. Producers should be supported and their costs should be covered for these. Although some deficiencies are generally in policies of developing countries related to organic agriculture, the advantages that they have should be remembered. In organic agriculture, there is no need for big investments for irrigation, energy and outside inputs. But investment is needed in order to make production by giving importance to especially trainings and researches. Additional supports for these should be provided to universities and research institutes. R&D activities conducted by public and private sector institutions related to organic agriculture is limited although they have increased with the efforts of some university research institutions in recent years. R&D works in organic agriculture should be supported continuously. One of the most important steps to be taken is that more agricultural (especially as aimed at organic agriculture) R&D activities should be encouraged in Technoparks which continue their activities under the coordination of universities and which are established in some parts of Turkey. Technics and technologies used in organic agriculture are acceptable indicators in terms of green marketing with current condition. So, it is not necessary for new environmental systems with more cost as in conventional production systems to be formed. However, following new technologies produced on this subject may be useful for differentiation of organic producers and for being favored in the market more. It is significantly important to consider differences the business is within in the use of new technologies in organic agriculture. The new technology produced should be examined thoroughly with regard to location of the business, species produced, kind and business capital and should be adopted according to this. Especially as new packaging technologies, compostable packages, reduced production materials or those that may be used with different purposes, technological systems which increase the efficiency in water and energy use during production process and recycling involve techniques and technologies that may form differences depending on business and that may be used in organic agriculture within green marketing perception. In order them to be able to follow the technologies which improves fast in these matters, limits of supports of current technological renewing and capacity increasing applied to SMEs should be enlarged in a way that will be valid for organic agriculture producers. Although export of organic agriculture products in Turkey is increasing more and more, the share of the country in organic agriculture and food products market is too low. Especially, supply of organic agriculture and food products in North American and European countries cannot meet demand increase in these markets. Therefore, these markets present a good opportunity for developing countries whose ecology and infrastructure is suitable for organic agricultural production and export like Turkey. Unfortunately, organic products which are exported as raw material without being processed such as dried fruit, nut, peanut and field corps and etc. mean loss in potential export revenues. In this sense, consultancy and technical support should be provided to producers in order for them to produce processed production not raw material. So added values will have stayed within the country. Because of limited works of non-governmental organizations (NGO) with local quality, organic agriculture and food market in Turkey is far from reaching the level intentioned and targeted. Besides, deficiency of cooperation between public, private sector and NGO’s and that there is no knowledge 31

 Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey

sharing network confront us as another critical question. The numbers of producer cooperatives and organizations formed by producers’ making organic production coming together is limited. Because they cannot get sufficient incentives from governments, they cannot defend their rights against private sector sufficiently and they cannot play an effective role in organic agriculture and food product market. FALM should apply suitable incentive instruments and polices via especially organic producer unions, NGOs or private companies or directly to producers in order to ease transition process of producers towards organic production via financial incentives such as credit with low interest, premium price, cheap organic input and marketing guarantee. Similarly, FALM should support organic producer organizations via research, training and publishing activities. Organic agriculture should be encouraged via public and private institutions with pilot projects in places whose ecology is suitable for organic agriculture in order for organic agriculture to be adopted and become widespread. In addition to organic herbal production at which we are good, special importance should be given to organic animal production which is too limited in order to increase export potential of Turkey in the world’s market of organic agriculture and food where a great completion are lived and required encouragement precautions should be taken in order for it to improve. In addition to organic marketing companies working as aimed at export, especially local organic producer unions should be supported financially by the government. In order for organic production and domestic market of organic food to improve, process of organic production, control, certification and marketing which are complex should be eased via required legal regulations. In recent years, Conformity of the legislation of our country to the works done in order to simplify organic agriculture legislation in EU should be enabled. Works aimed at increasing consumer awareness about organic agriculture and food products via works of raising awareness of consumers should be increased. Turkish organic agriculture sector should be coordinated with the help of a high council to be formed and cooperation should be increased between related institutions. Data aimed at organic production and export should be gathered single-handedly, a reliable database should be formed and results should be published officially. Works of product branding and labeling which are wrong like “Natural”, “village product”, “without fertilizer”, “without pesticides” organic agriculture and food product or which are used to mislead consumers and which causes concept confusion should be terminated legally. In order to increase consumer trust in organic products, project management, and control and certification process of organic products should be brought into conformity with international Organic Agriculture and food legislation and standards. Organic agricultural production works should be integrated with ecologic agricultural tourism services within the country and local practices should open to international ecotourism field. In addition to this, trade of organic products other than organic agriculture and food products (such as organic cosmetics, textile, wood, tree and local handcraft products etc.), production processes which do not pollute environment and which are compatible with ecology should be encouraged.

FUTURE RESEARCH DIRECTIONS The most important subject emphasized usually in the studies where Organic agriculture in Turkey is examined is that Eastern and Southeastern parts of Turkey are very suitable for organic agriculture. But, Eastern and Southeastern parts of Turkey are also the most problematic geography of Turkey socio-economically. Because of terrorism lived for years, these regions are in the last places of regional

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 Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey

development ranking. In addition, the provinces in this region are in the last places of economic and social criteria such as education, employment and growth. It is a reality which is known and accepted by everyone that supports, subsidies and donations granted in these regions are not used efficiently and effectively at desired level. Because of terrorist activities, which have increased recently, the number of investors coming are very limited even if the region is the place where investments are encouraged the most. As in all kinds of investments, the most important factor for people who want to make investment in organic agriculture is the feeling of security. Therefore, in addition to supports and incentives granted, formation of atmosphere of security and stability in especially Eastern-Southeastern region should be primary goal. One of the most important ways of being able to give the required feeling of security to investors and getting rid of deadlock stated above is to bring Government Business Enterprises (GBE) which were carried out as an effective policy in a period to the agenda again with the occasion of organic agriculture investments. The state can collect private enterprises and entrepreneurs in the GBEs within by controlling supervision mechanism and administrative mechanisms. In the structure of GBEs are partnership structures which are established between private sector and the public in general. So, investors who feel the support of public on their back can make investments more comfortably and securely. This model was applied in Kibbutz farms in Israel and gave positive results. Similar structures may be formed in Turkey. Local people can carry out organic agricultural activities jointly on their own land or on treasure land by working in coordination with the state. With this occasion, wrong use of supports and subsidies granted may be avoided. This system will be an important argument in the solution of unemployment which is one of the biggest problems in especially Eastern and Southeastern Region of Turkey. In the periods ahead, researchers may concentrate on this subject. And benefit of probable organic agriculture GBEs that will be formed may be discussed.

CONCLUSION In recent years, the greatest agricultural successes are to be found in being able to realize production increases by reducing negative environmental conditions. This is only made possible by using sustainable and environmentally friendly methods in agricultural production. Green Marketing practices bring an agenda of activities aimed at increasing the use of organic methods in the agricultural sector. Communities around the world are becoming increasingly aware of the environment and its effect on human health. As this awareness increases, the demand for organic products will also increase. As the production of organic produce rapidly increases around the world, this will cause competition between developing countries in the international market. Turkey is in a position to be one of the most important countries with a say in the global market for organic produce, if it can activate its potential in this field with timely interventions. When Organic Agriculture becomes economically viable, it can generate new employment opportunities and can reveal the new organic products of input giants. It also protects the environment, meets the quality demands of consumers, generates alternatives with regard to rural welfare, and provides increased added value with new products. In terms of sustainability, although organic agriculture has its weaknesses and strengths, its greatest strength can be summarized as the continuity of soil and water resources, thus

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 Practice of Green Marketıng Activities in the Organic Agricultural Sector in Turkey

protecting and maintaining the continuity of agricultural production. In terms of protecting soil resources, it is important to prevent agricultural land from being used for purposes other than agriculture. Rich biological diversity, relatively clean ecological areas, plant species that are resistant to diseases and pests, and low levels of chemical input are among the main advantages that would come with the development of organic agriculture in Turkey and other developing countries. Therefore, Turkey has great potential to develop and produce a number of products (though not some tropical fruit) because of its ecology, geographical and topographical structure, and various climate characteristics. In addition, the agricultural production system in Turkey is spread over a very large area. Compared to industrialized countries, Turkey’s use of chemical input per unit area of agriculture is very low. As a result, there is no intensive pollution in its agricultural land, especially in the Eastern part of Turkey, where the transition towards organic agriculture would be easier than in industrialized regions. Therefore, Turkey can avoid the environmental problems associated with intensive chemical input in agriculture, which is a problem in a number of developed countries. On the other hand, rural employment can be helped by increasing the organic production of labor-intensive products with high added value. As a result, the development of organic agriculture in Turkey should be accelerated, together with: • • • • •

The financial support of governments for types and figures increasing. Producer and consumer training. Universities and research institutions’ increasing their R&D activities. The continuous informing the public with visual and written media tools. The publishing of agricultural and research studies Cooperation with the private sector and NGOs.

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This research was previously published in Green Marketing and Environmental Responsibility in Modern Corporations edited by Thangasamy Esakki, pages 136-163, copyright year 2017 by Business Science Reference (an imprint of IGI Global).

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Chapter 3

Rights of Nature to Protect Human Rights in Times of Environmental Crisis Susana Borràs Rovira i Virgili University, Spain

ABSTRACT The well-being of humans and nature are inextricably linked. Nature is particularly mistreated in light of its characterization as merely “property” to be bought, sold, and ultimately degraded for profit. Reinforcing this misperception is the fact that modern environmental laws themselves implicitly accept this claim of “nature as property.” They legalize nature’s destruction by dictating how much of the environment can be exploited and degraded, rather than as an integral ecological partner with its own rights to exist and thrive. Instead, we need laws grounded in the inherent rights of natural world to exist, thrive, and evolve. The article focuses on the transition from the ‘right to the environment’ to a biocentric approach constructed around ‘rights of nature.’ This transition is evident in various new legal instruments, which serve as models for legal systems that can steer us towards more robust and effective environmental laws.

I. INTRODUCTION: FACING NEW CHALLENGES ON ENVIRONMENTAL PROTECTION1 The possibility to recognize and protect the Rights of the Nature is, with no doubt, a brand new approach in the field of environmental law. Traditionally, legal systems have considered nature as a “property”, as an object over which human rights have been recognized and protected. Moreover, the promotion of laws and contracts to guarantee the property rights of individuals, corporations and any other legal entities as subjects of rightshave been common. The consequence, therefore, is that environmental laws and regulations, despite their preventive approach, have been developed over the last years in a way that recognize and legalize environmental harm. The amount of pollution and degradation allowed in the environment has been regulated within the legal framework and in some cases foresee the potential for environmental degradation. DOI: 10.4018/978-1-5225-9621-9.ch003

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 Rights of Nature to Protect Human Rights in Times of Environmental Crisis

Therefore, the human rights approach would offer a chance to protect the environment, conceiving it as a necessary dimension to enhance the most fundamental human rights. Certainly, the recognition ofindividual rightsin relation tothe environmenthas had a significantinfluence at supranational level. However, in general, the level of recognition of a human right to an adequate environment has not been without controversy: first of all, the protection of the environment through the configuration of a human right to an adequate environment rather than imposing obligations to protect the environment has no positive impact on the conservation of natural resources; secondly, the recognition of the protection of the environment is not really an individual right, but a programmatic norm lacking forcibility and, therefore, not required to the State (Bedoya, 2006). Differently, a new approach is emerging, the recognition of the rights of nature, which imply a holistic approach to all ways of life, including all ecosystems. In recent years, a series of normativeprecedents have surfaced, which recognize nature has certain rightsas a legal subject and holder of rights. These precedentscontribute, together with greater sensitivity to the environment, to areorientation ofhow to protect the environment, considering the Earth as the center where life takes place. Therefore, the rights of nature are recognized as a holistic concept comprising all kinds of life and their ecosystems. Through this perspective, called “biocentrism”, Nature is not an object of protection anymore, but a real subject of rights, with fundamental rights as any other subject has, for example the right to exist, to survive and to maintain and regenerate vital cycles. The implication of this recognition is that human beings have the legal authority and responsibility to enforce these rights on behalf of nature. This concept is based on humans as part of life on earth having to live within its ecological limits, rather than being the center of environmental protection as the “anthropocentric” approach proposes. Recognizing the rights of nature, Ecuador, Bolivia and a growing number of communities in the United States are basing their environmental protection policies on the premise that nature has inalienable rights, as have human beings. This premise is a radical but natural move away from the assumption that nature is a property under the rule of human law. Certainly, this view is a departure from Western culture and the development model which promotes the destruction of environment and life: climate change, disappearance of natural areas, indiscriminate surface felling of trees, desertification of new territories, dumping of toxic substances from industries into rivers, seas or lakes, oil slicks caused by ships and endless actions of a system that appears to legitimize environmental damage. This article, tracks the change in approach from anthropocentric to biocentric, which allows for an evolution in the legal protection of the environment: from human rights to the rights of nature. This new vision of environmental protection and how it is introduced into the different regulatory systems and its implementation is analyzed, including the recent trend in attributing a greater role to human responsibility in environmental protection. The article also discusses these new regulatory precedents, which undoubtedly mark an evolution in environmental law, both nationally and internationally. This new way ofprotecting the environment, due to the awareness of events, has led to the adoption of legislative measures on environmental law aimed at achieving an environmental policy more consistent with the conservation of natural resources, and establishing offenses andsanctions pointing more to the responsibility of those human beings who damaged nature. Nature meets its obligation to support life while humans increasingly take advantage of natural resources, causing irreversible environmental damage. This article explores how this recognition involves a number of issues to be resolved, as to who is able to claim these rights (on behalf of Nature) and how to make the legal system defend them.

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II. THE ENVIRONMENTAL PROTECTION THROUGH HUMAN RIGHTS APPROACH The traditional perspective to protect the environment has been “anthropogenic” based on the idea that a healthy environment is inherent for the dignity of every person. This concept necessarily takes for granted other human rights, including the right to life and human development. The indivisibility and interdependence exerted by the right to environment on the other human rights is evident: it strengthens and extends the meaning of already secured rights or rights, which, like the right to environment, are in the process of being set up. For example, the right to environment reinforces the content of the right to life, that is, a right to a dignified life in environmentally suitable conditions to promote healthy human development. The fact that there is interdependence between environmental rights and other fundamental rights has actually divided the doctrine, in the sense that few understand that the right to environment reinforces the content of other rights and what should be done is to integrate environmental aspects into the definition of other human rights.In this respect, there is a need to recognize a right to an indivisible and substantive environment, being the reflection of social demand to live in a decent and ecologically suitable environment, where the person can develop in harmony with nature (Déjeant-Pons, 1994). The existence of a growing social concern about the state of the environment and scientific alarm alerting us to the serious consequences of economic growth without limits requires the need for environmental protection through the adoption of international legal measures as well as regional and national ones. The Universal Declaration of Human Rights of 1948 (UN, 1948), although being a document that does not explicitly relate to environment, is the first legal basis on which they could settle the right to an adequate environment. Article 25 states that “everyone has the right to a standard of living adequate for himself and his family, health and well-being ...”. Subsequently, the International Covenant on Civil and Political Rights (UN, 1966a) and the International Covenant on Economic, Social and Cultural Rights (UN, 1966b), both of 1966, indirectly refer to the right to a healthy environment, relative to the right to life, as Article 6 of the International Covenant on Civil and Political Rights states by the express provisions the need to improve the environment as one of the requirements for the proper development of the individual. For example, Article 11 of the International Covenant on Economic, Social and Cultural Rights, when it recognizes the right of all people to an adequate standard of living and to the continuous improvement of living conditions; or Article 6 of the International Covenant on Civil and Political Rights, when a reference to the universal right to life is made. In this regard, the Human Rights Committee has stated: The term ‘the right to life is inherent in the human person’ cannot be understood in a restrictive manner (...) the protection of this right requires the adoption of positive measures by States. In this respect, the Committee considers it appropriate that States take all possible measures to reduce infant mortality and increase life expectancy, especially adopting measures to eliminate malnutrition and epidemics. (UN Human Rights Committee, 1982) Therefore, the right environment is not a result of social development but a prius for human existence. Logically, suitable environment precedes the law itself: without a suitable environment, there are no humans, no society, no law…(Gormley, 1990, p. 97).

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The first written suggestion that there should be a human right to a healthy environment came from Rachel Carsonin her book Silent Spring, published in 1962: If the Bill of Rights contains no guarantees that a citizen shall be secure against lethal poisons distributed either by private individuals or by public officials, it is surely only because our forefathers, despite their considerable wisdom and foresight, could conceive of no such problem. (Carson, 1962, pp. 12-3) But the first formal recognition of the right to environment occurs in the United Nations Declaration on the Human Environment, Stockholm, 1972 (U.N. GAOR, 1972), which states in Principle I that the person has the fundamental right to freedom, equality and the enjoyment of “satisfactory living conditions in an environment whose quality allows him to live with dignity and welfare”, and has a solemn obligation, in return for this right, “... to protect and improve the environment for present and future generations.”. This principle states that in addition to the rights for first and second generations, man has a “fundamental right” to enjoy adequate living conditions in an environment the quality of which allowsdignity oflifeand well-being, that is to say, a life, which will enhance the rights of future generations. This idea is expressed in the Preamble to the Declaration, paragraphs 1 and 2, stating that “the two aspects of human, natural and built environment are essential to human well-being and to the enjoyment of fundamental human rights, including the right to life”, adding later that “the protection and improvement of human environment is a major issue which affects the well-being of peoples and economic development throughout the world, (...), and the duty of all governments”. Despite this express recognition in an international document, the Declaration does not provide the necessary control mechanisms to make them effective and also is a non-legally binding document. From the substantive content of human rightspoint of view, after the 1972 Stockholm Declaration there has been a major trend in national legal orders towards recognising the environment –often at a constitutional level–as a specific right with different characteristics, depending on the political context and legal traditions of each country. In similar terms, Article 1 of the Charter of Environmental Rights and Obligations of Individual, Groups and Organizations, adopted in Geneva in 1991, provides that: “All the Human Beings Have the basic right to an environment adequate for their health and well-being and the responsibility to protect the environment for the benefit of present and future generations”. Subsequently, the World Commission on Environment and Development UN proposed as a legal principle: “All human beings have the fundamental right to an environment adequate for their health and welfare” (UNEP, 1987). Similarly, in 1990, in its Resolution 45/94, the General Assembly adopted a milder version of this formulation: “Everyone has the right to live in an environment adequate for their health and welfare.”(UN, 1990). The Rio Declaration on Environment and Development of 1992 (UN, 1992) consolidated this trend by pointing out in the first Principle that all human beings are at the centre of concerns for sustainable development and are entitled to a healthy and productive life in harmony with nature. However, this Principle of the Rio Declaration loses firmness in relation to the provisions of the Stockholm Declaration, and as with the Stockholm Declaration, no accurate means exist to enforce the principles of the Declaration. Despite these shortcomings, both the Stockholm Declaration and the Rio assume an important role in the recognition of environmental problems and are a step in the development of international environmental law. In later lectures on Sustainable Development in Johannesburg in 2002 and Rio de Janeiro in 2012, it was possible to proclaim the right to a healthy environment. Parallel to these developments in the recognition of the human right to environment, in the field of the Economic and Social Council (ECOSOC) of the United Nations, the Sub-Commission on Prevention of 41

 Rights of Nature to Protect Human Rights in Times of Environmental Crisis

Discrimination and Protection of Minorities, under the Commission on Human Rights, has carried out important work. This has covered the harmful effects of the illicit movement and dumping of dangerous and toxic waste and products on the enjoyment of human rights, as well as the issue of human rights and the environment, through the work of the special Rapporteur Mme. Fatma Zohra Ksentini. This special Rapporteur carried out work in relation to the issues of dangerous products and waste dating back to 1989. As a result, the Subcommittee (coming out of the Sub-Commission on Prevention of Discrimination and Protection of Minorities)2 concludes that the information available to them on human rights and environment, including “Environmental Perspective to the Year 2000 and after”, justified the need for a study of the environment and its relationship with human rights (UN, 1989). Following the studies conducted in 1994 Mme. Ksentini presented a final report in which a concept of human rights and the environment is much closer to Principle I of the Stockholm Declaration of 1972 than the Principle I of the 1992 Rio Declaration.3 The main conclusion of this report is that there has been a change in environmental law to provide the right to a healthy and decent environment. This right is part of the existing international law and has the capacity for immediate implementation through bodies dedicated to the protection of human rights. According to this report, the substantive elements of environmental rights include the right to development, life, and health and have procedural aspects such as public participation and access to effective national solutions. Attached to this report, there is the draft of the Declaration of Principles on Human Rights and the Environment, an overview of consultations with NGOs between 1990 and 1994, and a summary of national legislation and practices compiled by the Special Rapporteur based on the responses received from 67 governments. Despite the important content of this document, there has been no attempt to complete this project, neither by the General Assembly nor by the Human Rights Commission nor the Economic and Social Council. Only the United Nations General Assembly in its Resolution 45/1994, adopted on December 14 1990, states that everyone has the right to live in an environment adequate to ensure their health and well-being. Similar expressions are found in various multilateral treaties dedicated to environmental protection, such as the Convention on Biological Diversity, 1992; the 1992 United Nations Framework Convention on Climate Change; the United Nations Convention to Combat Desertification in Those Countries Experiencing Serious Drought and/or Desertification, particularly in Africa, 1994; and Convention 169 of the International Labour Organization on Indigenous and Tribal Peoples in Independent Countries 1989. It is also necessary to add that the Institute of International Law, in its 68th session in Strasbourg in 1997, stated in Article 2 of its Resolution n. 1 of September 41997 “... every human being has the right to live in a healthy environment” (IDI, 1998). Moreover, the 7th Goal of the Millennium Development Goals was about ensuring environmental sustainability, including the incorporation of the principles of sustainable development into countries’ policies and programmes to reverse the loss of environmental resources (UN, 2000). Later, in 2007, the UN General Assembly adopted the UN Declaration on the Rights of Indigenous Peoples, which in article 29 proclaims “Indigenous peoples have the right to the conservation and protection of the environment...” (UN, 2007). In March 2012, based on several other resolutions related to human rights and the environment and human rights and climate change, the Human Rights Council during its 19th session, established by Resolution 19/10, the mandate of the human rights and the environment (HRC, 2012a), which aims, among other things, to study human rights obligations related to the enjoyment of a safe, clean, healthy and sustainableenvironment, promoting best practices regarding the use of human rights in the formulation of environmental policies.4 In the first report of December 22 2012 on the issue of human rights

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obligations related to the enjoyment of a safe, clean, healthy and sustainableenvironment, states and others concerned are urged to remember that the lack of a full understanding of the contents of all the human rights obligations related to the environment should not be interpreted as that such obligations do not exist (HRC, 2012b). In June 2012, at the UN Conference on Sustainable Development, States renewed their commitment to “the promotion of economically, socially and environmentally sustainable future for our planet and for present and future generations” (UN, 2012), without asserting the real right for humans to a healthy and safety environment. In general, linking human rights with the environment creates a rights-based approach to environmental protection that places the people harmed by environmental degradation at its center, but leaves the environment undermined to people needs.

III. HUMAN RIGHTS PROTECTION WITHOUT PROTECTING NATURE? The formal recognition of a universal right to an adequate environment faces a number of obstacles, which have led to a sector denying its existence. In part because this right departs from the utilitarian and anthropocentric perspective, which has allowed the existing formal recognition of such right, but it has not been enough to protect nature, biodiversity and even the human health. The major obstacles have been the traditional notion of state sovereignty, the lack of legally binding instruments and the unenforceability of this right due to the legal uncertainty of the protected object and the legitimacy of the holders. This leads to an absence of effective means for its defense and implementation of its protection. However, this has not prevented the protection of the environment, as part of the contents of a new human right by various international instruments. While it is true that currently there is no legally binding international instrument declaring a human right to the environment for the implementation of other fundamental rights. The recognition of this right, however, can be sensed in the existing international consensus to protect the environment for the benefit of humans. However, a suitable and quality environment does not presuppose respect and guarantee of human rights. The idea is well-established in international law that States should take measures to ensure respect for and protection of the environment as essential to the fulfillment of human rights (Lewis, 2012, p. 36). Considering that a suitable environment is a necessary component of human rights is also a priority for the competent bodies of the United Nations on the matter. As of 2012, 177 of the world’s 193 UN member nations recognize this right through their constitution, environmental legislation, court decisions, or ratification of an international agreement, among these, some subnational governments recognize the right to a healthy environment, including six American states, five Canadian provinces or territories, and a growing number of cities. One of the biggest obstacles to the recognition of this right lies in state sovereignty; that is, the set of powers, which a state exercises exclusively on their territory recognized by the international order. Currently the only existing limit on the sovereign exercise of the functions of environmental management and imposed by international law is to manage the environment in a way that other States are not disadvantaged by the misuse of the natural resources. This question is contained in Principle 21 of the Stockholm Declaration, which states: In accordance with the UN Charter and the principles of international law, States have the sovereign right to exploit their own resources pursuant to their own environmental policy and the obligation to

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ensure that the activities carried out within their jurisdiction or control do not cause damage to the environment of other States or of areas beyond national jurisdiction. (UN, 1972) Also, the Rio Declaration in Principle 2 (UN, 1992) reproduces the provisions of Principle 21 of the Stockholm Declaration. Another obstacle to the recognition and realization of the right to the environment, which is already been referred to above, is the absence of a legally binding international instrument that explicitly recognizes this right. Some authors such as Makarewicz understand that documents like the Declaration of Stockholm or Rio constitute a generally accepted interpretation of the notion of human rights contained in the United Nations Charter (Makarewicz, 1986, p. 81). Handl and others (1995, p. 287) state that even if in some state practices this right does not separately exist, those states understand the right to environment is implied in inalienable rights, which cannot be knocked down, but in practice, this is not the case related to the right to environment. Nevertheless, within the limitations of economic and social rulings, the right to environment gets stronger. Despite the “soft law” character of the international instruments, which recognize the right to environment, this right is inalienable qualifying; while the environmental degradation threatens the survival of humankind. Moreover, the flexible nature of existing instruments in this area can provide the further development of legally binding instruments, because “…when new values emerge, they need first to be so formulated as to pave the way for future developments in the form of binding instruments.” (Kiss, Cançado Trindade, 1995, p. 287). In fact, the various aforementioned international instruments reflect the willingness to recognize the human right to the environment both for environmental protection and to ensure human survival. In this sense, perhaps the only way to articulate a human right to the environment is through the recognition of the existence of an international tradition generated by a constant and repeated international legal practice, along with the willingness to conceive this human right to a healthy environment (Lee, 2000, pp. 308-09). Lee states that consecutive unreserved reinforcement of this right in different non-binding documents constitutes an evidence of a comprehensive and consistent practice of States in the international arena. This practice can contribute to the final creation of a right to a proper and healthy environment as a principle of customary international law. Another present difficulty in the recognition of the right to the environment is the inability to exercise the right to environment properly before the court because of the indecisive nature of the legal concept of “environment” and the lack of procedural mechanisms to invoke its protection. These obstacles prevent full recognition of a right, which is still in formation, but its implementation can be promoted by establishing mechanisms such as information, participation, resources and education to influence the political will of the states and enable a human right to the environment to be legally binding. Legal systems seem to ignore the current social impulse, which recognizes the right to environment only acknowledging the legal status of other human rights. This clearly reflects which difficulties international human rights theory poses for the introduction of ecological limitations into international human rights law. In some sense, because the anthropocentric perspective, which is also the case for traditional western view of development and progress, centers on humans and it implies that humans are separate from Nature; in short, Nature is just a basket of resources that humans must take advantage of to feed economic growth (Gudynas, 2011, p. 262). Based on the idea that the anthropocentric, a human right to environment is required to protect the most vulnerable people to the impacts of environmental degradation, but this view should to be combined with a complementary approach to protect the environment with the protection of human rights. 44

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IV. TOWARDS THE PROTECTION OF NATURE In current legal systems, our living Earth is perceived as an object without rights. Yet fictitious entities, such as corporations, are granted rights similar to those of humans without reciprocal and enforceable responsibilities and accountability. Since the existing environmental and human right laws are not enough to protect nature, biodiversity and human health, the destruction of our Earth continues, and without redress. Therefore, another approach to environmental protection is required. The so-called “biocentric approach”, developed mainly by mega-diverse countries and developing with indigenous populations, offers a different world view raising the “anthropogenic” to recognize and protect nature as having rights and as a legal entity. This possibility is certainly a novel perspective on environmental law, as it departs from the above-mentioned perspective. As already discussed, traditionally legal systems have regarded nature as “property”, an object on which to develop and protect rights. The most common has been the promotion of laws and contracts to protect the property rights of individuals, corporations and other legal entities, such as legal subjects. The consequence is that the laws and regulations on environmental protection, which have mushroomed in recent times, despite emphasizing the preventive orientation, actually legalize environmental damage by regulating how much pollution or destruction of nature may occur in the context of the law. Even the recognition of the human right to the environment or the environmental dimension of the human rights has not been sufficient to ensure the protection of the environment and the welfare of the people. This approach is not free of criticism, in the opinion of Bosselmann (2001, p. 108): […] in the long term the existence of an environmental human right could be seen as self-contradictory. A better option is the development of all human rights in a manner, which demonstrates that humanity is an integral part of the biosphere, that nature has an intrinsic value, and that humanity has obligations toward nature. In short, ecological limitations, together with corollary obligations should be part of the rights discourse. The recognition of the rights of nature is an integral holistic view of all lifestyles comprising all ecosystems. Through this perspective, nature is no longer protected, but a subject of protection rights granted to nature in all forms of life, has the right to exist, persist, maintain and regenerate its vital cycles. The counterpart to this recognition means that humans have the legal authority and responsibility to enforce these rights on behalf of nature. This conception is based on humans as part of life on earth and living within ecological limits and therefore as Caldwell has observed: “Humanity has no extraordinary moral claim or rights over the natural world.” (1972, pp. 236). The “biocentric” view arises from the severity of the environmental status and the threat on natural ecosystems. The conception “biocentrism” is based on the idea that humans are part of nature and that nature conservation is, above all, a duty of human beings: both must coexist for the perfect organic balance of the planet (Lanza & Berman, 2009). According to this argument, any form of life is important to the balance of nature (Emmenegger & Tschentscher, 1994, pp. 545-92). The idea that nature possesses inalienable rights akin to human rights has gone from a strictly theoretical concept to the basis for policy changes in several countries. To recognize the rights of nature Ecuador in its constitution, Bolivia in its legislation, and a growing number of communities in the United States, are basing their environmental protection systems on the premise that nature has inalienable rights, as do humans. This premise is radical but natural, emerging as a reaction to “anthropogenic” forces that

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subordinate the environmental protection to the interests and / or human needs, reducing nature to a mere property, under the rule of law (Galeano, 2008).

1. Changing the Approaches to Protect the Nature Following this other perspective of environmental protection, one of the first cases in which the rights of nature appear was the historic case of environmental law on the redwoods of California (Sierra Club v. Morton) in 1972, where the excessive corporate profit motives aimed to turn the habitat of huge old trees into an amusement park. It created a legal battle in which judges and academics questioned whether the trees should be entitled to a judicial proceeding (Pelizzon, 2011, pp. 6-12). In his dissenting opinion, Judge William O. Douglas argued that “inanimate objects” should legitimately to sue before the courts: The critical question of “standing” would be simplified and also put neatly in focus if we fashioned a federal rule that allowed environmental issues to be litigated before federal agencies or federal courts in the name of the inanimate object about to be despoiled, defaced, or invaded by roads and bulldozers and where injury is the subject of public outrage. Contemporary public concern for protecting nature’s ecological equilibrium should lead to the conferral of standing upon environmental objects to sue for their own preservation. This suit would therefore be more properly labeled as Mineral King v. Morton. (Sierra Club v. Morton, pp. 742-43) Douglas continued: Inanimate objects are sometimes parties in litigation. A ship has a legal personality, a fiction found useful for maritime purposes. The corporation sole—a creature of ecclesiastical law—is an acceptable adversary and large fortunes ride on its cases.... So it should be as respects valleys, alpine meadows, rivers, lakes, estuaries, beaches, ridges, groves of trees, swampland, or even air that feels the destructive pressures of modern technology and modern life. The river, for example, is the living symbol of all the life it sustains or nourishes—fish, aquatic insects, water ouzels, otter, fisher, deer, elk, bear, and all other animals, including man, who are dependent on it or who enjoy it for its sight, its sound, or its life. The river as plaintiff speaks for the ecological unit of life that is part of it. (Sierra Club v. Morton, p. 743) As Berry (2014) explains, every being in the Earth Community has three rights: the right to be, the right to habitat, and the right to fulfil its role in the ever-renewing processes of the Earth community. This same reflection, led several authors from around the world to address this issue (Frazier Nash, 1989; Hanna et al., 1996; Boyle, 2006; Harding, 2007; Cameron, 2007). To mention a few: Stone (1972; 2010) in the United States, Godofredo Stutzin (1984, 2002) in Chile, or Cormac Cullinan (2002, 2008 and 2011) in South Africa. A few years later, in 1982, over one hundred member states of the General Assembly of the United Nations adopted the World Charter for Nature, which states that “Humanity is a part of nature and life depends on the uninterrupted functioning of natural systems which ensure the supply of energy and nutrients” and provides a set of principles to be considered by man in their procedures with respect to the environment (UN, 1982). In this sense, the article establishes the duty of every person to act in accordance with the provisions of the Charter and to ensure the objectives set out in the Charter. This document recognizes the intrinsic value of nature and human beings aspart of nature, and it calls for humans to be

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guided by a moral code of conduct that does not compromise the integrity of those other ecosystems or species with which they coexist. It also regulates that human activity must be developed according to the earth limits and processes, and according with the common equity and the precautionary principle. The Charter states, “Humanity is part of nature and life depends on the uninterrupted functioning natural systems that are sources of energy and nutrients. Every form of life is unique, warranting respect regardless of its worth to human beings and other living things for recognition; man must be guided by a moral code of action”. Ashby (1978, pp. 82-5) asserts that no one can predict the full consequences of tinkering with any part of an ecosystem. Even the non-living environment has properties without which life as we know it would be inconceivable. Consequently, the author continues, “the rights of nature” must be protected by law. Regarding the nature of Rights, Thomas Berry (Bell, 2003) explains that: 1. All rights are role-specific or species-specific, and limited. Rivers have river rights. Birds have bird rights. Insects have insect rights. Humans have human rights. Difference in rights is qualitative, not quantitative. The rights of an insect would be of no value to a tree or a fish. 2. Human rights do not cancel out the rights of other modes of being to exist in their natural state. Human property rights are not absolute. According to Stone (1972, p. 489), one of the strengths of regarding natural objects as bearers of rights, Stone contends, is that it would reflect a fundamental shift away from the current view that nature exists for men. In 2000, a group of non-governmental organizations and movements adopted the Earth Charter, which “seeks to inspire in all peoples a sense of global interdependence and shared responsibility for the welfare of the human family, the greater community of life and future generations” (Earth Charter, 2000). Four pillars of sustainability are: 1. 2. 3. 4.

Respect and care for the community of life; Ecological integrity, Social and economic justice, and Democracy, Nonviolence and Peace, and sixteen other principles.

The Charter also recognizes the role of traditional, cultural and spiritual knowledge of indigenous peoples, non-discrimination and self-determination. Although this document is not legally binding, its principles are considered of universal relevance. In 2009, Polly Higgins, a lawyer and activist in the UK, started a campaign calling on the United Nations to adapt a law recognizing the mass destruction of ecosystems a crime against international peace, that is, as an ‘ecocide’.5 Ecocide is defined as “The extensive destruction, damage to or loss of ecosystem(s) of a given territory, whether by human agency or by other causes, to such an extent that peaceful enjoyment by the inhabitants of that territory has been severely diminished” (Higgins et al., 2013, pp. 251-66). Founded on the duty to care for the planet, this crime against peace would be strict liability and erga omnes: which means compulsory for all, even those States who are not subscribed to the International Criminal Court (ICC). Mining, extraction of fossil fuels and deforestation could be classified as ecocide according to the “Eradicating ecocide campaign”, which is a law against ecocide to be fully implemented in 2020.

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Thus, over 10 countries have already recognized a form of ecocide in their national laws, including Georgia, Kyrgyzstan, Russia and Vietnam. In 2011, The Hamilton Group and held a mock trial in the Supreme Court of the United Kingdom to test the proposed crime of ecocide.6 A process of restorative justice7 was followed in 2012 from a fictitious company and victims including Earth (the voice of the Gaia Foundation), indigenous peoples and future generations. Since January 2014, in Europe, more than 112,000 people signed a petition through the European Citizen’s Initiative for a European Directive on ecocide.8 In 2014, a coalition including End Ecocide in Europe, the European Network of Environmental Prosecutors, Globe EU and Green Cross International, launched a campaign in the European Parliament calling for the establishment of a Criminal Court on the Environment and Health, both at the European and International level with legal penalties for environmental damage. Once a crime of ecocide is recognized, the Criminal Court may allow an application through the Charter of Brussels, which would create a separate court. The Charter of Brussels has been opened to signatures since September 2014.9 In addition to this initiative of “ecocide” on April 22, 2010, World Day of Mother Earth, participants at the World People’s Conference on Climate Change and the rights of nature developed and adopted the Universal Declaration of Rights of Mother Earth (People’s Conference on Climate Change and the Rights of Mother Earth, 2010). This Declaration acknowledges Mother Earth as a living being with rights, including the rights to life, to existence and continues its vital cycles and processes free from any human interference. Even in 2012 the UN Conference Rio + 20 the need to live in harmony with nature has been recognized and in paragraph 39 of the Resolution of the General Assembly of the United Nations, “The Future We Want” refers to some countries recognize the “Rights of Nature” (UN GAOR, 2012), when asserts that: 39. We recognize that planet Earth and its ecosystems are our home and that “Mother Earth” is a common expression in a number of countries and regions, and we note that some countries recognize the rights of nature in the context of the promotion of sustainable development. We are convinced that in order to achieve a just balance among the economic, social and environmental needs of present and future generations, it is necessary to promote harmony with nature. Peter Roderick, a lawyer also from the UK, proposed in 2011 a “Draft Declaration on Planetary boundaries”10, in order to recognize and respect the Earth system processes that sustain life and promote responsibility to safeguard these processes of serious or irreversible harm. The Declaration is based on research conducted by Rockström (2009) and published in Nature in 2009 holding that there are 9 Earthcritical processes and associated thresholds that we must live within in order to avoid irreversible damage to our planet Earth and. According to this research, three of these boundaries have been breached: climate change; biodiversity and the nitrogen cycle. In this vein, in 2013, the Planetary Boundaries Initiative, a legal think tank, presented a petition for the adoption of an agreement on the protection of land system before the Open Ended Working Group of the United Nations on Sustainable Development Goals (ODS), as the main global priority to the goals of sustainable development after 2015.11 These are just some examples of international trends, mostly from academia and social movements, claiming environmental protection through the recognition of the legal personality of nature. This “biocentric” approach, as discussed below, has been reflected in some significant changes, legally speaking, and they deserve some attention. All demonstrate that in practice, recognising Rights of Nature is not difficult.

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2. Recognising the Rights of Nature Among the protective laws of nature, at the oldest constitutional level is the Weimar Constitution of 1919. It has the reputation, together with the 1917 Constitution of Querétaro, of being one of the pioneers in incorporating social rights in the constitution. However, the Weimar Constitution is the first to protect nature. It provides in Article 150 that “Nature enjoys the protection and aid of the State”. Despite this precedent, constitutions of the time did not include issues of nature protection and the human right to nature, including even the Universal Declaration of Human rights in 1948. This is due to a lack of awareness about environmental damage. The first constitutions in the Americas are totally unaware of the existence of living beings other than human beings. The emphasis was on recognizing property rights related to land, water and nature. During the 1980’s and 1990’s there is a wave of reforms in environmental legal frameworks in almost all South American countries, recognizing so-called third generation rights, incorporating related environmental issues, from the perspective of human rights. Few charters on environmental protection contain the perspective on rights of and duties to nature (Boyd, 2012). The Constitutions of Colombia (1991) and Bolivia (in the 2002 reforms) provided that “all persons have the right to enjoy an ecologically balanced healthy environment” and the rights mentioned future generations. Environmental Law No. 1333, April 27 1992 (Bolivia, 1992) was a regulatory precedent recognizing the right to a healthy environment for people and living things in Bolivian legislation. In the Constitution of Peru, there is no right in itself, but an obligation of regulation. In Ecuador’s Constitution, coded in 1984 “the right to live in a pollution-free environment and the states’ obligation to promote the conservation of nature” is introduced. In 1998, the precautionary principal and the right for an individual to take an action to protect the environment is recognized. In 2007, Venezuela’s Constitution recognizes the right and duty of each generation to protect and maintain the environment for its benefit and the future world. Everyone has to enjoy individually and collectively a live and a secure, healthy and ecologically balanced environment. Significantly, after 89 years of Weimar, both the new Constitutions of the Plurinational State of Bolivia adopted in 2009, alongside the Ecuadorian Constitution from September 2008 included content in their respective sections, recognizing the rights of indigenous peoples and rights of all citizens to a healthy and balanced environment (Acosta & Martínez, 2009). In the Previous Constitution of Bolivia the right to a healthy environment was recognized so that individuals and communities of present and future generations, and other living beings could develop normally and securely. In particular, in Articles 33 and 34, the Magna Carta expresses the real rights of the population, and of the future generations of that country, to enjoy a healthy environment, protected and balanced, granting any person, either individually or on behalf of the communities, the power to take legal action in defence of the right to environment. Both the Ecuadorian (2008) and Bolivian (2009) Constitutions mention nature, but while the Ecuadorian respects it as a living being with which on has to live in order to manage “living well”, the Bolivian Constitution considers nature as a helpless and a vulnerable object requiring state protection (Cofre Lagos, 2006). However, in this case, nature always appears in the context of ancestral knowledge, acquired through an intense co-existence with nature itself. The text also diverges radically on another point. Bolivia’s Constitution sees the industrialization of nature as a goal; whereas in the Ecuadorian case nature is presented as a subject of rights for the first time. The Bolivian text ends up creating a link between nature and modernity through progress, while the Ecuadorian Constitution breaks away from this perspective with a biocentric turn. It states that there must be a dynamic relationship between 49

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society, the state, and the market, but balanced and in harmony with nature; granting nature inalienable rights and thus making it a subject of law (Zaffaroni, 2010; De Prada García, 2014).12 The Plurinational State Constitution of Bolivia, in Article 381, declares that the State shall protect all genetic resources and micro-organisms found in the ecosystem of the territory, as well as the knowledge associated with their use and exploitation. Article 382 says the State has power and duty for defence, recovery, protection and reparation of biological material coming from natural resources, ancestral knowledge, and other ways originating within the territory. Article 387 states that the law will regulate the protection and use of forest species of socio-economic, cultural and ecological relevance, giving special importance to the protection of coca, establishing that the State protects the nature and ancestral coca as a cultural heritage, a renewable natural resource of biodiversity, and as a factor of social unity (Article 384). In the two constitutions, particularly in the Bolivian case, indigenous people have incorporated their demands to build plurinational states to represent them and their cultural values, expressed in the “Vivir Bien” (“living well” or “Suma Qamaña” in Aymara). In the Bolivian legislation this meant Nature qualified as a “Subject of Rights” – a truly normative leap. In the Ecuador’s Case “Buen Vivir” (“Living Well” or in Quechua “Sumak Kawsay”). In Chapter 7, Article 71 provides that Nature, or “Pachamama”, where live occurs and is reproduced, has the right to integral respect for its existence, maintenance and regeneration of its live cycles, structure, functions and evolutionary process. The indigenous worldview is reflected in the Bolivian Constitution in its preamble In ancient times mountains arose, rivers spread out from one place to another, lakes were formed. Our Amazonia, our swamps, our highlands and our plains and valleys were covered with greenery and flowers. We populated this sacred Mother Earth with different faces, and since that time we have understood the plurality that exists in all things and in our diversity as human beings and cultures. Thus, our peoples were formed, and we never knew racism until we were subjected to it during the terrible times of colonialism. Everything had its place, and humans and nature co-existed in harmony. The preamble reflects a dialogue from the past, in the present, saying that since time immemorial plurality and diversity are respected. It refers to the natural environment and land, as well as Mother Earth, in which original context various indigenous peoples emerged. Harmony was broken by colonization, introducing racism and altering the order in which indigenous people lived (Caudillo Félix, 2010). It was not until 2010 that Bolivia adopted the first legislative package in the world in which the ancient indigenous conception of nature as a living being entered, giving nature equal rights to humans. Specifically the laws are: Law No. 071 of the rights of Mother Earth (2010) and Framework Act No. 300 of Mother Earth and Integral Development of Good Living (2012). Even though these laws are mostly abstract, their existence helps elevate a debate about the relationship between people and nature. In particular, the Law on the Rights of Mother Earth endorses some guiding principles, including the “common good”, not multiculturalism and commodification of nature, and requires the state and citizens to respect the rights of the Earth. Under the Act, companies and individuals may be responsible for causing environmental damage and responsible for its repair. The Act also provides for an Ombudsman for Mother Earth to protect their interests.

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As fruit of these constitutional developments, on April 22 2009, the General Assembly of the United Nations, at its 63rd meeting, unanimously adopted the draft submitted by Evo Morales, the Bolivian President, stating that every April 22 is celebrated as International Day of Mother Earth (instead of the Day of Earth) (UN, 2009). Concluding the look at Ecuador and Bolivia’s Constitutions, indigenous movements there have managed to incorporate their worldview, values and requirements within their constitutions (Wray, 2008). However, it is considered that the only way to make the principles contained in the Magna Cartas effective is through daily struggles and processes of autonomy and self-management of their people. Previous political experiences have taught them the limitations of the system and the need to continue fighting for their collective rights, the establishment of a plurinational state, and an intercultural society that recognizes and respects indigenous peoples (Vargas, 2011, pp. 70-86). In this regard, it is important to mention that in the United States of America, more than 24 towns and cities have implemented ordinances for the Rights of Nature (Kurth et al. 2012). One of the first legal instruments titled “Sewage Sludge Ordinance” was adopted in 2006 in Tamaqua Borough, Pennsylvania, which meant that corporations could not spread sewage sludge as fertilizer on farmland, even where the owner of the land consented. This Ordinance recognizes the rights of natural communities and ecosystems to exist and flourish, and recognized ecosystems as legal persons (s 7.6). Corporations may not interfere with the right of ecosystems to exist and flourish and Tamaqua residents can pursue actions on behalf of ecosystems. With this move, Tamaqua became the first US municipality to recognize the rights of nature and to enable residents to take action to vindicate those rights. Another relevant example is Pittsburgh city ruling (2010, § 618.03), which prohibits companies drilling for natural gas in the city. This ordinance elevates the rights of individuals, the community and nature over corporate “rights” and thus becomes the first city in the USA to recognize the rights of nature as legally binding. By recognizing the rights of nature, ecosystems and communities against businesses and other levels of government, which can authorize such drilling, and by authorizing Pittsburgh residents to exercise those rights on behalf of threatened ecosystems, these ecosystems are effectively protected. Santa Monica (2013) also passed a ruling that elevates its right to enforce its Sustainable City Plan, including rights to clean air, water and soil, and the rights of nature above corporate entities’ privileges and powers. Since 2010, at least 18 Community Bills of Rights to ban natural gas drilling and hydraulic fracturing have been passed in municipalities in California, New York, New Hampshire, Maine, Maryland, Ohio, Pennsylvania and Virginia, and defeated in New Mexico.13 Specifically, the Town Mountain Lake Park Ordinance on Natural Gas Extraction (2011); West Homestead, Pennsylvania Community Rights Gas Extraction Prohibition (2011); Town of Wales, New York Community Protection of Natural Resources (2011);14 Baldwin, Pennsylvania Community Protection from Natural Gas Extraction Ordinance (2011); Wilkinsburg, Pennsylvania Community Protection from Natural Gas Drilling Ordinance (2011);15 Forest Hills Borough’s Community Rights and Protection from Natural Gas Exploitation Ordinance (2011); State College Borough’s Community Bill of Rights Home Rule Charter Amendment (2011); Las Vegas, New Mexico’s Community Water Rights and Local Self-Governance Ordinance (2013), amongst many others. These are the first communities in the U.S. to ban fracking, recognizing the rights of nature, and subordinating corporations to the people by popular vote. Although these initiatives recognize rights of nature at the local level, it poses the question whether this recognition of nature’s rights is ecologically valid (Rodrigues, 2014, pp. 170-84). Although the initiatives quoted above are local, policy development in the United States shows that attributing rights to nature is no exclusive to indigenous societies with a particular worldview. Western societies also promote

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change in this direction, in response to new challenges that nature faces defenseless against the intense activity of large industrial corporations (Vermont Rights of Nature, 2012).

3. Protecting the Rights of Nature Especially the indigenous, social movements have been the promoters of this new “biocentric” perspective, based on worldview, values ​​and demands for the legal recognition of the rights of nature. However, it is necessary to analyze the effectiveness of these rights beyond formal legal recognition. In this sense, the practice has encompassed not only the protection of nature itself, but also the protection of the intangible and the spiritual, ensuring their preservation, and the protection of sacred sites and ancestral knowledge. In certain cases, the formal recognition of the rights of Nature has implied the creation of institutional bodies and processes, such as Guardians for the Earth in Bolivia, and Ombudsman for Future Generations. In addition, many countries recognise locus standi/standing for the public to issue legal proceedings in the public interest (e.g. UNECE Aarhus Convention) - which could be expansively interpreted as including Nature, and even directly on behalf of Nature (e.g. Ecuadorian Constitution and local ordinances in the U.S.). These institutional tools can amplify the protection of the environment. Regardless of the extent of rights granted to nature, it must rely on human representation to assert and defend these rights in a court of law (Donald Cameron, 2007). The first case of judicial enforcement of the rights of nature occurred in the year 2011 Action Protection, resolved on appeal by the Criminal Division of the Provincial Court of Loja (Wheeler versus Director de la Procuraduria General del Estado en Loja, 2011), presented by Richard Frederick Wheeler and Eleans Geer Huddle against the Provincial Government of Loja “for nature particularly in favor of the Vilcabamba river” over the works of the Vilcabamba-Quinara road expansion. The government project to build a highway without the required environmental impact studies, negatively affected the flow of the river causing floods and disrupted wildlife and the livelihoods of local communities. The court decision was issued on March 30, 2011 by the Provincial Court of Loja, which granted an injunction against the Provincial Government of Loja to stop violating the constitutional rights of the Vilcabama River to exist and to maintain its vital cycles, structure, functions and evolutionary processes (Daly, 2012, pp. 63-6). This is the first case of successful Nature Rights under Article 71 of the Ecuadorian Constitution (Wheeler versus Director de la Procuraduria General del Estado en Loja, 2011). The Chamber granted the motion, agreeing that “the action of protection is the only suitable and effective remedy to stop immediately and focused environmental damage” and applying the precautionary principle, the judges say “[...] “until such time it is objectively proven that no probable or certain danger exists over works carried out in a particular area producing contamination or environmental damage, it is the constitutional duty of judges to immediately pay attention to safeguarding and enforcing the legal protection of the rights of Nature, avoiding contamination by whatever means, or ensuring remedy. Note that with relation to the environment we shall consider not only certain damage, but also indications of possibility” [...]”(Wheeler versus Director de la Procuraduria General Del Estado en Loja, 2011, §5). Therefore, the Court confirmed the principle of precaution that until the government can show that the widening of the road would not affect nature; the presumption is to protect the rights of nature. The Court also endorsed the intergenerational principle, recognizing the importance of nature to protect the interests of present and future generations and ordered the government to submit environmental impact studies, develop a plan of rehabilitation and remediation, and publicly apologize for the start of construction of a road without the necessary environmental license (Smith, 2009; De Prada, 2014). 52

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The Chamber recalls that the Constitution “... unprecedented in the history of mankind, recognizing nature as a subject of rights [...]”; assumed as an obvious and indisputable fact the “importance of Nature”, to the point that they consider “any argument about it is succinct and redundant”, incorporating the decision that the idea that damage to it is “generational damage “, defined as” those which by their magnitude impact not only on the current generation but their effects will impact on future generations [...]” (Wheeler versus Director de la Procuraduria General del Estado en Loja, 2011, §7 and 8). In addition it modifies the burden of proof freeing the plaintiffs from proving damage, stating that it is the “[...] the plaintiffs did not have to prove potential damage. The Loja Provincial Government would have to provide evidence that the activity of opening a road neither affected nor would affect the environment in the future. It would be inadmissible to reject an action protecting Nature for the lack of prof presented, as in case of possible or assumed already caused environmental damage through pollution, the nonexistence of this damage should be proved not just by whoever is in a better position to do so but by the one who argues, ironically, that such damage does not exist”[...] ” (Wheeler versus Director de la Procuraduria General del Estado en Loja, 2011, §10). Despite the excitement surrounding this finding, which advocates recognition of nature as a subject of rights, the Board does not deny the possibility of the work, but states it should respect the “rights of nature” without specifying how they are violated. It merely repeats the Constitution “is violating the law of nature has to be fully respected its existence and the maintenance and regeneration of its vital cycles, structures, functions and evolutionary processes”. In fact, all the reasoning is redirected towards the human right to a healthy environment. The action on behalf of the defense is of particular interest “[...] As regards the allegation that the people need [...] roads, indicates that: in case of conflict between two protected interests (sic) Constitution, the solution must be found in accordance with the legal elements which constitute the case and in light of the constitutional principles and values. This work is an essential function of interpretation by the constitutional court. But in this case there is nothing to ponder because there is no collision of constitutional rights or compromise of one of them, in that if the VilcabambaQuinara road is not enlarged, it complies with the constitutional rights of Nature. In any case, the interest of these populations in the road is lessened compared with the interest in a healthy environment that includes a larger number of people” (Wheeler versus Director de la Procuraduria General del Estado en Loja, 2011, §12). Accordingly, the judgment states that the Provincial Council is responsible for damages, ordering that environmental recommendations are welcome and “public apology for starting the construction of a road without the environmental licensing.” Also in Ecuador, on November 26, 2010, an international alliance of environmental activists16 filed a lawsuit against British Petroleum (BP) in the Ecuadorian Constitutional Court, in defense of the rights of nature, which are recognized in the Ecuadorian Constitution 2008. In this sense, the Ecuadorian Constitution recognizes the right of nature to be restored and allows a citizen or group to present a case before the Constitutional Court of Ecuador for a violation occurring in a different country,which affects Earth as a whole. Instead of seeking financial compensation, the coalition calls on BP to disclose the data and information on the ecological destruction caused by the oil spill, and to restrain BP from mining oil underground as in the spill in the Gulf of Mexico disaster (Gaia Learning Centre, 2011). Following this recognition of nature as a subject of rights, the Chief Justice in Belize ruled in 2010 that a reef is not owned, but is a living being that is part of the national heritage of Belize and cannot be sacrificed to the commercial interests (Supreme Court of Belize, A.D. 2009; Court of Appeal of Belize, A.D. 2011). The case is from January 13, 2009, when a cargo ship collided with Mesoamerican Reef, near Caye Glory in Belize, damaging 6,000 square meters of pristine reef. The Mesoamerican reef more

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than 225 million years old, is the largest coral reef in the Atlantic Ocean and is home to over 60 species of coral reef fish and 500 other species. The Court considered the shipping company responsible and required it to pay $ 11 million Belize dollars ($ 5.5 million US Dollars), plus interest at 3% per year for environmental and ecological loss and the cost of restoration. In this line, it is also interesting that from 1997, OxlajujAjpop, an organization of indigenous Mayan spiritual leaders, has been advocating for and developing a proposal for a Sacred Sites Act in consultation with indigenous communities. This bill is to ensure the recognition of sacred sites and territories and governance, access, use and conservation of communities. It has not yet been accepted by all members of Congress and government, but negotiations continue. OxlajujAjpop is also calling for a new Constitution and the legal reform that respects Mother Earth, ecosystems and indigenous territories, and a ‘socially and legally’ pluralistic state (National Conference of Ministers spirituality Maya of Guatemala, 2008). Another interesting case is related to a group of international activists, who requested the opening of a trial in the Constitutional Court of Ecuador in 2010 referring to the right of nature and the right of sea further than the territory of Ecuador, to claim justice in the case of the Deepwater Horizon disaster, which is the famous British Petroleum oil spill in the Gulf of Mexico, in the name of the right of the sea.The claim challenged the usual jurisdiction territorial competence and mobilized new rights and visions which exist only in a few countries like Ecuador and Bolivia. This case illustrates how the traditional systems to demand compensation can be changed, in that the request can require a series of actions by the company BP, and not necessarily a direct financial compensation. For example, BP shall maintain the same quantity of oil underground as before the extraction, or use specific technical cleaning mechanisms, implying an economical sacrifice or a change in behaviour by the company, as a disincentive for repeating their actions, instead of simply a financial award. Such an example teaches an important although basic lesson: losses caused by environmental injustice go further than the money value. As far as possible justice should evolve, towards a diversity of values that can be incorporated into the sentencing systems in the court. In 2012, the “Custodians of Sacred Natural Sites” Kenya, South Africa, Ethiopia and Uganda adopted a Common Declaration of African customary law for the Protection of Sacred Natural Sites in Nanyuki, Kenya (Custodian Meeting Nanyuki, 2012). The Declaration recognizes that sacred natural sites and territories are places of ecological, spiritual and cultural significance, where laws and ecosystem boundaries exist and must be respected. The Declaration provides important guidance on sacred natural sites which should be respected and prohibited for any activity, except necessary spiritual practices, and that the traditional systems of government, which communities hold should be recognized. Similarly, in New Zealand, following more than a century of petitions and legal action by local iwi (Maori tribal group), the Whanganui river in New Zealand was granted the legal status of a person under the name Te Awa Tupua. This legal victory means that the river now enjoys the same rights and responsibilities before the law as people and corporations and both the government and the Maori have been designated guardians to ensure that the river’s rights are protected (Tutohu Whakatupua, 2012). This precedent-setting legal case is the first time the rights of a river have been guaranteed in this way, opening up exciting possibilities for protecting, and changing how we understand our relationship with, the natural world. Apart from these cases, it is worthwhile mentioning that the first Permanent Court of Ethics was established on January 17 2014, for the Rights of Nature and Mother Earth, thanks to the Global Alliance for the Rights of Nature. Its inaugural meeting, attended by over 400 people, was held in Quito, Ecuador, the country which acknowledged these rights for the first time in its constitution. The Tribunal was chaired by Vandana Shiva. This first preliminary hearing was to determine eligibility for the award 54

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of rights of numerous acts of nature, including those affected by mining and commercial agriculture. The role of this Court is to promote the establishment of a future permanent court to contribute to the development of legislation that recognizes the rights of nature (Viale, Machado, & Acosta, 2014). The Court is held in different parts of the world, for example, in the negotiations on climate change (COP 20) in Lima in December 2014 (Larrea, 2013; Acosta, 2013).17 The initiative arose and was the expression of the coordinated action of a wide range of social movements and organizations from around the world, all moved by the desire to denounce the attacks, which Nature had suffered, and the suffering that comes from the past, systematically and with increasing intensity, in the name of “progress.” This Court, a pioneer in the search for ways to build global justice against crimes against life, was established as a permanent platform to hear and judge cases of violation of the rights of Mother Earth that took place around the world. In this first session of the Permanent Court of Ethical Rights of Nature included representatives from Australia, Switzerland, South Africa, USA, Spain, Canada, India, Romania, Bolivia, Argentina and England, Colombia, Germany, France, as well as Ecuador were included. After a full day session with presentations and discussions, the court took the unanimous decision to admit nine cases considered emblematic of the violation of the laws of Nature. Six spot cases were presented: pollution ChevronTexaco (Ecuador); the threat to the Great Barrier reef due to coal mining (Australia); copper sky mining in the Cordillera del Condor reservoir case Mirador (Ecuador); cases of hydraulic fracturing (USA) and two cases on a global scale representing systemic violations of the rights of Mother Earth, involving genetically modified or transgenic organisms and climate change; and lastly the proposed oil drilling in Yasuní-ITT (Ecuador). During the Yasuní –ITT case, because of the immediate threads, and the convincing evidence the Tribunal agreed to establish a special Courtroom for this item, to consider the harassment of defenders of nature, including the people gathering signatures for a community consultation with which to put the brakes on the exploitation of crude in the Yasuní-ITT. It was also to consider the suspension of extraction activity in Block 31 and 43 (ITT), and carry out a general audit of all activities in the Yasuní National Park. It was consistent that the Court of the Rights of Nature originates in Ecuador, the first country to recognize these rights in its constitution. It is ironic, however, that Ecuador has abandoned its leadership and its commitment to respect the rights of nature set out in its Constitution, which was overwhelmingly approved by the Ecuadorian people at the polls (Figueroa, 2011). The Government of Ecuador is currently promoting the expansion of oil production and large-scale mining threatening three million hectares of the Amazon forest remnants, while carrying out a systematic campaign against those individuals and organizations that defend the rights of Mother Earth protected by the Ecuadorian Constitution. The criminalization of popular resistance is undoubtedly the government tool to further expanding extraction: minerals, petroleum, biofuels, etc. These cases illustrate to a greater or lesser extent, certain changes in the way of protecting the environment, moving away from the traditional anthropogenic perspective. Graduallysocialchanges areinfluencingthe evolution of the lawfor the benefit ofnature. Thesechanges respondto the attempt tostophumanizingnature and make the human beingresponsiblefor protectingthe environment. In some sense, history shows again that culture changes law and law in turn, broadly can change culture.

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V. CONCLUSION Environmental awareness generated by progressive degradation of the environment, from different areas has led to the call for a formal recognition of the importance of environmental protection for human well-being. However, the anthropocentric approach developed to protect human rights has shown that it is not enough to protect the environment. The traditional anthropocentricparadigm furthers dangerous ideas around the commodification and financialization of nature. So the new road for the biocentric perspective away from the Western model of development to a more holistic approach based on indigenous concepts such as “Living Well” or “Good living” and allowing for the development of the “right to a healthy environment” and “the rights of nature.” The conception of an environmental dimension as an integral part of the realization of human rights has contributed to increased lack of care about environmental protection for the benefit of human welfare. The consequence has been the subordination of the well-being of ecosystems to satisfy human interests, not always respectful of natural cycles. Thus, the protection of nature through a human rights perspective has generated the dispersal of laws according to the subjective and fragmented interests of human groups. The new focus on environmental protection, which has been discussed in this article, establishes a new relationship between humans and nature and harmony between the two, which should be preserved as a guarantee of nature’s regeneration. It promotes the legal recognition of nature favouring the unification of laws throughout the different legislations by providing rules protecting the natural world with a common denominator, based on the needs of the biosphere. According to that, states must be required to prioritize the welfare of citizens and the natural world, developing public policies that promote sustainability and control of industries. The national economy should operate within the limits of nature. This certainly will not be an easy task. What may seem utopian is slowly becoming a reality in many countries. The key is to change policies and laws related to the environment, which simply encode pollution and destruction. The changes only will be succeeded, if such policies and laws recognize human rights as well as human responsibilities for a healthy and resilient Earth. Despite the possible contradictions on a practical level, the emerging new regulations based on the biocentric approach at least raise the man’s need to change the way it treats nature, but this new concept has not been widely translated into the world of laws and policies, or society in general. According to this concept, natural rights are not opposite to human rights: human rights are a subset of natural rights, because humans are a part of the nature. The final idea is not the imposition of the biocentric view on the anthropocentric legal protection of the environment, but to change the way we conceive this protection: it is important to protect nature, but not under the blanket of protecting human interests. Social movements and even academic efforts should be made to invest in favour of the rights of nature and at least a new opportunity to preserve the environment and, of course, our welfare. Critically, therights of Nature framework provides a path through which people can re-learn respect for Mother Earth and for human rights.

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Larrea, C. (2013). La Explotación Petrolera en el Parque Nacional Yasuní y los Derechos de la Naturaleza. Retrieved from 23 June 2015 from: http://therightsofnature.org/wp-content/uploads/ITTDerechosNaturaleza.pdf Lee, J. (2000). The Underlying Legal Theory to Support a Well-Defined Human Right to a Healthy Environment as a Principle of Customary International Law. Columbia Journal of Environmental Law, 25(2), 283. Lewis, B. (2012). Environmental Rights or a Right to the Environment? Exploring the nexus between Human Rights and Environmental Protection. The Macquarie Journal of International and Comparative Environmental Law, (1), 36. Ley de derechos de la Madre Tierra. Ley Nº 071, Gaceta Oficial. December 21, 2010 Ley del Medio Ambiente. Ley 1333, Gaceta Oficial. April 27 1992. Ley marco de la Madre Tierra y Desarrollo Integral para Vivir Bien. Gaceta Oficial October 15, 2012. Makarewicz, A. (1986). La protection internationale du droit à l’environnement. Environnement et droits de l’Homme. UNESCO. Melo, M. (2009). De Montecristi a Cochabamba. Los derechos de la Madre Tierra en debate. Retrieved 23 June 2015 from http://therightsofnature.org/wp-content/uploads/pdfs/Espanol/Melo_Montecristi%20 a%20Cochabamba_2009.pdf Mountain Lake Park (2011), Md., Ord. No. 2011-01 (Mar. 3, 2011). Ms Westerhaven Schiffahrts GMBH & CO KG Redier Shipping BV vs. The Attorney General of Belize. Court of Appeal of Belize, A.D. 2011 Civil Appeal No. 19, 2010. National Conference of Ministers spirituality Maya of Guatemala -OxlajujAjpop. (2008). Organization for the recovery, conservation, dignity and administration of the holy places Mayas (NIM Q’ATB’ALtzij KECH AJQ’IJAB’OXLAJUJ Ajpop) of January 18, 2008. Retrieved 23 June 2015 from http://sacrednaturalsites.org/es/items/nim-qatbal-tzij-kech-ajqijab-oxlajuj-ajpop/?COLLCC=1422104073 Pelizzon, A. (2011). Keeping the Fire: Impressions of Earth Jurisprudence, 14. Southern Cross University Law Review, 6–12. Rockström, J., Steffen, W., Noone, K., Persson, A., Chapin F. S., Lambin, E., … Foley, J. A. (2009). A safe operating space for humanity. Nature, 461, 472-475. Retrieved 23 June 2015 from http://www. nature.com/news/specials/planetaryboundaries/index.html Rodrigues, S. (2014). Localising ‘the rights of nature’: a critical discourse analysis, Green Letters: Studies. Ecocriticism, 18(2), 170–184. Sierra Club v. Morton. United States Supreme Court. 405 U.S. 727, 741-43 (1972). Smith, G. (2009). In Ecuador, Trees Now Have Rights. Earth Island Journal, 15-15.

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State College Borough Bill of Rights. (2011). Community Bill of Rights and Natural Gas Drilling Ban Section 41.2-205. Retrieved 30 August 2015 from http://www.statecollegepa.us/DocumentCenter/Home/ View/3028 State of New Mexico, County of Mora, Ordinance 2013-01. (n.d.). Retrieved 30 August 2015 from https:// es.scribd.com/doc/139339332/Mora-County-Oil-and-Gas-Ordinance Statement of Common African Customary Laws for the Protection of Sacred Sites. (2012). Custodian Meeting Nanyuki, Kenya. Retrieved 23 June 2015 from http://sacrednaturalsites.org/es/items/statementof-the-common-african-customary-laws-for-the-protection-of-sacred-sites/?COLLCC=1400401888 Stone, C. (1972). Should Trees Have Standing? Toward Legal Rights for Natural Objects, 45. Southern California Law Review, 450. Stone, C. (2010). Should Trees Have Standing? Law, Morality, and the Environment. Stutzin, G. (1984). Un imperativo ecológico: reconocer los derechos de la Naturaleza. Ambiente y Desarrollo, 97-114. Stutzin, G. (2002). Nature’s Rights: Justice Requires that Nature Be Recognised As a Legal Entity. Resurgence Magazine, (210). Retrieved 5 October 2015 from http://www.resurgence.org.uk UN Sub-Commission on Prevention of Discrimination and Protection of Minorities Decision 1989/108, UN. Doc. E/CN.4/Sub.2/1989/58, at 71, 1989. The Earth Charter. (2000). Retrieved 23 June 2014 from: http://www.earthcharterinaction.org/invent/ images/uploads/echarter_spanish.pdf Town of Wales, New York (2011) Intro. No. 2-2011, Local Law no. 2011: a Local Law, amended the Local Law 1 - 1993. Tutohu Whakatupua (2012) (Agreement between Whanganui Iwiand the Crown, 30 August 2012) at 2.4. UN General Assembly. (2009). Declaring the International Mother Earth Day. Retrieved from http:// www.un.org/en/ga/search/view_doc.asp?symbol=A/RES/63/278&Lang=S UN General Assembly. (2012). The future we want. Retrieved from http://www.un.org/ga/search/view_doc. asp?symbol=A/RES/66/288&Lang=E UN General Assembly. (2007). United Nations Declaration on the Rights of Indigenous Peoples. Retrieved from http://www.un.org/esa/socdev/unpfii/documents/DRIPS_en.pdf UN General Assembly. (2000). Millennium Declaration. Retrieved from http://www.un.org/spanish/ milenio/ares552.pdf UN General Assembly. (1990). Need to Ensure a Healthy Environment for the Well-Being of Individuals. Retrieved from http://www.un.org/documents/ga/res/45/a45r094.htm UN General Assembly. (1982). World Charter for Nature. Retrieved from: http://www.refworld.org/ docid/3b00f22a10.html

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UN Human Rights Committee (HRC). (1982). CCPR General Comment No. 6: Article 6 (Right to Life). Retrieved 2 March 2016 from http://www.refworld.org/docid/45388400a.html Universal Declaration of Human Rights. (1948). G.A. res. 217A (III), U.N. Doc A/810 at 71. Retrieved 5 October 2015 from http://www.ohchr.org/EN/UDHR/Documents/UDHR_Translations/eng.pdf Vargas Lima, A. E. (2011). El Derecho al Medio Ambiente en la Constitución Política del Estado Plurinacional de Bolivia. Academic Press. Vermont Rights of Nature. (2012). Vermont Rights of Nature. Retrieved 14 September 2015 from https:// www.facebook.com/VermontRightsOfNature Viale, E., Machado, H., & Acosta, A. (2014). La Madre Tierra tiene Derechos: primero tribunal para defenderlos. Retrieved 23 June 2015 from http://www.rebelion.org/docs/180605.pdf West Homestead Borough. (2011). Allegheny County. Ordinance. Wheeler versus Director de la Procuraduria General Del Estado en Loja, Juicio. Sentencia Causa, 30 de marzo del 2011, Acción de Protección No. 11121-2011-00010, Sala Penal de la Corte Provincial de Loja. Retrieved 23 June 2015 from http://therightsofnature.org/first-ron-case-ecuador World People’s Conference on Climate Change and the Rights of Mother Earth. (2010). Universal Declaration of Rights of Mother Earth. Retrieved 23 June 2015 from http://therightsofnature.org/universaldeclaration/ Wray, A. (2008). Los derechos de la naturaleza. Retrieved 23 June 2015 from http://cywlegal.com/inter. asp?s=3&ss=13&n=107 Zaffaroni, E. R. (2010). La naturaleza como persona: Pachamama y Gaia. In Bolivia: Nueva Constitución Política del Estado. Conceptos elementales para su desarrollo normativo (pp. 109–132). La Paz: Vicepresidencia del Estado Plurinacional de Bolivia.

KEY TERMS AND DEFINITIONS Anthropocentric Approach: Viewpoint arguing that human beings are the central or most significant entities in the world. Biocentrism: The view or belief that the rights and needs of humans are not more important than those of other living things are. Ecocide: The extensive destruction, damage to or loss of ecosystem(s) of a given territory, whether by human agency or by other causes, to such an extent that peaceful enjoyment by the inhabitants of that territory has been severely diminished. Environmental Law: The field of law that covers the protection of environment from a legal aspect; Human right to environment: is the enjoyment of everybody, without discrimination, to a safe, healthy and ecologically balanced environment. Environmental Protection: Policies and procedures aimed at conserving the natural resources, preserving the current state of natural environment and, where possible, reversing its degradation.

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Good Living (Buen Vivir): The Ecuadorian concept of sumak kawsay, meaning a full life in kichwa. It has emerged as a response to the traditional strategies for development and their negative environmental, social, or economic effects. It is an alternative concept of development that focuses on the attainment of the “good life” in a broad sense, only attainable within a community; a community that includes Nature. Living Well (Vivir Bien): The Bolivian concept emanating from Latin America’s indigenous peoples. The term translates as sumaq kawsay and suma qamaña in Quechua and Aymara, the two main indigenous languages of the Andes and it implies the creation of a new global relationship with nature and among human beings, expanding the rights to Mother Earth, setting ethical values and responsibilities of peoples with Mother Earth, the fulfillment of obligations of States, communities, and individuals with Mother Earth; and the protection of the environmental functions of Mother Earth as community-goods. Mother Earth: A dynamic living system comprising an indivisible community of all living systems and living organisms, interrelated, interdependent and complementary, which share a common destiny. Nature Rights: The recognition that our ecosystems – including trees, oceans, animals, mountains – have rights just as human beings have rights (nature in all its life forms has the right to exist, persist, maintain and regenerate its vital cycles). Nature: All the ​animals, ​plants, ​rocks, etc. in the ​world and all the ​features, ​forces, and ​processes that ​happen or ​exist​independently of ​people, such as the ​weather, the ​sea, ​mountains, the ​production of​ young ​animals or ​plants, and ​growth. Rights of the Mother Earth: Mother Earth and all beings of which she is composed have the following inherent rights: the right to life and to exist; the right to be respected; the right to regenerate its bio-capacity and to continue its vital cycles and processes free from human disruptions; the right to maintain its identity and integrity as a distinct, self-regulating and interrelated being; the right to water as a source of life; the right to clean air; the right to integral health; the right to be free from contamination, pollution and toxic or radioactive waste; the right to not have its genetic structure modified or disrupted in a manner that threatens it integrity or vital and healthy functioning; the right to full and prompt restoration the violation of the rights caused by human activities; the right to a place and to play its role in Mother Earth for her harmonious functioning; the right to wellbeing and to live free from torture or cruel treatment by human beings.

ENDNOTES

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This chapter has been prepared under the DER2013-44009-P Project entitled“Del desarrollo sostenible a la justicia ambiental: hacia una matriz conceptual para lagobernanza global” (2014-2016), whose main researcher is Dr. Antoni Pigrau Solé. The Subcommission on the Promotion and Protection of Human Rights was established by a decision of the Commission on Human Rights of 10 Feb. 1947. Its former name was: Subcommission on Prevention of Discriminationand Protection of Minorities (renamedby ECOSOC decision 1999/256 of 27 July 1999). The Subcommittee commissioned Mme. Ksentini to develop a methodology for such a study. Two years later, Mme. Ksentini presented a preliminary report (E / CN.4 / Sub.2 / 1991/8, August 2, 1991). In this report, the provisions of several international and national human rights instruments relating to the environment, their relationship with other rights such as the rights of indigenous peoples and the right to development, the human rights violations and environmental degradation

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are discussed and so are the environment, ecological rights and the implementation of environmental protection procedures. At the request of the Subcommittee, Mme. Ksentini presented two more reports, one in 1992 (E / CN.4 / Sub. 2/1992/7 on July 2, 1992 and Add.1) and another in 1993 (E / CN.4 / Sub.2 / 1993 / 7, July 26, 1993). Mr. John Knox was appointed in August 2012 for a period of three years, as the first Independent Expert on the issue of human rights obligations related to the enjoyment of a safe, clean, healthy and sustainableenvironment. His main tasks in accordance with Resolution 19/10, which established the mandate of the independent expert, inter alia, are the following: to study the human rights obligations related to the enjoyment of a safe, clean, healthy and sustainable environment, in consultation with relevant stakeholders; identify and promote best practices, and exchange opinions, in the performance of its obligations and commitments to support human rights, support and strengthen environmental policy, especially in the field of environmental protection; develop a compendium of best practices; make, within its mandate, recommendations that could contribute to achieving the Millennium Development Goals, in particular the Millennium Development Goal; and consider the results of the UN Conference on Sustainable Development (Rio +20), and provide a perspective of human rights monitoring processes. Retrieved from http://eradicatingecocide.com/ (accessed June 23, 2015). See also online: https://www.youtube.com/playlist?list=PLFB4F5595F6740619&feature=viewall (accessed June 23, 2015). Retrieved from http://www.gaiafoundation.org/blog/the-sentencing-justice-for-the-earth-community (accessed June 23, 2015). Retrieved from http://www.endecocide.eu/end-ecocide-continues-collect-signatures/?lang=en (accessed June 23, 2015). For more information: http://iecc-I tpie.org/en (accessed June 23, 2015). Retrieved from http://planetaryboundariesinitiative.org/about-2/declarations/draftonpb (accessed June 23, 2014). A summary of seven short expert commentaries on the planetary boundary concept that were published at 3 Nature reports, Climate Change, October 2009, 112-119. Retrieved from http://www.anu.edu.au/climatechange/wp-content/uploads/2009/09/climate-commentaryoctober-2009.pdf. For more information: http://planetaryboundariesinitiative.org/2013/12/03/recommendationsevidence-from-the-planetary-boundaries-initiative-on-sdgs/ (accessed June 23, 2014). In 2012 Kate Raworth proposed combiner understanding planetary boundaries to social boundaries, being essentially interdependent. In its report A Safe and Just Space for Humanity: ‘Can we live Within the donut’ integrates the study of Rockström and other ‘9 Processeses Earth-system’ with “11 dimensions of human deprivation”. The Ecuadorian constitutional text has three Articles where the following rights for nature are established: the Article 71 on the Nature, or Pachamama, where life is reproduced and occurs, has the right to integral respect for its existence and for the maintenance and regeneration of its life cycles, structure, functions and evolutionary processes. Article 72 refers that the Nature has the right to be restored. This restoration shall be apart from the obligation of the State and natural people or legal entities to compensate individuals and communities that depend on affected natural systems. In those cases of severe or permanent environmental impact, including those caused by the exploitation of non-renewable natural resources, the State shall establish the most effective mechanisms to achieve the restoration and shall adopt adequate measures to eliminate or mitigate

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harmful environmental consequences. Article 73 states that the State shall apply preventive and restrictive measures on activities that might lead to the extinction of species, the destruction of ecosystems or the permanent alteration of natural cycles. The introduction of organisms and organic and inorganic material that might definitively alter the nation’s genetic assets is forbidden. All these Ordinances were drafted in consultation with the Community Environmental Legal Defense Fund (CELDF). See http://celdf.org/resources-ordinances (accessed August 2, 2014). This amended another old Local Law 1 - 1993 known as “adoption of code”, adopted by the Town Board of the Town of Wales on May 11, 1993, by adding a new chapter 162 known as the “protection of natural resources”. Borough Council of Wilkinsburg, Allegheny County, Pennsylvania adopted ordinance number 28-70 that enacts an enforceable Local Bill of Rights, along with a prohibition on natural gas extraction to protect those rights. The group included Nnimmo Bassey from Nigeria and Vandana Shiva of India (both winners of the Right Livelihood Award), and other activists from Mexico, Peru and Ecuador, including the Chairman of the Constitutional Review Panel of Ecuador. Check the following information online. Retrieved from https://www.youtube.com/ watch?v=LrD7CdQMA6g and http://derechosdelanaturaleza.org/(accessedJune23,2015).

This research was previously published in Defending Human Rights and Democracy in the Era of Globalization edited by Christina Akrivopoulou, pages 225-261, copyright year 2017 by Information Science Reference (an imprint of IGI Global).

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Chapter 4

The Impact of Kisan Call Centers on the Farming Sector Kartik Chachra Institute of Management Technology Ghaziabad, India Gowtham Seelam Institute of Management Technology Ghaziabad, India Harshit Singh Institute of Management Technology Ghaziabad, India Mayukh Sarkar Institute of Management Technology Ghaziabad, India Anshul Jain Institute of Management Technology Ghaziabad, India Ankush Jain Institute of Management Technology Ghaziabad, India

ABSTRACT The Indian Agriculture has been an area with varied challenges. This sector is responsible for the growth rate and generating a per capita income. This sector generates a whopping 28% of the total GDP of India and over 15% of the total exports. The usage of Internet and phone technology can fill these gaps to a large extent. A continuous two way interaction among the farmers and agricultural scientists will ensure agricultural extension. A landmark step was taken on January 21, 2004 when the Department of Agriculture & Cooperation, launched Kisan Call Centers (KCC) with the help of the extensive telecom industry to deliver extension services to the farming community. The main purpose of these call centers is to answer the queries raised by the farmers in their local language, on continuous basis. At present the Kisan Call Centers are running from 14 locations all over India. In this chapter, we are trying to analyze how this strategy to help the farming community was introduced and how it is being implemented.

DOI: 10.4018/978-1-5225-9621-9.ch004

Copyright © 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 The Impact of Kisan Call Centers on the Farming Sector

INTRODUCTION The role of agriculture in India’s socio-economic development is inherent since ancient times. Even today agriculture forms a significant part of the GDP and overall growth and sustainability of India. This sector provides employment to 51% of the total workforce, being the largest economic sector amongst others such as mining, tourism, retail, textile, industry and services. That being mentioned, the challenges before the agricultural practices in India are immense. It will not only benefit the overall economic progress of the country, but is also essential for the workforce of the nation, two thirds of which, directly or indirectly depends on the same. It contributes to around 27% of the GDP of India and somewhere around 13-16% of the exports. Still, the yields are not only lesser than expected, they are highly unstable and the gaps in technology transfer are much more intense as compared to those in areas that are irrigated. Kisan call center is a Government of India initiative under the department of Agriculture and Cooperation. This initiative is primarily aimed towards assisting the farmer community for any issues or queries that they may have and also in training them to face the immense inevitable challenges. These knowledge centers are active throughout India providing services to farmers in terms of assistance and guidance in solving their problems in their regional local languages. Providing a structure to this entire operation of query handling involves effective use of technology, networking, a strong knowledge base, technically educated and informed staff. These call centers make use of an extensive telecommunication network, having a strong back end Management Information System to address the queries of farmers across the country, regarding agriculture practices and latest farming techniques. The scheme’s objective is to serve the farming community spread over 5 lakh villages across the nation. The need of the hour is to pay greater and more focused attention to information by extensively using the appropriate tools and technologies that help farmers cope up with the diverse challenges and learn new opportunities on a continuous basis. To capitalize on future export opportunities of agriculture products, the country needs to match global standards in terms of quality, stability and hygiene. Hence, the farmer should be aware and informed of the latest efficient agricultural practices. The Kisan Call Center aims to fulfill the following: • • • •

Fast and effective spreading of information Minimizing the gap between Farmer and Research Labs, agriculture universities, market, corporates On demand specific individual knowledge transfer and adequate facilitation Efficient use of the huge and complex telecom infrastructure

While the state of Kentucky, US is following GAP (Good Agricultural Practices) to ensure safety from post production deceases in the crops, and the GAP in Rome (Italy) are focused on setting up protocols and appropriate processes, the services provided by KCC are rather educational and informative in nature. They aim to educate the farmer with innovative and new technologies and techniques that should be implemented in order to yield better results. Recently, to facilitate the queries of the farming community in an easier way, the Department of Agriculture and Cooperation has come up with an idea of Kisan SMS (Short Messaging Service) Portal. The users have to register and enroll themselves via a mobile number. Once registered, the user will receive regular updates about weather and agricultural alerts, absolutely free of cost. In this case, a farmer will be getting an SMS messages providing expert information and delivering services on his mobile from

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agriculture scientists at various levels. The services cover diverse areas such as crop production and protection, animal husbandry, fisheries as well as dairying. New types of information and services are expected to be included as the system progresses based on the different requirements of farmers. Some of these include: 1. 2. 3. 4. 5. 6. 7.

Weather information including forecast Alerts for farming related facts Timely Information regarding disease/pests outbreaks Technology related support for crop cultivation according to local conditions Awareness of new crop variety Market know how Soil fertility reports

THEORETICAL FRAMEWORK Here we describe the concept and structure of the implemented knowledge based service, also the infrastructure and technology involved in connecting the farmers with the personnel who address their individual queries in their local language. The steps for a typical calling procedure can be seen in Figure 1, below. Each call follows a pre-defined protocol and queries are addressed according to their nature by various levels of representatives, from agriculture graduates, postgraduates equipped with computer Figure 1. Steps involved in a typical calling procedure Source: National Institute of Agricultural Extension Management

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systems, Subject Matter Specialists (SMSs) or Subject Matter Experts (SMEs) having sound technical knowledge, and various other but related scientists to promptly assist the farmers with their respective questions and doubts. This way these call centers provide extension services to the farmer community according to the nature of the problem. This is an opportunity for businesses with the existing extension services to grow their network further to help farmers in remote areas of the country adopt better practices. When a KCC (Kisan Call Center) representative receives a call, he or she addresses the query based on their own knowledge and understanding. Also, the representative has access to a knowledge database containing FAQs, which is updated continuously with every incoming and outgoing call. The different type of calls can be identified as— Technical Query: • • • • • •

Crop Production Crop Protection Horticulture Agriculture Animal Husbandry Marketing Others include:

• • • • • •

Admin related query Regarding Government Schemes Subsidy Seeds Positioning Gypsum, Fertilizers, Pesticides Credit and insurance

Farmers can provide feedback on the agriculture services provided by the government and the private sector; this helps in regular monitoring and improvement in services. These call centers are generally a part of an organization like Research Stations, ATICs, Agriculture Colleges or are outsourced, as per the specific requirements. The objectives of such ATICs are the provision of a single and streamlines delivery system for the services and products to the kisans (farmers) and other FIGs as a continuous process of technology dissemination innovation. They also encourage the callers/users and facilitate them to provide their valuable feedback. The services offered by the call centers usually include customer support, multi-lingual direct assistance and other services. The senior agriculture scientists and experts in the government system are Nodal Officers. The infrastructure of Kisan Call Centers is divided into three levels: •

Level I: A Call Center that is professionally managed including all the basic requirements for a stable network and smooth communication. The call center management dedicated for the KKC services maintains Local Area Network (LAN), Air Conditioning, equipment such as computers, headphones and an Uninterrupted Power Supply. Qualification representative: M.Sc. in Agriculture

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•

•

The major functions carried out by a Level I representative are being a first point of contact to the farmers, he attends the call with a welcoming message and takes the question down and feeds that into the computer by himself. The operator will be fluent in the local language and in most of the cases he is equipped to answer the question himself. Level II: A response center handling the services of Subject Matter Specialists for individual problem based query resolution. This contains upgraded and more robust technology setup as compared to Level I. Qualification of representative: PhD. In Agriculture, with 10-15 years of experience in relevant sector. The Level II representative holds certain responsibilities like answering the questions if the Level I representative couldn’t answer the questions posed by the farmer. The Level II representatives comprises of the Subject Matter Specialists who stays at their respective places like educational institutions or the Govt. Offices. Depending on the expertise they hold the specific question will be forwarded to those persons. The expertise basically will be classified depending upon the crop or certain other parameters. In any case if the person is unavailable then there is a callback option where the question poser will be called back in mostly less than 72 hours. Level III: the Nodal Cell comprising of the Nodal Institutions is also fully equipped with the appropriate logistic support. The senior officers resolve queries and problems using software analysis tools. Qualification of manager: Masters in Agriculture, having 5-10 years of experience

For Level II and Level III support, agriculture agents are nominated from various institutions and organizations all over India. Proper training and induction is provided to the nominated graduates. An important part of this organization is the Human Resource. The personnel attending calls need to possess basic skills to attend to farmers’ calls effectively. Few skills identified are •

•

70

Soft Skills ◦◦ Greeting and facilitation ◦◦ Ability to speak using farmer’s language ◦◦ Usage of simple sentences and words ◦◦ Patient listening ◦◦ Probation of the details ◦◦ Diagnosis of the query/problem raised by the farmer ◦◦ Answering at the level of the farmer Communication Skills ◦◦ Empathizing with the caller ◦◦ Active listening ◦◦ Commitment to assist the caller ◦◦ Assertive responses ◦◦ Relating with local or personal experiences, as need be ◦◦ Polite replies ◦◦ Subtle modulations or transitions in voice ◦◦ Closing the calls with greetings as well

 The Impact of Kisan Call Centers on the Farming Sector

•

Computer Operating Skills ◦◦ Basic know how of the mouse and the keyboard ◦◦ Basic know how of the internet ◦◦ Receiving and sending electronic mails

For successful implementation of any system there is always a need to monitor and review the regular performance using methods such as feedback from inside and outside the organization. Storing the data by Nodal Offices on a regular basis lays the foundation of such an extensive knowledge base. Analysis of the collected data takes place at these Nodal Institutions by specialist suitable for the job. The same Nodal Institutions are also responsible for documentation and reporting that help in creating consolidated courses of action for individual farmer’s query.

OBJECTIVE • • •

Study of the concept and mechanism of operation. Understanding the ground level function of Kisan Call Centers. Analyzing the structure of the scheme.

RESEARCH DESIGN Based on the learning and research, the elements of survey and data collection were inferred, by focusing on the planning, implementation and management of Kisan Call Centers. Certain Measurement indicators were identified to assess their performance and recommend opportunities for improvement. Parameters that were chosen include • • • • • •

Number of daily calls received Agent quality Network sustainability Infrastructure Utility of software and technology Training

The expectations of the government and other stakeholders in the scheme were used to form an understanding about the size of the scheme. Some of the expectations from this scheme: • • • • • • •

Over 500 calls per day Technically sound personnel with good communication skills to resolve problems efficiently Smooth network quality and reliable connections Building regular Database Adequate infrastructure matching all technical requirements Simple User Interface of software Technical training to be continuously provided to representatives

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A strong software tool that has been developed by Telecommunications Consultants India Ltd. (TCIL) supports Kisan Call Centers and ensures instant and continuous connectivity across the entire network. The Management Information System enables technical assistance to farmers and recording of queries to build a database, which is accessible all times to the KCC. The database mainly consists of questions asked by farmers along with their answers. Report generation software is bought in use by the agriculture graduates having a user interface to generate reports based on specific parameters entered by the agents, according to the requirements of the concerned farmer. The filters used for scanning through database for generation of report are date, location, crop, problem etc. This data is made available over the Internet once the report is generated.

RESEARCH METHODOLOGY Secondary data was gathered from various sources such as articles, journals and case studies from the Ministry of agriculture. This data was the basis of obtaining an in depth knowledge of the concept leading to a structure for the research. Primary research was conducted involving site visit of KCC’s nodal office in Ghaziabad. Information was gathered on the implementation and response of farmers towards the scheme. The objective of the primary research was to conduct analysis of data collected and inferring the grass root level implementation implications of the scheme. Further, identifying loopholes, if any and providing recommendations based on the learning and findings.

LITERATURE REVIEW Maximizing the crop productivity is one of the major problems in a country like India where agriculture is the primary occupation. The crop productivity poses a huge problem pertaining to the amount spend on raising the crop and the amount a farmer can earn selling the crop in the market. One among the many reasons for not achieving the desired output is that the expert advice is not reaching the farmers on time. There is a lot of information gap between the research and actual practice. To bridge this gap, the research paper (P. Krishna Reddy and R. Ankaiah, 2005) mentions about a framework. According to the framework mentioned, each farmer will be equipped with Agricultural information dissemination system (AgrIDS) which is cost effective. This helps the farmers to cultivate with the help of both the crops related, location related experts. The proposed framework mentions the integration of IT services, which grew rapidly over the last few decades, with agriculture. As it was mentioned that all the farmers will be made available, the AgrIDS system, so that the farmers can get the timely advise from the experts. It involves the pictures taken from the fields and then they will be transferred to the experts. They will have a look at those pictures and then will provide the advice analyzing them. The advice definitely will not be based on the received pictures alone but there are lot many details the experts, in their own area of expertise, will suggest the farmers which crops to elect and raise depending upon some of the major factors influencing the agriculture like rainfall, soil type, weather etc. Also financial experts suggest the farmers about the crops which possibly will have high demand in the international or the domestic market which will help the farmers to earn profits. Also production of certain crops in the country is rather scarce when the consumption is taken

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into consideration so government can take steps into providing certain schemes that can motivate the farmers to raise that crop. The research paper (P. Krishna Reddy and R. Ankaiah, 2005) also mentions about the drawbacks of the traditional system. At present the insights given to the farmers are in a generic and not specific to the certain farmers so for some the advice helps but a lot people might get affected either by not getting the desired productivity nor the profits. It does not cover all the farmers but only a few. There are numerous reasons some being the literacy levels, lack of awareness etc. The traditional process is just a one way process and if the farmers need more information on what they have been farming they couldn’t get the information on time. The major drawback being unaccountability – number of advices given and the number of advices that are turned out to be useful. The proposed AgrIDS overcomes these drawbacks to a major extent. The AgrIDS system will be using the data ware housing technologies, data mining techniques. Saving large amounts of data has become an easy task in the recent years. So all the queries that the system will receive in the form of either text or photos will be recorded along with the answers. This data being saved can be used in the future if the advice is requested for similar kind of problem by a farmer. In the present world extensive information is available online and there are many companies whose business model runs only on the data. With all of this enormous amount of data available it can be analysed and then refined so that the patterns can be drawn using the data mining techniques. Extrapolating the data available simulation models can be developed so that the future possibilities can be drawn from them. For all of this to happen the internet should be made available to all class of people where they can make use of the system proposed. The system consists of various parts including farmers, coordinators, AEs and Agricultural information system where all of them are integrated using internet. The amount a farmer would invest in receiving the advices is substantially less by using this system. Amount of pesticides and fertilizers to be used for a crop can be moderated based on the actual requirement for high output. Because of lack of experience of the farmers they might not be using the adequate amounts of pesticides or the manure. So making this AgrIDS system available to the farmer, the money a person spends on the fertilizers will be saved substantially. A research was taken up by a group of researchers from MSSRF (M.S Swaminathan Research Foundation) about the technical advancements in the field of crop husbandry that took place in the country pre – post independence periods and their implications. The research paper (R. Rukmani) mentions about the ICAR system which developed around 3000 hybrids and high yielding varieties related to various crops which promises more productivity and less prone to diseases. Some of these varieties were used in the country to witness a huge increase in the crop productivity. The statistics backs the fact that the growth rate in the 1990s was less compared to 1980s possible reason mentioned was because of the lack of the proactive decisions by the country in that time frame. Also the challenges faced by the government are the Intellectual property rights adoption and the assessment of advances in the biotechnology fields. The policies during the early decades after independence will have to see a significant change to meet the present changes in the field of the crop husbandry. Considering both the research papers, (R. Rukmani) mentions about how the scientific technology totally shifted the face of agriculture to meet the growing demand and also mentions that some amends to the present policies are required to withstand the changes in this present world. This research paper (P. Krishna Reddy and R. Ankaiah, 2005) mentions about a framework consisting of AgrIDS that will help the farmers. While during the early decades when there was only a limited connectivity among the

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people, the state had taken steps to help farmers use the ICAR developed crop varieties (like Rice, Wheat and some Cereals) and it took decades for the crop productivity to reach to the current state. While taking into account the connectivity among people and the reach of any information in the present day, with advancements in the scientific development and integrating those with the IT models such as AgrIDS will definitely help the increase in the crop productivity. Kisan call center have been one of the most pioneering initiatives by the Government of India. According to a report published in Asia Pulse, the Kisan call centers in India received 318,106 calls in total. These calls were from farmers who belonged to remote and tribal areas who sought solutions for their problems that varied from agriculture to animal husbandry. The Indian Society of Agricultural Professionals (ISAP) released this data. The ISAP is the organization that sponsors the functioning of the call centers. The article further stated that most of the queries originated from Shivouri and Shajapur districts in Madhya Pradesh. Also, the tribal areas over there also called up these centers to clear their doubts. The number of calls relating to agriculture crops were 173,274, while those about horticulture summed up to 93,299 and 12,802 were from the field of animal husbandry. Currently, the service has been made available from 6 AM to 10 PM, except for Sundays and gazetted holidays. The service is provided beyond these hours by an IVRS system. There are fifteen subject specialists that are employed and available at the call centers in Madhya Pradesh who work in two shifts to ensure maximum time is available to cater to the queries of farmers. The Kisan call center here is managed and run by National Agricultural Development Project through a private public partnership. The Kisan call centers are equally effective when it comes to solving the problems of farmers in the hilly regions of Himachal Pradesh. A study conducted by Sharma and Singh in 2011 concentrated on two cash crops that are grown in the region, apple and tomato. These crops are grown in the high and medium hills of the state respectively. According to the study, the farmers who used the services of the calls center were more informed about their crops and benefitted from it. The productivity of crops of these farmers was much higher than those who did not used the services. It suggested that the farmers should be educated by the media and government about the call center so that farmers can grow their crops more effectively and scientifically. Recently, the Government has collaborated with IFFCO Sanchar Limited for the restructuring of the KCC’s. The new call centers would be state of the art and shall provide professional assistance as well as well technical innovations to the existing service network. These include call barging that will be handled by experts and officers of the government, video conferencing, dynamic monitoring of the working of the call centers. The books and reference material provided to the employees will also be upgraded to the latest editions of modern agricultural practices. The IKSL (IFFCO Kisan Sanchar Ltd.) has attempted to provide many innovation, interactive and engaging services for the farmers that subscribe to the KCCs. These services and its subscription is absolutely free of charge and includes benefits and activities like free voice messages on a daily basis to every subscriber, on his area of interest, call back facilities, mobile quizzes, common forums and focus groups. Their prime mission is to empower the rural section of the society and the farmers with high quality and germane services and information, through proper telecommunication and other communication channels. 84% of farmers were satisfied with the advice that they received from the call center personnel, as stated by the study conducted by Administrative Stall College of India in 2012. The study further revealed that the advice helped the farmers in efficiently managing their fertilizer and pesticide usage, which reduced the weeds, pests and diseases in crops. Moreover, this initiative is built and structured in a manner to accommodate continuous evaluations and monitoring, that would help the same to grow 74

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in a more effective manner. After the research, it was also found that TNAU (Tamil-Nadu Agricultural University) formed Farmer’s Associations – FIG (Farmer Interest Group) which is essentially an independent and self-managed group of farmers with common goals and interests. The members of this group pool in their resources, so that by uniting their resources, they can work towards the fulfilment of their common goals and objectives and share the consequential benefits.

DATA ANALYSIS Nodal officers in Delhi and Ghaziabad aided in collection of data, to assess the performance and grass root level implementation of KKCs. The Scheme was launched at the time when BJP government was in power in India and the KKCs received recognition, showing good results and positive response from farmers. The services provided through KCCs are monitored and reported by these Nodal offices. Although, the offices were equipped with all the facilities claimed by the government, a lackadaisical attitude was observed on our visits to the offices in New Delhi and Ghaziabad. All over the scheme has a total outreach to over 1500 villages and around 30 districts in 17 states of the country. This scheme has also provided employment to over 1800 BPL (Below Poverty Line) youth, living in rural India, by conducting training programs. The knowledge base has grown immensely since the inception of these call centers. KCCs have enabled spread of knowledge amongst farmers and access to information easy by providing a proper channel supported by the government and private parties. States where the scheme has been most successful, like, Bhopal, Madhya Pradesh have KCCs running in Public Private Partnerships (PPP). A list of call centers across major states can be seen in Table 1.

RESULTS AND FINDINGS The important findings from the project research are that Kisan Call Centers have: • • • • • • •

Transformed and impacted the lives of more than 1.25 lakh farmer families. Provided Specialized Training and job opportunities to over 1800 BPL youth. Promoted Entrepreneurial developments to bring in greater avenues for private ventures to agriculture graduates. The Bhopal KCC alone has answered up to 5 lakh queries during 2008-11. Made effective use of technology. A robust MIS system helps in advisory services and building knowledge base. Over 250 graduates, those have been certified as Crop Certified Advisor (CCA). Highest calls recorded for the vegetable growers, closely followed by food grain growers and fruit growers. 23.5 percent of the calls were recorded for the information about various diseases in the crops and 6.9 percent of the calls were related to animal husbandry.

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Table 1. Call centers across major states S.no

State/ UT

KCC Location

Language

Telephone Lines (Outgoing- incoming)

1.

Andhra Pradesh

Hyderabad

Telugu

2-3

2.

Bihar

Patna

Hindi

1-2

3.

Jharkhand

Ranchi

Hindi

2-3

4.

Chhattisgarh

Raipur

Hindi

3-4

5.

Delhi

New Delhi

Hindi

2-4

6.

Dadra, Nagar Haveli

Ahmedabad

Gujarati

1-2

7.

Gujarat

Ahmedabad

Gujarati

3-4

8.

Punjab

Chandigarh

Punjabi

2-3

9.

Haryana

Chandigarh

Hindi/Haryanvi

3-4

10.

Himachal Pradesh

Shimla

Hindi

2-3

11.

Jammu & Kashmir

Jammu

Dogri, Kashmiri, Ladhaki

2-3

12.

Karnataka

Bangalore

Kannada

2-3

13.

Kerala

Trichur

Malayalam

1-2

14.

Maharashtra

Nagpur

Marathi

2-4

15.

Uttar Pradesh

Kanpur

Hindi

3-4

16.

Rajasthan

Jaipur

Hindi

2-3

17.

Tamil Nadu

Coimbatore

Tamil

2-4

18.

Uttarakhand

Dehradun

Hindi

NA

19.

Arunachal Pradesh

Itanagar

Adi

NA

20.

Assam

Guwahati

Assamese

NA

*NA—Not Available Source: Directorate of Extension - KCC

SUGGESTIONS AND FUTURE IMPLICATIONS The use of technology is critical to bridge the economic gap prevailing in the country, to stimulate growth by building individual capacity to generate value through learning the immense opportunities in agriculture and allied services. A shortcoming in the TOT (Transfer of Technology) model is a prominent challenge for the current private and public extension systems, however, the effective and efficient use of telecommunication channels, relevant technologies and internet, this gap can be bridged by a considerable extent. After studying and analyzing the concept implemented by the government with the emergence of KCCs, we suggest that more private organizations should show participation in such initiatives, by forming alliances with the government and NGOs. In states where the scheme is to be launched, the mobile carrier partner companies can come up with initial promotional offers for farmers, such as distribution of registered sim cards to them. This would encourage the farmers, make life easier for them and spread greater awareness amongst them regarding KCCs.

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Also, more importance should be given to courses like CCA (Crop Certified Advisor) and the youth, especially in the rural parts of the country, should be encouraged to pursue this as a career option. Contemporary technology should be leveraged more effectively to facilitate growth. Promotional campaigns using mobile wagons and kiosks should effectively spread the scheme to untouched remote areas of the country.

REFERENCES Chouhan, R. S., Kumar, Dushyant, & Sharma, H O (2011). Performance of Kisan Call Center: A Case Study of Kisan Call Center of Indian Society of Agribusiness Professionals Bhopal (Madhya Pradesh). Indian Journal of Agricultural Economics. Retrieved October 9, 2013, from http://search.proquest.com/ docview/912670940?accountid=50136 Dhyani, S. (n.d.). BPO Caretel announced the achievements of their “Kisan Call Center” project As Kisan Call Center completes its successful 5th Year. Retrieved October 10, 2013 from http://www.indiaprwire.com/pressrelease/agriculture/2009011718157.pdf IFFCO Kisan Sanchar Ltd. (n.d.). Retrieved February 12, 2014, from http://www.iksl.in/ KCC: Features, Directorate of Extension. (n.d.). Retrieved October 10, 2013, from http://vistar.nic.in/ training/locations.asp Kisan Call Center. (n.d.). Retrieved May 5, 2013, from http://agricoop.nic.in/policyincentives/kisancalldetail.htm Krishna Reddy, P., & Ankaiah, R. (n.d.). A framework of information technology-based agriculture information dissemination system to improve crop productivity. Ministry of Communications and Information Technology, Department of Information Technology, New Delhi, India. Retrieved May 17, 2014, from http://www.currentscience.ac.in/php/toc.php?vol=088&issue=12 Mukherjee, A. (2007). Fodder on the Line. Business Today, 16(9), 62. Retrieved October 8, 2013, from http://web.ebscohost.com/bsi/detail?sid=62b7dd32-2b33-47ea-9c6f-f67a8b588225%40sessionmgr14& vid=1&hid=19&bdata=JnNpdGU9YnNpLWxpdmU%3d#db=bth&AN=24844647 Over 300,000 MP Farmers Indian used Kisan Call Center: Report, Asia Pulse Pty Ltd. (2010). Retrieved October 10, 2013, from http://search.proquest.com/docview/759359583?accountid=50136 Rahul, A. (2011). Kisan Call Center: Bridging the information gap. Retrieved October 10, 2013, from http://www.thebetterindia.com/2304/kisan-call-center-bridging-information-gap/ Rao, S., & Sharma, V.P. (n.d.). Tele-Agri-Advisory Services for Farmers: a Case Study of Kisan Call Center in Andhra Pradesh. Academic Press. Rukmani, R. (n.d.). Measures of Impact of Science and Technology in India: agriculture and rural development. Retrieved May 21, 2014, from http://www.currentscience.ac.in/Downloads/download_pdf. php?titleid=id_095_12_1694_1698_0

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Sharma, B. R., Singh, P., & Sharma, A. (2011). Role of Kisan Call Centers in Hill Agriculture. Indian Society of Agricultural Economics. Retrieved October 11, 2013, from http://search.proquest.com/docv iew/912670948?accountid=50136 Tiwari, R. (2012). Government ropes in IFFCO Kisan Sanchar Limited to improve Kisan Call Centers [Agriculture]. The Economic Times (Online). Retrieved October 7, 2013, from http://search.proquest. com/docview/1011117854?accountid=50136 User Manual Version 1.0 for Kisaan SMS Portal. (n.d.). Retrieved September 8, 2013 from http://farmer. gov.in/advs/User%20Manual%20for%20Kisaan%20SMS%20Portal_Ver1%200.pdf

KEY TERMS AND DEFINITIONS AgrIDS: Agricultural information dissemination system, an online system proposed where the entire process of examining the crop and suggesting the productive steps by the specialists can be done online. ATIC: Agricultural technology information Centre, a place where the information regarding the agriculture can be available. GAP: Good Agricultural Practices, the best practices that can be adopted to attain the best possible output. KCC: Kisan Call Center, a call center where farmers can get their queries regarding the agriculture can be answered. PPP: Public Private Partnerships, a type of partnership where the public, private together is involved to raise the capital and be a part and owner of certain project. SME: Subject Matter Experts, a part of the KCC where they would be answering the questions addressed to them to their best in order to resolve the farmer’s queries. TOT: Transfer of technology, where the use of technology among the stake holders.

This research was previously published in Promoting Socio-Economic Development through Business Integration edited by Shalini Kalia, Bhavna Bhalla, Lipi Das, and Neeraj Awasthy, pages 76-88, copyright year 2015 by Business Science Reference (an imprint of IGI Global).

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Chapter 5

Fundamentals of Electrostatic Spraying:

Basic Concepts and Engineering Practices Manoj Kumar Patel Academy of Scientific and Innovative Research, India & CSIR-Central Scientific Instruments Organisation, India Chirravoori Ghanshyam CSIR-Central Scientific Instruments Organisation, India

ABSTRACT The desired attributes of electrostatic spraying are uniform deposition onto both directly exposed or obscured crop surfaces which minimize the off-target losses of active ingredients to soil, water, atmosphere and provide more effective and economical pest control. This chapter presents an overview of electrostatic spraying technologies in the field of agriculture emphasizing the key role of advanced electrostatic instrumentation and chronicles the scientific innovations in the parlance of providing cost effective and reliable commercial systems along with an insight on the needs of future research perspectives and directives. It is aimed primarily at a familiarization with spraying concepts and engineering practices. This text is to bridge the knowledge and experience gap among researchers and technology developers and the people involved in electrostatic processes applied to agriculture and food processing. It will also introduce the engineering aspects of design and development of an electrostatic spraying nozzle for agricultural applications.

INTRODUCTION Air-assisted electrostatic sprayers are advanced agri-instruments for efficient use of pesticides to agricultural crops, orchards, plants, trees etc. The electrostatic spraying technique is all about reducing the use of pesticide by increasing the efficiency and bio-efficacy. Bio-efficacy is a measure of the biological efficacy of an active ingredients of agro chemical such as insecticide etc. The methods used to perform the function of bioremediation are known as bioremediators. Electrostatic spraying is to be the one DOI: 10.4018/978-1-5225-9621-9.ch005

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 Fundamentals of Electrostatic Spraying

among the available spraying techniques in precision agriculture and food processing. For example, the electrostatic spraying technique can be used for protective biomaterial coatings to fruits and vegetables for resistance towards microbial attacks, to enhance the transportation life, to control spoilage microorganisms, antimicrobial sprays for enhanced food safety etc. It is a method which reduces the environmental pollution by reducing contamination to soil as well as air. In totality, it reduces the chemical consumption which is used indiscriminately through conventional methods such as pedestal-mounted sprayers, the high pressure spray guns, the hand pressure swirl nozzles and the consecutive high volume spraying systems etc. The trans-disciplinary aspects of the embryonic field of electrostatic spraying have provided a major motivation to agricultural and food processing researchers for the development of novel techniques for spraying liquid pesticides to crops and orchards, protective coatings to food and food packaging, in addition to other applications of sprays to industrial, manufacturing and transportation, medical facilities and devices etc. This chapter is to be one among the motives behind the renewed curiosity in the usage of the electrostatics in liquid based spraying. Although, organic measures for crop protection are being preferred, chemical intervention is still the fastest and most economical way for crop protection. However, due to lack of awareness and ignorance, pesticides are being used indiscriminately leading to side effects on human health and ecosystem. Electrostatic method of pesticide application reduces off-target drift, environmental pollution and human health risks and increases the bio-efficacy and mass transfer efficiency onto the biological surfaces of crops and trees with uniform back deposition. Law, (1978); Jia, Xue, Qui, & Wang, (2013) explained the design and development of induction based electrostatic sprayer for agricultural usage and evaluated the performance. So far, the equipment available in the market are uncontrolled in terms of spraying variability. Pesticide application control, targeted pesticide delivery and variable pesticide spraying are the key to improve operation quality, reduce chemical waste, environmental pollution and operational costs. This entices to develop a sensing mechanism which would discriminate between the presence and absence of pesticide application surfaces. He, Yan, & Chu, (2003) developed the automatic target detecting air-assisted electrostatic orchard sprayer. In this spraying system, the sensing mechanism is based on infrared proximity sensors which determine the presence and absence of target to be sprayed. Other than infrared proximity sensors, ultrasonic sensor mechanism is another substitute for target detection and canopy mapping. Sensory attributes stipulate a good approximation of target and canopy mapping for targeted delivery of pesticides to actual target. Automation and mechanization with respect to agricultural pesticide spraying is one of the naive research topics in the present scenario. The last decade has witnessed the application of existing electrostatic techniques to various fields accompanied with rapid improvements of the spraying technology. Zhang, Srirama, & Mazumder, (2007) have worked on a new approach in signal processing and sampling which shows that electrostatic applications have gone beyond the earth and reached to Lunar and Mars missions. Space research needs electrostatics in dust and particle control. Mazumder et al., (2006); Hamid, & Atan, (2008); Ghayempour & Mortazavi, (2013); Khan, Maan, Schutyser, Schroën, & Boom, (2013) ; Zhang, Kobayashi, Uemura, & Nakajima, (2013) have shown the numerous applications of electrostatic spraying to various fields such as agriculture, medical, transportation, painting and industrial applications, though agriculture remained the main area of research during the last decade. Electrostatic application to agricultural pesticide spraying has revolutionized agriculture farming scenario by making advances and developments via off-target pest control to increase bio-efficacy and deposition efficiency. There is also an increase in deposition

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efficiency by applying suitable charging techniques, better corrosion resistant material used in electrode design for spray charging and its insulation, liquid atomization methods, post processing of the spray by air assistance, automation of spray system and cost effective compact design and development for the layman in terms of easy-to-handle and simplicity of use. Developing an automated system for greenhouse spraying is the biggest challenge in the current scenario of research, since working environment inside the greenhouse is unbearable and dreadful due to the presence of increased level of humidity, carbon di-oxide and high temperature. Prolonged exposure of greenhouse workers to these conditions leads to a scratchy and hazardous work environment. Significant novel and innovative thoughts also came into existence; however, technical improvements and applications of the electrostatic spraying technique to various fields remain the main focus. This chapter reviews the advances made in electrostatic pesticide spraying to agriculture and a brief description has also been made for the charge to mass determination, software like Fluent, CFD (Computational Fluid Dynamics) used in hydrodynamics and aerodynamics processes to simulate the electrostatic models with user defined functions and Deposit Scan to measure the percentage coverage, spray deposition rate and distribution of the charged droplets etc. It seeks to give a fundamental understanding of basics of electrostatic spraying to agriculture; along with the intricacies associated with the design and development of such high performance, efficient, efficacious modern advanced agri-instruments. In this chapter, innovative and technical concepts have been summarized and explained in detail that came into existence in electrostatic spraying along with the prevue of future perspectives and needs in the current scenario. However, before getting involved with the intricacies of electrostatic pesticide spraying, one may discuss the need for and applications of electrostatics in spraying.

Purpose of Pesticide Spraying The use of pesticides to crops, orchards, plants and trees is among the most important pre-harvest facets of precision agriculture to protect the crops and for boosting the food production. Abhilash & Singh, (2009) discussed the importance of pesticides in the process of development of sustainable agriculture and shown that pesticides have become an important tool as a plant protection agent. However, exposure to pesticides both professionally and ecologically causes a number of human health concerns. The application of pesticides is one of the most frequently used methods to protect crops, orchards and trees against diseases and insects in agriculture. Off-target drift of pesticides is a term used for individuals droplets containing the full of life ingredients that are not lay down onto the target area, when spreadover crop protective pesticides to agricultural targets. The droplets most susceptible to off-target drift are usually smaller in size, less than 150μm in diameter (usually indicates the Volume Median Diameter, VMD) and effortlessly moved off the actual target area by wind, gravitational force or other agro-climatic, harsh and transient environmental conditions. The larger droplets settle down on the ground because of gravitational force. For example the conventional spraying statistics for grape growers shows that almost 60-70% of the pesticides have been lost via off-target drift and non-target deposition. Underside of the leaves and hidden areas remain untouched with the sprayed chemicals. Efficient use of pesticides can protect and optimize the environment and natural resources, since the use of non-renewable pesticides and fertilizers is perhaps irretrievable, and encompasses an environment cost. Crop protection chemicals deposited in undesirable areas raised serious concerns caused by spray

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 Fundamentals of Electrostatic Spraying

drift, such as surface water contamination, damage to sensitive neighboring crops, health hazards for living individuals as well as masses and possible adulteration to the target and adjoining areas or possible over application within the target area. Off-target drift destruction can be managed by identifying and regulating the factors that affect it such as environmental conditions, equipment and methods used for liquid spraying etc., later being the most predominant factor to avoid such consequences.

Causes of Spray Drift Managing spray drift improves pesticide bio-efficacy by guaranteeing that the correct amount of dose reaches at the target. Drift takes away the pesticide from the intended target, making it less effective, and deposits it where it is neither needed nor desired. There may be two kinds of drift in agricultural pesticide spraying: • •

Finely divided spray drift is off-target movement of the spray particles. Vapor drift is the volatilization of the pesticide segments and their movements away from the actual target.

The pesticide then becomes an environmental pollutant in the off-target areas where it can injure susceptible vegetation, contaminate water, or damage wildlife. A number of variables underwrite to spray drift; these are predominantly due to the spray equipment system and meteorological factors: • • • •

Droplet size and spray height. Operating speed, direction and wind velocity. Air temperature and humidity. Crop protection chemicals and carrier volumes.

Various officialdoms conduct rigorous distribution and drift testing. The reliable data is also very important when conducting drift experiments and it comes from independent testing agencies, such as Food and Environment Research Agency (FERA) in the United Kingdom, the Julius Kuhn Institute (JKI) in Germany and the Centre for Pesticide Application and Safety (CPAS) in Australia. Varieties and consumption of pesticides worldwide have been increasing dramatically as increased human population and crop production. In this process, misuse of pesticide becomes more and more serious, has resulted in heavy environmental pollution and health risk of living beings. Study shows that, even a fraction of percentage of efficiently sprayed protective pest by using advanced spraying equipment such as electrostatic nozzle, is sufficient for the desired biological target as compared to conventional methods. The charged particle evaporation, droplet instability and its implications to agricultural spraying are justifiably explained and presented theoretically as well as experimentally by Law & Bowen, (1975). The surface energy condition can be drastically altered by the presence of unbound surface charge on an air-borne spray droplet. Evaporating droplet carries no charge as a result an increase in surface charge density is witnessed. This increase in charge per unit area cannot increase infinitesimally; approaches a critical level, called Raleigh limit of charge, at which the liquid surface ruptures and gives birth to small daughter droplets.

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ELECTROSTATICS AND PESTICIDE SPRAYING: THEORETICAL CONCEPTS Electrostatic force field application in agricultural spraying is a new technique to apply for the protective liquid pesticides and to reduce the off-target drift. It improves the efficiency of the system and bio-efficacy of the biological crops. For example, air-assisted electrostatic spraying, aerial electrostatic spraying system assembled in Helicopter and Tractors, are the modern systems used in agricultural pesticide spraying applications. In electrostatic spraying, finely divided droplets are charged by the application of high electrostatic potential to charging electrode. The system should work at lowest possible applied voltage so that it will work on low power consumption and hence the duration of the power supply. For efficient working of the system, ultimately one has to increase the charge to mass ratio at lower applied voltage as there is a trade off between applied potential and power consumption. Electrostatic space charge and induced image charge forces enhance the uniformity of spray on the target surface, increase the transfer efficiency, bio-efficacy and adhesion. Electrostatic forces minimize the effect of gravitational force which is the main cause of spray drift and ground fall of the pesticide. The electrostatic forces levitate the charged droplets against the gravitational force; however levitation of the droplet depends upon the droplet diameter, surface tension, applied electric field and density of the liquid. The electrostatic spraying process is a very complex phenomenon which can be divided into three basic regions:

Hydro Electrodynamics It mainly consists of liquid atomization and finely divided particulate matter charging. Liquid atomization can be achieved through centrifugal, pressure, air, hydraulic, pneumatic or electrostatic forces solely or by a combination of two or more of these forces. Chigier, (2007) showed the Challenges for future research in atomization and spray technology. Droplet charging methods include conduction, induction, tribo-electric, and corona charging; the induction charging is predominant in conductive liquid pesticide spraying.

Aerodynamics It includes charged particles/droplets transport and charge retention. In the droplet transport region, aerodynamic, inertia, electrostatic and gravitational forces work together to determine the trajectories of the charged droplets.

Electrostatics It mainly involves the actual spray deposition on the target; either it is conducting or non-conducting target. Electrostatic deposition onto a conductive target relies upon a displacement current to transfer electric charge onto or off the target to a degree appropriate for maintaining it at earth potential in the presence of the approaching charged-particulate cloud. In electrostatic spraying, it is assumed that the charged particulate matter is a slow moving phenomenon and therefore magnetic Lorentz force is negligible in comparison to electrostatic force.

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 Fundamentals of Electrostatic Spraying

In electrostatic pesticide spraying, the following fundamental phenomena are of great importance which have to be taken into consideration for the better understanding of the subject: • • • • •

Droplet charging methods. In-flight trajectory of charged droplet. Optimizing the deposition field and transient effects at deposition targets. Charge to mass evaluation and hence efficiency and efficacy of the spraying system. Understanding the drop size and its measurement.

Droplet Changing Methods Research approaches to agricultural spray charging have been based upon several distinct principles. Maski & Durairaj, (2010) showed in their previous work that a major portion of the electrostatic pesticide spraying has been in the development of reliable means for droplet charging. Motion of a charged particle can be easily controlled by the electric force, which depends on the charging level. Therefore, it is desirable to charge the particle to as high as possible and the charged droplet must be acted upon by an electric field. Well known and field-proven methods for imparting the necessary and sufficient charge to pesticide spraying droplets are divided on the basis of conductivity of the liquid to be sprayed: • • •

Ionized-field droplet charging (for both types of conductive as well as non-conductive liquids). Electrostatic-induction droplet charging (only for conductive liquids). Direct contact charging (for non-conductive liquids).

Law, (1984) presented a thorough consideration of these charging techniques and pros and cons accompanying with each method, accentuating their applicability as dictated by the physical properties of the pesticide-liquid to be electrified. Each method of charging has advantages and disadvantages in terms of liquid conductivity to be electrified, the level of applied voltage, insulation from the rest of the associated device, power consumptions etc. Induction charging is the most predominant method of charge electrification to fine droplets in pesticide spraying.

Ionized Field Droplet Charging In corona charging, a sharp electrode is held at a high potential resulting in a local electric field high enough to ionize the surrounding air. The positive charges in the ionized air are less mobile than the negative ones and so remain in the vicinity of the electrode long enough to be picked up by a passing liquid stream. It requires a high applied voltage ranging from few thousands to more than a hundred thousand volts, depending upon the geometry of the charging equipment. Either solid or liquid particles, of diameters larger than approximately 0.5 μm, travelling through this ionized-field region can acquire by ion attachment, a saturation charge dependent upon the particles dielectric constant, its surface area, and electrical characteristics of the corona discharge. Ionized-field charging theory has been well developed mathematically by Law, (1984) and can be used to calculate the net electrical charge imparted to an air-born particle as:

84

 Fundamentals of Electrostatic Spraying

K −1   4πε o Eo rp2 q p = f 1 + 2  2 K +  

(1)

where K is the dielectric constant, f is the saturation factor, Eo is the applied electric field and rp is the radius of the droplet. The fraction of the saturation charge actually attained by the particle depends upon the residence time, and the concentration and mobility of the ion in the charging field. For aqueous-based sprays (K=80) charged to half-saturation (i.e. f=5) in a typical corona-discharge nozzle, droplet charge in coulombs typically attains a value of:

q p  6πε o Eo rp2

(2)

 9ε E  1    0 0  C/kg, where δ represents the surface mp  2δ  rp tension of liquid. While the ionized-field charging method is routinely used in a variety of commercial and industrial processes ranging from xerography to electrostatic precipitation, greater care must be exercised in properly designing the process into agricultural spray-charging devices, in order to maintain long-term charging reliability. Difficulties relate to the fragile nature of the exposed corona electrode, to the elevated ionizing voltage required (typically more than 15kV), and to the onset of reverse ionization from the passive electrode when inadvertently wetted or coated with resistive particles. With an associated charge to mass ratio of

qp

Induction Charging In 1980s, the work led by S. Edward Law at the University of Georgia, developed induction based spraycharging method meeting the engineering design requirements of robustness, simplicity, reliability, energy efficiency, and safety. The electrostatic-induction and the ionized-field spray charging methods are the ones widely used throughout many industrial processes. Agricultural charging based nozzle development has mainly relied upon the induction charging methods. This section presents a detailed consideration of induction spray-charging techniques, emphasizing their applicability as dictated by the physical properties of the pesticide-liquids to be electrified. Spray liquid is normally electrically neutral. To charge a spray, the normal balance between positively charged protons and negatively charged electrons has to be disturbed so that spray droplets carry either a net positive charge or net negative charge. Droplets with same electrical sign (+ or -) repel while those with opposite charges attract. Electrostatic induction has proved to be a very satisfactory alternative to the ionized-field method of charging spray droplets for agricultural pesticide applications. Figure 1 indicates the complete picture for understanding the induction charging phenomena. In this method, direct-transfer to the droplet-formation zone of a liquid jet results from electrostatic induction of electrons on to the continuous liquid jet and in order to maintain it at ground potential the presence of closely positioned induction electrode of positive polarity is required. Droplets, formed from the surface of this negatively-charged jet, will depart with net negative charge provided the droplet-formation zone remains subject to the inducing electric field acting between the non-ionizing electrode and the liquid jet.

85

 Fundamentals of Electrostatic Spraying

Figure 1. Induction charging of finely divided particulate matter

Gauss’s law indicates that maximum droplet charging should occur for the droplet-production zone located at the region which provides maximum field strength at the terminal surface of the liquid jet. In induction charging of the spray droplets, two time constants are of importance: 1. Time constant of charge-transfer (τ) 2. Droplets formation time constant (tf) The level of droplet charge imparted by electrostatic induction depends upon the relative time rate of charge transfer to the droplet-formation zone, as compared with the time required for droplet formation. The charge-transfer capability by induction from a grounded metal nozzle through the issuing liquid jet depends upon the electrical as well mechanical properties of the continuous liquid jet. The two most important properties of the liquid to be sprayed are: 1. Electrical properties such as conductivity, dielectric constant, permittivity etc. 2. Mechanical properties such as density, viscosity, surface tension etc. For pesticides, the spray-liquid characteristic may be specified by the charge-transfer time constant, which is a function of the electrical conductivity (σ) and the dielectric constant (K) of the liquid as: τ = (K ε0 ) / σ

(3)

If a duration of time tf, characterizes formation of discrete droplets from the continuous jet, then spray liquids must satisfy the condition τ α2m2 + λβ2m1

(2)

Table 10 shows the evolutionarily stable results. Figure 4. Phase diagram of the evolution (1)

Table 10. Evolutionary stable results (2) Balance Point

det J

tr J

Local Stability

(0,0)

+

-

ESS

(0, 1)

-

Uncertain

Saddle Point

(1, 0)

+

+

Unstable point

(1, 1)

-

Uncertain

Saddle Point

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 The Empirical Study on the Evolutionary Game Based Agricultural Products Supply Chain

When the upstream stakeholders’ excess return is less than the input costs, the excess return of the downstream stakeholders is greater than input costs, as the evolutionary stable results (0,0). Figure 5 depicts the phase evolution of the process. The final evolution result will converge to the set of (provide agricultural products with violations, not to assume responsibilities). r1e + β1m2 > α1m1 + λβ1m2 , r2e + β2m1 < α2m2 + λβ2m1

(3)

The Table 11 shows the evolutionary stable result When the upstream stakeholders’ excess return is greater than the input costs, the excess return of the downstream stakeholders is smaller than its input costs, as the evolutionary stable results (0,0). Figure 6 depicts the phase evolution of the process. The final evolutionary result will converge to the set of (provide agricultural products with violations, assume with no responsibilities). r1e + β1m2 > α1m1 + λβ1m2 , r2e + β2m1 > α2m2 + λβ2m1

(4)

Table 12 shows the evolutionary stable results. Figure 5. Phase diagram of the evolution (2)

Table 11. Evolutionary stable results (3) Balance Point

det J

tr J

Local Stability

(0,0)

+

-

ESS

(0, 1)

+

+

Unstable point

(1, 0)

-

Uncertain

Saddle Point

(1, 1)

-

Uncertain

Saddle Point

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 The Empirical Study on the Evolutionary Game Based Agricultural Products Supply Chain

Figure 6. Phase diagram of the evolution (3)

Table 12. Evolutionary stable results (4) Balance Point

det J

tr J

Local Stability

(0,0)

+

-

ESS

(0, 1)

+

+

Unstable point

(1, 0)

+

+

Unstable point

(1, 1)

+

-

ESS

(p , q )

-

0

Saddle Point

*

*

When the upstream stakeholders’ excess return is greater than the input costs, the excess return of the downstream stakeholders is also larger than its input costs, which is the evolutionary stable results (0,0), (1,1) from the evolution of the phase diagram. There are still two unstable points (0,1), (1,0) and the saddle point (p *, q *). Figure 7 depicts the process of the view of dynamic evolution from the saddle point and instability point even into the fold between the two game sides which converges on the critical line in different states. The evolution of the game results will change along with the saddle point and converges to a different equilibrium.

6. CONCLUSION 6.1. Test Results It can be seen that the relative size of the cost and the excess return of upstream and downstream stakeholders of agricultural products supply chain will directly affect the ultimate evolutionary stable results.

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 The Empirical Study on the Evolutionary Game Based Agricultural Products Supply Chain

Figure 7. Phase diagram of the evolution (4)

1. In Case of the Excess Returns Are Less Than the Cost of the Upstream or Downstream Stakeholders: By means of the evolutionary stable results of (0,0) from the three former evolutionary phase diagrams, whether what the initial state it starts from, the final results will converge to the evolutionary set of (provide agricultural products with violations, assume with no responsibilities). 2. In Case of the Excess Returns Are Greater Than the Input Costs of Upstream and Downstream Stakeholders: When the evolutionary stable results set to (0,0), (1,1), it means the upstream and the downstream stakeholders select to provide agricultural products with violations and not to assume responsibilities, or select to provide agricultural products with safety and assume responsibility individually. There are two unstable points (0,1), (1,0) and a saddle point (p *, q *) in the evolutionary phase diagram. The Figure 7 depicts a dynamic evolution with the critical line that was converged by a fold line between the saddle point and unstable point with the two parties during the game process. As seen in the upper right area ADBC, the system converges to the strategy set of (provide agricultural products with safety, assume responsibilities), and in the lower left area AOBD, the system converges to the strategy set of (provide agricultural products with violations, assume with no responsibilities). In a long evolutionary process, the outcome of the game will be varying along with the saddle point change, and will converge to different equilibriums. 1. The smaller the cost coefficient α, the greater of the top right area is, and the evolutionary game should become more possible to converge to (1,1). When the supply chain of agricultural products is becoming more and more refined, the chain is getting shorter and shorter, the market pays more attentions to standardization, the cost will be reduced accordingly. Meanwhile, the cost will be

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 The Empirical Study on the Evolutionary Game Based Agricultural Products Supply Chain

2.

3. 4.

5.

affected by the changes of cooperative enterprise operations management, the new technologies, the improved policy environment, and other factors. In order to reduce the cost factor for upstream stakeholders of agricultural products supply chain, the large-scale management must be formed, the establishment of supply alliances, the standardized management not only reduces costs but also ensure to offer the quality and safety of agricultural products. For the downstream stakeholders, the government policy support and incentive, such as willingness to assume responsibility of enterprises to implement certain compensations, rewards, and reducing the costs. The degree of synergy between the two sides of the game affects the overflow coefficient β. If the upstream stakeholders provide safe agricultural products, the downstream stakeholders assume responsibilities, both sides of the game launched an effective cooperation, and there is no evasion of responsibility, then one party can get the overflow income from the other side. The larger the overflow coefficient, the bigger the upper right ADBC area of the fold line is, the greater the probability of convergence of the evolutionary game (1,1) is. The higher the excess return, the greater the probability that the result of evolutionary game will converge to (1,1). Because getting excess return by both players is the shift in the relationship, so the game both parties can only be benefited mutually by improving the excess return e. When the corporate strength between both game sides has any gaps, the free-riding behavior may occur. In the case of upstream stakeholders providing agricultural products with violations, the downstream stakeholders are willing to assume responsibilities, when a product safety accident occurs, the government regulators should force suppliers take responsibility to reduce their hitchhiking earnings. Similarly, when the product-safety is provided by the upstream stakeholders, not assuming responsibility from the downstream stakeholders, in order to curb free riding behavior and reducing corresponding free-rider gains, raising the purchase threshold and signing accidentresponsibility-sharing agreement should be a necessary action to take. The larger the gaps between the two sides of the game, the smaller the upper right area of ADBC is, and the more likely the game results will converge to the (0,0). Conversely, the smaller the gaps between the two sides, the more probabilities of the game results converge to the (1,1), and more possibilities of providing agricultural products with safety, and assuming greater accountability will be. In order to get a rational situation, the cooperation strength between two sides should be equivalent, then it about to converge to the (1,1), and ultimately to achieve stable results.

6.2. Policy Recommendations According to the above analysis of the game model, the long-term equilibrium outcome of the game may have two distinct states. The final equilibrium point is determined by the value of each parameters in the payoff matrix and the initial state of the game.

6.2.1. Increase the Excess Return Because of the higher excess returns, the evolutionary game strategy between the upstream and downstream stakeholders of agricultural products supply chain will converge to (1,1) which is the strategy set of (provide agricultural products with safety, assuming responsibilities). Therefore, raising the excess earnings will improve the quality-safety of agricultural products supply chain.

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 The Empirical Study on the Evolutionary Game Based Agricultural Products Supply Chain

6.2.2. Reduce Collaboration Costs and Improve Penalty Costs Due to the cost factor α is smaller, the evolutionary game strategy between the upstream and downstream stakeholders will converge to (1,1). Therefore, reducing the costs of the upstream and downstream stakeholders should make both sides do not have to worry about their benefits from the impact of high costs. It can also avoid the adverse effects for reducing costs by paying the price of cutting the strategy of quality-safety of agricultural products.

6.2.3. Reduce the Relative Size of Cooperative Enterprises When a node enterprises on an agricultural supply chain to cooperate, along with the increased size of the game between the two sides, the game results will converge to (0,0), namely the set of (provide agricultural products with violations, assume with no responsibilities). The inconsistency of the relative size can easily lead to the problem of earnings gap. To avoid such problems, happen and get a rational situation, the cooperation strength between two sides should be equivalent, so that to avoid the income gap impacts on the quality and safety of the agricultural products supply chain.

6.2.4. Minimize Free-Riding When the corporate strength between both game sides has any gaps, the free-riding behavior may occur. When the free-riding factor gets higher and higher, the game results will converge to (0,0). Hitchhiking may easily lead to make noncompliance of agricultural products mixed into and then flow to the consumer market, affecting the quality and safety of agricultural products supply chain

6.2.5. Increase Overflow Income With the effective cooperation carried by both sides of the game on the agricultural supply chain, one side can obtain spillover income from the other side, and the more spillover income, the more possibly the evolutionary game will converge to (1,1). Increasing overflow income can make both sides of the game to promote cooperation in good faith, and also better able to improve the quality and safety of agricultural supply chain.

REFERENCES Chenxiaolin, & Fengjunwen. (2007). Evolutionary game based study on the quality and safety of agricultural products. Technical Economy, 26(11), 79-84. Cornelia, A. (2011). Farmers’ choices in the vegetable supply chain: Problems and possibilities. Agricultural Economics and Rural Development. Institute of Agricultural Economics, 8(2), 221–234. Engle, S. (2006). Over labeling and lobbying: The case of credence goods. Environmental Modeling and Assessment, 11(11), 115–130. doi:10.100710666-005-9030-6

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Folkerts, H., & Koehorst, H. (1998). Challenges in International food supply chains: Vertical co- ordination in the European agribusiness and food industries. British Food Journal, 100(8), 385–388. doi:10.1108/00070709810247762 Frank, S., & Henderson, D. (1992). Transaction costs as determinants of vertical coordination in US food Indus- tries. American Journal of Agricultural Economics, 74(2), 941–950. doi:10.2307/1243192 Gigler, J. K., Hendrix, E. M. T., Heesen, R. A., van den Hazelkamp, V. G. W., & Meerdink, G. (2002). On optimization of agricial by dynamic programming. European Journal of Operational Research, 139(1), 613–625. doi:10.1016/S0377-2217(01)00191-6 Hennessy D.A., Roosen J., Miranowski J.A., & Inra. (2001). Leadership and the provision of save food. American Agricultural Economics Association, 83(4), 862-874. Henneta, J. C., & Arda, Y. (2008). Supply chain coordination: A game-theory approach. Engineering Applications of Artificial Intelligence, 21(1), 399–405. doi:10.1016/j.engappai.2007.10.003 Huang, Y., Huang, G. Q., & Newman, S. T. (2011). Coordinating pricing and inventory decisions in a multi-level supply chain: A game-theoretic approach. Transportation Research Part E, Logistics and Transportation Review, 47(2), 115–129. doi:10.1016/j.tre.2010.09.011 Kooten, O. V., Aramyan, L. H., & ... . (2007). Performance Measurement in agri-food Supply Chains: A case study. Supply Chain Management: An International Journal, 12(4), 304–315. doi:10.1108/13598540710759826 Liying. (2011). Theoretical and empirical study on the agriculture-supermarket jointing in China. Liaoning, Shenyang Agricultural University. Maze, B. A., Polin, S., Raynaud, E., Sauvee, L., & Valceschini, E. (2001). Quality signals and governance structures within European agro-food chains: A new institutional economics approach. Paper presented at the 78th EAAE Seminar and NJFSeminar330, Economics of Contracts in Agriculture and the Food Supply Chain, Copenhagen (pp. 15-16). Pouliot S, &Summer D.A. (2008). Traceability, liability, and incentives for food safety and quality. American Agricultural Economics Association, 90(1), 15-27. Reynolds, N., Fischer, C., & Hartmann, M. (2009). Determinants of sustainable business relationships in selected German agri-food chain. British Food Journal, 111(8), 776–793. doi:10.1108/00070700910980919 Tatum, J. D., Belk, K. E., George, M. H., & Smith, G. C. (1999). Identification of quality management practices to reduce the incidence of retail beef tenderness problems: Development and evaluation of a prototype quality system to produce tender beef. Journal of Animal Science, 77(5), 2112–2118. doi:10.2527/1999.7782112x PMID:10461989 Veen-Dirks, P. M. G. V., & Verdaasdonk, P. F. A. (2009). The dynamic relation between management and control and government structure in a supply Chain context. Supply Chain Management: An International Journal, 14(6), 466–478. doi:10.1108/13598540910995237

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Wangshuang, Liugaosheng et al. (2013). Evolutionary game based analysis of food safety. Macro management, 5(3), 1-3. Xieruiying, & Wangjining. (2012). Evolutionary game based analysis on the behavior of producers and sellers in food safety chain. Communication of Finance and Accounting, 12(7), 144-146. Xinglijuan, & Tianshuangliang. (2011). The analysis of evolutionary game on the behavior of food safety supervision. Journal of Chongqing University of Arts and Sciences (Natural Science Edition), 30(1), 13-16. Yangkun, & Qiqinghua. (2012). Game model based research of food safety regulatory in China. Journal of Wuhan Polytechnic University, 31(2), 77-80. Yangqing, & Shiyaneng. (2011). Evolutionary game based analysis on the food safety supervision. Journal of Wuhan University of technology (information engineering edition), 33(4), 670-672.

This research was previously published in the International Journal of Operations Research and Information Systems (IJORIS), 8(1); edited by John Wang, pages 40-57, copyright year 2017 by IGI Publishing (an imprint of IGI Global).

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Chapter 21

IoT Based Agriculture as a Cloud and Big Data Service: The Beginning of Digital India Sukhpal Singh Gill University of Melbourne, Australia Inderveer Chana Thapar University, India Rajkumar Buyya University of Melbourne, Australia

ABSTRACT Cloud computing has transpired as a new model for managing and delivering applications as services efficiently. Convergence of cloud computing with technologies such as wireless sensor networking, Internet of Things (IoT) and Big Data analytics offers new applications of cloud services. This paper proposes a cloud-based autonomic information system for delivering Agriculture-as-a-Service (AaaS) through the use of cloud and big data technologies. The proposed system gathers information from various users through preconfigured devices and IoT sensors and processes it in cloud using big data analytics and provides the required information to users automatically. The performance of the proposed system has been evaluated in Cloud environment and experimental results show that the proposed system offers better service and the Quality of Service (QoS) is also better in terms of QoS parameters.

1. INTRODUCTION Emergence of ICT (Information and Communication Technologies) plays an important role in the agriculture sector by providing services through computer-based agriculture systems (Singh and Chana, 2015). But these agriculture systems are not able to fulfill the needs of today’s generation due to processing of large amount of data, lack of important requirements like processing speed, data storage space, reliability, availability, scalability etc. and even resources used in computer-based agriculture systems are not utilized DOI: 10.4018/978-1-5225-9621-9.ch021

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 IoT Based Agriculture as a Cloud and Big Data Service

efficiently. Agriculture-as-a-Service (AaaS) applications exhibit Big data characteristics. For example, the volume of agriculture dataset captured by environments such as Open Government Data Platform India (data.gov.in, 2015), India Agriculture and Climate Data Set (Sanghi et al.), and regional land and climate modelling in China (Shangguan et al., 2012) can be in order of 1000000 records with size of 3.5 GB. The data is coming in large data variety and volume from both users in the form of images like damaged crop images due to weather, insects etc. and devices through Internet of Things (IoT) sensors and satellites (GPS systems) that send weather related images. As a result of regular capturing and collection of datasets, they grow with the velocity of 80.72 KB/minute or more (data.gov.in, 2015). To solve the problem of existing agriculture systems, there is a need to develop a cloud-based service that can easily manage different types of agriculture related-data based on different domains (crop, weather, soil, pest, fertilizer, productivity, irrigation, cattle, and equipment) through these steps: i) gather data from various sensors through preconfigured devices, ii) classify the gathered data (heterogeneous, high volume of big data) into various classes through analysis, iii) store the classified information in cloud repository for future use, and iv) automatic diagnosis of the agriculture status. As large number of users are using agriculture systems operating on large datasets simultaneously, there is a need of highly scalable and elastic distributed computing environment such as cloud computing. In addition, cloud-based autonomic information system should be able to identify the QoS (Quality of Service) requirements of user request and resources should be allocated efficiently to execute the user request based on these requirements. The main aim of this paper is to design architecture of Agriculture-as-a-Service (AaaS) that manages various types of agriculture-related data based on different domains. This is realized through the following objectives: i) propose an autonomic resource management technique which is used to a) gather the information from various users through preconfigured devices, IoT sensors, GPS (Global Positioning System), etc. b) extract the attributes, c) analyze the information by creating various classes based on the information received, d) store the classified information in cloud repository for future use and e) diagnose the agriculture status automatically and ii) perform resource allocation automatically at infrastructure level after identification of QoS requirements of user request. The rest of the paper is organized as follows. Section 2 presents related work of existing agricultures systems. Proposed architecture is presented in Section 3. Section 4 presents Autonomic Resource Management. Sections 5 describe the experimental setup and present the results of evaluation. Section 6 presents conclusions and future scope.

2. RELATED WORK Existing research reported that few agriculture systems have been developed with limited functionality. Related work of existing agriculture systems has been presented in this section.

2.1. Existing Agriculture Systems Ranya et al. (2013) presented ALSE (Agriculture Land Suitability Evaluator) to study various types of land to find the appropriate land for different types of crops by analyzing geo-environmental factors. ALSE used GIS (Global Information System) capabilities to evaluate land using local environment conditions through digital map and based on this information decisions can be made. Raimo et al. (2010) proposed FMIS (Farm Management Information System) used to find the precision agriculture requirements for

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information systems through web-based approach. Author identified the management of GIS data is a key requirement of precision agriculture. Sorensen et al. (2010) studied the FMIS to analyze dynamic needs of farmers to improve decision processes and their corresponding functionalities. Further they reported that identification of process used for initial analysis of user needs is mandatory for actual design of FMIS. Zhao (2002) presented an analysis of web-based agricultural information systems and identified various challenges and issues still pending in these systems. Due to lack of automation in existing agriculture system, the system is taking longer time and is difficult to handle dynamic needs of user which leads to customer dissatisfaction. Sorensen et al. (2011) identified various functional requirements of FMIS and information model is presented based on these requirements to refine decision processes. They identified that complexity of FMIS is increasing with increase in functional requirements and found that there is a need of autonomic system to reduce complexity. Yuegao et al. (2004) proposed WASS (Web-based Agricultural Support System) and identified functionalities (information, collaborative work and decision support) and characteristics of WASS. Based on characteristics, authors divided WASS into three subsystems: production, research-education and management. Reddy at el. (1995) proposed GIS based DSS (Decision Support System) framework in which Spatial DDS has been designed for watershed management and management of crop productivity at regional and farm level. GIS is used to gather and analyze the graphical images for making new rules and decisions for effective management of data. Shitala et al. (2013) presented mobile computing based framework for agriculturists called AgroMobile for cultivation and marketing and analysis of crop images. Further, AgroMobile is used to detect the disease through image processing and also discussed how dynamic needs of user affects the performance of system. Seokkyun et al. (2013) proposed cloud based Disease Forecasting and Livestock Monitoring System (DFLMS) in which sensor networks has been used to gather information and manages virtually. DFLMS provides an effective interface for user but due to temporary storage mechanism used, it is unable to store and retrieve data in databases for future use. The proposed QoS-aware Cloud Based Autonomic Information System (AaaS) has been compared with existing agriculture systems as described in Table 1. All the above research works have focused on different domains of agriculture with different QoS parameters. None of the existing agriculture systems considers self-management of resources. Due to Table 1. Comparisons of existing agriculture systems with proposed system (AaaS) QoS-aware (Parameter)

Resource Management

Big Data

Mechanism

ALSE (Elsheikh et al., 2013)

Non-Autonomic

Yes (Suitability)

Soil

Yes

No

No

FMIS (Nikkila et al., 2010)

Non-Autonomic

No

Pest and Crop

No

No

No

WASS (Hu et al., 2004)

Non-Autonomic

No

Productivity

No

No

No

AgroMobile (Prasad et al., 2013)

Non-Autonomic

Yes (Data accuracy)

Crop

Yes

No

No

DFLMS (Jeong et al., 2013)

Non-Autonomic

No

Crop

No

Yes

No

Autonomic

Yes (Cost, Time, Resource Utilization, Latency, Throughput and Attack Detection Rate)

Crop, Weather, Soil, Pest, Fertilizer and Irrigation

Yes

Yes

Yes

Proposed System (AaaS)

440

Domains

Data Classification

Agriculture System

 IoT Based Agriculture as a Cloud and Big Data Service

lack of automation of resource management, services become inefficient which further leads to customer dissatisfaction. The proposed system is a novel QoS-aware cloud based autonomic information system and considers various domains of agriculture and, allocates and manages the resources automatically which is not considered in other existing agriculture systems.

3. AGRICULTURE-AS-A-SERVICE ARCHITECTURE The existing agriculture systems are not able to fulfill the needs of today’s generation due to lacking in important requirements like processing speed, data storage space, reliability, availability, scalability etc. Even resources used in computer based agriculture systems are not utilized efficiently. To solve the problem of existing agriculture systems, there is a need to develop a cloud-based autonomic information system that delivers Agriculture-as-a-Service. This section presents architecture of cloud-based autonomic information system for agriculture service called AaaS that manages various types of agriculture-related data based on different domains. Architecture of AaaS is shown in Figure 1. QoS parameters (execution time and cost) must be identified before the allocation of resources. AaaS is the key mechanism that Figure 1. Agriculture-as-a-Service architecture

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 IoT Based Agriculture as a Cloud and Big Data Service

ensures that the resource manager can serve large amount of requests without violating SLA terms and dynamically manages the resources based on QoS requirements identified by QoS manager. The services of AaaS has been divided into three types: SaaS (Software as a Service), PaaS (Platform as a Service) and IaaS (Infrastructure as a Service). In SaaS, a user interface is designed in which users can interact with system. Aneka is a .NET-based application development PaaS, which is used as a scalable cloud middleware to make interaction between cloud subsystem and user subsystem. In IaaS, an autonomic resource manager manages the resource automatically based on the identified QoS requirements of a particular request. The architecture of AaaS comprises of two subsystems: i) user and ii) cloud.

3.1. User Subsystem This subsystem provides a user interface, in which different type of users interact with AaaS to provide and get useful information about agriculture based on different domains. Nine types of information of different domains in agriculture has been considered: crop, weather, soil, pest, fertilizer, productivity, irrigation, cattle, and equipment. Users are basically classified in three categories: i) agriculture expert, ii) agriculture officer, and iii) farmer. The agriculture expert shares professional knowledge by answering farmer queries and updates the AaaS database based on the latest research done in the field of agriculture with respect to their domain. Agriculture officers are the government officials that provide the latest information about new agriculture policies, schemes, and rules passed by the government. Farmer is an important entity of AaaS who can take maximum advantage by asking his queries and getting automatic reply after analysis. Users can monitor any data related to their domain and get their response without visiting the agriculture help center. It integrates the different domains of agriculture with AaaS. The queries received from user(s) are forwarded to cloud repository for updates and response sends back to particular user on their preconfigured devices (tablets, mobile phones, laptops etc.) via internet.

3.2. Cloud Subsystem This subsystem contains the platform in which agriculture service is hosted on a cloud. Details about users and agriculture information are stored in a cloud repository in different classes for different domains with unique identification number. The information is monitored, analyzed, and processed continuously by AaaS. The analysis process consists of various sub processes: selection, data preprocessing, transformation, classification and interpretation as shown in Figure 1. Different classes for every domain and sub classes for further categorization of information have been designed. In storage repository, user data is categorized based on different predefined classes of every domain. This information is further forwarded to agriculture experts and agriculture officers for final validation through preconfigured devices. Further, a number of users can use cloud-based agriculture service so the QoS manager and autonomic resource manager in cloud subsystem have been integrated. QoS manager identifies the QoS requirements based on the number and type of user queries as discussed in previous research work (Jeong et al., 2013; Singh and Chana, 2015; Singh et al., 2015). Based on QoS requirements, autonomic resource manager identifies resource requirements automatically and allocates and executes the resources at infrastructure level. Performance monitor is used to verify the performance of system and also maintain it automatically. If the system will not be able to handle the request automatically then the system generates an alert.

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 IoT Based Agriculture as a Cloud and Big Data Service

3.2.1. Cloud-Based Agriculture Service Cloud-based agriculture service provides a user platform through which user can access agriculture service as shown in Figure 2. Firstly, agriculture service allows user to create profile for interaction with AaaS. After profile creation, the user is required to provide his personal details along with the details of information domain. AaaS analyses the information to verify whether the data is complete or not for further processing by performing various checks. Further data is processed and redundancy of data is removed and data is used to select domain to which data belongs. Information is classified properly in order with unique identification number. This information is forwarded to agriculture experts and agriculture officers for final validation through preconfigured devices. After successful validation of information, it is stored in AaaS database. If user wants to know the response of their query, then system will automatically diagnose the user query and send the response back to that user.

3.2.2. Detailed Methodology AaaS allows users to upload the data related to different domains of agriculture through preconfigured devices and classified them based on the domains specified in database. Subtasks of information gathering and provided in AaaS are: i) selection, ii) preprocessing, iii) transformation, iv) classification and v) interpretation. In selection, target datasets are created based on the relevant information that will further be considered for analysis in next sub process. In preprocessing, different users have different information regarding agriculture. To develop a final training set, there is need of preprocessing steps because data might contain some missing sample or noise components. In AaaS, data preprocessing contains four different sub processes: i) data cleaning, ii) data integration, iii) data conversion and iv) data reduction. Data transformation provides an interface between data analysis sub process (classification) and data preprocessing. After data preprocessing, this process converts the labeled data into adequate format suitable for classification. In classification, AaaS classify the agriculture information of different users of different domains based on the extracted data. K-NN (k-Nearest Neighbor) classification mechanism Figure 2. Functional aspects of AaaS

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 IoT Based Agriculture as a Cloud and Big Data Service

has been used in this research work to identify the different class labels of users. K-NN is supervised machine learning technique which is used to classify the unknown data using training data set generated by it. K-NN used to identify the productivity level through Training Instance Dataset (TID). Figure 3 describes the K-NN Algorithm. In K-NN algorithm, distance is computed from one specific instance to every training instance to classify that unknown instance. Both k-nearest neighbor and k minimum distance is determined and output class label is identified among k classes. During training phase, K-NN Algorithm utilizes training data. Figure 4 illustrates the classification process used in this research work. K-NN model is used to identify the productivity level through Training Instance Dataset (TID). Five levels of productivity (A - E) have been fixed as shown in Table 2. The level ‘A’ indicates the productivity is very high while level ‘E’ indicates the productivity is very low. Based on the given information, TID identifies the class in which given data belongs. Figure 3. Pseudo code of K-NN algorithm

Figure 4. Classification process

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 IoT Based Agriculture as a Cloud and Big Data Service

Table 2. Productivity Levels Productivity Level

Description

A

Very High Productivity

B

High Productivity

C

Neutral Productivity

D

Low Productivity

E

Very Low Productivity

Test data is an input of this model and it is compared with TID and identifies the class in which data laid using following rule: Rule: If {Crop Name ˄ Temperature ˄ Soil Texture ˄ Season ˄ Pesticide ˄ Fertilizer} then Productivity The final step is to interpret the agriculture data submitted by different users of different domains which helps user to understand the classified datasets. AaaS is capable to diagnose the agriculture status based on the information entered by user and send the diagnosed agriculture status to particular user automatically. Six attributes have been considered: Crop Name, Temperature, Soil Texture, Season, Pesticide and Fertilizer and one output: Productivity. Based on these six attributes, AaaS designs rules. Values for six variables are considered as TID. For example, refer to Table 3. AaaS uses the rule shown in Table 3 to find the productivity level using TID (see Table 4). Similarly, any type of query related to different domains can be asked by users and AaaS executes the user query and send response back to particular user automatically based on the rules defined in AaaS database. Through AaaS, users can easily diagnose the agriculture status automatically.

3.2.3. Infrastructure Management (IaaS) Efficient management of infrastructure in cloud is mandatory to maintain the performance of the AgriInfo. It comprises of two sub units: QoS Manager and Resource Manager. Table 3. User wants to retrieve the productivity level using AaaS User Query Crop Name Soybean

Temperature 21-27 °C

Soil Texture Slity Loam Clay

Season Winter

Pesticide

Fertilizer

Organochlorine

Productivity

Urea

?

Table 4. AaaS response utilized to in order to find the productivity level using TID AaaS Response Crop Name Soybean

Temperature 21-27 °C

Soil Texture Slity Loam Clay

Season Winter

Pesticide Organochlorine

Fertilizer Urea

Productivity C

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 IoT Based Agriculture as a Cloud and Big Data Service

3.2.3.1. QoS Manager User submits a request to Agri-Info to retrieve some specific agriculture related information. Agri-Info identifies the QoS parameters required to process the user request through analysis based on user request. Based on the key QoS requirements of a particular user request, the QoS Manager puts the user request into critical and non-critical queues through QoS assessment. For QoS assessment, QoS Manager will calculate the execution time of user request and find the approximate user request completion time. If the completion time is lesser than the desired deadline then it will execute immediately with the available resources and release the resource(s) back to resource manager for another execution otherwise calculate extra number of resources required and provide from the reserved stock for current execution. 3.2.3.2. Resource Manager Further, two resource scheduling policies (Singh and Chana, 2015) are used to schedule the resources for execution of user queries: time based and cost based scheduling policy. Time based scheduling policy works as per following: First, the allocation agent begins to compute the Deadline Time of the user request in the given budget. Allocate resources based on time, the user request which has shortest Deadline Time will execute first. If the two requests have same deadline time then that request will execute first that has lesser execution time. The allocation agent then schedules all the requests with smallest execution time request to the resources that provide high QoS. The rules for time based scheduling policy are described in Table 5 along with their conditions. Cost based scheduling policy works as per following: First, the allocation agent begins to compute the cost of each request then sort, as the priority is given to the request which has maximum budget. If the two requests have same budget then that request will execute first that has lesser execution time. The allocation agent then schedules all the requests with high budget request to the resources that provide high QoS. Finally, all other requests are scheduled on the available resources set. The rules for cost based scheduling policy are described in Table 6 along with their conditions.

4. AUTONOMIC RESOURCE MANAGEMENT Working of autonomic element of Agri-Info is based on IBM’s autonomic model that considers four steps of autonomic system: i) monitor, ii) analyze, iii) plan and iv) execute as shown in Figure 1. The objective of resource provisioning in autonomic resource management is to provision the resources to process user requests. The requests submitted should be executed within their budget and deadline. Requests submitted by user to resource provisioner are stored as bulk of workloads for their execution.

Table 5. Rules of time based resource scheduling Request Pending

Urgency

Add Resource

Request

Yes

Yes

Reserve

Submit

Yes

No

Available

Submit

No

-

-

Finish

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 IoT Based Agriculture as a Cloud and Big Data Service

Table 6. Rules of cost based resource scheduling Request Pending Yes

RA > 0 True

Et > Wd True

Status

BA > Pr True

Add Resource

Yes

False

True

True

Add Resource

No

-

-

-

Finish

Yes

True

False

True

Finish

Yes

True

True

False

Finish

RA = Resource Available, Et = Estimated Time, Pr = Resource Price, Wd = Desired Deadline and BA = Available Budget. Details of both time and cost based scheduling policy is given in previous research work (Singh and Chana, 2015).

All the submitted workloads are analyzed based on their QoS requirements. Based on importance of the attribute, weights for every cloud workload are calculated. After that, workloads are clustered based on k-means based clustering algorithm for better resource provisioning (Singh et al., 2015). If the value of workloads executes within deadline and budget and [Resource Consumption and Requests Missed is lesser than Threshold Value] then it will provision resources otherwise generate alert for analyses the workload again. After successful provisioning of resources, Resource Scheduler (RS) takes the information from the appropriate workload after analyzing the various workload details which user request demanded (Singh and Chana, 2015). Knowledge Base contains details of all the resources available in resource pool and reserve resource pool. Based on Cloud consumer details, RS assigns resources and executes Cloud workloads. During execution of a particular cloud workload, the Resource Executor (RE) will check the current workload. If the resources are sufficient for execution then it will continue with execution otherwise request for more resources. If the value of Resource Consumption and Requests Missed is lesser than threshold value, then RE will execute workloads otherwise RE will generate alert. After successful execution of Cloud workloads, RE releases the free resources to resource pool and RE is ready for execution of new cloud workloads. During execution of user requests, performance is monitored continuously using sub unit performance monitor to maintain the efficiency of Agri-Info and generates alert in case of performance degradation. Alerts can be generated in two conditions generally: i) if resource consumption is more than threshold values of resource consumption to execute user request (Action: Reallocates resources) and ii) if the number of missed requests are greater than the threshold value (Action: Predict QoS Requirements Again). Same action is performed twice, if Agri-Info fails to correct it then system will be treated as down. Components of autonomic system are described below:

4.1. Sensors Sensors get the information about performance of other nodes using in the system and their current state. Firstly, the updated information from processing nodes is transfer to manager node then manager node transfers this information to sensors. Updated information includes information about QoS parameters (execution time, execution cost and resource utilization etc.).

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 IoT Based Agriculture as a Cloud and Big Data Service

4.2. Monitor Initially, Monitors are used to collect the information from sensors for monitoring continuously performance variations by comparing expected and actual performance, and monitors the value of resource consumption and missed requests. Actual information about performance is observed based QoS parameters and transfers this information to next module for further analysis.

4.3. Analysis and Plan Analyze and plan module start analyzing the information received from monitoring module and make a plan for adequate actions for corresponding alert. Following formula is used to calculate Resource Consumption (Equation 1): n  ActualResourceUsage   Resource Consumption = ∑   PredictedReesourceUsage  i =1 

(1)

where Actual Resource Usage is usage of resource to execute particular number of user requests and Predicted Resource Usage is resource usage estimated before actual execution and n is the number of resources. Assumed: Predicted Resource Usage ≤ Actual Resource Usage . Value of ResourceConsumption . is more than 1 generally because Actual Resource Usage is more than Predicted Resource Usage but ideally it will be 1 when both are equal. In this research rk, maximum values for ResourceConsumption has been fixed and that is called threshold value. Following formula is used to calculate number of requests missed (Requests Missed ) in a particular period of time (Equation 2): Requests Missed = [Number of Requests Executed Successfully – Number of Requests Missed Deadline]

(2)

For successful execution of resources, value of Requests Missed is lesser than threshold value. Algorithm 1 is used to analyses the performance of management of resources. With the help of (Equation 1) and (Equation 2), resource consumption is calculated and allocates the resources for execution and then compares the resource consumption with threshold value (Thc ) . If resource consumption is less than threshold value and value of Requests Missed is less than threshold value (Thm ) then execution of resources continues otherwise no resource is allocated and process of reallocation is started using Algorithm 1. After meeting this condition, resources are allocated for further execution and value of resource consumption and Requests Missed are checked periodically. In case of more value than threshold, alert will be generated by performance monitor.

4.4. Executor Executor implements the plan after analyzing completely. To reduce the execution time and execution cost and improve resource utilization is a main objective of executor. Based on the output given by

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 IoT Based Agriculture as a Cloud and Big Data Service

Algorithm 1. Analyzing and Panning Unit (AU)

analysis and executor tracks the new user request submission and resource addition, and take the action according to rules described in knowledge base.

4.5. Effector Effector is used to exchange updated information and it is used to transfer the new policies, rules and alerts to other nodes with updated information.

5. PERFORMANCE EVALUATION The aim of this performance evaluation is to demonstrate that it is feasible to implement and deploy the agriculture as a service on real cloud resources. Tools used for setting up cloud environment for performance analysis are Microsoft Visual Studio 2010 (SaaS), Aneka (PaaS), SQL Server 2008, and Citrix Xen Server (IaaS). Aneka has been installed along with its requirements on all the nodes that provide cloud service. Nodes in this system can be added or removed based on the requirement. AaaS is installed on main server and tested on virtual cloud environment that has been established at CLOUDS Lab, University of Melbourne, Australia. Different number of virtual machines have been installed on different servers, and deployed the AaaS to measure the variations. In this experimental setup, three different cloud platforms are used: Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS) as shown in Figure 5. At SaaS level, Microsoft Visual Studio is used to develop e-agriculture web service to provide user interface in which user can access service from any geographical location. At PaaS level, Aneka cloud application platform is used as a scalable cloud middleware to make interaction between IaaS and SaaS, and continually monitor the performance of the system. At IaaS level, three different servers (consist of virtual nodes) have been created through Citrix Xen Server and SQL Server has been used for data storage. Scheduler as shown in Figure 5, runs at IaaS level on Citrix Xen Server. Computing

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 IoT Based Agriculture as a Cloud and Big Data Service

Figure 5. Deployment of components at runtime and their interaction

nodes used in this experiment work are further categorized into three categories as shown in Table 7. The execution cost is calculated based on user request and deadline (if deadline is too early (urgent) it will be more costly because there is a need of greater processing speed and free resources to process particular request with urgency). There is individual price is fixed (artificially) for different resources because all the resources are working in coordination manner to fulfill the demand of user (demand of user is changing dynamically). Experiment setup using 3 servers in which further virtual nodes (12 = 6 (Server 1) +4 (Server 2) +2 (Server 3)) are created. Every virtual node has different number for Execution Components (ECs) to process user request and every EC has their own cost (C$/EC time unit (Sec)). Table 1 shows the characteristics of the resources used and their Execution Component (EC) access cost per time unit in Cloud dollars (C$) and access cost in C$ is manually assigned for experimental purposes. The access cost of an EC in C$/time unit does not necessarily reflect the cost of execution when ECs have different Table 7. Configuration Details of Cloud Environment Resource_Id

Configuration

Specifications

Operating System

Number of Virtual Node

Number of ECs

Price (C$/EC Time Unit)

R1

Intel Core 2 Duo - 2.4 GHz

1 GB RAM and 160 GB HDD

Windows

6

18

2

R2

Intel Core i5-23102.9GHz

1 GB RAM and 160 GB HDD

Linux

4

12

3

R3

Intel XEON E 524072.2 GHz

2 GB RAM and 320 GB HDD

Linux

2

6

4

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 IoT Based Agriculture as a Cloud and Big Data Service

capabilities. The execution agent needs to translate the access cost into the C$ for each resource. Such translation helps in identifying the relative cost of resources for executing user requests on them. Due to limited number of resources, cost increases with increase in user requests. Cost is varying in two different cases: i) relaxed deadline and ii) tight deadline. In both cases, when the deadline is low (e.g. 200 secs), the number of user requests processed increases as the budget value increases. When a higher budget is available, the execution agent uses expensive resources to process more user requests within the deadline. Alternatively, when scheduling with a low budget, the number of user requests processed increases as the deadline is relaxed. Different number of experiments has been performed by comparing AaaS (QoS-aware Autonomic) as discussed in Section 4 with non-autonomic resource management technique (non-autonomic) in which no autonomic scheduling mechanism is considered while allocating resources to process the user requests.

5.1. Datasets Datasets used in this research work are downloaded from the Open Government Data Platform India (data.gov.in, 2015), India Agriculture and Climate Data Set (Sanghi et al.), and regional land and climate modelling in China (Sanghi et al.) can be in the order of 1000000 records, with size of 3.5 GB. The data is coming in large data variety and volume from both users in the form of images like damaged crop images due to weather, insects etc. and devices through Internet of Things (IoT) sensors and satellites (GPS systems) that send weather related images. As a result of regular capturing and collection of datasets, they grow with the velocity of 80.72 KB/minute or more (Sanghi et al.). Five different tables used to process the different types of data as described in Table 8 to Table 12. Table 8. Crop Information CropId

Crop Name

Crop Type

Soil Texture

Min Land

Growing Period

Seed Type

Price

Quantity

C1

Rice

Kharif

Slity Clay

5 Acre

3 Months

Wet

1200 Rs./Kg

2 Kg/Acre

C2

Maize

Rabi

Slity Loam Clay

4 Acre

4 Months

Dry

1600 Rs./Kg

1 Kg/Acre

C3

Wheat

Zaid

Loam Clay

3 Acre

3 Months

Wet

1000 Rs./Kg

2 Kg/Acre

C4

Sugarcane

Cash

Slity

4 Acre

6 Months

Dry

800 Rs./Kg

6 Kg/Acre

Table 9. Weather information Crop Name

Temperature

Season

Pressure (CFM)

Wind Speed

Rainfall

Location

Rice

15-18 °C

Winter

0.75 to 1.5

16 Km/h

300–650 mm

Ambala

Maize

17-22 °C

Summer

0.05 to 0.5

12 Km/h

100–150 mm

Amritsar

Wheat

25-30 °C

Rainy

1.5 to 5.2

17.3 Km/h

200–250 mm

Ganga Nagar

Sugarcane

35-40 °C

Summer

1 to 10

8 Km/h

400–600 mm

Pathankot

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 IoT Based Agriculture as a Cloud and Big Data Service

Table 10. Soil information Soil Texture

Inorganic Material

Bulk Density

Organic Material

Water

Air

Color

Structure

Infiltration

Slity Clay

2.60 to 2.75 grams per cm3

Sand and clay

Plant and animal residues

25%

28%

Brown

Plate-like

15 mm/hour

Slity Loam Clay

2.7 to 2.75 grams per cm3

Sand and Slit

Animal residues

22%

18%

Red

Prism-like

10 mm/hour

Loam Clay

2.60 to 2.75 grams per cm3

Clay and Slit

Plant residues

37%

21%

Brown

Block like

18 mm/hour

Slity

2.60 to 2.75 grams per cm3

Sand, Slit and Clay

Plant and animal residues

31%

29%

Black

Sphere like

22 mm/hour

Table 11. Pest information Crop Type

Crop Disease

Effect

Kharif

Bacterial brown spot

Degrade soil fertility

Reduce Irrigation

Carbonate

Yes

Rs. 1500/L

Improve Productivity

Rabi

Zonate eye spot

Degrade productivity

Distribute Soil

Organophosphate

No

Rs. 2200/L

Improve soil fertilization

Zaid

Dwarf bunt

Increase risk of other disease

Spray irrigation

Parathyroid

Yes

Rs. 2300/L

Reduce risk of other diseases

Cash

Ergot

Degrade productivity

Drip Irrigation

Parathyroid

Yes

Rs. 1800/L

Reduce productivity

Treatment

Pesticide Name

Solubility in Water

Price

Outcome

Table 12. Fertilizer information Crop Type

Fertilizer Name

Nutrient Composition

Price

Kharif

Urea

Nitrogen in form of urea (amide) (N)

7000 Rs./10 Kg

Rabi

Ammonium-Nitrate

Ammoniacal Nitrogen, Nitrogen Nitrate and Urea Nitrogen

9100 Rs./10 Kg

Zaid

Ammonium-Sulphate

Ammoniacal nitrogen and Sulpher

6200 Rs./10 Kg

Urea-Ammonium

Ammoniacal nitrogen and Neutral ammonium citrate Soluble phosphate

13200 Rs./10 Kg

Cash

5.2. Performance Metrics The following metrics are used to calculate the execution cost, execution time, resource utilization, latency, detection rate and scalability for processing user requests as taken from previous work (Singh and Chana, 2015; Singh et al., 2015; Singh and Chana, 2016): Execution Time is a ratio of difference of request finish time (WFi ) and request start time (WStarti ) to number of requests. Following formula is used to calculate Execution Time (ET) (Equation 3):

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 IoT Based Agriculture as a Cloud and Big Data Service

n  WF −WStarti   ETi = ∑  i   n  i =1

(3)

where n is the number of requests to be executed. Execution Cost is defined as the total amount of cost spent per one hour for the execution of request and measured in Cloud Dollars (C$). Following formula is used to calculate execution cost (C) (Equation 4): C = ETi ×Price

(4)

Latency is a defined as a difference of time of input cloud workload and time of output produced with respect to that workload. Following formula is used to calculate Latency (Equation 5): n

Latencyi = ∑ (timeof  output  produced after  execution  − time of  input of  cloud  workload )

(5)

i =1

where n is number of workloads. Resource Utilization is defined as a ratio of actual time spent by resource to execute workload to total uptime of resource for single resource. Following formula is used to calculate resource utilization (Equation 6): n   workload  actual timespentby    resourceto execute  ResourceUtilization  = i ∑   total uptimeof  resource i =1

(6)

where n is number of workloads. Security is measured in terms of detection rate. Experiment has been conducted with different type of attacks (DoS, R2L, U2R and Probing) and different tools used to launch different attacks are metasploit framework for DoS, Hydra for R2L, NetCat for L2R and NMAP for probing. Detection Rate is the ratio of total number of true positives to the total number of intrusions (Sorensen et al., 2010): Detection Rate =

Total Number of True Positives Total Number of Intrusions

(7)

Scalability is measured in terms of throughput. It is the ratio of total number of workloads to the total amount of time required to execute the workloads. Following formula is used to calculate throughput (Equation 8): Throughput =

TotalNumberofWorkloads(Wn )

Total amount of   time required toexecutethe   workloads (Wn )



(8)

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 IoT Based Agriculture as a Cloud and Big Data Service

5.3. Experimental Results Experiment has been conducted with 180 user requests for verification of execution cost, execution time, resource utilization, latency, detection rate and scalability. With increasing the number of user requests, the value of latency is increasing. The value of latency in QoS-aware autonomic system is lesser as compared to non-autonomic based resource scheduling at different number of user requests as shown in Figure 6. The maximum value of latency is 193 seconds and minimum value of latency is 59 seconds in QoS-aware autonomic resource management technique. Average latency in QoS-aware autonomic is 15.22% lesser than non-autonomic resource management technique. The value of average cost for both QoS-aware cloud based autonomic resource management technique and non-autonomic resource management is calculated with different number of user requests as shown in Figure 7. Average cost is increasing with increase in number of user requests. At 180 user requests, average cost in QoS-aware autonomic is 25.36% lesser than non-autonomic resource management technique. QoS-aware autonomic performs excellent with different number of user requests. Execution cost in QoS-aware autonomic is 27.65% lesser than non-autonomic resource management technique. As shown in Figure 8, the execution time is increasing with increase in number of user requests. At 90 user requests, execution time in QoS-aware autonomic resource management technique is 24.66% lesser than non-autonomic resource management technique. After 120 user requests, execution time increases abruptly in non-autonomic resource management technique but QoS-aware autonomic performs better than non-autonomic technique. Average execution time in QoS-aware autonomic is 18.960% lesser than non-autonomic resource management technique. With increasing the number of user requests, the Figure 6. Effect of change in number of user requests on latency

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 IoT Based Agriculture as a Cloud and Big Data Service

Figure 7. Effect of change in number of user requests on execution cost

Figure 8. Effect of execution time with change in number of user requests

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 IoT Based Agriculture as a Cloud and Big Data Service

percentage of resource utilization is increasing. The percentage of resource utilization in QoS-aware autonomic resource management technique is more as compared to non-autonomic resource management (non-autonomic) at different number of user requests as shown in Figure 9. The maximum percentage of resource utilization is 94.66% at 180 user requests in QoS-aware autonomic but QoS-aware autonomic performs better than non-autonomic technique. Average resource utilization in QoS-aware autonomic is 31.96% more than non-autonomic resource management technique. Scalability is measured in terms of throughput. Number of software, network and hardware faults (fault percentage) has been injected to verify the throughput of the proposed system with 100 user requests. Figure 10 shows the comparison of throughput of both QoS-aware autonomic resource management approach and non-QoS based resource management technique (non-autonomic) at 100 user requests and it is clearly shown that QoS-aware autonomic performs better than non-autonomic. In this experiment, it has been found the maximum value of throughput at fault percentage 45% i.e. QoS-aware autonomic has 26% more throughput than non-autonomic. Detection rate increases with respect to time and it considers the number of blocked and detected attacks. For new attack or intrusion detection, database is updated with new signatures and new polices and rules are generated to avoid same attack. Experiment has been conducted for known attacks; it is clearly shown in Figure 11 that QoS-aware autonomic performs better than snort anomaly detector (non-autonomic). Further signatures of some known attacks have been removed from database to verify the working of proposed system. Table 13 describes the comparison of execution time used to process different number of workloads (90 and 180) on cloud environment for proposed system with different number of Virtual Machines (VMs). The number of VMs used to execute the workloads was incremented gradually showing how Figure 9. Effect of change in number of user requests on resource utilization

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 IoT Based Agriculture as a Cloud and Big Data Service

Figure 10. Throughput [100 user requests] vs. Fault percentage (%)

Figure 11. Detection rate vs. Attacks

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 IoT Based Agriculture as a Cloud and Big Data Service

Table 13. Total execution time of a bulk of cloud workloads distributed in three servers Virtual Nodes

Number of Workloads

R1

R2

Total Workers

R3

Execution Time (Seconds)

45

1

0

0

1

436.12

45

1

1

0

2

428.69

45

2

1

0

3

418.97

45

2

2

0

4

407.55

45

3

2

0

5

398.17

45

4

2

0

6

380.30

45

4

2

1

7

361.66

45

4

3

1

8

345.18

45

5

3

1

9

331.21

45

5

3

2

10

315.03

45

5

4

2

11

299.97

45

6

4

2

12

276.16

90

1

0

0

1

1803.11

90

1

1

0

2

1771.18

90

2

1

0

3

1759.66

90

2

2

0

4

1736.15

90

3

2

0

5

1691.77

90

4

2

0

6

1668.96

90

4

2

1

7

1636.11

90

4

3

1

8

1625.19

90

5

3

1

9

1578.21

90

5

3

2

10

1551.68

90

5

4

2

11

1529.11

90

6

4

2

12

1503.11

the total execution time was reduced when more VMs were added to the cloud. With one virtual node running on Server R1, execution of 45 workloads finished in 436.12 seconds. With 12 virtual nodes (6 running on R1, 4 running on R2 and 2 running on R3), the application took 276.16 seconds. It is noted that the execution time is reduced with adding additional virtual nodes.

5.4. Statistical Analysis Statistical significance of the results has been analyzed by Coefficient of Variation (Coff . ofVar .) , a statistical method. Coff . ofVar . is statistical measure of the distribution of data about the mean value. Coff . of Var. is used to compare to different means and furthermore offer an overall analysis of performance of the technique used for creating the statistics. It states the deviation of the data as a proportion of its average value, and is calculated as follows (Equation 9):

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 IoT Based Agriculture as a Cloud and Big Data Service

Coff . ofVar .=

SD ×100 M

(9)

where SD is a standard deviation and M is mean. Coff . ofVar . of execution time and have been studied of QoS-aware autonomic resource management technique and non-autonomic resource management technique as shown in Figure 12 and Figure 13. Range of Coff . ofVar . (0.25% - 1.69%) for execution time and (0.37% - 1.96%) for cost approves the stability of QoS-aware autonomic resource management technique as shown in Figure 12 and Figure 13. Small value of Coff . ofVar . signifies QoS-aware autonomic resource management technique is more efficient in resource scheduling in the situations where the number of user requests has changed. Value of Coff . ofVar . decreases as the number of user requests is increasing. Figure 12. CoV for execution time with each scheduling algorithm

Figure 13. CoV for execution cost with each scheduling algorithm

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6. CONCLUSION AND FUTURE DIRECTIONS Cloud-based autonomic information system (AaaS) for agriculture service has been presented, which manages the various types of agriculture-related data based on different domains through different user preconfigured devices. K-NN (k-Nearest Neighbor) classification mechanism is used to classify the agriculture data. Further, classified data is interpreted and users can easily diagnose the agriculture status automatically through AaaS. In addition, AaaS uses two resource scheduling polices (time and cost) for efficient resource allocation at infrastructure level after identification of QoS requirements of user request. The performance of proposed system has been evaluated in cloud environment and experimental results show that the proposed system performs better in terms of execution time, cost, resource utilization, latency, scalability and security. In future, the proposed technique can be extended by incorporating other QoS parameters like network bandwidth, availability, customer satisfaction, computing capacity etc. Proposed technique can be extended by developing pluggable scheduler, in which resource scheduling can be changed easily based on the requirements.

ACKNOWLEDGMENT One of the authors, Dr. Sukhpal Singh Gill [Post Doctorate Fellow], gratefully acknowledges the CLOUDS Lab, School of Computing and Information Systems, The University of Melbourne, Australia, for awarding him the Fellowship to carry out this research work.

REFERENCES Agriculture Data, Government of India. (n. d.). Retrieved from https://data.gov.in/catalogs/sector/Agriculture-9212 Elsheikh, R., Mohamed Shariff, A. R. B., Amiri, F., Ahmad, N. B., Balasundram, S. K., & Soom, M. A. M. (2013). Agriculture Land Suitability Evaluator (ALSE): A decision and planning support tool for tropical and subtropical crops. Computers and Electronics in Agriculture, 93, 98–110. doi:10.1016/j. compag.2013.02.003 Hu, Y., Quan, Z., & Yao, Y. (2004). Web-based Agricultural Support Systems. Proceeding of the Workshop on Web-based Support Systems (pp. 75-80). India Agriculture And Climate Data Set. (n. d.). Retrieved from https://ipl.econ.duke.edu/dthomas/ dev_data/datafiles/india_agric_climate.htm Jeong, S., Jeong, H., Kim, H., & Yoe, H. (2013). Cloud Computing based Livestock Monitoring and Disease Forecasting System. International Journal of Smart Home, 7(6), 313–320. doi:10.14257/ ijsh.2013.7.6.30 Narayana Reddy, M., & Rao, N. H. (1995). GIS Based Decision Support Systems in Agriculture. National Academy of Agricultural Research Management Rajendranagar.

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Nikkilä, R., Seilonen, I., & Koskinen, K. (2010). Software architecture for farm management information systems in precision agriculture. Computers and Electronics in Agriculture, 70(2), 328–336. doi:10.1016/j.compag.2009.08.013 Prasad, S., Peddoju, S. K., & Ghosh, D. (2013). AgroMobile: A Cloud-Based Framework for Agriculturists on Mobile Platform. International Journal of Advanced Science and Technology, 59, 41–52. doi:10.14257/ijast.2013.59.04 Ruixue, Z. (2002). Study on Web-based Agricultural Information System Development Method. Proceedings of the Third Asian Conference for Information Technology in Agriculture, China (pp. 601-605). Shangguan, W., Dai, Y., Liu, B., Ye, A., & Yuan, H. (2012, February 29). A soil particle-size distribution dataset for regional land and climate modelling in China. Geoderma, 171, 85–91. doi:10.1016/j. geoderma.2011.01.013 Singh, S., & Chana, I. (2015). QoS-aware Autonomic Resource Management in Cloud Computing: A Systematic Review. ACM Computing Surveys, 48(3), 1–46. doi:10.1145/2843889 Singh, S., & Chana, I. (2015). QRSF: QoS-aware resource scheduling framework in cloud computing. The Journal of Supercomputing, 71(1), 241–292. doi:10.100711227-014-1295-6 Singh, S., & Chana, I. (2015). Q-aware: Quality of service based cloud resource provisioning. Computers & Electrical Engineering, 47, 138–160. doi:10.1016/j.compeleceng.2015.02.003 Singh, S., & Chana, I. (2016). EARTH: Energy-aware Autonomic Resource Scheduling in Cloud Computing. Journal of Intelligent and Fuzzy Systems, 30(3), 1581–1600. doi:10.3233/IFS-151866 Sørensen, C. G., Fountas, S., Nash, E., Pesonen, L., Bochtis, D., Pedersen, S. M., ... Blackmore, S. B. (2010). Conceptual model of a future farm management information system. Computers and Electronics in Agriculture, 72(1), 37–47. doi:10.1016/j.compag.2010.02.003 Sørensen, C. G., Pesonen, L., Bochtis, D. D., Vougioukas, S. G., & Suomi, P. (2011). Functional requirements for a future farm management information system. Computers and Electronics in Agriculture, 76(2), 266–276. doi:10.1016/j.compag.2011.02.005

This research was previously published in the Journal of Organizational and End User Computing (JOEUC), 29(4); edited by Steven Walczak and Sang-Bing Tsai, pages 1-23, copyright year 2017 by IGI Publishing (an imprint of IGI Global).

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ICTs for Agricultural Development and Food Security in Developing Nations Bhattacharjee Suchiradipta Independent Researcher, India Raj Saravanan National Institute of Agricultural Extension Management (MANAGE), India

ABSTRACT Development has many faces and complete wellbeing of human population is the most important one of them which in more than one ways involves agriculture and the farming population. Providing needed information at the right time to the rural population is the first step in their empowerment and ICTs can play an immensely important role in providing that information by increasing the dialogue between development professionals and rural people at every stage of development process. According to recent statistics released by ITU, over the last 15 years, ICTs have grown in unprecedented ways providing huge opportunities for social and economic development and this growth can be an advantage to rural advisory services. Providing correct and personalized information needs expert opinions and so multistakeholder engagement makes the process more efficient and ICTs provide a very unique and important platform for such collaboration, thus bringing together different stakeholders for efficient partnership. The various tools and technologies can also be tailored according to the needs of end users. But in spite of the advantages, ICTs can only be universally accepted and used when the challenges of accessibility, acceptability, funding, and sustainability are overcome. There are no formula for sure success with ICTs and situation is the best determinant of the strategy to be used and so, a balanced and strategic use of ICTs depending on the clients’ needs can best utilize its potential for agricultural development and food security in developing nations.

DOI: 10.4018/978-1-5225-9621-9.ch022

Copyright © 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 ICTs for Agricultural Development and Food Security in Developing Nations

INTRODUCTION Global development has many faces and all of them concern human development – taking people out of poverty, assuring food security for everyone, and ensuring a fairly comfortable life. This is a difficult task considering one in nine people in the world suffer from hunger. The problem becomes complicated with the uneven distribution of the famished population with higher concentration in countries of Sub-Saharan Africa where one in four people suffer from chronic hunger, as well as Southeast Asia which has the largest number of undernourished persons (FAO, 2015). One of the largest missions taken worldwide in recent times to ensure human development was the Millennium Development Goals (MDGs) adopted at the Millennium Summit of 2000 of the United Nations, where the member countries promised global partnership and set time bound quantified targets with a deadline of 2015. These MDGs were formulated with the goal of all round human development by eradicating hunger and poverty, providing universal primary education, promoting gender equality and women empowerment, reducing child mortality, improving maternal health, combating major life threatening diseases across the world, ensuring environmental sustainability, and developing a global partnership for development (Millennium Project, 2006). The MDGs targeted world poverty in its many dimensions and by 2015, though the target of halving extreme poverty has been met, it was far from being well distributed across the continents. While a few Asian countries accounted for most of the decline, the absolute number of poor has risen in Sub Saharan Africa. Poverty and food insecurity in the world right now is predominantly rural with 78 per cent of the world’s extreme poor living in rural areas with the majority dependent on agriculture. In addition, almost 60 per cent of child labour worldwide is found in agriculture. The world has the capacity to produce enough food to feed everyone equally, even with the estimated 60 per cent increase in production to meet the projected demands of 2050, yet still, the rural poor - mostly consisted of subsistence producers, family farmers, and landless labourers – live on less than $1.25 USD per day. After 2015, the development agenda shifted from goals and targets to measurements and means. As a result, discussions on building on innovative ways to address the world’s most pressing challenges began and Sustainable Development Goals (SDGs) were implemented. One of the five agents of change identified for transforming development economies is family farmers and small scale producers. Agricultural growth is up to five times more effective than any other sectoral growth in resource poor low income countries in reducing poverty (FAO, 2015) but the problem is more than sustainable agricultural production; it is of connecting the farmers and making them informed, and helping them to organize themselves to get the most out of their investment in their agricultural fields. In so doing, Information and Communication Technologies (ICTs) can be a very important aid to rural advisory services.

INFORMATION EMPOWERMENT Information is a critical input in agriculture and given at the right time, it can prove to be the most important one (Saravanan and Suchiradipta, 2015b). Providing needed information at the right time to the rural population is the first step in their empowerment and ICTs can play an immensely important role in providing that information by increasing the dialogue between development professionals and rural people at every stage of the development process. Information empowerment of rural people helps them to be active partners in development efforts and not mere beneficiaries. ICTs make the job easier

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through TV, radio, computer, mobile phones, and recently social media. But in developing countries, information poverty is one of the more significant and insidious obstacles to effective exploitation of information processing and other types of technology (Sadowsky, 1996). According to recent statistics released by ITU, over the last 15 years, ICTs have grown in unprecedented ways providing huge opportunities for social and economic development. Since 2000, internet penetration has increased 7 fold from 400 million users in 2000 to 2.2 billion users in 2015. Mobile subscriptions are up from 738 million to 7 billion and developing countries provide a wide opportunity for further development with new users and more population to reach (ITU, 2015). Social media, the recent addition to the world of ICTs, is gaining popularity very fast with a global penetration of 29 per cent, a 12 per cent increase from 2014 with a major boost from increased mobile subscriptions. Facebook is the most popular social media platform with about 1.5 billion users worldwide (Kemp, 2015) and the number increasing every day. But conditions in least developed countries (LCDs) are still challenging. Internet penetration is 9.5 per cent for population and 7 per cent for households, mobile broadband subscription is only 12 per cent of the population and fixed broadband subscription negligible at 0.5 per cent. Also, the fact that monthly fixed broadband prices are three times higher and mobile broadband prices are two times higher in developing countries than in developed countries (ITU, 2015) is only adding to the cause with poor households finding it difficult to invest in internet services.

ICTs in Rural Advisory Services (RAS) With increasing diversities in agriculture, more stakeholders and increasing need to produce more to reach farmers at the right time with correct and needed information is not limited only to the extensionists. Moreover, information being one of the most critical inputs in agriculture, farmers are willing to pay for it, thus making extension a profitable business. But providing correct and personalized information needs and expert opinions on a timely basis is a complex process and so multi-stakeholder engagement makes it more efficient. ICTs provide a very unique and important platform for such collaboration, thus bringing together different stakeholders for efficient partnership.

Philosophy and Principles of ICTs for Agricultural Development (Adopted From Saravanan et al., 2015a) ICTs are better enablers for information and knowledge access and sharing among agricultural innovation system actors compared to conventional methods. They also complement the conventional extension advisory methods. The guiding principles (World Bank, 2011; Saravanan 2011b; Saravanan, 2013) of ICTs for a more efficient extension and advisory services (EAS) are: • • •

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Relevant Content: Contextualized or farmer specific, need based, timely and quality content is the major aim of ICT based EAS. Appropriate ICT: Among a variety of ICTs, choose the formats, channels, tools, devices and applications that best match the purpose, content and clientele. Integration of Methods, Actors and Services: Integrating ICTs with other conventional extension methods (like Farmer Field Schools (FFS), Community Knowledge Workers (CKWs), etc), pluralistic actors (public, private, Farmer Based Organisations (FBOs), etc) with their services along the value chain will create synergy in extension and advisory services.

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•

• • • •

Information PLUS: To convince the clientele, (i.e. show and tell). ICT based information alone is not enough and needs to be combined with field demonstrations, exposure visits, group discussions etc. Not just advisory information, but a complete resource package across the agricultural value chain1 needs to be provided. Human Element: Commitment of the extension stakeholders to use ICTs, development of ICT champions with the legacy of promoting continuous leaders and followers are important. ICTs Complementary to EAS: ICTs can play only a complementary role in extension. If they are used appropriately, they create synergy and better impact with conventional extension efforts. Institutionalizing ICTs: Institutional policy and guidelines to use, developing the ICT literacy and competency among the human resource and infrastructure development should be an integral part of the institutional set-up. Reasonably Long Term and Continuous Engagement with ICTs: To see the better outcome, ICTs need to be integrated with the conventional extension approaches for a reasonably (at least for 5 years) long period.

Broad Areas of ICT Implementation for Agricultural Development (Adopted From Saravanan et al., 2015a) ICTs based extension advisory methods are implemented along the agriculture value chain activities such as pre-production, production, post-harvest and marketing, financial services (credit, payment, savings, insurance, etc.), climate and other data. Five broad areas1 of ICTs implementation are: 1. Offering Localized and Customized Information, Advisory and Other Services: Farmers call centres (FCCs), mobile apps, radio, TV etc. 2. Helping to Create, Document, Store, Retrieve, Share and Manage the Information: Web portals, crop specific portals, knowledge banks, expert systems and agricultural information management systems etc. 3. Enabling Collaboration, Sharing and Partnerships for Innovation Among Extension Actors: Social media, Dgroups etc 4. Enabling Farmers and Others to “Gain a Voice”: Community radio, tele-centres, videos, communities of practice (COPs) etc. 5. Facilitating Capacity Development of Farmers, Extension Professionals and Other AIS Actors: E-learning mechanisms (Open Distance Learning (ODL), Learning Object Repositories (LOR), Massive Open Online Courses (MOOCs) and other e-learning mechanisms etc.), training by using ICTs, survey and monitoring tools and applications. ICTs have been used in various forms depending on the need of the clientele, location specificity, availability and accessibility of technology and so on. Major forms of ICT tools and applications in Rural Advisory Services (RAS) are discussed below: •

Radio and Television: Radio and TV are the earliest forms of ICTs used in agricultural extension and advisory services and are the most popular with the rural communities. They have been very helpful in dissemination of information and technologies among the farmers in rural areas but

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•

•

their very nature inhibits interactivity or location specificity which restricts their scope in information dissemination in an era of technology. In recent times though, community radio stations have tackled the problems of location specific information and have made the rural people major stakeholders in information dissemination and discussions about community development. Interactive Multimedia Compact Discs (IMCDs), Decision Support Systems (DSS), and Expert Systems: Multimedia is a combination of text, graphics, art, sound, animation, and video elements where the viewers can control what elements are delivered and when. This is known as interactive multimedia. IMCDs offer learners complete and individual control over their learning and encourages better understanding between individual learners and the subject matter. Decision support system (DSS) is a computer program application that analyzes data and presents it so that users can make decisions more easily. DSS uses Artificial Intelligence (AI) and expert systems to present data in a format suitable to the users. Expert systems are tools for information generation from given information by simulating human reasoning about a problem domain. The knowledge acquisition process for building an expert system facilitates the integration of knowledge and experiences of different specialties which help generate advice based on its knowledge base and reasoning mechanism from all developed extension documents. Web Portals: Web portals are digital platforms that provide organized gateways to information or act as aggregators of knowledge from various stakeholders. They are specifically designed single access points to information collected from diverse sources. In agricultural extension and advisory services context, web portals can be of two types – those providing technical and market knowledge to end users at the grassroots level, and those helping with capacity development of extension personnel. Financially and socially, portals can have far reaching impact on users. Illiteracy – both educational and technological – can be a barrier in accessing web portals by grassroots level users but with the help of extensionists, they can be of much help to the rural communities (Saravanan et al., 2015b). A few examples of some successful initiatives to use web portals for agricultural communication are discussed below.

University Web Portal TNAU Agrictech Portal has been catering to the needs of farmers, extensionists and other stakeholders in agriculture and allied sectors since 2009. It offers a diverse range of information from crop related to weather information, daily market prices, schemes and programs for farmers, daily news, events and publications supported by multimedia, expert systems and many others. The portal can also be accessed in Tamil and English languages and offers a keyword search facility. Farm technology portal (http:// agritech.tnau.ac.in) was designed by integrating the allied sectors of agriculture, horticulture, agricultural marketing and agriculture business, agricultural engineering, sericulture, seed sector, forestry, fisheries and animal husbandry. This dynamic portal page holds more than half a million pages in Tamil and English with multiple media content. According to Google Analytics, from April 1st 2015 the daily visitors ranged between 26000-28000, new visitors numbered 1,44,100 at the rate of 57%, the new sessions were 2,33,168 with an average session duration of 4:09 minutes, number of page views were 7,39,706 with a bounce rate of 62%. The average page/session was 3:17 minutes. The online input information service ensures timely sourcing of critical inputs to farmers in the state. By using the last mile connectivity, Short Message Messages (SMS), more than 10,000 million SMS

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have been sent to farm beneficiaries in English and Tamil through m- kisan mobile linked interface. The agritech portal is linked to social media networks like blogs, twitter and YouTube, and Facebook messages are updated on agriculture related news on a daily basis both in English and Tamil.

Crop Specific Portal “Rice Knowledge Management Portal” (www.rkmp.co.in), as the name exemplifies, facilitates efficient management of the enormous knowledge on rice crop on a single click. With more than 16,000 pages of validated and localised content in seven vernacular languages and 18 stakeholder platforms, this is considered as the largest repository of knowledge on any single crop across the globe. Today, a rice farmer from any corner of the country is able to get all the rice related reliable information specific to their region in the language of his choice. The dream of any extension professional to provide the right information at the right time and context in the local languages to the farmers is realized through Rice Knowledge Management Portal - the one stop shop for rice related information.

Web Portal for Agriculture Videos Access Agriculture (www.accessagriculture.org) is a video based web portal started in 2012 with training videos in agriculture and allied sectors, business skill development and market development. It has something to offer to all agricultural stakeholders. The online videos can also be downloaded and language of the audio can also be requested as per preference of the user. The web portal also has social media presence in Facebook and LinkedIn and has a video social media site called AgTube.

Web Portal by the Extension Organisation eXtension (www.eXtension.org) is an interactive learning environment delivering the best, and most researched knowledge from the land-grant university minds across America. eXtension connects knowledge consumers with knowledge providers - experts who know their subject matter inside out. eXtension is unlike any other search engine or information-based website. It’s a space where university content providers can gather and produce new educational and information resources on wide-ranging topics. Because it is available to students, researchers, clinicians, professors, farmers as well as the general public, at any time from any Internet connection, eXtension helps solve real-life problems in real time.

Web Portal for Integrated Rural Advisory Services As part of the India Development Gateway initiative of Government of India, Vikaspedia portal (www. vikaspedia.in) is aimed at creating a versatile collective knowledge repository and demand driven information in the development oriented sectors including Agriculture. This multilingual portal is serving as a collaborative content creation, knowledge sharing and utilization platform for the stakeholders in agriculture and allied sectors14. Currently, Vikaspedia is one of the largest knowledge portal hosting information/knowledge in 10 Indian languages, offering information on success stories, best practices, government schemes, technologies, market information and related value added services in Agriculture.

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•

•

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Online Learning Platforms: Learning platforms are interactive online services that provide learners with resources to support and enhance educational delivery and management. They are virtual learning environments that make the process interactive with integrated discussion boards, chat rooms and other such facilities where contents are both expert suggested and user generated. These kinds of learning platforms also serve as online repositories and can be very helpful for all agricultural stakeholders to increase their expertise on practical topics while sharing experiences with their colleagues across the globe and leaning from others’ experiences. A good example of online learning platforms is Massive Open Online Courses (MOOCs) that have recently become very popular among all agricultural stakeholders. Mobile Phones: Mobile phones are devices that can create, store, access and share information anytime, anywhere and teamed up with extension and advisory services can help improve the livelihood of rural people by taking timely information to their fingertips at potentially low cost. They also provide the unique opportunity of instant feedback and one on one interaction with experts. mExtension can facilitate the creation of scalable, replicable and commercially sustainable advisory services for rural clients and women can especially benefit from the services if access to mobile phones can be ensured (Saravanan and Suchiradipta, 2015c). mExtension: Agricultural extension and advisory services are provided through a number of modes – push and pull SMS, interactive voice response (IVR), mobile apps (mApps), and so on – sometimes individually and sometimes integrated. While SMS and IVR services are accessible from both feature and smart phones, mApps require smart phones. Services can be free or subscription-based. Cost does not seem to affect popularity as shown by services such as IKSL in India, iCow in Kenya, Kilimo Salama in Kenya and Rwanda, and e-Krishok in Bangladesh. Mobile-based advisory services are mostly targeted at farmers and the rural population but collaboration among stakeholders in agricultural innovation systems (AIS) for providing content is not unknown. The advisory services also vary from providing solely agricultural information (e.g. Gobi Sahana Sarana in Sri Lanka) to providing micro insurance to rural people (Kilimo Salama in Kenya and Rwanda), real time market information (e-soko active in 10 African countries), farmer-specific fertiliser recommendations (NMRiceMobile in Bangladesh, China, India, Indonesia, Phillipines and West Africa) or integrating agricultural and weather information along with entertainment to attract large numbers of rural people (Nokia Life Tools) (Saravanan and Suchiradipta, 2015c). Social Media: Social media are web based tools of electronic communication that allow users to personally and informally interact, create, share, retrieve, and exchange information and ideas in any form (text, pictures, video, etc.) that can be discussed, archived and used by anyone in virtual communities and networks (Saravanan and Suchiradipta, 2015d). While social media has been playing a significant role in personal communication and development communication across the globe, in the agriculture sector its popularity has also been increasing. Increased use of social media in agvocacy (agvocacy is the combination of two words agriculture and advocacy, and means talking for and about agriculture) can increase the dialogue among agricultural stakeholders and make information access much easier for rural smallholders. Also, with proper planning, a social media communication strategy can be scalable across geography (local, regional, national, global), topics of interest (e.g. business, career, agronomic practices, crops, etc.), and type of clients (women, young people, smallholders, etc.) (Saravanan et al., 2015c).

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Extension professionals are using social media to form networks and farmers are taking to social media to talk to peers and consumers. All big things in agriculture – new technology or innovations, seminars and meetings, workshops and trainings, reports, publications – get tweeted or hashtagged. Facebook, Twitter, YouTube, and blogs are the major platforms for agricultural information dissemination. The uses of socially integrated messaging apps are also increasing in the rural areas. But still, there is a difference in the intensity of use in developed and developing countries – basically due to economic conditions and infrastructure availability. In spite of the differences, use of social media is picking up in rural areas of developing and least developed countries as well (Suchiradipta and Saravanan, 2016) GFRAS Global survey on use of social media in agricultural extension and rural advisory services conducted online during 2015 across 62 countries and 229 respondents provided interesting responses. Facebook was found to be the most popular social media platform used by extension professionals. The major activity on social media was searching for news events and sharing information. A major impeding factor for social media use was the lack of authenticity of information shared online. Social construction of information (development and publication of information socially by the users) was considered the most important feature of social media (95.1%). Ninety five percent of the respondents believed social media can play an important role in bridging the gap between stakeholders in Agricultural Information services (AIS). Reaching clients (77.4%) was a major use of social media in AEAS. Training in social media use was uncommon, and 71% of the respondents said they need training on social media use. If and when there was training conducted by the respondents’ organizations, it mainly focused on the specifics of different social media platforms and awareness creation on the use of social media in agricultural extension. But on an organizational level, social media is still not given much importance by higher authority and social media policy restricts rather than encourages its use. Also, weak or non-existent connectivity in rural areas, high cost of data charges, illiteracy of the clients and low participation and lack of interest of clients are reported to be major problems. Overall, the survey found that social media is a very useful tool in agricultural extension and rural advisory services. To quote one respondent, “social media is not only a tool for reaching large audiences; it is also an opportunity to develop relationships.” (Suchiradipta and Saravanan, 2016) The use of social media is becoming more and more pronounced in agriculture and a few of the popular social media accounts and handles across various platforms, as in Table 1, will give a better idea into their works. ICTs have provided many opportunities for collection, processing, storage, retrieval, managing and sharing of information in multiple format for providing a wide range of services (information, awareness, promotional, advisory, knowledge, technology transfer, training, education, and much more) to farmers and other agricultural innovation system (AIS) actors in a timely, comprehensive, cost-effective, and interactive manner (Saravanan et al., 2015a). But one important factor that impacts the success of ICT based projects is the suitability of the technology used. In areas where the majority of the end users are illiterate, TV, radio, voice based mobile advisory services and video- based web portals are more appropriate; community radio and mobile phones are more suitable media to engage women farmers. Young farmers can be most engaged on social media platforms like Facebook, Twitter and Whatsapp, and depending on the electronic device availability with the client, the development organizations need to provide basic infrastructure like internet kiosks to access the information provided. To make ICTs a real success and not a piecemeal approach in RAS, more attention needs to be paid to the ‘I’ and ‘C’ of

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Table 1. Examples of use of social media in agriculture Name of Group/ Community/ Pages

Description

Target Users

Region

FACEBOOK By farmers Livestock Information and Marketing Centre (https://www.facebook.com/ groups/Livestock.TN/)

Members (farmers, extension personnel, scientists, market functionaries, consumers, local leaders, etc.) of this group share information related to livestock production, management, marketing, etc. A separate page is also on Facebook related only to marketing of livestock. (https://www. facebook.com/Livestock.Market)

Agricultural stakeholders related to livestock

India

Mkulima Young (Young Farmer) (https://www.facebook.com/ mkulima.young)

This page is an information sharing platform for young farmers started by Joseph Macharia, a young farmer himself. Mostly agro-advisory and market information are shared.

Young farmers

Kenya

Turmeric Farmers’ Association of India (https://www.facebook.com/ turmeric.farmers)

This page was created by turmeric farmers to stabilize the price of turmeric in the market. To date, the farmers connect through the page and share information to keep turmeric price stable and increase marketing opportunities of turmeric.

Turmeric farmers

India

National Ecological Producers Association (APNE) (https://www.facebook.com/anpe. peru)

Information related to ecological farming is shared through the page.

Farmers

Peru

Krishi Vigyan Kendra, Namakkal communicates information related to farmers’ training programmes, availability of inputs etc. through this account

Subject Matter Specialists of KVK, farmers, agricultural stakeholders

India

Agricultural Extension in South Asia (AESA) (https://www.facebook.com/ groups/428431183848161/)

Members post links to relevant publications on extension and advisory services, announcements of workshops and conferences, major policy decisions on extension, reports of meetings/ workshops and blogs relevant to the broader theme of extension

Agricultural Extension stakeholders

South Asia

Global Forum for Rural Advisory Services (GFRAS) (https://www.facebook.com/ groups/gfras/)

This page provides information related to advocacy and leadership on pluralistic, demand-driven rural advisory services.

AEAS Professionals and others

Global

Mr. Madhu Balan, a public extension officer started a Facebook group to cater to the information needs of famers in 2012. This group exchanges information on improved farm technologies, initiates discussion with other farmers and extension personnel, share information and photos on best practices by other farmers, government schemes, etc. Question and answers, information on Terrace garden and hydroponics are the most discussed topics in this group.

Farmers and others who are interested in agriculture

India

AgChat (https://twitter.com/agchat)

The AgChat (Twitter online discussion group by the AgChat Foundation) started in 2009 by a group of American farmers is widely used in USA, UK, Australia, New Zealand and Ireland for facilitating discussions of industry issues between farmers and agribusinesses

Farmers, entrepreneurs, farm product consumers

USA, UK, Australia, New Zealand, Ireland

Agriculture Proud (https://twitter.com/AgProud)

Twitter handle of Ryan Goodman, a young farmer and rancher from Montana, US. Through his Twitter account he shares his experiences of farm life and answers questions from fellow farmers, agriculture enthusiasts, and consumers.

Agriculture enthusiasts, consumers, and fellow farmers

USA

Young Farmers (https://twitter.com/F4YFKenya)

Information shared through this Twitter handle of the Foundation for Young Farmers shares information for better agriculture with the objective to attract more youth to farming.

Young farmers

Kenya

By extension centres Krishi Vigyan Kendra, Namakkal (https://www.facebook.com/krishi. namakkal) By extension professional networks

By extension personnel Vivasayam Karkkalam (Let us Learn Agriculture) (https://www.facebook.com/ groups/madhualan) TWITTER Farmers

continued on following page

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Table 1. Continued Name of Group/ Community/ Pages

Description

Target Users

Region

Extension centres USDA (https://twitter.com/USDA)

The Twitter handle of U.S. Department of Agriculture shares latest news, events, and information in agriculture

Farmers, extensionists, development practitioners

USA

INGENAES (https://twitter.com/INGENAES)

This Twitter handle of Feed the Future initiative Integrating Gender and Nutrition within Agricultural Extension Services shares information and gender-appropriate, nutrition-enhancing technologies to improve life and livelihood of women farmers

Researchers, extensionists, farmers

Global

eXtension4U (https://twitter.com/eXtension4U)

Twitter handle of eXtension.org, a research based learning network of cooperative extension of USA. Sound research based information is shared through the handle.

Farmers, researchers, policy makers of USA related to Agric. Research and Dev

USA

MEAS (https://twitter.com/MEAS_ extension)

Twitter handle of the project Modernizing Extension and Advisory Services shares good practice strategies and related information to ultimately raise farm income and enhance livelihood of rural poor of 12 selected countries of Asia and Africa.

Development practitioners

Global

GFRAS (https://twitter.com/infogfras)

This page provides information related to advocacy and leadership on pluralistic, demand-driven rural advisory services.

Extensionists, development practitioners, researchers, policy makers

Global

e-Agriculture (https://twitter.com/e_agriculture)

Twitter handle of e-Agriculture, a global initiative to enhance sustainable agricultural development and food security by improving the use of ICTs. Information shared is related to recent developments, efforts, publications and stories of ICT use in agriculture.

Farmers, researchers, development practitioners

Global

Gate to Plate Blog (Michele Payn-Knoper) (http://www.causematters.com/ blog/)

Through this blog, agriculturist, entrepreneur and founder of Cause Matters Corp. shares her views about food and agriculture.

Farm product consumers, agriculture enthusiasts, farmers

USA

Ecoagriculturist (Oluwabunmi Ajilore) (https://ecoagriculturist.wordpress. com/)

The blogposts are related to sustainable agriculture, environment, youth involvement in agriculture, ICT4Ag, and other related topics. The blog was also a winner of the YoBloCO Awards of CTA in 2014.

Farmers

Nigeria

The Unconventional Farmer (Gil Carandang and Patrick Gentry) (http://theunconventionalfarmer. com/flog/)

Featured in top 50 farm blogs by www.seametrics.com, this blog covers natural farming techniques from Japanese and Korean natural farmers. Topics range from farming techniques to animal care for urban and rural farmers.

Farmers, agriculture enthusiasts

Global

AGRF Blog (African Green Revolution Forum) (http://www.agrforum.com/blog/)

The AGRF was established in 2010 to initiate discussions and develop concrete plans for achieving Green Revolution in Africa. The blog is a part of the initiative where issues related to African agriculture and ways to develop are discussed by various authors working in different capacities in the agriculture sector. The posts are by invitation only to maintain professionalism.

Policy makers, private actors, civil society actors, researchers, farmers, agribusinesses

Africa

Agricultural entrepreneurship (Penn State Extension) (http://farmbusiness.blogspot.in/)

This blog is especially helpful for agripreneurs for getting information on marketing, economics, and other recent news in agricultural industry. Since 2008, 348 blog posts have been made by the eight contributors.

Agripreneurs

USA

Professional networks

BLOGS Individual blog

Institutional blog

continued on following page

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Table 1. Continued Name of Group/ Community/ Pages

Description

Target Users

TNAU Agritech Portal blog (Tamil Nadu Agricultural University) (http://tnauagritechportal.blogspot. in/)

The blogs of TNAU Agritech Portal deals with everything agriculture – from sowing to harvesting, crop protection to crop management, weather, recent happenings in the agriculture industry, schemes and programs for farmers, ICTs, and many more. A total of 940 blog posts have been made since 2012, 541 of which are made in 2015 itself, by 43 members consisting of extensionists, researchers, academicians, and farmers.

Farmers, agripreneurs, extensionists

Region

India

YOUTUBE Farming First (https://www.youtube.com/user/ FarmingFirst/)

This channel highlights the mission of the agricultural development coalition of the same name, founded in 2009. Made up of 131 organizations worldwide, Farming First prioritizes the protection of natural resources, knowledge sharing, local infrastructure, harvests, market access, and innovative research (www.foodtank.com).

Policy makers, researchers, agricultural enthusiasts and practitioners

CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) (https://www.youtube.com/user/ CCAFS)

The videos shared by the channel features stories of smallholder farmers, interviews with leading agricultural experts across the globe, and innovative information on climate-smart agriculture (www.foodtank.com).

Researchers, farmers, policy makers

Global

IFADTV (https://www.youtube.com/user/ IFADTV/)

It is a well produced and highly engaging channel from the International Fund for Agricultural Development (IFAD). Videos feature news stories about smallholder farmers in addition to interviews with agriculture experts (www.foodtank.com).

Policy makers, farmers, extensionists

Global

Farmers Weekly Video (https://www.youtube.com/user/ FarmersWeeklyVideo/)

It is produced by U.K.-based Farmers Weekly, a multimedia independent information service for farmers and agricultural businesses. Videos contain information on how to make agri-businesses sustainable, advice on farming careers, and information on different crop inputs (www. foodtank.com).

Farmers, extensionists, agribusinesses

U.K.

Global

(Suchiradipta and Saravanan, 2016)

ICTs rather than the ‘T’ only (Saravanan and Suchiradipta, 2015a). This requires shifting the focus to specific target groups and engaging them fruitfully to ensure successful implementations of ICTs. Youth everywhere can be the most important stakeholder in this process.

Youth and ICTs in Agriculture ICTs for Youth (ICT4Y) in Agriculture ICTs and youth can prove to be a great catalyst in agriculture. ICTs are the developmental tool kits to empower the rural youth to fight against the odds of poverty, backwardness and illiteracy and come out victorious in their agricultural fields. It is not a mere technological innovation to come and go but application of ICTs in agriculture is a permanent solution to many of the problems of the sector in developing countries. It will also bridge the gap between the present and past making young people the catalyst for the change among their peers. Moreover, forming an opportunity of employment for the rural youth does not only help them but saves the society from many odds. ICTs empower the rural youth and channel their energy in a desired direction. Of the other direct impact of ICTs on youth in agriculture are forming virtual peer groups to share their experience. The youths from various parts of the world with the Web 2.0 can gain exposure to what is happening in the agricultural front in other parts of the world and thus gain a better understanding of their own situation. This helps them to take better decisions in their own condition. It also gives them the

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opportunity to give their voice in the policy making process. ICTs increase the productivity and inspire the youth to venture in agripreneurship. ICTs also increase the social status of the farmers and the need for social recognition attracts others to the use of technology in their conditions. It also increases the negotiating power of the farmers and makes them more informed for so as not to be cheated by others. The role of ICTs, thus, can be felt in every sphere of life of the farm youth. As shown in the Figure 1, it is a lifelong process of learning from their own experiences, from others in the community (both actual and virtual) or from access to the worldwide knowledge repository and also passing that knowledge to those who need it. Not only that, it also helps in their skill formation and proper planning and management of their investments thus ensuring an inclusive individual and community development. In many countries, mobile phones have reduced the work of farmers allowing they to devote to other works. They do not have to walk long distances in order to transfer money from the bank or get information about market prices. It has also inspired the farm youth to take entrepreneurial steps in innovative ways to make agriculture remunerative and thus reduce the drudgery involved.

Youth for ICTs (Y4ICT) All the discussions till now have been on how the ICTs can revolutionize agriculture. But like all other technologies, it needs a carrier to take it forward and implement it. ICTs are powerful only as long as they are used to their fullest potential. The youth who form a major portion of the developing world can get the best out of them because of their natural affinity to technology. It is important for the young people to participate in the ICT initiatives and their implementation, as they know best the needs of their community and themselves. It also adds the bottom-up approach to the project implementation making it more realistic and fruitful. The youth can play a big role in bridging the digital divide that exists in developed and developing countries and also the rural and urban areas. They can not only help themselves but also the other community members to get the best out of their land (Suchiradipta and Saravanan, 2013).

Youth and ICTs: Example of a Fruitful Relationship In North-East India, Jhum cultivation (Slash and Burn Agriculture) is the most predominant form of agriculture. The prevalence of number of tribal dialects makes communication difficult for change Figure 1. Potential of ICTs in youth and community development (Haddad, 2007)

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agents. Hence, considering the farming situation and difficulty in communication of appropriate farm information, an e-extension project (e-Arik) was initiated since 2007 in East Siang district of Arunachal Pradesh state. To overcome communication difficulty and also to motivate rural farm youth and others to take up profitable farming activities, four educated tribal farm youth were used as ‘farmer facilitators’ along with ICTs. They were given advanced farm technological training at the constituent college of the Central Agricultural University (CAU) and KVK. The farm youth helped to create general agricultural and rural development awareness among tribal farmers, facilitated eco-friendly and sustainable farm technology dissemination, developed vocational efficiency among farmers, formed farmer groups for self-help, facilitated use of local resources, helped to make timely decisions by the farmers themselves and suggested alternative ways to solve farming and other rural problems in twelve selected villages. By the efforts of farm youth facilitators by following ‘farmer to farmer communication’ approach and using ICT tools, 44 percent and 92 percent of farmers adopted the information on climate smart practices on paddy (Oriza sativa) and Khasi Mandarin (Citrus reticulata) crops respectively. After three years of project initiation, 55 percent of farmers developed new Khasi Mandarin orchards in their Jhum field, which means they are permanently moving from age old Slash and Burn agriculture to settled cultivation. Even after the completion of the project, trained farm youth are serving as a link between agricultural development departments and tribal farmers for facilitating advanced farm trainings and advisory services and they become ‘local knowledge managers’ to foster agricultural development in the remote tribal villages” (Saravanan, 2011a & b).

IMPLEMENTATION OF ICTs IN RAS Appropriateness of ICTs depends on the situation and their use is most successful as a catalyst of development and to do so a few logical steps need to be followed. While the steps may be indicative of the logical delivery of ICT projects, they are not absolute in any terms, but very much flexible depending on the need of the situation and best judgements of the extension organisation, based on detailed need assessment surveys among clientele and other stakeholders (Saravanan et al., 2015a). 1. Need Assessment: EAS is most useful and applicable when information and services provided are localized and need based and so for the ICT projects to be successful, the first and foremost action of a host organization should be need assessment of the target community. 2. Benchmark Survey: Standards or points of reference are very important for ICT enabled services to meet their objectives and this makes benchmark surveys a necessity. They are also useful as standards of monitoring and evaluation. 3. Content Development: Localized and customised content needs to be developed based on the results of need assessment and benchmark surveys to avoid the problem of blanket recommendation. 4. ICT Selection, Development and Testing: Based on localised needs, content, and target groups, the appropriate ICT tool needs to be selected, developed and pilot tested for determination of suitability. 5. Awareness Programs and Registration: One major drawback in ICT projects is lack of awareness of target users about its existence or benefits and to solve that, innovative awareness campaigns need to be conducted to make them aware of the projects. In the case of subscription based services, it is more important as the users need to register to receive the benefits.

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6. Extension, Advisory and Other Services: Based on demand and needs of the users, the services are to be provided to the targeted groups. 7. Partnership and Integration of Services: Depending on the need of the project and the services provided, collaboration among stakeholders needs to be formed and integration of services are to be determined to provide quality service to the users. 8. Monitoring and Stabilization: Continuous monitoring is an important function, especially in the pilot phase, to determine the suitability of the project to target users and accordingly modify the services offered to ultimately scale up the project in a profitable manner. 9. Impact Assessment: It remains one of the most important steps in implementation of ICT projects as the impact ultimately decides the degree of success of the projects in bringing the desirable changes in the target group as well as the factors deciding its sustainability for the long run.

SWOC ANALYSIS OF ICTs IN RAS ICTs no doubt have the immense benefit of reaching the unreached, thus making it one of the most important supplements to RAS. This gives a huge opportunity to reach the BoP farmers and provide them necessary information to commercialize their agricultural practices and become self-sufficient. Then again, ICTs are only useful when the farmers can access the infrastructure, which is oftentimes non-existent in rural parts of the developing world, mostly when they are literate and tech savvy and also can bear the cost of the devices necessary. However, once these challenges of funding of projects, sustainability and acceptance by rural people are overcome, ICTs can become the most important catalyst in development of the rural population in the developing countries. The various strengths, weaknesses, opportunities and challenges of ICTs in RAS are presented in Table 2. Figure 2. Steps for implementation of ICT enabled RAS (Saravanan et al., 2015a)

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Table 2. Strengths, weaknesses, opportunities, and challenges of ICTs in RAS Strengths Better access to services Cost-effective Timely Any time anywhere Supplements the role of extensionists Better research-extension-client system linkages

Weaknesses

Opportunities

Challenges

Success depends on human commitment Lack of personal touch in RAS Lack of ICT skill and competency Lack of institutional ICT policy in RAS Long-term sustainability

Continuous improvement of ICT infrastructure Penetration of high end mobile phones Reducing cost of ICT infrastructure and services Multiple players in RAS services provision using ICTs

Farmer-specific and relevant content Language barriers Low literacy of rural farmers Imparting skill and competence among RAS stakeholders to use ICTs Duplication and contradictory information flow

(Saravanan et al., 2015a)

Capacities Required for Using ICTs in Agricultural Development ICT is an umbrella term used for different types of communication technologies that sometimes require completely different kind of skill set to productively develop, implement, and use them for development purposes. Also, depending on the target user, content modification becomes a very important issue. All these require professional capacities in both technology and social sciences. Table 3 below discusses the various capacities needed for successful implementation and ways to develop the major ICT tools predominant in agriculture.

Governance in ICTs for Agricultural Development In the context of Agricultural Innovation Systems (AIS), to provide a quality extension and advisory services to the users, development and maintenance of the ICT projects needs to be a well thought out and planned measures involving more than one stakeholder working together. And this calls for a wellstructured system that involves aptly positioned stakeholders to avoid overlapping roles. Depending on the type of ICT application, the type of governance varies and it is detailed in Table 4.

Table 3. Capacities required in and ways to develop ICT based interventions ICTs

Capacities Required

Ways to Develop

Social media

Basic knowledge and skill in using internet and social media

Creating interest groups, awareness and training programmes and regular interaction and sharing

Radio, TV, tele-centres

Minimum knowledge of operating the stations and creation of suitable programs for selected medium. RAS professionals should create and deliver appropriate content.

Training in script writing, and content treatment. Need and location specific program creation and inclusion of farmers in the programs

Web portals, expert systems, Mobile apps, MOOCs

Proficiency in IT, expertise in choosing and packaging the content. Knowledge of web content development, content creation, interactive portal management, etc.

Specialized training for developing IT and subject matter experts. Integrating and updating content regularly, interactivity and knowledge base creation

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Table 4. Governance of ICT based projects in agriculture ICTs

Maintenance

Social media

Individually maintained by extension organizations

Radio, TV, tele-centres

Programs recorded by extension organization, TV stations broadcast

Web portals, expert systems, Mobile apps, MOOCs

Hosted by extension organization, they provide information to farmers

Partnership

Stakeholders

Roles

Generally does not arise. Groups and communities can be managed in partnership mode.

All agricultural stakeholders can be brought on same platform

Host organization connects to clients and other stakeholder for better coordination and information sharing among the actors in AIS

PPP model, collaboration among public organizations.

Extension organizations, radio/TV stations or tele-centres, agricultural institutions, farmers

While extension organizations develop content of program, it is recorded by the radio/TV station or tele-centre crew. Agricultural institutions can act as information resource and farmers are the end users

Extension organization, web content developer/ app developer/course content developer, agricultural institutions (optional), and farmers

Development and management is a collaborative task, considering the involvement of many stakeholders. While the developers need to give constant upgrade, enhancements, maintenance and support, the RAS/ subject matter organization deals with content to be fed and expert service if needed to keep the information up-to-date. Farmers and others are end users.

Depending on stakeholders involved, it can be manned from PPP to profit oriented models.

Costs for Using ICTs for Agricultural Development Cost of using/ developing ICTs ranges from free to a few million USD depending upon the infrastructure and scale of coverage. Capacity development activities also require considerable amount of money (Table 5).

CRITICAL ANALYSIS OF MAJOR ICTs It is true that ICTs have transformed communication but in terms of its global reach, there are many more landmarks that need to be crossed. With increased access to the internet and increasing number Table 5. Tentative costs of hosting different ICT based initiatives ICTs

Items

Indicative Cost Involved

Social media

Internet with ICT device

ICT device cost (mobile phone/ or tablet or laptop or computer) and internet charges.

Radio, TV, tele-centres

ICT infrastructure, training for the facilitators, content creation

Depending on air time, the cost can vary from a few hundred to several thousand USDs. However, most of the state/ NGO owned TV, Radio stations can be used freely by the agricultural advisory institutions for extension and advisory services.

Web portals, expert systems, Mobile apps, MOOCs

Hiring a software specialist, training for maintenance, content collation, multimedia content, hosting etc

• Creating a basic website (USD 300 – USD 2,000), CMS integration (USD 2,000 -10,000), simple semantic portals (with 500 nodes of content USD 10,000 – 25,000) and multi-site semantic portals with multiple portlets (USD 25,000 – 60,000) and maintenance of web portals also requires considerable cost. • Expert systems may cost USD 1,000- 10,000 depending upon the design, software, and size of contents. • mApp development can be free of cost to USD 70,000 depending on its architecture and web interface

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of communication technologies with diversified working principle, a multifaceted situation is gaining traction which requires immediate attention to details for faster and wider acceptance. This specifically brings attention to the need for critically examining the advantages as well as the drawbacks of all these tools and build upon the information to make them an integral part of rural agricultural advisory systems worldwide. Table 6 deals on the same in details.

Problems Implementers’ Perspective 1. Connectivity and Infrastructure: Poor connectivity in rural areas, absence of electricity, transportation, markets and other infrastructural inadequacies restrict the implementers in using ICTs for development. 2. Technical Workforce: Technical human resource for ICT projects is very important for their smooth functioning. Functions like regular and timely updating of databases, developing location specific information, web integration and arrangement of links in case of web portals, transforming data/information in accessible formats for all type of users need technical workforce, which needs to be specifically trained in the tasks which is another challenge for the implementing agencies (Saravanan and Suchiradipta, 2015a). 3. Sustainability of Funding: ICT projects at the initial or pilot phase are more often than not funded by an external agency but after the pilot phase, in most of the cases, funding dries up and so do the projects. Financial sustainability is often addressed too late or never and so, irrespective of the influence of the projects on rural farming, communities have to wrap up, thus disappointing the beneficiaries and making them disinterested in such future attempts. 4. Effective Participation of Communities: Lack of proper planning, differences in project objectives and community needs, limited capacity building program of projects, lack of or limited interest of the community in projects due to their temporary nature, uninvolved communities as major stakeholders in projects, etc. (Saravanan, 2012) are some important factors that keep agricultural communities away from the ICT projects. 5. Lack of Leadership: To diffuse ICTs and implement them in a large scale in rural areas, effective leadership is needed at both institutional and community level. Opinion leaders in communities often lack interest in them and the younger generation does not have enough followers to effectively diffuse them in the communities, which makes a barrier in increased use of ICTs by rural communities. 6. Farmers’ Access to ICTs: The rural smallholders often do not have access to any ICTs – personal or otherwise - which makes information delivery through those media or applications redundant. 7. Institutional Barriers: Lack of flexibility in content delivery, limited innovation, lack of institutional ownership, limited technical human resource, conflict of interest among project partners, limited research collaboration, red-tapism, and project tourism attitude, etc. (Saravanan, 2012) often take the focus away from the major objective of the projects – development of communities.

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Awareness, advisory, technology transfer, mass advisory, promotional

-Portability -Low cost -Popularity in rural community

Advisory, technology transfer, awareness, documenting and sharing ITK

-Easy way of demonstration -Portability -Popularity in rural community

-Availability of playing device with farmers - Relevancy of personal context

TV Broadcasting

Awareness, advisory, technology transfer, mass advisory, promotional, documenting and sharing of ITK

-Suitable for all stakeholders -Good medium for demonstrations

-One way communication -Location specificity -Relevancy of personal context -Popularity

Target groups

Major RAS functions

Advantage

Limitation

-Lack of skill -Lack of funding

-Tool of social learning -Increased women participation

-Network coverage -Relevancy of personal context - Popularity in agricultural use

-Illiteracy -Network coverage - Relevancy of personal context -Popularity in agricultural use

-Illiteracy -Access to kiosks -Popularity among rural community -Updated database

-Easy access to expert advice -Location and farmer specific solution -Instant solutions

-Low cost -Portability -Easy feedback -Accessible for illiterates -Increased access to public information

-Low cost -Location and farmer specificity -Timely information

(Source: Saravanan et al., 2015a; Saravanan et al, 2015 b; Saravanan et al., 2015c; Saravanan and Suchiradipta, 2015c)

-Location specificity -

Community Radio Advisory, knowledge sharing, technology transfer, mass advisory

Text

Awareness, advisory, technology transfer, knowledge sharing, mass advisory, feedback

Voice Advisory, market and information linking, mass advisory, feedback, awareness, promotional, linking with AIS actors

Expert Systems/ DSS/ IMCDs

Awareness, advisory, market information and linking, credit and banking access, mass advisory, promotional, linking with AIS actors

Digital Video -Access to player -Very specific type of information -Relevancy in personal context

-Suitable for demonstrations -Low cost -High popularity -Increased women participation

Knowledge sharing, documenting and sharing ITKs, technology transfer, training, knowledge sharing

Farmers, agripreneur, extensionist

-Limited scope -Less popular

-Suitable for awareness creation -Innovative and interesting

Advisory, technology transfer, awareness

Illiterate farmers, extensionist

Animation

Literate farmers, extensionist, agripreneur

-Expert advice -Good scope for training

-Limited access Limited scope -Unavailability of infrastructure in rural areas -Rarely used

-Illiteracy -Needs technical expertise -Possibly outdated content -Limited customization for individuals -Limited access by women farmers

Training, advisory, linking with AIS actors, feedback

Advisory, documenting and sharing ITKs, market information and linking, input linking, M&E, enumeration, survey, linking with AIS actors, feedback

-Integrated information -Location specificity -Interactive -Open access

Farmer, extensionist

Web Site/ Web Portal/ Knowledge Banks/Online Repositories Literate farmers, agripreneur, input dealer, stakeholder in marketing channel, extensionist, policy maker

Tele/ Video Conference

Farmers, agripreneur, input dealer, stakeholder in marketing channel, extensionist

-Illiteracy -Accessible only in smart phones -Information not personalized

-Illiteracy -Needs technical expertise -Possibly outdated content -Limited customization for individuals -Limited access by women farmers

-Integrated information -Location specificity -Interactive -Open access

Training, education

Awareness, advisory, knowledge sharing, market information and linking, credit and banking access, input linking, feedback, promotional, technology transfer, M&E -Interactive -Updated information -Customization of information based on personal needs

Extensionist, researcher, academician, farmer, agripreneur, policy maker

Mostly literate farmers, entrepreneur, input dealer, stakeholder in marketing channel and value addition, extensionist

Mobile Apps

Literate farmers, agripreneur, input dealer, stakeholder in marketing channel, extensionist

With Internet

Computer/ Laptop/ Smart phones

e-Learning Platforms (MOOCs)

Farmers, agripreneur, input dealers, stakeholder in value chain, extensionist

Without Internet

Information and Communication Technologies (ICTs) Mobile Phones (Basic/ Feature)

-Illiteracy -Limited access -Costly data charges -Redundancy of information -Unauthenticated information

-Interactivity -User generated content -Easy access in multiple devices -Increases dialogue among development practitioners

Awareness, promotional, advisory, knowledge sharing, documenting and sharing ITKs, technology transfer, market information and linking, mass advisory, linking with AIS actors, feedback

Literate farmers, agripreneur, input dealers, stakeholder in marketing channels, extensionist, research and academic institution, experts, policy maker

Social Media

Women farmer, agripreneur, stakeholder in value chain, input dealer

Radio

Video with DVD

Farmers, agripreneur, extensionist

Radio Broadcasting

Farmers, agripreneur, input dealers, stakeholder in value chain, extensionist

TV

Table 6. Critical analysis of major ICTs

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End Users’ Perspective 1. Illiteracy: ICTs, for example mobile phones, social media, web portals, online knowledge repositories, etc. require functional literacy at the least but even that is absent in many rural areas of developing and least developed countries. Furthermore, education illiteracy which is technical illiteracy remains another constraint. And in such cases, the illiterate farmers have very few options in accessing information and so reach is limited. 2. Infrastructure: Basic infrastructures in rural areas still have a long way to go. While in some areas telecommunication structures are poor or absent, in many parts of the world, electricity is yet to reach. Added to that is the absence of other infrastructures likes markets, credit facilities, transportation and so on, that limits or discourages the use of ICTs by the rural communities. 3. Cost of Technology: Affordability of technology is also a hindrance in its use to many smallholders. While devices like kiosks, computers, video players, etc. can be accessed from telecentres, mobile phones and other such personal devices are often out of reach for many farmers in developing countries. Also, the cost of data and other charges become expensive for many to afford (Suchiradipta, 2012). 4. Information Explosion: While a large amount of information is available in the public domain to access by anyone, this information can be confusing to many users. While filtering of important information is done by extensionists to suit the needs of the individual farmer, the farmers may not always be as competent in filtering those which may be more confusing than helpful. 5. Lack of Awareness and Promotion: Since ICTs are new introductions in extension services in many rural areas, proper awareness is needed in making the rural communities interested in using them. Also, because of lack of promotion, they often do not participate in the initiatives as active stakeholders.

Evidence of Impact and Potential Scalability of ICTs for Agricultural Development Impacts of development efforts are generally multifaceted and their impact on social and personal lives of the benefactors is both direct and indirect, making them harder to point out clearly. With a two-sided argument existing around ICTs, mapping out the impact indicators can go a long way in evaluating the impact of the ICT based efforts and clearly state the achievements and limitations. They can also help with the potential scalability of ICT projects across the world, where crossing the hurdle of pilot stage is still a big concern. Table 7 discusses the same in details:

Issues of Sustainability in Using ICTs for Agricultural Development Major factors that determine the sustainability of ICT use are the ICT tools used, the domain of the service providers (public or private) and the cost incurred in providing the services. Generally, advisory through TV, Radio and community radio, social media are free of cost services. Mobile, web, interactive multimedia CDs, Videos etc. are fee based value added services or free of cost depending upon the host institutions. Governments/ public sector service providers mostly provide free of cost services (Farmers call centres, Front line SMS etc). Private sector actors are generally implementing financially sustain-

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Table 7. Impact indicators and potential scalability of ICT based projects in agriculture ICTs

Impact Indicators

Potential Scalability

Social media

Large number of YouTube channels hosted by farmers, popularity of the Twitter handle of AgChat, highly active social media pages in extension like GFRAS, AESA and farmers’ pages like Mkulima Young provide the evidence of impact. Participation of the members in the continuous engagement and discussions, creation and sharing of contents, increase in the membership subscription and feedback of members can serve as impact indicators for social media.

Facilitation of social media platforms is key for achieving the growth of audience and scalability is continuous with the increase of members’ enrolment which requires high level of participation and engagement of stakeholders

Radio, TV, Tele-centres

Significant knowledge enhancement through radio programs has been noticed among farmers is exposed to radio programs5. Before-after comparison of knowledge is an important impact indicator of broadcast services indicator.

Increasing number of programs in the prime time can give the agricultural programs larger audience and increased popularity

Web portals/ web sites/ MOOCs

e-Chaupal initiative in India for market price dissemination increased the price of soybean by 1.7 per cent and the result was instantaneous. It increased farmers’ share in producers’ money and reduced the cost incurred7. Access Agriculture, through videos hosted in the web portal, has changed the life of farmers across Asia and Africa, especially of women by taking information to them and organizing and empowering them8.Time and cost saved, income increased, increased market participation, etc. after use of information provided through web portals, can act as impact indicators for web based information services.

Continuous monitoring and evaluation and based on the findings making necessary changes depending on clients’ response is the best way to scale up web portals/expert systems and MOOCs

Mobile based advisory services

Higher market participation by farmers, reduced wastage, increased transaction, and declined search and transportation costs can serve as indicators of effectiveness of mExtension services. Information through mobile phones have strengthened local livelihoods, natural resources, increased awareness and networking opportunities, especially among women. Time saved, cost saved, income increased after use of information provided through mExtension services can act as impact indicators

Financial sustainability of mobile based services is the major issue in their scaling up and profitable business model is a necessity. Also, development beyond thepilot phase is most important for long term sustainability.

able and profitable models (e-Choupal in India, iCow and Kilimo Salama in Kenya, FCC in Uganda, and IKSL in India etc). However, for the profit oriented services, end users’ perception of usefulness of information is the ultimate determinant of the success of the business model. Sustainability of ICT projects beyond pilot phase has been a major drawback in their long term existence and there is more than one factor that influences their sustainability. The business model is very important factor since finances are the major cause of their cessation beyond the pilot stage. Also, profit oriented or financially sustainable services are more user demand oriented as subscription is important for incoming cash flow and with satisfactory service, users are found to be willing to pay for the services as in case of e-Choupal and IKSL in India, iCow and Kilimo Salama in Kenya, FCC in Uganda among many others. The funding agency also decides the business model to some extent, for example, as with government funding, cost-free services are more common whereas with public or private funding, profit motive is also a major factor along with development. The cost of providing the services impacts the business model to some extent. Another factor that impacts sustainability of ICT projects are demand based information delivery. Agriculture being location specific, crop specific and time specific, blanket recommendations are helpful to none. Customized demand based information and advisory in ICTs are not choices but a necessity for long term sustainability. Also, with changing dynamics of agriculture and time, farmers are focusing more on commercialization and so are demanding to be highly engaged to advisory service providers as important and active

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stakeholders of the system rather than mere beneficiaries of top-down development approach. Applications like social media, mApps, mobile and web based advisory services enable high user engagement and help them to customize the information they retrieve, thus making it personalized and applicable. This is an important feature in sustainability of ICT projects for long term.

CONCLUSION AND RECOMMENDATIONS With increased technological advancement and its increased use in rural areas, farming communities are to gain a lot from the use of ICTs in information access related to their life and livelihood. Information is more important in agriculture and ICTs have the potential to be an aid in taking the much needed information to the farming communities. Inspite of the potentials, problems are many as discussed earlier and to overcome those, some steps become necessary, as discussed below: 1. Implementation from Where Users Are: Information provided to smallholders, irrespective of the means of delivery, needs to be location specific and timely. For any ICT based application, that is an opportunity as well as a challenge as the easier means of communication requires it to be updated regularly. And since access is easier compared to other traditional means, to gain and retain the users’ faith in the service, the information needs to be location specific, and if possible, personalized. 2. Youth Involvement: The youth are the first to adopt any technological innovation in a social system and their involvement in planning and implementation is very important for overall success of the projects (Suchiradipta and Saravanan, 2013). Moreover, they can be leaders in community and family in diffusion of technologies for agricultural information. 3. Institutionalization of ICTs: To make ICTs an integral part of extension, the concerned institutes need to make their use an integral part of the work environment and the employees need to be encouraged about their use. Institutions also need ICT policies to encourage their use along with setting standards and boundaries that define the use of ICTs like social media focusing on the objectives and mandates of the institutions. 4. Providing Basic Infrastructures: Use of ICTs can only help the rural communities so far without any basic infrastructures like transportation, markets, credit facilities, etc. to translate the information acquired into practical action. Providing these basic facilities in rural areas is as important as the information, maybe more and so, in collaboration with competent authorities, development of infrastructure also needs to be prioritized. 5. Appropriate Partnerships: Appropriate partnerships are very important in the implementation of ICT projects for ensuring a smooth flow of resources (especially the funds to purchase and maintain ICTs), participation of local communities and institutions, regular updating of recent information in timely manner, effective management of stakeholders, and avoiding conflict for smooth functioning. 6. Partnership with Local Institutions: ICT applications are best applicable to smallholders when specific to their situations and to develop data and information that is timely and location specific, forging partnership with local research stations, universities, and other local institutions is desirable. Moreover, this makes getting up-to-date data easier and link-ups fruitful (Saravanan and Suchiradipta, 2015a).

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REFERENCES FAO. (2015). Five agents of change for a sustainable world. Accessed on 24 September 2015 from, http://www.fao.org/post-2015-mdg/news/detail-news/en/c/281554/ Haddad, W. (2007). ICTs for Education: A Reference Handbook. Accessed on October 12, 2008 from, http://www.ictinedtoolkit.org/usere/p_page.php?section_number=0 ITU. (2015). ICT facts and figures 2015. Retrieved from http://www.itu.int/ict Kemp, S. (2015). Digital, social and mobile worldwide in 2015. Accessed on August 12, 2015 from, http://wearesocial.net/blog/2015/01/digital-social-mobile-worldwide-2015/ Millennium Project. (2006). Millennium Development Goals – What they are. Accessed on September 24 2015 from, http://www.unmillenniumproject.org/goals/ Sadowsky, G. (1996). The Internet Society and Developing Countries. Accessed on October 25, 2015 from, http://www.isoc.org/oti/printversions/1196prsadowsky.html Saravanan, R. (2011a). Tribal Farm Youth for Facilitating Agricultural Advisory Services by ICTs: A Success Story from North-East India. Abstract Volume of the National Seminar on Attracting Farm Youth to Sustainable Agriculture. Saravanan, R. (2011b). e-Arik: Using ICTs to Facilitate “Climate-Smart Agriculture” among Tribal Farmers of North-East India. ICTs and Agricultural Adaptation to Climate Change Case Study. Centre for Development Informatics, University of Manchester. Accessed on April 5, 2012 from www.niccd. org/NICCD_AgricAdapt_Case_Study_eArik.pdf Saravanan, R. (2012). e-Initiative for Agricultural Extension: Browsing for Logout? Proceedings of the AFITA/WCCA 20012-8th Asian Conference for Information Technology in Agriculture (AFITA) and World Conference on Computer in Agriculture (WCCA). Retrieved from http://www.afita.org/graph/ web_structure//files/Seminar%20%2807%29-01%281%29.pdf Saravanan, R. (2013). e-Agriculture prototype for knowledge facilitation among tribal farmers of NorthEast India: Innovations, impact and lessons. Journal of Agricultural Education and Extension, 19(2), 113–131. doi:10.1080/1389224X.2012.718247 Saravanan, R., & Suchiradipta, B. (2015a). Role of ICTs in family farming: Experiences and way forward. In Family Farming and Rural Economic Development. New India Publishing Agency. Saravanan, R., & Suchiradipta, B. (2015b). Invest in IT to boost agricultural services. Smart Agri Post: Empowering Agripreneurs, 1, 22-24. Retrieved from http://www.smartagripost.com/wp-content/uploads/2015/07/Smart-Agripost-July-20153.pdf Saravanan, R., & Suchiradipta, B. (2015c). mExtension – Mobile Phones for Agricultural Advisory Services. Note 17. GFRAS Good Practice Notes for Extension and Advisory Services. GFRAS: Lindau, Switzerland. Retrieved from www.g-fras.org/en/download.html?download=349:ggp-note-17-mextensionmobile-phones-for-agricultural-advisory-services

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Saravanan, R., & Suchiradipta, B. (2015d). Social media: Shaping the future of agricultural extension and advisory services. GFRAS interest group on ICT4RAS discussion paper. Lindau, Switzerland: GFRAS. Saravanan, R., Suchiradipta, B., Chowdhury, A., Hambly Odame, H., & Hall, K. (2015c). Social Media for Rural Advisory Services. Note 15. GFRAS Good Practice Notes for Extension and Advisory Services. GFRAS. Retrieved from www.g-fras.org/en/download.html?download=355:ggp-note-15-social-mediafor-rural-advisory-services Saravanan, R., Suchiradipta, B., Meera, S. N., Kathiresan, C., & Anandaraja, N. (2015b). Web Portals for Agricultural Extension and Advisory Services. Note 16. GFRAS Good Practice Notes for Extension and Advisory Services. GFRAS. Retrieved from www.g-fras.org/en/download.html?download=356:gfrasggp-note-16-web-portals-for-agricultural-extension-and-advisory-services Saravanan, R., Sulaiman, R. V., Davis, K., & Suchiradipta, B. (2015a). Navigating ICTs for Extension and Advisory Services. Note 11. GFRAS Good Practice Notes for Extension and Advisory Services. GFRAS. Retrieved from www.g-fras.org/en/download.html?download=351:ggp-note-11-navigatingicts-for-extension-and-advisory-services Suchiradipta, B. (2012). Mobiles for mobilizing Agricultural Extension in India. Credit Seminar presented in School of Social Sciences. College of Post Graduate Studies, Central Agricultural University, Umiam, Meghalaya, 793, 103. Suchiradipta, B., & Saravanan, R. (2013). Youth and ICTs for Agricultural Development. In K. Narayana Gowda, M. S. Nataraju, & V. Veerabhdraiah (Eds.), Youth in Agriculture and Rural Development. New Delhi: New India Publishing Agency. Suchiradipta, B., & Saravanan, R. (2016). Social media: Shaping the future of agricultural extension and advisory services. GFRAS interest group on ICT4RAS discussion paper. GFRAS. Available at www.g-fras.org/en/knowledge/gfras-publications.html?download=414:social-media-shaping-the-futureof-agricultural-extension-and-advisory-services World Bank. (2011). ICT in agriculture: Connecting small holders to knowledge, networks, and institutions. e-Source Book. Report no. 64605. Washington, DC: The World Bank. Available at: http://www. ictinagriculture.org/content/ict-agriculture-sourcebook

This research was previously published in Agricultural Development and Food Security in Developing Nations edited by Wayne G. Ganpat, Ronald Dyer, and Wendy-Ann P. Isaac, pages 106-129, copyright year 2017 by Information Science Reference (an imprint of IGI Global).

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Exploring Alternative Distribution Channels of Agricultural Products Kallirroi Nikolaou Aristotle University of Thessaloniki, Greece Efthimia Tsakiridou Aristotle University of Thessaloniki, Greece Foivos Anastasiadis Aristotle University of Thessaloniki, Greece Konstadinos Mattas Aristotle University of Thessaloniki, Greece

ABSTRACT Fresh fruits and vegetables constitute the basis of many people’s daily nutrition habits and different distribution systems have been developed to cover daily supply needs. Important components of alternative distribution channels among others are high quality, high standards and consumer-producer trust. Although numerous studies have been conducted on alternative types of distribution channels, there is a lack of research on consumer behaviour towards these ways of distribution. The aim of this article is to identify consumer attitudes and preferences towards alternative agricultural distribution channels regarding fresh fruits and vegetables. In addition, this article contributes to the understanding of consumer behaviour, by pointing out the factors that affect the final purchase of agricultural products.

INTRODUCTION Globalization and recent economic trends have created highly complex supply chains and as a result their design, organization, interactions, competencies, capabilities and management have become key issues (Ashby et al., 2012). A close study of past research has shown only some traces of a structured approach to supply chains including their weak aspects and the risks involved (Svensson, 2000, Sheffi, 2001, DOI: 10.4018/978-1-5225-9621-9.ch023

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 Exploring Alternative Distribution Channels of Agricultural Products

Zsidisin et al., 2000, Guertler and Spinler, 2015, Dekker et al., 2013, Cantor et al., 2014, Heckmann et al., 2015). In order to have an integrated supply chain, a totally new approach needs to be implemented, whose development involves other related disciplines, such as market research and operational strategic management, incorporating empirical research theories and methodologies (Cheng and Grimm, 2006, Wisner, 2003). The aim of any commercial operation, including the agrifood sector, is obviously competitive advantage, which can be created by synchronizing supply chain strategy with competitive policy (Porter, 1985). This can be accomplished by establishing a wide spectrum of alternative and opportunity networks, such as distribution channels, that form a coordinated, integrated whole (Achrol, 1997, Tsang, 2000). Important components of alternative distribution channels among others, are high quality, high standards and consumer-producer trust (Whatmore, 2003). A customer-centered approach (Spiller, 2008) and a short distribution channel direct product provision from producer to consumer, are fundamental to optimal distribution. It was found that short supply chains incorporate farmers’ markets, street stalls and street markets, direct farm sales and more recently the Internet. A key priority of agriculture and rural development is to strengthen both the means of distribution and the processes and functions of the short supply chain (Burt and Wolfley, 2009, Mauleón, 2003, Falguera et al., 2012). A competitive perishable food industry, can not only provide healthy and safe food to consumers but also may constitute a factor in stabilizing the economy by generating jobs, for instance, even during the global economic crisis (Mattas and Tsakiridou (2010). Although numerous studies have been conducted on alternative types of distribution channels, there is no specific research in the field on consumer behaviour towards the use of alternative distribution channels of agricultural product in Greece.

LITERATURE REVIEW To begin with, the salient characteristics of innovativeness which reinvigorate supply chain management have appeared in conceptual and empirical studies (Chapman et al., 2003, Roy et al., 2004, Soosay et al., 2008, Panayides and Venus Lun, 2009), while Yu et al., (2014) stress that integrated green supply chain management has a positive result on operational performance. In their explanation on the historic evolution of Decision Theory in management, French et al.(2009) state that for an up-to-date, successful decision-making process, the characteristic of sustainability is needed. There are many researches that focus on the estimation that there is a lack of structured approach regarding supply chains that also include the weak aspects and the risks involved (Sheffi, 2001, Svensson, 2000, Guertler and Spinler, 2015, Dekker et al., 2013, Cantor et al., 2014, Heckmann et al., 2015). Ashby et al (2012) find that the design, organization, interactions, competencies, capabilities and management of complex supply chains have become key issues. Xue et al., (2014) investigate that alternative channel structures are affected by supply chain, and consumer behavior is affected by alternative channel structures. A key priority of agriculture and rural development is to strengthen both the means of distribution and the various processes and functions of the short supply chain (Burt and Wolfley, 2009, Mauleón, 2003, Falguera et al., 2012). Mattas and Tsakiridou (2010) focus on a competitive perishable food industry during the global economic crisis, besides providing healthy and safe food for consumers, may become a factor of stabilizing the economy. Generally, there is growing interest in alternative food systems within the context of environmental and social sustainability (Cleveland et al., 2014).

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As concerns the Local food networks focus on sustainable food production, distribution and consumption through collaboration to establish local, self-reliant economies (Katchova and Woods, 2013). As concerns the Fair trade, is associated with people’s rights to an acceptable standard of living, quality of life, equal participation opportunities, and ecological sustainability (Micheletti and Stolle, 2012). By adopting green marketing, firms can emphasize their social responsibility and promote their businesses as friends of the environment (Almossawi, 2014). The promotion of green purchasing behaviour to young people is a growing tendency (Almossawi, 2014). Furthermore, consumer perception, organic product characteristics, such as product labelling, product innovations and the range of products on the market, is increasing (Schleenbecker and Hamm, 2013). The new construct of Consumer Sustainability Consciousness enables an understanding of sustainable consumption products and consumer behaviours through an integrated Triple Bottom Line (TBL) perspective (Carvalho. et al., 2015). There are specific models of personalities of on-line consumes based on emotions, attitudes and perception that affect purchasing behaviour (Schröder et al., 2015). Consumer purchasing behaviour of minimally processed fresh fruit and vegetables has implications for marketing strategies (Stancu et al., 2016). Rödiger and Hamm, (2015) find that price affects consumer behaviour in their willingness-to-pay for organic food has mixed and contradictory results. The use of EU quality labels on food products is slowly but steadily affecting consumer purchasing decisions (Grunert and Aachmann, 2016). Suprem et al, 2013, find that the application of technology systems is an emerging area and plays an important role in the agrifood sector. As results based on previous researches about the characteristics and criteria of alternative agricultural distribution channels, it becomes obvious that there is a great interest for further studies regarding the attitude and behaviour of consumers towards these alternative channels of distribution. The objective of this research is to investigate consumer attitudes and preferences towards alternative distribution channels regarding agricultural products and especially, fresh fruits and vegetables. Thus this study contributes to the understanding consumer behaviour, highlighting the factors that affect the final purchase of agricultural products. This objective includes the main research on how willing consumers are to trust alternative ways of distribution. The research hypothesis constitutes a possible answer to a research question and it is determined after a review of a relevant literature, which leads the researcher to expect a specific relationship between variables (Syed, 2009). Based on the research objective, the following hypotheses are defined and examined: H1: There is a relationship between the use of alternative distribution channels for purchasing agrifood products and consumer’s socio-economic characteristics or consumer behaviour is affected by alternative channel structures (reveals from 2 and 3 section of questionnaire). H2: A key priority of agriculture and rural development is to strengthen both the means of distribution and the various processes and functions of the alternative distribution channels (reveals from 2 and 3 section of questionnaire). H3: There is growing interest in alternative food systems within the context of environmental and social sustainability (reveals from the first section of questionnaire). H4: The new construct of Consumer Sustainability Consciousness enables an understanding of sustainable consumption products and consumer behaviors through an integrated Triple Bottom Line (TBL) perspective (take into account the sustainability issue, the Social- environmental-economic perspective and reveals from 2 and 3 section of questionnaire).

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H5: Consumer purchasing behaviour is influenced by inter-personal suggestion (reveals from the first section of questionnaire). H6: The application of technology systems is an emerging area and plays an important role in the agrifood sector (reveals from the first section of questionnaire). H7: Consumer purchasing behaviour of minimally processed fresh fruit and vegetables has implications for marketing strategies (this reveals from the results from all the research and it is affairs of the study contribution).

METHODOLOGY The research took place in Thessaloniki during January to March 2016 using a random sampling approach and collecting 420 valid questionnaires. Descriptive statistics, cross-tabulation and Qualitative-Research (Q-R) hybrid methodology were applied in order to measure consumer behaviour towards alternative distribution channels of agricultural products. The present study illustrates that consumers are interested in alternative distribution channels and the supply of fresh fruits and vegetables. The results of the survey may offer constructive conclusions for policy makers, entrepreneurs, consumers and the academic sector. In particular, the present study concluded, that consumers trust alternative distribution channels for purchases of fresh fruit and vegetables, since they believe that these channels increase employability. The study concludes that there is space for further development and promotion of alternative distribution channels in the agricultural and food sector. In accordance with relative literature in the same cases due to investigate consumer behaviour use this methodology model (Kim and Lee, 2015). Especially, Q methodology has been applied to explore subjective perspectives in many research cases (Zanoli et al., 2015, Chapman et al., 2015, Kraak et al., 2014). For the analysis through SPSS tool, we could use frequency, cross-tabulation and concerning the core of Q–R hybrid methodology, Multivariate Analysis of Variance (MANOVA) (Chen et al., 2015). Especially, Q methodology includes a qualitative research and R methodology based on empirical approach, although this study will design a Q tool as a Q–R method that forms a link between qualitative and quantitative research. More specific, the aim of this study is to discover and interpret a systematic classification of customer types based on the subjectivity of Q theory in a qualitative approach. Following, the theoretical and conceptual interpretations are verified and generalized in sequence by combining the Q and R empirical methods. The results of this research can be applied in the investigation on consumer behavior towards alternative distribution channels of agricultural products (Kim and Lee, 2015). With this method we could explore local resident’s experiences and perceptions, could examine 42 statements concerning attitudes towards alternative distribution channels of agricultural product and mainly fresh fruits and vegetables. The Q method is a qualitative research approach based on process theory that examines human (consumers’) behavioral and motivational traits in the field of market research. It is a model based on subjectivity research that investigates human characteristics, such as feelings and emotions, preferences and choices, tastes and ideals. The individual ‘subjective’ experience each consumer has with the real- world functions within an “internal frame of reference”, forming the ‘schemata’ that appears in questionnaires with words and phrases such as ‘me’, ‘to me’ ‘in my opinion’, ‘in my view’, etc. (Kim and Lee, 2015). Q method is a new scientific approach in consumer behavior research that enables the formulation of hypotheses by focusing on discovery rather than preconceived concepts (Kim et al., 1993, Kim and

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Lee, 2015). In comparison to the R method, which is a simpler type of quantitative study, the Q method is far more complex. Variables in Q concern a person, not items as in R. The R method requires a relatively large sample size so as to estimate the population characteristics, whereas Q sampling is a much more intricate process. It involves the careful attention of the researcher in order to obtain every case of subjectivity that is expressed. Q method, which involves the study of human beings, compares the intraindividual differences of one stimulus rather than inter-individual ones (Kim and Lee, 2015).

Q-Methodology In order for methodology Q to be conducted, 42 statements based on recent bibliography were created, and they were printed in 42 numbered cards. Then, the participants were asked to read the statements in the cards and then divide them in 3 categories. In the first category, they put the statements they disagree with, in the second those statements which they had a neutral attitude towards and in the third category belonged the statements they agree with. Then, the participants were asked to categorize these 42 cards in the survey’s questionnaire, as it is shown in picture 1. Initially, two statements that the participants disagreed with were listed in position -4 (absolutely disagree), then three statements were listed in column -3 (strongly disagree), five statements were listed in column -2 (disagree), and seven statements in column -1 (moderately disagree). The same charting of statements was conducted for the statements, which the participants agreed with or they felt neutral about (Figure 1). In a few words, the participants were asked to list 42 statements in a questionnaire of 42 cells, where 17 statements were distributed in the 17 cells that expressed absolute disagreement till partial disagreement, 17 statements in the cells that expressed agreement, partially or absolutely, and eight statements in the column intended for neutral attitude, the process of filling out the questionnaire was approximately 60 minutes. Figure 1. The Q deck of Q methodology in which participants were asked to fill in 42 statements in 42 cells

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In total, 80 questionnaires were filled out by consumers which know about alternative distribution channels and the fruit and vegetables that are being distributed through them. Every completed questionnaire of qualitative survey represents the subjective opinions of every participant regarding alternative distribution channels, agricultural fruit and vegetables, agricultural products, supply chains and the effect of capital controls on the raw fruit and vegetable market. After the questionnaires had been filled out, the data were inserted in the PQMETHOD program, via which Factor analysis was conducted. Each factor represents the opinions of the participants. From the analysis above two factors have derived. In particular, in the first factor the statements which participants agreed with the most are presented in Table 1, while the statements which participants disagreed with the most are presented in Table 2.

Results In Table 1, it is evident that social media, act as a means of advertising which affect consumer attitude towards fruit and vegetable. It is also evident that how much customers trust the producers is very important. Plus, capital controls affect which alternative distribution system of raw fruit and vegetable consumers are going to choose. Then, in factor number, the interest of consumers in the further development of alternative distribution channels is evident, while they believe that farmers should be educated on new technologies, which will enforce the alternative distribution channels of agricultural products. From the statements that express disagreement, in factor 1, we can conclude that customer-centred approach in not an important factor in today’s market, while environmental conscience is absent from the

Table 1. Factor 1 – Statements, which customers mostly agreed with Statement

Rank

Social media affect the purchase of raw fruit and vegetable via alternative channels distribution.

+4

Trust towards raw fruit and vegetable producer is of crucial importance for choosing the alternative distribution channel

+4

Capital controls affect consumers’ preference, when they choose alternative distribution channels.

+3

I am interested in up-dating and modernizing of alternative distribution systems

+3

I believe that farmers should receive proper training on new technologies, so that distribution channels will be enhanced and developed.

+3

Table 2. Factor 1 – Statements that participants mostly disagree with Statement

Rank

Promoting a “green” purchasing behaviour of young people is a growing trend.

-4

There is a luck of structured approach regarding supply chains, which include their weaknesses and risks.

-4

Designing, organising, interactions, and possibilities as well as management of complicated supply chains have become important issues.

-3

In today’s market customer centred approach is important.

-3

Alternative distribution channels are affected by the supply feature in the chain and consumer behaviour is affected by the alternative structures in the channel.

-3

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purchasing behaviour of young consumers. Furthermore, one can observe that customers disagree with poorly structured supply chains, with the effect of supply chains on alternative distribution systems and on consumers’ attitude. Lastly, it derives that the design, structure and perspectives, as well as management of complicated supply chains are not important issues to the participants. In Tables 3 and 4 the statements of the second factor are presented (Factor2) which represent the strong agreement and strong disagreement of the participants. In particular, in Table 3 gender appears to affect very much the purchase of products, especially via internet, and it is also observed that customers become more and more familiar with the alternative distribution channels. Furthermore, the use of alternative distribution channels could possibly affect and change consumers’ way of living, while suggestions from one person to another on a personal level seem to affect purchasing behaviour. Therefore it is believed that the use of technology systems will greatly affect the agricultural and food sector. In Table 4, it is evident that statements which cause disagreement in Factor 1, are also included in Factor 2, in a different ranking position nonetheless. Results regarding “disagreement statements” enforce the consumers’ beliefs regarding “green” purchasing attitude of young people, supply chains, and the necessity of adopting a customer oriented approach in today’s market. Eleven statements derived from this survey which cause either agreement or disagreement in both factors, and they are presented in Table 5. It is believed that these statements represent the positive (or negative) attitude of consumers towards the sectors of alternative distribution channels and agricultural products. In particular, on a statistical level smaller than 0.01 (p-value> ... >>> Pr >>> ... >>> PR , which means that achievement of goals under the priority factor Pr is preferred most to the next priority factor Pr +1, r = 1, 2, ..., R − 1, where >>> stands for ‘much greater than’. Now, in actual practice, DM is confused in most of the times to assign proper priorities to goals with regard to their achievements. Therefore, sensitivity analysis of solutions with changes of priorities of model goals is made and Euclidean distance function is used to determine the optimal solution.

Use of Euclidean Distance Function for Priority Structure Selection Let, P be the total number of possible priority structures with regard to generation of different solutions. Then, let {x jp ; j = 1, 2,..., n } be the optimal solution obtained with the selection of p-th priority structure, p = 1, 2, ..., P . P

Consequently, the ideal solution can be recognized as {x ; j = 1, 2,..., n } , where x = max {x jp } , * j

* j

p =1

j=1,2,…,n. Using the Euclidean distance function, the distance of p-th solution from ideal point can be obtained as n

D ( p ) = [∑ (x j* − x jp )2 ]1/2 , j =1

(25)

where D ( p ) denotes distance function to measure distance between the solution achieved under p-th priority structure and ideal solution. Now, from the viewpoint of closeness of a solution to ideal point, the minimum distance always provides optimal decision.

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Let, D (t ) = min {D ( p ) ; p = 1, 2,..., P } ,

(26)

where, ‘min’ stands for minimum. Then, t-th priority structure is selected as appropriate one to obtain optimal solution in inexact environment. Now, it is to be noted that computational complexity arises for solving MODM problems with nonlinear objectives with the use of traditional approximation techniques, and solution of a problem often leads to a local optimum rather than global one. Further, computational load due to linearization (Pal et al., 2003) as well as approximation error frequently occurs for use of traditional optimization methods. To avoid the shortcomings, GA method (Michalewicz, 1996) is used to EGP model in (23) to obtain satisfactory solution.

GA SCHEME FOR EGP MODEL In GA (Holland, 1973; Goldberg, 1989), generation of new population is made by adopting the operators, selection, crossover and mutation. The real value coded chromosomes are considered here in the evolutionary process of solving the problem. The simple roulette-wheel selection (Deb, 2002), arithmetic crossover (Hasan, & Saleh, 2011) for exploration of the promising regions of search space and uniform mutation (Craenen, Eiben, & Marchiori, 2001) for exploitation of best candidate solution in the domain of interest are considered in the process of executing the problem. Now, the functions Z in (23) appears as evaluation function in the proposed genetic scheme. The evaluation function is expressed as:   K eval ( Ev )r = (Zv )r = ∑ wrk− drk−  , v = 1, 2 ,..., pop__size,   k =1 v

(27)

where, (Z v )r is actually renamed for Z in (23) to measure fitness value of v-th chromosome, when

evaluation for achievement goals at r-th priority level ( Pr ) is considered in execution process. The best value (Zk*) for fittest chromosome at a generation is determined as: Z k* = min {evel (Ev )k | v = 1, 2 ,..., pop_size}, k = 1, 2, ..., K

(28)

The execution of the problem step-by-step for achievement of model goals has been well presented in (Pal, & Chakraborty, 2013). Now, different types of decision variables and parameters involved in crop production planning are introduced below.

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DEFINITIONS OF VARIABLES AND PARAMETERS 1. Definition of Variables Two types of variables, decision variables associated with arable land utilization for cultivation of seasonal crops and constrained variables associated with irrigation water supply system, are involved with the problem. 1. Decision variables: x cs = Allocation of land for cultivation of crop c during season s,c = 1, 2, ...,C ; s = 1, 2, ..., S . 2.. Constrained variables: CWs = Supply of canal-water during season s, s = 1, 2, ..., S . GWs = Supply of groundwater during season s, s = 1, 2, ..., S .

2. Definition of Parameters Two types of parameters, farm input and output parameters, are involved with the problem. The input parameters are associated with utilization of farming resources, and output parameters are associated with crop production and revenue achievement decisions in an agricultural planning system. 1. Farm input Parameters: a. Interval Coefficient. [mhcsL , mhcsU ] = Interval of machine-hour (in hours (hrs)) requirement for tillage per hectare (ha) of land for cultivating crop c during season s. [mdcsL , mdcsU ] = Interval of manpower (in days) requirement for cultivation of crop c during season s.

U [ frcsfL , frcsf ] = Interval of fertilizer f ( f = 1, 2, ..., F ) utilization per ha of land for cultivating crop c dur-

ing season s. [PcsL , PcsU ] = Interval of production of crop c during season s. [AcsL , AcsU ] = Interval of cash requirement for purchase of various farming materials per ha of land for crop c cultivated during season s.

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b. Target Intervals. [DsL , DsU ] = Interval of arable land (in ha) utilization for cultivating the crops in season s. [MH L , MH U ] = Interval of total machine-hour (in hrs) required for all -seasons of a plan period. [MD L , MDU ] = Interval of total manpower (in days) required for all seasons of plan a period. [FRfL , FRUf ] = Interval of total amount of fertilizer f ( f = 1, 2, ..., F ) (in quintals (qtls)) required for yielding all the crops in a plan period. [CR L , CRU ] = Interval of budget allocation for purchase of different resources. [CW L , CW U ] = Interval of the supply of canal-water (in million cubic meters (MCM)) for cultivation in a plan period. [GW L , GW U ] = Interval of possible evacuation of groundwater (in MCM) for cultivation of all varieties of crops throughout the seasons in a plan period. c. Random coefficient: wucs = Estimated amount of water consumed (in cubic meter (CM)) per ha of land for cultivation of crop c during season s, s= 1,2,…,S. d. Probabilistic parameter: RWs = Expected amount of rainwater (in millimeter (mm)) precipitated during season s, s= 1,2,…,S. 2. Farm output parameters a. Interval coefficient [mpcsL , mpUcs ] = Interval of possible market price (Rupees/quintal (Rs./qtl)) of yielding crop c cultivated during season s, s= 1,2,…,S. b. Target intervals [APcL , APcU ] = Interval of annual production (in qtls) of all varieties of crop c cultivated during all seasons of a plan period.

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[MP L , MPU ] = Interval of market price of all the yielding crops cultivated in different seasons of a plan period. [FG L , FGU ] = Interval of annual production of all major food-grain crops cultivated during all seasons of a plan period. c. Farm output ratio interval L U [Ryzs , Ryzs ] = Interval of production ratio of y-th and z-th crops cultivated in season s

( y, z = 1, 2, ..., C ; y ≠ z ). Now, following the expressions in (1) and (2), the algebraic structures of interval goals of the problem can easily be obtained. Then, the associated planed-interval goals can be determined by the expressions in (11) and (13).

PLANED-INTERVAL GOALS The planed-interval goals are actually basic structural forms of objective goals to design the model of the problem. Planed-interval goals are discussed as follows. 1. Land utilization goal. The goals for utilization of total cultivable land for production of various seasons during a plan period take the form: C

∑x c =1

cs

= [DsL , DsU ],

s = 1, 2,..., S

(29)

2. Productive resource goals: 2. a. Machine-hour goal. Total machine hour within a specified interval need be provided to tillage land in different seasons. The goal appears as: S

C

∑∑ s =1 c =1

[mhcsL . x cs , mhcsU . xcs ] =

[MH L , MH U ]

(30)

2. b. Manpower requirement goal. Requirement of manpower within a specified interval must be considered for smooth functioning of various activities throughout a plan period. The planned interval goal takes the form:

751

 A Genetic Algorithm to Goal Programming Model for Crop Production

S

C

s=1

c =1

∑ ∑ [md

L cs

. xcs , mdcsU . xcs ] = [MD L , MDU ]

(31)

2. c. Fertilizer requirement goal. To maintain the fertility of soil, different types of fertilizers in essence are utilized to yield seasonal crops. The planned-interval goals for fertilizer requirement take the form: S

C

s =1

c =1

∑ ∑ [ fr

L csf

U . x cs , frcsf . x cs ] = [FRfL , FRUf ], f = 1, 2, ...., F

(32)

3. Budget allocation goal. An estimated budget for miscellaneous expenditure would have to be allocated for the purpose of purchase of seeds, fertilizers and other productive resources. The goal appears as: S

C

s =1

c =1

∑ ∑[ A

. x cs , AcsU . x cs ] = [CR L , CRU ]

L cs

(33)

4. Crop production goal. 4. a. Total seasonal crop production goal. To meet the demand of agricultural products in society, crop production within a specified interval is highly expected by farm manager. The goal expressions is stated as: S

∑ [P s =1

L cs

. xcs , PcsU . xcs ] = [Pc L , PcU ], c = 1, 2, ..., C

(34)

4. b. Major food-grain crop production goal. Some of the seasonal crops are taken in a group as main sources of major food-grains, where one of which can be consumed as an alternative to other ones in a same group to meet the need of main food products. Therefore, cultivation of major food-grain crops in different seasons would have to be considered as a convex combination of them in a plan period. The major food-grain crop production goal with target interval appears as: S

C1

S

∑ ∑ βg xgs [PgsL .xgs , PgsU .xgs ] = ∑ [FG L , FGU ], s =1 g =1

where,

g =1

C1

∑β g =1

g

= 1, 0 < βg < 1, and where g is used as a rename of the crop c to indicate its inclusion

in the set of major food-grain crops C1 (C1 < C).

752

(35)

 A Genetic Algorithm to Goal Programming Model for Crop Production

5. Crop production ratio goal. Since total arable land is limited, allocation of land (in ha) in certain seasons would have to be made in such a way that some principal crops could be yielded for civil utility purposes, beyond of satisficing different food-grain demands in society. In such a case, pairwise ratio of production of crops cultivated during a season can reasonably be taken into account in a crop production decision situation. The planned-interval goal expression in linear form appears as: S  S   ∑ P L x − RU PU .x , ∑ PU x − R L P L  yz zs zs ys ys yz zs   s =1 ys ys s =1     = 0, 0 , y, z ∈ {1, 2,...,C }; y ≠ z  

(

)

(

)

(36)

6. Annual profit goal. The annual profit depends upon market price of individual yield crops. Therefore, planned-interval goal is considered for profit achievement. The goal expression appears as: S

C

∑ ∑ [(P s =1

c =1

cs

L

mpcsL . xcs − AcsU . xcs ), (PcsUmpUcs . xcs − Acs L . xcs )] = [MP L , MPU ]

(37)

7. Water supply goals: a. Canal-water supply goal. The supply of canal-water from a River-barrage is the major source of irrigation water, which is inexact in nature owing to capacity limitation of barrage as well as constraints on the release of water up to a certain level to preserve ecosystem on earth. The planned-interval goal appears as: S

∑ CW s =1

s

= [CW L , CW U ]

(38)

b. Groundwater supply goal. Groundwater is always scarce in nature and abstraction of it cannot be made after a certain level to preserve biodiversity as well to make protection against water contamination with mixing of harmful minerals that lie in deep groundwater level. The planned- interval goal takes the form: S

∑ GW s=1

s

= [GW L , GW U ]

(39)

Now, the system constraints, which are inherently inflexible (rigid) in nature, are discussed in the following section.

753

 A Genetic Algorithm to Goal Programming Model for Crop Production

System Constraints Water Supply Constraints The adequate supply of water for cultivation is a major input in an agricultural production system. But, a water supply form reserve-water source is very limited owing to capacity limitations of them as well as to serve the other purposes in society including preservation of bio-diversity. The two types of water utilization constraints are discussed as follows. 1. Water utilization constraints The utilization of both the canal-water and groundwater need essentially be considered with great care, because they are always constrained for allocation to agricultural system. The water utilization constraints can be deterministically obtained as: S

CWs ≤ ys ∑ CWs ,

s = 1, 2,..., S ;

s =1

S

GWs ≤ z s ∑ GWs , s =1

s = 1, 2,..., S

(40)

where, ys and zs designate the percentages of utilizing the total allocation of canal-water and groundwater, respectively, to s-th cropping season of the plan period. 2. Total water utilization constraints. A large part of the total demand of irrigation water depends solely on seasonal rainfall, which is highly uncertain as a natural phenomenon. As a matter of fact, adequacy of supplying total irrigation water in a cropping season is always probabilistic. The seasonal water utilization constraints appear as: C

Pr [∑ wucs .x cs − (CWs + GWs ) ≤ RWs ] ≥ ps , s = 1, 2,..., S c =1

(41)

Now, executable EGP model of the problem is demonstrated through a case example.

CASE EXAMPLE The agricultural planning problem of Hooghly district in WB of the tropical country India is considered to demonstrate the proposed method. Hooghly district is typically known for its fertile soil to cultivate various season based principal crops throughout a planning year. Actually, the regional topography of Hooghly district is with average elevation of 19 meters from sea level and drained by the rivers, Hooghly river (i.e., the end part of Ganga river) and Damodar river. As such, it is an ideal landscape for agricultural industry in India.

754

 A Genetic Algorithm to Goal Programming Model for Crop Production

Location Map of Hooghly District is presented in Figure 1. The data were collected from various agricultural planning units: District Statistical Hand Book (2011), Economic Review (2011), Department of Agri-Irrigation of Hooghly District, Basak (2000). Three prominent cropping seasons: Summer, Rainy and Winter, successively appear in WB in a planning year, and the patterns of seasonal crops cultivated in the sequential seasons are Pre-kharif, Kharif and Rabi, respectively. The major crops are: Jute, a variety of Paddy, Groundnut, Wheat, Mustard, Potato and Sesame. Again, season based cultivation of crops are: Jute and Aus-paddy in Summer, Amanpaddy and Groundnut in Rainy, and Boro-paddy, Wheat, Mustard, Potato and Sesame in Winter. In model formulation, the seasons are sequentially denoted as: 1, 2, 3, and crops are successively numbered: 1, 2, 3, 4, 5, 6, 7 . Then, the decision variables to represent seasonal crops are defined as: (Jute, Aus-paddy, Aman-paddy, Groundnut, Boro-paddy, wheat, Mustard, Potato, Sesame) = (x 11, x 21, x 22 , x 32 , x 23 , x 43 , x 53 , x 63 , x 73 ). In sequel of model formulation, five years’ (2007-2011) rainfall data were taken into account to accommodate probabilistic constraints of the problem. The various types of data associated with objectives and constraints of the model are summarized in Table 1, Table 2, and Table 3, respectively. Now, following the expressions in (15)-(18), the model goals are constructed by using data presented in Table 1 and Table 3.

Construction of Model Goals 1. Land utilization goals: x 11 + x 21 + d1−L − d1+L = 198650, x 11 + x 21 + d1−U − d1+U = 228776; (Summer) x 22 + x 32 + d2−L − d2+L = 197550, x 22 + x 32 + d2−U − d2+U = 228776; (Rainy)

Figure 1. Location map of Hooghly district

755

 A Genetic Algorithm to Goal Programming Model for Crop Production

Table 1. Data description of target intervals of goals Goal

     Target Interval

1. Land Utilization (’000 ha):      (a) Pre-kharif

[198.650, 228.776]

     (b) Kharif

[197.550, 228.776]

     (c) Rabi

[197.950, 228.776]

2. Machine-hour requirement (in ’000 hrs):

[48650, 49776]

3. Manpower requirement (in ’000 man-days):

     [86395, 90177]

4. Fertilizer requirement (in metric ton):   (a) Nitrogen

     [35.00, 38.59]

  (b) Phosphate

     [19.80, 20.67]

  (c) Potash

     [15.00, 16.56]

5. Budget allocation (in Rs. Lac)

     [154550.30. 169784.54]

6. Crop production (in ’000 metric ton):      (a) Jute

     [45.06, 46.12]

     (b) Aus-paddy

[279.56, 300.25]

     (c) Aman-paddy

[715.33, 735.45]

(d) Groundnut

[23.72, 25.76]

     (e) Boro-paddy

[359.72, 372.67]

     (f) Wheat

[6.14, 6.94]

     (g)Mustard

[9.50, 10.17]

     (h) Potato

     [3218.73, 3247.50]

7. Total production (in ’000 metric ton) of major food-grain crops (Paddy and Wheat):

     [1356.814, 1377.140]

8. Annual profit (in Rs. Lac):

     [145175.80, 145326.70]

9. Production ratio (Jute and Aus-paddy):

     [1.20, 1.25]

10. Water supply (in MCM):      (a) Canal-water

[1555.5, 1635.37]

     (b) Groundwater

[1355.45, 1443.33]

Note: Rs. = Rupees in Indian currency.

Table 2. Data description of rainfall Year 2007

756

Rainfall (RWs) (in mm) Pre-Kharif

Kharif

Rabi

437

1264.11

58.8

2008

505.25

833.23

86.2

2009

273.94

855.67

25.4

2010

683.04

603.88

53.4

2011

375.75

930.34

44.4

 A Genetic Algorithm to Goal Programming Model for Crop Production

Table 3. Data description of interval coefficients and random coefficients

Crop

[mhcsL , mhcsU ]

U [ frcsfL , frcsf ]

[mdcsL , mdcsU ]

N

[PcsL , PcsU ]

[AcsL , AcsU ]

[mpcsL , mpUcs ]

wucs

P

K [2731, 2755]

[18655, 18845]

[870, 1050]

520

Jute

[198, 210]

[86, 94]

[45, 56]

[19, 22]

[18, 20]

Aus-paddy

[420, 430]

[57, 64]

[58, 63]

[26, 33]

[22, 28]

[4324, 4401]

[21050, 21350]

[925, 1150]

864

Amanpaddy

[200, 210]

[56, 63]

[75, 85]

[30, 34]

[30, 34]

[4323, 4365]

[22250, 22750]

[920, 1000]

1270

Groundnut

[102, 119]

[28, 31]

[48, 52]

[24, 30]

[18, 24]

[2198, 2236]

[19250, 19750]

[720, 800]

255

Boro-paddy

[805, 822]

[55, 65]

[145, 155]

[78, 82]

[78, 82]

[5115, 5148]

[36430, 36970]

[950, 1105]

1787

Wheat

[200, 210]

[36, 43]

[105, 115]

[52, 58]

[47, 53]

[2380, 2432]

[24965, 25035]

[1350, 1475]

382

Mustard

[98, 105]

[27, 34]

[75, 85]

[35, 45]

[25, 35]

[1025, 1078]

[18520, 18786]

[2965, 3065]

255

Potato

[332, 345]

[66, 74]

[260, 290]

[165, 190]

[165, 190]

[27490, 27537]

[59245, 61390]

[500, 600]

457

Sesame

[95,105]

[26, 34]

[45, 55]

[22, 28]

[12, 18]

[813, 835]

[14170, 14595]

[2920, 3160]

286

Note: N = Nitrogen, P = Phosphate, K = Potash.

x 23 + x 43 + x 53 + x 63 + x 73 + d3−L − d3+L = 197950, x 23 + x 43 + x 53 + x 63 + x 73 + d3−U − d3+U = 228776 (Winter)

(43)

2. Productive resource goals: a. Machine-hour requirement goals: 210x 11 + 430x 21 + 210x 22 + 119x 32 + 822x 23 + 210x 43 +105x 53 + 345x 63 + 105x 73 + d4−L − d4+L = 4865000,



198x 11 + 420x 21 + 200x 22 + 102x 32 + 805x 23 + 200x 43 + 98x 53 + 332x 63 + 95x 73 + d4−U − d4+U = 49776000



(44)

b. Man-power requirement goals 94x 11 + 64x 21 + 63x 22 + 31x 32 + 65x 23 +

757

 A Genetic Algorithm to Goal Programming Model for Crop Production

43x 43 + 34x 53 + 74x 63 + 34x 73 + d5−L − d5+L = 16395000, 86x 11 + 57x 21 + 56x 22 + 28x 32 + 55x 23 + 36x 43 + 27x 53 + 66x 63 + 26x 73 + d5−U − d5+U = 17177000



(45)

c. Fertilizer requirement goals: 56x 11 + 63x 21 + 85x 22 + 52x 32 + 155x 23 + 115x 43 + 85x 53 +290x 63 + 55x 73 + d6−L − d6+L = 35000000, 45x 11 + 58x 21 + 75x 22 + 48x 32 + 145x 23 + 105x 43 + 75x 53 +260x 63 + 45x 73 + d6−U − d6+U = 38590000 22x 11 + 33x 21 + 34x 22 + 30x 32 + 82x 23 + 58x 43 + 45x 53 + 190x 63 + 28x 73 + d7−L − d7+L = 19800000, 19x 11 + 26x 21 + 30x 22 + 24x 32 + 78x 23 + 52x 43 + 35x 53 + 165x 63 + 22x 73 + d7−U − d7+U = 20670000 20x 11 + 28x 21 + 34x 22 + 24x 32 + 82x 23 + 53x 43 + 35x 53 + 190x 63 + 18x 73 + d8−L − d8+L = 18000000, 18x 11 + 22x 21 + 30x 22 + 18x 32 + 78x 23 + 47x 53 + 25x 53 + 165x 63 + 12x 73 + d8−U − d8+U = 18980000



(Fertilizer N)



(Fertilizer P)



(Fertilizer K)

(46)

3. Budget allocation goals: 18.85x 11 + 21.35x 21 + 22.75x 22 + 19.75x 32 + 36.97x 23 + 25.04x 43 +18.79x 53 + 61.39x 63 + 14.59x 73 + d9−L − d9+L = 15455030, 18.66x 11 + 21.05x 21 + 22.25x 22 + 19.25x 32 + 36.43x 23 + 24.97x 43 +18.52x 53 + 59.25x 63 + 14.17x 73 + d9−U − d9+U = 16978454 4. Crop production goals a. Total seasonal crop production goals.

758





(47)

 A Genetic Algorithm to Goal Programming Model for Crop Production

2755x 11 + d10− L − d10+ L = 45060000, 2731x 11 + d10−U − d10+U = 46120000; (Jute) 4401x 21 + d11−L − d11+L = 279560000, 4324x 21 + d11−U − d11+U = 300250000; (Aus-paddy) 4365x 22 + d12− L − d12+ L = 710330000, 4323x 22 + d12−U − d12+U = 735450000; (Aman-paddy) 2236x 32 + d14− L − d14+ L = 23720000, 2198x 32 + d14−U − d14+U = 25760000; (Groundnut) 5148x 23 + d13− L − d13+ L = 357720000, 5115x 23 + d13−U − d13+U = 372670000; (Boro-paddy) 2432x 43 + d15− L − d15+ L = 6140000, 2380x 43 + d15−U − d15+U = 6940000; (Wheat) 1078x 53 + d16− L − d16+ L = 9500000, 1025x 53 + d16−U − d16+U = 10170000; (Mustard) 27537x 63 + d17− L − d17+ L = 3218730000, 27490x 63 + d17−U − d17+U = 32500000 (Potato)

(48)

b. Major food-grain crop production goals. The crops Paddy and Wheat are the major foodgrain sources across the countries. Therefore, a convex combination of annual production of Paddy and Wheat with certain target interval is considered to supply the demand of major food-grains. The model goals associated with the defined interval goals appear as: β2 (4.401.x 21 + 4.365.x 22 + 5.148x 23 ) + 2.432β4x 43 + d19− L − d19+ L = 1356.814, β2 (4.324.x 21 + 4.323.x 22 + 5.115x 23 ) + 2.380β4 .x 43 + d19−U − d19+U = 1377.140

(49)

5. Crop production ratio goals. In the crop production system, it is to be noted that Jute is a single season based crop and it is only used as raw material for textile product. Therefore, ratio of production of Pre-khariff crops, i.e., ratio of Jute and Aus-paddy would have to be maintained with a view to make adequate production of Jute depending on the needs in society. The model goals for the defined ratio appear as: − − − d21+L = 0, 2.755x 11 − 5.189x 21 + d21 − d21+U = 0 (Jute and Aus Paddy) 2.73x 11 − 5.501x 21 + d21 L U (50)

6. Annual profit goals: 10272.50x 11 + 29561.5x 21 + 21400x 22 + 8638x 32 + 20455.40x 23 + − 10970x 43 + 14520.70x 53 + 73832x 63 + 12216x 73 + d20 − d20+ L = 1451758000, L



759

 A Genetic Algorithm to Goal Programming Model for Crop Production

4914.7x 11 + 18647x 21 + 17021.60x 22 + 6075x 32 + 11525.50x 23 + − 7095x 43 + 11513x 53 + 48205x 63 + 9569x 73 + d20 − d20+U = 1453267000 U



(51)

7. Water supply goals: a. Canal-water supply goals 3

∑ CW s =1

s

− − + d22 + d22 = 1555.5, L L

3

∑ CW

s

s =1

− − + d22 + d22 = 1635.37 U U

(52)

b. Groundwater supply goals 3

∑ GW s =1

s

− − + d23 + d23 = 1355.45, L L

3

∑ GW

s

s =1

− − + d23 + d23 = 1443.33 U U

(53)

Now, the constraints in crop production system are discussed as follows.

Construction of Constraints Water Supply Constraints 1. Reserve-Water Utilization Constraints It is to be noted that the chance of regular rainfall is very low during Summer season, and cultivation mainly depends on supply of water from reserve-water sources. Again, although Rainy and Winter are the major cropping seasons, the chance of precipitation in rainy season is very high and water consumption in winter is lower than the other two seasons. As such, utilization of cannel-water and groundwater for production of Pre-khariff crops are considered 60% and 50%, respectively, of their total amounts earmarked for supply to agriculture sector all over the seasons of the plan period. Following the expression in (38), the affinity constraints can be presented as: 3

3

s =1

s =1

CW1 ≤ 0.60 ∑ CWs , GW1 ≤ 0.50 ∑ GWs

(54)

2. Total Water Utilization Constraints The optimal yields of all the seasonal crops depend on how the probability levels of total water utilization constraints are satisfied during the cropping seasons. The satisficing levels of probabilities in the three successive cropping seasons, Pre-kharif, Kharif and Rabi, are considered 0.90, 0.85 and 0.65, respectively, which are depended on the needs of watering during the respective seasons. Following the procedure and using the data in Table 2, the mean and variance pairs (E (RWs ), Var (RWs )), s = 1, 2, 3,

760

 A Genetic Algorithm to Goal Programming Model for Crop Production

associated with the successive seasons are obtained as (455.00, 18782.92), (897.45, 45514.89), (53.64, 393.94). Then, following the expression in (39), the deterministic equivalents of probabilistic constraints for three cropping seasons are obtained as: 5.02 x11 + 8.64x 21 − (CW1 + GW1 ) ≤ 331.65 (Summer) 12.70 x32 + 2.55x 42 − (CW2 + GW2 ) ≤ 715.66 (Rainy) 17.87x 53 + 3.82x 63 + 2.55x 73 + 4.57x 83 + 2.86x 93 − (CW3 + GW3 ) ≤ 40.10 (Winter)

(55)

Then, priority based EGP model can be constructed by using the expressions in (23) and (24). In the execution process, five priority factors P1, P2 , P3 , P4 and P5 are defined to include the model goals in (43)-(53). Three priority structures are considered to execute the problem under three successive Runs and then to perform sensitivity analysis on model solution. Now, the general executable EGP model is obtained as follows. Find {x 11, x 21, x 22 , x 32 , x 23 , x 43 , x 53 , x 63 , x 73 } so as to: Minimize Z p and satisfy the goal expressions in (43) - (53), subject to the constraints in (54) and (55) with 0 < β2 , β4 < 1, β2 + β4 = 1, and − + drkL + drkU −Vr ≤ 0, r ∈ {1, 2, 3, 4, 5}; k ∈ {1, 2,..., 24}

0 < λr < 1, r = 1, 2, 3, 4, 5.

(56)

where, β2 and β4 are associated with the goal expressions in (49). The three priority achievement functions Z p , p = 1, 2, 3 , defined for the three successive Runs are presented in Table 4. Now, for model simplification, λr = 0.5, ∀r , and β1 = β2 = 0.5 are taken into account for executions of problems under the three Runs, where equal weights are also given to goals included at the same priority level for achievement of their aspired levels. Then, in course of solving the problem in (56), evaluation of the function Z p ,(p = 1, 2, 3), is considered the fitness function in GA and execution is made step-by-step according to assigned priorities of model goals of the problem. Generation numbers = 300 is initially taken into account to conduct the experiment.

761

 A Genetic Algorithm to Goal Programming Model for Crop Production

Table 4. Priority achievement functions under the three Runs Run

Priority Achievement Function (Zp)

1

  20   16   − + − + λ P λ   , ( + ) + ( 1 − λ ) , ( d + d ) + ( 1 − λ ) V w d d V P w ∑ ∑  2kL 2kU 2 2  1k 1kL 1kU 1 1 2 2 2k  1  1       = = k k 10 18  22   3   − + − + P λ   w ( d + d w d d V ) + λ ( + ) + ( 1 − λ ) , ∑ ∑  3k 3kL 3kU 3 3k 3kL 3kU 3 3  3 3   k =21 Z1 =   k =1    − + − + P4 λ4 (w 49 (d49L + d49U ) + λ4w 4,17 (d4,17 L + d4,17U )) + (1 − λ4 )V4 ,      8   P λ ∑ w (d − + d + ) + (1 − λ )V   5k 5kL 5kU 5 5  5  5    k =4  

2

22   3   − + − + P λ   ( + ) + λ ( + ) + ( 1 − λ w d d w d d ) V , ∑ ∑  1 1 1k 1kL 1kU 1 1k 1kL 1kU  1  1    = = k k 1 21     16   20   − + − +     P2 λ2 ∑ w2k (d2kL + d2kU ) + (1 − λ2 )V2  , P3 λ3 ∑ w 3k (d3kL + d3kU ) + (1 − λ3 )V3  ,   k =18  Z 2 =   k =10   − + − + P4 λ4 (w 49 (d49L + d49U ) + λ4w 4,17 (d4,17 L + d4,17U )) + (1 − λ4 )V4 ,      8   P λ ∑ w (d − + d + ) + (1 − λ )V   5k 5kL 5kU 5 5  5  5    k =4  

3

  16   20   − + − + λ P λ   , ( + ) + ( 1 − λ ) , ( d + d ) + ( 1 − λ ) V w d d V P w ∑ ∑  2kL 2kU 2 2  1k 1kL 1kU 1 1 2 2 2k  1  1       = = k k 18 10    − + − + P3 λ3 (w 39 (d39L + d39U ) + λ3w 3,17 (d3,17 L + d3,17U )) + (1 − λ3 )V3 ,    22 Z3 =   3   − + − +  P λ ∑ w (d + d ) + λ ∑ w (d + d ) + (1 − λ )V  ,  4kU 4 4k 4 kL 4 kU 4 4  4  4 k =1 4k 4kL   k =21     8   P λ ∑ w (d − + d + ) + (1 − λ )V   5k 5kL 5kU 5 5  5  5    k =4  

(

(

(

The genetic parameter values are considered as: Probability of crossover pc = 0.8 Probability of mutation pm = 0.08 • •

762

Population size =100 Chromosome length =150.

)

)

)

 A Genetic Algorithm to Goal Programming Model for Crop Production

The GA is implemented using the GA-Toolbox under MATLAB Optimization Tool (MATLAB-Ver. R2010a) to execute the problem. The execution is performed in Intel Pentium IV with 2.66 GHz, Clockpulse and 4 GB RAM. The land utilization decisions under three Runs are displayed in Table 5. From the results displayed in Table 5, the ideal solution point, the elements of which correspond to the maximum of individual variable values achieved under the three Runs, is found as: (x 11, x 21, x 22 , x 32 , x 23 , x 43 , x 53 , x 63 , x 73 ) = (16.500, 62.621, 163.878, 11.179, 69.557, 2.936, 8.812, 116.911, 29.374). Then, the Euclidean distances of individual solutions of the successive three Runs from ideal solution are determined as: D (1) = 0.963,

D (3) = 0.961.

D (2) = 23.839,

The result shows that the minimum distance corresponds to D (3) = 0.961 . Thus, the priority structure under Run 3 is acceptable one for optimal land allocation decision in the farm management system. The resulting land allocation (in ’000 ha) decision is obtained as: (x 11, x 21, x 22 , x 32 , x 23 , x 43 , x 53 , x 63 , x 73 ) = (16.500, 62.621, 163.878, 10.608, 69.557, 2.935, 8.812, 116.911, 28.611). The production of crops (in ’000 metric ton) in interval forms are found as: Jute = [45.46, 45.95], Aus-paddy = [270.812, 275.453], Aman-paddy = [706.257, 715.027], Groundnut = [23.816, 24.719], Boro-paddy = [365.784, 378.079], Wheat = [6.985, 7.138], Mustard = [9.032, 9.500], Potato = [3211.883, 3219.378], Sesame = [23.219, 23.576]. Table 5. Land allocation decisions under the three Runs Land Allocation (’000 ha) Run

x 11

x 21

x 22

x 32

x 23

x 43

x 53

x 63

x 73

   1

16.500

62.621

163.878

10.608

69.557

2.936

8.812

116.818

28.611

   2

16.500

62.621

163.878

11.179

54.399

2.936

8.812

98.427

29.374

   3

16.500

62.621

163.878

10.608

69.557

2.936

8.812

116.911

28.611

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 A Genetic Algorithm to Goal Programming Model for Crop Production

Here, using the additive rule of interval arithmetic, the production of total Paddy in interval form is obtained as [1342.853, 1368.559]. In the context of above crop production achievements, it is to be noted that the utilization of canalwater and groundwater during all the seasons are 97.96% and 75.23%, respectively. The interval of profit achievement (in Rs. Lac) = [145115.331, 145338.432]. The result indicates that the obtained solution is most satisfactory for crop production decision in inexact environment. To illustrate more the effectiveness of the proposed method, the modelling aspect without considering any priority structure is considered.

EGP Model Without Priority Structure If priorities are not considered, the model would be the conventional EGP model proposed by Inuiguchi, & Kume (1991). Here, the executable model appears as follows. Find {x 11, x 21, x 22 , x 32 , x 23 , x 43 , x 53 , x 63 , x 73 } so as to: K

− + ) + (1 − λ)V } Minimize Z ′ = {λ ∑ wk (dkL + dkU k =1

and satisfy the goal expressions in (43) - (53), subject to the constraints in (54) and (55) with 0 < β2 , β4 < 1, β2 + β4 = 1, and − + dkL + dkU −V ≤ 0 , k=1, 2,…, K

(57)

K − + + dkU )] , where, V = [max (dkL k =1

Here, equal weights are also given to the model goals, that is, wk = 1/23, ∀k , and β1 = β2 = 0.5 are considered in the executable model of the problem. Then, the achieved land allocation (in ’000 ha) decision is (x 11, x 21, x 22 , x 32 , x 23 , x 43 , x 53 , x 63 , x 73 ) = (16.500, 62.621, 163.878, 10.608, 69.557, 2.936, 8.812, 116.911, 10.107) The production of crops (in ’000 metric ton) in interval form are obtained as: Jute = [45.46, 45.95], Aus-paddy = [270.812, 275.453], Aman-paddy = [706.257, 715.027],

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Groundnut = [23.816, 24.719], Boro-paddy = [365.784, 378.079], Wheat = [6.985, 7.138], Mustard = [9.032, 9.500], Potato = [3211.883, 3219.378], Sesame = [8.217, 8.492]. Here, the interval of total production of Paddy is found [1342.853, 1368.559]. The result shows that production achievement of Sesame is quite dissatisfactory in terms of the specified interval of demand, where the intervals for achievement of other crops are found acceptable with regard to meeting the need in society. Here, utilization of groundwater is found 8.32% more than that of the result obtained under the proposed method. The interval of profit achievement (in Rs. Lac) = [145101.023, 145237.453], which is an inferior one in contrast to the result achieved by employing the priority-based IVGP method. Therefore, it may be said that the EGP method is better than that of conventional IVGP method studied previously concerning achievement of pragmatic solution in inexact environment. However, to make a precise interpretation of using the proposed method, a performance comparison is made with possible crisp solutions of the results discussed under the above two approaches along with existing cropping plan of Hooghly district in the next section.

Illustration for Solution Comparison The crisp version of the solutions for crop production and profit achievement obtained under the different approaches are presented as follows. •

sing the midpoint arithmetic rule of interval analysis, the achievement levels of production (in U ’000 metric ton) of crops obtained under the proposed approach are as follows.

(Jute, paddy, Groundnut, Wheat, Mustard, Potato, Sesame) = (45.705, 1355.706, 24.267, 7.062, 9.266, 3215.604, 23.60). The achievement profit = Rs. 145226.283 Lac. •

I f the crisp definitions of model parameters are considered by using the midpoint arithmetic rule, then the production levels (in ’000 metric ton) of crops are found as:

(Jute, paddy, Groundnut, Wheat, Mustard, Potato, Sesame) = (45.705, 1355.706, 24.267, 7.062, 9.266, 3215.604, 8.354). The achievement of profit = Rs. 145169.238 Lac. •

I n a precise decision environment, the existing land utilization (in ’000 ha) decision for seasonal crops in the planning year (2011-2012) is

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 A Genetic Algorithm to Goal Programming Model for Crop Production

(Jute, paddy, Groundnut, Wheat, Mustard, Potato, Sesame) = (9.12, 203.42, 2.87, 1.96, 7.68, 72.45, 16.18). The crop production (in ’000 metric ton) decision is (Jute, paddy, Groundnut, Wheat, Mustard, Potato, Sesame) = (25.89, 879.24, 7.09, 3.42, 15.97, 1960.34, 15.56). The achieved profit = Rs. 98673.59 Lac. It may be mentioned here that the existing land allocation pattern for cropping plan is mostly adopted on the general prediction of demands of crops in society and not based on any planning model. Now, the graphical representations of the above crisply defined solutions against crop production decision are displayed in Figure 2. Similarly, the schematic presentations of crisply defined solutions against profit achievement decision are displayed in Figure 3. Figure 2. Comparison of crop production under the two approaches and existing plan

Figure 3. Comparison of profit achievement under the two approaches and existing plan

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The graphical comparisons indicate that the proposed approach is superior over other ones with regard to acceptable crop production decision. Remark 1: It may be mentioned that, if any change of decision with regard to resource utilization as well as crop production is needed there in inexact environment, then that can be considered in the model with possible changes of interval parameters as well rearrangement of priorities of model goals of the problem. Remark 2: With regard to implementation of the proposed model, the problem with involvement of computational load with rearrangement of priorities in different ways in solution search process may generally be raised in the context of management of farm. Because, if R be the total number of priorities, R! priority structures may have to be considered there to search optimal solution. But, it is worth mentioning here that at most ‘five’ priority levels are typically involved (Ignizio, 1976) and the conflict to assign priorities occurs up to ‘three’ priority levels in actual practice in a decision environment.

FUTURE RESEARCH DIRECTIONS In future study, the proposed approach can be extended to cropping plan for fuzzy description on bounds of interval data of model parameters with a view to further relaxation on resource utilization plan towards arriving at more effective crop production decision. Again, the possible extension of land under cultivation along with investment in rain-fed agriculture to improve environmental sustainability, agricultural waste-water management and other crop yielding criteria may be introduced in the model presented here, that are the emerging research problems with regard to take challenges for elimination of hunger and poverty in society. However, may be said that the study made in this chapter leads to open up new avenues to modeling agricultural problems in the current scenario of increasing demands of food grains in society.

CONCLUSION In this chapter, a GA based EGP formulation of agricultural problems with interval model data under a set of chance constraints is presented. The study provides a new way of modeling and solving farm management problems in uncertain environment. Further, other different types of parameters and environmental constraints can be accommodated in the proposed model to make cropping plan towards meeting the demand of various food products in modern society.

ACKNOWLEDGMENT The authors would like to thank the Editors, Handbook of Research on Natural Computing for Optimization Problems, and anonymous Reviewers for their valuable comments to improve the presentation of the chapter.

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Hasan, B. H. F., & Saleh, M. S. M. (2011). Evaluating the effectiveness of mutation operators on the behaviour of genetic algorithms applied to non-deterministic polynomial problems. Informatica, 35(4), 513–518. Heady, E. O. (1954). Simplified presentation and logical aspects of linear programming technique. Journal of Farm Economics, 36(5), 1035-1054. doi:.org/stable/1234313 Holland, J.H. (1973). Genetic algorithms and optimal allocation of trials. SIAM Journal of Computing, 2(2), 88-105. doi:10.1137/0202009 Hulsurkar, S., Biswal, M. P., & Sinha, S. B. (1997). Fuzzy programming approach to multi-objective stochastic linear programming problems. Fuzzy Sets and Systems, 88(3), 173–181. doi:10.1016/S01650114(96)00056-5 Ida, M. (2000). Interval multiobjective programming and mobile robot path planning. In New Frontiers in Computational Intelligence and its Applications. IOS Press. Ida, M. (2003). Portfolio selection problem interval coefficients. Applied Mathematics Letters, 16(5), 709–713. doi:10.1016/S0893-9659(03)00071-5 Ignizio, J. P. (1976). Goal programming and extensions. Lexington Books. Ignizio, J. P. (1982). Linear programming in single- and multiple-objective systems. Englewood Cliffs, NJ: Prentice-Hall. Inuiguchi, M., & Kume, Y. (1991). Goal programming problems with interval coefficients and target intervals. European Journal of Operational Research, 52(3), 345–360. doi:10.1016/0377-2217(91)90169-V Israel, B. A., & Robers, P. D. (1970). A decomposition method for interval linear programming. Management Science, 16(5), 374–387. doi:10.1287/mnsc.16.5.374 Jiang, C., Han, X., Liu, G. R., & Liu, G. P. (2008). A nonlinear interval number programming method for uncertain optimization problems. European Journal of Operational Research, 188(1), 1–13. doi:10.1016/j. ejor.2007.03.031 Kall, P., & Wallace, S. W. (1994). Stochastic programming. Chichester, UK: John Wiley. Liu, B. (2003). Theory and practice of uncertain programming. Heidelberg, Germany: Physica-Verlag. Mazoyer, M., & Roudart, L. (2006). A history of World agriculture: From the Neolithic age to the current crisis. New York: New York University Press. Michalewicz, Z. (1996). Genetic Algorithms + Data Structures = Evolution Programs (3rd ed.). Berlin: Spriger-Verlag. doi:10.1007/978-3-662-03315-9 Molden, D. (Ed.). (2007). Water for Food, Water for Life: A Comprehensive Assessment of Water Management in Agriculture. London, UK: Earthscan. Moore, R. E. (1966). Interval analysis. Prentice-Hall. Moore, R. E. (1979). Methods and applications of interval analysis. Philadelphia: SIAM. doi:10.1137/1.9781611970906

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Nix, J. S. (1979). Farm management, the state of the art (or science). Journal of Agricultural Economics, 30(3), 277–292. doi:10.1111/j.1477-9552.1979.tb02143.x Norton, R. D., & Schiefer, G. W. (1980). Agricultural sector programming models: A review. European Review of Agriculture Economics, 7(3), 229–264. doi:10.1093/erae/7.3.229 Ogryczak, W. (1997). Preemptive reference point method. In J. Climacao (Ed.), Multicriteria Analysis (pp. 156–157). New York: Spinger-verlag. doi:10.1007/978-3-642-60667-0_16 Olivera, C., & Antunes, C. H. (2007). Multiple objective linear programming models with interval coefficients –an illustrated overview. European Journal of Operational Research, 181(3), 1434–1463. doi:10.1016/j.ejor.2005.12.042 Pal, B. B., & Chakraborti, D. (2013). Using genetic algorithm for solving quadratic bilevel programming problems via fuzzy goal programming. International Journal of Applied Management Science, 5(2), 172–195. doi:10.1504/IJAMS.2013.053690 Pal, B. B., Chakraborti D., & Biswas, P., 2009. A genetic algorithm based hybrid goal programming approach to land allocation problem for optimal cropping plan in agricultural system. IEEE Xplore Digital Library, 181-186. doi:10.1109/ ICIINFS.2009.5429867 Pal, B. B., Gupta, S., & Chakraborti, D. (2010). A genetic algorithm based stochastic simulation approach to chance constrained interval valued multiobjective decision making problems. IEEE Xplore Digital Library, 1-7. doi:10.1109/ICCCNT.2010.5591826 Pal, B. B., & Kumar, M. (2013). Interval goal programming for economic - environmental Power generation-dispatch problems. IEEE Xplore Digital Library, 1-8. doi:10.1109/FUZZ-IEEE.2013.6622446 Pal, B. B., Kumar, M., & Sen S. (2012). Management decision making for proper academic personnel planning in university system - an intervalvalued goal programming approach. International Journal of Applied Management Science, 4(3), 284-310. doi:.2012.047678 doi:10.1504/IJAMS Pal, B. B., & Moitra, B. N. (2003). A goal programming procedure for solving problems with multiple fuzzy goals using dynamic programming. European Journal of Operational Research, 144(3), 480–491. doi:10.1016/S0377-2217(01)00384-8 Ravindran, A., Ragsdell, K. M., & Reklaitis, G. V. (2007). Linear Programming Engineering optimization: method and applications (2nd ed.). Academic Press. Review, E. (2012). Department of Bureau of Applied Economics and Statistic. Govt. of West Bengal. Romero, C. (1991). Handbook of critical Issues in goal programming. Oxford, UK: Pergamon Press. Romero, C. (2004). A general structure of achievement functions for goal programming model. European Journal of Operational Research, 153(3), 675–686. doi:10.1016/S0377-2217(02)00793-2 Sahinidis, N. V. (2004). Optimization under uncertainty: state-of- the- art and opportunities. Computers and Chemical Engineering, 28(6-7), 971-983. doi:.09.017 doi:10.1016/j.compchemeng.2003 Simon, H. A. (1945). Administrative behaviour. New York: The Free Press.

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Slowinski, R. (1986). A multicriteria fuzzy linear programming method for water supply system development planning. Fuzzy Sets and Systems, 19(3), 217–237. doi:10.1016/0165-0114(86)90052-7 Slowinski, R., Urbaniak, A., & Weglarz, J. (1983). Bicriterion capacity expansion planning of a water supply system. Mathematics of Operations Research, 46, 733–744. Taguchi, T., Ida, K., & Gen, M. (1998). A Genetic Algorithm for Optimal Flow Assignment in Computer Network. Computers & Industrial Engineering, 35(3-4), 535–538. doi:10.1016/S0360-8352(98)00152-1 Wheeler, B. M., & Russell, J. R. M. (1977). Goal programming and agricultural planning. Operational Research Quarterly, 28(1), 21-32. doi: jstor.org/stable/3008887 Yeh, W. W. G. (1985). Reservoir management and operations models: a state-of-the-art review. Water Resources Research, 21(12), 1797-1818. doi: 021i012p01797 doi:10.1029/WR Yu, P. L. (1973). A class of solutions for group decision problems. Management Science, 19(8), 936–946. doi:10.1287/mnsc.19.8.936 Zadeh, L. A. (1965). Fuzzy Sets. Information and Control, 8(3), 338–353. doi:10.1016/S00199958(65)90241-X Zimmermann, H.-J. (1987). Fuzzy Sets, Decision Making and Expert Systems. Boston: Kluwer Academic. doi:10.1007/978-94-009-3249-4

ADDITIONAL READING Askew, A. J. (1974). Chance-constrained dynamic programming and the optimization of water resource systems. Water Resources Research, 10(6), 1099-1106. doi: p01099 doi:10.1029/WR010i006 Cullather, N. (2010). The hungry world: America’s cold war battle against poverty in Asia. America. Harvard University Press. Pal, B. B., & Basu, I. (1996). Selection of appropriate priority structure for optimal land allocation in agricultural planning through goal programming. Indian Journal of Agricultural Economics, 51, 342–354. Pal, B. B., & Kumar, M. (2013). Interval goal Programming for economic - environmental power generation-dispatch problems. IEEE Xplore Digital Library,1-8. doi:10.1109/FUZZ-IEEE.2013.6622446

KEY TERMS AND DEFINITIONS Farm Planning: Proper allocation of cultivable land for optimal production of several seasonal crops by utilizing different productive resources. Fractional Programming: Special field of study in the area of mathematical programming, where certain objective functions appear in the form of ratios for optimizing them in the decision environment. Genetic Algorithm: Genetic algorithm is an adaptive heuristic search algorithm based on the evolutionary ideas of natural selection and genetics in living system.

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Goal Programming: Goal programming is a goal-oriented optimization technique to solve decision problems with multiplicity of objectives in crisp environment. Interval Programming: Interval programming is the modelling aspects of optimization problems in which model parameters are defined in the form of bounded intervals. Stochastic Programming: Stochastic programming is an optimization technique for solving problems with probabilistically defined data in uncertain environment.

This research was previously published in the Handbook of Research on Natural Computing for Optimization Problems edited by Jyotsna Kumar Mandal, Somnath Mukhopadhyay, and Tandra Pal , pages 30-65, copyright year 2016 by Information Science Reference (an imprint of IGI Global).

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Chapter 34

Mobile Vision for Plant Biometric System Shitala Prasad GREYC – Imaging Lab, CNRS, France

ABSTRACT In human’s life plant plays an important part to balance the nature and supply food-&-medicine. The traditional manual plant species identification method is tedious and time-consuming process and requires expert knowledge. The rapid developments of mobile and ubiquitous computing make automated plant biometric system really feasible and accessible for anyone-anywhere-anytime. More and more research are ongoing to make it a more realistic tool for common man to access the agro-information by just a click. Based on this, the chapter highlights the significant growth of plant identification and leaf disease recognition over past few years. A wide range of research analysis is shown in this chapter in this context. Finally, the chapter showed the future scope and applications of AaaS and similar systems in agro-field.

INTRODUCTION1 At the beginning of this century, there was a tremendous technological revolution in the field of wireless communication and mobile technology. Mobile and ubiquitous computers are increasing their magnitude in every small, portable, wireless computing and communication fields. The technological omnipresence of ubiquitous devices invisibly activates the world by providing accessibility anywhere-anytime computing. However, this revolution is still slow in the agricultural sphere, despite the advancements in technologies making it possible to build and deploy wireless sensor networks (WSN) in fields that would radically improves the farming efficiencies. This is because the current wireless technologies are too expensive and complicated for farmers to use especially in the developing countries like India. Twoway radios have long been used by farmers in many such developed countries with large farmlands to contact their employees, farm suppliers, equipment dealers, agents, buyers and farm awareness. Today, world-wide availability of smartphones and cellular networks, the use of mobile phones in agricultural sector is popularly, replacing the use of two-way radios (Wang, Li, Zhu, & Xu, 2016). The advantage of using two-way radios and mobile phones is that these wireless tools are relatively cheap and very simple DOI: 10.4018/978-1-5225-9621-9.ch034

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 Mobile Vision for Plant Biometric System

to use. Additionally, smartphones have several important advantages such as all the brands of mobile phones are generally compatible for running various types of application software, and are equipped with Wi-Fi, Bluetooth, camera(s) and GPS capabilities. In Asia-Pacific region, India has outscored the other nations in terms of the number of mobile users. With such rapidly increasing tele-density, mobile penetration in rural areas is also growing strongly. These days, mobile phones are available to people even in rural India, especially among the agrarian community. Motivated by the advancement in mobile technology and the wide-spread use of phones in India, as discussed above, researchers are aiming to help the illiterate agrarian community to improve their agricultural activities through the use of mobile phones. Thus, a new agro-information technology needs to be introduced in order to bridge the gaps between the real and digital objects via mobile computing (MC) and augmented reality (AR).

Agricultural Scenario In developing countries, agriculture accounts the major role of rural employment and holds the promise for socio-economic growth. In fact, agro-community is roughly five-times more effective in raising the income of poor farmers compared to any other sector. Agricultural improvement also directly impacts on the hunger and malnutrition and thus plays a significant role in decreasing the occurrences of famine. However, the growing global population has heightened the demand for foods. Due to the lack of infrastructure in rural areas, raising the food prices and the climatic change and the real effective and “smart” agriculture is essential. Together with geographic information systems (GIS) and virtual reality (VR) smartphones can play an important role in precision agriculture environment (Bakhsh, Colvin, Jaynes, Kanwar, & Tim, 2000; Jain, Tim, & Jolly, 1995; Tim, 1995). Some of the uses of on-farm wireless network technologies in improving the agricultural productions are discussed in (Vellidis et al. 2007; Izzat, Ismail, Mehat, & Haroon, 2009; Revenaz, Ruggeri, & Martelli, 2010).

Mobile-Based Agriculture Information and Communication Technology (ICT), particularly mobile technologies, are often seen as the ’game changer’ in agro-community. The already existing m-Agricultural information system provides a giant leap in agriculture that offers a plethora of services, serving as a tool for information dissemination (Brugger, 2011). Various mobile-based services such as Internet-based, SMS-based information services (Gore, Lobo, & Doke, 2012), voice-based agro-advisory services like mKRISHI -(Shinde et al. 2014), and videos over mobile networks (Pande, Jagyasi, & Choudhuri, 2009) are utilized for transferring general knowledge about the farming techniques and trends, information of the plants and their varieties regarding how to keep them disease free. The general awareness in India by using m-Agriculture techniques since last decade are listed in Figure 1. But due to the limited and disconnected services they did not server the real needy. Specifically, m-Agriculture refers to the delivery of agriculture-related services via mobile communication technology (Brugger, 2011). In order to make decisions on agricultural measures, it provides an individual decision support systems and services. These decision are based on the local contextual information, i.e., delivering location-specific information like climatic patterns, soil and water conditions. Here, m-Agricultural termed to involve gathering of related information through mobile technologies like automated weather stations or sensors used in mobile. Thus, m-Agriculture involves a two-way advisory

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Figure 1. Mobile-based ICT agro-services launched in India

systems that provides individual feedbacks and advices like remote diagnosis of diseases by experts using some fertilizers/chemicals. These advisory systems typically include smartphones and intermediaries for wireless communication with the farmers and require remote sensing instruments like GIS. m-Agriculture projects are built on the opportunities to increase the use of mobile/ubiquitous devices by farmers in the developing countries. Therefore, the primary objective of this chapter is to project such mobile-based vision systems for plant species identification and disease diagnosis using plant leaf imaging. Why an agro-vision system? Because famers or the other illiterate (non-botanical) person may not be able to explain the exact visual symptoms occurred on the crop to the expert to get a proper solution for the problem(s).

Motivation The biodiversity is rapidly disappearing and we are losing the opportunities to know and understand the complexity of our mother-nature. Smart technologies are indispensable in order to rapidly identify the species and access the biodiversity information. If possible, it also develops the eco-informatics expert systems. Thus, mobile-based automated plant biometric system to automatically segment leaf from a complex background, followed by leaf analysis to identify the plant species, and diagnose the diseases on the leaf, is a need. Currently, there are several plant classification methods such as plant genetics method, cytotaxonomy method and chemotaxonomy method. Plant species classification is not only botanic, but also is the foundation of ecology, medicine and life science (Wang, Li, Zhu, & Xu, 2016). According to a survey conducted in 2003, botanists claimed that to identify more than 3,15,000 plant species the key features used are fruits, flowers, stems, roots and leaves (Scotland & Wortley, 2003). Different types of plant leaves are shown in Figure 2. However, fruits and flowers are seasonal and may not be available throughout a year for identification purpose, while roots and stems are difficult to analyze. This is not the case with a plant leaf. It is available throughout the year and can easily be photographed; containing

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Figure 2. The common shapes of simple leaves (Plant Glossary, 2009)

sufficient information for species analysis. As a result, majority of the existing techniques are based on plant leaf features such as leaf shape, leaf margin, leaf vein and leaf texture (Cope, Corney, Clark, Remagnino, & Wilkin, 2012). Some of the basic plant leaf shapes with their venation details are shown in Figure 2. These features are well explanatory in real world but for virtual or digital world they are mathematically represented using various transforms in both spatial and frequency domain (Cope et al., 2012). In this chapter, both spatial and frequency domain representations of plant leaf features are highlighted for further analysis (specie or disease recognition).

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The chapter, especially focus on the novel techniques used for plant identification and disease diagnosis. The graphical abstract of the proposed system is shown in Figure 3 where the crop leaf (object) is photographed via mobile/ubiquitous device, and subsequently represented mathematically in feature space which is then projected for classification using an optimal classifier. The next few sections describe the existing automated plant biometric systems and their limits with their comparison and results.

BACKGROUND As discussed, the manual monitoring and experimenting involves human expertise which is a tedious, time consuming, brittle and frustrating practice. Users need to traverse a decision tree manually to make a decision related to species, as shown in Figure 4(a). Botanists collect the specimens and preserve them in herbaria like Royal Botanical Gardens, Kew in London2 (Kumar et al. 2012), as shown in Figure 4(b). The herbarium can be seen as a major collection of experts’ knowledge in form of a structured repository and thus, to facilitate the access they are being digitized with images of species, dates, locations and so on. In computer vision (CV) and pattern recognition (PR), feature representation and feature selection are the most important aspect of research since many decades. Various image processing and machine learning algorithms such as neural network (NN), support vector machine (SVM), and k-nearest neighbor (k-NN)

Figure 3. The graphical abstract of the proposed system

Figure 4. (a) Hierarchy of biodiversity classification and (b) bio-specimens herbaria

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are used in different domains like medical imaging (Orr, Peersson, Marquand, Sartori, & Mechelli, 2012), surveillance (Pogorelc, Bosni, & Gams, 2012), object recognition, species identification (Kumar et al. 2012) and designing automated defence systems (Heinze, Goss, & Pearce, 1999). The development and ubiquity of technologies like mobile cameras and mobile processors in related fields have brought such ideas close to the reality (MacLeod, Benfield, & Culverhouse, 2010). Therefore, various CV systems have been proposed for plant identification using their fruits, flowers or leaves3, especially morphological studies, e.g., Tilia (Schneider, 1912), Ulmus (Melville, 1937), Betula (Natho, 1959) and many more. There are many aspects of plants that are used by botanists in identification such as the 2-dimensional outlines of leaf, veins of leaf, margin of leaf and texture of leaf. Among these, leaf shape information is the mostly exposed and popular method among CV researchers. The two well know mobile applications launched in market for species identification are LeafSnap and Leafview. Both uses the leaf shape information for plant leaf identification via iPhone, as shown in Figure 5(a-b). LeafZone4 (Figure 5c) is another app that not only identifies the plant species but also provides information about the effect of ozone on them making it more exciting for people to know their nature.

Leaf-Shape-Based Identification Leaf shape has the maximum discriminative power among all the other parts of a plant. At the same time, leaves of the same plant may have different shapes and size. Over it, leaves of different species may have similar characteristic shape. As discussed above, the existing algorithms used to extract shape 3 are Fourier analysis (McLellan & Endler, 1998), information in the frequency domain from a leaf I leaf elliptic Fourier descriptors (EFDs) (Neto, Meyer, Jones, & Samal, 2006) and Fourier harmonics (Hearn, 2009). Following this, Principal Component Analysis (PCA) was also applied to reduce the dimensionality of the feature-space for efficient classification. The advantage of using such methods is that the shape can be reconstructed from its descriptors and are rotation invariant. Recently, EFDs was also used by different authors for leaf shape analysis (Andrade, Mayo, Kirkup, & Van-Den-Berg, 2008; Lexer et al. 2009; Neto et al. 2006). Next, a number of approach uses contour signatures for leaf shape classificaFigure 5. (a) LeafSnap, (b) LeafView, and (c) Leafzone are the popular electronic plant information systems

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tion such as the morphological description (Cope et al. 2012) and the centroid-contour distance (CCD) (Wang, Chi, & Feng, 2003). CCD is a sequence of distances between the center pixel to the contour of the object and hence, suffers from orientation problem. The other signatures include centroid-angle and tangents of the leaf outline. Meade and Parnell (2003) and Wang, Chi, and Feng (2003) attempted to increase the CCD accuracy when applied on leaf shape identification. A new time-series shapelets approach to calculate local features was proposed by Ye and Keogh (2009) and Prasad, Kumar, and Ghosh (2016). But a major difficulty with these contour based signatures is that they are sensitive to self-intersection which occurs quite often with multiple lobe leaves and in compound leaves. Prasad, Kumar, and Ghosh (2016) overcomes with this limitation to some extent. Another common approach for shape extraction is the use of movement invariant (MI) features (Zulkifli, Saad, & Mohtar, 2011), region-based features (Lee & Chen, 2006), and others. Warren (1997) proposed an automated system to recognize plant genus “Chrysanthemum” with thirty species. In Warren (1997), three basic mathematical descriptors such as the shape, color and size of leaf, flower and petal were used to identify the species. Similarly, authors (White, Marino, & Feiner, 2006 & 2007; White, Feiner, & Kopylec, 2007), used a morphological descriptor for shape information extraction from a complete leaf image. They designed a mobile vision Tablet-PC-based electronic field guide to identify plant leaves for the use of botanists and others to make their work much easier. Since LeafSnap is designed for iOS, Zhao et al. (2015), proposed ApLeaf, an Android based replica of LeafSnap with few pros-and-cons. Thus, Multiscale-ARCH-height (MARCH) a shape-based algorithm for mobile devices to retrieve plant leaf image was introduced in Wang, Brown, Gao, and Salle (2015). In Prasad, Kumar, and Ghosh (2013b), the authors proposed a mobile plant identification system with a statistical leaf shape information. Here, they used the reduced shape and color mean information where the leaf image was down sampled to an acceptable and feasible limit which is optimal for mobilelevel computing. The first step in this was to capture an isolated constant background plant leaf image 3 using mobile camera. The pre-processing step is minimal or negligible due to the above pre-segI leaf mented input leaf. The shape and color features are extracted and used for classification after limiting 3 I leaf to a fixed window size to make the approach translation and scale invariant. Since shape or color cannot be used individually for a reliable leaf classification, as they may vary with different conditions and locations, researchers applied a decision level fusion to avoid such problem(s). The first level decision is based on shape information which is subsequently verified in the second level using color features (Prasad, Kumar, & Ghosh, 2013b). For the purpose of shape feature extraction, geometric features (elongation, roundness, circularity and porosity) and polar Fourier transform features were used. On the other hand, for color features, the mean, standard deviation, skewness and kurtosis were derived (Prasad, Kumar, & Ghosh, 2013b). To test the functionality two different datasets were used: Flavia dataset5 and a set of hundred plant species dataset (Wu et al. 2007) with an accuracy of 91.34% and 76.21%, respectively. Other than this, few other authors have used some very specific leaf features to identify plant species, such as the leaf lobedness (Pauwels, Zeeuw, & Ranguelova, 2009) and fractal combined with Linear Discriminant Analysis (LDA) (Bruno, deOliveira Plotze, Falvo, & deCastro, 2008). It is found that fractal features are significant only if used with the combination of other features. In 2006, Du, Huang, Wang, and Gu proposed a polygonal representation of plant leaves for comparison limiting the method to a more generic tasks.

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Leaf Veins and Margin-Based Identification The second commonly used leaf information is its vein pattern. The common leaf vein structure are shown in Figure 2. The veins provides structure to a leaf and thus, the vein pattern of a leaf can serve as a measure for its identification. The algorithms proposed in these are Independent Component Analysis (ICA) (Li, Chi, & Feng, 2006) and Artificial Ant Swarm Intelligence (AASI) (Mullen, Monekosso, Barman, Remagnino, & Wilkin, 2008) to extract leaf edge and leaf vein patterns for species recognition. Cope, Remagnino, Barman, and Wilkin (2010) used Genetic Algorithm (GA) to identify vein pixels and non-vein pixels. Whereas, vein extraction is best achieved by using threshold and neural network approach, as claimed by Fu and Chi (2006). Some other similar methods are discussed by Nam, Hwang, and Kim (2008) and Park, Hwang, and Nam (2008). The third information used to classify a plant species is by its leaf margin. However, it is not a perfect feature and, therefore, generally used only in combination with other features. The leaf margin often consists of teeth pattern, as shown in Figure 1, which offers a small contribution in automated plant species recognition. Clark (2004) used multi-layer perceptron for identifying species and in Clark (2009), he used a hair descriptor as one of the features in self-organizing map (SOM) for Tilia classification. Rumpunen and Bartish (2002) used a manual measure to calculate the angle and length of the leaf tooth. If undamaged leaves are available, then leaf margin may be a good option for the purpose. On the other hand, leaf vein combined with leaf margin may perform well in damaged leaf cases. But for taxa that do not have teeth, it may fail.

Leaf-Texture-Based Identification Last but the most important information of a plant leaf is its texture and so many novel techniques have been proposed using it. The size and color of plant leaf varies arbitrarily and even in a single plant two leaves may have different sizes. Thus, the algorithm needs to be translation, scale and rotational invariant, as in case of Curvelet transform (CT) (Prasad, Kumar, & Tripathi, 2011). Image texture quantifies the perceived texture of an image and can be calculated using either structural approach or statistical approach. Backes, Gonalves, Martinez, and Bruno (2010) proposed multi-scale fractal approach to represent the texture of leaf and used neural network for classification. Other methods based on Gabor transform (GT) (Casanova, de Mesquita, & Brun, 2009; Cope et al. 2010, 2012), wavelet transform (Liu et al., 2009) and Relative sub-Image Coefficient (RSC) feature (Prasad, Kundiri, & Tripathi, 2011a) were proposed to extract leaf texture for species recognition. In 2014, Yanikoglu, Aptoula, and Tirkaz used shape-texture-color features to identify plant species from photographed images with a maximum accuracy of 81% in various lighting, poses, and orientation conditions. Finally, each method has its own pros and cons. It is conjectured that texture combined with contour-based shape analysis may be the best solution in the present context. The plant biometric also entered into the deep learning and come up with several convolutional approaches for plant leaf species classification (Lee, Chan, Wilkin, & Remagnino, 2015; Sünderhauf, McCool, Upcroft, & Perez, 2014; Reyes, Caicedo, & Camargo, 2015; Jassmann, 2015).

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Based on Flowers and Other Parts of Plants In the literature, there is a dearth of research done on leaf lamina feature extraction using wavelet and Gaussian interpolation (Gu, Du, & Wang, 2005). To other extent, 3D image processing has also been proposed for leaf feature extraction (Ma et al. 2008). They combined 2D leaf images to extract 3D leaf structure and together with 2D and 3D information, leaf boundary segmentation is achieved by applying normalized-cuts. They applied CCD for classifying leaf into palmate and cordate. Similarly, Teng, Kuo, and Chen (2009) used stereo imaging and stereo matching for the same purpose. A number of approaches have also been proposed that use flower as a key to identify plant6. In case of flower, color is the most common and significant feature. Nilsback & Zisserman, (2010) combined petal shape and color information to design flower segmentation algorithm. Hong, Gang, Jun-li, Chi, and Zhang (2004) used the same color-histogram with CCD and angle-code histogram to classify a set of fourteen species. Yoshioka, Iwata, Ohsawa, and Ninomiya (2004) used Elliptic Fourier Analysis (EFA) for shape analysis of petals in case of Primula sieboldii while Gage and Wilkin (2008) used EFA for outline analysis of tepals (such as petals and sepals) of three species of Sternbergia to validate whether they actually have distinct morphology. Huang, Huang, Du, Quan, and Gua (2006) used Gabor transform (GT) and radial Probabilistic Neural Network (PNN) for bark texture analysis. Lastly, few of the researchers used digital imaging on plant root to analyze root shapes and structures via polynomial curve fitting (Huang, Jain, Stockman, & Smucker, 1992; Zeng, Birchfield, & Wells, 2010). Recently, Mzoughi, Yahiaoui, Boujemaa, and Zagrouba (2015) proposed a hybrid approach for plant species identification. They used leaf arrangement, leaf lobation and leaf partition information to form the feature space necessary for classification. But again, this novel retrieval strategy lacks proper feature representation and selection for ImageCLEF 2011 leaf dataset7. Majority of them are content-based image retrieval which needs to be replaced by semantic and cognition based resulting higher level of accuracy in very small time of response (Candan, Kim, Nagarkar, Nagendra, & Yu, 2011; Li et al., 1997, 1998).

Mobile-Based Plant Species Identification System On the other side of the coin, MC can aid timely access to agriculture related information such as production monitoring, bank policies, m-agriculture commerce, and so on, as claimed by Prasad, Kumar, and Ghosh (2013a). Other than Kumar et al. (2012), White et al. (2006), Zhao et al. (2015), Prasad, Kumar, and Ghosh (2013b), Prasad, Kumar, and Ghosh (2015) presented an Agriculture-as-a-Service (AaaS) framework combining MC, AR and wireless communication technologies with cloud computing (CC) to better serve the agricultural community (agro-community). As the third eye of farmer, AaaS automatically assists in monitoring their crop fields by a smart remote expert’s eye. As discussed above, majority of works were desktop driven and limited to laboratory only. Few approaches are executed on mobile device as an interface such as the LeafSnap, Apleaf, and AgroMobile. Nonetheless, the mobile applications are very popular among the mass communities compared to other desktop-based systems. In addition to this, Mobile Cloud Computing (MC2) manages the energy consumption of a mobile phone supporting an off-line accessibility of plant information and pathological data, as shown in Figure 6. Accordingly, Kim et al. (2013) proposed a self-growing agriculture knowledge using CC services assisting farmers to make smart decisions. The detailed MC2 in agriculture is discussed in Prasad, Kumar, and Ghosh (2013a, 2015).

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Figure 6. AgroMobile framework (Prasad, Kumar, & Ghosh, 2013a)

Disease With recent advances in technology, Prasad, Kumar, and Ghosh (2016a) proposed a system that can recognize plant leaf disease using efficient CV algorithms. The author used Gabor Wavelet transform (GWT) over GLCM for disease patch pattern computation which is further used for classification using k-NN. The dataset used was a diseased leaf dataset with 5 different pathogen attacks on 4 different species. The system proposed is an Android-based mobile client-server architecture which even an illiterate farmer can operate. The server performs feature extraction followed by classification of the disease and inform the farmer in the field via a fax-back system. The accuracy reported by the author is 93% for diseased identification. In this paper, author have also mentioned an unsupervised leaf diseased patch segmentation in L*a*b* color space which is quite acceptable (Prasad, Kumar, & Ghosh, 2016a). Such system in future may be used to monitor, control and manage the agricultural productions automatically without any manual expert via MC2 (Prasad, Kumar, & Ghosh, 2013a, 2015). The tremendous growth in MC2 and its rising popularity among people all over the globe have motivated researchers to develop ubiquitous plant disease diagnosis system.

DATASETS For plant biometric system, several plant leaf datasets are introduces with different challenges like the first dataset which is mostly used by researchers is the Flavia Leaf dataset (Wu et al. 2007) having 32

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different species and 1900+ high quality image samples. Secondly, ICL (Intelligent Computing Laboratory) Leaf dataset (ICL) with 220 species, third is 100 plant leaf dataset (Mallah, Cope, & Orwell, 2013), and fourth is Swedish leaf dataset 11 (Sderkvist, 2001). All these leaf datasets are semi-segmented and so pre-processing is reduced. While there is another big dataset called PlantCLEF 2015 dataset8 which is composed of 113,205 plant images of 1000 different species (trees, herbs and ferns) in Western European regions (Goeau, 2015). A diseased leaf dataset collected from Indian Institute of Technology (IIT) Roorkee and Forest Research Institute (FIR) Dehradun campuses (Prasad, Kumar, & Ghosh, 2014, 2016a) is also available for plant leaf disease identification. More details related plant leaf datasets and research papers can be found on http://www.visionbib.com/bibliography/applicat842l1.html.

COMPARISON EVALUATION The contribution of automated plant biometric system since 2000 is shown using a graph (Figure 7), where y-axis shows the number of good related articles published in respective year on current topic (Wang et al., 2016). The increasing number shows the dedication of CV researchers in agriculture field. For comparison, several datasets are compared with different approaches proposed, as mentioned in this chapter, is shown in Table 1. The first column is for Flavia dataset and second for ICL leaf dataset. The third column is a mixed dataset highlighted only to compare the highest accuracy achieved by various researchers in recent years in plant species identification. From Table 1, it is seen that CNN is currently the best feature map to represent plant leaves for accurate classification. The problem with CNN is it needs a proper training with large datasets which requires huge number of resources. AaaS framework in reality may server agro-community in all sectors with high accuracy assisting famers when, what and how to plant with what fertility rate and chemical/natural controls. It even aware one remote farmer working in other end of world with the situations of other farmer’s failures while cultivation.

CONCLUSION In this chapter, a brief survey of automated plant biometric systems since decades is presented highlighting the current state-of-the-art. According to several authors, plant leaf patterns are represented mathematiFigure 7. Distribution of standard publications in field of plant species identification

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Table 1. State-of-the-art in plant biometric system Flavia Dataset

ICL Dataset

Other Datasets

Methods

Accuracy (%)

Methods

Accuracy (%)

Methods

Accuracy (%)

MCC (Adamek & Connor, 2004)

84.93

IDCS (Ling, Member, & Jacobs, 2007)

81.39

Wang et al., 2016

93.00

TAR (Alajlan, Kamel, & Freeman, 2007)

85.03

MCC (Adamek & Connor, 2004)

73.17

Lee, Chan, Wilkin, & Remagnino, 2015

99.50

IDSC (Ling, Member, & Jacobs, 2007)

88.11

TAR (Alajlan, Kamel, & Freeman, 2007)

78.25

Jassmann, 2015

81.60

TSLA (Mouine, Yahiaoui, & VerroustBlondet, 2013)

93.53

Fourier (Wang et al. 2015)

60.08

Kruse et al., 2014

95.00

MARCH (Wang et al. 2015)

96.15

MARCH (Wang et al. 2015)

85.31

Arunpriya & Thanamani, 2014

88.60

Prasad, Kumar, & Ghosh, 2016

97. 96

Prasad, Kumar, & Ghosh, 2016

96.50

Priyankara & Withanage, 2015

96.48

cally using various transforms including both spatial and frequency domain. More than fifty feature spaces for ten different plant datasets are discussed using different classifiers. Based on this survey, we find out the pros and cons of different feature spaces and classifiers. The future scopes and applications of such systems in agro-communities also motivate researchers to work in this field.

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Wang, Z., Chi, Z., & Feng, D. (2003). Shape based leaf image retrieval. IEE Process. -. Vision, Image, and Signal Process., 150(1), 34. doi:10.1049/ip-vis:20030160 Wang, B., Brown, D., Gao, Y., & La Salle, J. (2015). MARCH: Multiscale-arch-height description for mobile retrieval of leaf images. Inform. Sciences, 302, 132–148. doi:10.1016/j.ins.2014.07.028 Wang, Z., Li, H., Zhu, Y., & Xu, T. (2016). Review of Plant Identification Based on Image Processing. Archives of Computational Methods in Engineering, 1–18. Warren, D. (1997). Automated leaf shape description for variety testing in chrysanthemums. In IET 6th Int. Conf. on Image Process. and its Applicat. (pp. 497 - 501). 10.1049/cp:19970943 White, S., Feiner, S., & Kopylec, J. (2006). Virtual vouchers: Prototyping a mobile augmented reality user interface for botanical species identification. In Process (p. 133). IEEE Virtual Reality. doi:10.1109/ VR.2006.145 White, S. M., Marino, D. M., & Feiner, S. (2006). LeafView: A User Interface for Automated Botanical Species Identification and Data Collection. In ACM UIST 2006 Conf. Companion, (pp. 1-2). Montreux, Switzerland: ACM. White, S. M., Marino, D., & Feiner, S. (2007). Designing a mobile user interface for automated species identification. In Human Factors in Computing Systems, CHI’07, (pp. 291-294). doi:10.1145/1240624.1240672 Wu, S. G., Bao, F. S., Xu, E. Y., Wang, Y., Chang, Y., & Xiang, Q. (2007). A Leaf Recognition Algorithm for Plant Classification Using Probabilistic Neural Network. In Int. Symp. on Signal Process. and Inform. Technology, (pp. 11-16). 10.1109/ISSPIT.2007.4458016 Wu, S. G., Bao, F. S., Xu, E. Y., Wang, Y., Chang, Y., & Xiang, Q. (2007). A Leaf Recognition Algorithm for Plant Classification Using Probabilistic Neural Network. In Int. Symp. on Signal Process. and Inform. Technology, (pp. 11-16). 10.1109/ISSPIT.2007.4458016 Yanikoglu, B., Aptoula, E., & Tirkaz, C. (2014). Automatic plant identification from photographs. Machine Vision and Applications, 25(6), 1369–1383. doi:10.100700138-014-0612-7 Ye, L., & Keogh, E. (2009). Time series shapelets: a new primitive for data mining. Process. of the 15th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, 947-956. 10.1145/1557019.1557122 Yoshioka, Y., Iwata, H., Ohsawa, R., & Ninomiya, S. (2004). Analysis of petal shape variation of Primula sieboldii by elliptic Fourier descriptors and principal component analysis. Annals of Botany, 94(5), 657–664. doi:10.1093/aob/mch190 PMID:15374833 Zeng, G., Birchfield, S. T., & Wells, C. E. (2010). Rapid automated detection of roots in minirhizotron images. Machine Vision and Applications, 21(3), 309–317. doi:10.100700138-008-0179-2 Zhao, Z.-Q., Ma, L.-H., Cheung, Y., Wu, X., Tang, Y., & Chen, C. L. P. (2015). ApLeaf: An efficient android-based plant leaf identification system. Neurocomputing, 151, 1112–1119. doi:10.1016/j.neucom.2014.02.077 Zulkifli, Z., Saad, P., & Mohtar, I. A. (2011). Plant leaf identification using moment invariants & General Regression Neural Network. In 2011 11th Int. Conf. on Hybrid Intelligent Systems (HIS), (pp. 430-435). 10.1109/HIS.2011.6122144 790

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ENDNOTES 3 1 2

6 4 5



7 8

The author is currently in NTU, Singapore as Research Fellow. http://apps.kew.org/herbcat/navigator.do Several research are going on Plants, Leaf Shapes, Leaf Analysis and Leaf Segmentation. http:// www.visionbib.com/bibliography/applicat842l1.html#Plants, Leaf Shapes, Leaf Analysis, Leaf Segmentation http://leafzone.keydown.org/index.html http://flavia.sourceforge.net/ Several research going on Plants species, Flowers, Flower Shape and Flower Color. http://www. visionbib.com/bibliography/applicat842f1.html#Plants, Flowers, Flower Shape, Flower Color http://www.imageclef.org/2011/Plants http://www.imageclef.org/

This research was previously published in Ubiquitous Machine Learning and Its Applications edited by Pradeep Kumar and Arvind Tiwari , pages 15-38, copyright year 2017 by Information Science Reference (an imprint of IGI Global).

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Demand for Food Diversity in Romania Lucian Luca Institute of Agricultural Economics, Romania Cecilia Alexandri Institute of Agricultural Economics, Romania Bianca Pǎuna National Institute of Economic Research, Romania

ABSTRACT The present research work applied a food diversity measurement tool (Transformed Berry Index) on the 2011 Household Budget Surveys data. The investigation was performed on household purchased based TBI measure and on actual consumption TBI, in order to highlight the errors that one would make if one fails to take into account the production of goods by the household. There are some important differences in the food diversity of the actual food consumption in comparison to the purchased food quantities, the number of food items being higher in the case of actual consumption. However, food diversity does not seem to be influenced by the residence area (urban vs. rural) in any of the two approaches.

INTRODUCTION In Romania, the transition period was associated to a massive reduction in the population’s real incomes, this leading to the increase in the consumption of products considered inferior from a nutritional point of view, such as potatoes and cereal-based products, together with the decrease in consumption of the products that are more valuable in nutritional terms, such as meat and dairy products. Food substitutions took place not only inside certain groups of products, but also between groups of products (meat with cereals, for instance), out of the households’ need to adjust their food expenditures in the situation of real incomes diminution (Petrovici and Ritson, 2000).

DOI: 10.4018/978-1-5225-9621-9.ch035

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 Demand for Food Diversity in Romania

Subsequently, in the period of accession preparation to the European Union, and in the post-accession period, meat and dairy consumption increased, but the still low incomes resulted in a very high share of food expenditures in the household budget, in parallel with the relatively low dietary diversity, low consumption of fresh fruit and vegetables and high consumption of animal fat. An important part of the food consumed by households comes from the own produced food and this is especially true for rural households. The difficult situation from an household economic point of view due to the severe reduction in incomes, led to the increase in the share of consumption from own resources. The transfers of products from the rural to the urban households from the same family continue to represent a cultural pattern, and in the situations of crisis even a survival strategy for extended families. Due to this reason, the investigation of food diversity in Romania cannot be made by exclusively applying the methodology specific to the developed countries, where most food products are bought, as this would exclude the food consumption from own resources, the contribution of which is quite significant for certain households. The present research work applied food diversity measurement tools for a data set obtained from the Household Budget Surveys for the first quarter of the year 2011, both for the amount of products bought by the households and separately for the amount of products effectively consumed on the households, in order to highlight the differences between the results of the two approaches. Numerous approaches link dietary diversity to the level of incomes (Jackson, 1984). Thus, in the situation when the level of incomes is low, only a subset of available foodstuffs is bought. This pattern is known as the hierarchic demand system. The higher the level of consumption, the larger the number of products that go to the consumer’s basket.Most studies dedicated to the developed countries reveal the positive correlation between diversity (measured by the Herfindahlindex or the entropy index) and the level of incomes, measured by the real income per capita. One of these studies (Lee and Brown, 1989), where consumer demand for food diversity is measured by the entropy and Simpson indices for budget share, show that consumer demand for food diversity is related to total food expenditures and household size and composition. The econometric models by which the dietary diversity in the developed countries was investigated, for instance in Germany (Thiele and Weiss, 2003), reveal that dietary diversity is influenced by the household socio-economic characteristics, by income in the first place, then by the household size and composition, mainly the number of children 7 – 17 years old, the residence area and the size of the locality where the household is located. Dietary diversity decreases with the age of household members (up to 46 years), to moderately increase afterwards, in general the relationship being non-linear. The farmer households feature lower diversity for the purchased products, as certain foodstuffs are produced on their own households. While in the consumption pattern of developed countries, in nutritional terms, it is not the variety between the groups of products that is mostly important, but rather the variety between the individual products, in the less developed countries the diversity between groups of food products can be more important than the diversity of products as such, which could belong to the same group (Swindale and Bilinsky, 2006). At the same time, in the case of subsistence economies, a positive influence upon food diversity on the rural households is brought by the household’s access to the agricultural resources (Taruvinga et al., 2013). Recent studies in the New Member States of EU, including Romania, dedicated to dietary diversity, measured by the Count Measure and the Transformed Berry Index, indicates that food diversity is income elastic (Cockx et al., 2015; Cupak et al., 2014; Alexandri and Pauna, 2015, Alexandri and Kevorchian, 2015). The gender and occupational status of the household head play an important role, as female793

 Demand for Food Diversity in Romania

headed households have significantly higher levels of food diversity and self-employment in agriculture decreases diversity measured by food expenditures. The results further indicate a significantly positive effect for the presence of young children.

METHODOLOGY Romania has some particularities in terms of consumption when compared to other similar countries. Almost half of the population live in rural areas, and a large percentage of them are self-employed in subsistence agriculture. Besides the obvious poverty aspects of this occupation, it means that a large share of the households’ food consumption is not transacted on the market but is produced in-house. The effect of self-consumption on diversity is not very easy to assess, households might use the additional resources available to them for buying other food products (ambiguous effect on diversity), but they could equally buy non-food products (diversity decreases). This is why authors are interested to see how the determinants of diversity vary when the purchased food quantities are considered and when the actual food consumption are considered, and in order to do so, it was estimated the same diversity function for both data sets. The diversity measure that we have used in the paper is the Transformed Berry Index (TBI) which is computed using the share of expenditure for all purchased food products. We have computed two indices one based on the actual food purchased by the household and the second based on the actual household consumption. In the case of actual consumption, for each food product which originates from own production a price was imputed, equal tothe price of the purchased product in the same household if available, or the average sample price for that product if that food item was not purchased by the household. The Berry Index (BI) is constructed by adding the square of the share of expenditure for all food products: 2

 x  BI = 1 − ∑  i   X  i =1  n

where: xi is the expenditure on the i product and X is the total food expenditure. Typically, the dependent variable in a regression is the transformed Berry Index (TBI) which is computed from the BI as follows:  BI   TBI = ln  1 − BI 

DATA AND ESTIMATION RESULTS We use the Household Budget Survey for first quarter of the 2011 (7843 households). The survey contains detailed information on the composition of the household like the age of the members, education level, occupational status, etc. as well as information on the consumption and income in the month of the interview. The survey includes 106 records for food expenditure/consumption, and this is the information

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that is used for computing the diversity measures described above. Table 1 presents the values of TBI for the two approaches, purchased quantities and actual consumption. The importance of taking into consideration the consumption of food coming from own resources of the household is revealed by the higher diversity in the case of estimating the demand on the basis of actual food consumption compared to the results for the purchased food quantities. Thus, the average number of effectively consumed food items is 36.2, while the number of purchased food items is 22.5. There are also relevant differences in the case of BI (0.93 versus 0.88) and TBI (2.72 versus 2.22), with higher values for actual food consumption compared to purchased food quantities. The graphs in Appendix A plot the relationship between TBI and the age of the household head in the case of the expenditure based TBI (Figure 1) and actual consumption based TBI (Figure 2). The graphs indicate the importance of selecting the appropriate measure of diversity. Since the importance of own produced goods in total consumption differs from urban to rural households, the diversity gap between urban and rural households is greatly diminished when appropriately defining the household consumption. On the other hand, it does not appear that the age of the household is an important determinant of the food diversity for a given household. The other graphs in the same Appendix A present the dependence of the expenditure based TBI (Figure 3) and actual consumption based TBI (Figure 4) as a function of the total household income. The graphs use nonparametric methods and their shortcomings are evident on the graph, due to the scarcity of the data, the method is not very reliable at both ends of the data. As expected there is some increase in diversity due to the increase in household income both in the case of urban and rural households. Again, the gap between the rural and urban household diversity diminishes significantly when the diversity measure based on actual consumption is employed. There seems that the relationship between income and food diversity is less elastic when using actual consumption measures in comparison to expenditure measures. The equations estimated have as dependent variable the Transformed Berry Index (TBI) measured based on the purchased goods and on the effective consumption. The explanatory variables used are: the logarithm of the household income, in order to assess the elasticity of the diversity with respect to income, information on the household composition, the characteristics of the household head, and information on the residence area. The household composition variables are the number of household members and the number of children. The household characteristics that are included in the equation are age, education, occupational status. In terms of residence, we have included a dummy for the urban households, the county of residence. In addition, the education of the household head was interacted with the residence area (urban/rural) in order to assess whether the educated/uneducated urban households made different choices in terms of diversity in comparison to the educated/ uneducated rural households. Table 1. Statistics of the Transformed Berry Index Variable

Obs.

Mean

Std. Dev.

Min

Max

Actual food consumption TBI

7843

2.724478

0.38573

0.09713

3.708334

2.2217

0.607214

-1.17966

3.531456

Purchased food quantities TBI

7835

Source: authors’ computations

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By estimating the two regressions the goal was to understand how distorted the results would be if one fail to take into account the fact that numerous households are able to consumed foods which are produced internally. The output results for the two TBI computed as explained above are presented in Appendix B (see Table 2).

REGRESSION ON TRANSFORMED BERRY INDEX A very important determinant of diversity is household income. As expected, in both regressions the food diversity increases with the increase in income, but the TBI based on actual food consumption is less elastic than the TBI based on purchased food quantities, indicating that one might arrive to misleading results if one does not take into account the actual food consumption and looks only at the purchased food consumption. The education level in the case of the urban households is important in the determination of TBI diversity. In both regressions, any education means higher diversity in comparison to the omitted category which is no education, but again the importance of education on diversity is misleading if one analysis the diversity computed based on the purchased foods. This time the coefficients are five times as big as the correct ones, falsely indicating that higher educated urban households are opting for a more diverse diet. The rural education level is not significantly affecting the diversity level of the household. It appears that no education for the household heads means less diversity. There are certain levels of education that seem to be associated with higher TBI diversity (before university studies). As regards the occupational status of the household head, housewives are associated with lower diversity of food. The age of the household head does not appear to have a significant effect on the food diversity of the household, ceteris paribus. A female household head has a positive influence on the TBI measure, both in the case of purchases and of actual consumption. Household composition greatly affects the TBI diversity, the increase in the number of members decreases diversity, but if the household has children the diversity is increased. As before, the effect on diversity of household size is overvalued by the TBI based on purchased goods. There is some indication that cultural differences may affect the food diversity of households. There are some counties which appear to be associated with higher or lower food diversity. TBI measure of diversity is higher for the households located in developed counties and lower in less developed counties.

CONCLUSION Romania has some particularities in terms of consumption when compared to other similar countries. A large percentage of rural population are self-employed in subsistence agriculture. The investigation of food diversity in Romania cannot be made by exclusively applying the methodology specific to the developed countries, where most food products are bought, as this would exclude the food consumption from own resources, the contribution of which is quite significant for certain households. The present research work applied a food diversity measurement tool, Transformed Berry Index (TBI), on a Household Budget Surveys data set for the first quarter of the year 2011. TBI was computed for the amount of products bought by the households and separately for the amount of products effectively consumed on the households, in order to highlight the differences between the results of the two approaches.

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There are some important differences in the food diversity of the actual food consumption in comparison to the purchased food quantities. The TBI diversity is more elastic with respect to income in the case of purchased food quantities than in the case of actual food consumption, indicating that one obtains misleading results if one is not careful in the definition of the diversity. A female household head has a positive influence on the TBI measure, both in the case of purchases and of consumption. The education level seems to be important in the determination of TBI diversity only in the case of the urban households. Household composition greatly affects the TBI diversity, the increase in the number of members decreases diversity (both for purchases and consumption) but if the members are children, diversity increase. Food diversity does not seem to be influenced by the residence area (urban vs. rural) in any of the two approaches. Yet TBI measure of diversity is higher for the households located in developed counties and lower in less developed counties.

ACKNOWLEDGMENT The research leading to these results has received funding from the European Union’s Seventh Framework Program under Grant Agreement no. 290693 (FoodSecure) and from UEFISCDI (Romania) under contract 198/EU/2012.

REFERENCES Alexandri, C., & Kevorchian, C. (2015). Food consumption diversity in Romania. Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca. Horticulture, 72(1), 243–248. Alexandri, C., & Pauna, B. (2015). Assessment of food consumption diversity for Romanian households. LSMAScientific Research. Agricultural Management, 17(1), 282-289. Cockx, L., Francken, N., & Pieters, H. (2015). Food and nutrition security in the European Union: Overview and case studies. FOODSECURE Working paper no. 31. Cupak, A., Pokrivcak, J., & Rizov, M. (2014). Demand for the Food Diversity in Central and Eastern European Countries: an Evidence from Slovakia. Paper presented at the 142nd EAAE Seminar, Budapest. Jackson, L. F. (1984). Hierarchic demand and the Engel curve for variety. The Review of Economics and Statistics, 66(1), 8–15. doi:10.2307/1924690 Lee, J. Y., & Brown, M. G. (1989). Consumer demand for food diversity. Southern Journal of Agricultural Economics, 21(December), 47–54. doi:10.1017/S0081305200001163 NIS. (2012). Co-ordinates of living standard in Romania. Population income and consumption. The year 2011. Bucharest, Romania: National Institute of Statistics. Petrovici, D., & Ritson, C. (2000). Food consumption patterns in Romania. British Food Journal, 102(4), 290–307. doi:10.1108/00070700010327724

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Swindale, A., & Bilinsky, P. (2006). Household Dietary Diversity Score (HDDS) for Measurement of Household Food Access: Indicator Guide (FHI 360/FANTA). Washington, D.C. Taruvinga, A., Muchenje, V., & Muchenje, A. (2013). Determinants of rural household dietary diversity: The case of Amatole and Nyandeni districts, South Africa. International Journal of Development and Sustainability, 2(4), 2233–2247. Thiele, S., & Weiss, C. (2003). Consumer demand for food diversity: Evidence for Germany. Food Policy, 28(2), 99–115. doi:10.1016/S0306-9192(02)00068-4

This research was previously published in the International Journal of Food and Beverage Manufacturing and Business Models (IJFBMBM), 2(1); edited by Constantin Zopounidis and George Baourakis, pages 44-55, copyright year 2017 by IGI Publishing (an imprint of IGI Global).

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APPENDIX A Dependences of Transformed Berry Index (TBI) Figure 1. The dependence of expenditure based TBI as a function of the age of the household head

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Figure 2. The dependence of consumption based TBI as a function of the age of the household head

Figure 3. The dependence of expenditure based TBI as a function of the total household income

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Figure 4. The dependence of consumption based TBI as a function of the total household income

APPENDIX B Table 2. The estimation regressions of Transformed Berry Index Actual Food Consumption

Purchased Food Quantities

Number of obs

7816

7808

F(111, 7708)

33.96

47.7

Prob> F

0

0

R-squared

0.3204

0.4076

Adj R-squared

0.311

0.399

Root MSE

0.31987

0.46941

Coef

Prob

Coef

Prob

Logarithm of income

0.15372

0

0.234934

0

Second month of the quarter

0.012121

0.171

0.081059

0

Third month of the quarter

-0.01891

0.035

0.049938

0

Female

0.072031

0

0.068747

0

Urban household

-0.21138

0.21

-0.15106

0.54

Education level of the rural household head, omitted category is no education Primary school

-0.10581

0.518

-0.06234

0.4

Secondary school

-0.06951

0.67

-0.05021

0.5

continued on following page 801

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Table 2. Continued Actual Food Consumption

Purchased Food Quantities

Vocational education

-0.03863

0.812

-0.03973

0.6

First two years of highschool

-0.05976

0.723

-0.09088

0.3

High school

-0.01477

0.928

0.039272

0.61

Post high school schooling

-0.00763

0.963

0.008172

0.93

Short term university degree

-0.03911

0.814

0.005787

0.96

University degree

-0.03207

0.844

0.156606

0.11

Doctoral studies

-0.06602

0.752

-0.12009

0.8

Education level of th urban households, omitted category is no education Primary school

0.159363

0.349

0.475731

0.06

Secondary school

0.134853

0.426

0.53855

0.03

Vocational education

0.110727

0.513

0.573263

0.02

First two years of highschool

0.085705

0.628

0.539452

0.04

High school

0.114061

0.501

0.497585

0.05

Post high school schooling

0.09285

0.593

0.516825

0.04

Short term university degree

0.191115

0.299

0.494392

0.07

University degree

0.192876

0.269

0.385081

0.13

Doctoral studies

0.527302

0.171

0.567561

0.32

Occupational status of the household head, omitted category is wage earner Patron

0.202358

0.005

0.232364

0.03

Self-employed in non-agricultural activities

-0.02162

0.313

-0.01598

0.61

Member in a non-agricultural cooperative

0.075064

0.642

0.162339

0.49

Self-employed in agricultural activities

0.011712

0.507

-0.02329

0.37

Member in an agricultural cooperative

-0.22113

0.334

-0.09906

0.77

Unemployed

-0.00107

0.958

-0.0412

0.17

Pensioner

0.016125

0.285

0.035886

0.11

Pupil

0.046893

0.669

-0.38204

0.02

Student

-0.06337

0.213

-0.34258

0

Housewife

-0.08891

0.062

-0.14902

0.03

Dependent person

-0.1805

0

-0.04948

0.52

The age of the household head, omitted category is less than 30 years between 30 and 39

0.036519

0.115

0.053812

0.16

between 40 and 49

0.004575

0.837

-0.00039

0.99

between 50 and 59

0.006842

0.76

-0.00828

0.83

over 60

0.0149

0.548

-0.04141

0.26

2 members

-0.02846

0.009

-0.10233

0

3 members

-0.11116

0

-0.22185

0

4 members

-0.17356

0

-0.29489

0

5 members

-0.20803

0

-0.33321

0

Number of household members, omitted category is one member

continued on following page

802

Demand for Food Diversity in Romania

Table 2. Continued Actual Food Consumption

Purchased Food Quantities

6 members

-0.3206

0

-0.40882

0

7 members

-0.42802

0

-0.58347

0

1 child

0.070138

0

0.146454

0

2 children

0.133468

0

0.193642

0

3 children

0.128

0.003

0.282483

0

4 children

0.173756

0.024

0.338271

0

5 children

0.234619

0.02

0.388104

0.01

Arad

-0.04143

0.239

0.165858

0

Arges

-0.02847

0.418

0.054178

0.29

Bacau

0.167189

0

0.332162

0

Bihor

0.207654

0

0.266073

0

BistritaNasaud

0.035482

0.362

0.173195

0

Botosani

0.047578

0.179

0.083837

0.11

Brasov

0.050322

0.129

0.288045

0

Braila

0.133885

0.001

0.380932

0

Buzau

0.052015

0.144

0.321964

0

Caras-Severin

0.145652

0

0.233873

0

Cluj

0.089038

0.007

-0.08739

0.07

Constanta

-0.1063

0.002

0.114265

0.02

Covasna

0.229402

0

0.093961

0.11

Dambovita

-0.10683

0.002

0.147829

0

Dolj

-0.06945

0.037

0.170133

0

Galati

-0.23205

0

-0.14144

0.01

Gorj

-0.10794

0.005

-0.10872

0.06

Harghita

-0.02796

0.471

0.058356

0.31

Hunedoara

0.113388

0.001

0.262106

0

Ialomita

-0.00678

0.861

0.24962

0

Iasi

0.109898

0.001

0.325117

0

Ilfov

0.173466

0

0.478951

0

Maramures

0.029661

0.421

0.096954

0.07

Mehedinti

-0.34734

0

-0.2433

0

Mures

0.069689

0.042

0.00325

0.95

Neamt

0.001972

0.957

0.16821

0

Olt

-0.21143

0

-0.05381

0.31

Prahova

0.042886

0.198

0.303305

0

Satu Mare

-0.17011

0

-0.13255

0.02

Salaj

0.014234

0.722

0.029865

0.61

Number of children, omitted category is no child

County, omitted category is Alba

continued on following page

803

Demand for Food Diversity in Romania

Table 2. Continued Actual Food Consumption

Purchased Food Quantities

Sibiu

0.1096

0.002

0.052334

0.31

Suceava

0.255623

0

0.433883

0

Teleorman

-0.44748

0

-0.18834

0

Timis

-0.08138

0.013

0.081765

0.09

Tulcea

0.05227

0.204

0.135762

0.03

Vaslui

-0.08767

0.018

0.086875

0.11

Valcea

-0.20064

0

-0.3434

0

Vrancea

-0.15821

0

0.03135

0.56

Bucharest, s1

-0.05555

0.254

0.220799

0

Bucharest, s2

-0.09287

0.028

0.243482

0

Bucharest, s3

-0.02204

0.619

0.237548

0

Bucharest, s4

0.146235

0

0.354457

0

Bucharest, s5

0.110701

0.018

0.417674

0

Bucharest, s6

0.064074

0.123

0.383846

0

Calarasi

-0.14633

0

-0.06042

0.28

Giurgiu

-0.07481

0.056

0.15741

0.01

Constant

1.732855

0

0.307566

0.01

Source: authors’ computations

804

805

Chapter 36

Simulation-Based Approaches for Ecological Niche Modelling: A Geospatial Reference Anusheema Chakraborty TERI University, India P K Joshi Jawaharlal Nehru University, India

ABSTRACT Over recent years, many modelling approaches have been used to map and monitor both present and potential distribution of species in the context of ecological niche-based conservation, especially in the face of global environmental change. Using different statistical techniques in a built-in geographic information system (GIS), the development of predictive species distribution models has extensively increased. This chapter introduces a geospatial reference to simulation-based approaches of ecological niche models. The chapter discusses various environmental modeling tools and simulation models available in open source domain used by scientific communities. As an effort of this chapter, we focus on the potential of using such experimental models for large-scale ecosystem modelling studies, highlighting opportunities of research, for a variety of bio-geographical applications. It would serve as a basis for beginners in ecology exploring this field of research, who can further contribute and develop such models to better understand the complex field of ecosystem studies.

INTRODUCTION The knowledge of spatial distribution of species is essential, especially to investigate the species’ realized and fundamental niches. The understanding of this species-environment relationship is central for many current research programmes in ecology and conservation under global change (climatic and environmental) and it is of great scientific and societal relevance. This realization of the importance of predictive modelling of species is crucial in the field of both conventional as well as applied ecological research. Over past few years, species distribution models have seen an impressive growth in its modDOI: 10.4018/978-1-5225-9621-9.ch036

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 Simulation-Based Approaches for Ecological Niche Modelling

elling approaches in studies of biogeography, conservation biology, ecology, palaeo-ecology, wildlife management, and more recently, studying the effects of climate change (Table 1). Such an experimental modeling approach allows us to estimate species’ ecological requirements (Araújo and Guisan, 2006), generally based on various hypothesis (Guisan and Zimmermann, 2000). The idea is to quantify correlation between known occurrence of species and features of the ecological and environmental landscape (Miller, 2010). These models are often termed as species distribution models, climatic envelope models, or, most commonly known as, ecological niche-based models. The aim of such models is to reconstruct empirically derived ‘environmental profile’ which can be used to estimate the ecological space of species and/or predict the geographical distribution of species (Peterson, 2006). This sort of useful predictive modelling technique has had overwhelming success in the recent past (Austin, 2007, 2002; Elith et al., 2006, 2002; Guisan and Thuiller, 2005; Guisan and Zimmermann, 2000; Peterson, 2006; Sinclair et al., 2010). However, despite widespread use of these models, conceptual ambiguities and the biotic as well as abiotic limiting constraints need to be clearly addressed before any practical application of these modeling results are made available (Araújo and Guisan, 2006; Dormann, 2007). The predictive modelling of species is one of the vital components of applied research (geography and ecology). With the advancement in geographic information system (GIS) and other related technologies, increased availability of satellite-based remotely sensed data and myriad number of open source tools that have developed; this enables scientists to employ powerful and sophisticated means of species’ distribution modelling. As a result of simultaneous development of parallel applications with considerably different objectives, this process referred here as ‘ecological niche-based modelling’ has been previously described as ‘predictive vegetation mapping’ (Franklin, 1995; Miller et al., 2007), ‘predictive habitat distribution modeling’ (Guisan and Zimmermann, 2000), ‘bioclimatic envelope modeling’ (Heikkinen et al., 2006; Pearson and Dawson, 2003), ‘habitat suitability index mapping’ (Brown et al., 2000; Roloff and Kernohan, 1999), ‘habitat suitability modeling’ (Hirzel et al., 2006, 2002), and ‘niche modeling’ Table 1. Some of the uses of ecological niche-based models Quantifying the environmental niche of species

Austin et al., 1990; Vetaas, 2002

Testing biogeographical, ecological and evolutionary hypotheses

Anderson et al., 2002; Graham et al., 2004; Leathwick, 1998

Supporting appropriate management plans for species recovery and mapping suitable sites for species reintroduction

Pearce and Lindenmayer, 1998

Assessing species invasion and proliferation

Beerling et al., 1995; Peterson, 2003

Supporting conservation planning and reserve selection

Araújo et al., 2004; Ferrier, 2002

Suggesting unsurveyed sites of high potential of occurrence for rare species

Engler et al., 2004; Raxworthy et al., 2003

Modelling species assemblages (biodiversity, composition) from individual species predictions

Ferrier et al., 2002a; Guisan and Theurillat, 2000; Leathwick, 1998

Assessing the impact of climate, land use and other environmental changes on species distributions

Thomas et al., 2004; Thuiller, 2004

Building bio- or ecogeographic regions

No published example found

Improving calculation of ecological distance between patches in landscape meta-population dynamic and gene flow models

No published example found

Source: Guisan and Thuiller (2005).

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 Simulation-Based Approaches for Ecological Niche Modelling

(Peterson, 2006; Stockwell, 2006), among other terms. The ecological niche-based models, for instance, have been used to study relationships between environmental factors and species richness (Nally and Fleishman, 2004), presence of species in landscape influenced by characteristics and spatial configuration of habitats (Araújo and Williams, 2000; Dormann et al., 2007; Ferrier et al., 2002b; Scotts and Drielsma, 2002), potential of invasive non-native species (Peterson, 2003), historical species’ distributions (Hugall et al., 2002; Peterson et al., 2004) or species’ distributions in future climates (Araújo et al., 2004; Bakkenes et al., 2002; Thomas et al., 2004; Thuiller et al., 2005; Woodin et al., 2013), and ecological and geographic differentiation of the distributions of closely-related species (Graham et al., 2004). Another controversial usage of terms relates the concepts of ‘habitat’ and ‘niche’, which needs to be clarified by scientific researchers while conducting any predictive modelling studies on spatial distribution of species (Miller, 2010). Hence, what needs to be addressed is the urgency in rigorous assessments in this field of science to move forward with much transparency in the usage of terms (Kearney, 2006). Unambiguous interpretation of the aforementioned concepts requires explicit chosen assumptions and hypothesis about the spatial extent and spatial resolution of the areas that are measured; the types, mechanisms and effects of the biotic and abiotic interactions that may affect the distributions; the different roles that environmental and climate variables that can influence the presence and absence of species, and also the anthropogenic disturbances should be accounted in the niche definitions; and the scope of spatial displacements in ecological and evolutionary time frames. The correlative ecological niche-based models often require little knowledge of the mechanistic links between species and its surrounding environment, which acts as an advantage for poorly studied taxa (Kearney and Porter, 2009). In many circumstances, this can be proven beneficial given the paucity in the amount of data available (Barbet–Massin et al., 2012), but otherwise, scientists employing ecological niche-based models should reflect more on their limitation of these approaches. The key issue in species distribution modeling is the selection of the explanatory variables to create species-environment profile that supposedly predicts the distribution and abundance of organisms (Dormann, 2007). Since the causal mechanism of species distribution is not readily quantifiable, we often resort to substitute and proxies (Minor and Urban, 2007). Table 2 summarizes the shortcomings of ecological niche-based models and species distribution projections. The most basic and fundamental constraint of the usage of such models is the understanding of physiological limitations of the species. Although, the field of physiological ecology is developing ever so quickly (Buckley et al., 2010; Helmuth et al., 2004), much still needs to be done to overcome the barrier of limiting behavioral, morphological, and physiological traits of species with GIS datasets (Kearney and Porter, 2009). In correlative modelling approaches, species occurrences information is linked with GIS built-in environment through different statistical techniques. In mechanistic modeling approaches, information on the functional traits of species is linked with GIS built-in environment through different models that explicitly capture key processes by which traits and habitat features interact to determine species-environment relationship. In this chapter, we aim to review the various steps involved in predictive modeling of species, from the conceptual model formulation to species prediction and its application. After highlighting the major concerns on using such predictive models, we provide a basis for further developing the current existing ecological niche-based models. This state of the art technology, even though has been used considerably, with spectacular progress in dealing with the challenge of impacts of climate change; a better integration of these models with ecological theory can help to avoid the precluding use of these models in many theoretical and practical applications. We first define the concept of the term used from here on, ecological niche-based models, and provide an overview of the basic ecological theory and major assumptions 807

 Simulation-Based Approaches for Ecological Niche Modelling

Table 2. Overview of problems associated with ecological niche-based models General Species Distribution Model Issues Causal drivers are rarely quantifiable. Species may not be at equilibrium with environmental drivers Limiting factors may differ throughout a species’ range Distribution patterns are governed by processes at multiple spatial scales Extrapolation Issues Identity of limiting factors may change with environmental change Biotic interactions are probably affected by environmental changes Genetic structure of species is likely to be affected by environmental changes Trends may not be valid beyond the range of present data Environmental change scenarios are spatially uncertain Statistical Issues Drivers have non-linear effects on species distribution patterns Drivers interact in their effects Causal drivers may be correlated with each other Data points in space are non-independent (spatial autocorrelation) Presence-absence data have low information content Low sample size and parsimony may lead to inadequately simple models Source: Dormann (2007).

used in the predictive modelling process. We outline the steps involved in making a niche-based model used in the field of applied ecology, and we identify issues and applications associated with new developments in this field. We then discuss some methodological issues involved, and the decisions that are made during the process of developing a model and its calibration, and the implications of such results in ecological conservation and management. We summarize this chapter by addressing the challenges that should be overcome keeping in mind the limitations of these models. To add to this, we also discuss niche conservatism across different time scales and spatial scales in order to suggest future direction of species distribution modelling.

BACKGROUND The ecological niche-based models attempts to provide detailed prediction of the distribution of species which is trained on its presence or abundance or absence or may be both, by relating it to environmental variables. For instance, the major concept central to predictive modelling is the distinction between geographic and ecological space, where geographic space is defined by either two-dimensional or threedimensional space having information on species (such as occurrence records), and ecological space is a hypothetical multi-dimensional space which can be defined by sets of environmental layers (Figure 1). In the field of ecology, any framework will have three basic major components for the statistical modelling process; namely,

808

 Simulation-Based Approaches for Ecological Niche Modelling

Figure 1. An example showing relationship between species and environmental data, and predictive modelling (current and future) of species using any set environmental variables

1. Ecological model, 2. Data model, and 3. Statistical model (Austin, 2002). The ecological information to be used or tested in the study would be comprised in the ecological model. The data model would consist of the information regarding data collection and its pre- and postprocessing. The statistical model would involve the choices of statistical method being employed, the error basis function and other significant tests to be conducted. The models interact with each other and determine the success or failure of any statistical predictive species distribution modelling process. The ecological niche-based models are empirical models which mainly relate field observations with environmental variables; based on statistical or theoretical surfaces (Guisan and Zimmermann, 2000). The information about species data can simply be the presence, presence-absence, absence or abundance observations based on either random or stratified field sampling, or historical observations (Guisan and Thuiller, 2005). The environmental variables, however, can have direct or indirect influence on the species, optimally chosen to reflect the three foremost types of influences on the species, such as,

809

 Simulation-Based Approaches for Ecological Niche Modelling

1. Limiting factors (or regulators), 2. Disturbances, and 3. Resources. These relationships between the species in study and its overall environment can cause different geographical distribution patterns that needs to be observed at different temporal and spatial scales (Figure 1), often in a hierarchical manner (Pearson et al., 2004) (Figure 2). For robust prediction of distribution of species, the understanding of the elements that can limit geographical range of species is crucial. The different statistical techniques used in the ecological niche-based models analyze organisms and its spatial existence in the ecosystems. These models vary significantly in scope and complexity. The distribution of species is intertwined with myriad number of climatic and environmental factors, which lead to the presence of a species at a particular geographical location. The niche-based modeling involves two fundamental steps; first, estimate the relationship among species in a particular area with respect to its biotic and abiotic conditions and second, forecast changes in the speFigure 2. General hierarchical ecological niche-based models Source: Adapted from Guisan and Thuiller (2005).

810

 Simulation-Based Approaches for Ecological Niche Modelling

cies’ distribution in response to any environmental change. Some species distribution models strategies predict changes in the geographical distribution of species by combining factors that relate to niches and suitable environmental surroundings with the presence and abundance of species in a single modeling framework. In contrast to this archetype, a pure niche-based model will first estimate suitability on the basis of current environmental information. This kind of niche model is then applied to predict future conditions to estimate the potential areas suitable for that particular species’ growth, which can serve as a critical input for a spatially explicit simulations (Anderson, 2013). The distribution and abundance of any species’, however, can be influenced by many ecological and evolutionary processes, which may or may not be limited to a species’ niche (Figure 3). The niche of any species’ can be predicted through either correlative or mechanistic models (Table 3); lately, efforts have been attempted to successfully link them (Kearney and Porter, 2009). Mechanistic models are directly on physiological and behavioral tolerances. However, these models can be quite difFigure 3. Major ecological processes can be captured by niche-based models. These processes may or may not include biotic interactions (realized niche vs. fundamental niche). Source: Adapted from Kearney and Porter (2009).

811

 Simulation-Based Approaches for Ecological Niche Modelling

Table 3. A comparison of mechanistic and correlative approaches to species distribution modelling Mechanistic (Physiological) Approaches

Correlative (Statistical) Approaches

Advantages of Mechanistic Approaches

Advantages of Correlative Approaches

Conceptualization

Theoretical basis

Energy-mass balance, climate space, mechanistic conceptualization of the Hutchinsonian niche

Probability, statistical theory, pattern recognition, often considered in the context of the Hutchinsonian niche or habitat concepts

Grounded in physico-chemical principles, provides mechanistic understanding of underlying processes

Can implicitly incorporate any process, biotic or abiotic, statistically associated with the independent variables, can be used to develop hypotheses about underlying processes

Model selection

Prescribed (variants of an energy balance equation)

Flexible (numerous algorithms and variable selection procedures, e.g. regression, maximum entropy, polynomial ⁄ linear terms)

Energy ⁄ mass balance equation provides a common frame of reference

Can be more easily tailored to fit available data

Generality (transferability) and precision

High generality across environments but potentially low precision

Local analysis often with high precision, although choice of variables and fitting strategy can be tailored for emphasizing generality or precision

Scope of applications extends to non-equilibrium/novel circumstances

More likely to capture a limiting processes, less likely to overestimate potential range

Data Requirements

Species data

Functional traits, (morphology physiological and behavioural responses)

Occurrence data (presence only, presence ⁄absence or abundance records)

Directly applies physiological understanding to range prediction. Can be applied when occurrence data is limited or in non-equilibrium ⁄novel circumstances

Exploits a more commonly available data source

Spatial data

Prescribed – energy balance equations demand specific independent variables

Flexible

Less subjectivity in variable selection

While directly related (proximal) environmental variables are preferable, can exploit a wider range of proxy spatial data types

Scale

Prescribed – highly proximal (scale of an individual organism)

Flexible

Less subjectivity in variable selection

Can use data sets of a wider range of scales, can capture processes at different scales within a single model

Parameters

Trait values, enegry/mass transfer coefficients, physiological response curves (may themselves be parameterized statistically)

Dimensionless coefficients

Robust because parameters are estimated independently of the (geographical range ⁄abundance) data

Pragmatic because parameters are estimated from a single dataset within a single analytical framework

Geographical variation (plastic and genetic)

Explicit

Implicit

Permits assessments of the degree of geographical variation and inference on its adaptive significance

Easier to incorporate geographical variation because it is indirectly represented in the occurrence data

Implicit

Permits explicit consideration of evolution, avoids confounding with other processes that may alter environmental associations through time

Can exploit readily available datasets to set up testable hypotheses about the past evolution of traits

Model Fitting

Evolutionary change

Explicit

Inference Output

Fitness components (survival, performance, development, growth and reproductive capacity)

Dimensionless habitat suitability indices or estimates of probability of occurrence or abundance

Highly interpretable ecologically, may serve as input into other process models (e.g. dispersal)

Provides a simple output indirectly representing many different processes

Validation and evaluation

Validation through independent empirical studies (field and laboratory), e.g. of behaviour, body temperature, energy and water turnover, evaluation against independently observed occurrence

Fit evaluated against original occurrence input data, subsets of original data left aside for validation, or (rarely) independent data on distribution and abundance

Biologically grounded and independent of the data used to derive the model

Often easier because model construction and validation ⁄ evaluation uses a single, readily available dataset and analytical framework

Source: Kearney and Porter (2009).

812

 Simulation-Based Approaches for Ecological Niche Modelling

ficult to be implemented give the amount of extensive data it requires, along with cost factors. Hence, for most studies related to distribution mapping of species, correlative approaches are used. This can be conducted due to relatively easily available and accessible online and offline data sources regarding species occurrences and environmental conditions. Nonetheless, the challenges for building an ecological niche-based model differ substantially between mechanistic and correlative approaches; however, many relevant principles hold true for both the approaches (Anderson, 2013). In this chapter, we aim to sketch a conceptual overview of niche and niche-based models in the field of ecological modelling. In order to do so, the theoretical paradigm of the selection criteria of the nichebased models while considering the methodological constraints is highlighted in the upcoming sections.

Niche Concept and Niche-Based Models The notion of ‘ecological niche’ is central to ecology of an organism, where the ecological properties of species and area of geographical distribution is related (Grinnell, 1917; James et al., 1984). Over the years, scientists are trying to estimate distributional area of species, by calculating ‘environmental’ or ‘ecological’ niches (Guisan and Zimmermann, 2000; Peterson, 2006). The foundation of niche modeling may vary depending on the application of niche concept being applied, namely, Grinnellian concept, Eltonian concept and Hutchinsonian concept of ecological niches (Table 4). The term ‘niche’ is used interchangeably by the modelers; although, much has been written about its different interpretations, both in general (Chase and Leibold, 2003; Pulliam, 2000) and as applied to ecological niche-based models in particular (Araújo and Guisan, 2006; Austin, 2002; Franklin, 2010; Guisan and Zimmermann, 2000; Kearney, 2006; Soberón and Peterson, 2005). It is, therefore, important to clarify which ecological niche concepts are being translated in the species distribution modeling process.

Model Selection and Methodological Considerations There can be many modeling approaches, consequently, resulting in different outputs, depending upon the selection of the constructed ecological niche-based model. These modeling approaches could vary Table 4. Summary of division of niche concepts Relevant Environmental Variables

Generalities Regarding Scale

Grinnellian niche

Variables not affected by the presence of the focal species

Coarser grains; geographic extents

Densityindependent

Related to intrinsic population growth rate

Static models

Eltonian niche

Variables affected by the presence of the focal species

Finer grains; local extents

Densitydependent

Related to instantaneous population growth rate

Dynamic models

Hutchinsonian niche

Variables affected by the presence of the focal species

Spatial grains; regional to continental extents

Densitydependent

Related to instantaneous population growth rate

Static models

Niche Perspective

Nature of Driving Factors

Relationship to Population Growth Rate

Relevant Modeling Approach

Source: Adapted from Anderson (2013).

813

 Simulation-Based Approaches for Ecological Niche Modelling

from the input sources itself, depending on the amount of data available. For instance, the model may be constructed from species occurrence points (presence; or presence/absence information) which acts as the dependent variable, and along with the required available environmental data of the same or approximately same region, which act as the independent variables. This kind of approach will lead to two types of common outputs: binary classification of geographical region as being within or outside the species distribution, and continuous or probabilistic distribution of species. The parameters can be further projected using future climate scenarios to develop and map the predicted future distribution of the species. Predicting the distribution of species has gone through different phases in history: 1. Based on empirical data, non-spatial statistical quantification of the species–environment relationship, 2. Expert-based spatial modelling of distribution of species (non-statistical, non-empirical), and 3. Modelling of distribution of species through spatially explicit statistical and empirical models (Guisan and Thuiller, 2005). With the evolvement of this field, it can be seen that there is little agreement on appropriate data, methodology or even interpretation, and mostly, there is little discussion behind the conceptual framework on which the predictive ecological niche-based model is based. Even for comparison, the different methods of modeling approaches rarely use the same type of data (whether it is the abundance or presence/absence information), or type of the regression method being applied (for example, multiple linear versus curvi-linear), or even the usage of common set of predictor variables. Most of the evaluation of comparisons among the different set of modeling approaches by scientists lies in how the methods are being applied, i.e. model parameterization (Austin, 2007). Although, the basic paradigm for any modelling approach consists of commonly agreed set of evidences (that is, presence or absence data on species), a conceptual framework (viz. the niche theory to be considered), set number of variable that can be considered (climate and environmental condition of species distribution) and method of modeling the distribution (for example, logistic regression) (Guisan and Zimmermann, 2000). Nonetheless, the ecological niche-based models, even with different levels of complexity fit within a basic framework. For instance, it either is using only climate as independent variables or/along with the usage of biophysical variables. The least common used models generally include the models that are constructed from physiological needs of different species (Kearney and Porter, 2009), rather than more commonly used species–climate models that are based on the distributional data. Selecting the model best or most appropriate using the most influential predictors is crucial. Shortcomings in the selection procedure have been recognized and in response, newer approaches have been implemented to better predict species distributions (Guisan and Thuiller, 2005). These ecological nichebased distribution models can be developed using a variety of algorithms, including heuristic models (for example, BIOCLIM—Busby, 1991), statistical models (such as, generalized additive models, i.e., GAMs—Guisan et al., 2002), combinatorial optimization (e.g., genetic algorithm for rule set production, i.e., GARP—Stockwell, 1999) and machine learning (for instance, artificial neural network, ANN— Hilbert and Ostendorf, 2001; or, maximum entropy, MAXENT—Phillips et al., 2006). Studies have used multiple models to extrapolate global extinction rates from climate change (Thomas et al., 2004; Woodin et al., 2013). Table 5 lists the most of different published predictive models for studying speciesspecific information. One can conclude that each modeling approach has its own merits and demerits, 814

 Simulation-Based Approaches for Ecological Niche Modelling

Table 5. List of ecological niche-based models Type of Models

Data Type

Reference(s)

ANUCLIM

Envelope model

P

Xu and Hutchinson, 2011

BIOCLIM

Envelope model

P

Busby, 1991

BAYES

Predictive statistical model

P

Aspinall, 1992; Ellison, 2004

BIOMAPPER

Envelope model

P

Hirzel et al., 2007

BIOMOD

Envelope model

P, A

Thuiller et al., 2009

BRUTU

Regression, a fast implementation of a GAM

P, A

Hastie et al., 2009

DOMAIN

Multivariate distance

P, A

Carpenter et al., 1993

ENFA

Ecological niche factor analysis

P

Hengl et al., 2009

LIVES

Multivariate distance

P, A

Elith et al., 2006

GAMs

Generalized additive models

P, A

Guisan et al., 2002

GBMs

Boosted decision trees

P, A

Friedman et al., 2000

GLMS

Generalized linear models (logistic regression, auto-logistic regression, regression and others)

GARP

Genetic algorithm for rule set prediction

P, A

Stockwell, 1999

GDM

Generalized dissimilarity model

P, A

Ferrier et al., 2002b

GRASP

Generalized regression analysis and spatial prediction

P, A

Lehmann et al., 2002

MARS

Regression; multivariate adaptive regression splines

P, A

Moisen and Frescino, 2002

MAXENT

Maximum Entropy

P, A

Phillips et al., 2006

ModEco

Envelope model

P, A

Guo and Liu, 2010

NPMR

Non-parametric multiplicative regression

P, A

Yost, 2008

OM-GARP

Open modeller-GARP

P, A

Elith et al., 2006

SPECIES

Artificial neural network (ANN)

P

Pearson et al., 2002

Guisan et al., 2002

Source: Adapted from Guisan and Thuiller (2005) and Wisz et al. (2008). P – Presence; A – Absence.

and accordingly has its own important strengths and weaknesses. In order to test the performance of any modeling approach, it can be generally evaluated using a test or validation datasets (Elith et al., 2006; Hijmans, 2012; Wisz et al., 2008). What can be achieved, or hoped to be achieved, is the use of different set of modelling approaches, and identification of significant interactions among the species and the environment to better understand the complexity in nature.

Functionalities and Possibilities At times, bearing in mind the availability of data and the landscape constraints, as researchers we also need to delimit the scope and extent of our analysis. While doing so, one needs to also consider the abiotic, biotic and movement factors (‘the BAM diagram’) that may or may not limit the distributions of species in geographical space (Figure 4). This kind of illustration of the scale-dependent relationship is critical for identifying the nature of differences in predicting the distribution of species. These three interacting set of factors, 815

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Figure 4. A simplified version of the BAM diagram; the distribution of species corresponds to three sets of factors: abiotic niche (A), biotic niche (B), and, accessibility or movement (M). A and B roughly correspond to the fundamental ecological niche (A) and the realized ecological niche (A ∩ B, here termed the potential geographic distribution). The area corresponding involvement of all the three set of factors (A ∩ B ∩ M) is the actual geographic distribution of species. [Note: The absence of species can be due to incorrect environment, lack of dispersal capacity; and also due to both incorrect conditions and limited dispersal (it can be present anywhere, depending on the condition)]. Source: Adapted from Soberón and Peterson (2005).

1. Abiotic, 2. Biotic, and 3. Movement factors, help us in anticipating the geographical distributions of organisms. The basic requirements of most of the ecological-niche based models are the same. The set of applications that they have been used for have are summarized in Table 6. The first and foremost step is to understand the ecological requirements of the species by understanding its ecological dimensions relevant to the geographical distribution (Peterson, 2006). The second most important criteria is the knowledge on limiting factors that constitute the geographical space of any species should be clearly understood and categorized before applying any niche-based model for ecological studies. Depending on the availability of the data required, one can then select the appropriate best model for selecting the

816

  Overall low error needed

Causal

Yes

Overall low error needed

Potential

No

Grain required

Causal variables needed, or surrogates OK?

Need model response curve or parameter retrieval

Error needs

Potential distributional model versus realized distribution?

Uncertainty estimates needed?

Source: Peterson (2006).

Yes

Any

Form of prediction (e.g., binary, ranked, absolute)

No

Potential

Causal

Any

Any

Any

Quality of Interest

  Understand Biogeography and Dispersal Barriers

Understand Ecological Requirements of Species

No

Realized

No

Potential

  Low omission (don’t mind searching extra localities, but don’t want to leave anything out)

  Low omission (don’t mind searching extra localities, but don’t want to leave anything out)

Yes

Realized

  Low commission (very high cost of errors)

  Useful, to avoid error

Yes

Realized

  Low commission (very high cost of errors)

  Useful, to avoid error

Surrogates

  Surrogates OK if within range; causal necessary if extrapolating

  Surrogates OK if within range; causal necessary if extrapolating No

  Individualpopulation

  Individualpopulation

Any

  Conservation Planning and Reserve System Design Absolute

  Identify Sites for Translocations and Reintroductions Absolute

Any

Find New Species

No

Surrogates

Population

Any

  Find Unknown Populations

No

Realized

Overall

No

Causal

Any

Any

  Predict Effects of Habitat Loss

No

Potential

Overall

No

Causal

Any

Any

  Predict Species’ Invasions

Table 6. Summary of different uses of ecological niche-based models, and their requirements in terms of output and information

No

Both

Overall

No

Causal

  Any, but may be limited by resolution of climate change data sets

Any

  Predict Climate Change Effects

 Simulation-Based Approaches for Ecological Niche Modelling

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distribution model for predictive studies. The third basic requirement of any models would lie in the known and unknown population of species. The in depth understanding of the ecological niche-based models functions and further possibilities will help in prioritizing areas based on the patterns of species’ occurrences. This can help in establishing conservation sites accordingly to the most likely suitable or unsuitable sites for the species in study, depending on the case of management strategy that may be. The relatively easier applicability of the ecological niche-based models helps in identifying the framework that can be applied for conservation of the threatened or likely to be the threatened species in present as well as in future.

Assumptions and Statistical Stumbling Stones Since the information on both species’ occurrences and the environmental as well as climatic data is limited to either time or space, the species-environment relationship that is generated through these ecological niche-based models, it can only provide us a overview of the expected relationship. One of the convenient ways of working around such predictive modelling approaches is to assume that the species modeled would attain if not any complete but partial pseudo-equilibrium with its environment (Guisan and Thuiller, 2005). The appropriate selection of the models for correlative niche modeling, both regarding records of the species’ presence or absence, along with environmental variables assumes certain hypothesis. Much of the information regarding the environment and climatic parameters at the predictive species’ site, show disagreement with the correlative niche modelling techniques found at presence records datasets (Anderson, 2013). To add to this, several statistical obstacles are also there when it comes to interpretation of these modelling results. The first and foremost factor that needs to be looked in details is the availability of data. The collection of data at different resolutions, during different time periods, along with collection under different taxonomic concepts and ecological hierarchies creates difficulty, depending on the purpose of niche modeling exercise. To integrate all the data available in one platform itself, is a big challenge and requires more specific dedicated analysis, unlike done otherwise. The first challenge and the major assumption that is considered in most studies are the linear predictors used for species distribution (Dormann, 2007). For most ecological studies, one can safely accept non-linear effect of species abundance or performance to environmental variables (Austin, 2002). Likewise, few analysis attempt to investigate of species distributions with interactions among environmental drivers (Thuiller et al., 2003). The second most important assumption is disregarding the commonalities among interrelated drivers (Anderson, 2013; Dormann, 2007). Many a times, the predictive modelling approach fails to detect the species in the geographical space (whether or not it occupies those regions). The abiotic conditions that can be found in the species’ occupied areas correspond to the species’ occupied niche space, which is termed the realized niche in the analysis. Even if we assume that all occurrences of species represent demographic sources and the sampling was unbiased, the presence-only records may provide inadequate and/or inaccurate classifications of the species’ fundamental niche for the examined abiotic variables. Therefore, we can conclude two major issues that contribute to the performance of ecological niche-based models: 1. The limited range of environmental conditions that exist in a study site; and 2. Non-equilibrium distributions of species (Anderson, 2013).

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Another ambiguity that may arise is the purpose of the modeling approach, where the estimates of the fundamental niche require clarity in the niche space assumption, that is, whether it is applicable to the study region (correlative niche modelling) or experiments (mechanistic niche modelling). Moreover, correlative niche models assume that presence records constitute unbiased samples, unlike mechanistic niche models. Table 7 summarizes these assumptions regarding occurrence data as the dispersal/demograpic noise assumption, the biotic noise assumption, and the human noise assumption. Each assumption relates to the condition for a particular species in any given study site. These descriptions clearly leave us a bleak impression on the current state of the art modelling approaches. However, it is known that species’ distribution modelling has both potential for science and social science. Since the assumptions lead us to principally selecting the ecological niche-based model to be applied, one must acknowledge them clearly before concluding any solutions. If any such assumption is not clarified in a study, the niche model will automatically start accounting for incomplete or distorted predictive estimate of specie’s geographical distribution. Despite the drawbacks, many insightful studies have been attempted to solve the above mentioned problems. Realizing these caveats is essential, as one may take up the endeavor to solve such ecological riddles.

FUTURE RESEARCH DIRECTIONS Given the current need to improve our knowledge on the distribution of species in the era of global change, we need to address the issues in our modelling approaches. Consideration of few steps is crucial to successfully apply the practical solutions of such predictive modeling experiments. To further develop Table 7. Four assumptions associated with data used in niche models estimating abiotic suitability for a species, with recommendations for correlative models of Grinnellian niches Name of Assumption

Assumption

Consequences of Violation

Niche space assumption

The study contains the full range of conditions that the species can inhabit (for the examined abiotic variables)

The existing fundamental niche is smaller than the fundamental niche; the species’ response is truncated for one or more abiotic variables

Dispersal/ demographic noise assumption

Factors related to dispersal, establishment, and persistence do not cause the species to occupy an environmentally biased subset of the abiotically suitable areas

The occupied niche space is smaller than the existing fundamental niche; the species’ response is truncated and/or distorted for one or more abiotic variables

Biotic noise assumption

Biotic interactions do not cause the species to occupy an environmentally biased subset of the abiotically suitable areas

Same as above

Human noise assumption

Human modifications of the environment do not cause the species to occupy an environmentally biased subset of the abiotically suitable areas

Same as above

Recommendations Use presence records from many portions of the species’ range and over multiple time periods; examine response curves and detect truncations in calibration region

Use occurrence data (presence records and comparison data) only from regions where the species is at equilibrium with abiotic variables or where limitations caused by dispersal/ demography, biotic interactions, or human modifications do not cause the species to occupy an environmentally biased subset of the abiotically suitable areas

Source: Anderson (2013).

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these ecological niche-based models, few recommendations should be considered in such experiments and their projections. The first critical step would imply to understand the uncertainties involved with the outputs of predictive modeling of the distribution of species. The identification of the flaws causing major variability should be noted and accepted in the models. These assumptions include the quality of primary and secondary data being collected, the choice and collinearity of explanatory predictor variables, and type of statistical modelling approach considered (Dormann, 2007). The next step would involve efforts to compare the differences in outputs of the distribution models. Consideration of maximum possible abiotic and biotic factors accounting for the ecological processes is also important. Given the data availability, such factors can determine the performance of the niche models. And lastly, the validation of such predictive modeling exercise should be thoroughly conducted before jumping to conclusion on the geographical range of species distribution. Although many studies have been using predictive ecological niche-based models for impacts studies on climate change and species conservation, recent studies suggest that their uses is in now resurfacing in theoretical ecology and evolution. However, given the pitfalls in this field of study, we need to be reasonable and therefore, further improve the methods. Species which require general environment to survive are preferably better candidates for such modeling studies. While species which require more specific explicit environment of survival, may not be best modeled with such species distribution models. The future of this field of science lies in further developing the basic biological and ecological research tools. If our understanding and knowledge of the target species’ ecology is clear, such predictive models can be very well utilized. We need to improve our modelling algorithms and try to use the best available method. Systematic collection of species distribution records is essential as it represents the basic requirement of any model. Even the collection of absences is valuable, because many modeling routines may require both absence and presence data information about the species. Both the geographic and environmental space should be well-sampled and surveyed for these niche models. The outputs of such studies should be regularly monitored especially while predicting future distribution of species. In this way, the models can be further validated and improved. While addressing the uncertainties explicitly, it should be communicated with other researchers, along with managers and policy makers, so as to put these models to better use. Whether it is the migration process, or the dynamics of species, or the incorporation of biotic interactions while modelling the functional traits and communities, it should be explored more in this field (Guisan and Thuiller, 2005). It would be interesting to see such efforts which can drastically influence the outputs and reliability of such modelling approaches.

CONCLUSION Although there has been tremendous development that has been made on many aspects related to the building and evaluation of ecological niche-based models, focused future efforts should be considered for developing and standardized more robust modelling frameworks. This chapter points out the critical, but obvious issues that need to addressed. It may be pointed out that, although it may seem obvious, it has been neglected in the past. However, recent efforts have been made to improve such modelling frameworks, while keeping mind the uncertainties. Many important basic concepts require deeper dwelling and understanding. Some of them are as follows:

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1. To explore the relationship between niche concepts and species distribution; 2. To assess the equilibrium or pseudo-equilibrium stages of modelled species; and 3. To investigate the degree to which competition among species can limit their geographical ranges along environmental gradients (Guisan and Thuiller, 2005). Both information of time scale and spatial scale should be further enhanced to decrease the errors and uncertainties in ecological niche-based models. Sources of biological data continue to expand, particularly for presence-only observations; environmental data are available at even finer spatial resolutions; and more complex modeling algorithms are being developed or becoming accessible to the SDM community. Each step taken in the species distribution modeling process involves a combination of assumptions and subjective decisions that propagate to affect the product, which is increasingly used to inform policy decisions. Given their current and potential use in a wide range of applications, these conceptual issues associated with the data and methods used need further study. With this chapter, we try to highlight issues that can be identified in such simulation experiments of ecological niche-based models, in a geographic built-in environment. Whether it is the spatial autocorrelation, or paucity in the availability of data, there is still considerable debate that needs to be addressed. Although, we try to model scenarios of species’ distribution based on simulated data, it can be proven most useful if the assumptions of niche concept and the environmental profile can be further elucidated. If the ecological niche-based models are used in forecasting studies, issues of ecological equilibrium theory and ecological niche conservatism should be answered prior to such exploration. In conclusion, with this chapter, we critically assess different ecological modeling approaches. We focused on the potential of using such experimental models for large-scale ecosystem modeling studies. This can serve as a basis for the scientist and researcher interested ecological modeling, who can further contribute and develop such models to better understand the complex field of ecosystem studies. We urge the ecologists, geographers, bio-geographers, modelers, and biologists to work in unison and contribute in a much concentrated manner to further develop this field of scientific research. Along with this we also need initiatives to develop interfaces between the scientific interpretation and required generalization for policy analysis.

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Peterson, A. T. (2003). Predicting the geography of species’ invasions via ecological niche modeling. The Quarterly Review of Biology, 78(4), 419–433. doi:10.1086/378926 PMID:14737826 Peterson, A. T. (2006). Uses and requirements of ecological niche models and related distributional models. Biodiversity Informatics, 3(0), 59–72. doi:10.17161/bi.v3i0.29 Peterson, A. T., Martínez‐Meyer, E., & González‐Salazar, C. (2004). Reconstructing the Pleistocene geography of the Aphelocoma jays (Corvidae). Diversity & Distributions, 10(4), 237–246. doi:10.1111/ j.1366-9516.2004.00097.x Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190(3-4), 231–259. doi:10.1016/j.ecolmodel.2005.03.026 Pulliam, H. R. (2000). On the relationship between niche and distribution. Ecology Letters, 3(4), 349–361. doi:10.1046/j.1461-0248.2000.00143.x Raxworthy, C. J., Martinez-Meyer, E., Horning, N., Nussbaum, R. A., Schneider, G. E., Ortega-Huerta, M. A., & Peterson, A. T. (2003). Predicting distributions of known and unknown reptile species in Madagascar. Nature, 426(6968), 837–841. doi:10.1038/nature02205 PMID:14685238 Roloff, G. J., & Kernohan, B. J. (1999). Evaluating reliability of habitat suitability index models. Wildlife Society Bulletin, 27, 973–985. Scotts, D., & Drielsma, M. (2002). Developing landscape frameworks for regional conservation planning; an approach integrating fauna spatial distributions and ecological principles. Pacific Conservation Biology, 8, 235. Sinclair, S. J., White, M. D., & Newell, G. R. (2010). How useful are species distribution models for managing biodiversity under future climates. Ecology and Society, 15, 8. Soberón, J., & Peterson, A. T. (2005). Interpretation of models of fundamental ecological niches and species’ distributional areas. Biodiversity Informatics, 2(0), 1–10. doi:10.17161/bi.v2i0.4 Stockwell, D. (1999). The GARP modelling system: Problems and solutions to automated spatial prediction. International Journal of Geographical Information Science, 13(2), 143–158. doi:10.1080/136588199241391 Stockwell, D. (2006). Improving ecological niche models by data mining large environmental datasets for surrogate models. Ecological Modelling, 192(1-2), 188–196. doi:10.1016/j.ecolmodel.2005.05.029 Thomas, C. D., Cameron, A., Green, R. E., Bakkenes, M., Beaumont, L. J., Collingham, Y. C., ... Williams, S. E. (2004). Extinction risk from climate change. Nature, 427(6970), 145–148. doi:10.1038/ nature02121 PMID:14712274 Thuiller, W. (2004). Patterns and uncertainties of species’ range shifts under climate change. Global Change Biology, 10(12), 2020–2027. doi:10.1111/j.1365-2486.2004.00859.x PMID:25200514 Thuiller, W., Araújo, M. B., & Lavorel, S. (2003). Generalized models vs. classification tree analysis: Predicting spatial distributions of plant species at different scales. Journal of Vegetation Science, 14(5), 669–680. doi:10.1111/j.1654-1103.2003.tb02199.x

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Thuiller, W., Lafourcade, B., Engler, R., & Araújo, M. B. (2009). BIOMOD–a platform for ensemble forecasting of species distributions. Ecography, 32(3), 369–373. doi:10.1111/j.1600-0587.2008.05742.x Thuiller, W., Lavorel, S., Araújo, M. B., Sykes, M. T., & Prentice, I. C. (2005). Climate change threats to plant diversity in Europe. Proceedings of the National Academy of Sciences of the United States of America, 102(23), 8245–8250. doi:10.1073/pnas.0409902102 PMID:15919825 Vetaas, O. R. (2002). Realized and potential climate niches: A comparison of four Rhododendron tree species. Journal of Biogeography, 29(4), 545–554. doi:10.1046/j.1365-2699.2002.00694.x Wisz, M. S., Hijmans, R., Li, J., Peterson, A. T., Graham, C., & Guisan, A. (2008). Effects of sample size on the performance of species distribution models. Diversity & Distributions, 14(5), 763–773. doi:10.1111/j.1472-4642.2008.00482.x Woodin, S. A., Hilbish, T. J., Helmuth, B., Jones, S. J., & Wethey, D. S. (2013). Climate change, species distribution models, and physiological performance metrics: Predicting when biogeographic models are likely to fail. Ecology and Evolution, 3, 3334–3346. PMID:24223272 Xu, T., & Hutchinson, M. (2011). ANUCLIM Version 6.1. Fenner School of Environment and Society. Canberra: Australian National University. Yost, A. C. (2008). Probabilistic modeling and mapping of plant indicator species in a Northeast Oregon industrial forest, USA. Ecological Indicators, 8(1), 46–56. doi:10.1016/j.ecolind.2006.12.003

This research was previously published in the Handbook of Research on Advanced Computational Techniques for SimulationBased Engineering edited by Pijush Samui, pages 148-170, copyright year 2016 by Engineering Science Reference (an imprint of IGI Global).

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Section 4

Utilization and Applications

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Chapter 37

Information Societies to Interactive Societies:

ICT Adoptions in the Agriculture Sector in Sri Lanka Uvasara Dissanayeke University of Peradeniya, Sri Lanka H.V.A. Wickramasuriya University of Peradeniya, Sri Lanka

ABSTRACT Information is crucial for the development of any sector, including agriculture where information needs to be exchanged with farmers and other stakeholders quickly. Thus, efficient linkages for information sharing are essential. ICT innovations enable the shaping and reshaping of communication and interaction. Many of the technology driven information dissemination methods have been initiated by government, private, non-profit making bodies and independent research groups. This chapter explains the integration of ICT within Sri Lankan agriculture communities and how the focus is changing from information dissemination towards facilitating interactions among the stakeholders. The present status of agriculture information dissemination, including the ICT interventions is given. Prevailing issues and limitations in these ICT-based information dissemination approaches initiated by the different entities is explained, giving due recognition to various factors that have contributed to the adoption of ICT initiatives. The chapter ends outlining the possibilities for future focus on ICT activities in an agriculture information society.

AGRICULTURE INFORMATION SOCIETY Agriculture plays an important role in the Sri Lankan economy. Agriculture provides a direct source of income for around 31% of the population (Central Bank of Sri Lanka, 2013b). The rural population in Sri Lanka is around 85% (World Bank, 2014), and agriculture is both a direct and indirect source of living for about 65% of the population who live in these rural areas. The contribution of agriculture to the country’s gross domestic production is about 10.8% (Central Bank of Sri Lanka, 2013a). DOI: 10.4018/978-1-5225-9621-9.ch037

Copyright © 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Information Societies to Interactive Societies

Right information delivered at the right time is vital for successful farming. Farmers need information regarding crop growth, pest and disease problems, and marketing. A study conducted by De Silva and Ratnadiwakara (2008) reports that information search cost accounts for 11% of the total cost, and nearly 70% of the transaction cost. Information search costs arises from the need to obtain information related to decisions such as the crops to plant, agronomic practices, pest and disease identification and management, harvesting, storage and post-harvest practices. Information systems which provide the required information are described in Table 1. Transaction costs are incurred in transactions related to the purchase of inputs such as seed, fertilizer, and pesticides, and also in the sale of produce. Additional transaction costs are seen when farmers deal with external agents indirectly through Farmer Organizations. In such instances transaction costs arise between farmers and the Farmer Organizations, and also between the Farmer Organizations and the external agencies such as input suppliers or buyers. Appropriate information systems can reduce the transaction costs incurred in such situations. At present most of the information obtained, and transactions conducted are through traditional mechanisms. Generally in Sri Lanka farmers have been obtaining information through the farm visits of, or the office visits to, extension agents. Thus, if the time spent by the farmers for this activity is taken also into account appropriately the information cost is bound to increase. Furthermore, it is noted that this cost analysis is from the perspective of the farmer. When the time and other associated cost, such as the transport cost, of the extension agent is also taken into account the actual cost of such information would vastly increase. Hence mechanisms which obviate the need for such meetings could reduce the associated information costs. ICT mechanisms are very well positioned for this, thus being able to reduce this information costs. It is not argued that ICT mechanisms are appropriate for all situations. Rather, that it would be appropriate in many situations. The reasons for such an assertion are as follows. Unlike in mass communication, or even group communication methods adopted in agricultural extension, the information provided through ICT mechanisms could be tailored to the particular requirements of the specific farmer, as in the traditional individual extension methods. For example, the requirements for a particular crop, or variety, could be provided. The needed information could be obtained irrespective of the location of the farmer. Transport and time costs too would be almost eliminated. Interactivity, which is not generally used or possible through many other information providing channels, could also be used. For example, Smartphones could be used to take photographs of field problems such as pests or diseases which are sent for possible identification, after which requests for further information, or recommendations for the management of such problems, or the links to the appropriate information which is already available could be sent back to the farmer. The added advantage of this mechanism lies in the fact that if the first level of personnel handling such requests are unable to provide the information that they can channel it to increasingly higher levels of experts, according to the nature of the question, and then respond to the information seeker. Access to such higher levels of expertise would not normally be possible for most information seekers. Even in instances where such access may be possible, the time taken for access to personnel and awaiting their response could possibly lead to a situation where the response is of lesser value due to the associated delays. For example, measures against a pest or disease attack should be taken as quickly as possible. Even a delay of a few days could lead to substantial losses. A further advantage lies in the fact that the proficiency of the limited experts could be more widely utilized to service a larger group of people. Thus, the expertise of officers based in central stations could be utilized from almost any area of the country. There are many traditional sources of agricultural information as seen in Table 1. Technical advice was traditionally provided by extension agents, including subject matter specialists, attached to various 830

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Table 1. Agriculture information sources which cater for farmers information needs Sources of Information

Information Needs

Input suppliers (Agro chemical merchants)

• Seeds and planting materials • Agro chemicals: fertilizers, pesticides, herbicides • Agriculture equipment, machinery

Markets /buyers

• Market prices • Places

Extension agents

• Technical advice • Training opportunities, demonstrations, plant Clinic • Government subsidy schemes, loans

Subject matter experts and researchers

• Solutions for farm management practices • Latest innovations

Mass media

• Weather information • Market prices

Farmer organization

• Cultivation plans • Water availability

1920 Agri advisory service

• Technical information related to farming • Purchasing inputs • Marketing

Sources (Dissanayeke & Wanigasundera, 2014; Wijerathna, 2011; Dissanayake, Wijekoon, Madana, & Wickramasinghe, 2009)

government departments and institutions. For example, the Department of Agriculture had a vast network of field level extension agents who catered to the needs of farmers in the food crop sector. However, it is noted that this coverage has been greatly diminished due to the transfer of the field level extension agents to another department. Technical advice on crops such as tea, rubber and coconut, as well as information on subsidy schemes are provided by different agencies related to these crops. Whilst these agencies use mass media too, the 1920 Agri-Advisory Service is a telephone based service introduced by the Dept. of Agriculture. However, as seen in Table 1, apart from these sources there are numerous other information providers too. Though information suppliers like input suppliers are likely to be biased, farmers obtain information from them due to the relative convenience. Whilst physical markets also provide marketing information, its range and accuracy is certainly limited. Accordingly, most of the traditional information sources could be vastly improved as seen by the steps already taken, as given in this chapter, and also by initiatives that could be taken in the future.

Information Needs of the Farmers As mentioned previously, farmers need information throughout the cultivation process until they harvest and sell the products. De Silva and Ratnadiwakara (2008) proposed a six stage value chain for agriculture information starting from the decision on which crop to cultivate until selling the harvest. During the first stage the farmers have to decide on several aspects such as which crop to cultivate, the extent of land to be allocated for a particular crop, when to start cultivation, and making arrangements for working capital. Selecting a suitable crop would be depending on many factors such as climatic conditions, season of the year, availability of seed and other raw materials including labour and, fertilizer. The second stage is where they purchase or use their own seeds saved from previous cultivations. Land preparation and planting is regarded as the third stage in which plant beds are prepared and sub-

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sequently planting seeds. During this stage the farmers have to decide on labour; whether to hire or use family labour, and use of machinery in land preparation. Growing is the fourth stage in the agriculture value chain, where farmers are faced with issues such as managing pest attacks, diseases, irrigation, fertilizer, weeding. During this stage, the farmers look for fertilizer and subsidy programmes. In the next stage farmers engage in harvesting, sorting and packing. During this period they have to find labour for harvesting, storing spaces. They would also look up to information on post-harvest management and value addition too. Selling represents the last stage of the value chain in which farmers have to make decisions on market prices, places to sell the produce and transport arrangements. Accordingly a farmer has to take numerous decisions regarding the cultivation of crops. Thus, a farmer is basically a manager who has to make numerous decisions from selection of crop to ultimate sale of produce. Thus, decisions support systems, which go beyond just the provision of generalized technical information, are needed for commercial farmers. A pilot product for such a decision support systems for the vegetable sector has been developed by one of the co-authors with the collaboration of many other technical personnel. It provides information to help decide what vegetable to grow, seed requirements, cultivation practices, input requirements including labour for specific growing areas, pest and disease control measures, harvesting and post-harvesting practices. The costs and returns of all these practices, as well as the cash flows and the overall income and expenditure are provided to facilitate farmers to take decisions. In certain areas of the country farmers make collective decisions at the Farmer Organization level with respect to field and irrigation channel maintenance activities, as well as cultivation aspects such as cultivation dates and crops. Collective decisions are especially important when dealing with external agencies as in agreements related to Forward Sales Contracts, where Farmer Organizations could agree to provide a crop to a particular purchaser at agreed upon prices. In such instance access to market information to negotiate prices would help in reducing associated transaction costs. Furthermore, such systems should facilitate communication between the Farmer Organizations, or network/s of Farmer organizations, and the produce buyers. As Farmer Organizations make collective purchases of inputs, such as fertilizer, these information systems should enable the aforementioned communication abilities with potential suppliers of agricultural inputs too. As indicated the need for information in agriculture is very wide. This need is further expanded as it includes a very large number of entities requiring widely differing types of information. In terms of sectors it needs to cater to the sectors such as crop, animal husbandry, and fisheries. Within a sector such as the crop sector it needs to cater to differing segments such as the food crop sector, the plantation sector, the protected agriculture sector, the floriculture sector, and the food processing sector. Within each segment it needs to provide information on crop and variety selection, cultivation practices, pest and disease management, harvesting and post-harvest practices as well as marketing information. Due to this diversity it is essential that an overall strategy to provide agricultural information take cognizance of this fact. Accordingly, multiple initiatives, rather than just a few, are needed by different players to provide the information requirements in agriculture. Institutions, which have developed strong ICT capabilities and initiatives, such as the Department of Agriculture, could be supported to provide advice and training to other agriculture organizations to develop their own information services. Such a mechanism should provide for new initiatives from the different organizations, to enable adaptation and innovation to develop and deliver products most suited for their clientele.

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Arising from the diversity of requirements noted above, another perspective is possible in terms of Agricultural Information Systems. Roling (1988) in his work on Agricultural Knowledge Systems identified many sub-systems such as the research, dissemination (or extension), user (or farmer), training, input supply/ marketing, policy, and NGO sub-systems. This view broadens the scope of agricultural information systems, indicating user needs beyond that of the farmer. An overall information strategy for the agricultural sector certainly needs to take account of all these needs. Clearly priority areas of importance, and possibility, need to be the initial initiatives. However, an overall strategy should not get bogged down only with the initial initiatives, and their maintenance, but also forge ahead to meet the other information requirements too.

Traditional Systems of Agriculture Extension Traditionally, the scientific research and new knowledge related to agricultural practices were delivered to farmers through a process of farmer education, aiming to increase produce and productivity of agriculture. Provision of such information can lead to improved yields (Rosegrant & Cline, 2003). This process of disseminating agriculture information is known as agricultural extension whilst a village bound extension agents typically play the main role in bridging the gap between research and practice. A variety of teaching methods, such as individual methods e.g farm visits, group methods e.g. demonstrations, and mass methods e.g. television and radio programmes are used to educate the beneficiaries. In a given agriculture education system, learning could take place along four paradigms; technology transfer, advisory work, human resource development, and facilitation and empowerment (National Agricultural and Forestry Extension Service [NAFES], 2005). Technology transfer involves a top-down approach to deliver specific recommendations related to cultivation practices the farmers need to adopt, while advisory services help farmers in clarifying problems, by responding to their queries with technical prescriptions. Facilitation for empowerment involves facilitating experiential learning and farmer to farmer exchanges. Farmers are encouraged to make their own choices, by interacting with each other. However, it is seen that the traditional methods of information dissemination have become less successful and less cost effective due to various reasons. The average number of farm families to be served by a single extension officer has exceeded 4000, which is an extremely hard target to achieve. The withdrawing of grass root extension workers from extension activities and overburdening of extension workers with duties other than provision of extension services are two of the other constraints that affected the agriculture extension system in Sri Lanka. Decentralization of the extension services to provincial government has weakened the extension service seriously affecting the research –extension linkage, and the efficiency of the national agriculture extension system. Weak knowledge management systems especially in the areas of information sharing, dissemination of information, and agricultural extension is being regarded as one of the major challenges ahead of agriculture research and extension today. Given the fact that many farmers are literate, and the growth of ICTs in the recent years, integration of ICT is seen as one of the promising solutions, which can be used to provide up-to date information to the agriculture sector. The efforts to harness ICTs in reaching agricultural communities were evident during last decade, when looking at the investments made by the agriculture organizations, including major projects such as the cyber extension project, which will be discussed later in this chapter. A number of agriculture based organizations have started websites and have started offering web based services.

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Access to ICTs Compared to other low income countries Sri Lanka performs exceptionally well in its affordable ICT services, as it has remarkably lower mobile broad band prices (International Telecommunication Union [ITU], 2012). The ICT development index (IDI) ranks Sri Lanka in 105th position in year 2011, out of 155 countries. The same index places Sri Lanka at 50th position in terms of ICT prices. Table 2 shows the sub-indices used to calculate the IDI, and the rank of Sri Lanka based on the sub indices. Sri Lanka provides one of the lowest mobile –cellular prices thus being ranked in the 14th position in the mobile– cellular price category of the IDI. Mobile subscriptions per 100 people is as high as 99.2 at the end of year 2013 (TRCSL, 2013). It is noted that this value does not indicate the percentage of subscribers as it is fairly a common practice in Sri Lanka to have multiple subscriptions, probably due to the fairly low cost, and in some cases, free availability of such mobile subscriptions.

Internet Sri Lanka has a well developed broadband infrastructure; however the penetration is relatively low. Fixed line penetration is 2.35%, while mobile broadband subscriptions are around 5.9% (Telecommunications Regulatory Commission of Sri Lanka [TRCSL], 2013). At present there is a well developed broadband market, with different fixed and mobile operators providing broadband services through different technologies. There is a potential to increase the broadband use in the future. Both the TRCSL and the Information and Communication Technology Agency of Sri Lanka (ICTA) have made broadband access a policy focus. Examples of recent ICT development projects include the setting up of over 500 rural tele-centers, a subsidy scheme to build and operate a fiber backbone in rural areas, and the development of e-government applications (ITU, 2014).

Literacy The adult literacy rate in Sri Lanka is around 91% (Central Bank of Sri Lanka, 2013b) which indicates that the majority of the population, including the farmers, can read and write. High literacy levels give a definite advantage in using various ICT resources, and it is an important factor to be considered in planning for information and communication interactions. Table 2. IDI sub indices and rank of Sri Lanka (Source ITU, 2012) Index

Sub-Indices

Rank 2011

ICT access/ readiness infrastructure

fixed-telephony mobile telephony international Internet bandwidth households with computers households with Internet

103rd

3.3

ICT intensity/ Usage

Internet users fixed (wired)-broadband mobile broadband

112th

0.67

ICT capability or skills

adult literacy gross secondary enrolment gross tertiary enrolment

98th

6.45

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ICT INTERVENTIONS There are many ICT based interventions to serve the agriculture society in its various stages of the production process. Some projects stand out due to its coverage of population, publicity and investments: Among these are, the government initiated a cyber extension project, agri-advisory service, and other collaborated projects on SMS based market price dissemination systems. Websites are the most commonly adopted web technology by most of these organizations, which is similar to the observations reported by Rhoades and Aue (2010) who studied the use of social media in agriculture information dissemination. Use of social network sites like Facebook or micro blogging sites such as Twitter is not commonly seen at the organizational level. Interactive Voice Response (IVR) methods are still at research level and are successfully tried out with smaller communities. This section discusses some of the important ICT interventions that attempted to use ICTs in reaching various levels and categories of the farming community.

Cyber Extension Project The DOA initiated a cyber extension project way back in 2004 as an “appropriate information exchange mechanism which seems affordable and convenient for rural farmers in satisfying their information needs” (Wijekoon, Emitiyagoda, Rizwan, Rathnayaka, & Rajapaksha, 2014). This was established in two phases; as a wireless extension strategy at first and as a real cyber extension mechanism with internet and telecommunication facilities as the second phase. It was felt necessary and important that farmers were provided with necessary information needed in the various stages of the farm decision making process and the extension system was facing criticisms that it was not being able to satisfy the information demands from the farmers. The Department of Agriculture was thus looking for alternative methods powered by the latest ICTs and their solutions is to introduce computer based learning to the farmer community. Forty five agrarian service centers, out of the 550 centers, were selected to establish cyber extension units (CEU). A cyber unit was provided with a computer, digital camera, internet facility, telephone, printer and a scanner, similar to a rural information center with the aim of supporting the agriculture community in the area. Thus, a set of Interactive Multimedia CDs (IMMCDs) were designed as an offline cyber extension strategy to provide crop related information to the farmer community. Typically a CD contained information on various aspects of the growth of a particular crop including cultivation and management aspects of crops such as chili, big onion etc. There are also a few CDs which present information on more general topics such as ‘integrated pest management’, home gardening, and micro irrigation, which discuss important management practices that are common for a group of crops. The learning contents in the CDs were developed with the assistance of Research Officers who verified the technical information. These IMMCDs included video clips, audio narrations, graphics, images and text based illustrations. The extension agent is to act as the officer in charge of the cyber unit while farmers can use the CDs when they visit the extension agents’ office and learn the technical information provided in the CDs. The extension officer may also use the CDs in farmer training classes to design training aids. A list of IMMCDs that have been produced by the Department of Agriculture and is available in the sales outlets is presented in Table 3. These CDs are available mostly in Sinhala, some in Tamil, and a few in English. Lack of awareness of the cyber mechanism was seen as one of the major problems according to (Wijekoon et al., 2014). Later the DOA had taken steps to popularize the CEUs among farmers. However

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Table 3. List of CDs available in the cyber extension units (Source Department of Agricutlure Sri Lanka [DOA], 2010) Languages [S] –Sinhalese, [T]- Tamil, [E] – English

Title of the CD Anthurium

[S], [E]

Banana cultivation

[S]

Bean cultivation

[S]

Betel

[S]

Big onion cultivation

[S] [T]

Brinjal cultivation

[S] [T]

Chili

[S]

Coconut (I, II)

[S]

Compost making

[S]

Cucurbitaceae plants

[S]

Forages

[S]

Gerbera cultivation

[S]

Home gardening

[S]

Integrated pest management

[S]

Jack

[S]

Leafy vegetables

[S]

Maize cultivation

[S]

Micro irrigation

[S]

Mushroom (I, II)

[S]

Orange /Citrus

[S]

Orchid

[S]

Paddy

[S] [T]

Papaya cultivation

[S] [T]

Potato cultivation

[S]

Protected agriculture

[S]

Pulses

[S]

Rambutan cultivation

[S]

Red onion cultivation

[S] [T]

Royal botanical garden

[E]

Soil conservation

[S]

Tibbatu

[S]

Tomato cultivation

[S] [T]

Underutilized fruit crops

[S]

Upcountry vegetables

[S]

Vegetable insect pests

[E] [S]

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there are other problems such as poor computer skills by the farmers to use CDs on their own (Dissanayeke, Wickramasuriya, & Wijekoon, 2009). Certain farmer groups are seen more confident in using CDs to obtain information. These are the well-educated and mostly part time farmers who have a main source of income other than agriculture. Some of them even had computer facilities in the home and they made copies of these CDs for later reference. However the majority of the famers had to mainly depend on the cyber extension unit to use these CDs, while they need the extension agent’s assistance to select the relevant pieces of information. This interferes with the schedule of the extension agent because he is pre-occupied with other major responsibilities, rather than only managing the CEU. Considering this difficulty, the DOA is planning to appoint a separate officer to manage the CEU and help with farmers to find the necessary information. The IMM CDs have an interactive user interface where the users have some control in selecting what information to be viewed and when. This can be considered as a positive development because farmers, being adult learners, need to have some control over what they want to view. However the best uses of these could not be harnessed by many farmers mainly due to the poor computer skills and less access to computer facilities. A substantial amount of resources has been expended to develop good ICT material such as the IMM CDs for the food crop sector in Sri Lanka as mentioned above. However, as with any other information source, it is important to continuously update such material. While updating may not be as glamorous and rewarding as the initial development of a product, it is very important to ensure that the information seekers are provided with current information. Apart from the greater fulfillment of the information needs leading to greater customer satisfaction, it will also enhance the trust and credibility of these sources of information. This is especially so when such material becomes available online. To facilitate such updating and appropriate technical system, key responsible persons whose work will be appropriately recognized, adequate support staff and financial allocations are important. Another important consideration of the cyber extension project is to link farmers with the other major agriculture stakeholders such as, wholesale traders, researchers and policy makers. It is considered necessary and important to regulate the information flow between stakeholders i.e. researchers and farmers, farmers and policy makers, farmers and traders. It is expected that this would enable farmers to make email queries to researchers seeking technical assistance to solve field problems. However this objective is achieved to a lesser extent so far due to limitations such as low computer literacy of farmers, Extension officers are overburdened with responsibilities other than managing the cyber unit and assisting farmers to send emails will add to their already heavy workload.

Marketing Information Systems According to Dharmaratne (2013), Sri Lanka had commenced an Agriculture Market Information System (AMIS) as early as 1980s. Market data had been collected, analysed and finally disseminated to interested parties. The main purpose of the system was to measure food security and provide price signals to agriculture marketing stakeholders including the small farmers, traders and policy makers. AMIS had been initiated as two bulletins; a weekly publication that included information on wholesale and retail market prices of nine food items, including price comparisons with the previous week, producer price, statistical indicators such as range and average price. The bulletin was made available for policy makers, general public, and media agencies. The second publication was a monthly information system, which provided key indicators of prices, production, crop situation and food stocks.

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Some of the major problems with the initial years of implementing AMIS were poor understanding of the purpose of data and information collection, underutilization of data and information, ineffective communication and presentation, lack of internationally comparable and compatible methodologies for data and information handling and limited capacity of national programs. Farmers were also unable to use the system as the information provided by the system was limited to a few crop types. These were hardly enough to make right decisions. In addition the small farmers and traders were not skilled enough to interpret some of the data presented in the bulletin. It is also noted that these earlier systems did not meet the actual needs of farmers for real time information. Whilst this information is certainly useful for academic studies and policy decision makers, its utility to farmers is limited. However, present data collection, analysis, and dissemination possibilities have enabled the rapid collection and provision of user required specific information almost in real time. Thus, the use of present day Agricultural Marketing Systems by farmers too is bound to increase. However other stakeholders such as policy makers, scientists, and academics are also able to use the system in a useful way.

Agriculture Advisory Service A call centre solution known as Agriculture Advisory Service is implemented by the DOA as a supplementary service to the present extension system in the country. This is foreseen as a quick mechanism of disseminating agriculture information to strengthen the linkages between research, extension, training, and farmers. This type of a system helps to facilitate a demand driven extension service, as the farmer initiates the communication process. The extension officers, working in the call center, assist farmers in solving their various problems such as agriculture related technical matters, inputs and marketing problems. The service, which is available in the local languages, receives nearly 100 to 250 calls from the agriculture community every day and is regarded as one of the most wide spread ICT related agriculture activites in Sri Lanka (Dissanayake et al., 2009; DOA, 2010; Wijerathna, 2011). A study conducted by Dissanayake et al. (2009) reports that the farmer community is satisfied with the information provided, while the field extension staff regards the service as an effective solution which eases their work at the field level.

Mobile Based Information Services Mobile based information dissemination methods recieved wide attention in the recent years mainly due to the availability of mobile phones among people in Sri Lanka, including the farmers. A recent study shows that about 73% of the rural farmers have access to a mobile phone while some extended farm families had access to more than one mobile phone at a time (Dissanayeke & Wanigasundera, 2014) making it a common household item. When compared with the use of computers with internet facilities, the mobile phone was found to be the most common ICT facility among the farmers. Wide usage and accessibility to mobile phones has given opportunities to see how to use mobile based information systems in reaching the farming community. Short message service (SMS) based systems to send market prices, toll free call line facilities to inquire about agriculture based queries, and interactive voice response systems have been experimented with, and later some used by government, private sector, non-government based organizations as well as by independent research groups. Some of the important mobile based initiations are discussed later in this chapter.

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Use of mobile SMSs to deliver important pieces of information has become popular worldwide due to the simplicity, effectiveness and low cost (Dhaliwal & Joshi, 2010; Fafchamps & Minten, 2012). Information related to commodity prices, market opportunities, crop advisory, and weather information are the main types of information that are sent to farmers using SMSs in the above studies. Many farmers preferred to have these informative SMSs as it is an inexpensive way to get access to important information. Given this fact that the present access and use of mobile devices is very high, and also that it could be expected to grow even further, this should be seriously considered as a tool that would have even more importance in the future. Initiatives should not be limited to basic cell phones but should cover applications for Smartphone too. While the majority of the present farming population may not own Smartphone yet, their prices will undoubtedly come down making them more affordable. Further, given the large number of migrant workers who have gone overseas from rural areas, the want for communicating with them will propel more people to purchase Smartphone even as prices come down as well. Thus ownership per se of Smartphone in the rural areas is bound to increase. Even if people may not have their own Smartphone, they are bound to have access to them through other rural people who own them. If the information is valuable enough farmers will probably be willing to pay enterprising people who could look up the information on behalf of the farmers for a small reasonable charge. Owners of communication centres that are spread all over the country could be one group that might show interest in such an enterprise.

Mobile SMS Based Price Information Dissemination Services “Govi Gnana Seva” The Govi Gnana Seva (GGS) project started as an independent price collection and dissemination service to help farmers get the best possible prices for their produce. This is one of the pioneer projects to initiate sending vegetable market prices to farmers in Sri Lanka (De Silva, 2008). The project operated from the Dambulla Dedicated Economic Center from where vegetable spot prices are collected and then sent by SMSs to the farmers who are registered with the system. Traditionally low farm-gate prices, especially for perishable crops such as vegetables, have been reported even when consumer prices for the same products are relatively much higher. Whilst the low bargaining power of individual small scale farmers is one factor, another factor is their lack of knowledge regarding the prevailing wholesale prices in major agricultural markets closer to the urban areas. Hence, the attempts to fill the information gap between farmers and markets became significantly important. Later the GGS project started a partnership with a leading mobile company and continued to offer the service on a Tradenet platform (Dialog Axiata PLC, 2009). They have also expanded the service to collect price information from 2 other dedicated economic centers. The system can match the buyers with possible sellers and send alerts to both parties with their respective contact details (de Soyza, 2014). The buyer and seller can negotiate and proceed with the transactions. Buyers and sellers can upload posts to the Tradenet using web, WAP, call centre and IVR, SMS and USSD access technologies using English language or the two local languages.

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Interactive Voice Response (IVR) Systems IVR System for Mushroom Farmers The Ruhunu University together with a private mobile service provider developed an Interactive Voice Response (IVR) system to educate small-scale mushroom farmers. This is implemented as a technology dissemination programme under the Life Long Learning for Farmers (L3F) employing ICT for one of its components. The IVR system embedded pre-recorded messages of two minutes duration for six months to guide listeners on how to establish, and manage a mushroom shed. Business planning and financial management lessons are also included (Wijeratne & Silva, 2013). About 5000 farmers have taken part in the programme. Farmers are able to obtain needed information quickly and accurately using ICTs. The study reports that the majority have accessed the knowledge system, which can be considered as a positive development. They have listened to the voice mail during their free time. Poor feedback from farmers is seen as one of the limitations by the researchers. The L3F have recently started a similar programme in collaboration with the Open University of Sri Lanka (OUSL) and the same mobile service provider to offer financial management lessons to rural women using IVR systems.

Agricultural Price Information Index In the recent years a government based agricultural research institutions have started offering daily whole sale vegetable price information, collected from eight markets Island wide with the assistance of a private mobile service provider, one of the leading mobile service providers in the country (Hector Kobbekaduwa Agrarian Research and Training Institute [HARTI], 2014; Mobitel Pvt Ltd, 2014). The service is made available in the two local languages using an Interactive Voice Response System (IVR) to the customers of the same mobile service provider. The callers have to bear the cost for using the IVR system.

Decision Support Systems Social Life Network Social Life Network (SLN) is an attempt in developing a holistic mobile based system to aid farmer information needs, throughout the farming life cycle (De Silva, Goonetillake, & Wikramanayake, 2012). The SLN will address issues such as ‘how to strengthen the linkages among various agriculture stakeholders using mobile based systems’, and ‘how to capitalize on the latest mobile technologies such as inbuilt sensors and processing capabilities’. As implied in its name, this system intends to create a network of the users, who would generate real time information, through their participation in the SLN, which will eventually be accessible for the same user community in return. It is assumed that such systems would eventually help the stakeholders to make informed decisions by opening up opportunities for predictive models to strengthen the decision making process. Mobile interfaces of the SLN have been continuously tested with the stakeholders, using action research approaches, to assure user-friendly and usable designs

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Websites The Internet and websites play a major role in today’s information culture. A website can be used to post important information that could make the farming community instantaneously aware of relevant information (Reddy & Ankaiah, 2005). Websites can further act as an important medium to ensure the dissemination and sharing of essential agriculture information that fits the agriculture community’s interests and needs. A content analysis study, which evaluated 27 agriculture related websites in Malaysia, concludes three important categories of information that should be there in agriculture websites namely technical information with regard to crops, fisheries, and livestock, training opportunities offered by the institutions, and the financial aspects related to capital, loan facilities and interest rates (Ramli, Hassan, Samah, Sham, & Ali, 2013). A number of agriculture related organizations in Sri Lanka have marked their web presence (Table 4) providing useful information for the visitors. In fact reports do indicate a high impact on the agriculture sector, next to the telecommunications sector (Jayathilake, Jayaweera, & Waidyasekera, 2010). The types of information and services available through these websites include; technical information related to crop and livestock, marketing information, online services, training opportunities, organizational structure and administrative divisions, vision and mission, news briefs, and contact information. Almost all the websites are available in English, while the majority has accommodated Sinhalese language as well. Only a few websites have the complete Tamil translations, while this facility is under construction on many sites. For systems where the target group is the farmers, in most instances the content material will have to be in both local languages which are Sinhala and Tamil. As the availability of the same content in both languages is not seen on all sites, this needs to be done. Hence efforts for automatic translation from one language to another needs to be enhanced. Such a facility, together with verification by experts, should be used to enhance the efficiency and reliability of having the content in both languages. To the extent possible, English versions are to be made available to meet requirements of multi-lingual companies and NGOs, as well as other users such as students. The Department of Agriculture (DOA) website has been recognized both locally and internationally for its pioneer work in using ICTs for agriculture information dissemination in Sri Lanka. According to the website statistics, the number of hits exceeded 3 million as of 2014 whilst thousands of online users visit the website every day. This website has been recognized as the best website among the government websites over several years and provides an example for the other websites which followed. Thus we discuss some of the important features in the DOA website, which is of prime importance to understand the agriculture information culture in the country.

Technical Information Dissemination Most of the websites presented in Table 4 have made efforts to share technical information related to cultivation aspects in their websites. Online learning resources, including pdf versions of printed publications, and video documentaries are most commonly used to achieve this objective. The DOA website publishes technical information related to important crop varieties that are grown in the country under the crop recommendation section. These crops belong to the food crop sector including rice, vegetables, fruits, grains, tubers, oilseed crops and condiments. Specific information

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Table 4. Websites of some of the main (government) agricultural organizations Organization

Some of the Important Features

Department of Agriculture (DOA) http://www.agridept.gov.lk

• Technical information dissemination – Video documentaries, online learning resources, publications • Market information • Training opportunities • Languages–Sinhalese, Tamil, English

Institute of Post Harvest Technology (IPHT) http://www.ipht.lk

• Technical information dissemination • Training opportunities • Languages: Sinhalese and English languages only

Department of Export Agriculture (DEA) http://www.exportagridept.gov.lk

• Subsidy schemes • Farm gate prices of export agriculture crops • Technical information dissemination related to crop management practices • Video documentary • Training opportunities • Languages

Tea Research Institute (TRI) http://tri.lk

• Technical information dissemination – list of publications and advisory circulars • Languages: Sinhalese and English languages only

Rubber Research Institute (RRI) http://www.rubberdev.gov.lk

• Technical information dissemination – online learning resources • Price information • Download applications for various services offered by the institution • News updates • Statistics • Languages – English, Sinhalese, Tamil

Rubber Development Department of Sri Lanka (RDD) http://www.rubberdev.gov.lk

• Services- subsidies, extension services • Download applications • Statistics • Price information

Coconut Research Institute (CRI) http://cri.gov.lk

• Technical information dissemination using, online learning resources, publications, and video documentaries • Online forms to make inquiries • News updates • Languages: English, Sinhalese, Tamil

Coconut Cultivation Board (CCB) http://www.coconut.gov.lk

• Technical information dissemination using online learning resources. • Subsidy programmes, credit facilities and loans facilities • Download loan applications • Crop input prices • News and event information • Languages: English, Sinhalese, Tamil

Coconut Development Authority (CDA) http://www.cda.lk

• Information on key products • Online directory to find exporters and traders • Publications • Statistics • Languages: English, Sinhalese, Tamil

Department of Animal Production and Health (DAPH)

• Online application portal to apply for import and export permits • Publications • Livestock statistics

Hector Kobbekaduwa Agrarian Research and Training Institute (HARTI) http://www.harti.gov.lk

• Display market information • Publications • Facilities available • News and events

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related to the nutritious value of the produce, recommended varieties, suitable climatic conditions, and crop management practices such as propagation, pest and diseases, fertilizer application, post-harvest handling, and value addition are presented in English and one other local language (Sinhalese). This technical information is presented in the format of online learning resources, using interactive menus to locate learning contents. Text based illustrations were the most commonly used medium, while graphics and photographs are also used appropriately to illustrate facts. Similar efforts have been made by several other organizations to disseminate technical information. It is a positive trend to observe that many of these organizations have shared their printed publications on the website as a portable document format (pdf) files, giving an opportunity for online users to download them easily without any cost. These publications otherwise have to be purchased from selected sales outlets. Sales outlets sometimes face problems when certain publications are sold out, and when the farmers who are coming for the particular publication has to wait for the next print. Some other organizations have displayed the list of publications in the webpage with the respective prices, directing farmers to the sales centers where a copy can be obtained. Publications include books, leaflets, agriculture magazines, advisory circulars, and other agro-technology based reports that are originally designed to be in the printed format. Video is a very powerful source to provide information, compared to other mediums as it can combine several media at the same time. It is seen that only a very few agricultural organizations other than the DOA is utilizing online videos to reach agriculture audiences. This situation is similar to the observations made elsewhere (Goodwin & Rhoades, 2009; Rhoades & Aue, 2010). The Department of Agriculture has a repository of video documentaries produced for national television that is made available for the online users. The DOA has its own video production unit at the Audio Visual Center where these documentaries have been produced. Thus a rich collection of more than 300 video documentaries are now available in the DOA website. The Department of Export Agriculture and the Coconut Research Institute are two other organizations that have made good use of online videos in agriculture related technical information dissemination. Both these organizations have shared these videos on YouTube, which is an important step in reaching non-agriculture audiences and especially young farmers. In fact it is important to get more agriculture related videos on such common platforms to reach a majority of the community.

Agriculture Information Management Systems The Agriculture Information Management System (AgMIS) is developed by the DOA to share information related to food crops such as cultivation extents, production or yield forecast, and contact details of the farmers and officers involved. This is an interactive system which is developed to minimize marketing problems, while it is also expected that it would provide a comprehensive database for policy makers to help in planning and decision making (Food and Agriculture Organization of the United Nations [FAO], 2014). Latest news updates related to the food crop sector is displayed in the website for the frequent visitors in English and the two local languages. Only a few organizations are seen supporting online databases to manage information on buyers and sellers. The Coconut Development Authority maintains an online directory to provide information on manufacturers and importers for interested parties. Users can search a manufacturer based on the district, product and product type using an interactive menu in this website which help stakeholders to access important information easily.

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Agricultural Price Information Use of websites to display market information is seen as one of the recent developments. As seen in Table 4, several organizations have started publishing market prices of the relevant crops as well as related products on their websites so that online users can glance through these prices before making important decisions. Some organizations are using multiple methods such as publishing on the website using interactive menus, mobile IVR based systems, and publishing as PDF documents. For instance the Hector Kobbekaduwa Agrarian Research Training Institute started publishing the daily and weekly food prices on their website for easy access. This is an interesting difference from the earlier system they had, which was available on printed format only. Wholesale, retail and farm gate prices of more than 100 commodities can be obtained through the web site in the two local languages and also in English. Interactive menu items help the users to locate and view a specific category of product easily, and this saves time as otherwise time has to be spent on browsing a long list of items. The same information available in the website is accessible using a mobile based IVR system too, as discussed under mobile based systems. Farm gate prices for all the export agriculture crops, collected weekly by the Economic Research Unit of the Department of Export Agriculture, are displayed on their website. A mobile version of the website is also available, making it easier for the export agricultural crops stakeholders to view information using a Smartphone. Information for the past few years have been saved on the website that helps users to compare prices in different years and different seasons of the year, thus making it easier in taking important decisions such as selling the produce. The Rubber Development Department is yet another organization that uses their website to publish price information. The latest information is published on the home page itself, making it much easier for the users to have a quick glance over the prices. Detailed information related to a specific year or month or a date can be obtained easily using the interactive menus.

Agriculture Related Services A comprehensive list of services offered by a particular organization is available on many of the web sites. These services include training opportunities, credit and loan facilities, subsidy programmes, provision of export /import permission, agriculture inputs, certifications and some analytical services such as soil testing. In most of these cases, the website is simply being used to create an awareness in the public of the types of services, posting a brief description of the services. A few organizations such as CCD and RRI have moved a step forward by enabling the download of a copy of an application form through the website. DAPH has an online application portal, which can be used to submit applications and track the progress of the application to obtain import and export permits, which is an interesting development. Extension and training opportunities were displayed on most of the websites mainly to make the public aware about these programmes. Furthermore, information related to credit facilities and subsidy schemes are also seen, along with facilities to download application forms from the website, as in the case of the Coconut Cultivation Board.

Information and Communication Technology Agency (ICTA) of Sri Lanka Most of the websites and the features discussed in the section above are funded by the ICTA, which is the single apex body, owned by the government, involved in ICT policy and direction in the country.

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Its work includes improving technological capacity of the country, such as building ICT infrastructure, and the ICT readiness of its people, through education and human resources development. ICTA has provided financial support to a number of agriculture based organizations to establish interactive information services that are directly related to agriculture information dissemination. A complete list of these organizations and types of services financially supported are presented in Table 5. ICTA has also supported disseminating agricultural best practices through e-Learning by funding two important projects namely Wikigoviya by the Department of Agriculture, and Navagoviya by a private organization. Wikigovia consists of an e-learning system, agri-forum to discuss agricultural issues of importance, and an agriculture Wikipedia that can be edited by users (“Wikigoviya,” 2014). The Navagoviya website is an initiation from a leading private sector company to develop and deploy e -earning and digital content to build awareness of new techniques and technologies in the agricultural sector. Most of these websites are published in English and two other local languages. Rural resource centers, with internet facilities have been established to disseminate information at the village level. These centers are referred to as “Nenasala Centers” and currently there are 667 such centers. Nenasala centers provide a range of services including high speed internet access, e-mail, telephone, computer training classes and other ICT related services. The content essential to the rural community is available to all users in the Sinhala and Tamil languages. Nenasalas also caters to the diverse needs of the village community including agriculture, fisheries, and trade, which make it an important landmark in agriculture and related information culture in Sri Lanka. ICTA has also funded a SMS enabled platform to exchange dairy product information among a small community of farmers. The system helped farmers to access a database to obtain necessary information, connect with the extension officer, the veterinarian, and other service providers. In addition a network of computers with touch screens were set up in public places for the easy access by farmers who does not have mobile phones (Mubarak, 2009).

Table 5. Interactive information services funded by ICTA (source Information and Communication Technology Agency [ICTA], 2013) Organization

E-Service Offered by the Website

Rubber Development Department of Sri Lanka (RDD)

Provide Rubber Prices

Department of Animal Production and Health (DAPH)

• Online Application Submission portal • DAPH Application Manager

Department of Export Agriculture (DEA)

Market Information

Department of Agriculture (DOA)

• Farmer Database • Classifieds - Advertising platform for farmers to sell their products • Agriculturists – to get contact information of agriculture specialists and their publications

Hector Kobbekaduwa Agrarian Research and Training Institute (HARTI)

• Weekly food prices • Daily food prices

Tea Small Holdings Development Authority (TSHDA)

Subsidy Information

Sri Lanka Tea Board

• Tea Price • Tea Directory

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PROBLEMS AND LIMITATIONS ICT adoption is seen to be moderate among the farmer community, and a large part of this success can be attributed to the growth of the telecommunication sector in the recent years. The latest ICT based inventions in the agriculture sector can be seen as more of an effort to harness the best uses of ICTs in the agriculture information dissemination process. In this context, it is more likely to expect the emergence of information dissemination systems that are more of a technology driven nature than that of user driven nature, which could be a major drawback. In the future it is more important to see how to develop systems that would cater to actual information needs of the farmer community, by getting their involvement in the design process. On the other hand we can see reasons such as cost of technology, lack of ICT proficiency, and inability to cater for the actual user needs slowing down the adoption and use of ICTs in agriculture. According to Jayathilake et al. (2010) the cost of technology can be seen as the main drawback that limit ICT adoption among farmer. Farmers’ reluctance to invest on ICT based services could be due to a low awareness of the benefits of such services, less trust on the return of the investment, and high initial cost. This especially affects small farmers who practice subsistence agriculture, who see spending on ICTs as a waste of money, and who do not see the benefits of investing on them. During the inception of ICT projects, we can see more farmers using the systems when the services are offered free of charge, and there is no financial cost to the farmer. Latterly the farmer has to bear at least a very small part of the cost such as the cost of the telephone call, which was toll free at the inception. Lack of ICT proficiency is seen as another important reason that affects the use of ICT in agriculture. For instance the unfamiliarity with mobile based technologies may lead to poor adoption of mobile SMS based price information systems. The majority of the farmers would be more conversant with the voice based services, while only a few are comfortable with SMS due to various reasons such as lack of technical know-how, and language proficiency (Wijerathna, 2011). Poor language proficiency is mainly due to the inability in using the English alphabet in sending and receiving text messages, rather than their literacy levels. Sri Lanka enjoys fairly high literacy rates due to the free education system thus there is a high potential to impart technology based education. As most of the mobile phones used in the country have English language inbuilt, it is necessary to come up with solutions to have phones with local language facilities and information systems. Interestingly the young and progressive farmers are seen mostly using these ICT based systems, and generally, low income, elderly farmers lag behind being unable to use the SMS facility. Little or no emphasis has been given on linking farmers with the other important stakeholders such as extension agents, researchers, subject matter experts, traders, and input suppliers. Even though the present ICTs can be successfully used in strengthening the existing networks, and can be used to facilitate interaction among stakeholders very little attention is paid in this regard. This does not encourage interaction between the various stakeholders and the farmer is generally unaware of who else will be there in the network. This might be one of the reasons for the poor adoption of such technologies. The other possible reasons may be lack of awareness, negative attitude of some individuals at senior management levels, and administration problems, as with the case of cyber extension project (DOA, 2010) It is seen that most of the attention is presently devoted to developing websites however the power of other web technologies such as social media, video sharing, and micro blogging has not yet being

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recognized. Rhoades and Aue (2010) noted similar observations with a group of agriculture journalists from the United States. Accordingly, most participants have seen the benefits of such tools, but some are still doubtful to adopt them because of the fear of time and resources needed.

FUTURE FOCUS The landscape of agriculture information systems is changing. Commercialization, intensification and a greater involvement of the private sector is seen. Furthermore an expansion of the food processing sector is also seen. Thus, the need for agriculture related information has changed and grown in terms of the end users as well as the need for specialized information as in the case of protected agriculture. With the drastic reduction of the field extension workers in the 1980’s, the agricultural extension role of the Department of Agriculture too has changed. The private sector and the NGO sector have undertaken the provision of agricultural extension, or information, services. However, these are but limited initiatives. The varying ICT initiatives already undertaken have tried to address this gap between the need for enhanced information and the reduction in the traditional extension services provided. There certainly is the need for more initiatives, some, if not many, of which should be from the ICT sector. An apex body, such as a joint one between the Council for Agricultural Research Policy (CARP) and the Information and Communication Technology Agency (ICTA) which are the main respective government bodes at the national level, together with representation from the private agricultural companies, the plantation companies, and representatives of the farming communities should be formed. Such a body should map out the overall policy and strategy for agricultural related ICT initiatives. Seed funding should be provided for initiatives. Funding could be under different categories serving different purposes. It could also be under different scopes to include small short term projects, as well as more complex and longer term projects. Joint proposals by a technical agricultural agency and ICT competent personnel should be encouraged. The technical agency should prove its commitment and capability to maintain such a system once developed. The rationale for the above are elaborated upon below. Whilst efforts of individual agencies and personnel do contribute to the availability of agricultural information, those would be dependent on their priorities, capabilities, and interests. When uncoordinated, such efforts may be duplicated, not completed due to the lack of competence or funds, and not adequately maintained over time. Furthermore, important areas may not be addressed. Hence, the coordination of information systems in the agricultural sector is important. The strategy for such coordination should be done by a representative body. Thus for Sri Lanka, representatives keen and committed to this initiative, from the following organizations could be considered for such a body. The Sri Lanka Council for Agricultural Research Policy (CARP) is the main body for agricultural related activities, whilst the Information and Technology Agency (ICTA) is the main organization involved in public funded ICT initiatives and thus, is in a good position to play a key role. Representation from the Ministry of Agriculture would be required to align initiatives to related policy, and also to influence the formulation of such policy. The Department of Agriculture, whilst being the main organization for the food crop sector, is also the organization that has been innovative and done the largest amount of work in agricultural ICT sector, as indicated before, and thus should continue to play a leading role in this sector. It would also be important to obtain representation from other agriculture related Departments, and the plantation

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crop sector as well, as they generate the technology and information for such sectors as well as providing the agricultural extension services. Another sector to be included would be representation from the Universities, with Faculties of Agriculture, as they represent another important source of knowledge and research in agriculture. Whilst the organizations identified above are mainly the information providers, it would be important to include the actual users of such information too to make such initiatives more demand driven. Hence the importance of key farmer representatives who are in a position to understand the possibilities and requirements from anticipated information systems. These could be from different categories identified to be important. The consideration of the needs of larger entities such as the Regional Plantation Companies, which are responsible for the management of the private plantation estates, as well as the requirements of the small-holders in these sectors too need to be ensured through appropriate participation. Similarly the requirements of the private sector agricultural organizations that are playing an increasing role, especially in catering to the more commercialized agricultural ventures need to be ensured. The requirement of NGOs for reliable agricultural information is also high since many have agricultural components in their projects, and hence their needs also should be considered. A committee comprising all those identified might be too large. However, their representation and input would certainly add value to future efforts. Hence, one way to balance these competing requirements of wider representation and a leaner committee could be to have a committee with permanent representation from the relatively more important organizations, and rotating membership of the other segments. Wide representation of this nature would enable clearer identification of key ICT initiatives that need to be focused on, coverage of a wider area in terms of both technical areas and information requirements, and better maintenance and future enhancements to the products. This forum would also enable the determination of possible lead-roles, such as the Department of Agriculture providing leadership and support to other organizations in their areas of ICT development. It could also determine those with multiplier effects, such as a base ICT system that is developed for the technical content only to be included by the different agencies. Since many agricultural organizations could lack personnel competent to develop full information systems, systems such as these would enable those organizations, normally unable to do so, to provide information to their clients through these ‘pre-written shells’ of ICT systems. The role of a committee, such as the one proposed above, should be mainly to determine overall policy, priorities, strategy, and funding mechanisms. Deliberations of such a committee should be infrequent, but well planned and prepared for, and of high intensity, whereby substantial objectives are accomplished. If implementation is to be handed over to such a committee, apart from the need for frequent meetings of the main personnel, it would also need additional support staff and other resources. Thus, a more feasible alternative for implementation of the coordination of initiatives would be the handling of such activities by an existing national level organization, such as the ICTA in Sri Lanka. Such an agency could call for proposals according to the guidelines determined by the main committee, and coordinate the selection of projects, fund disbursement, and the progress monitoring and evaluation of agricultural ICT projects, which would be then and addition to the nature of activities already undertaken by them. An agency such as this could be involved in ensuring the maintenance and thus the longer term sustainability and continued utility of these ICT initiatives. Clearly, a mechanism to propel activities towards desired goals, as determined by a representative committee as outlined above, would be to provide funding for the determined areas. Given the fact that most ICT information system initiatives are of relatively lower cost in comparison to infrastructure projects or organizational expansion, and also the relative availability of funds as countries strive to become

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more knowledge based economies and allocate funds accordingly, the availability of funds for these purposes is probably not a constraint. Funds could be provided mainly for the development of products. This funding should cover the period beyond the testing and prototype stages to actual initial use by the end users. This funding would act as an incentive for innovative ideas and possibilities. It would also enable those agencies lacking the needed ICT personnel for product development to hire them for the period needed. Whilst the major portion of the available funding could be for new initiatives, it would also be prudent to allocate funds for enhancement of previous products. In any field, and especially in ICT products, continuous improvements are almost essential. Hence, whilst the agency undertaking the initiative should be able to fund and undertake normal maintenance of the product, periodic major revisions could be supported as in its initial development. The allocation of available funds should be pre-determined based on the needs and priorities identified for ICT activities in agriculture. For example allocations could be done proportionate to both the relative importance and need of different sectors such as the crop, animal husbandry, fisheries, and food processing sectors. Even though important, the funding for an area could be curtailed if suitable ICT applications already exist for that area. Within a sector, such as the crop sector, a similar pre-determination of the allocation of funds could be done for the food crop and plantation sectors. This process could be continued to a reasonable level to ensure that adequate coverage is provided. Such pre-determination of allocations should allow for reasonable margins of cross over, whereby provisions for certain areas are increased above the pre-determined allocation, and another/others reduced correspondingly. This would minimize the acceptance of a weak proposal purely because of it falling within a given area of allocation, and also increase the acceptability of a good proposal which might not have been funded due to other better proposals being allocated the available funds for that particular area. In the allocation of funding for different areas it would be beneficial to strategically allocate funds based on short term, and probably smaller and simpler systems, as well as more long term, and probably larger information systems. Whilst many ideas for the short term could be projects with a relatively limited scope the longer term projects could be more complex and of greater scope. A mix of both would be needed. Smaller applications could be completed quicker and show results fast, thus giving a quick return on investment, as well as being a motivating factor for further work by the basically non-ICT personnel who probably would be a major group desiring to develop such systems. The areas considered could either be technical areas of importance, or areas of information systems which are complex systems akin to Enterprise Resource Planning systems of other sectors. Thus, the need for more complex systems to cater for more integrated information requirements should not be overlooked. Especially in such instances the involvement of ICT professionals should be ensured. In general the strength of a technical agency would be its personnel, knowledge base and research output in the crops or areas related to the agency. In terms of ICT initiatives a weakness in many of these agencies, especially the smaller ones, would be the lack of personnel competent enough to develop and continuously maintain information systems. Hence, it would be beneficial to promote collaboration between personnel in these organizations and ICT competent technical organizations or personnel. This could be accomplished through the specific indication of such a requirement for funding purposes. The evaluation of proposals could be based on the agricultural competence and accomplishments, as well as the ICT competence and accomplishments of the personnel involved. In an era of knowledge explosion, updating data to minimize obsolete information is essential. Furthermore, maintenance of an information system by rectifying bugs, or errors in the system, and also

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minor modifications and upgrading of the system has to be done. Thus, to enhance the continued utility, and thus the use, of the information systems developed, the capacity and commitment of an organization desiring to develop a new system, to maintain such a system in the future should be determined. Possibilities for an external agency, or agencies, to provide such backup if needed should be determined. A network of practitioners could also be promoted to help both in the initial development, as well as this latter aspect of maintenance.

Facilitation of the Interaction among Agriculture Stakeholders Use of ICT based information exchange systems is most commonly seen among young and progressive farmers. Thus, future ICT based agricultural information systems need to be able to cater to their information needs, by identifying these farmers as special target communities. While doing so it is vital to move toward more interactive systems and building communities of stakeholders those who would interact and learn from each other’s. Facilitation of interactions is important for two reasons. Firstly, farmers are likely to learn more from their colleagues than the extension agent or other authorities, as the problems they experience in the field are similar to the other farmers. They are much more likely to follow the footsteps of a successful farmer from the same community as the results are proven readily. Farmers, in general, are knowledgeable on whom to go for advice, while they relate to their own community and colleagues first when they have a problem. Secondly, the farmers would like to discuss and share what they found as a useful piece of information with their colleagues. The farmers prefer to see the opinion of the others in the community before adopting agricultural practices even when the information is passed down by the extension agent or any other important source. Thus it is necessary to create ICT based systems that can be used to facilitate interaction and information sharing among the agricultural communities. Participation of agricultural extension officers and other subject matter experts in such systems is crucial for successful functioning of such systems. These officers can initiate interactions, aware farmers on latest technologies and practices, and various other opportunities available for their training and development. Using the traditional system of extension to give away such information would be more time consuming when compared to an ICT based system. When implementing such ICT based mechanisms, we need to pay attention to three important aspects; use of existing technologies when and where applicable in order to minimize the cost, go for participatory methods in developing and implementing ICT based agriculture information systems, and providing training for target communities. Ideally we can develop applications and software to facilitate farmer collaboration using ICTs. However this could take a long time, and may involve substantial costs for development and maintenance of such systems. One alternative is to choose from the existing web based technologies, namely social networking, blogging, sending and receiving SMSs and IVR services, that are freely available with minimum or no maintenance cost. Some of these technologies have been tested out with smaller communities and has given promising results. Being in the category of a middle income country, it would be useful for Sri Lanka to explore existing and emerging technologies and modify them based on the specific requirements of the target groups. Adoption of such ICT based information systems by the agriculture community depends on a number of aspects. One important question is ‘how a given farmer community choose a suitable web based

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technology for collaboration?’ This could be made possible in a number of ways. Ideally the community could make use of web technology, including social media, which the members are already familiar with. There are farmers and other stakeholders, those who already use web based technologies for interactions. Especially, the young farmers today are well aware of social networks and they can be encouraged to use such networks to link with other farmers. Another option would be an outside facilitator, such as the extension agent or any other authoritative person, introducing farmers to networking using social media. With a little help from the government or another organization in training these officers, they can easily initiate these networks at village level. Use of participatory and interactive project designs when implementing ICT interventions with agricultural communities would improve the chances of sustainable impacts on target communities (Donovan, 2011). Accordingly future projects can adopt design research approaches, while ensuring stakeholder participation throughout the design process. This would lead to higher participation, easy adoption and sustainability, as farmers would get a sense of ownership for the outcome. In many instances the average farmers may not have the necessary skills and attitudes to use a given ICTs although they are willing to do so. Thus, it is important to provide necessary training for them. The farmers who are conversant in using such technology could be identified and they could be assigned to help the other farmers. There are informal leaders and followers in the community. We need to identify these groups and help them identify suitable ICT based communication systems to facilitate collaboration. It is important to identify the existing means of communication (such as face-to-face gatherings) that can be enhanced, or replaced, with modern ICTs, to strengthen the networks that are already present in the community. This would give recognition to each stakeholder in the system and users would be more comfortable in interacting with people who are already known to them.

CONCLUSION Information and communication technologies have revolutionized the traditional systems of information exchange mechanisms, while opening up number of gateways to integrate ICTs in the development process. The agricultural information society has been significantly affected by these latest ICTs. A number of interventions made to harness best use of ICTs in agriculture information dissemination. Computer based learning methods, mobile based information dissemination systems and websites are the most common. The major challenges ahead of the agriculture information society are less emphasis on networking stakeholders, duplication of work due to poor coordination, cost for developing and maintenance of ICT based systems, lack of ICT proficiency among farmers, and inability to cater to the actual user needs by the existing systems The possibility of using existing web based technologies, which are freely available, have not been adequately explored. Addressing the above limitations is going to be very challenging. However, some of them can be addressed by ensuring proper coordination among the organizations, developing suitable ICT based agriculture information systems by following participatory research approaches, choosing from the existing web based technologies such as social media and modify them to suit local situations, and provide support for target communities by providing necessary training.

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REFERENCES Central Bank of Sri Lanka. (2013a). Annual Report 2013. Colombo: Si Lanka. Central Bank of Sri Lanka. Central Bank of Sri Lanka. (2013b). Sri Lanka Socio-Economic Data 2013 (Vol. XXXVI). Colombo, Sri Lanka: Central Bank of Sri Lanka. De Silva, H. (2008). Using ICTs to create efficient agricultural markets: A future vision for Sri Lanka [PDF document]. Retrieved from http://www.lirneasia.net/wp-content/uploads/2008/03/de-silva_transaction-costs-in-sri-lanka-the-future.pdf De Silva, H., & Ratnadiwakara, D. (2008). Using ICT to reduce transaction costs in agriculture through better communication: A case-study from Sri Lanka. Retrieved from http://www.lirneasia.net De Silva, L. N. C., Goonetillake, J. S., & Wikramanayake, G. N. (2012). A holistic mobile based information system to enhance farming activities in Sri Lanka. In Engineering and Applied Science (EAS 2012), IASTED Conferences, Vol 785 (pp. 91–99). ACTA Press. 10.2316/P.2012.785-092 de Soyza, M. (2014). Dialog Tradenet. Digital Knowledge Center. Retrieved from http://digitalknowledgecentre.in ICT for Agriculture in Sri Lanka. (2010). Department of Agriculture Sri Lanka (DOA). Retrieved from http://www.afaci.org Dhaliwal, R. K., & Joshi, V. (2010). Mobile Phones - Boon to Rural Social System. [LICEJ]. Literacy Information and Computer Education Journal, 1(4), 261–265. Dharmaratne, T. A. (2013). Agricultural market information system in Sri Lanka: Costs, transmission, reliability, volatility and adequacy to the policy needs. Proceedings of the International Conference on Agricultural Statistics VI. Rio de Janeiro, Brazil. Retrieved from http://www.fao.org Dialog Axiata, P. L. C. (2009). Dialog Tradenet and GGS partnership set to revolutionise agri market access. Retrieved from http://www.dialog.lk Dissanayake, D. M. L. B., Wijekoon, R. R. A., Madana, P., & Wickramasinghe, Y. W. (2009). Awareness and effectiveness of the toll free agricultural advisory service of the department of agriculture. Abstract of Final Year Research Symposium 2009, Volume 03. Faculty of Agriculture Rajarata University of Sri Lanka. Retrieved from http://repository.rjt.ac.lk/7013/1685 Dissanayeke, U., & Wanigasundera, W. A. D. P. (2014). Mobile based information communication interactions among major agriculture stakeholders: Sri Lankan Experience. Electronic Journal of Information Systems in Developing Countries, 60, 1–12. Dissanayeke, U. I., Wickramasuriya, H. V. A., & Wijekoon, R. (2009). Evaluation of Computer Based Learning Materials in Agricultural Information Dissemination in Sri Lanka. Tropical Agricultural Research, 21(1), 73–79. Donovan, K. (2011). Anywhere, anytime - mobile devices and their impact on agriculture and rural development. Proceedings of the ICT in Agriculture: Connecting Smallholders to Knowledge, Networks, and Institutions (pp. 49–70). Washington. Retrieved from http://www.ictinagriculture.org

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Fafchamps, M., & Minten, B. (2012). Impact of SMS-based agricultural information on Indian farmers. The World Bank Economic Review, 26(3), 383–414. doi:10.1093/wber/lhr056 Food and Agriculture Organization of the United Nations (FAO). (2014). Agriculture Management Information System. Department of Agriculture, Government of Sri Lanka (DOASL). Retrieved from http://www.agmis.lk/ Goodwin, J., & Rhoades, E. (2009). Agricultural Legislation: The Presence of California Proposition 2 [YouTube video]. Proceedings of the Annual National Agricultural Education Research Conference. Louisville, Ky. Hector Kobbekaduwa Agrarian Research and Training Institute (HARTI). (2014). Mobitel agri price information index. Retrieved from http://www.harti.gov.lk Information and Communication Technology Agency of Sri Lanka (ICTA). (2013). List of Interactive Information Services. Retrieved from http://www.icta.lk International Telecommunication Union. (2012). Measuring the Information Society CH 1211. (p. 213). Geneva, Switzerland. Retrieved from http://www.itu.int International Telecommunication Union (ITU). (2014). Statistical market overview: Sri Lanka. Retrieved from http://www.itu.int Jayathilake, H. A. C. K., Jayaweera, B. P. A., & Waidyasekera, E. C. S. (2010). ICT adoption and its’ implications for agriculture in Sri Lanka. Journal of Food & Agriculture, 1(2), 54–63. doi:10.4038/jfa. v1i2.1799 Mobitel Pvt Ltd. (2014). Agri Price Information Index. Retrieved from http://www.mobitel.lk Mubarak, C. (2009). e-Sri Lanka: What is in it for agriculture. Proceedings of Joint National Conference on Information Technology in Agriculture (pp. 7–10). Colombo, Si Lanka. University of Moratuwa, Sri Lanka and University of Ruhuna, Sri Lanka. National Agricultural and Forestry Extension Service (NAFES). (2005). Consolidating Extension in the Lao PDR (p. 77). Retrieved from http://www.laolink.org Ramli, N. S., Hassan, S., Samah, B. A., Sham, M., & Ali, S. (2013). Comparison of crop, fisheries and livestock information displayed on agriculture websites. Journal of Basic and Applied Scientific Research, 3(6), 760–765. Reddy, P., & Ankaiah, R. (2005). A framework of information technology-based agriculture information dissemination system to improve crop productivity. Current Science, 88, 1905–1913. Rhoades, E., & Aue, K. (2010). Social agriculture: Adoption of social media by agricultural editors and broadcasters. Proceedings of 107th Annu. Mtg. Of Southern Association of Agricultural Scientists (pp. 1–20). Orlando, Florida. Roling, N. (1988). Extension Science: Information Systems in Agricultural Development (p. 233). UK: Cambridge University Press.

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Rosegrant, M. W., & Cline, S. A. (2003). Global food security: Challenges and policies. Science, 302(5652), 1917–1919. doi:10.1126cience.1092958 PMID:14671289 Telecommunications Regulatory Commission of Sri Lanka (TRCSL). (2013). Statistical Report -2013. Retrieved from http://www.trc.gov.lk Wijekoon, R., Emitiyagoda, S., Rizwan, M. F. M., Rathnayaka, R. M. M. S., & Rajapaksha, H. G. A. (2014). Cyber extension: An information and communication technology initiative for agriculture and rural development in Sri Lanka. Food and Agriculture Organization. Document for Technical Consultant. Retrieved from http://www.fao.org Wijerathna, S. (2011). Mobile telephony for agricultural development of Sri Lanka (p. 45). Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1976180 Wijeratne, M., & Silva, N. D. (2013). Mobile phone intervention for Sri Lankan mushroom producers. Proceedings of 27th Annual Conference of Asian Association of Open Universities. Pakistan: Allama Iqbal Open University, Pakistan. Wikigoviya. (2014). Retrieved from http://www.goviya.lk/index.php/en World Bank. (2014). Urban population Data. Retrieved from http://data.worldbank.org

This research was previously published in the Handbook of Research on Cultural and Economic Impacts of the Information Society edited by P.E. Thomas, M. Srihari, and Sandeep Kaur , pages 420-443, copyright year 2015 by Information Science Reference (an imprint of IGI Global).

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A Case Study of Innovation Platforms for Agricultural Research, Extension, and Development: Implications for Non-Formal Leadership and Adult Learning Matthew L. S. Gboku Sierra Leone Agricultural Research Institute, Sierra Leone Oitshepile M. Modise University of Botswana, Botswana Jenneh F. Bebeley Sierra Leone Agricultural Research Institute, Sierra Leone

ABSTRACT Stakeholder organizations clearly need to have more than a symbolic role in IAR4D decision making. They are currently hindered by their lack of knowledge of leadership roles and capacity to implement the IAR4D. In this chapter, the authors have presented the use of the IAR4D in Sierra Leone with clear justification of how it fits into contemporary approaches and interventions at the national, regional and global levels. The chapter focuses on the “Dissemination of New Agricultural Technologies in Africa (DONATA)” project in Sierra Leone as a shining example of leadership development and adult learning in both formal and non-formal settings. The authors highlight current challenges of the use of innovation platforms through IARD and articulate implications of the case study for adult education, agricultural extension and non-formal training in agricultural research institutions. The chapter ends with recommendations for surmounting the current challenges of the case described.

DOI: 10.4018/978-1-5225-9621-9.ch038

Copyright © 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 A Case Study of Innovation Platforms for Agricultural Research

INTRODUCTION This case is taken from the Sierra Leone Agricultural Research Institute (SLARI) using the success story of the Dissemination of New Agricultural Technologies in Africa (DONATA) project. The project was implemented by the Njala Agricultural Research Centre (NARC), which is one of the seven constituent centres of (SLARI). The case is developed from the reports covering the work of Sahr Fomba, Lansana Sesay, and Alhaji Massaquoi between 2008 and 2014. As Projects Development and Management Officer at one time and now Research Coordinator of SLARI, the lead author of this article participated in several of the activities of DONATA Project but he takes no responsibility for the reports from which the case is developed. Rather credit is fully given to the authors of those reports from which excerpts are taken. The Authors’ understanding of the aim of the publication for which this chapter is meant is the following: 1. Selection of a leadership case 2. Demonstration of why the selected case qualifies to be a shining example of leadership within the context of adult education (e.g. Agricultural extension, or other non-formal education projects) 3. Highlights of current challenges facing the case of leadership described. 4. Recommendations for surmounting the current challenges of the case described. Within the above framework, we have structured the chapter into six sections as follows. The first section is the introduction which provides the reason for this chapter, what the chapter entails and the manner in which it is structured. The second section provides the historical perspectives of research in Sierra Leone including the various institutions conducting research, the approaches used and a clear differentiation of efforts before the IAR4D approach and what pertains presently. In the third section of the article, the authors specifically present the use of the IAR4D in Sierra Leone with clear justification of how it fits into contemporary approaches and interventions at the national, regional and global levels. The fourth section is about the case study on the “Dissemination of New Agricultural Technologies in Africa (DONATA)” as a shining example of leadership development and adult learning in both formal and non-formal settings. Following the case presentation, the authors focused discussion on the implications of the case for adult education, agricultural extension and non-formal training on innovation platforms. The sixth section of the article addresses the challenges facing the use of Innovation Platforms (IPs) which is presented in the case study as model example for the promotion, dissemination and adoption of agricultural technologies. Finally, the article ends with a discussion of the implications of the case study for leadership development in adult education settings.

HISTORY OF RESEARCH IN SIERRA LEONE In this section, the authors looked at the institutional arrangements involved in conducting research from pre-colonial to the present time and also the approaches used for conducting research from independence (1961) to the present era of the Integrated Agricultural Research for Development (IAR4D).

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Institutional Setting Sierra Leone has had a long history of agricultural research, spanning almost 100 years. Up to the early 1980s research efforts in Sierra Leone were fragmented and uncoordinated, with research programs controlled by separate institutions with the mandate confined to annual crops. In 1985, the National Agricultural Research Coordinating Council (NARCC) was established to coordinate research and harmonize research activities. The Mission of NARCC was to support the promotion of pro-poor sustainable growth for food security and job creation as part of Sierra Leone’s Poverty Reduction Strategy Paper. The two constituent institutes of NARCC at the time were the Rice Research Institute dealing with rice, millet, sorghum, banana, plantain and vegetables, and the Institute of Agricultural Research dealing with cassava, sweet potato, yam, maize, cowpea, groundnut, soybean and sesame. In addition to the research institutes, Njala University and the University of Sierra Leone also carried out agricultural research. The devastation of research infrastructure during the ten year civil war (1992 – 2002) and the departure of well-trained scientists during this period brought agricultural research to a halt. Since 2001, many of the scientists have however returned and there is goodwill from the Government and partners to resuscitate the research establishment. After a period of coordination of agricultural research under NARCC, the Government of Sierra Leone (GoSL) established the Sierra Leone Agricultural Research Institute (SLARI) through the SLARI Act of Parliament of 2007. SLARI is now the agricultural research and agricultural technology generating body for the benefit of the farming, fishing and forestry sectors and to provide for other related matters. As a major role player in addressing the many challenges facing the agriculture, fishery and forestry sub sectors in Sierra Leone, SLARI is expected to conduct research to obtain knowledge, information and technologies needed for sustainable development of the country’s agricultural sector. In order to position itself strategically as a key driver in the transformation of the agricultural sector from subsistence to a commercial and profitable business enterprise, SLARI has adopted the Agricultural Product Value Chain (APVC) approach to research for development within the framework of Integrated Agricultural Research for Development (IAR4D). The adoption of this approach to research requires SLARI to shift focus from production of commodities to differentiated agricultural products including increased value-addition to commodities within the rural areas and development and promotion of new products that fit the demands of the target market (SLARI, 2011a). The adoption of the APVC approach to research for development has been necessitated by the renewed focus on agriculture and agribusiness as priority sectors for spurring economic growth in Africa with calls for development of APVCs that integrate producers and markets to make the agricultural sector more responsive to consumer demands. An important feature of the APVC approach according to Hawkins, Heemskerk, Booth, Daane, Maatman, and Adekunle, (2009) is that it permits analysis of the whole product system leading to the identification and prioritization of opportunities and problems throughout the system which facilitates the development of more realistic research and development intervention projects. In addition to this, the APVC approach to research for development implies expansion of the research portfolio to components such as post-harvest processing, marketing and internalization of consumer needs. The approach involves working with all players along the different APVCs from resources, production, processing, marketing to consumption. The APVC approach is characterized by increased vertical coordination of many actors along the commodity chain including research, extension, farmers, policy, processors, input and output market, transporters, and agricultural financing agencies (FARA,2007), and 857

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would be expected to demand for more integration and coordination of all different service providers around priority APVCs.

Research Approaches The history of research in Sierra Leone is tied to the use of a number of approaches which span from colonial to the present era. During the colonial era (1950 – 1960), the traditional approach to agricultural research was mainly supply-driven, in which researchers set the research agenda without consulting clients and other stakeholders. Up to the late 1960s, most research efforts tended to be largely commodity and factor oriented. The underlying paradigm is that understanding of the whole comes from understanding of the parts and their interactions. This paradigm works well especially where interactions among the parts are not important, that is, where the whole is essentially the sum of the parts. However, work done with farmers in many parts of the world has shown that they operate complex farming systems and they have to make difficult decisions about adoption of technologies (Bigs & Clay, 1981; Chanbers et al, 1989; Okali, Sumberg & Farrington, 1994). Because if this complexity of the farming systems, the traditional approach, often referred to as the top-down approach, to agricultural research and development was not having an impact on small-scale agriculture. Chambers et al. (1989) further observed that the way agricultural research and extension organized itself was a major reason why science was failing to improve the livelihood of the poor. Consequently, the linear research-extension-farmer linkage and technology transfer championed by the public extension service in 1960s and 1970s are no longer suited to agricultural research for development. During the early 1970s and early 1980s following Independence of most African countries, there was a start in history with the formation and consolidation of the National Agricultural Research System (NARS) supported by International Agricultural Research Centres. During this era, we experienced disjointed disciplinary on-station research, and cultivar development. Towards the late 1980s, the need to strengthen the NARS was realized. This was also the advent of extension services as link to farmers. Linear technology transfer model was dominant. Emphasis was placed on improved management of NARS for program relevance to client. Analysis of complex farming systems under which farmers operate led to the conclusion that appropriate technology could only be developed if it was based on full knowledge of the existing farming system, and that technologies should be evaluated not only in terms of their technical performance in specific environments, but also in terms of their conformity with the objectives, capabilities and socioeconomic conditions of clients. As a result, research and development practitioners looked for alternative approaches to agricultural research and development. Between the mid to late 1990s, the farming systems research approach became very popular with emphasis on adaptive on-farm research, sustainable agriculture, multi-disciplinary research approach, pluralistic participation, grassroots emphasis, information system and long term innovation development. From the definition, FSA is holistic and participatory, multi- and -interdisciplinary, demand-driven and problem-solving. It promotes partnerships and linkages, as well as synergies and cost-effectiveness in research and development. While FSA transformed the way research was conducted, its participatory nature was limited to incorporation of farmers and did not permeate research institutions that continued to operate singly. In the mid to late 1990s there was popularization of the farming systems research approach involving adaptive on-farm research. The FSA emphasis also remained at the farm level addressing production oriented issues with little attention directed at research on the other aspects such as processing and marketing. 858

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Realizing the weaknesses of the FSA at the end of the 1990s the concept of a “national system of innovation” emerged. The framework was developed after the realization that the objective of agricultural technology innovation must shift from increasing outputs and yields to transforming agriculture into a more responsive, dynamic and competitive sector. This shift was triggered by the emergence of major structural changes in the global food and agricultural systems including the integration of agriculture into global markets, the emergence of consumers as key drivers of technological change, the growth of private investment in new agricultural technologies, and the revolution in information and communication technologies combined with the growing recognition that agricultural innovation is far more complex and less linear than once believed. In Agricultural Innovation Systems (AIS), heterogeneous actors interact in the generation, exchange and use of information and knowledge; individuals and organizations in the system learn and change; and social and economic institutions condition these interactions and processes. The concept embraces not only the science suppliers but the totality and interaction of actors involved in innovation. It includes the farmer as part of a complex network of heterogeneous actors engaged in innovation processes, along with the formal and informal institutions and policy environments that influence these processes. In effect, this framework represents a move away from a more linear interpretation of innovation as a sequence of research, development and dissemination, to an interpretation that recognizes innovation as a complex web of related individuals and organizations, notably private industry and collective action organizations, all of whom contribute something to the application of new or existing information and knowledge. The concept of agricultural innovation systems can be summarized by at least ten basic principles that include Focus on innovation rather than production; Interaction and learning; Linkages for accessing knowledge and learning; Broad spectrum of actors with new actors and new roles in the innovations process; Attitudes, practices and interaction of behavioral patterns that determine the propensity to innovate; The importance of policies in innovations; The inclusion of stakeholders and the demand side in the innovations process; Experiential learning and capacity building; Changing to cope with change; and Coping with “sticky” information that is local and specific to owners and not easily available to others. In the recent era of 2000 till now, the need to refocus research for development is emphasized. It involves the development of technology transfer approaches, multi-disciplinary and multi institutional approaches, and development of the IAR4D.

THE USE OF IAR4D IN THE SIERRA LEONE AGRICULTURAL RESEARCH INSTITUTE A growing awareness amongst rural development practitioners of a need for “new and alternative ways of doing business” has created an increased demand for capacity development in how teams and partnerships are formed, planned, operated and managed. This search for an alternative integrated innovation process has led to the development of Integrated Agricultural Research for Development (IAR4D) approach. The IAR4D approach emerged after it was realized that the advances in research through the integrated pest management (IPM), integrated soil fertility management (ISFM) and integrated natural resource management (INRM) approaches offered an alternative approach for integrated research, although they fell short of integrating policies and markets, among others, into the research process. The IAR4D approach sets out a process and progressive procedures and accompanying tools for planning the resolution of complex problems and implementing rural development activities that respond to the

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needs of beneficiaries and involved stakeholders, contribute to broad development objectives and that use multi-dimensional participatory and systems approaches. The IAR4D is a process-oriented approach that recognizes the need for collective action by involving a broad range of stakeholders and multiple knowledge sources including indigenous knowledge and technology that can be used to address complex development challenges. The IAR4D approach also recognizes both spatial and temporal scales and interdependencies; multiple effects and trade-offs of different options; and the need to involve a wide range of stakeholders often with conflicting interests in collective action. Equally important is the inclusion of the social component including negotiation between differing perspectives, policy formulation, institutional change and development, land use and planning, and conflict and information management. The need to break away from single disciplinary and conventional research approaches and instead focus more holistically on the context (social, ecological, economical and institutional) which determines success and failure in achieving impact required a range of actions, the most important of which include (i) Facilitating more engagement of farmers and other participants in production to consumption chain; (ii) Enabling farmers to access efficiently functioning agricultural output and input markets; and (iii) Providing support to smallholders and pastoralists to engage in knowledge intensive integrated management of their natural resources and achieve sustainable improved livelihood. In order to achieve the desired results, these services are to be achieved in an integrated manner with closer interactions and wider ranging partnerships between and within research institutions, public, private and civil society organizations. An Innovation Platform (IP) forms the core of the IAR4D structure. The IP is an informal coalition, collaboration, partnership and alliance of agricultural research for development actors, that is, public and private scientists, extension workers, representatives of farmers, farmers’ associations, private firms and NGOs, and government policy makers who communicate, cooperate and interact to set priorities, develop concepts and plans to promote agricultural productivity and profitability. The core competencies brought to bear by IP are greater than the sum of IP’s constituents acting independently. The implementation of IAR4D hinges on four interactive process oriented support pillars namely (i) bringing about organizational and institutional change, capacity building for project teams and institutions; (ii) knowledge management and information sharing; (iii) monitoring, evaluation, impact assessment and lesson learning; and (iv) change and integration of markets, policies, NRM and productivity into innovation processes. The impact pathway for IAR4D begins with the establishment of IP where priorities that would determine the objectives of the research are agreed upon, a concept and plan of action developed and roles of each actor or groups of actors on the platform are clearly defined. The research process would then involve the use of inputs which is further broken into three phases as follows: 1. Identification of a common challenge through the IP and using inputs through an action research process to generate outputs in accordance with the project’s priorities and objectives. 2. Innovation stage which involves development of processes to deliver the outputs to beneficiaries (putting research into use, sometimes referred to as the innovation process). This involves putting into use the outputs generated by the research process. This process is facilitated by the IP and leads to incremental changes in relationships and behavior of stakeholders, in particular the users of the research outputs.

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3. Out-scaling by using agricultural development processes leading to improved food security, income, livelihood assets, the natural resource base and resilience to shocks; that is, impact. The mandate of IP actors ordinarily stretches beyond the IAR4D site. Accordingly, these actors serve as agents for out-scaling the research approach and its outputs beyond the initial site.

CASE STUDY: DISSEMINATION OF NEW AGRICULTURAL TECHNOLOGIES IN AFRICA (DONATA) PROJECT Background Promotion of Science and Technology for Agricultural Development in Africa (PSTAD) is an African Development Bank (AfDB) project with DONATA as subproject aims to improve on the agricultural productivity of resource-poor farmers. In 2008 SLARI/NARC with the sponsorship of AfDB, FARA, and ACORAF/WECARD established five demonstration/multiplication plots in five rural communities in the Bombali Shebora chiefdom in the Bombali District of Northern Sierra Leone and the Njaluahun Chiefdom in the Kailahun District of Eastern Sierra Leone. In 2011 another chiefdom, Gbendembu Ngowahun, Bombali District, and two others, Konike Barrina and Kolila Rowala in Tonkolili District, Northern Sierra Leone were added with total of ten platforms. In the same year, the Kayamba and Kori chiefdoms in the Moyamba district were added with a total of eight platforms, while in the Eastern Sierra Leone, Small Bo and Gaura chiefdoms in Kenema district and Luawa chiefdom in the Kailahun district were added with a total of 12 platforms. Overall, a total of thirty five innovation platforms were established between 2008 and 2011. Farmer-Based Organizations (FBOs) under the Dissemination of New Agricultural Technologies in Africa (DONATA) project in Sierra Leone has been much referred to as an example of successful Innovation Platforms (IPs) in rural markets. The activities of FBOs have developed since 2008, supported by various NGOs and the Njala Agricultural Research Centre (NARC), a constituent centre of the Sierra Leone Agricultural Research Institute (SLARI). During this period, the group collaborated with private sector individual partners in Bo and Makeni townships and effective intermediaries to set up an effective supply system of the desired quantity of quality gari product suitable for the urban markets of Freetown, Conakry and Monrovia. This has resulted in in increased yields and income for the participating farmers, as well as a dependable supply of quality cassava and gari products for the urban consumers of Sierra Leone, Guinea, and Liberia. DONATA’s aim was the wide-scale dissemination and adoption of new and proven agricultural technologies in stakeholders’ communities of Sierra Leone, to enhance food security and reduce rural poverty. While the focus of DONATA in Sierra Leone was on cassava based technologies in CORAF/WECARD, DONATA had three main elements: • • •

Establishment of Innovation Platforms for Technology Adoption (IPTA) to strengthen the innovation capacity of stakeholders in agricultural research and development on the African continent. Dissemination of new proven technologies, and Upgrading knowledge and skills.

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The Innovation Platform for Technology Adoption (IPTA) actors in Sierra Leone include farmers, processors, traders, researchers, extension workers, policymakers, drivers and micro finance organizations. The farmers form the foundation of the Innovation Platform for Technology Adoption (IPTA). They are the producers of the cassava tubers, the basis for processing and transformation. The traders most often buy either cassava tubers and sell to the cassava processors or buy processed products of cassava and sell to consumers. The processors transform cassava into products such as gari, fufu and starch. The researchers develop higher yielding cassava varieties and associated agronomic practices to replace low yielding local strains while the extension workers organize these stakeholders into platforms and facilitate meetings of the actors. The micro finance organizations target these platforms to offer micro credits. Loans are often given to only farmers and traders of the platforms who have the capacity to pay back. The ward councilors facilitate access to land and settle dispute among members of the platform. The expected outputs from the DONATA project were improved cassava varieties of SLICASS 1, 4, 6 and TME419 promoted and disseminated, and timely planting in Northern Sierra Leone were promoted and adopted. Farmers were actively involved in multiplying cassava cuttings for sale, while selling the tubers to processors, who produce gari and fufu for the markets. Technologies were demonstrated, disseminated and adopted through innovation platforms for technology adoption (IPTAs). To build capacity in development and promotion of selected technologies, training was given to researchers and extension agents. Some researchers received formal (M.Sc. level) training and short-term training, while extension agents receive training from the National Agricultural Research System (NARS). The development of innovation platforms under the DONATA project was neither a single approach, nor the efforts of a single organization that assisted the FBOs. Rather, it was the FBOs that attracted the attention of the organizations that assisted them in pursuing their objectives, improving their skills and desire to be innovative. There was constant collaboration between the FBOs that constituted the innovation platforms and the Njala Agricultural Research Centre in identifying and selecting other IP stakeholders including processors, transporters, marketers, and input suppliers. This is to say that the IP which initially started with a farmer based organization had only farmers as the pioneers on an innovation platform. The International Institute for Tropical Agriculture (IITA) with a sub-regional office in Sierra Leone also gave important support, directly or through the Sierra Leone Agricultural Research Institute. Research organizations played a service-provision role and, over a longer period, engaged in capacity building of stakeholders within the cassava value chain. Before the establishment of the IPTAs, improved cassava planting materials were not wide spread. They were only available to contact farmers who were in close touch with the research institute. The IPTA has facilitated a wider spread of improved technologies from research. Farmers’ output in cassava production and processing has greatly improved. Cassava was initially processed into two major forms; gari and fufu. Now cassava is both cash and an industrial crop in Sierra Leone. Most of the IPTAs feed the cassava processing factories with raw tubers. Before the IPTAs, most farmers depended on local planting materials that were lower in yields and susceptible to pests and diseases. Cassava products such High Quality Cassava Flour (HQCF), odorless fufu flour and some others are the initiative of the IPTAs in Sierra Leone. Also, through IPTA there has been an effective grasshopper control on most cassava farms through date of planting. The cassava value chain initiative has also been promoted by the IPTAs. Now even cassava leaves are not thrown away but dried in solar driers milled into powder for sale on the market. Much more income is now realized by farmers from cassava production and processing than before the IPTAs.

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Knowledge and skills on the cassava value chain were enhanced in most part of the country by the establishment of the IPTAs. In Bombali district, the IPTAs increased cassava production by 50%. That necessitated the cassava value chain initiative at all platforms. Skills on how to process cassava leaves into powder for cassava leaf source were learnt. Processing cassava into HQCF was also learnt by most people through the IPTA. Odorless Fufu flour was until recently completely absent in Sierra Leone. Now most IPTAs with cassava processing facilities process cassava into HQCF and they do so with safer measures by containing them in plastic sachets and label. These skills have enhanced variety of cassava products on the markets and contributed to diversification of food consumption in Sierra Leone. In the past most Sierra Leoneans only accept having eaten when their meal is rice. That is gradually changing as more appealing products are now formed from cassava. With the IPTAs, income levels of most cassava producers is improving as the land size cultivated to cassava is increased and more processing centers established. In Bombali district most DONATA platforms have graduated into Farmer Based Organization (FBO) and started bank accounts for savings. Some platforms have raised quite some amount of money and initiated a loan revolving scheme for the group members. This to a large extent has improved on the welfare of most IPTA members. The table below gives highlights of the income generated from IPTA farms in Bombali district.

IMPLICATIONS OF THE CASE The case described above qualifies as a shining example of leadership within the context of adult education (E.g. Agricultural Extension, or Other non-formal education projects). Below is a narrative of how the case has illustrated the principles of adult learning in three areas of adult education and lifelong learning.

Adult Learning Principles Illustrated Knowles’ in the 1970s identified six adult learning principles as listed. 1. Adults are internally motivated and self-directed in setting goals and planning learning activities. 2. Adults bring life experiences and knowledge to learning experiences. Subject matter and learning experiences must be provided that begins where the learner is. 3. Adults are goal oriented. Learning activities should be provided that take into account the wants, needs, interests, and aspirations. 4. Adults are relevancy oriented 5. Adults are practical and they learn what they practice. 6. Adult learners like to be respected. The question is how can the adult learning principles be illustrated to facilitate stakeholders’ learning on an innovation platform within the IAR4D? Principle 1: Adults are internally motivated and self-directed in setting goals and planning learning activities.

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Adult learners according to Fidishun (2000) resist learning when they feel others are imposing information, ideas or action on them. The role of the facilitator on an innovation platform is to move the actors towards more self-directed and responsible learning as well as to foster the actor’s internal motivation to learn. As an experienced facilitator, you can: • • • • • • • •

Set up a training program that is less structured but gives more responsibility to the actors on the IP with less supervision and at the appropriate place that is challenging but not overloaded for the IP actors/learners. Develop dialogue with the actors to optimize your approachability and encourage asking of questions and exploration of concepts. As the actors provide solutions to the facilitator’s questions, they feel more confident and more equal with the facilitator in knowledge sharing. Show interest in the IP actor’s thoughts and opinions by actively and carefully listening to the questions they pose. Lead the actors toward inquiry before supplying them with the facts. Provide regular constructive and specific feedback, which could be either positive or negative. Set projects or tasks for the IP actors which reflect their interests and which they must complete within a specified timeframe. Encourage the use of their resources first before considering other options in the pursuit of their goals. Acknowledge the actors’ preferred way of learning or doing and to discuss this with the group.

Principle 2: Adults bring life experiences and knowledge to learning experiences. Adults like to be given opportunity to use their existing foundation of knowledge and experiences gained from life, and apply it to their new learning experiences. As an experienced facilitator on the IP, you can: • • •

Find out about the actors on the platform in terms of their interests and past experiences in the family and at work. Assist the actors to draw on past experiences when problem-solving, reflecting and applying critical reasoning processes. Facilitate reflective learning opportunities which Fidishun (2000) suggests can also assist the learners to examine existing biases or habits based on life experiences and “move them toward a new understanding of information presented”.

Principle 3: Adults are goal oriented. Adult learners become ready to learn when ‘they experience a need to learn it in order to cope more satisfyingly with real-life tasks or problems (Knowles, 1980 p.44) as cited in Fidishun (2000). Your role as an IP facilitator is to facilitate learners’ readiness for problem-based learning and increase the actors’ awareness of the need for the knowledge or skill presented. As an experienced facilitator, you can:

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• • •

Provide meaningful learning experiences that are clearly linked to personal, client and fieldwork goals as well as assessment and future life goals. Provide real case studies as a basis from which to learn about theory, methods, functional issues and implications of relevance. Ask questions that motivate reflection, inquiry and further research.

Principle 4: Adults are relevancy oriented. Adult learners want to know the relevance of what they are learning to what they want to achieve. Some ways to help learners on an IP is to see the value of their observations and practical experiences throughout their involvement on the platform are to: • •

Ask the actors to do some reflection on for example, what they expect to learn prior to the experience, on what they learnt after the experience, and how they might apply what they learnt in the future, or how it will help them to meet their learning goals. Provide some choice of fieldwork project by providing two or more options, so that learning is more likely to reflect the actors’ interests.

Principle 5: Adults are practical. Through practical field experiences, interacting with real clients and their real life situations, learners move from classroom and textbook mode to hands-on-problem solving where they can recognize first hand, how what they are learning applies to life and the work context. As an experienced facilitator, you can: • • •

Clearly explain your critical reasoning when making choices about assessments, interventions and when prioritizing client’s needs. Be explicit about how what the learner is learning is useful and applicable to the job and client group you are working with. Promote active participation by allowing learners to try things rather than observe. Provide plenty of practice opportunity in assessment, interviewing, and intervention processes with ample repetition in order to promote development of skills, confidence and competence.

Principle 6: Adult learners like to be respected. Respect can be demonstrated to your learners by: • • • •

Taking interest Acknowledging the wealth of experiences that the learner brings to the platform. Regarding them as colleagues who are equal in life experience. Encouraging expression of ideas, reasoning and feedback at every opportunity.

It is important to keep in mind that the learner is still developing occupational therapy clinical practice skills. However, with the theory and principles of adult learning in mind, you can facilitate the learning approach of the students to move from novice to more sophisticated learning methods. This facilitates greater integration of knowledge, information and experience. The learner learns to distinguish what is important when assessing and working with clients, how to prioritise client needs, goals and caseload.

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When rules can be put aside and how/when the approach to occupational therapy practice and professional communication emerges from strict modelling of behaviour into a unique therapeutic and professional expression of self (Fidishun, 2000; Lieb, 1991).

Agricultural Extension Principles Illustrated The case of DONATA project in Sierra Leone has also demonstrated the principles of agricultural extension in the promotion and dissemination of agricultural technology for the benefits of cassava value chain actors. The Njala Agricultural Research Centre has done this with the following guiding principles for growth in agricultural production illustrated: Principle 1: Empowerment of end-users to ensure their meaningful participation in setting priorities and work program for research, extension and training to ensure their relevance. Principle 2: Planned subsidiarity to give responsibility and control over resources for agricultural research, extension and training activities at the lowest appropriate level of aggregation (local, national and regional). Principle 3: Pluralism in the delivery of agricultural research, extension and training services so that the diverse skills and strengths of a broad range of service providers such as universities, nongovernmental organizations (NGOs), public and the private sector can contribute to publicly supported agricultural productivity operations. Principle 4: Evidence-based approaches with emphasis on data analysis, including economic factors and market orientation in policy development, priority setting and strategic planning for agricultural research, extension and training. Principle 5: Integration of agricultural research with extension services, the private sector, training, capacity building, and education programs to respond in a holistic manner to the needs and opportunities for innovation in the sector. Principle 6: Explicit incorporation of sustainability criteria in evaluation of public investments in agricultural productivity and innovation programs (fiscal, economic, social and environmental). Principle 7: Systematic utilization of improved management information systems, in particular for planning, financial management, reporting, and monitoring and evaluation. Principle 8: Introduction of cost-sharing with end-users, according to their capacity to pay, to increase their stake in the efficiency of service provision and to improve financial sustainability. Principle 9: Integration of gender considerations at all levels, including farmers and farmers’ organizations, the private sector, public institutions, researchers and extension staff. Principle 10: Farmer operations based on demand driven technologies generated by research.

IAR4D Principles Illustrated Principle 1: Integration of perspectives, knowledge and actions of different stakeholders around a common theme The various members of each Farmer Based Organization initially received training in Farmer Field Schools (FFS) on basic farming skills, records keeping, farm management, business skills, group dynamics and governance of social organizations. Graduation of farmers from FFS with these basic farm

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skills qualified them to form an FBO which further received training on cassava production techniques, cassava disease management and cassava seed multiplication, which has led to an increase in production and productivity. The increase in production presented a marketing problem, and through the assistance from SLARI with financial support from Common Funds for Commodity (CFC) and DONATA Project, contact with potential buyers was established, credit was obtained and farmers were given training in developing business plans. The demand of quality processed cassava led to technical support from IITA with training on various processing equipment for gari and high quality flour products. Training, exposure and interaction of members has made it possible to separate entry points within the same IP with some acting as producers, and others as processors, transporters, and marketers. Principle 2: Integration of learning that stakeholders achieve through working together Beyond a simple concerted process, IAR4D according to Hawkins, Keemskert, Daane, Maatman and Adekunle (2009) is a social learning process, with stakeholders learning from the experience of working together. The different collaborative activities between SLARI, IITA, NARC, and local NGOs have provided improved insight into rural innovation process facilitated by DONATA staff but experimented and managed successfully by the various IP all actors. The focus in this kind of learning as noted by Hawkins et al. (2009) is primarily on the processes of stakeholder interaction themselves, rather than on the specific solutions to the research and development challenge, and learning occurs at the individual, innovation platform and institutional levels. Principle 3: Integration of analysis, action and change across the different dimensions of development The various IP groups have managed to substantially increase incomes from the cassava sales. As presented in the NARC Annual Technical Report for 2014, a total of ten (10) innovation platforms (IPS) have been established between 2008 to 2011 and are now fully functioning with a total membership of 5650 (3065 males and 2600 females) in the cassava value chain. In 2013, a total of 45.7t of gari was produced by all the IPs, valued at US$44,244.15 and marketed. This was followed by high quality cassava flower (HQCF) at 6t, fetching US$6976.70 and wet foo-foo and foo-foo flour at 42.25 t which fetched US$22,266.20. The total sale of all processed products was 162.25t and valued at USD121,919.14, and together with the sale of 29,600 bundles of cassava sticks (a bundle = 100 x 1m cassava sticks) valued at US$ 41,400 giving a gross income of US$ 163,359.14 for all the ten IPs. A total area of 452 ha was under cassava cultivation in all the IPs with average yields of 29-30t/ha for SLICASS 4, and 30-35t/ha for SLICASS 6 (Sesay, Massaquoi, & Fomba, 2014). There is no evidence however if men and women were paid the same prices and whether both gender gained equal benefits. Similarly, the work on DONATA does not show whether gains from the project were invested in natural resource management, which signals the need to address these issues. Principle 4: Integration of analysis, action and change at different levels of spatial and social organization To be effective in promoting innovation, IAR4D needs to promote change and enhance learning at all levels of the organization, including field, farm and watershed, product, firm, value chain, business cluster, individual, group, community, organization, and innovation levels (Hawkins et al. (2009). Elements in the success of the Innovation Platforms were the building of group cohesion as a result of the

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FFS training, working together as a FBO and also learning the processes of starting and operating an innovation platform.

Implications of the Case Study for Leadership Development Leadership as observed by Oduaran (n.d) is one of the most studied, observed and least understood phenomena people have grappled with over the years. The difficulty in understanding the concept according to Oduaran arises from the fact that there are no commonly agreed criteria by which we can describe the essence and process of leadership. The authors of this paper briefly explore the meaning of leadership in this section, and move on to identify the functions of a leader in the IAR4D approach. A synthesis provided on the definition of leadership by Northouse (2013) is that whether viewed as a personal quality or an organizational function, leadership can only be defined more correctly from at least six perspectives, which include: • • • • • •

The focus of group processes in which the leader is the individual who is at the middle of group change and activity and entails the ability to get the will of the group on his/her side. Perspective of personality elements in which leadership is perceived as “a combination of special traits or characteristics” that an individual has. It is those special traits or characteristics that enable the leader to motivate others to accomplish or complete given tasks. Perceived as an act or behavior in which interest is in the kind of things that leaders do in order to bring about change in a given group. From the point of view of power relationship when leadership is perceived as the exercise of power in order to bring about a change in the followers. Perceived as an instrument of goal achievement, which portrays leadership to be something that could be used in helping members of the group to achieve their goals while at the same time meeting their needs. From the skills perspective, when leadership places emphasis on capabilities including knowledge and skills that bring about effective leadership.

In every definition of leadership, the leader and the followers are equally important. However, it is often the leader who is expected to initiate the relationship, create the communication linkages and strive to maintain the relationship that s/he has established. Thus, leadership is a relationship activity in which the leader and followers must be understood thoroughly. From the synthesis provided by Northouse (2014), Leadership can be defined as a process of influencing others, in which the leader demonstrates ability to develop a vision that is well communicated, builds trust among colleagues, and takes effective action to maximize the efforts of others towards the achievement of a common goal. Technically speaking a leader could use social influence to just organize the efforts of others, without necessarily maximizing their effort. However, leadership is not about getting people started for developing cassava and rice technologies to improve productivity and food security.” It is rather, “the leader sees the present food insecurity and poverty”, and influence the followers to get started and see how fast they can achieve the goal of improving productivity and food security. We can achieve the goal of

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improving productivity and achieving food security in twenty five years. However, if the same goal can be attained in three years, we are both effective and efficient.

Functions of Leaders: Common activities for leaders are planning, organizing, directing, and controlling. In a typical research setting, leaders are expected to execute these common activities as shown in Table 1 below: • • • • • • • •

Firstly, leaders focus the attention of a group on purpose. For example, a leader will focus attention of colleagues by asking “Why do we constitute the rice research task force?” “What is our mission?” Leaders are result oriented. That is leaders organize work around results that will make the vision a reality. This means moving from a written document to action within a specified time frame. Leaders help the group internalize the vision through communication and information sharing. Leaders define a clear set of values and guiding principles that support the vision and promote individual accountability. This accountability is the glue that holds the vision intact. Leaders inspire trust by motivating, challenging, encouraging, empowering and moving their people. Leaders take a risk by stepping outside their comfort zone and think outside their mandate. Leaders innovate and develop rather than maintaining the status quo. Rather than doing things right, leaders do the right things.

CURRENT CHALLENGES FACING THE USE OF INNOVATION PLATFORMS The use of innovation platforms is a major tool in the implementation of the IAR4D processes. The DONATA projects in Sierra Leone have made significant contributions towards improving productivity in the past seven years through the promotion and dissemination of improved crop varieties particularly cassava coupled with key management practices. The impact indicators of the long-term investments in agricultural research using the case of DONATA are beginning to show but are yet to be evaluated Table 1. Common activities executed by leaders Leader Planning

• Devises strategy • Sets direction • Creates a vision

Organizing

• Gets people on board for strategy. • Communicates strategy • Networks with those led.

Directing

• Empowers people

Controlling

• Motivates • Inspires • Gives sense of accomplishment

The characteristics of leaders emerging from the functions listed above are critical to reiterate.

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in terms of: (i) the productivity impact that focuses on the efficient use of resources; (ii) the livelihood impact which determines whether gains of increased productivity benefit the mass of society; and (iii) the environmental impact which determines whether the gains achieved by the first two impact indicators can be sustained. Despite the gains realized in DONATA, there are numerous challenges that need to be addressed to achieve a sustainable broad based agricultural growth. These are:

General Challenges The major challenges facing the agricultural sector include but not limited to the following: 1. Sierra Leone’s population stands at 5.93 or 6% but 70.2% of the population leaves below the poverty line of $1.25. Poverty and unemployment is rampant. 2. 26% of the population is undernourished and are food insecure with impaired physical and cognitive values. 3. Poor physical infrastructure e.g. roads, marine transport, markets, communications (ICT) and energy. Without the prerequisite infrastructure it will be difficult to achieve agricultural products value chain activities. 4. Poor knowledge infrastructure and therefore need to advance the harnessing of Science, Technology and Innovations to improve competitiveness That is, there is need to promote science policy and its implementation. 5. Inherently poor soils. Most soils in Sierra Leone are ferralitic in origin and low in mineral nutrients reserves and therefore inherently low in fertility. Soil management including integrated soil fertility management practices should be given priority in our research agenda. 6. Low agricultural production growth rate (5.31%): low adoption of technology and area expansion for yield versus low intensification practices. 7. Planning approach is usually of short horizon and lack of foresight thinking. Our population is projected to double by 2050 and it means doubling or tripling current production levels. Planning approach is also based on limited scenarios and problem solving with little or no focus on exploiting opportunities. 8. Programs are usually fragmentary (between research, extension, training and education, NGO, farmers and policy makes) and are implemented in isolation resulting to duplication. There is weak human and institutional capacity. 9. Need to change mind-set of dependency and waiting for problems to be solved rather than exploiting opportunities.

Challenges in Developing Research Leaders for IAR4D The major challenges in developing leadership of IAR4D are: 1. Resources for training at various levels of academic certification. The least cost for training research leaders based on our present experience with the World Bank project is as follows: a. MSc/Phil degree: $34,000 - $56,000 b. PhD degree: $74,000 - $126,000

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To reduce the cost of leadership development, the Sierra Leone Agricultural Research Institute (SLARI) recruits people with a first degree as Research Assistant. Better still SLARI preferably recruit research scientists with a Master of Science degree over first degree holders. 2. Retentions of leaders in research institutions. Very few research institutions in Sub-Saharan Africa have adequate capacity to retain the very leaders they have trained. Incentives such as competitive salaries, standard accommodation, recreational facilities, educational facilities for the children of research leaders, and transportation are lacking. In real cases also there is the lack of laboratories, equipment and financial resources for research scientists to prove their leadership potentials in working with their colleagues. 3. The right gender balance between male and female scientists is hardly achieved because of the lack of female scientists to fill similar leadership positions like their male counterpart. In Sierra Leone, we have traced the gender gap right from the primary and secondary stages of our educational system where the girls are not encouraged to do sciences like physics, chemistry, biology, and mathematics. When this foundation is missed, getting the females into university programs like food sciences, agricultural sciences, engineering sciences, and environmental sciences becomes impossible. The ultimate consequence is that few females are available to take positions of soil scientist, agronomist, breeder, food technologist, entomologist, plant pathologist, hydrologist, irrigation specialist, biotechnologist, and biometrician. 4. Getting the right diversity of scientists to fill the leadership gaps as dictated by our research programs has not been achieved, and will continue to be a major challenge in the near future. Not until recently with the advent of the IAR4D which encourages the use of the Agricultural Product Value Chain (APVC) approach, our research focus has been mainly biological and/or production oriented with little or no attention to non-biological or non-production oriented activities such as processing, fortification, transporting, packaging, marketing, and consumption. Now that research diversity could be enhanced under the IAR4D using the APVC approach, trained leadership is required to achieve the strategic goals of the research institution.

REFERENCES Biggs, S. D., & Clay, E. J. (1981). Sources of innovation in agricultural technology. World Development, 9(4), 321–336. doi:10.1016/0305-750X(81)90080-2 Chambers, R. (1989). Farmers First: Farmer Innovation and Agricultural Research. London: IT Publications. Chema, S., Gilbert, E., & Roseboom, J. (2003). A Review of Key Issues and Recent Experiences in Reforming Agricultural Research in Africa. ISNAR. Available at ftp://ftp.cgiar.org/isnar/publicat/PDF/rr-24.pdf) FARA (2007). Sub-Saharan Challenge Program, Medium Term Plan 2008-2010. FARA. Hawkins, R., Heemskerk, W., Booth, R., Daane, J., Maatman, A., & Adekunle, A. A. (2009). Integrated Agricultural Research for Development (IAR4D). Paper prepared for the Forum for Agricultural Research in Africa (FARA) Sub-Saharan Africa Challenge Program (SSA CP).

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Jones, M. (2009). Integrated Agricultural Research for Development (IAR4D). Paper prepared for Forum for Agricultural Research in Africa (FARA) Sub-Saharan Africa Challenge Program (SSA CP). Lieb, S. (1991). Principles of adult learning. Phoenix, AZ: Vision – South Mountain Community College. Retrieved from http://honolulu.hawaii.edu/intranet/committees/FacDevCom/guidebk/teachtip/ adults-2.htm Mukiibi, J., & Youdeowe, A. (2005). Agricultural Research Delivery in Africa: An assessment of the requirements for efficient and effective and productive African NARS. Northouse, P. G. (2013). Leadership: Theory and Practice. Los Angeles: Sage Publications. Okali, C., Sumberg, J., & Farrington, J. (1994). Farmer Participtory Research: Rhetoric and Reality. London: Intermediate Technology publications. doi:10.3362/9781780444932

ADDITIONAL READING Brookfield, S. D. (1986). Understanding and Facilitating Adult Learning. A comprehensive analysis of principles and effective practices. Milton Keynes: Open University Press. Collins, M. (1991). Adult Education as Vocation. A critical role for the adult educator. London: Routledge. Courtney, S. (1989). Defining adult and continuing education. In S. B. Merriam & P. M. Cunningham (Eds.), Handbook of Adult and Continuing Education. San Francisco: Jossey-Bass. Darkenwald, G. G., & Merriam, S. B. (1982). Adult Education. Foundations of practice. New York: Harper and Row. Fomba, S. N. (2011). Promotion of Science and Technology for Agricultural Development in Africa (PSTAD). Quarterly Progress Report to FARA on RAILS and DONATA. Fomba, S. N. (2014). Dissemination of New Agricultural Technologies in Africa (DONATA). Semi-yearly progress Report. January – June. Jarvis, P. (1987). Adult Learning in the Social Context. Beckenham: Croom Helm. Sahr N. Fomba (2012). Report on the Tour of the Parliamentary Oversight Committee on Agriculture of the NARC Research sites, infrastructure and facilities. SLARI. (2011a). Sierra Leone Agricultural Research Institute. Strategic Plan, 2012-2021 SLARI. (2011b). Sierra Leone Agricultural Research Institute. Operational Plan, 2012- 2016 SLARI. (2011c). Sierra Leone Agricultural Research Institute. Investment Plan, 2012-2021 http://www. fara-africa.org/networking-support-projects/ssa-cp

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KEY TERMS AND DEFINITIONS Adult Education: A practice in which adults engage in organized and sustained learning activities intentionally designed for the purpose of bringing about gains in new forms of knowledge, skills, attitudes, or value among those whose age, social roles, or self-perception define them as adults. Adult Learning: ‘The entire range of formal, non-formal and informal learning activities which are undertaken by adults after a break since leaving initial education and training, and which results in the acquisition of new knowledge and skills’. Agricultural Extension: Is a general term involving the provision of assistance to farmers to help them identify and analyze their production problems and become aware of the opportunities to make improvement through farmer education and the application of scientific research and new knowledge to agricultural practices. Agricultural Product Value Chain (APVC): Although there is no universally accepted definition of the term, it normally refers to the full range of value adding activities required for an agricultural product or service to move through the different phases of production, including procurement of raw materials and other inputs, assembly, physical transportation, acquisition of required services such as transport or cooling, and ultimately response to the end customer’s demand (Kaplinsky and Morris, 2000). ‘Demand’: What people ask for, need and value so much that they are willing to invest their own resources, such as time and money, in order to receive the services. Demand Driven Technology Transfer: The demand drive technology transfer maintains the assumption that new technology drives innovation, that generation of this technology is most by publicly funded research institutions (Rogers, 1070), and that this technology is generated and transferred to the end users in a demand/market driven and more outward looking process (Chema, Gilbers & Roseboom, 2003) by involving the end users in assessing their needs and social realities which informs the technology generation and transfer processes. Farming Systems Approach (FSA): “A multi- (inter- and intra-) disciplinary approach to generation and diffusion of knowledge and technologies for specific target groups of clients with their participation focusing on identified priority problems, constraints and opportunities of the production system under consideration in different biophysical and socioeconomic conditions, with emphasis on improving the productivity of the existing system”. Integrated Agricultural Research for Development (IAR4D): An action research approach for investigating and facilitating the organization of groups of stakeholders, including researchers, to innovate more effectively in response to changing complex agricultural and natural resources management contexts for improved developmental outcomes (FARA, 2007). Innovation Platform (IP): “A physical and/or virtual network of stakeholders which has been set up around a commodity or system of mutual interest to foster collaboration, partnership and mutual focus to generate innovation on the commodity or system” (Adekunle and Fatundi 2012). Multidisciplinary Approach: An approach which involves drawing appropriately from multiple disciplines to redefine problems outside of normal boundaries and reach solutions based on a new understanding of complex situations. Multi-Institutional: Institutional system consisting of more than one service facility which has cooperative administrative arrangements through merger, affiliation, shared services, or other collective ventures.

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Multi-Stakeholders: These are persons with common interests and have agreed rules about cooperation. They are involved in learning and are action oriented and system thinking. They are concerned about knowledge and information sharing. Participation and empowerment is their goal. National Agricultural Research System (NARS): In any given country, all institutions and organizations actually or potentially involved in agricultural research and technology development together constitute the NARS of that country. Strong linkages are necessary between National Agricultural Research Institutes (NARIs) and specialized commodity research institutes, universities, industrial research laboratories, development organizations and the extension services, which are all involved in agriculture-related development activities. Stakeholders: Stakeholders refer to individuals, groups or organizations that can affect or are affected by a particular issue, system or innovation, Related terms are “interest groups”, which indicate that people can be grouped according to a common interest, and “actors” which emphasizes that some or all stakeholders are active and interact with each other (Hawkins et. al, 2009).

This research was previously published in Cases on Leadership in Adult Education edited by Oitshepile MmaB Modise, pages 173-197, copyright year 2015 by Information Science Reference (an imprint of IGI Global).

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Economic Transformation of Austrian Agriculture Since EU Accession Erika Quendler Federal Institute of Agricultural Economics, Austria Christina Mayer Statistics Austria, Austria Karl Michael Ortner Federal Institute of Agricultural Economics, Austria

ABSTRACT After joining the European Union (EU) in 1995 Austria adopted the Common Agricultural Policy (CAP). This chapter reviews the changes in agricultural production and the economic situation of agriculture since the accession to the EU. The analysis is primarily based on macro-economic data from the Economic Accounts for Agriculture (EAA) over the period between 1995 and 2014. Select examples identify the developments applicable for Austria – also in comparison to other EU countries and groups of countries as well as to Switzerland. Expectations and forecasts regarding the consequences of integration, e.g. changes in the price levels, have been more or less fulfilled but there is a need for further research on the development of regions and on special issues such as the resilience of Austrian agriculture.

INTRODUCTION With its accession to the EU Austria adopted all rights and obligations pursuant to the Common Agricultural Policy (CAP) (Art. 137 of the Act of Accession). Market organisations, price policies and payments to agriculture and forestry (in short: “farm payments”) had to be adjusted to the EU regime (Schneider, 1997). In general, competition was endorsed by the CAP, interventions in agricultural and food markets were reduced and measures to support prices were cut drastically and replaced by direct payments. With respect to structural policies, more emphasis was devoted to efficiency and performance. DOI: 10.4018/978-1-5225-9621-9.ch039

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 Economic Transformation of Austrian Agriculture Since EU Accession

Environmental aspects got increased attention; regional policy including programs for rural areas was upgraded (Schneider, 1997, p. 156). In order to mitigate losses of income due to inherent competitive weaknesses, structural disadvantages and accession-related price cuts, temporary transitional assistance in the form of degressive compensatory payments and aid for the write-down on agricultural products were granted (Ortner, 1996; Sinabell, 2004; Hofreither, 2006, p. 23). Since then the CAP was subject to four reforms, the last of them in 2009 and 2013. These reforms were gradual adaptations of the mechanisms that were put in place to achieve the objectives spelled out in the Treaty of Rome (Hambrusch, Heinschink, & Tribl, 2015). In the context of these reforms new objectives have been added (Regulation Establishing Rules, 2013; Regulation on Support, 2013). These encompass economic objectives (ensuring food security through sustainable agricultural production, improving competitiveness and increasing Value Added in the food chain), environmental objectives (sustainable use of natural resources and combating climate change), and territorial objectives (ensuring economic and social dynamics of rural areas) (Massot, 2013). The current chapter addresses the question of how, in this context, the economic situation of Austrian agriculture has developed since accession to the EU. The chapter is organised in several sections, starting with the history of agricultural developments and events in Austria. A brief introduction into the methodology applied is followed by an outline of the importance of agriculture by its Value Added and its contribution to the overall economy; a description of the components of agricultural output and the development of their shares; a portrayal of the composition and significance of farm payments for the development of the economic situation in agriculture; and an illustration of the development of agricultural income. Based on these results authors highlight strategies of how to mitigate or adapt Austrian agriculture to current challenges, followed by a section on possible fields of further research. The chapter is based on statistical data from Economic Accounts for Agriculture (EAA). Key developments in Austria and other EU countries as well as Switzerland are addressed. Furthermore, payments for Austrian agriculture are compared to the overall budget and the net contribution to the EU budget using data of National Accounts (NA), reports of the Ministry of Finance (Bundesministerium für Finanzen, 2013, 2015), reports of the Ministry of Agriculture (Bundesministerium für Land- und Forstwirtschaft, Umwelt & Wasserwirtschaft, 2015) and the Financial Report of the European Commission (2015b).

BACKGROUND Austrian agriculture was perceived as a sensitive area with regard to EU integration. The main problems of the sector were: • • •

Inadequate preparation for the Single Market; The country’s idiosyncratic natural and structural features; Differences in agricultural policies (Schneider, 1989, 1993, 1994).

The adoption of the CAP was associated with a fundamental transformation of economic conditions including profound changes in market organizations, price policy, agricultural support, and competitiveness. Traditionally, the role of government in agriculture has been strong in Austria, in particular in the dairy and cereals sectors where marketing boards administered prices, managed production and exports. In addition, equity considerations and environmental concerns remained very important. Politicians com876

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mitted themselves not to let per capita farm income fall behind the level of income growth in the overall economy. This was done in order to maintain the small-scale structure of farming (family farms) and to give farmers in disadvantaged (mountainous) regions the opportunity to stay viable through supplementary income payments. However, these direct payments were counterbalanced by production and fertilizer levies and accounted only for a part of support given to the agricultural sector (as measured by the Producer Subsidy Equivalent) (Organisation for Economic Co-operation and Development, 1995). The major policy instrument was market price support through border protection and export subsidies. The result was that farmers increased production until the government introduced quantitative restrictions on milk deliveries and support to oilseeds and protein crops in order to clear cereals markets. Joining the EU provided an opportunity for market liberalisation and access to the huge EU market for agricultural products, which was almost closed until then except for certain tariff quotas, a situation that forced the government to spend substantial amounts for export subsidies to allow excess production to be sold in world markets. However, the prospect of low agricultural producer prices in the EU was a major concern for farmers and processors who had hitherto been protected from competition in the domestic market. In the EU agricultural producer prices had been lowered following the CAP reform in 1992. In Austria, price adjustments had been postponed but were unavoidable after the conclusion of the Uruguay Round of negotiations of the General Agreement on Tariffs and Trade (GATT), which obliged Member States’ agriculture and food sectors to reduce export subsidies, internal support and border protection (Ortner, 1994). Thus, the challenge was to adjust Austrian agriculture to international markets while meeting policy objectives and securing support for EU accession. Agricultural prices dropped in the wake of EU accession by 22% on average while farmers could expect to pay only slightly less for inputs (Schneider, 1997). In the short run, the challenge was met surprisingly well due primarily to a momentous upgrade of support payments. Degressive compensatory payments were granted upon accession until 1999 to facilitate adjustment. Income support to farmers in mountainous and disadvantaged regions almost doubled, and the scope and volume of payments under the Austrian Program for Environmentally Sound Agriculture increased substantially (Ortner, 1996, 1997a). While the immediate changes upon accession are well documented in the literature, it is less obvious how Austrian agriculture developed in the longer run. Was there a major drop in agricultural income? Did production go down? How did the structure of agricultural output change? These developments are considerably steered by the evolution of agricultural policies and markets. Rather than outlining these changes here, the authors will comment on them as data which shed light on these issues is presented and discussed.

MAIN FOCUS OF THE CHAPTER Methodology The economic situation of Austrian agriculture is the subject of agricultural statistics both from a microeconomic and a macroeconomic perspective. The microeconomic situation is surveyed in terms of standardised accounting results at the level of agricultural holdings in the EU – the Farm Accountancy Data Network (Gahleitner, Kirner, & Resl, 2015). The macroeconomic approach accounts for agriculture

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overall, using the framework of EAA (Regulation on the Economic Accounts, 2003; European Union, 2013). Aggregate economic accounts for agriculture have been published within the EU since 1964 and from 1969 onwards based on common definitions and procedures. The EU’s EAA has been continuously adapted (Berkeley, 1996, p. 91). Several documents about the methodology on the EAA – with a standard set of concepts, definitions and roles for accounting – are available on the Internet (European Commission, 2000; Regulation, 2003; European Union, 2013). The EAA is a complementary (satellite) system to National Accounts which provides more detailed and comprehensive branch-specific information on agriculture than would be possible within the framework of NA (European Commission, 2000). The EAA is based on the collection and aggregation of numerous statistical information presented within a consistent framework. It draws upon agricultural production statistics (such as the harvest survey and slaughtering statistics), supply balance sheets, price statistics and farm accounting data as well as administrative data of the paying agency (Agrarmarkt Austria) and the Federal Ministry of Agriculture, Forestry, Environment and Water Management (BMLFUW), information from the Chambers of Agriculture, producer associations and non-agricultural statistics (External Trade Statistics). In the course of preparing and systematically compiling the EAA the data is checked for consistency, plausibility and comprehensiveness (Kniepert, Mayer, & Ortner, 2009, p. 84). The EAA is made up of a sequence of linked accounts which enable the assessment of the economic performance of the agricultural industry, from production to primary income generated. Financial flows to and from the government (taxes on production, subsidies), wages paid as well as rents and interest are constituent parts in this framework (European Commission, 2000). Furthermore, the EAA records basic data on wealth creation and labour input into agriculture (Bundesamt für Statistik, 2006, p. 40). The EAA provides comparable monetary values which inform about the general structure of agricultural production and changes in the economic values of agricultural production and income. The calculation scheme is presented in Figure 1. Figure 1. Agricultural economic accounts – scheme Source: European Commission, 2000; Regulation, 2003

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The indicators and figures calculated within the EAA provide the basis for a wide range of possible analyses, e.g. production patterns, input mix, terms of trade and productivity. Changes in the monetary values of output, intermediate consumption and Value Added can be broken down into price and volume components. However, in order to investigate the causes of the trends observed, it is often necessary to consult further information sources not included in the EAA, such as data on world markets, exchange rates, consumer preferences, legislation, economic conditions, policies, etc. (Kniepert et al., 2009, p. 84). These economic data play a prominent role in CAP policy formation as well as in monitoring past behaviour of the agricultural industry. Even in the absence of an agricultural policy with specific income goals, the economic activities of the agricultural industry would have to be accounted for as there is a general need to monitor the state of the agricultural system (Berkeley, 1996, p. 90). Furthermore, the EAA form the basis for depicting the agricultural industry in National Accounts. Since there are certain conceptual differences between these two systems of economic accounts, the EAA data has to be adapted for inclusion into NA. In order to maintain consistency, data of NA is used for comparisons of developments of the agricultural industry with that of the overall economy in the following section. The comparisons are based on NA data compiled according to the former European System of Accounts 1995 (ESA 1995) as this data is available since 1976.

Position of Agriculture in the Economy ESA 1995 data show that from EU accession in 1995 to 2012 the Gross Value Added (GVA) of the overall economy increased nominally from €157.4 billion to €277.6 billion, representing an increase of 76%. During the same period GVA of the primary sector (agriculture, forestry and fishing) increased by only 14%, from €3.9 billion to €4.4 billion (Statistics Austria, 2013). Within the primary sector, GVA of forestry increased significantly more strongly (44%) than that of agriculture (5%). In this regard, however, it is necessary to note that the development of GVA in agriculture – in contrast to that of forestry – was significantly influenced by changes in the types of support to agriculture, i.e., the introduction of degressive compensatory payments from 1995 to 1998 and decoupling of subsidies since 2005. The direct contribution of agriculture to the economic performance of Austria as a share of agricultural GVA in Total Value Added of the economy dropped from 4.5% in 1976 to 1.9% in 1995. From 1995 to 2005, the share of agriculture decreased further to 1.1%. In the period 2006 to 2012 the share of agriculture in Gross Value Added fluctuated between 1.0% and 1.2% (Figure 2). In comparison to other EU countries, the share of agriculture in Austria was at 1.2% in 2011, lower than the average of EU-28 (1.5%) and slightly lower than that of EU-15 (1.3%). The relative economic weight of agriculture is significantly lower in Western and Northern Europe than in Eastern and Southern Europe. The contribution to Total Value Added is highest in Romania (2011: 6.8%) and Bulgaria (5.1%), followed by Hungary (4.4%), Poland (3.6%), and Lithuania (3.2%). The lowest levels can be found in Luxembourg (0.3%), Sweden (0.4%), Belgium and the United Kingdom (0.6% each), and Germany (0.7%) (Figure 3). Furthermore, Figure 3 illustrates that countries with a high share of agriculture, forestry and fishing in Total Gross Value Added have been experiencing a strong slowdown since 1995. The Value Added share of agriculture in the overall economy, however, is an insufficient indicator of the relevance of this industry as agriculture contributes significantly to the economic performance of its upstream and downstream sectors (Ortner, Neuwirth, & Wagner, 2010). Furthermore positive and negative externalities which go along with agricultural production, e.g. the contribution to security 879

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Figure 2. Share of the primary sector in the Gross Value Added of the Austrian economy, in %, 1976-2012 Source: Statistics Austria, 2013

of food supply, the environmental impact of farming practices, the amenity of certain landscapes and wildlife, etc., remain unconsidered.

Agricultural Production Output Value: Composition and Development In 1995 Austrian agriculture produced goods and services at a total value of €5.83 billion (Statistics Austria, 2015). This value includes subsidies on products amounting to €0.95 billion minus taxes on products in the amount of €0.02 billion. Until 1999, the output value of the agricultural industry at basic prices, which is referred to below as total output value of agriculture, declined to €5.4 billion. This decrease was primarily due to the schedule of degressive compensatory payments that were granted to facilitate EU accession. Between 2000 and 2004, the trends in the total output value were primarily dictated by the development of producer prices and output volumes. The annual rates of change of the output value of the agricultural industry fluctuated during this period within a range of (-3.2%) (2002) to (+6.2%) (2001). After a slight increase in 2000 and a hefty price-induced increase in 2001 there were declines in 2002 and 2003 and another increase in 2004. In 2005, decoupling of a large share of acreage premiums and certain livestock premiums led to a strong decrease of the total output value. Year 2006 marked the start of a very dynamic development characterized by a strong upward trend in agricultural output value, which was interrupted by a slump in 2009 in the wake of the financial and economic crisis. Particularly high growth rates occurred in 2007 and 2011. In the years 2012 and 2014, weather-related crop failures

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Figure 3. Share of agriculture, forestry and fishing in the Total Gross Value Added by Member States of the EU, 2011 Source: Eurostat, 2015a

and low yields weakened the result. In 2012, despite generally favourable price developments in agricultural markets, the output value of the agricultural industry increased only slightly, and it dropped according to preliminary calculations by 2.3% to some €7.1 billion in 2014. Only €0.09 billion of this amount were subsidies on products while taxes on products amounted to approximately €0.05 billion in 2013 (Statistics Austria, 2015). Austrian agriculture contributed about 1.7% to the total output value of the agricultural industry of EU-28 in 2013; its share of EU-15 was 2.1% (1995: 2.3%) (Eurostat, 2015b).

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The output of the agricultural industry includes agricultural goods (crops and livestock), agricultural services and inseparable non-agricultural secondary activities. On average over the years 1995 to 2013 the share of animal output was 47% (with a minimum of 44% in 1999 and the maximum of 51% in the years 2005 and 2006) and that of crop output 43% (minimum: 39% in 2005; maximum: 46% in 1999 and 2011). Inseparable non-agricultural secondary activities accounted for 5% to 7%. The importance of agricultural services increased slightly although their share was still comparatively low at some 4.5% in 2014 (Statistics Austria, 2015). In the period 1995 to 2014 there was no systematic shift in the relative contribution of crop and animal output to the total output value of the agricultural industry. Their shares fluctuated from year to year at times rather strongly. However, the importance of individual branches within the crop and animal production changed. Within crop production, the share of special crops (wine, fruit and horticulture) increased from 30% in 1995 to 46% in 2005 while the share of arable crops declined during the same period from 51% to 32%. These shifts were due, inter alia, to the scaling down of degressive compensatory payments granted upon EU accession and decoupling of most acreage premiums in 2005. From 2006 to 2012, the shares of arable crops in crop output fluctuated rather strongly, from slightly less than 30% in 2009 to between 40% and 42% in the years 2007 and 2010 to 2012. A major contributor to these fluctuations was the cereals sector whose output value dropped in 2005 as a result of the replacement of acreage premiums by the single farm premium but increased significantly afterwards, although subject to very large annual fluctuations. Within the cereals sector, the share of maize increased markedly at the expense of barley, oats, and rye. Protein crops lost out and within oilseeds, soy cultivation increased significantly in recent years. In animal production, which is dominated by milk, cattle, and pigs, the share of poultry and eggs increased at the expense of other animals and animal products (Statistics Austria, 2015).

Development of Volumes and Prices Figure 4 shows the developments of volume and price indices of the agricultural industry’s output in the years 1995 to 2014 in comparison to the corresponding indices of intermediate consumption. It reveals a significant increase in the prices from 2006 to 2012 of output as well as intermediate consumption; obviously, the cost of inputs increased more heavily. 2013 and 2014 prices declined, with a stronger decline of output prices. The output volume of the agricultural industry exhibits stronger dynamics after 2006. The volume of crop output is, due to weather conditions, subject to rather large annual fluctuations while the volume of animal output developed rather evenly. In both crop and animal production, the output volume increased relative to the level in 1995. In crop production, output volumes of arable and special crops increased, whereas fodder production declined. With respect to prices, there was a relatively steady upward trend for special crops while the prices of arable crops were significantly more volatile (Figure 5). In animal production, the increase in output volume was, inter alia, due to an increase in milk production. Prices followed an upward trend in recent years, which, however, was less pronounced than that of crops (Figure 6).

Agricultural Payments This section presents the development of agricultural payments overall as well as in the context of the EAA, followed by an analysis of subsidies on products and other subsidies on production and their shares

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Figure 4. Volume and price indices1) for output and intermediate consumption of Austrian agriculture, 1995-2014, 1995 = 100 Note: 1) based on previous year’s prices Source: Statistics Austria, 2015

Figure 5. Crop output in Austria, volume and price indices1), 1995-2014, 1995 = 100 Note: 1) based on the previous year’s prices. Fodder: prices based on production cost. Source: Statistics Austria, 2015

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 Economic Transformation of Austrian Agriculture Since EU Accession

Figure 6. Animal output in Austria, volume and price indices1), 1995-2014, 1995 = 100 Note: 1) based on the previous year’s prices. Source: Statistics Austria, 2015

in factor income. A comparison with select EU countries and groups of countries is made in order to allow for an assessment of these developments. The European Commission (Regulation Establishing Rules, 2013; Regulation on Support, 2013) uses the term “payments” for monetary transfers from the public sector to the agriculture and forestry sector. Most of these payments are relevant for the EAA, in particular payments under pillar 1 (e.g. direct payments to farmers linked to market organizations) and pillar 2 (e.g. payments in the form of compensation for environmental activities, payments for the modernization of agricultural holdings). In paragraph 2 the Austrian Agriculture Law of 1992 provides for direct payments, interest subsidies and other grants and subsidies to agriculture: production-neutral direct income support and performancerelated direct payments, improvement of quality, support for environmentally sound activities and production-limiting measures in the crop and livestock sectors, measures to improve the competitiveness in agricultural production and marketing, measures to sustain farming and infrastructure, research and development and their adoption in agriculture, forestry and water management, and measures to promote investment into agriculture and forestry (Bundeskanzleramt, 2015).

Overall In the period of 1959-1994, payments for agriculture and forestry in Austria were granted through the so-called “Green Plan” established by the Agriculture Law and by payments in connection with market

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organizations (Ortner, 1997b). EU accession and thus the adoption of the CAP called for significant changes in the grant regime, and additional measures of the CAP had to be implemented (Bundesministerium für Land- & Forstwirtschaft, 1996, p. 145; Hambrusch et al., 2015). Since its creation, the CAP has always been adapted to respond to challenges of the time. Major reforms have been implemented in the wake of the following milestones (European Commission, 2015b): •

• • •

The Agenda 2000 reform improving competitiveness in world markets by lowering producer prices and introducing policies to enhance rural areas, the environment and food safety, in particular “cross-compliance” (payments are conditional on environmental, animal welfare and health standards) and the modulation of premium payments (thresholds); The 2003 reform or “mid-term review” decoupling of direct payments from production and introducing the single farm payment in connection with cross compliance requirements; The 2008 CAP “Health Check” expanding rural development policy, discarding the acreage setaside obligation and limiting the EU’s agricultural expenditure; The CAP reform 2014-2020 maintaining the two pillars but increasing the links between them, thus offering a more holistic and integrated approach to policy support. Specifically it introduced a new architecture of direct payments to be better targeted, more equitable and “greener”, an enhanced safety net against income loss, and strengthened rural development.

The described policy evolution over roughly a decade and a half can be characterised as a slow transformation process from a set of universal, obligatory, 100% EU-financed, agricultural commodity support measures towards a more market-oriented, decoupled, decentralised and co-financed rural development approach. This seems to recognise that compensatory payments should be transitional and ultimately phased out, leaving the regionalised and co-financed rural development measures as the core of the policy. If this comes about to the extent established by the goals of a common EU policy, common financing will be justified (Buckwell, 2015, p. 515). Figure 7 shows changes in the development of the payments for Austrian agriculture and forestry in the years between 1990 and 1994 and the following financial periods as an EU member state. Since accession, payments for agriculture and forestry in Austria have been funded by the EU, the Federal State and the Federal Provinces. They were allocated for the EU financial periods 1995-1999, 2000-2006 and 2007-2013 to facilitate planning and evaluation. Since the year 2000, these funds have been split into budgets for direct payments and market-related measures (1st pillar of the CAP), rural development (2nd pillar of the CAP) and other expenditures (Bundesministerium für Land- und Forstwirtschaft, Umwelt und Wasserwirtschaft, 2015, p. 102). The figure clearly shows the effects of accession and the reforms of the CAP during that time. The EAA only includes payments paid to farmers directly. Payments that are related to agriculture but granted to other industries – such as exports subsidies – are not considered (Kniepert et al., 2009, p. 83). Furthermore payments are divided into three categories: “subsidies on products”, “other subsidies on production” and “capital transfers”. Income is defined as including payments classified as “subsidies” but not capital transfers which remain unconsidered in the calculation of agricultural income (Regulation on the Economic Accounts, 2003, Annex I, para. 3.051, 3.088).

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Figure 7. Development of the payments for Austrian Agriculture and Forestry (EU, federal and provinces funds) in € million, 1990-2014

Source: Bundesministerium für Land- und Forstwirtschaft, Umwelt und Wasserwirtschaft, 2015; Bundesministerium für Finanzen, 2013

Development According to EAA The change in the orientation of the CAP is demonstrated by the evolution of expenditures, echoing the policy shift since 1990. Figure 8 shows that payments which are to be recorded in the EAA (subsidies and capital transfers paid to farmers) increased during the observation period while the share of payments related to agriculture but excluded from the EAA decreased. The share of capital transfers remained almost constant. Subsidies on products (direct payments for crop and animal production) increased significantly upon EU accession. In 2005, most of them were transformed to constitute the single farm payment. The jump in 1995 followed by the slump until 1999 is due to the implementation of degressive compensatory payments. Since EU accession, payments for environmental activities have constituted a significant share of total payments. The corresponding amounts stayed at about the same level over the years, as did those for compensatory allowances (support to unfavourable areas). While capital transfers exhibited a slight upward trend, the trend of other items in the category “other subsidies on production” (those except agrienvironmental measures, compensatory allowance and single farm payment) declined slightly (Figure 9).

Share of Subsidies in Factor Income: Comparative Analysis for Selected EU Countries and Country Groups The relative contribution of subsidies to farm income is quite different in the various EU countries. Among the countries surveyed here Austria (AT), after Finland (FI), followed by Sweden (SE) is one 886

 Economic Transformation of Austrian Agriculture Since EU Accession

Figure 8. Share of payments included in the EAA in total agricultural payments in AT, in %, 1990-2014 Source: Statistics Austria, 2015

Figure 9. Austrian agricultural payments included in the EAA, in € million, 1990-2014 Source: Statistics Austria, 2015

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of the countries with the highest share of subsidies in factor income. Italy (IT) has the lowest share, and France (FR), the United Kingdom (UK), Germany (GE), and Switzerland (CH) occupy the middle ground between Italy and Austria. While the shares in Switzerland and the United Kingdom have changed rather evenly over the years, other countries showed stronger fluctuations (Figure 10 and Figure 11). The share of product-related subsidies and other subsidies in factor income in the EU East has been aligning itself to that of the EU West over the years. The countries of the EU South clearly exhibit the smallest share. There is an obvious gap between northern and southern EU countries. The shares in the EU North fluctuate more widely. Austria’s share is within the range of the EU North (Figure 12 and Figure 13). A comparison with the EU average shows that the share in the EU South is smaller and the EU East is about average. In the EU West, the EU North and Austria the contribution of subsidies to factor income is significantly higher (Figure 13). Since these shares are not available differentiated by structural features, it is difficult to analyse the impact of these features. The European data, which are available, support only a macro view, which means that the existence of different average farm sizes in individual countries distorts the comparison between them. In countries with a significant number of small and micro enterprises, subsistence farms and farms with negative profit, the inclusion of these businesses in a survey produces lower average incomes which are difficult to compare. Moreover, these statistics do not convey information about whether agricultural payments are targeted and efficient in achieving their targets at minimum cost.

A Note on the Federal Budget and Net Contribution Table 1 shows the development of the federal budget and the agricultural budget and its composition during the period from 1995 to 2014. From there it is obvious that the agricultural payments share does Figure 10. Share of subsidies in factor income, in % – AT, GE, FR, UK, IT, FI, SE, and CH, 1995-2014 Source: Eurostat, 2015b

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 Economic Transformation of Austrian Agriculture Since EU Accession

Figure 11. Share of subsidies in factor income, in % – AT, GE, FR, UK, IT, FI, SE, and CH as well as in the euro area and the EU-27 and EU-28, average for the period 1995-1999, 2000-2006, and 2007-2014 Source: Eurostat, 2015b

Figure 12. Share of subsidies in factor income, in % – AT and the EU sub-regions (EU North, EU South, EU West, and EU East), 1995-2014

Note: EU North: Denmark, Finland, Sweden, Estonia, Lithuania, and Latvia; EU South: Italy, Portugal, Spain, Greece, and Cyprus; EU West: Belgium, Germany, France, Luxembourg, the Netherlands, the United Kingdom, Ireland, and Austria; EU East: Bulgaria, Czech Republic, Croatia, Hungary, Poland, Romania, Slovenia, and Slovakia (after Eurovoc). Source: Eurostat, 2015b

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 Economic Transformation of Austrian Agriculture Since EU Accession

Figure 13. Share of subsidies in factor income, in % – AT, the EU sub-regions (EU North, EU South, EU West, and EU East), the euro area, the EU-27 and EU-28, average for the periods 1995-1999, 20002006, and 2007-2014 Source: Eurostat, 2015b

not exceed single digits. The highest share was 4.3% of the federal budget in 1995; before it was around 2%, and it hovered around 3% after 2005. Table 1 also shows that a significant share of agricultural payments is financed by the EU. Nowadays the EU general budget originates mainly from so-called own resources (Art. 311 TFEU, formerly Art. 269 TEC). These funds are collected by Member States and forwarded to the EU budget. A comparison of the contributions of a Member State with its remittances from the EU budget delivers the net financial position (Figure 14 and Figure 15). This parameter gives information about the immediate financial consequences arising from the inclusion of the Member State in the EU budget. However, the net financial position is not sufficient to capture the total economic impact of EU membership. Such general assessments must be based on a far more comprehensive economic theory and statistical studies. The balance of a country shows whether it is a net contributor (negative sign) or a recipient (positive sign). Although the balance solely compares contributions to and receipts from the EU budget, it is an instrument of budgetary discipline and plays a significant role in negotiations and decisions on the allocation of the EU funds (“net contributor discussion”). The sum of all negative balances (2000: €15.2 billion; 2005: €17.5 billion; 2010: €31.0 billion; 2014: €43.5 billion) measures the extent of redistribution between Member States which is generated by the EU budget (Bundesministerium für Finanzen, 2013, 2015; European Commission, 2015a). The financial contribution of the Member States to the EU budget evolved very dynamically. As Figure 14 and Figure 15 show, net recipients and contributors change over time. Some Member States, like Germany, Austria, Belgium, and Luxembourg, are net contributors (Figure 14). The main net recipients are less developed regions (Figure 15).

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Table 1. The federal budget and the agricultural budget of AT, in € billion, million, and in %, 1990-2014

Year

Overall federal budget

Expenses for agriculture and forestry (agricultural budget)

Share of agriculture and forestry in % of the total budget

of which Subsidies for agriculture and forestry (1)

€ billion

of which share of EUfunds

Personnel and material expenses (2)

Protective hydraulic engineering and avalanche control

€ million

Share of subsidies for agriculture and forestry in % of the federal budget

Share of subsidies in % of agricultural budget

1990

45.4

1,035

2.3

729

1.6

70.4

1991

49.3

1,148

2.3

823

1.7

71.7

1992

53.7

1,286

2.4

955

1.8

74.3

213

118

1993

62.2

1,294

2.1

953

220

121

1.5

73.6

1994

62.0

1,487

2.4

1,021

228

128

1.6

68.0

1995

55.6

2,408

4.3

2,022

960

264

122

3.6

84.0

1996

54.9

2,119

3.9

1,743

1,010

264

112

3.2

82.3

1997

60.5

1,933

3.2

1,536

911

272

125

2.5

79.5

1998

56.5

1,828

3.2

1,461

927

242

126

2.6

79.9

1999

57.2

1,749

3.1

1,332

876

279

138

2.3

76.2

2000

58.2

1,953

3.4

1,513

1,041

302

138

2.6

77.5

2001

60.4

1,924

3.2

1,467

1,052

327

130

2.4

76.3

2002

61.8

1,994

3.2

1,502

1,062

337

155

2.4

75.3

2003

61,4

2,024

3.3

1,557

1,098

322

145

2.5

76.9

2004

65.0

2,075

3.2

1,623

1,187

327

124

2.5

78.2

2005

66.0

2,294

3.5

1,818

1,388

331

145

2.8

79.2

2006

70.5

2,319

3.3

1,792

1,360

338

188

2.5

77.3

2007

72.3

2,037

2.8

1,521

1,193

347

170

2.1

74.7

2008

80.3

2,181

2.7

1,641

1,249

364

176

2.0

75.2

2009

69.5

2,252

3.2

1,814

1,353

253

185

2.6

80.6

2010

67.3

2,176

3.2

1,755

1,297

244

176

2.6

80.7

2011

67.8

2,034

3.0

1,610

1,236

247

177

2.4

79.2

2012

72.9

2,109

2.9

1,673

1,263

253

184

2.3

79.3

2013

75.6

2,494

3.3

1,979

1,269

306

209

2.6

79.4

2014

75.8

2,226

2.9

2,074

1,287

308

141

2.7

93.2

Note: 1) expenditure on agriculture, forestry and water management, federal budget, 2) personnel and operating expenses of the central government and subordinate agencies, administrative expenses of the AMA. Source: Bundesministerium für Land- und Forstwirtschaft, Umwelt und Wasserwirtschaft, 2015, p. 228

Austria’s net contribution to the EU amounted to €435.5 million in 2000; it grew until 2014 to €1,240.6 million (European Commission, 2015a). In the year 2000 Austria received about €0.9 billion and in 2014 approximately €1.3 billion of the EU funds. They were spent primarily for the benefit of Austrian agriculture which received approximately 70% of the total EU budget remittances (Bundesministerium für Finanzen, 2013, p. 36; European Commission, 2015a). 891

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Figure 14. Financial net positions – net contributors to the EU budget (operational budget balances in % of Gross National Income, GNI), 2000-2014 Source: Bundesministerium für Finanzen, 2013, 2015; European Commission, 2015a

Figure 15. Financial net positions – net recipients of the EU budget (operational budget balances in % of GNI), 2000-2014 Source: Bundesministerium für Finanzen, 2013, 2015; European Commission, 2015a

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Income From Agricultural Activity One of the main objectives of the CAP is to ensure a fair standard of living for the agricultural population, in particular by increasing the individual earnings of persons engaged in agriculture (see. Art. 39 of the Treaty on the Functioning of the European Union, TFEU). For an assessment of whether this objective is being achieved data on the composition and evolution of agricultural income is provided, inter alia, by the EAA. Income aggregates and indicators provided by EAA solely relate to income generated by agricultural activities and exclude income from other sources such as income from other gainful activities, wages and salaries or social benefits. The EAA provides several income figures for the agricultural industry, among them Net Value Added at factor cost (“factor income”) which measures the remuneration of the factors of production: land, labour and capital. In 1995, the total of the output value of the agricultural industry at producer prices plus agricultural payments in the form of subsidies on products and other subsidies on production amounted to €6.8 billion. About a third of this, €2.3 billion, remained as factor income. In subsequent years, this share varied between 27% and 35%; in 2014, the share was 25% of the output value (approximately €8.4 billion). The development of the total of the agricultural output value and subsidies, what it was used for and how much remained as factor income, are presented in Figure 16 and Figure 17. Net entrepreneurial income is agricultural factor income minus compensation of employees, rents and interest paid, plus interest received. It measures the remuneration of non-paid labour (i.e., labour by family members spent in their agricultural units), owned land and capital. Figure 16. Value of Austrian agricultural output at producer prices, subsidies on products and other subsidies on production, in € billion at current prices, 1995-2014 Source: Statistics Austria, 2015

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Figure 17. Production costs and factor income of Austrian agriculture, in € billion at current prices, 1995-2014

Source: Statistics Austria, 2015

In 1995, net entrepreneurial income of the agricultural industry amounted to approximately €2 billion, which corresponded to 90% of factor income (Figure 18). Its share in factor income followed a declining trend in the observation period except for annual fluctuations. In 2014, it accounted only for 73% of factor income. Farm incomes are very volatile over time. The development of factor income is determined by changes in output levels and prices; subsidies and taxes on products; intermediate consumption levels and prices; consumption of fixed capital; other subsidies and taxes on production (Chatellier, Guyomard, Latruffe, & Levert, 2007, p. 3). The development of net entrepreneurial income also depends on changes in compensation of employees, rents paid and interests paid and received. In Austria, the scheduled reduction of degressive compensatory payments was one of the main causes for the drop in income in the years immediately after EU accession. However, in 2001 factor income returned to the level of 1995 in nominal terms. Significant increases in income were observed in 2006 and 2007 as well as 2010 and 2011. The decline in 2009 was due to a sharp drop in agricultural prices in the wake of the economic and financial crisis. In the years 2012 to 2014, farm incomes decreased again. In real terms, i.e., deflated by the implicit price index of Gross Domestic Product at market prices (GDP), both factor income and net entrepreneurial income declined during the observation period. Despite the declining amounts of real income generated by agricultural activity in total, income per work unit has exhibited an upward trend since 2001 – although with significant annual fluctuations (Figure 19). This development was due to structural changes in agriculture and the associated decrease in agricultural labour input. According to the EAA, agricultural labour input decreased from 188,400 annual work units (AWU) in 1995 by almost a third to 127,600 AWU in 2010. A decrease of non-salaried

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Figure 18. Income generated by agricultural activity in Austria, in € billion, 1995-2014 Source: Statistics Austria, 2015

Figure 19. Index of nominal and real agricultural income per AWU in Austria, 1995 = 100, 1995-2014 Source: Statistics Austria, 2015

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labour was partially offset by an increase of salaried employees whose share in agricultural labour input increased from 6% in 1995 to 11% in 2010. At the European level, the index of real factor income per annual work unit (which is also referred to as indicator A) is primarily used to monitor agricultural income development and for income comparisons between Member States. As Figure 20 shows, indicator A developed quite differently in Austria, Germany, France, the United Kingdom, Italy, Switzerland, Finland, and Sweden. Germany and Sweden exhibit a trend similar to that of Austria from 2000, with factor income per AWU growing more variedly and steeper in Germany than in Sweden and Austria. In Switzerland, the development was quite stable, with a little slope and slight fluctuations. France, however, had a similar development to that of Austria from 2005, but from 1995 to 2000 factor income per AWU declined slightly, followed by a stable increase. Finland showed an extreme decrease until 1998, followed by a stable increase. In Italy, factor income per work unit remained at the level of 1995 until 2004, decreased until 2010 and recovered until 2013.

Main Developments in a Nutshell Accession to the EU made Austria part of a single market, thereby intensifying competition through the elimination of trade barriers to other Member States. The preceding analysis showed that Austrian agriculture, which was considered a critical industry regarding EU accession (Schneider, 1997), has managed to weather the last twenty years since joining the EU without incurring massive losses of production and income (Gahleitner et al., 2015; Hambrusch et al., 2015). For Austrian agriculture the consequences of integration have more or less manifested themselves as follows: Figure 20. Index of real agricultural factor income per AWU, 1995 = 100 – AT, GE, FR, UK, IT, FI, SE, and CH, 1995-2014 Source: Eurostat, 2015b

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•

•

•

•

The relative economic weight of the primary sector is below the EU-28 average. The economic importance of agriculture, measured as Value Added share in the overall economy, has been declining. The overall economy benefitted from accession as other sectors grew, due to integration effects (research and development, foreign direct investment) which are difficult to determine exactly (Breuss, 2003, p. 551). Even though output volume expanded over the observation period and output prices showed a significantly upward trend from 2006 onwards, real factor income as well as real Entrepreneurial Income generated by agricultural activity fell below the levels of 1995. Real income per AWU has however risen due to structural changes in agriculture leading to a significant decrease in the agricultural labour force. Agriculture in Austria and other EU countries depends heavily on direct payments. There has been a gradual reduction in subsidies, as a result of continuing pressure from the World Trade Organization (WTO), although subsidies in emerging economies have been increasing in recent years. Furthermore, the 2007-2008 world food price crisis has renewed calls for farm subsidies to be removed in light of evidence that farm subsidies may influence the level of food prices, which has a particularly detrimental impact on farmers in developing countries (EurActor Network, 2008). Changes in agricultural subsidies are necessary and occur continuously. The reduction of production-related subsidies andtransfers and the targeting of subsidies are seen as important for the liberalisation of markets and the sustainable development of developing and emerging countries. Current economic developments such as the financial crisis, intensive lobbies in various Member States, elections and political power struggles but also the need to deliver public goods suggest that the transformation of funding and the diminution of EU agricultural subsidies are likely to continue from financial period to financial period (Kraut, 2009, p. 61).

Other critical developments are less predictable. There are significant “wild cards”: global warming, biotechnology and the changing role of Africa, China, Russia and the Middle East.

SOLUTIONS AND RECOMMENDATIONS The fact that Austrian agriculture has managed to weather the last twenty years since joining the EU without incurring massive losses of production and income (Gahleitner et al., 2015; Hambrusch et al., 2015) was mainly due to substantive public measures and structural adjustment. In order to cope with current and futures challenges like global warming, volatile prices and tightening of public budgets, Austrian agriculture can adopt the following strategies: •

•

New customer segments: The growth in emerging markets of both population and the economy increases the level and quality of demand for agricultural and food products. According to forecasts of the Food and Agriculture Organization (2011) overall food demand will increase by 1.1% a year between 2006 and 2050, or by 70% over the whole period (KPMG International, 2013, p. 13). Diversification of output: Whereas the primary goal of agriculture is to produce food, feed and fibre, the sector is also being asked to provide a range of non-commodity outputs which are associated with agriculture such as access, recreation, conservation, amenity, heritage, tourism and 897

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•

ecosystem services. Farmers and policymakers face the challenge to meet these demands by exploiting opportunities and offering targeted support to specific priorities as exemplified by the 2nd Pillar of the CAP. Customer awareness: The population is aware that Austrian agriculture provides important ecological and social services (open landscape, road access, accommodation, skills, education, etc.), especially in the less-favoured areas. In order to match demand for and supply of these services, their level depends on the willingness to pay (WTP) for positive and the avoidance of negative externalities. Agriculture will benefit from ‘green subsidies’ and adapt to them depending on how they are implemented in different agricultural policy measures, i.e., the rural development programme.

FUTURE RESEARCH DIRECTIONS Areas of potential interest for future research include the following: •

•

•

•

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The ongoing shifts in policy objectives and the volatile income in agriculture increase the necessity for policy-makers and scientists to take into account all sources of income of agricultural households, not just those derived from agricultural activity. Generally, in the EU, data on agricultural household incomes is scarce and calculation methods are not harmonised. Nevertheless, the European Commission (2010, p. 3) concludes “that farm households in many Member States derive a significant share of income from off-farm sources, i.e., mainly other gainful activities, but also social transfers and property income. Importantly, the share of off-farm income has increased in many of the countries for which data is available” (Statistic Canada, 2009; Schnepf, 2015, p. 24). In a free market, people ignore the positive externalities of consumption, e.g. when cycling to work, you take the cultivated landscape for granted. This raises the question about the value of these externalities, which are subject to agricultural policy and EU subsidies and can be estimated by WTP. WTP is the amount of money a person would be willing to pay for a higher level of environmental or commodity quality (Golan & Kuchler, 1999; Spencer, 1996). According to James (2002), tools for measuring WTP (which include the contingent valuation, travel cost and hedonic pricing) can be used to answer questions such as how much consumers are willing to pay for a quality upgrade or what impact a particular government intervention might have. Agriculture is confronted with the following challenges – as described in the following familiar mix of broad European rural development objectives – of maintaining resilience and improving agricultural productivity to help ensure food security for citizens at a lower resource cost; improving environmental performance of agriculture; contributing to reasonable living standards for primary producers; assisting the development of rural areas, especially remote and marginal areas (Buckwell, 2015, p. 512). In upcoming evaluation activities as well as for further reforms it has to be examined whether these objectives are met. Conventional agricultural accounts – such as EAA – allow a macro level follow-up of economic functions but offer no insights into the multifunctional contribution of the agricultural industry to society, nor do they reflect the true costs of agricultural production for society. There is a need to

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•

analyse the relationship between the economic activities of agriculture and the environment, with agriculture having both positive and negative impacts on the local and surrounding environment. For this purpose, the System of Environmental-Economic Accounting for Agriculture, Forestry and Fisheries (SEEA AFF) is currently being developed within the framework of the SEEA Central Framework. A further step would be to consider social aspects as well as cultural ones. And finally, Austrian and European agriculture are becoming more frequently influenced by volatile producer prices, volatile energy markets, localised natural hazards such as flooding, and the effects of regulations on technology use and labour supply. Some agricultural areas continue to lose their competitive edge to other regions with, say, more favourable climate or adequate labour supply. Unfortunately, many agricultural programmes tend to favour stability-enhancing management strategies with little attention to adjustment capacity in agriculture itself. There is a need to examine the adjustment capacity of agriculture and to analyse the role that institutional factors and in particular product market regulations play in this adjustment process.

CONCLUSION This chapter provides key insights into the evolution of Austrian agriculture within the EU. The authors’ results are in line with the literature on Austrian’s accession to the EU (Breuss, 2003; Schneider, 1997) and studies at European level (European Commission, 2010). Analyses have demonstrated that Austrian agriculture in general has so far found ways to adapt to the change in the agricultural regime attendant to EU membership and its wide-reaching effects on agricultural markets and production conditions. As the evolution of the CAP gets underway, the future development of Austrian agriculture remains to be seen. It will depend primarily on the development of markets under globalization and climate change as well as technological advancement along with the consumers’ demand. Future agricultural reforms are likely to be made in relation to the goals of developing intelligent, sustainable and inclusive growth as outlined in the Europe 2020 strategy, while taking into account the productivity and diversity of agriculture.

NOTE This chapter is a revised version of a contribution by Christina Mayer and Erika Quendler entitled ‘Die österreichische Landwirtschaft seit dem EU-Beitritt aus Sicht der Landwirtschaftlichen Gesamtrechnung’ published in E. Egartner, T. Resl (Hrsg.). Einblicke in Österreichs Landwirtschaft seit dem EU-Beitritt (p. 155-195). Schriftenreihe 108. Wien: Bundesanstalt für Agrarwirtschaft.

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Ortner, K. M. (1997b). Die österreichische Agrarpolitik bis zum EU-Beitritt. Die österreichische Landwirtschaft im EU-Agrarsystem. Klosterneuburg: Agrarverlag. Ortner, K. M., Neuwirth, J., & Wagner, K. (2010). Economic Effects of the Common Agricultural Policy on Employment in Austria. Rural Areas and Development, 7, 213–223. Regulation Establishing Rules for Direct Payments to Farmers under Support Schemes within the Framework of the Common Agricultural Policy. (2013). Publication No. 1307/2013. Brussels: The Official Journal of the European Union. Retrieved May 13, 2015, from http://eur-lex.europa.eu/legal-content/ EN/TXT/?qid=1431545697703&uri=CELEX:32013R1307 Regulation on Support for Rural Development by the European Agricultural Fund for Rural Development (EAFRD). (2013). Publication No. 1305/2013. Brussels: The Official Journal of the European Union. Retrieved May 13, 2015, from http://eur-lex.europa.eu/legal-content/EN/TXT/?qid=1431545955727& uri=CELEX:32013R1305 Regulation on the Economic Accounts for Agriculture in the Community. (2003). Publication No. 138/2004. Brussels: The Official Journal of the European Union. Retrieved October 20, 2015, from http://eur-lex. europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32004R0138&qid=1447943645565&from=EN Schneider, M. (1989). Österreichs Land- und Forstwirtschaft und der EG-Binnenmarkt. Vienna: WIFO. Schneider, M. (1993). EG-Binnenmarkt als Herausforderung für Österreichs Landwirtschaft und Nahrungsmittelindustrie. Vienna: WIFO. Schneider, M. (1994). Chancen und Risiken der Landwirtschaft im EU-Binnenmarkt. Österreich in der Europäischen Union. Anforderungen und Chancen für die Wirtschaft, 67, 46–61. Schneider, M. (1997). Österreichs Landwirtschaft unter EU-Bedingungen. WIFO-Monatsberichte, 3, 155–170. Schnepf, R. (2015). U.S. Farm Income. Outlook for, 2015. Retrieved from http://fas.org/sgp/crs/misc/ R40152.pdf Sinabell, F. (2004). Entwicklungstendenzen der österreichischen Landwirtschaft seit dem EU-Beitritt. Retrieved August 28, 2014, from http://www.bmlfuw.gv.at/land/laendl_entwicklung/Online-FachzeitschriftLaendlicher-Raum/archiv/2004/Sinabell.html Spencer, H. (1996). Consumer Willingness to Pay for Reduction in The Risk of Food Poisoning in UK. Journal of Agricultural Economics, 47(3), 403–420. Statistic Canada. (2009). Statistics on Income of Farm Operators. Retrieved June 1, 2015, from http:// www.statcan.gc.ca/pub/21-206-x/2012000/t078-eng.htm Statistics Austria. (2013). Volkswirtschaftliche Gesamtrechnungen. Hauptergebnisse 1980-2012. Wien: Statistik Austria. Retrieved September 15, 2014, from http://www.statistik.at/dynamic/wcmsprod/ idcplg?IdcService=GET_NATIVE_FILE&dID=146425&dDocName=071993

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ADDITIONAL READING Aiginger, K. (2009). Strengthening the Resilience of an Economy. Enlarging the Menu of Stabilisation Policy to Prevent Another Crisis. Inter Economics, 44(September/October), 309–316. doi:10.100710272009-0308-9 Chatterton, J., Audsley, E., Graves, A., Morris, J., & Williams, A. (2012). Using Systems-based LCA to Investigate the Environmental and Economic Impacts and Benefits of the Livestock Sector in the UK. Cranfield: Cranfield University. Cunha, A., & Swinbank, A. (2011). An Inside of the CAP Reform Process. Exploring the MacSharry, Agenda 2000 and Fischler Reforms. Oxford: Oxford University Press. doi:10.1093/acprof:o so/9780199591572.001.0001 Egartner, E., & Resl, Th. (Eds.), Einblicke in Österreichs Landwirtschaft seit dem EU-Beitritt. Wien: Bundesanstalt für Agrarwirtschaft. European Commission. (2002). The European Framework for Integrated Environmental and Economic Accounting. Retrieved May 24, 2015, from http://ec.europa.eu/eurostat/documents/39314/44178/Handbook-IEEAF-2002.pdf/c7b2aeaa-c4dd-49ce-bf25-05740d90e043 Hovorka, G. (2009). Eckpunkte einer zukunftsfähigen (Berg) Landwirtschaft. Retrieved May 17, 2011, from http://momentum-kongress.org/hovorka-gerhard-eckpunkte-einer-zukunftsfahigen-berglandwirtschaft Kay, A. (2003). Path Dependency and the CAP. Journal of European Public Policy, 10(3), 405–420. doi:10.1080/1350176032000085379 Matthew, A. (2015). Reflections on the CAP post 2014. In J. Swinnen (Ed.), The Political Economy of the 2014-2020 Common Agricultural Policy. An Imperfect Storm (pp. 493–508). London: Rowman & Littlefield International Ltd. Philippidis, G., & Hubbard, L. J. (2001). The Economic Cost of the CAP Revisited. Agricultural Economics, 25(2-3), 375–385. doi:10.1111/j.1574-0862.2001.tb00216.x Pieters, H., & Swinnen, J. (2014). Trading-off Volatility and Distortions? Food Policy during Price Spikes. Retrieved November 25, 2015, from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2533975 Swinnen, J. (2015). The Political. De Economía, 2014–2020. Treasury, H. M. (2008). Global Europe: Vision for a 21st Century Budget. London: HM Treasury. Verhaegen, E., Wustenberghs, H., Lauwers, L., & Mathijs, E. (n.d.). Integrated Economic and Environmental Accounting for Agriculture. Retrieved June 1, 2015, from http://www.nass.usda.gov/mexsai/ Papers/multifunc.pdf

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KEY TERMS AND DEFINITIONS Agricultural Industry: A collection of local kind-of-activity units that carry out agricultural activities including both farms and specialist agricultural contractors. The output of agriculture also includes inseparable non-agricultural secondary activities that these units carry out. It excludes services relating to design, planting and maintenance of gardens, parks, and green areas for sports facilities. It also excludes units producing solely for their own consumption. Agricultural Labour Input: All employed and self-employed persons that provide paid and unpaid labour input to residential units, which perform characteristic activities (agricultural and inseparable non-agricultural secondary activities) of the agricultural industry. Due to the consideration of part-time and seasonal work, labour force and its changes are measured in annual work units (AWU). One AWU equals one person in full-time employment in agriculture in one year. Employment has an important influence on the calculation of the income indicators. Agricultural Production at Basic Prices: Equals value of crop and animal output, agricultural services output and the value of inseparable non-agricultural secondary activities, valued at basic prices. Valuation at basic prices means the taxes on products and services are excluded and subsidies on products and services are included. The output of the agricultural industry results from the market production of goods and services as well as non-market production for individual final use (own consumption by agricultural households, own-account produced fixed capital goods of crops and livestock). Furthermore, parts of the output consumed by the agricultural units themselves are included in the output value (crop products that are used as fodder within the unit). Agricultural Production at Producer Prices: Equals the value of crop output, animal output, agricultural services and the value of inseparable non-agricultural secondary activities, valued at the (farm-gate) producer prices without VAT. Basic Prices: Amounts received by the producer for a unit of goods or services, minus any tax payable on that unit as a consequence of production or sale (i.e., taxes on products), plus any subsidy receivable on that unit as a consequence of production or sale (i.e., subsidies on products). Capital Transfers: Require the acquisition or disposal of an asset, or assets, by at least one of the parties to the transaction. Whether made in cash or in kind, they result in a commensurate change in the financial, or non-financial, assets shown in the balance sheets of one or both parties to the transaction. Economic Accounts for Agriculture (EAA): The purpose is to analyze the production process of the agricultural industry and the primary income generated by this production. It contains provides detailed data on value of output (at producer prices and basic prices), intermediate consumption, subsidies and taxes, consumption of fixed capital, rents and interests, capital formation, etc. The values are in current as well as in constant prices. Furthermore, Agricultural Labour Input (ALI) and Unit Values (UV) are an integrated part of the overall concept of EAA. Entrepreneurial Income: Equals net operating surplus/net mixed income less rents paid and interest plus received interest that refers exclusively to agricultural production. Factor Income: An amount for the remuneration of the production factors: labour, capital and land. Factor income incorporates subsidies on agricultural products and other subsidies on agricultural production. Due to the importance of the subsidies in agriculture and redirection of the common agricultural policy in indirect support in the form of other subsidies on production, factor income is more appropri-

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ate for reflecting the economic state of agriculture than Value Added. Factor income equals Net Value Added at basic prices less other taxes on production plus other subsidies on production. Factor income also equals the sum of net operating surplus/mixed income and compensation of employees. Gross Domestic Product (GDP): Aggregate measure of production equal to the sum of the Gross Value Added of all resident institutional units engaged in production (plus any taxes, and minus any subsidies, on products not included in the value of their outputs). Subsidies: Current unrequited payments which general government or the institutions of the European Union make to resident producers with the objective of influencing their levels of production, their prices or the remuneration of the factors of production. Subsidies on agricultural products are subsidies payable per unit of a good or service produced. Other subsidies on production include all subsidies, other than subsidies on products, from which resident producer units can benefit as a result of engaging in production (for example agri-environmental measures, subsidies for agricultural production in less favoured or mountain areas and compensation for current loses).

This research was previously published in Global Perspectives on Trade Integration and Economies in Transition edited by Vasily Erokhin, pages 299-329, copyright year 2016 by Business Science Reference (an imprint of IGI Global).

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Economic Growth and Climate Change: An Exploratory CountryLevel Analytics Study Wullianallur Raghupathi Fordham University, USA Viju Raghupathi Brooklyn College (CUNY), USA

ABSTRACT In this article, the authors use analytics to explore the association between economic growth and climate change at a country-level. They examine different indicators to better understand the macro issues and guide policy decision-making. The authors analyze global economic growth and climate change using the World Bank data of 131 countries and 16 indicators for the period 2005 to 2010. The analysis shows overall economic growth is positively associated with climate change. This implies country leaders should design and implement structured development plans if they are to promote economic growth to alleviate poverty while simultaneously mitigating climate change.

INTRODUCTION According to scientists and policymakers, the earth’s climate is changing. Temperatures are rising, snow and rainfall patterns are shifting, and extreme weather events—intense rainstorms, record-high temperatures, alternating cyclone/hurricane occurrences and long dry spells—are wreaking havoc in different parts of the world (International Monetary Fund, 2008; U.S. Environmental Protection Agency, 2016). Researchers are generally confident that many of these changes and trends are associated with increased levels of carbon dioxide and other greenhouse gases (GHG) in the earth’s atmosphere, and that these increases have been brought about by human activities (International Monetary Fund, 2008; U.S. Environmental Protection Agency, 2016)). Climate change refers to “any substantial change in DOI: 10.4018/978-1-5225-9621-9.ch040

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 Economic Growth and Climate Change

measures of climate (such as temperature or precipitation), lasting for an extended period (decades or longer). Natural factors have caused the climate to change during previous periods of the Earth’s history, but human activities are the primary cause of the changes that are being observed now (International Monetary Fund, 2008; Stern, 2006; The National Academies Press, 2010a, 2010b; U.S. Environmental Protection Agency, 2016).” Human activities are generally understood to include economic development and growth activities (The National Academies Press, 2010a, 2010b; Ward and Shively, 2012). The primary sources of greenhouse gases, in order of importance, are: electricity generation, land-use changes (e.g., deforestation), agriculture, and transportation (International Monetary Fund, 2008; Stern, 2006; The National Academy of Sciences, 2014). While the literature strongly suggests rich (developed) countries have historically dominated emissions, and poor (developing) countries will contribute to the rise in emissions rapidly, the current debate and global talks on climate change center around how to mitigate climate change while keeping equity and poverty reduction (Soubbotina, 2004; Tol, 2009) in mind (International Monetary Fund, 2008; Markandya, 2011). For example, increases in energy-related emissions of carbon dioxide, the largest and fastest growing source of GHG emissions, are primarily driven by growth in GDP capita and population increases, and these increases are only partially offset by more efficient use of energy (Markandya, 2011; Ward and Shively, 2012). While China, India, and other developing countries contribute to most of the growth in emissions, developed countries account for most energy-related emissions in the past and, thus, for most of the current stock of these emissions (Markandya, 2011). When changes in land-use and deforestation are considered, however, advanced countries are responsible for less than half of the current stock of total emissions (Markandya, 2011). In other words, the amount of carbon dioxide a country emits into the atmosphere depends mainly on the size of that country’s economy, the level of its industrialization, and the efficiency of its energy use (Mattoo and Subramanian, 2012; Raghupathi and Raghupathi, 2016; The National Academies Press, 2010b). Until now, though developing countries contain most of the world’s population, their industrial production and energy consumption per capita have been relatively low. There can be little doubt that the primary responsibility for global warming lies with developed countries. But the link between economic growth and increased energy consumption, in conjunction with increased carbon dioxide emission, is direct and positive for all countries (Mattoo and Subramanian, 2012). That said, at high-income levels, there are indications of lower per capita energy consumption and pollution despite economic growth (Raghupathi and Raghupathi, 2016; The National Academies Press, 2010b) explained by increased efficiency in energy use thanks to environmentally cleaner technologies. Also, a higher-income country will typically demand a proportionally larger service sector, and service is a far less energy intensive sector compared to, say, manufacturing (Mattoo and Subramanian, 2012). In summary, we know that developed countries have to reduce emissions, and they need to identify innovative strategies and technologies to develop and use. Furthermore, developed countries need to transfer and make these technologies available to developing countries. Progressive development assistance and aid have to be provided to developing countries, engaging them in rapid economic development and poverty reduction, and at the same time, keeping greenhouse gas emissions in check (The National Academies Press, 2010a). However, considering most developing countries do not commit to reduce greenhouse gas emissions, arguing that these commitments would undermine their economic development and impede poverty alleviation, finding the right balance between economic growth and climate change is a key challenge (Mattoo and Subramanian, 2012; The National Academies Press,2010a; United Nations Development Program, 2013). Naturally, all countries contemplating mitigation will want to

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understand the economic impact and whether climate change mitigation will allow them to enhance or maintain growth (International Monetary Fund, 2008). Key to this research, therefore, is the question of whether there is an association between economic growth (development) and climate change: Is climate change directly associated with economic growth? If so which indicators are significant? In this exploratory study, we address these questions. The findings have numerous implications. First, if an association exists, developed countries should make reparations for past and current emissions. Second, they should help developing countries engage in structured development by promoting equity to balance poverty alleviation with climate change mitigation and prevention. Third, countries with innovative strategies and technologies should facilitate the transference of such technologies to developing countries to mitigate climate change. Fourth, countries with experience and expertise in climate-change-mitigation strategies, studies, and research should share those experiences with countries that do not have similar experience or resources. The rest of this paper is organized as follows: First, we describe the methodology of our study; we then discuss results and offer analysis; thirdly, we outline the scope and limitations of the study; fourthly, we offer contributions; finally, we offer conclusions and policy implications.

MATERIALS AND METHODS We study the association between climate change and economic growth at a global level, using analytics. Analytics is the “application of models, methods, and tools to analyze large data sets to gain insight to make informed decisions (Raghupathi & Raghupathi, 2016). Analytics, a collection of decision support technologies, enables scientists and policymakers to understand and make better/faster decisions related to a domain. As more data is generated digitally and otherwise, decision-makers strive to leverage abundance of rich data using sophisticated analytic techniques - including artificial intelligence, machine learning, statistics, and visualization - so as to be data-driven in their decision-making. The domain of climate change is complex and multidimensional including facets of climate impacts, adaptation, mitigation and policy (Becken, 2013). Public knowledge of the domain is limited and its effects are perceived as abstract and unclear. In addition, the perception about climate change varies between countries (Capstick et al., 2015). In order to be effective, global concern about climate change should be preceded, at the very least, by knowledge about its nature and effects (Shi et al., 2014). There is therefore a basic need for research to communicate all relevant information related to the domain in a simple and effective manner. With this premise in mind, we deploy the analytic technique of visualization in the current research. Visualization has been used in domains such as environmental and climate science to effectively communicate the meaning in complex and large data sets to a wide audience (Bohman et al., 2015). Additionally, in the realm of climate change, since the impact varies geographically, there is an inherent spatial dimension to its adaptation and mitigation which lends itself very well to visualization. Visual representation of scientific data helps communicate and increase the knowledge and recognition of the effects of climate change and of planning and decision making in the domain (Salter et al., 2009; Sheppard 2012; Sheppard et al. 2011; White et al. 2010). Being an exploratory research, our objective is to be data-driven and identify patterns and meaning in the data by directly interacting with the data, gaining insight, drawing conclusions and making fact-based recommendations. We call this evidencebased climate change analysis.

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The research methodology is comprised of the following phases: data collection, indicator selection, data preparation, analytics platform and tool selection, and analytics implementation (Table 1). The phases are general enough to be applied to any domain in which analytics is deployed (Raghupathi & Raghupathi, 2016). The data for climate change and economic growth indicators for the years 2005 to 2010 were downloaded from the World Bank website (http://data.worldbank.org/data-catalog/world-development-indicators). This was the only available data. There are a few reasons why data was not available for some indicators, countries and years, in the data source. Some indicators are derived from sporadic surveys and are only available every few years. Additionally, some countries do not report data on a regular basis due to several reasons such as conflict, lack of statistical means, and others. Also, in some countries data simply does not exist for some years. Despite these challenges, the indicators from World Bank are generally accepted as authentic indicators of economic growth and climate change (http://data.worldbank.org/indicator). As the World Bank says, “the primary World Bank collection of development indicators, compiled from officially-recognized international sources…presents the most current and accurate global development data available, and includes national, regional and global estimates.” The economic indicators include GDP (current US$), GDP per capita, GDP growth (annual %), Gross savings (% of GDP), Trade (% of GDP), Industry (% of GDP), and Exports of goods and services (% of GDP). The climate change indicators include CO2 emissions (kt), CO2 emissions per capita, Forest area (% of land), Improved water source (% of population with access to improved water), Energy use (kt of oil equipment), Energy use per capita (kg of use per capita), and Electric power consumption per capita (kw per capita). Table 2 shows a description of the variables with measures. We collected the data for 131 countries and used the income group classifications from the World Bank (http://go.worldbank.org/CWTURYIPS0): low income, lower middle income, upper middle income, and high income. The high-income classification is bifurcated into member and non-member countries of the Organisation for Economic Co-operation and Development (OECD). The OECD strives to promote and maintain the economic and social well-being of its member countries. Most country-level research uses World Bank’s income group classification as the benchmark for comparative trend analyses. In our data, 47 countries fall under the high-income classification, 40 under upper middle income, 32 under lower middle income, and 12 under lower income classification. We included the geographic regions where the countries belong, such as East Asia and Pacific, Middle East and North Africa, Europe and Central Asia, Latin America and Caribbean, North America, South Asia, and Sub-Saharan Africa.

Table 1. Research methodology summary Data Collection

World Bank

Indicator Selection

Economic and Climate Change indicators Control: Income group, Region

Data Preparation

Data extracted from World Bank website in csv format and prepared for loading into analytic tools

Platform /Tool Selection

Multiple tools

Implementation

Analysis and reports implementation using analytic tools

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Table 2. Description of indicator variables Climate Change Indicators CO2 emissions (kt)

Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. Excludes carbon dioxide produced during consumption of solid, liquid, and gas fuels, and of gas flaring.

CO2 emissions per capita

CO2 emissions divided by population

Forest area (% of land area)

Land under natural or planted stands of trees of at least 5 meters in situ, whether productive or not, and excludes tree stands in agricultural production systems (e.g., in fruit plantations or agroforestry systems) and trees in urban parks and gardens

Improved water source (% of population with access)

% of population using an improved drinking water source, including piped water on premises and other improved drinking water sources (public taps, standpipes, tube wells, boreholes, protected dug wells and springs, rainwater)

Energy use (kg of oil)

Use of primary energy before transformation to other end-use fuels, which is equal to indigenous production plus imports and stock changes, less exports and fuels supplied to ships and aircraft engaged in international transport

Energy use per capita (kg of oil per capita)

Energy use divided by population

Electric power consumption (kw per capita)

Measures the production of power plants and combined heat and power plants, less transmission, distribution, and transformation losses and own use by heat and power plants Economic Growth Indicators

GDP (US$)

Gross Domestic Product

GDP per capita (US$)

GDP divided by population

GDP growth (annual %)

Annual Percentage Growth of GDP at market price based on constant local currency

Gross savings (% of GDP)

Gross national income less total consumption, plus net transfers measured as a share of Gross Domestic Product

Trade (% of GDP)

Sum of exports and imports of goods and services measured as a % of GDP

Industry value added (% of GDP)

Net output of a sector after totaling all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. Comprises value added in mining, manufacturing, construction, electricity, water, and gas.

Exports of goods and services (% of GDP)

Value of all goods and market services provided to the rest of the world. Includes the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, including communication, construction, financial, information, business, personal, and government services; excluding compensation of employees, investment income, and transfer payments. Control Variables

Income Group

High OECD/non-OECD, upper middle, lower middle, low

Region

East Asia/Pacific, Europe/Central Asia, Latin America/Caribbean, Middle East/North Africa, North America, South Asia, Sub-Saharan Africa

The raw data were extracted in CSV format from the sources, and the extracted data were integrated, cleansed, and standardized for loading into the analytics tool. To perform the analytics, several tools, which utilize visualization and other techniques, were chosen for identifying trends and patterns in the data and for facilitating various analyses. To reiterate, based on the literature, our overall data-driven research proposition is that economic growth is positively associated with climate change. In the datadriven approach, we let the data tell the story (U.S. Environmental Protection Agency, 2016).

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RESULTS AND ANALYSIS The distribution of the sample by region and by income are shown in Figure 1. Figure 1 shows that the region of Europe and Central Asia has the majority of high-income OECD countries followed by North America. North America is comprised of all high-income OECD countries. The region of Sub-Saharan has the highest number of low-income countries. We analyzed the different income groups to discern possible trends and variations in economic growth and economic growth.

CO2 Emissions Since CO2 emission is an important indicator of climate change, we analyzed it for the sample countries for the period 2005 to 2010 (Figure 2). Figure 2 reveals a drop in CO2 emissions in 2008-09 for all income groups. There is a likely explanation for the drop: the 2007-08 global financial crisis saw the failure of large financial institutions, drop of stock markets worldwide, and an overall decline in industrial and economic activity. It’s reasonable to presume that the drop in CO2 emissions is associated with the decline in the global economy that followed the crisis. We compared the median and average CO2 emissions across different income groups to gain a better understanding of the pattern of CO2 emissions over the years (Figure 3). The top panel in Figure 3 shows average emissions, and the bottom panel shows the median emissions, for the four income groups. In terms of average emissions, upper middle-income countries have surpassed high income countries since 2009, while in median emissions terms, high-income countries take the lead. The low-income group shows the lowest emissions and no variation over the years in terms of average or median emissions. CO2 emissions seem to be positively associated with the income of Figure 1. Distribution of the sample of countries by region and by income group

*For a more accurate representation see the electronic version.

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Figure 2. Trend of CO2 emissions

*For a more accurate representation see the electronic version.

Figure 3. Trend of median and average CO2 emissions

*For a more accurate representation see the electronic version.

countries. For a clearer picture, we considered CO2 per capita emissions instead of total CO2 emissions, because per capita takes population into account. It is a fact that low-income countries have a much higher population than high-income countries, and therefore including per capita emission in our study offers a more balanced approach for analysis. The box chart in Figure 4 clearly shows that the per capita CO2 emissions is much higher in highincome countries than in others. Elevated levels of industrialization in high-income countries accounts

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Figure 4. CO2 emissions per capita

for the high emission levels. Not surprisingly, low-income countries show the lowest emissions per capita. Clearly, there is a positive association between a country’s per capita CO2 emissions and income. Economic growth is associated with higher income and therefore with higher emissions (Ravallion et al., 2000). Countries need to consider a possible trade-off between economic growth and social equity in ensuring prevention of climate change and global warming. The Kyoto Protocol (KP) is an international treaty that extends the 1992 United Nations Framework Convention on Climate Change (UNFCCC) that commits its parties to reduce greenhouse gas emissions, including CO2 emissions (Iwata and Okada, 2014). The KP was initially adopted in Japan in 1997 and entered into force in 2005 with an objective to reduce GHGs by about 5% from 1990 levels. In the second commitment period, parties committed to reduce GHG emissions by at least 18% below 1990 levels during the years 2013-2020. Countries that have binding emission targets under the KP have consistently lower CO2 emissions (about 7-105 lower) than they would, in the absence of benchmarks (Almer and Winkler, 2017; Grunewald and Martınez-Zarzoso, 2009). In spite of controversy on the effectiveness of the KP (Bohringer and Vogt, 2003), enforcing such treaty is generally viewed as an integral step to addressing global climate change (Rollings-Magnusson and Magnusson, 2000).

Energy Use and Electricity Consumption Figure 5 shows the distribution of energy usage and electricity consumption for the four income groups over the six years we are focused on here. The top portion of the graph shows the distribution for energy usage and the lower portion depicts the distribution for electricity consumption. As seen in Figure 5, high-income OECD countries have the highest electricity consumption, and the consumption has increased steadily over time. The consumption in the low- and middle-income countries has been limited and did not change significantly in the period 2005 to 2010. With respect to energy

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Figure 5. Distribution of energy use and electric power consumption

*For a more accurate representation see the electronic version.

usage, high-income non-OECD countries exhibit the greatest energy usage, followed by high-income OECD. Lowest usage is by low-income countries. Our results reflect two important issues that need to be addressed. One is the disparity between high and low-income countries in terms of energy and electricity usage or consumption. The United Nations Framework Convention on Climate Change (UNFCCC) under the Kyoto Protocol set up international funding programs such as the Adaptation Fund to finance projects aimed at helping low income countries adapt to the harmful effects of climate change. This enables transfer of funds and technology from developed/high income to developing/low income countries. The second issue is to ensure that the high usage and consumption of energy and electricity by high income countries does not adversely impact climate change. It is therefore imperative that these countries reinforce the importance of sustainable energy sources and consumption (Winston et al., 2017). Reducing emissions from the energy sector is a major challenge for climate change since electricity generation is one of the major contributors to anthropogenic emissions (Hansen et al., 2007; Voorspools et al., 2000; Vougioukli et al., 2017). There is a need for countries to explore alternative means of electricity production using renewable rather than non-renewable sources. An example is the hydropower which is a way of producing electricity using moving water (Vougioukli et al., 2017). Hydropower can be used on a small scale to generate electricity in remote or mountainous areas.

Forest Area We looked at the distribution of forest area, which represents the percentage of natural or planted trees that are preserved, excluding trees in urban parks and gardens. Figure 6 shows the distribution by region. Figure 6 depicts a heat map and shows regions with high forest area in green and low forest area in red. Regions such as East Asia and Pacific (Brunei, Japan, Korea, Malaysia, Cambodia, and Indonesia), Europe and Central Asia (Finland, Sweden, Slovenia, Latvia, and Estonia), parts of Sub-Saharan Africa

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Figure 6. Distribution of forest area by region

*For a more accurate representation see the electronic version.

(Gabon, Congo Democratic Republic), Latin America and Caribbean (Brazil, Columbia, Bolivia, Peru, and Venezuela) show high levels of forest area. The Sub-Saharan region belongs to the low-income country classification, but it also shows a high level of forest area. We looked next at the distribution of forest area by income to see whether there is any association (Figure 7). We expected to find that high-income countries emphasize industrialization over agriculture and would show greater deforestation compared to medium- and low-income countries. Figure 7 shows that high-income OECD countries have the largest percentage of forest area, followed by upper middle- and low-income countries. While the level of forest area is fairly consistent for the high and upper middle-income countries, it decreases over time for low-income and lower-middle-income countries. Efforts to increase industrialization may account for this decrease in forest area in low- and lower-middle-income countries. It’s noteworthy that, contrary to our expectation, economic development did not adversely affect forest area; high-income countries still show the greatest percentage of forest area. This finding offers promise.

GDP per Capita and Energy Usage per Capita We looked at the economic indicator of GDP per capita for an association with energy usage per capita to learn whether developed countries with high GDP per capita use more energy than other income groups (Figure 8). Figure 8 shows the relationship between GDP per capita and energy use per capita to be significant (p 0 are influence zones of minima. ∆Du = 0 interprets edge locations, and represent an essential property for the construction of morphological filters. The idea here is to apply either dilation or erosion to the image I, depending on whether the pixel is located within the influence zone of a minimum or a maximum. The Catchment basin C(M) associated to a minimum M is the set of pixels p of Ω an open bounded domain of R, such that a water drop falling at p flows down along the relief, following a certain descending path, and eventually reaches M. The catchment basins of an image I correspond then to the influence zones of its minima, and the watershed will be defined by the lines that separate adjacent catchment basins (Belaid and Mourou 2009; Gonzalez and Woods 2009). Computation of watersheds and the most commonly used is based on an immersion process analogy. This immersion process can be formulated as follows, Let hmin and hmax are the smallest and the largest values taken by f. Let Th = {p ∈ Ω, f (p) ≤ h } be the threshold set of f at level h. A recursion with the

gray level h increasing from hmin and hmax , in which the basins associated with the minimum of f are successively expanded. Let X h is the union of the set of basins computed at level h. A connected component of threshold set Th + 1 at level h + 1 can be a new minimum, or an extension of a basin in X h .

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By denoting minh , the union of all regional minima at level h, the following recursion defines the watershed by immersion. x = T hmin  hmin  ∀h ∈ hmin,hmax − 1 , X n +1 = minh +1 UIZTh +1(X n )    k

( )

with IZTh +1 = ∪ iZTh +1 X n , k − is the number of minima of I and iZTh +1 (X hi ) i =1

{

i

}

iZ Ω (Yi ) = Z ∈ Ω, ∀k ≠ i, dΩ (Z ,Yi ) ≤ dΩ (Z ,Yk )

(11)

The set of the catchment basins of a gray level image I is equal to the set Xh max . At the end of this

process, the watershed of the image I is the complement of Xh max in Ω (Belaid and Mourou 2009). The main issue with watershed technique is that it is highly sensitive to local minima. And at each minima a watershed is created. If there is a noise in the image, it creates a watershed which is not desired. So the image with noise will have an impact on the segmentation. In order to rectify this issue the sigma setting of the Gaussian filter is adjusted to smoothen the image, which minimizes the noise and the local minima in turn. This enhances the usefulness of the watershed segmentation. The level of this sigma can be balanced by the user. While setting up the sigma value if the Gaussian filter care has to be taken with the value of sigma, if the value of sigma is too high, the watershed location will be shifted to some other location due to the impact of Gaussian blurring. This algorithm is based on region, and tried to create different regions present in the given input image. Later based on the similarities, the region can be split or merged. Once again the complexity of background in the input image creates regions which are the combination of foreground and background in certain points due to similarities. The watershed segmentation results are shown in Figure 5 and the performance watershed technique is shown in Table 1.

Maximal Similarity Based Region Merging (MSRM) From the analysis and experimentation of the above methods, it is evident that single segmentation techniques will not suited to the requirement. This makes the automatic segmentation very complex and leads to the need of suitable hybrid segmentation techniques. Automatic segmentation of object from background is very hard in case of natural images with color and texture features. Because of this difficulty, semi-automatic segmentation methods with user interactions have been become very popular. The low level image segmentation methods like mean shift (Cheng 1995; Bailer et al. 2005; Zheng et al. 2009), watershed (Belaid and Mourou 2009) etc. will divide the image into small regions. Even these may suffer with over segmentation issues, these methods provide a good reason for the low level operation such as region merging. This is a Hybrid technique which works using the combination of mean shift and region merging technique. The MSRM method is based on the initial segmentation of mean shift. The interaction information is through markers, which is the input provided by the user

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Figure 5. Results of Arecanut crop bunch segmentation using Watershed method

by indicating roughly the object and background. The markers are simple strokes. Once the strokes are marked on the mean shifted input image, this method calculates the similarity of various regions and merges them based on maximal similarity rule. At the end of merging process, the object is extracted from the background (Singh and Singh 2010). The mean shift algorithm is defined as in (Bailer et al. 2005; Zheng et al. 2009), Let S ⊂ X be a finite set or data or sample. Let K be a kernel and w = S → (0, ∞) a weight function. The sample mean with kernel K at x ∈ X is defined as,

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∑ K (s − x )w(s)s m(x ) = ∑ K (s − x )w(s)

(12)

s ∈S

s ∈S

Let T ⊂ X be a finite set or (cluster centers). The evolution of T is the form of iterations T ← m(t ) with m(T ) = {m(t ); t ∈ T } known as a mean shift algorithm (Bailer et al. 2005). For each t ∈ T , there is a sequence t, m(t ), m(m(t )),.... is called as the trajectory of t . The weight w(s ) can be either fixed all through the process or re-evaluated after each iteration. It may also be a function of the current ‘T’. The algorithm works till it reaches a fixed point (m(T ) = T ) . In this work, the EDISON system was used to carry out mean shift segmentation (EDISON v1.1 2002). Once the mean shift segmentation is done, there are small regions available. To guide the region merging process, the regions should be represented by certain descriptors with a rule for merging. A region can be described by some features like color, texture, edge, shape and size. Color histogram is used as an effective feature for representing the object color statistics. The RGB color space is used for color histogram and each color channel i.e., R,G,B are quantize into 16 levels and histogram of each color is computed in the feature space of 16x16x16= 4096 bins. In the interactive program part, users will mark the some regions as object and some as background. The similarity measure (R, Q) between two regions R and Q to accommodate the comparison between various regions is defined as, 4096

ρ(R,Q ) = ∑ HistRu ⋅ HistQu

(13)

u =1

where HistRu and HistQu are normalized histograms of R and Q, and u represents the uth element of them. ρ is a divergence measure known as Bhattacharyya coefficient (Fukunaga 1990) having a straight forward geometric interpretation. It is the cosine of the angle between the unit vectors.

(

HistR1 ,...., HistR4096

)

T

and

(

HistQ1 ,...., HistQ4096

) . T

The higher the value of Bhattacharyya coefficient between R and Q, the higher the similarity between them. In the integrative image segmentation, user has to specify the object and the background. This can be marked by drawing some markers, such as a line, curve or a stroke to highlight the object and the background. One the marking is done, each region is labeled with three regions such as, marked object, marked background and non-marked region. For the total extraction of the object, user needs to assign each non-marker region with a correct label of object region or background region automatically. After marking process is done, the challenge lies in extraction of object contour from background. To identify all non-marker regions with the guidance of object and background markers, an adaptive maximal similarity based merging is used. Let Q be an adjacent of R and denote by SQ = SiQ , i = 1, 2,..., q

{ }

the set of Q’s adjacent regions. The similarity between Q and all its adjacent regions, i.e.,

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(

)

ρ Q, SiQ , i = 1, 2,...q are calculated. Obviously R is a member of SQ. If the similarity between R and Q

(

)

is the maximal one among all the similarities ρ Q, SiQ , we will merge R and Q. and the merging rule is given by,

(

)

Merge R and Q if ρ(R,Q ) = maxρ Q, S iQ i =1,2,...q

(14)

The MSRM process has two stages; first stage is about merging marker background regions with their adjacent regions. After this merging some non-marker background regions will be merged with the respective background markers. The second stage is focused on non-marker regions which are still remaining after first stage. This procedure is iteratively implemented and the iteration stops when the entire non marker region set will not find new regions for merging (Ning et al 2009). The corresponding results are shown on Figure 6 and the comparison of performance of this hybrid technique with other techniques is shown in Table 1. This hybrid segmentation technique gives somewhat promising result compared to the previous methods. This drives the need of hybrid segmentation techniques further for the problems related to natural image segmentation.

DISCUSSION AND CONCLUSION The different segmentation techniques explored in this chapter are having certain limitations (Khan and Ravi 2013). The threshold segmentation method neglects the spatial information of the image, it highly noise sensitive and selection of the threshold value is crucial and based on this it suffers either over segmentation or under segmentation issues. Sometimes this leads to pseudo edges or missing edges. In K-means clustering approach the selection of desired number of clusters based on needs to be set earlier. This creates ambiguity while setting of the number of clusters. Fuzzy C-means method raises the ambiguity among the choice of features for better results for the given image. This is somewhat slow; this can be overcome by using certain histograms as in Fast Fuzzy C Means clustering method (Chaabane et al. 2008). Watershed methods even though give good results, it suffers from over segmentation and it unnecessarily segments into a number of regions (Belaid and Mourou 2009). It provides the connected component at the cost of computation time. This faces difficulty when segmenting the image with noise. Maximal Similarity based Region Merging method is semi automatic and needs human intervention for marking the background and the object; this makes this method computationally slow. It is intolerant to noise and moderately detects multiple objects. After exploring the above mentioned color segmentation techniques since we got better results using MSRM in comparison with other techniques, we have evaluated the MSRM technique using the evaluation parameters such as, Correlation, Jaccard coefficient, mean square error (RMSE) and Dice coefficient. The correlation used as a measure of the similarity between ground truth image and a segmented image. The value of the correlation coefficient is between -1 and 1, where -1 indicates the similarity measure is away from the desired result. The Jaccard similarity coefficient, also known as the Tanimoto coefficient, measures the cover of two sets. It is characterized as the measure of the intersection

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Figure 6. Results of Arecanut crop bunch segmentation using Maximal Similarity based Region Merging (MSRM) method

of the sets partitioned by the span of their union. The Jaccard coefficient is zero if the two sets are disjoint, and is one if they are identical. So when applied this to evaluate the agreement of segmentation results, the goal is to get as close to 1 as possible. The simplest of image quality measurement is Mean square Error (MSE). The large value of MSE means that image is poor quality and The Root MSE (RMSE) is calculated using the formula, RMSE = MSE . The Dice coefficient is similar to Jaccrd coefficient and represents the size of the union of 2 sets divided by the average size of the two sets. Dice coefficient with value of 0 indicates no overlap; and a value of 1 indicates perfect agreement. Higher numbers indicate better agreement.

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The maximal similarity based region merging segmentation (MSRM) method is better compared to other methods and the corresponding evaluation is shown in Table 1 for images shown in Figure 6. From Table 1 it is evident that MSRM provides fair segmentation result and needs some improvement. This further drives for the need for some robust color segmentation algorithm for the purpose of Arecanut crop bunch segmentation.

FUTURE RESEARCH Based on the experimentation on different color segmentation techniques it is clear that there will be a need of efficient and robust color segmentation techniques is essential for natural images. Also with single algorithm the results are not promising, this makes the essentiality of some hybrid color segmentation techniques which is either the fusion of existing algorithms. In the last technique the approach is semiautomatic which require human intervention in choosing the back ground and the object of interest. So based on these issue the future direction of this work focused at the following: 1. Automation of object and background selection part of MSRM algorithm. 2. Exploring graph based segmentation methods for the better results (Baldevbhai and Anand 2012; Shi and Malik 2000). 3. Exploring more hybrid segmentation methods i.e., fusion of segmentation methods. 4. Formulation of robust color segmentation techniques for images with complex background. 5. Exploration and experimentation of new segmentation techniques on different color spaces and hybridization of the color spaces.

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Kim, J. B., & Kim, H. J. (2003). Multiresolution-based watersheds for efficient image segmentation. Pattern Recognition Letters, 24(1–3), 473–488. doi:10.1016/S0167-8655(02)00270-2 Koch, B., and Khosla, R.(2003). The Role of Precision Agriculture in Cropping Systems. Journal of Crop Production, 9(1/2), 361-381. Lee, D., Archibald, J. K., Chang, Y., & Greco, C. R. (2008b). Robust color space conversion and color distribution analysis techniques for date maturity evaluation. Journal of Food Engineering, 88(3), 364–372. doi:10.1016/j.jfoodeng.2008.02.023 Lee, D., Archibald, J. K., & Xiong, G. (2011). Rapid Color Grading for Fruit Quality Evaluation Using Direct Color Mapping. IEEE Transactions on Automation Science and Engineering, 8(2), 292–302. doi:10.1109/TASE.2010.2087325 Lee, D. J., Chang, Y., Archibald, J. K., & Greco, C. G. (2008a). Color quantization and image analysis for automated fruit quality evaluation. Proceedings of the IEEE International Conference on Automation Science and Engineering (pp. 194-199). 10.1109/COASE.2008.4626418 Liu, T., Xie, J., He, Y., Xu, M., & Qin, C. (2009). An Automatic Classification Method for Betel Nut Based on Computer Vision, Proceedings of the IEEE International Conference on Robotics and Biomimetics, Guilin, China (pp. 19-23). 10.1109/ROBIO.2009.5420823 Lucchese, L., & Mitra, S. K. (2001). Color image segmentation: a state-of-the-art survey. In Proceedings of the Indian National Science Academy (INSA-A), New Delhi, India (Vol. 67, pp. 207–221). Matthews, J. (1983). Some challenges for engineers in agriculture. Journal of the Royal Agricultural Society of England, 144, 146–158. Mondal, P., & Tiwari, V. K. (2007). Present status of Precision Farming: A Review. International Journal of Agricultural Research, 2(1), 1–10. doi:10.3923/ijar.2007.1.10 Muthukannan, K., & Latha, P. (2012). Clustering Techniques based Crops Image Segmentation. International Journal of Computer Applications (IJCA), 2, 33-37. Ning, J., Zhang, L., Zhang, D., & Wu, C. (2009). Interactive image segmentation by maximal similarity based region merging. Pattern Recognition, 43(2), 445–456. doi:10.1016/j.patcog.2009.03.004 Pantofaru, C., & Herbert, M. (2005). A Comparison of image segmentation algorithms [Tech. Report] (CMU-RI-TR-05-40). Pratt, W. K. (2008). Image segmentation - Text book of Digital image Processing (4th ed., pp. 579–622). Wiley. Scarlet, A. J. (2001). Integrated control of agricultural tractors and implements: A review of potential opportunities relating to cultivation and crop establishment machinery. Computers and Electronics in Agriculture Journal, 30(1-3), 167–191. doi:10.1016/S0168-1699(00)00163-0 Schettini, R. (1993). A segmentation algorithm for color images. Pattern Recognition Letters, 14(6), 499–506. doi:10.1016/0167-8655(93)90030-H

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Schillaci, G., Pennisi, A., Franco, F., & Longo, D. (2012). Detecting tomato crops in greenhouses using a vision based method. Proc. International Conference on Safety Health and Welfare in Agriculture and in Agro-food Systems, Ragusa – Italy (pp. 252-258). Shi, J., & Malik, J. (2000). Normalized Cuts and Image Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8), 888–905. doi:10.1109/34.868688 Singh, G., & Kamal, N. (2013). Machine Vision System for Tea Quality Determination – Tea Quality Index (TQI). IOSR Journal of Engineering, 3(7), 46-50. Singh, K. K., & Singh, A. (2010). A Study of Image Segmentation Algorithms for Different Types of Images. International Journal of Computer Science Issues, 7(5), 414–417. Sridevi, M., & Mala, C. (2012). A Survey on Monochrome Image Segmentation Techniques. Procedia Technology (Vol. 6, pp. 548-555). Stafford, J. V. (2000). Implementing Precision Agriculture in the 21st Century [Keynote address]. Proceedings of AgEng (Vol. 76, 267-275). Stafford, J. V., & Ambler, B. (1994). In-Field location using GPS for spatially variable field operations. Computers and Electronics in Agriculture Journal, 11(1), 23–36. doi:10.1016/0168-1699(94)90050-7 Stafford, J. V., Ambler, B., Lark, R. M., & Catt, J. (1996). Mapping and interpreting the yield variation in Cereal Crops. Computers and Electronics in Agriculture Journal, 14(2-3), 101–119. doi:10.1016/01681699(95)00042-9 Vijay, J., Sohani, M., Shrivas A. (2014). Color Image Segmentation Using K-Means Clustering and Otsu’s Adaptive Thresholding. International Journal of Innovative Technology and Exploring Engineering, 3(9), 72-76. Xi, Y., Feng, D. D., Wang, T., Zhao, R., & Zhang, Y. (2007). Image segmentation by clustering of spatial patterns. Pattern Recognition Letters, 28(12), 1548–1555. doi:10.1016/j.patrec.2007.03.012 Xu, L. (2009). Strawberry Maturity Neural Network Detecting System Based on Genetic Algorithm. Computer and Computing Technologies in Agriculture II, 2, 1201–1208. Yang, Y., Zheng, Ch., & Lin, P. (2005). Fuzzy C-means clustering algorithm with novel penalty term for image segmentation. Opto-Electronics Review, 13(4), 309–315. Yin H., Chai, Y., Yang, S. X., and Mitta, G. S. (2009). Ripe tomato extraction for a harvesting robotic system. In Systems, Man and Cybernetics (pp. 2984-2989). IEEE. Zhang, N., Wang, M., & Wang, N. (2002). Precision agriculture worldwide - an overview. Journal of Computers and Electronics in Agriculture, 36(2-3), 113–132. doi:10.1016/S0168-1699(02)00096-0 Zheng, L., Zhang, J., Wang, Q. (2009). Mean-shift-based color segmentation of images containing green vegetation. Journal of computers and electronics in agriculture, 65(1), 93-98. This research was previously published in the Handbook of Research on Advanced Hybrid Intelligent Techniques and Applications edited by Siddhartha Bhattacharyya, Pinaki Banerjee, Dipankar Majumdar, and Paramartha Dutta, pages 1-28, copyright year 2016 by Information Science Reference (an imprint of IGI Global).

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Chapter 49

Applying Indigenous Knowledge in Agricultural Extension in Zimbabwe Tinashe Mugwisi University of South Africa, South Africa

ABSTRACT Indigenous knowledge (IK) has been viewed as local knowledge that has been developed and accumulated, over time, by a community and has been passed down over generations. Such knowledge is represented in most spheres of human activity, such as in agriculture, traditional and alternative medicine, human and animal health, forestry and botany, among others. The purpose of this chapter is to discuss how IK is accessed and used by agricultural extension workers in Zimbabwe. The study reviews the relevant literature and focuses largely on Indigenous Agricultural Knowledge (IAK). The study utilises both quantitative and qualitative methods; a questionnaire was distributed and extension workers drawn from eight provinces of Zimbabwe. Mashonaland Central Province produced the highest number of respondents because the population for the province included ward and village extension workers in addition to the district and provincial extension officers and supervisors targeted in each province. From the projected sixty (60), forty four (44) districts participated. The study observed that indigenous knowledge is relevant in modern day agriculture and should be given sufficient attention in extension work. The study recommends that IK be documented and integrated into research, education and training for posterity.

INTRODUCTION Woytek (1998, p. 1) opines that the literature on indigenous knowledge (IK) does not provide a single definition of the concept, partly due to the differences in background and perspectives of the authors, ranging from social anthropology to agricultural engineering. The United Nations Environmental Programme (2008, p. 21) and Masalu, Shalli and Kitula (2010, p. 4) observe that a variety of terms have been used to describe this form of unique knowledge. These have included such terms as “local knowledge,” “traditional knowledge,” “indigenous traditional knowledge,” “indigenous technical knowledge”, “tradiDOI: 10.4018/978-1-5225-9621-9.ch049

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 Applying Indigenous Knowledge in Agricultural Extension in Zimbabwe

tional environmental knowledge”, “rural knowledge”, “traditional ecological knowledge” and so forth. Warren (1991), Woytek (1998), and Njiraine, Ocholla and Le Roux (2008) view indigenous knowledge as the local knowledge – knowledge that is unique to a given culture or society, which contrasts with the international knowledge system generated by universities, research institutions and private firms. It is the basis for local-level communication and decision making in agriculture, health care, food preparation, education, natural-resource management, and a host of other activities in rural communities. Rajasekaran, Martin and Warren (1994), Ghorbani, Khodamoradi, Bozorgmanesh and Emami (2012), Dixon (2001), Tikai and Kama (2004), Karthikeyan, Veeraragavathatham, Karpagam and Firdouse (2009) view indigenous knowledge as a systematic body of knowledge and skills acquired by local people through the accumulation of experiences, informal experiments, an intimate understanding of the environment. Woytek (1998, p. 2) observes the characteristics of IK, which distinguishes it from other knowledge as: • • • • • •

Local: It is rooted in a particular community and situated within broader cultural traditions; it is a set of experiences generated by people living in those communities. When transferred to other places, there is a potential risk of dislocating IK. Tacit Knowledge: Not easily codifiable. Transmitted Orally: Or through imitation and demonstration. Codifying it may lead to the loss of some of its properties. Experiential Rather than Theoretical Knowledge: Experience and trial and error, tested in the rigorous laboratory of survival of local communities constantly reinforce IK. Learned through Repetition: this is a defining characteristic of tradition even when new knowledge is added. Repetition aids in the retention and reinforcement of IK. Constantly Changing: being produced as well as reproduced, discovered as well as lost; though it is often perceived by external observers as being somewhat static.

According to Reij, Scoones and Toulmin (1996), Woytek (1998), and Warren (1991), the indigenous information systems are dynamic, and are continually influenced by internal creativity and experimentation as well as by contact with external systems and influences such as from immigrants, return migrants, extension workers, and visiting businessmen and so on. Woytek (1998, p. i) and Masalu et al. (2010, p. 5) perceive that indigenous knowledge is important as it contributes to communities in many ways. It provides the basis for problem-solving strategies for local communities, especially the poor. It represents an important component of global knowledge on development issues. Learning from IK, by investigating first what local communities know and have, can improve understanding of local conditions and provide a productive context for activities designed to help the communities. Understanding IK can increase responsiveness to clients. Adapting international practices to the local setting can help improve the impact and sustainability of development assistance. Sharing IK within and across communities can help enhance cross-cultural understanding and promote the cultural dimension of development. Help in identify innovative pathways to sustainable human development that enhance local communities and their environment. The United Nations Environmental Programme (2008) concur, adding that indigenous knowledge systems have enabled the various communities in those countries to live in harmony with their environ-

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ments for generations, and the systems are important tools in environmental conservation and natural disaster management. Some forms of IK are expressed through stories, songs, myths, proverbs, cultural values, beliefs, rituals, community laws and local language. IK is mainly of a practical nature, particularly in such fields as fisheries, agriculture, health, horticulture, forestry and environmental management in general (Masalu et al., 2010, p. 4). In traditional medical practice, certain herbs are known to treat a variety of ailments in both humans and animals. For example, according to the United Nations Environmental Programme (2008, p. 96) the Swazis use lihala (Aloe saponaria) to make preparations for treating high blood pressure, bile for nausea, fever and lethargy, snake bite, colon irritation, stomach ache. Ash from the leaves of the lihala can be used as cooking soda and as an ingredient for snuff, used by adults only.

BACKGROUND Agricultural extension, “involves the transfer of agricultural information and technology to the farmers and similarly transferring information from farmers to researchers” (Pazvakavambwa & Hakutangwi, 2006, p. 217). Umali-Deininger and Schwartz (1994, p. 1) argue that: “The backbone of all agricultural extension endeavours is the transfer of agricultural information to enhance the productive capacity of farmers.” Umali-Deininger and Schwartz (1994) further observe that embracing new technologies and production approaches in farming systems is essential in meeting the challenges of growing populations and the decreasing availability of productive land for agriculture. These efforts can be realised through the utilisation of various extension systems and approaches. Agricultural extension in Zimbabwe has mostly been public sector driven through the Ministry of Agriculture. Private extension services are largely undertaken and supported by farmers’ unions, private research organisations, and agricultural input suppliers such as seed and fertiliser companies as part of their business marketing. NGOs also provide their own extension services. Agricultural extension was introduced in Zimbabwe in 1927 by Emory D. Alvord with the help of nine field demonstrators (FAO, 2003). The Department of Agricultural Technical and Extension Services (AGRITEX) was established in 1981 following the merger of the Department of Conservation and Extension (CONEX) and the Department of Agricultural Development (DEVAG). CONEX had previously provided extension to large scale commercial farms while DEVAG catered for communal/ rural farmers (Rukuni, 2006). AGRITEX is headed by a Principal Director and seconded by two directors who are responsible for the Technical Division and Field Division respectively. The Field Division is headed by a director who is directly responsible for (8) eight provincial extension officers. Below the provinces are sixty (60) district extension officers, and below them are ward level extension personnel. Each province has six subject matter specialists (SMS). At district level (all sixty districts), there are three subject matter specialists and three hundred and eighty (380) zonal agricultural extension supervisors. The flow of information in the communication process follows both the top-down model and the bottom-up approach. Through AGRITEX officers based at the district offices, information is passed on to the AGRITEX extension supervisors and extension workers and then to the farmers. The officers and agricultural extension workers are also responsible for transmitting indigenous knowledge technologies, practices and problems from farmers to specialists and researchers. This creates a research extension network that is critical for appropriate research and extension messages/ communication (MoAMID, Department of AGRITEX, 2010).

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MAIN FOCUS OF THE CHAPTER The aim of this chapter was to investigate the use of indigenous knowledge in agricultural extension by addressing the following research objectives: 1. 2. 3. 4.

To establish whether IK is used by agricultural extension workers. To ascertain the frequency of use of IK by agricultural extension workers. To investigate how agricultural extension workers acquire IK. To establish the types of IK obtained from various sources by agricultural extension workers.

ISSUES, CONTROVERSIES, PROBLEMS Various studies have been conducted on the application of IK across disciplines and across the geographical divide. The section below provides literature on how IK has been applied in agriculture.

Indigenous Knowledge Types and Agriculture Abioye, Zaid and Egberongbe (2011, p. 3) perceive that farmers adopt a wide range of indigenous agricultural practices based on generations of experience, informal experiments and intimate understanding of their environments. They further observe that the application of indigenous agricultural farming has been reflected in the following: • • • • •

Indigenous methods of maintaining soil fertility. Indigenous methods of controlling pests and diseases. Indigenous soil preparation and planting materials. Indigenous methods of controlling weeds. Indigenous methods of harvesting and storage.

Indigenous Methods of Maintaining Soil Fertility and Water Conservation Shetto (1999, p. 67) opines that traditional agriculture in the past was compatible with the level of population and ecological environment; long bush fallow periods were effective in restoring soil fertility for the prevailing level of crop yields and intensity of cropping. He further asserts that conventional flat cultivation, which is associated with modern (mechanised) agriculture tillage, encourages splash and sheet erosion as it leaves the soil surface bare, under sporadic tropical downpours. There are several IK methods of maintaining soil fertility and these include; shifting cultivation, mixed cropping, intercropping, mulching, compost (dead leaves), animal manure, (cow dung and goat droppings), chicken waste, planting local legumes (green manure), and charcoal ashes (Tikai & Karma 2004, p. 73; Lakra, Singh, Sinha, & Kudada 2010; Singh & Sureja, 2008, p. 645; Fowler & Rockstrom, 2001; Kolawole, 2005; Mowo, Janssen, Oenema, German, Mrema and Shemdoe, 2006; Notsi 2012, and Mishra & Rai 2013). Non-tillage farming techniques, which involve clearing land by hand or burning, help maintain fertility and have minimum disturbance to the soil as only holes to accommodate the plant are dug using sticks (Tikai & Karma, 2004). 1109

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Singh and Sureja (2008, p. 643) observe that farmers are able to classify soils, broadly as agricultural and non-agricultural soils used for farming and domestic purposes. Based on their experience, farmers are also able to classify soils according to topography, texture and colour, stickiness, depth and crop comparability (Singh & Sureja, 2008, p. 643). Similarly, Mowo et al. (2006, p. 52), Buthelezi (2010), and Osbahra and Allanb (2003) note that the local qualities of good soils include colour (black), cracks during the dry season, presents vigorous growth of certain plants, good yield, and low watering frequency, and an abundance of earth worms. Notsi (2012, p. 13) indicates that one method among both Batswana and Basotho of evaluating soil moisture is the hand – feel and soil appearance method, determining soil moisture by hand only gives relative soil moisture and is more accurate than other methods. According to Singh and Sureja (2008, p. 647), Tekwa, Belel and Alhassan (2010), and Shetto (1999) other methods of soil and water conservation include making entire fields into smaller plots, planting shrubs and perennial grass on the edges to prevent runoffs, mulching of seeds to avoid wind erosion, in sloppy lands, hill terraces, earth contour ridges, construction and maintenance of waterways, ploughing and sowing across slopes reduces erosion and stone bunds/lines. Fenta (2009, p. 4) posits that farmers perceive soil fertility in terms of the capacity of soils for longterm productivity, their permeability, and water holding capacity, drainage, tillage, manure requirement and cultivability. To ascertain the accuracy of IK, Mowo et al. (2006, p. 47) compared soil fertility evaluation based on experience and knowledge of smallholder farmer communities with the evaluation by scientists based on soil analysis and model calculations. Farmers’ experience and knowledge of local indicators of soil quality were used in identifying soil fertility constraints and in generating resource flow maps. The study established that farmers’ indigenous knowledge in soil fertility evaluation mostly agreed with laboratory analysis and model calculations. Buthelezi (2010, p. 44) concurs observing that despite many differences between the scientific and indigenous approaches, farmers’ soil suitability evaluation and fertility perception corresponds with the scientific evaluation. Tekwa et al. (2010), and Mishra and Rai (2013) concluded that IK technologies appeared viable and relevant in conserving soil and water required for sustainable crop production.

Indigenous Methods of Controlling Pests Abate, Van Huis and Ampofo (2000, p. 642) assert that traditional control practices are still the major means of pest management to small-scale farmers in Africa and these control practices are based on built-in features in cropping systems, such as farm plot location, crop rotation, and intercropping, or on specific responsive actions to reduce pest attack, such as timing of weeding, use of plants with repellent or insecticide action, traps, scarecrows, smoke, and digging up grasshopper egg masses. MugishaKamatenesi, Deng, Ogendo, Omolo, Mihale, Otim, Buyungo and Bett (2008) identify the major field pests reported by farmers which included banana weevil, bean fly, cereal stem borers, pod feeders, grain moth, rodents, moths, termites, birds, aphids and cutworms. They observe that the use of synthetic pesticides has raised a number of both ecological and medicinal problems while botanical pesticides are hailed for having a broad spectrum of activity, being easy to process and use, with a short residual activity (Mugisha-Kamatenesi et al., 2008, p. 343). According to Tikai and Karma (2004, p. 71), and Mugisha-Kamatenesi et al. (2008, p. 343) some of the methods of controlling pests and diseases among crops include sanitation, burning and smoking, dusted plant materials (ashes and sand), and hand picking, fallowing and shifting cultivation, hand picking and squashing of beetles, slashing and burning, to use of physical barriers. Singh and Sureja (2008, p. 651) add that indigenous methods applied against 1110

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insects attack include that adult insects/caterpillars of different vegetables and pulse crops are physically picked from the plants of the infected fields and destroyed by burning and the resultant ashes are broadcasted to control the pests. Natural plant materials, using ash on crops, hot pepper mixed with ash, and spraying animal urine are found to provide effective substitutes for agrochemicals (Gana, 2003; Akullo et al., 2007, p. 7; Kiplang’at & Rotich, 2008, p. 725; Fenta, 2009, p. 3). Most of the indigenous insect pest control methods included measures to disrupt pests’ life cycle by periodically denying them food and to achieve maximum control where the manipulation of ordinary agricultural practices would follow. Odeyemi, Masika and Afolayan (2006, p. 169) observe that in the Eastern Cape, the stem borer (for example, Chilo partellus [Swinhoe]), grasshoppers, cut worms, millipedes, moles, birds and the maize storage weevil (Sitophilus zeamais) are some of the pests which pose a major threat to maize growers. Besides using synthetic pesticides, the authors note that intercropping was one way used to overcome this problem in which crops such as onion and garlic are known to have characteristic pungent smells that repel insects. They also observed that aqueous extract from plants such as wild marigold (unukanuke) and cape aloe (umhlaba) is prepared and sprayed on crops. Mugisha-Kamatenesi et al. (2008, p. 343) concluded that traditional pest control methods, particularly the use of indigenous pesticide plants if improved, offer a safer, eco-friendly, low cost and more dependable method of field crops protection.

Indigenous Methods of Controlling Weeds Weeding is generally conducted to eliminate plants which grow where they are not wanted as they may cause harm to legitimate crops. Tikai and Karma (2004, p. 74), and Notsi (2012) observe that methods of controlling weeds include hand weeding, shifting cultivation and fallowing, slashing and burning, intercropping and shallow cultivation. Singh and Sureja (2008, p. 646) also note that to enhance soil and water management, ploughing is a popular practice as it enables farmers to control pests, weeds and diseases by exposing the egg masses of insects and dormant spores of pathogenic organisms to the hot sun, killing embryos of weed seeds, while enhancing the water holding capacity of soil through reduced runoff losses. Rathore, Krose, Naro, Shekhawat and Bhatt (2012, p. 356) observed that the use of common salt for weed control under acidic conditions of a jhum paddy was not only effective in minimizing weed competition with planted crop, but also resulted in high productivity without negative impact on the fields. The method was also found to be cost effective compared to traditional methods such as hand weeding.

Indigenous Methods of Post Harvesting and Storage Studies have shown that communities preserve and store food for consumption after harvest as most crops are seasonal. The United Nations Environmental Programme (2008) for example, observes that in western Kenya beanstalks were burnt and the ashes used as a preservative for grain and cereals. Cowpea, apart from providing food during the rainy season, is harvested, boiled, dried and stored in granaries to be consumed during the dry season. Grain is harvested and dried in the sun after which it is sprinkled with ashes as long term preservation against pests and impending attacks. Ali, Yadav, Stobdan, and Singh (2012) identify three methods of storing vegetables, being sadong (underground pit), tsothbang

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 Applying Indigenous Knowledge in Agricultural Extension in Zimbabwe

(vegetable cellar), and charches (hanging) and these could keep fresh root crops, carrots, cabbage, onion and turnip fresh for periods ranging from two to eight months and in sub-zero temperature winter months. They observe that these methods can be helpful in developing low cost innovative methods of preservations, minimize the post-harvest losses and increase the availability of vegetables during winter months. Smit (1997), and Tikai and Karma (2004, p. 75) concur and add that storing crops in cool places such as sheds, pit storage and timely harvesting of crops to reduce high moisture content are some of the practiced IK methods. Also, Akullo et al. (2007, p. 6) observe that when farmers harvest cassava, for example, the tubers are buried in moist soil measuring one foot deep, while another method involves peeling, slicing, drying and storing in baskets. The harvested crops are dried and stored in various ways, including granaries for crops such as maize and other cereals. The granaries need to be well ventilated as moisture may cause the grain to rot (Kiplang’at & Rotich 2008, p. 726). Sinha (2010, p. 537) also notes that various trappings, rice mixed with toxic seeds, and leaves or branches of A.vulgaris are put in and around granaries for repelling insects as well as rats. Karthikeyan et al. (2009) looked at traditional storage practices in India observing that in the past, insect infestation was often a less serious problem because farmers cultivated traditional varieties, which although low yielding, were general less susceptible to insects attack. Karthikeyan et al. (2009), Sinha (2010), and Bett and Nguyo (2007) observe that the introduction of high yield varieties has resulted in high storage losses since the varieties are prone to insect attack, hence the need for remedies of which IK methods are considered low cost, avoid chemicals and use resources which are readily available. Seed Preservation For some communities, seed for planting, during the following season, is usually selected from the current harvest. As Moreno et al. (2006, p. 1778) observe the most common characteristics that Yaxcaba farmers take into account when selecting for seed are ear size and health uniformity of grain colour, and grain size, which are considered to be indicators of germination reliability. Kiplang’at and Rotich (2008, p. 725), and Sinha (2010) observe that farmers select seed which is healthy and a good size. These are then placed in baskets and hung on kitchen ceilings so that the smoke and heat can dry and preserve them. Ash and other concoctions are sprinkled over the seed to prevent the grain from being attacked by rodents, insects and other potentially harmful pests (Karthikeyan et al. 2009). Similarly, Moreno et al. (2006, p. 1782) note that in addition to granaries, some farmers make use of various containers to store their seed, placing them in different locations and maize seed ears are stored in the rafters of a household kitchen. Notsi (2012, p. 11) notes that among the Batswana and Basotho the seeds of indigenous vegetables such as Rothwe, theepe, tenane and morogo wa dinawa are collected when they are dry. Women dispatch the seeds by shaking or threshing dried indigenous vegetables; this will usually suffice for extracting the seeds, and the seeds are protected from over-drying by covering them with leaves or other specially prepared mixtures bags, or clay pots are also used to minimize the risk of over drying. Most seed or seedlings, if cleaned and stored properly, will remain viable for many years. Likewise, Karthikeyan et al. (2009) note that vegetable growers store seed indigenously, for use during the next seasons through methods like pressing the seed with the thumb, biting or smelling the seeds, to storing them in cow dung. Other methods include dusting seed with lime, mixing seed with ash or salt which was considered to have abrasive action on the insect skin preventing it from moving inside storage containers such as mud pots.

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Animal Health and Diseases Indigenous knowledge practices in animal husbandry involve both reproductive health and the treatment of diseases. Various disease control mechanisms for chickens are observed in Akullo et al. (2007, p. 9) and these include enkubebe (small ants), muziri (tiny fish) and cannabis leaves pounded and added to water, to treat the Newcastle disease, while diarrhoea is treated using a mixture of cowpea leaves and salt. Begna leaf sap, sap of Ada (Ginger) and crushed black pepper is mixed and fed to the cattle for coughs and colds; seven pieces of chicken egg per day, to be fed for seven days, for the treatment of anoestrus; while to treat wounds, powder is made by grinding the seeds of Ata (custard apple, Annona squamosa), which is applied topically on a worm-infested wound (De Amitendu, Tudu &Goswami 2004). Akullo et al. (2007, p. 9), The United Nations Environmental Programme (2008) observe that being mainly livestock keepers, the Maasai in Tanzania have a rich heritage of herbal cures for livestock. For example, they use osendu (Combretum mucronatum) to treat olchotai (guinea worm that attack throats of cows which they catch while drinking water), armme (Euphonobia cuneata) to treat abortion (brucellosis) in cattle and olorien (Olea africana) to sterilize milk gourds and treat East Coast fever in cattle. The leaves of the umsilinga (Melia azedarach) are used by the Swazis to prepare medicine for vomiting, running stomach, ulcers, high blood pressure, de-worming dogs and treating wounds in livestock. Adekunle, Oladele and Olukaiyeja (2002) observe that the frequently practiced indigenous control methods of pests and diseases by herdsmen are hygiene, self-diagnosis, use of herbs, movement from place to place, bush burning and spiritual incantation, magic and religious healing, mostly done by reading the Koran. Practical treatment including herbalism, ie treatment with parts of plants or other natural products, for example feeding animals with plants containing a high level of salt, that results in ticks falling off. Adekunle et al. (2002) also note that herdsmen’s ages, marital status, contact with extension agents and years of experience influence their decision in practicing indigenous control methods.

Indigenous Knowledge and Weather Focus Nyong, Adesina and Elasha (2007), and Elia, Mutula and Stilwell (2014) observe that there is a wealth of local knowledge based on predicting weather and climate and farmers have developed intricate systems for gathering, predicting, interpreting and decision making in relation to weather. According to United Nations Environmental Programme (2008) the Nganyi clan of Bunyore in western Kenya is known for their powers in predicting rain for more than 100 years and people believe that the Nganyi clan can make or stop rains, lightning and hailstorms, hence they take their weather advisories seriously and pay some fees to the family at the end of each season in the form of a share of their harvest. The clan perfected their rain-prediction art through observation of vegetation, trees, reptiles, birds and insects in the shrines. The United Nations Environmental Programme (2008, p. 61) opine that the art of traditional rainfall prediction is, however, shrouded in mystery and is considered as a gift for a few. The potential person to inherit the art is identified in good time and is taken through the process of learning the art. Mutasa (2011) establishes that farmers rely on indigenous knowledge to determine weather patterns as a result of the absence of conventional weather reports from the Agritex Department while the United Nations Environmental Programme (2008, p. 26) cites a case of peasant farmers who listen to weather forecasts on the radio by the meteorological department but still prefer to rely on their own traditional knowledge of when to start planting. The more the “scientific” forecasting deviates from traditional knowledge the

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less it is used for planning purposes by the indigenous communities (United Nations Environmental Programme, 2008, p. 26). Egeru (2012, p. 223) observes that the traditional rain prediction practices of using events, moon characteristics, tree phenology, diviners and particular animal behaviour patterns were still being utilized. Some of the prediction indicators used include a high density of spider webs in the locality is a sign of a very wet season. The indigenous methods used to predict drought and famine included the abundance of butterflies (Danaus plexippus) during the farming season, presence of army worms (Spodoptera exempta), animal and plant behavior, the availability of wild fruits and wind direction prior to the rainy season also gives indications of the season ahead (Mutasa, 2011; United Nations Environmental Programme, 2008). Maasai elders frequently use the behavior of animals and their health to foretell weather. For example, goat guts would be examined by a specialized Maasai elder, and if they were found to be having watery cysts on them during the month of August this would be taken to predict that the forthcoming season would have a lot of rains, but if the small intestine was found to be empty, drought, famine, hostility and war were to be expected in the chiefdom (United Nations Environmental Programme, 2008). Indigenous people living close to natural resources often observe activities around them and are the first to notice, identify and adapt to any changes. These changes may include the appearance of certain birds (seasonal migration), the mating of certain animals and the flowering of certain plants (Aluma 2001, p. 2; Gyampoh, Amisah, Idinoba and Nkem 2009, p. 70; Akullo et al. 2007). The indigenous knowledge on disaster prediction and early warning is based on keen observation of the behavior of animals, birds, insects, vegetation, trees, winds, air and water temperatures, clouds, earth movements and celestial bodies (United Nations Environmental Programme, 2008, p. 64).

Sources and Methods Used in Disseminating Indigenous Agricultural Knowledge Singh and Sureja (2008, p. 651) observe that people learn about local practices of managing indigenous agriculture and natural resources through various localized sources where parents, nature, rural schools and social institutions, friends, neighbours and village wise men act as sources of knowledge providers. Egeru (2012, p. 217) asserts that the transfer of this knowledge and associated practices has been embedded in the culture through various rites of passage such as birth, initiation into adulthood, marriage, death, twin dancing and social gatherings which include beer parties. These views are shared by Shetto (1999, p. 69), and Mishra and Rai (2013) who note that traditional or indigenous technologies evolved as a result of a gradual learning process and emerge from a knowledge base accumulated by rural people by observation, experimentation and a process of handing down across generations, peoples’ experiences and wisdom. Osbahra and Allanb (2003) expound that knowledge is acquired through personal experiences and overlapping communication pathways, both of which are influenced by social factors, including age, gender and family ties. Mundy and Compton (1991) observe that indigenous communication can take many different forms, which include the following: • •

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Folk Media: Used mostly for entertainment, but also educative (for example dance, song, plays, and storytelling among others). Indigenous Organisations and Social Gatherings: For example religious groups, village meetings, and women’s groups, among others.

 Applying Indigenous Knowledge in Agricultural Extension in Zimbabwe

• • • •

Deliberate Instruction: Most cultures have traditional schools where cultural practices are imparted and subject coverage ranges from general to specific areas, including medicinal and agricultural practices (for example initiation ceremonies). Records: Many societies keep formal records, and these may be written, curved, or painted; African storytellers narrate memorised historical epics and genealogies at length. Unstructured Channels: Indigenous communication occurs in many settings in Africa (Sturges & Neil, 1998): on the road, in the fields, at the market, and wherever people meet and talk, and such communication is spontaneous and informal. Direct Observation: Communication does not necessarily involve a second person; by observing a neighbour’s bumper crop, a farmer may conclude that the technique or variety used is good.

A study by Protz (1998) establishes how drama is developed to better understand how the nature of gender relationships within the farm family affects agricultural decision making, particularly with respect to fertiliser use and soil fertility issues.

METHODOLOGY Qualitative and quantitative techniques were applied in this study and data was collected through a questionnaire distributed to extension workers, and through interviews with key informants at the Ministry of Agriculture’s national offices. Zimbabwe has ten provinces of which two, Harare and Bulawayo, are urban and did not participate in the study. Extension workers were drawn from eight (8) provinces, which yielded eight provincial extension officers and sixty (60) district extension officers. Ninety-one (91) Subject Matter Specialists in the eight provinces and those stationed at the Head Office were also included in the study. The categories of Agricultural Extension Officers, Agricultural Extension Supervisors and Agritex workers were drawn from Mashonaland Central Province to constitute a representative sample of agro-regions II to V. Foti, Nyakudya, Moyo and Chikuvire (2007:30) explain that Mashonaland Central Province is made up of areas of varied agricultural potential ranging from agro-ecological region II to region V. Zimbabwe’s agro-ecological zones range from region I to V, hence owing to the large number of extension workers involved at ward level in the country’s eight provinces, the study of this category was restricted to Mashonaland Central Province, which was considered representative in terms of agricultural practices. From the 551 village/ward extension workers in the province, a sample of 10% (55) was selected. Purposive sampling was applied so that each of the seven districts in the province was represented. Random sampling was then applied to select village/ward extension workers in each district. Additional village/ward extension workers from fourteen districts (14) (agro-ecological zone I-V) were randomly selected to provide field experiences, although this category was extensively investigated in Mashonaland Central Province. Key informants (policy makers) were interviewed and these were the Director – Field Services division and Acting Director – Technical Services division. The questionnaires were distributed by the researcher and research assistants, and through the assistance of the provincial extension offices, for both Mashonaland and Manicaland regions. In order to validate the research instruments, a pilot study was conducted with the Ministry of Agriculture’s Department of Veterinary Services, which was not part of the main study. Data was analysed using SPSS and through content analysis. 1115

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RESULTS AND DISCUSSION The following sections present the results and discussion of the study.

Characteristics of the Respondents As indicated in Table 1, of the respondents who completed the questionnaire, one (0.6%) was a Director and another one (0.6%) was a Chief Agricultural Specialist. Twenty-one (12.2%) were in the category of Agricultural Specialist/Snr/Principal. Six out of eight Provincial Agricultural Extension Officers completed the questionnaire, being 3.5% of the total responses. Likewise, 38 (22%) district agricultural extension officers completed the questionnaires although 44 districts participated in the study. The other categories of respondents were: Agricultural Extension Officer/Snr Principal 30 (17.4%); 24 (14%) Agricultural Extension Supervisors and these were from Mashonaland Central districts and those randomly selected from other districts. In the lower category, 51 (29.7%) were Village/ward Agricultural Extension Workers, being extension personnel at grassroots level, i.e. village/ward level, and these were selected from Mashonaland Central for reasons already indicated in the methodology. With regards to qualifications of respondents, 66 (38.4%) were holders of a certificate in agriculture, and these were mostly extension workers at ward/village level. Twenty-four (14%) had a diploma; 67 (39%) had a bachelor’s degree; 3 (1.7%) had a post-graduate diploma; while 12(7%) were holders of a master’s degree. None of the respondents had a doctoral qualification.

Indigenous Knowledge Systems in Agricultural Extension The use and application of indigenous knowledge in agriculture has been demonstrated in literature. The study sought to ascertain the importance of indigenous knowledge in agricultural extension by looking at its utilisation, frequency of use and type of sources used. Indigenous knowledge was found to be highly utilised in the generation of agricultural innovations, 153 (89%). Extension workers who indicated in the negative were 19 (11%). Table 1. Designation of respondents Designation Director

Frequency N=172

%

1

0.6

Deputy Director

-

-

Chief Agricultural Specialist

1

0.6

Agricultural Specialist/Snr/Principal

21

12.2

Provincial Agricultural Extension Officer

6

3.5

District Agricultural Extension Officer

38

22

Agricultural Extension Officer/Snr Principal

30

17.4

Agricultural Extension Supervisor

24

14

Village/Ward Agricultural Extension worker

51

29.7

Total

172

100

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 Applying Indigenous Knowledge in Agricultural Extension in Zimbabwe

Frequency of Indigenous Knowledge Utilisation This section was an extension of 5.2 above and sought to find out how frequently indigenous knowledge was utilised by the respondents. The results indicated that a minority 19 (11%) of extension workers never used IK for extension while the remainder varied in their use of IK. Results also indicate that a significant number, 35 (20.3%), of extension workers very often utilised IK, while 59 (34.3%) indicated that they “often” and “sometimes” utilise IK for extension, respectively. Table 2 summarises the findings. Indigenous knowledge can be used to facilitate communication in rural development programmes, for example communication between project personnel and farmers is often very poor, particularly in projects with a structure that favours literacy, and this often results in a serious comprehension gap (Warren & Cashman, 1988, p. 4). It was thus significant to note that there was a high utilisation of indigenous knowledge among the respondents, although there were variations in the frequencies of utilisation among them. This is despite the fact that Bagnall-Oakeley et al. (2004, p. 119) observe that “although farmers utilise an indigenous knowledge system, the coverage of their indigenous knowledge system is frequently restricted and does not mesh well with the more formal research and extension networks”. Van den Ban and Hawkins (1996, p. 20) also observe that “it is generally recognised that indigenous farmers’ knowledge is crucially important for developing sustainable agriculture because this way of farming should be adjusted to local situations which the farmer usually knows better than the researcher or the extension agents”.

Sources of Indigenous Agricultural Knowledge Indigenous knowledge is acquired or derived from various sources, both formal and informal. This section sought to establish the sources of indigenous agriculture among the respondents. The results indicated that books were the chief source mentioned at 88 (51.2%), followed by 85 (49.4%) for conferences and workshops, and colleagues with 71 (41.3%). On the lower end of the scale, the sources which were considered the least by extension workers were village leaders/elders, and social gatherings, both mentioned by 34 (19.8%), and farmers’ groups, mentioned by 28 (16.3%). The farmer groups are based on voluntary membership although the membership tends to be high due to benefits derived. Table 3 provides a summary of the findings. The formal and non-formal nature of IKS was also reflected by the sources mentioned by the respondents. The study revealed that indigenous agricultural knowledge acquisition was derived from a variety Table 2. Frequency of indigenous knowledge utilisation Use of Indigenous Knowledge

Frequency N=172

%

Very often

35

20.3

Often

59

34.3

Sometimes

59

34.3

Never

19

11

Total

172

100

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 Applying Indigenous Knowledge in Agricultural Extension in Zimbabwe

Table 3. Sources of indigenous agricultural knowledge Sources of Indigenous Agricultural Knowledge

Frequency N=172

%

Personal experience

51

29.7

Books

88

51.2

Social gatherings

34

19.8

Conferences/workshops

85

49.4

Village leaders/elders

34

19.8

Agricultural shows

37

21.5

Village meetings

42

24.4

Farmer’s groups

28

16.3

Demonstration and observation

51

29.7

Colleagues

71

41.3

*Table indicates multiple responses.

of sources, both formal and informal. The responses show that formal sources, ie books and conferences/ workshops, were mentioned by the majority – 51.2% and 49.4% respectively – while colleagues were mentioned by 41.3% of the respondents. Whereas studies have shown that the transfer of IK and associated customs has been embedded in the culture and communicated mostly through informal sources (Mundy & Compton 1991, Akullo et al. 2007, p. 2, Kiplang’at & Rotich 2008, Gyampoh et al. 2009, Egeru 2012, p. 217) and others, it is interesting to note that books, conferences and workshops were ranked highly as chief sources by the respondents. What the study did not request were these sources for clarity. Studies have also shown that IK is at risk of becoming extinct if it is not documented (Singh & Sureja (2008), Lwoga, Ngulube & Stilwell (2010), Ghorbani et al. (2012), and Egeru (2012). Demonstrations/observations and personal experiences were also ranked high by the respondents, with the least mentioned being farmers’ groups. This observation is in concurrence with views from Shetto (1999), Osbahra and Allanb (2003), Mishra and Rai (2013) cited above. In contrast, for example, Lwoga, Ngulube and Stilwell (2010, p. 178) observed that in Tanzania IK was acquired through local sources such as parents/guardian/family, neighbours and friends, and personal experience. Sources such as books and other publications are not highly rated. Studies by Akullo et al. (2007), Kiplang’at and Rotich (2008), and Gyampoh et al. (2009) demonstrated that the elderly people in traditional societies provide the main source of IK based on experience accumulated over generations. Contrary to these observations from literature, it was also important to note that the elderly was not considered highly as sources of IK. The study has also shown that social gatherings and agricultural shows were among the numerous sources of indigenous knowledge by extension workers. Interviews were conducted with the two key informants (policy makers) drawn from Field Services division Technical Services division. The respondents acknowledged the importance of indigenous in extension services, indicating that IK was embedded in the Department of Research and Specialist Services’ (DR&SS) programmes and as AREX, when the two departments were previously merged. These observations dovetail with the responses in Table 3 in which village elders, village meetings and personal experiences were found to be among the key sources of information by extension personnel.

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Types of Indigenous Agricultural Knowledge Obtained From Sources The respondents were asked to indicate the types of IAK they obtained from the sources they had mentioned in the preceding question and based on agricultural topics and subtopics. Plant diseases and pests were mentioned by the majority of extension workers, 152 (88.4%), followed by plant breeding, 139 (80.8%), with dairy farming being third, mentioned by 135 (78.5%) respondents. The least mentioned was crop harvest and storage by 31 (18%) respondents. The responses are summarised in Table 4. Crop harvesting and storage was the least mentioned by 31 (18%) respondents. However, this is despite the observation that crop protection is closely linked to plant diseases and pests, which was mentioned by a high of 88.4% of the total respondents. Singh and Sureja (2008), Akullo et al. (2007, p. 2), Egeru (2012), argue that Indigenous Knowledge (IK) has for many years steered farmers in planning agricultural production and conservation of natural resources. In view of this, different types of Indigenous Agricultural Knowledge can be obtained from different sources. Pests and other diseases have been viewed as a major threat to farmers’ yields (Odeyemi, Masika and Afolayan, 2006, p. 169, Bett & Nguyo, 2007, Karthikeyan et al. 2009, Sinha, 2010). The study concurs as shown among the respondents, the higher categories of information obtained were plant diseases and pests (88.4%), plant breeding (80.8%), and dairy farming (78.5%), while information on plant pathology, animal breeding and soil classification were also reportedly obtained by more than 70% of extension workers. Information on crop harvesting and storage was the least mentioned by extension workers. The effectiveness of IK in agriculture is demonstrated in the studies by Dakora (1996), Tikai and Kama (2004), Abu (2005), Odeyemi, Masika and Afolayan (2006), Kiplang’at and Rotich (2008), Fenta Table 4. Types of indigenous agricultural knowledge obtained from sources Type of Indigenous Agricultural Knowledge Obtained

Frequency N

%

Soil fertility

75

43.6

Horticulture

81

47.1

Soil classification

123

71.5

Plant breeding

139

80.8

Poultry

102

59.3

Plant pathology

133

77.3

Dairy farming

135

78.5

Plant diseases and pests

152

88.4

Crop protection

36

20.9

Animal health

90

52.3

Tobacco culture

105

61

Animal breeding

127

73.8

Weather patterns

55

32

Crop harvesting and storage

31

18

Crop varieties

62

36

*Table denotes multiple responses.

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(2009), Handayani and Prowito (2010), Lakra, Singh, Sinha, and Kudada (2010), Mutasa (2011), and Mugisha-Kamatenesi et al. (2008). These studies look at the different types of IK, which include soil fertility, diseases and pests as sources of Indigenous knowledge as well as methods of disseminating IK. The study thus reveals that different types of Indigenous Agricultural Knowledge are obtained from a variety of sources by extension workers, with varying emphasis among the types.

FUTURE RESEARCH DIRECTIONS The utilisation of indigenous knowledge provides relevant and timely interventions in agricultural activities. As Abioye, Zaid and Egberongbe (2011, p. 9) noted “The urgency of indigenous knowledge documentation in Africa can be appreciated from the fact that when an old man dies in Africa, a whole library/archive perishes with him due to the oral nature of African indigenous knowledge”. Hence, Lwoga, Ngulube and Stilwell (2010, p. 175), point out that there is an urgent need to acquire, document and preserve IK for agriculture before much of it is completely lost. In order to continuously harness such knowledge, further research could be conducted on the perspectives from the indigenous farming communities. For example, the impact of climate changes on traditional practices, and on the availability of traditional plants which are used in most remedies.

CONCLUSION Indigenous Agricultural Knowledge was utilised as indicated by the majority of extension workers, although the frequency of utilisation varied among the respondents. The study also showed that Indigenous knowledge was used and highly appreciated by extension workers and was acquired from a variety of sources, both formal and informal. The top three sources of IK for extension workers were books, conferences/workshops and colleagues, with farmers’ groups being the least mentioned source for the two groups. The study revealed that Indigenous knowledge derivation transcended across the different agriculture disciplines (crop science, soil science, animal science, and post-harvest storage). Indigenous knowledge is used by farmers and extension workers as is evident from literature and the findings presented. It is applied in the crop production processes, which include planting, and protection against pests and other diseases, as well as in post-harvest. IK is also applied in animal husbandry in treating wounds and other diseases. Literature has, however, shown that there are challenges related to IK use in agriculture, which include the incapacity of traditional remedies to cure some ailments and how modern medicinal approaches become substitutes. As Ghorbani et al. (2012, p. 89) indicate indigenous knowledge is deteriorating quickly: by every death of old indigenous people, great knowledge resources would be lost also, so every action toward gathering indigenous knowledge is necessary. Singh and Sureja (2008, p. 653) challenge the need to educate policy makers and planners on the value of local and indigenous systems and the importance of integrating them in the development processes in South Africa, the government recognises and appreciates the importance of Indigenous knowledge and this has resulted in the establishment of a national IKS policy and dedicated secretariat (Njiraine, Ocholla & Onyancha, 2010, p. 195). Efforts have already been made for such integration in Uganda (Gorjestani, 2001) and Kenya (Kiplang’at & Rotich, 2008).

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The study recommends that IK methods should be documented and integrated into the curricula, especially extension training. The validity of IK against scientific measures is evident and supported by Mowo et al. (2006, p. 52), Buthelezi (2010), Osbahra and Allanb (2003). As noted by Rajasekaran, Martin and Warren (1994, p. 29), incorporating IK into agricultural extension education will among other things help to understand perspectives of local people, recognize the accomplishments of local farmers as well as increasing the participation of farmers and their organisations in integrating, utilizing and dissemination of what already exist.

REFERENCES Abate, T., Van Huis, A., & Ampofo, J. K. O. (2000). Pest management strategies in traditional agriculture: An African perspective. Annual Review of Entomology, 45(1), 631–659. Retrieved from http:// www.annualreviews.org/doi/pdf/10.1146/annurev.ento.45.1.631 doi:10.1146/annurev.ento.45.1.631 PMID:10761592 Abioye, A., Zaid, Y., & Egberongbe, H. A. (2011, August 13-16). Documenting and disseminating agricultural indigenous knowledge for sustainable food security: The efforts of agricultural research libraries in Nigeria. Paper presented at the 78th IFLA Conference, San Juan, Puerto Rico. Retrieved from http:// conference.ifla.org/past-wlic/2011/78-abioye-en.pdf Abu, G. A. (2005). The use of indigenous knowledge in animal and crop pest management in Benue State, Nigeria. Indilinga African Journal of Indigenous Knowledge Systems, 4(1), 243–248. Adekunle, O. A., Oladele, O. I., & Olukaiyeja, T. D. (2002). Indigenous control methods for pests and diseases of cattle in northern Nigeria. Livestock Research for Rural Development 14(2). Retrieved from http://www.lrrd.org/lrrd14/2/adek142.htm Akullo, D. (2007, August 19-23). Indigenous knowledge in agriculture: A case study of the challenges in sharing knowledge of past generations in a globalised context in Uganda. Proceedings of the World Library and Information Congress: 73rd IFLA General Conference and Council, Durban, South Africa. Retrieved from http://www.ifla.org/iv/ifla73/index.htm Ali, Z., Yadav, A., Stobdan, T., & Singh, S. B. (2012). Traditional methods for storage of vegetables in cold arid region of Ladakh. Indian Journal of Traditional Knowledge, 11(2), 351–353. Aluma, J. R. W. (2001). Integrating of indigenous knowledge (IK) in agriculture and health development process in Uganda. Retrieved from http://www.underutilizedspecies.org/Documents/PUBLICATIONS/j_ aluma_ik_uganda.pdf Bagnall-Oakeley, H., Ocilaje, M., Oumo, F. I., Nangoti, N., Oruko, O. L., & Rees, D. (2004). Mapping and understanding farmers’ indigenous agricultural knowledge and information systems and the implications for contracted research and extension systems. Ugandan Journal of Agricultural Sciences, 9, 119–125. Retrieved from http://www.naro.go.ug/Events/NARO%20Conference/Documents/Papers/ Theme%202/UJAS%209(1)%200119-0125%20Bagnall-Oakeley.pdf

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Ghorbani, E., Khodamoradi, M., Bozorgmanesh, M., & Emami, A. (2012). Indigenous knowledge in agriculture. World Rural Observations, 4(4), 88-92. Retrieved from http://www.sciencepub.net/rural Gorjestani, N. (2001). Indigenous knowledge for development: Challenges and opportunities. Retrieved from http://www.worldbank.org/afr/ik/ikpaper_0102.pdf Gyampoh, B. A., Amisah, S., Idinoba, M., & Nkem, J. (2009). Using traditional knowledge to cope with climate change in rural Ghana. Unasylva, 60, (231/232), 70-74. Retrieved from http://www.fao. org/3/a-i0670e/i0670e14.pdf Handayani, I. P., & Prowito, P. (2010). Indigenous soil knowledge for sustainable agriculture. In E. Lichtfouse (Ed.), Sociology, organic farming, climate change (pp. 303–318). London: Springer Science. doi:10.1007/978-90-481-3333-8_11 Harwood, R. R. (1990). A history of sustainable agriculture. In C. A. Edwards, R. Lal, P. Madden, R. H. Miller, & G. House (Eds.), Sustainable agricultural systems (pp. 3–19). Ankeny, Iowa: Soil and Water Conservation Society. Karthikeyan, C., Veeraragavathatham, D., Karpagam, D., & Firdouse, S. A. (2009). Traditional storage practices. Indian Journal of Traditional knowledge, 8(4), 564-568. Kiplang’at, J. N., & Rotich, D. C. (2008, August 24-27). Mapping and auditing of agricultural indigenous knowledge in Uasin Gishu and Keiyo districts in Rift Valley Province, Kenya. Proceedings of the World Conference on Agricultural Information and IT, IAALD, AFITA, WCCA ‘08, Tokyo University of Agriculture, Tokyo, Japan (pp. 719-730). Retrieved from http://www.cabi.org/gara/FullTextPDF/2008/20083298153.pdf Kolawole, O. D. (2005). Local farmers’ approach to soil conservation: Lessons from Nigeria. Indilinga – African Journal of Indigenous Knowledge Systems, 5(1), 75-86. Lakra, V., Singh, M. K., Sinha, R., & Kudada, N. (2010). Indigenous technology of tribal farmers in Jharkhand. Indian Journal of Traditional Knowledge, 9(2), 261–263. Lwoga, E. T., Ngulube, P., & Stilwell, C. (2010). Managing indigenous knowledge for sustainable agricultural development in developing countries: Knowledge management approaches in the social context. The International Information & Library Review, 42(3), 174–185. doi:10.1080/10572317.2010.10762862 Masalu, D. C. P., Shalli, M. S., & Kitula, R. A. (2010). Customs and taboos: The role of indigenous knowledge in the management of fish stocks and coral reefs in Tanzania. Dar es Salaam: University of Dar es Salaam in association with World Bank. Retrieved from http://siteresources.worldbank.org/ EXTCMM/Resources/CRTR_Customs_Taboos.pdf Ministry of Agriculture, Mechanisation and Irrigation Development. (2010). Department of Agricultural Technical and Extension Services. Mishra, P. K., & Rai, S. C. (2013). Use of indigenous soil and water conservation practices among farmers in Sikkim Himalaya. Indian Journal of Traditional Knowledge, 12(3), 554–564.

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Moreno, L. L., Tuxill, J., Moo, E. Y., Reyes, L. A., Alejo, J. C., & Jarvis, D. I. (2006). Traditional maize storage methods of Mayan farmers in Yucatan, Mexico: Implications for seed selection and crop diversity. Biodiversity and Conservation, 15, 1771–1795. Retrieved from http://download.springer.com/ static/pdf/107/art%253A10.1007%252Fs10531-004-6679 0.pdf?auth66=1405084103_834980f0e7eca0 39cc1da3b54e89deba&ext=.pdf Mowo, J. G., Janssen, B. H., Oenema, O., German, L. A., Mrema, J. P., & Shemdoe, R. S. (2006). Soil fertility evaluation and management by smallholder farmer communities in northern Tanzania. Agriculture, Ecosystems & Environment, 116, 47–59. Retrieved from http://www.sciencedirect.com/science/ article/pii/S0167880906001125# Mugisha-Kamatenesi, M., Deng, A. L., Ogendo, J. O., Omolo, E. O., Mihale, M. J., Otim, M., ... Bett, P. K. (2008). Indigenous knowledge of field insect pests and their management around Lake Victoria basin in Uganda. African Journal of Environmental Science and Technology, 2(8), 342–348. Retrieved from http://www.academicjournals.org/AJes Mundy, P., & Compton, J. L. (1991). Indigenous communication and indigenous knowledge. Development Communication Report, 74, 3. Retrieved from http://www.mamud.com/Docs/ic_and_ik_dcr.pdf Mutasa, M. (2011). Marrying indigenous knowledge and modern science sustains agriculture. Retrieved from http://mukundi.wordpress.com/2011/01/06/marrying-indigenous-knowledge-and-modern-sciencesustains-agriculture/ Njiraine, D., Ocholla, D., & Le Roux, J. (2008). Auditing the indigenous knowledge systems in South Africa (IKS): Challenges and opportunities. ESARBICA, 27, 203–222. Notsi, L. (2012, September 3-7). African indigenous farming methods used in the cultivation of African indigenous vegetables: a comparative study of Tsitas Nek (Lesotho) and Mabeskraal village (South Africa). Paper presented at the conference: Strategies to Overcome Poverty & Inequality, “Towards Carnegie III”, University of Cape Town. Retrieved from http://www.carnegie3.org.za/docs/papers/206_ Notsi_African%20Indigenous%20farming%20methods%20used%20in%20the%20cultivation%20of%20 African%20indigenous%20vegetables.pdf Nyong, A., Adesina, F., & Elasha, B. O. (2007). The value of indigenous knowledge in climate change mitigation and adaptation strategies in the African Sahel. Mitig Adapt Strat Glob Change, 12, 787-797. Retrieved from http://ies.lbl.gov/iespubs/8nyong.pdf Odeyemi, O. O., Masika, P., & Afolayan, A. J. (2006). Farmers’ knowledge and experience of indigenous insect pest control in the Eastern Cape province of South Africa. Indilinga – African Journal of Indigenous Knowledge Systems, 5(2), 167-174. Osbahra, H., & Allanb, C. (2003). Indigenous knowledge of soil fertility management in southwest Niger. Geoderma, 111, 457–479. Retrieved from http://www.sciencedirect.com/science/article/pii/ S001670610200277X# Pazvakavambwa, S. C., & Hakutangwi, M. B. K. (2006). Agriculture extension. In M. Rukuni, P. Tawonezvi, C. Eicher, M. Munyuki-Hungwe, & P. Matondi (Eds.), Zimbabwe’s agricultural revolution revisited (pp. 217–234). Harare: University of Zimbabwe Publications.

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Protz, M. (1998). Developing sustainable agricultural technologies with rural women in Jamaica: A participatory media approach. Retrieved from http://www.fao.org/sd/CDdirect/CDan0020.htm Rajasekaran, B., Martin, R. A., & Warren, D. M. (1994). A framework for incorporating indigenous knowledge systems into agricultural extension organisation for sustainable agricultural development in India. Journal of International Agricultural and Extension Education, 1(2), 25–31. Retrieved from http:// www.ciesin.org/docs/004-201/004-201.html Rathore, S. S., Krose, N., Naro, M., Shekhawat, K., & Bhatt, B. P. (2012). Weed management through salt application: An indigenous method from shifting cultivation areas, Eastern Himalaya, India. Indian Journal of Traditional Knowledge, 11(2), 354–357. Reij, C., Scoones, I., & Toulmin, C. (1996). Sustaining the soil: Indigenous soil and water conservation in Africa. London: Earthscan Publications. Rukuni, M. (2006). The evolution of agricultural policy: 1890-1990. In M. Rukuni, P. Tawonezvi, C. Eicher, M. Munyuki-Hungwe, & P. Matondi (Eds.), Zimbabwe’s agricultural revolution revisited (pp. 29–61). Harare: University of Zimbabwe Publications. Shetto, R. M. (1999). Indigenous soil conservation tillage systems and risks of animal traction on land degradation in Eastern and Southern Africa. In P.G. Kaumbutho, & T.E. Simalenga (Eds.), Conservation tillage with animal traction (pp. 67-73). Harare. Zimbabwe. Retrieved from http://www.atnesa.org/ contil/contil-shetto-indigenous.pdf Singh, R. K., & Sureja, A. K. (2008). Indigenous knowledge and sustainable agricultural resources management under rainfed agro-ecosystem. Indian Journal of Traditional Knowledge, 7(4), 642–654. Sinha, B. (2010). An appraisal of the traditional post-harvest management methods in Northeast Indian uplands. Indian Journal of Traditional Knowledge, 9(3), 536–543. Smit, N. E. J. M. (1997). The effect of the indigenous cultural practices of in-ground storage and piecemeal harvesting of sweet potato on yield and quality losses caused by sweet potato weevil in Uganda. Agriculture, Ecosystems & Environment, 64(3), 191–200. doi:10.1016/S0167-8809(97)00022-4 Stigter, C. J., Dawei, Z., Onyewotu, L. O. Z., & Xurong, M. (2005). Using traditional methods and indigenous technologies for coping with climate variability. Climatic Change, 70(1-2), 255–271. doi:10.100710584-005-5949-5 Sturges, P., & Neil, R. (1998). The quite struggle: Information and libraries for the people of Africa (2nd ed.). Loughborough: Cassell Academic. Tekwa, I. J., Belel, M. D., & Alhassan, A. B. (2010). The effectiveness of indigenous soil conservation techniques on sustainable crop production. Australian Journal of Agricultural Engineering, 1(3), 74–79. Tikai, P., & Kama, A. (2004). A study of indigenous knowledge and its role to sustainable agriculture in Samoa. Retrieved from http://www.mnre.gov.ws/documents/forum/2004/11%20Kama.pdf Umali-Deininger, D., & Schwartz, L. A. (1994). Public and private agricultural extension: Beyond traditional frontiers. Washington, D.C.: World Bank Publications. doi:10.1596/0-8213-2803-4

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United Nations Environmental Programme. (2008). Indigenous knowledge in disaster management in Africa. Nairobi: UNEP. Retrieved from http://www.icsu.org/icsu-africa/newscentre/news/Appendix9IndigenousBookletUNEP.pdf Van den Ban, A. W., & Hawkins, H. S. (1996). Agricultural extension (2nd ed.). Oxford: Blackwell. Warren, D. M. (1991). Using indigenous knowledge in agricultural development. World Bank Discussion Paper No. 127. Washington, D.C.: The World Bank. Warren, D. M., & Cashman, K. (1988). Indigenous knowledge for sustainable agriculture and rural development. London: International Institute for Environment and Development, Sustainable Agriculture Programme. Retrieved from http://pubs.iied.org/pdfs/X101IIED.pdf Woytek, R. (1998). Indigenous knowledge for development: A framework for action. Washington, D.C.: The World Bank. Retrieved from http://www.worldbank.org/afr/ik/ikrept.pdf

KEY TERMS AND DEFINITIONS Agriculture Extension: The transfer of agricultural information and technology to the farmers and similarly transferring information from farmers to researchers. Indigenous Agricultural Knowledge: The agricultural knowledge that peasant farmers have at any one time. It is constituted both by the empirical contents of that knowledge and by the principles that underlie its production, organization and meaning (Bebbington, 1990, p. 15). Indigenous Knowledge: The sum of experience and knowledge of a given ethnic group that forms the basis for decision-making in the face of familiar and unfamiliar problems and challenges (Warren & Cashman, 1988, p. 3). Sustainable Agriculture: An agriculture that can evolve indefinitely toward greater human utility, greater efficiency of resource use, and a balance with the environment that is favourable both to humans and to most other species (Harwood, 1990, p. 4).

This research was previously published in the Handbook of Research on Social, Cultural, and Educational Considerations of Indigenous Knowledge in Developing Countries edited by Patrick Ngulube, pages 303-323, copyright year 2017 by Information Science Reference (an imprint of IGI Global).

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Multiple Exploration of Entrepreneurs’ Suggestions for Agricultural Development of Local Regional Units in Greece Odysseas Moschidis University of Macedonia, Greece Vasileios Ismyrlis Greek Statistical Authority, Greece

ABSTRACT The purpose of the present article is to evaluate the factors which are considered to be important for the agribusiness development of a local economy, with data derived from the entrepreneurs’ perspective. For this purpose, an appropriate methodology was designed, in order to include the most of the aforementioned factors. Emphasis was given to questions which can illustrate the level of technological innovation with actions and initiatives like digital marketing, innovative ability and others. Therefore, a questionnaire was created and was then applied to many regions in northern Greece. In respect of data analysis, the contribution of Correspondence Analysis (CA), a method from the multidimensional statistics field, was crucial because it easily revealed the characteristics that intensively differentiated themselves. The above methodologies and their special characteristics facilitated also the implementation of SWOT analysis. In the case of the Regional Units examined in the current research, the positive and negative factors-points were easily revealed and presented.

DOI: 10.4018/978-1-5225-9621-9.ch050

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 Multiple Exploration of Entrepreneurs’ Suggestions for Agricultural Development

INTRODUCTION The agribusiness sector is facing many challenges worldwide, as the globalization affects its structure and access to markets. Having already many additional problems due to the complexities and uncertainties linked to the sector, it is nowadays even more essential to try to cope with and implement new methods and technologies. One major example of these complexities is the global production networks (Hampton et al., 2007). The present chapter is the beginning of a new research with a principle goal to help the administrations of the local authorities or/and central government evaluate their performance in aiming to pursue rural economic development. In their effort to contribute to this field, one of the most important actions is to implement initiatives that can assist the agricultural enterprises to develop and stabilize strong entrepreneurship values. Another important activity in the same direction, is to evaluate and record the current situation in their local regional unit. This can be succeeded with the utilization of suitable instruments that collect information from the entrepreneurs themselves. The above suggestion to collect information, can be realized with an effort to measure the factors that enhance agricultural development from the entrepreneurs’ perspective. In order to collect the relevant information, the research presented here, is based on data obtained by a questionnaire survey. The questionnaire that created by the authors, contained a section about demographics and another one concerning the entrepreneurs’ perception of the existed local agricultural development’s actions-factors. The main goal is to provide an important tool that administrators of the local authorities could use to make decisions, with an aim to improve the economic climate, and furthermore to pursue development. For the analysis of the data, Correspondence Analysis, a multidimensional statistical methodology, is mainly used, as the most suitable for discovering correspondences (Benzecri, 1992) between the variables. It is an exploratory methodology of data analysis that does not assume any distribution of the data and puts forward possible trends that exist in the data graphically (Greenacre, 2007), as well. The results are presented on graphs that represent the configuration of points in projection planes formed by the first principal axes (Lebart et al., 1984, p. 44). This approach enables the researcher not only to analyze the phenomenon in a more holistic way, but also to highlight potential issues and questions that have not been previously identified. Two proposed tables, which enable the evaluation of ordinal data in a different aspect, will also be utilized (Moschidis, 2006; 2009). The methodology utilized for the determination of the relationships of the different characteristics, is S.W.O.T analysis. The specific technique is used to evaluate the Strengths, Weaknesses/Limitations, Opportunities, and Threats involved in any business project (Piercy & Giles, 1989). It involves specifying the objective of the business venture or project and identifying the internal and external factors that are favorable and unfavorable to achieve that objective (Helms & Nixon, 2010). In the present case it can be used as a measure for evaluating and presenting the factors that can contribute to the economic development of a local regional unit. The research had started from regional units from Northern Greece, with a view to be generalized in national level. The study concluded in some interesting results; firstly, in some distinguished factors for the agricultural growth that should be taken into consideration by the authorities, and secondly in the realization that there appeared to be no differences in the opinions of entrepreneurs with different demographic backgrounds. The methodology used, seemed to be perfectly suitable to extract the elements that distinguished as from the present chapter.

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BACKGROUND Agricultural Economic Development and Innovation Agriculture is a business sector of the economy, but it seems to be a strategic one as it handles food safety and quality, it produces interdependencies with other sectors of the economy and deals with most of the natural resources of a country’s economy (Ariza et al., 2013). The global demand for food will increase by 70% until 2050, but the productivity of the agricultural sector has decelerated the last years (GSRT, 2013;Moschidis & Arabatzis, 2013). For all the above factors, governments are obliged to pay a close attention to this part of the economy. For example, in the unified Europe, there are some common targets and policies for the agricultural policy. As referred to the ‘’European Commission rural development program for 2014-2020’’ (European Commission, 2014), some of the priorities to be followed are: • • • • • •

Fostering knowledge transfer Enhancing competitiveness Promoting food chain organization and risk management Restoring, preserving and enhancing ecosystems Promoting resource efficiency and supporting the shift toward a low-carbon and climate-resilient economy Promoting social inclusion, poverty reduction and economic development in rural areas.

From all the above priorities it can be concluded that the agricultural sector inside the European Union should expand to fields like innovation or/and technology, that they may be seem peculiar (especially to Greek farmers) and perhaps a new addition for this sector, but they are implemented to all other business sectors and activities for many years and they seem to be essential to enhance competitiveness and to survive the demanding global environment. In addition, many researches have highlighted that topics as innovation, entrepreneurship and the learning organization have a linkage with market orientation (Johnson et al., 2009). Market orientation is also a key factor for the appropriate connection with the markets and the customer and this aspect has already been examined in the agribusiness field (van Duren et al., 2003). Development of agricultural entrepreneurship has been an important policy in order to increase the value of agricultural production and open up the sector for businesses which is a clear departure from what obtained in the past, when oil prices were at their peak (Olawa & Olawa, 2015). Agribusinesses should compete not only on domestic markets, but on global as well (Esterhuizen, 2006) as competition and customer orientation have further increased (Dlamini & Kirsten, 2014). Developing entrepreneurial skills of the farmers seem to be essential to expand the competitive ness of their enterprises, many times needed just to survive or to find chances to expand more. A contribution to this effort can always be an effective regional policy (Polyzos & Arabatzis, 2005), which involves the increase of economic productivity. The productivity of the agricultural sector can be further associated with factors like good rural infrastructure (Llanto, 2012) and access to appropriate technology (Pinstrup-Andersen & Shimokawa, 2007). Investment in infrastructure contributes to the reduction in transport and marketing costs and therefore producers are better linked to markets (Ashok & Balasubramanian, 2006). Surely,

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governments through public investment can further contribute to the establishment of the above factors (Nadeem et al., 2011). Innovation seems to be another key factor for economic growth and development, both for enterprises and countries. Innovation can be implemented in the fields of product, processes, organization and market (Śledzik, 2013) and can include and can be facilitated by technological aspects and actions (Papaioannou et al, 2015). Many of these actions are examined in the present questionnaire.

Greece’s Status in Agricultural Entrepreneurship, Innovation, and Technology Agriculture is the fourth most important economic activity (see economic sectors in ‘’Key terms and Definitions’’ section) within the structure of Greek GDP(Gross Domestic Product) and represents 3.7% of the total (ELSTAT, 2016), which makes it essential for the Greek economy, although there was a decline in this percentage from 6.08% in 2000 to 3.7% in 2013. Certainly, the economic turmoil existed since 2008 has a serious negative impact to the Greek food sector (Chatzipetrou & Moshidis, 2016). In terms of employment, agriculture accounts for 13.2% of the total in the country (European Commission, 2016). The Northern Greece regions, which are examined in the present study, include those of Central, Eastern and Western Macedonia, Hepirus and Thrace. All together they assemble the 29.4% of the total number of Greek agricultural enterprises and the 26.7% of the added values of agricultural production (ELSTAT, 2009). It seems that globalization has affected seriously the Greek agricultural sector, as it comes up afainst faces a situation with intense competitiveness with many other economies/countries that are in a position to offer much better prices and very often products of better quality. On the other hand, this globalization is always a big opportunity to enter into new markets and countries. Nevertheless, the Greek agricultural sector is confronts many negative issues, as the great number of small farms (European Commission, 2014) and the high rate of economically active people employed by the sector (Polyzos & Arabatzis, 2005). Concerning the innovation implemented in this sector, there is a lag in innovation measurement for agricultural firms (Ariza et al., 2013) all over the world and therefore data from two big surveys, the Global Competitiveness and the Global Innovation were also utilized. These surveys present specific indices to express many aspects of economic activities, but surely the most important ones, like competitiveness and innovation (Cornell University, INSEAD & WIPO, 2015; World Economic Forum, 2013). Greece seems to have achieved notable results in the last years (Cornell University, INSEAD & WIPO, 2015; World Economic Forum, 2015), concerning the Competitiveness and Innovation indices and certain pillars (Graduates in science, Quality research institutes, Ease of protecting investions) have distinguished. However, these results refer to the overall Greek economy and entrepreneurship and there is no specific data for the agricultural sector.

METHODOLOGY Questionnaire The fifty-five (55) questions of the current questionnaire (Table 11, Appendix), were taken from the relevant bibliography and included topics concerning competitiveness, innovation and other aspects of entrepreneurship. 1130

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More specifically the fifty-five questions (E1-E55), could be grouped in the following categories (in the parentheses some of them are referred): • • • • • • • • •

Economic factors (ease of getting credit, economic climate, strength of investors protection, effects of taxation, funding from ESPA program, supports new workplaces, agritourism’s expansion). Marketing factors (effective advertising, consumer satisfaction (examination of trends), possibility of exports, local demand, intensity of local competition) Quality of products and processes (quality of local suppliers, possession of quality standards as ISO 9001, 22000 or Agrocert) Human capital-Training-Skills (education, extent of staff training, skills possession) Infrastructure Logistics-Transports: (quality of roads, connection with big urban centers) Internet access and usage: (ICT Access, ICT Use) Information and knowledge diffusion-technology: (knowledge diffusion) Environment and Energy (ecological sustainability, photovoltaic parks, natural resource protection, protection of biodiversity) Innovation in production and marketing: capacity for innovation, use of digital marketing, number of new products, patents.

There were also four questions about demographics: age, level of education, profession and sex. This study covers the results from a research started in the beginning of 2015 and completed in the April of the same year in all the Regional Units of Northern Greece. The questionnaire was distributed to a broad sample of entrepreneurs in the local economy over eighteen years old, covered all professions and education levels. The question for the entrepreneurs was: “To what degree do you think the following characteristics exist in your business sector or local economy?”, and the possible answers were, 1:”not at all”, 2:”little”, 3:”somewhat”, 4:”much”, 5:”a great deal”. Consequently, higher scores on this scale indicate the strong existence of the characteristic. Moreover, there was a definite distinction to which factors referred to the local economy and which to the local business sector. The main subject to be answered was to seek the most and least featured factors that existed in the local economy or business sector. Afterwards, merely the questions from the agricultural entrepreneurs where distinguished and are presented from now on.

SWOT The S.W.O.T. analysis is a methodology from the field of management science, which is used to evaluate the Strengths, Weaknesses/Limitations, Opportunities, and Threats existed in any business project. It involves specifying the objective of the business venture or project and identifying the internal and external factors that are favorable and unfavorable to achieve that objective. The final step of the method is a presentation of a table, which includes all the factors for the Strengths, Weaknesses/Limitations, Opportunities, and Threats that exist in the current project. In the case of the regional public administration, SWOT analysis is a means of reviewing and evaluating on the performance and potentials of the local economy. With the execution of this process, to identify the local, regional unit economic performance, SWOT analysis can be a valuable evaluation tool for the management of the regional administration. 1131

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Correspondence Analysis and Special Tables of Coincidences C.A. is an exploratory technique of the data analysis field, which does not assume any distribution of the data and is putting forward intensively differentiated trends that exist in the data, graphically as well. (Moschidis et al., 2009). In this project C.A. is applied to two proposed tables of coincidences: 1. The table of evaluation: this table displays the distribution of the n1 individuals of group A in 3 grades of the three-grade scale (we assume for convenience that the p questions Ε1, Ε2,…, Εp are formulated in a three-grade scale (not at all(1)-moderate(2)- very much(3)), therefore the table of evaluation has the following form (Table 1): For the meaning of the numbers Kij, we note that number, e.g. Κ23 equals the number of the individuals of group A that chose for the question Ε2 the grade 3. 2. The table of comparative evaluation (Moschidis, 2006, 2009, 2015), which is defined in the comparative evaluation of the questions Ε1, Ε2,…, Εp from the two (or more generally) groups Α and Β. This table derives from the horizontal union of the tables of evaluations of groups A and B, therefore the table of comparative evaluation has the following form (Table 2): Subsequently, implementing the correspondence analysis to the table of comparative evaluation and the points-columns e.g. Α2, Β3 are close to the point-line Ε2 in the first factorial space, it transpires Table 1. The table of evaluation of the group Α A

Sum

A1

A2

A3

E1

K11

K12

K13

n1

E2

K21

K22

K23

n1

Ep

Kp1

Kp2

Kp3

n1

Sum

K1

K2

K3

pn1

Table 2. The table of comparative evaluation of groups Α, Β A

1132

Β

Sum

A1

A2

A3

B1

B2

B3

E1

K11

K12

K13

K’11

K’12

K’13

n1+n2=n

E2

K21

K22

K23

K’21

K’22

K’23

n

Εp

Kp1

Kp2

Kp3

K’p1

K’p2

K’p3

n

Sum

Κ.1

Κ.2

Κ.3

Κ’.1

Κ’.2

Κ’.3

pn

 Multiple Exploration of Entrepreneurs’ Suggestions for Agricultural Development

that group Α evaluated the criterion Ε2 with the grade “moderate”(2), while the group Β with the grade “very much” (3). With this aspect, the comparison of the views of the different groups A and B, for the criteria Ε1, Ε2,…, Εp is realized (Moschidis, 2006).

ANALYSIS Descriptive Statistics A brief presentation of some descriptive statistics of the sample analysed, are presented below: The average grade of the responses in the fifty-five questions, of all the agricultural entrepreneurs in the 5-point scale was 2.65, which means that the economic characteristics examined in this research, are not very well implemented in the regions. For example the percentage of the entrepreneurs that replied “somewhat” was 32.72% (Table 4).

Application of the Proposed Methodology Multivariate Analysis Firstly, for the implementation of the Correspondence analysis, the table of evaluation for the fifty-five questions was created (see Table 5). This table, is the realized application of the first one of the proposed tables, which were referred above in the methodology section. Table 3. Demographics of the respondents (agricultural entrepreneurs) Gender

%

Age

%

Education Level

%

Male

65.2

18-30

36.1

Not attended

1.0

Female

34.8

30-44

28.1

Primary

33.5

>45

35.8

Secondary

44.6

Univ.graduate

19.2

Post graduate

1.7

Table 4. Percentages of the responses in the 5-grade scale Response-Grade

Percentage-%

1:not at all

18.00

2: little

27.00

3:somewhat

32.72

4:much

16.93

5:a great deal

5.35

1133

 Multiple Exploration of Entrepreneurs’ Suggestions for Agricultural Development

Table 5. Table of evaluation of the fifty-five questions Questions

Grades 1

2

3

4

5

E1

20

51

78

29

2

E2

28

66

55

28

E3

20

50

76

28

E4

18

49

75

E5

19

58

71

E6

57

53

E7

44

⋮

⋮

E15

Questions

Grades 1

2

3

4

5

E19

34

60

60

23

3

3

E20

20

45

71

37

6

E21

19

40

50

57

33

5

E22

23

50

79

27

29

3

E23

61

55

51

13

51

19

0

E24

28

52

75

22

50

69

16

1

E25

24

45

69

⋮

⋮

⋮

⋮

⋮

⋮

⋮

⋮

72

62

37

7

2

E33

16

12

E16

35

22

57

44

22

E34

23

E17

30

28

49

43

30

E35

11

E18

71

52

42

14

1

E36

45

Questions

Grades 1

2

3

4

5

E38

76

50

40

9

5

7

E39

37

58

50

24

11

14

E40

24

62

67

22

5

1

E41

12

36

48

65

19

0

E42

12

27

46

63

32

3

E43

37

47

63

27

6

37

5

E44

50

64

53

11

2

⋮

⋮

⋮

⋮

⋮

⋮

⋮

⋮

34

51

67

E52

25

56

71

25

3

45

85

20

7

E53

29

53

71

25

2

48

66

45

10

E54

16

46

54

48

16

62

50

21

2

E55

22

56

76

26

0

For the better understanding of the numbers in the above cells, an example is given. Number 50 in question E7, corresponds to the grade 2 of the scale, which means that fifty respondents have answered “little” in this question. The results after the implementation of the correspondence analysis, to the table of evaluation are following. Firstly, the table of eigenvalues is presented, where the total inertia is 0.25167 (Table 6). • •

The first factorial axis (first main trend) interprets with a percentage of 72.66 the researched issue. The second factorial axis (second main trend) has a 19.79 interpretation percentage.

The first factorial space interprets data with a percentage of 92.45, which is a very good and adequate percentage for further analysis. From the results of correspondence analysis, which are presented in Table 7, we will use the most important interpretation indicator of point (characteristic) towards axis, which is Contribution (CTR), as it expresses its contribution’s percentage, in axis construction. The points with large CTR towards the axis, construct and many times highlight its physical importance.

Table 6. Eigenvalues-Inertia for the table of evaluation TOTAL INERTIA AXIS

0.25167

INERTIA

%EXPLAN

SUM

1

0.1828533

72.66

72.66

*****************************************

2

0.0498098

19.79

92.45

***********

3

0.0120358

4.78

97.23

***

4

0.0069669

2.77

100.00

**

1134

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 Multiple Exploration of Entrepreneurs’ Suggestions for Agricultural Development

Table 7. Interpretation indicators: Co-ordinates (#F1), Projections-correlations (COR), Contributions (CTR) of the first two axes #F11

COR

CTR

#F22

COR

CTR

#F1

COR

CTRR

#F22

COR

CTR

E1

-92

87

1

-281

825

28

E28

-86

192

1

171

763

10

E2

-166

415

3

-103

159

4

E29

1342

953

179

281

41

28

E3

-24

8

1

-219

758

17

E30

212

322

5

-272

529

26

E4

3

0

1

-264

942

25

E31

77

72

1

-246

719

22

E5

-90

100

1

-251

780

22

E32

647

843

41

-105

21

4

E6

-382

768

14

175

162

11

E33

1350

816

181

604

163

133

E7

-309

835

10

9

0

1

E34

-57

30

1

-185

323

12

E8

-409

849

16

157

125

10

E35

207

353

5

-273

607

27

E9

-167

453

3

-44

30

1

E36

-301

857

9

86

70

3

E10

190

263

4

-270

528

26

E37

907

854

81

253

66

23

E11

-319

912

10

-57

29

2

E38

-442

426

19

493

532

88

E12

-381

775

14

106

60

5

E39

-69

155

1

116

454

5

E13

-305

709

10

35

9

1

E40

-136

286

2

-139

300

8

E14

-481

765

22

240

191

21

E41

527

754

27

-149

59

9

E15

-525

585

27

435

405

69

E42

774

965

59

32

1

1

E16

375

690

13

142

99

8

E43

-106

722

2

-8

3

1

E17

518

824

26

232

165

19

E44

-396

838

15

156

130

9

E18

-463

567

21

370

364

50

E45

-427

807

18

172

131

10

E19

-209

856

5

-49

45

1

E46

-96

318

1

-76

201

3

E20

67

84

1

-218

888

17

E47

-566

629

31

422

350

65

E21

339

621

11

-128

87

6

E48

-118

421

2

-86

223

3

E22

-135

182

2

-263

697

25

E49

-369

709

13

165

144

10

E23

-446

763

19

233

209

19

E50

117

417

2

-134

539

7

E24

-162

384

3

-158

368

10

E51

-198

394

4

-220

491

17

E25

11

2

1

-199

909

14

E52

-140

321

2

-181

542

11

E26

594

913

35

-119

36

6

E53

-168

494

3

-157

428

9

E27

311

812

10

131

143

7

E54

315

772

9

-114

100

5

E55

-172

268

2

-270

663

26

Using F indicator (coordinate) we define the side of the axis in which the point (characteristic) is represented. Therefore, the points with positive coordinate are situated on the right side and on the other side are those with negative. We note that the average CTR is 1000:55= 18.18, where 55 is the number of the points-questions. Therefore, we can consider points of high contribution in axis construction, those with CTR values above average (CTR values over 20 are in bold for the first axis and over 25 for the second). Having in mind the above estimations and the help of the visualization of the axes (see Fig. 1, 2, 3), we conclude in the following results (Greenacre, 2007).

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 Multiple Exploration of Entrepreneurs’ Suggestions for Agricultural Development

Figure 1. First factorial axis

The first axis (Figure 1), opposes characteristics, that have proved to exist in a great extent in the local economy or agricultural sector, the following: “Productivity of the sector” (E29), ‘’Connection with big urban centers (E32), “Unemployment” (E33), “Sectorial unemployment” (E37), “Tourist sector’s development perspectives” (E41) “Secondary production perspectives” (E42), “Green development” (E17), ‘’ Connection with other sectors’’ (E26), to characteristics that their existence have been realized to be negligible, like: “Investments from outsiders” (E15) and “Innovative companies in the sector” (E47), ‘’Digital marketing in the sector’’ (E14) and ‘’Photovoltaic parks (E18) . The second axis (Figure 2) opposes factors that were ranked with 1 or 5, as: the “Investments from outsiders” (E15), “Photovoltaic parks” (E18), “Productivity in the sector” (E29), “Unemployment” (E33), “Knowledge diffusion in the sector” (E38), “Innovative companies in the sector” (E47) with factors that got the mediate values (3,4) like, “Care for biodiversity” (E1), “Access to internet” (E10), “Possession of quality certificates” (E55). From the preceding analysis and Figure 3, we can conclude (Greenacre, 2007), that there are many factors that seem to strongly differentiate themselves. Firstly, the positive ones (that contribute positively to the economic environment and entrepreneurship) are: “Productivity of the sector” (E29), ‘’Connection with big urban centers (E32), “Tourist sector development perspectives” (E41) “Secondary production perspectives” (E42), “Green development” (E17), “Connection with other sectors” (E26). From the opposing point of view, the negative ones are presented: “Investments from outsiders” (E15), ‘‘Innovative companies” (E47), ‘‘Digital marketing” (E14), ‘‘Knowledge diffusion” (E38), ‘‘Connection with other sectors” (E26), ‘‘Unemployment in the sector” (E37), “Unemployment” (E33), ‘‘General state of the economy” (E5). From the above results, important conclusions can be drawn from the SWOT analysis, which can be seen in Tables 8,9 for the local economy and the agricultural sector, respectively. Consequently, it is obvious that unemployment (inside the sector or not) from the perspective of the entrepreneurs, is a serious threat in the regions examined. On the other hand, there is an opportunity for the secondary production as well the tourist sector to further expand. Both previous factors are considered very important for the economic prosperity of any region. The agricultural sector of the regions examined, seems to experience some other problems too, like the lack of: innovation, knowledge diffusion and digital marketing, all of which are entrepreneurship friendly. On the other hand, the local

Figure 2. Second factorial axis

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 Multiple Exploration of Entrepreneurs’ Suggestions for Agricultural Development

Figure 3. First factorial space

Table 8. SWOT analysis of the local economy Strengths Green development

Weaknesses

Opportunities

Threats

Investments from outsiders

Secondary production perspectives

Unemployment

Photovoltaic parks

Tourism development perspectives

General state of economy

Connection with big urban centers

Table 9. SWOT analysis for the agricultural sector of the local economy Strengths Productivity

Weaknesses Digital marketing

Opportunities Connection with other sectors

Threats Unemployment in the sector

Innovative companies Knowledge diffusion

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 Multiple Exploration of Entrepreneurs’ Suggestions for Agricultural Development

agricultural sector seems to have an adequate connection with other sectors, and its productivity is well established. The general state of the economy is not well and there existed few investions from outside the local area. However, some other factors like green development, connecting with big urban centers, seem to be sufficiently featured in the regions examined.

Comparative Evaluation Except from the above analysis, the effect of all the demographic variables on the factors was also examined. Here, the table of comparative evaluation, which gives the possibility to compare the performance of different groups is applied. The findings showed that the opinions of the citizens do not change when they have different demographic characteristics, a result that means the evaluation from an entrepreneur’s perspective, is not affected by other factors. As an example, the comparative table of the fifty-five questions and the level of education, was also analyzed, after the implementation of Correspondence Analysis in the table of comparative evaluation (Table 10). The symbolization “Sec” belongs to entrepreneurs having completed education below bachelor (secondary or primary or no) and “Univ” to entrepreneurs with bachelor or even higher education. Certainly, Sec1 is the first grade of the category “Sec”, Sec2 is the second grade of the category and so on. The results derived, concluded that there is no difference in the opinions between entrepreneurs with a different level of education. This is also obvious in the visualization of the results, which are displayed in the first factorial space (Figure 4). The entrepreneurs with different level of education 1:Sec, and 2:Univ, have given similar responses, which can be resulted by the closeness of the points. For example, it can be seen from the points 15 and 25 (in the circle), where 15 is the fifth grade of education level 1 and 25 is the fifth grade of education level 2.

FUTURE RESEARCH DIRECTION The methodology presented in this research could be generalized in all Greek regions and therefore this offers a possibility to compare the economic situation in the different regions. More questions could be included in the questionnaire, in order to explore the possible reasons for the delay of the economic development and moreover the implementation of technology innovations in the agribusiness sector in Greece. Local and central governments can adopt measures to improve the situation regarding the economic climate and the same research could be repeated after some years in the same regions, in order to make longitudinal comparisons.

CONCLUSION The questionnaire designed for the purpose of the present study and which was pilot tested in regions of Northern Greece, has achieved with great ease to extract the most important factors of the economic environment and economic performance, assisted in this effort by a method of the multidimensional statistics field. Regarding the final results, about the local entrepreneurship’s opinions of the factors appropriate for economic development in all the regions, differences were detected in some factors. 1138

 Multiple Exploration of Entrepreneurs’ Suggestions for Agricultural Development

Table 10. Table of comparative evaluation of questions and level of education Ind

Sec1

Sec2

Sec3

Sec4

Sec5

Univ1

Univ2

Univ3

Univ4

E1

10

25

44

10

2

10

26

34

19

Univ5 0

E2

15

30

33

12

1

13

36

22

16

2

E3

9

26

40

13

3

11

24

36

15

3

E4

8

30

36

14

3

10

19

39

19

2

E5

15

23

38

14

1

4

35

33

15

2

E6

32

28

24

7

0

25

25

27

12

0

E7

23

21

40

6

1

21

29

29

10

0

E8

30

30

25

5

1

21

35

25

8

0

E9

21

24

37

8

1

15

22

37

11

4

E10

9

18

37

25

2

9

19

30

26

5

⋮

⋮

⋮

⋮

⋮

⋮

⋮

⋮

⋮

⋮

⋮

E50

13

28

32

13

5

9

19

30

26

5

E51

14

27

43

7

0

13

25

34

17

0

E52

18

27

36

10

0

7

29

35

15

3

E53

17

31

32

11

0

12

22

39

14

2

E54

11

30

25

18

7

5

16

29

30

9

E55

15

31

34

11

0

7

25

42

15

0

Figure 4. First factorial space of the table of comparative evaluation

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 Multiple Exploration of Entrepreneurs’ Suggestions for Agricultural Development

This result makes it possible for the researcher to discover the strengths and weaknesses of municipality’s economic performance and the possible potentials, for further improvement. In addition, it can be concluded that the general perception of the current situation in the regions examined is not influenced by the social characteristics of the entrepreneurs like level of education, age and sex. Concerning the innovation and technological aspects that companies could use, it can be deducted that the agricultural sector in the regions examined in this study, did not manage to implement most of them. Moreover, the present questionnaire can be an important tool to evaluate factors that contribute to the local economic development and can be used to extract the crucial factors that SWOT analysis requires. The correspondence analysis method seems to be perfectly suited for the extraction of the elements needed to perform the SWOT analysis. Particularly, with the contribution of the two proposed tables of evaluation, the final choice of the crucial factors was precise and immediate. This proposed method, can also be used as an instrument to measure and compare different regions’ performance, with the help of the indicators (questions) presented in the current study. This project can provide a measurement tool for Central Administration-Government, in order to compare and evaluate the economic performance and environment to different regions. It is a way to implement benchmarking, with the creation of a network of public administrations’ organizations which have common practices, and to develop a peer evaluation among them (Cappelli et al., 2011). This performance can be a criterion for another evaluation; the appropriate exploitation of the resources, that municipalities have at hand, in order to achieve their goals.

REFERENCES Ariza, C., Rugeles, L., Saavedra, D., & Guaitero, B. (2013). Measuring Innovation in Agricultural Firms: A Methodological Approach. Electronic Journal of Knowledge Management, 11(3), 185–198. Ashok, K. R., & Balasubramanian, R. (2006). Role of Infrastructure in Productivity and Diversification of Agriculture, A Research Report. Islamabad, Pakistan: SANEI. Benzecri, J. P. (1992). Correspondence Analysis Handbook. New York: Taylor & Francis. Cappelli, L., Guglielmetti, R., Mattia, G., Merli, R., & Renzi, M. F. (2011). Peer evaluation to develop benchmarking in the public sector. Benchmarking an International Journal, 4(4), 490–509. doi:10.1108/14635771111147605 Chatzipetrou, E., & Moschidis, O. (2016). Quality costing: A survey in Greek supermarkets using multiple correspondence analysis. International Journal of Quality & Reliability Management, 33(5), 615–632. doi:10.1108/IJQRM-01-2014-0004 Cornell University, INSEAD, & WIPO. (2015). The Global Innovation Index 2015: Effective Innovation Policies for Development. Authors. Dlamini, B., Kirsten, J., & Masuku, M. (2014). Factors Affecting the Competitiveness of the Agribusiness Sector in Swaziland. Journal of Agricultural Studies, 2(1). Esterhuizen, D. (2006). An Evaluation of the Competitiveness of the South African Agribusiness Sector. University of Pretoria. Available from UPeTD: Retrieved June 12, 2016, from http://upetd.up.ac.za/ thesis/ available/ etd-12082006144349/ unrestricted/ 00front.pdf,9/3/2010

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European Commission. (2014). Rural development programme. Retrieved June 10, 2016, from http:// ec.europa.eu/agriculture/rural-development-2014-2020/ European Commission. (2016). Factsheet on 2014-2020 Rural development programme for Greece. Retrieved July 12, 2016, from http://ec.europa.eu/agriculture/rural-development-2014-2020/countryfiles/el/factsheet-greece_en.pdf General Secretariat of Research and Technology-GSRT. (2013). Research and Innovation in the Agrobioalimentary cluster for the 2014-2020 period (in Greek). Retrieved July 12, 2016, from http://www. gsrt.gr/Financing/Files/ProPeFiles48/TO%20AΓPOBIOΔIATPOΦIKO%20ΣYMΠΛEΓMA%2020142020_EΣΠEK_10-7-2013_A_FINAL.pdf Greenacre, M. (2007). Correspondence Analysis in Practice. Boca Raton, FL: Chapman and Hall/CRC. doi:10.1201/9781420011234 Hampton, R., Fromm, I., & Nyhodo, B. (2007). International Trade, Consumer Behaviour and Trust: Factors Affecting Agribusinesses in Developing Countries. Marketing Department Faculty Publications. Retrieved June 20, 2016), from http://digitalcommons.unl.edu/marketingfacpub/6 Hellenic Statistical Authority (ELSTAT). (2009). Results of Agricultural-Livestock Census 2009. Retrieved from http://www.statistics.gr/el/statistics/-/publication/SPG31/Johnson, A., Dibrell, C., & Hansen, E. (2009, Spring/Fall). Market Orientation, Innovativeness, and Performance of Food Companies. Journal of Agribusiness, 27(1/2), 85–106. Hellenic Statistical Authority (ELSTAT). (2016). Gross value added by industry (A10) - NACE REV.2, the sector of Agriculture, Forestry. Retrieved June 10, 2016, from http://www.statistics.gr/el/statistics/-/ publication/SEL45/Helms, M. M., & Nixon, J. (2010). Exploring SWOT analysis - where are we now? A review of academic researchfrom the last decade. Journal of Strategy and Management, 3(3), 215–251. Llanto, G. (2012). The impact of infrastructure on agricultural productivity. Philippine Institute for Development Studies, Series: Discussion paper series (Philippine Institute for Development Studies), no. 2012-12. Moschidis, O. (2006). A proposal of comparative evaluation with the correspondence analysis [in Greek]. Journal SPOUDAI, 56(3), 95–113. Moschidis, O. (2015). Unified coding of qualitative and quantitative variables and their analysis with ascendant hierarchical classification. International Journal of Data Analysis Techniques and Strategies, 7(2), 114–128. doi:10.1504/IJDATS.2015.068745 Moschidis, O., & Arabatzis, G. (2013). SHP stations and integrated rural development: A multivariate statistical approach. International Journal of Green Economics, 7(4), 333–347. doi:10.1504/IJGE.2013.058561 Moschidis, O., Spathis, C., & Floropoulos, I. (2009). Methodological approach to Multidimensional exploratory evaluation of Taxis (Taxation information system) usefulness:Greek economy in Perspective. Journal of Financial Management and Analysis:International Review of Finance, 22(2), 1–12.

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Moschidis, O. E. (2009). A different approach to multiple correspondence analysis (MCA) than that of specific MCA. Mathématiques et sciences humaines. Mathematical Social Sciences, (186), 77–88. Nadeem, N., Mushtaq, K., & Javed, M. I. (2011). Impact of social and physical infrastructure on agricultural productivity in Punjab, Pakistan - A production function approach. Pakistan Journal of Life and Social Sciences, 9(2). Olowa O.W., & Olowa, O.A. (2015). Factors Affecting Entrepreneurship Development in Agribusiness Enterprises in Lagos State. Global Journal of Management and Business, 15(7). Papaioannou, E., Georgiadis, C. K., Moschidis, O., & Manitsaris, A. (2015). Factors Affecting Customers Perceptions and Firms Decisions Concerning Online Fast Food Ordering. International Journal of Agricultural and Environmental Information Systems, 6(1), 48–78. doi:10.4018/ijaeis.2015010104 Piercy, N., & Giles, W. (1989). Making SWOT Analysis Work. Marketing Intelligence & Planning, 7(5/6), 5–7. doi:10.1108/EUM0000000001042 Pinstrup-Andersen, P., & Shimokawa, S. (2007). Rural Infrastructure and Agricultural Development. In F. Bourguignon & B. Pleskovic (Eds.), Annual World Bank Conference on Development Economics – Global 2007: Rethinking Infrastructure for Development (pp. 175-203). Washington, DC: The World Bank. Polyzos, S., & Arabatzis, G. (2005). Labour Productivity of the Agricultural Sector in Greece: Determinant Factors and Interregional Differences Analysis. Department of Planning and Regional Development, School of Engineering, University of Thessaly, Discussion Paper Series. Śledzik, K. (2013). Schumpeter’s view on innovation and entrepreneurship. In Management Trends in Theory and Practice. University of Zilina. doi:10.2139srn.2257783 van Duren, E., Sparling, D., Turvey, C., & Lake, L. (2003). An assessment of the strategies and strengths of medium-sized food processors. Agribusiness: An International Journal, 19(1), 115–132. World Economic Forum. (2013). The Global Competitiveness Report 2013–2014. Geneva: World Economic Forum. World Economic Forum. (2015). Retrieved from http://www.weforum.org/reports/global-competitivenessreport-2014-2015

KEY TERMS AND DEFINITIONS Central Administration-Government: The government of a nation-state and this is a characteristic of a unitary state. Digital Marketing: The advancement of items or brands through one or more types of electronic media. For instance, publicizing mediums that may be utilized as a major aspect of the advanced advertising system of a business could incorporate limited time endeavors made by means of the Internet, online networking, cellular telephones and electronic boards, and in addition through computerized and TV and radio stations.

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 Multiple Exploration of Entrepreneurs’ Suggestions for Agricultural Development

Green Development: It is an area use arranging idea that incorporates thought of group wide or local natural ramifications of improvement, and site-particular green building ideas. This incorporates city arranging, natural arranging, engineering, scene design and group building. Infrastructure: Relatively lasting and foundational capital venture of a nation, firm, or venture that underlies and makes conceivable all its monetary movement. It incorporates authoritative, information transfers, transportation, utilities, and waste expulsion and preparing offices. A few definitions additionally incorporate instruction, human services and innovative work. Innovation: The way toward deciphering a thought or development into a decent or administration that makes esteem or for which clients will pay. In business, advancement frequently comes about when thoughts are connected by the organization with a specific end goal to facilitate fulfill the necessities and desires of the clients. Knowledge Diffusion: The way toward imparting exploration, developments as well as information to people, gatherings or associations. Learning Organization: An association that gains learning and enhances sufficiently quick to survive and flourish in a quickly evolving environment. Learning associations (1) make a society that empowers and backings nonstop representative learning, basic considering, and hazard bringing with new thoughts, (2) permit mix-ups, and esteem worker commitments, (3) gain for a fact and test, and (4) disperse the new information all through the association for fuse into everyday exercises. Market Orientation: A business methodology or logic that spotlights on distinguishing and meeting the expressed or shrouded needs or needs of clients. Productivity: A measure of the productivity of a man, machine, processing plant, framework, and so on., in changing over inputs into valuable yields. Productivity is processed by partitioning normal yield per period by the aggregate costs caused or assets (capital, vitality, material, faculty) devoured in that period. Sector (Economy/Business): The economic-business sector or corporate sector is a part of the economy made up by companies with the same characteristics. The three-sector theory in the economics, subdivides them into: The Primary Sector (Raw Materials): Agriculture, Fishery, Forestry. The Secondary Sector (Manufacturing): Manufacturing, Construction. The Tertiary Sector (Sales and Services): Services, Trade. Technology: The intentional use of data in the configuration, generation, and usage of products and administrations, and in the association of human exercises.

This research was previously published in Driving Agribusiness With Technology Innovations edited by Theodore Tarnanidis, Maro Vlachopoulou, and Jason Papathanasiou, pages 191-209, copyright year 2017 by Business Science Reference (an imprint of IGI Global).

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Multiple Exploration of Entrepreneurs’ Suggestions for Agricultural Development

APPENDIX Table 11 presents the number of entrepreneurs per question and grade, the averages of the responses per question and the analytical description of the questions. Table 11. Grades and averages of the 55 questions Gr1

Gr2

Gr3

Gr4

Gr5

Aver.

Ε1

Number

20

51

78

29

2

2.7

Care for the protection of biodiversity

Question

General

Gen/Sec*

Ε2

28

66

55

28

3

2.5

Care for the protection of natural resources

General

Ε3

20

50

76

28

6

2.7

Diffusion of knowledge and information

Sectorial

Ε4

18

49

75

33

5

2.8

Satisfaction from income

General

Ε5

19

58

71

29

3

2.7

Effective advertising

Sectorial

Ε6

57

53

51

19

0

2.2

Expectations of the agricultural policy implemented

Sectorial

Ε7

44

50

69

16

1

2.3

Intense business activity in your sector

Sectorial

Ε8

51

65

50

13

1

2.2

Encouragement of private initiative from local or central government

General

Ε9

36

46

74

19

5

2.5

Cooperation of local authority and entrepreneurs

General

Ε10

18

37

67

51

7

3.0

Access to internet and WWW

Sectorial

Ε11

37

61

65

17

0

2.3

Exploitation of European funding programs (ESPA)

General

Ε12

45

72

46

16

1

2.2

New technology and informatics usage

Sectorial

Ε13

40

70

46

23

1

2.3

Innovative agricultural companies

Sectorial

Ε14

56

70

45

8

1

2.0

Usage of digital marketing

Sectorial

Ε15

72

62

37

7

2

1.9

Investments from outsiders

General

Ε16

35

22

57

44

22

3.0

Environment awareness

Sectorial

Ε17

30

28

49

43

30

3.1

Green development

Sectorial

Ε18

71

52

42

14

1

2.0

Creation of Photovoltaic parks

General

Ε19

34

60

60

23

3

2.5

Support from government

General

Ε20

20

45

71

37

7

2.8

Contribution of tourism to the local economy

General

Ε21

19

40

50

57

14

3.0

Contribution of agricultural sector to the local economy

Sectorial

Ε22

23

50

79

27

1

2.6

Market knowledge

Sectorial

Ε23

61

55

51

13

0

2.1

General state of economy

General

Ε24

28

52

75

22

3

2.6

Cost of using infrastructure

General

Ε25

24

45

69

37

5

2.7

Access to internet and WWW

Sectorial

Ε26

12

27

58

60

23

3.3

Connection with other sectors

Sectorial

Ε27

27

43

52

35

23

2.9

Quality products

Sectorial

continued on following page 1144

Multiple Exploration of Entrepreneurs’ Suggestions for Agricultural Development

Table 11. Continued Number

Gr1

Gr2

Gr3

Gr4

Gr5

Aver.

45

49

50

26

10

2.5

Education and training of your sector

Sectorial

Ε29

3

10

45

64

58

3.9

Productivity of your sector

Sectorial

Ε30

16

39

66

51

8

3.0

Impact of Taxation

General

Ε31

22

39

71

43

5

2.8

Connection with the rest Greece

General

Ε32

14

23

52

68

23

3.4

Connection with big near urban centres

General

Ε33

16

12

34

51

67

3.8

Unemployment

General

Ε34

23

45

85

20

7

2.7

Number of Associations, Partnerships, Consortiums

Sectorial

Ε35

11

48

66

45

10

3.0

Number of Tourists

General

Ε36

45

62

50

21

2

2.3

Number of new patents, products

General

Ε37

11

25

57

40

47

3.5

Seasonal unemployment

General

Ε38

76

50

40

9

5

2.0

Knowledge diffusion in your sector

Sectorial

Ε39

37

58

50

24

11

2.5

The interest of the young people to become businessmen in the region

General

Ε40

24

62

67

22

5

2.6

Connection of primary sector with secondary

General

Ε41

12

36

48

65

19

3.2

Developmental perspectives of the tourist sector

General

Ε42

12

27

46

63

32

3.4

Secondary sector perspectives

General

Ε43

37

47

63

27

6

2.5

Existence of companies with export activity

General

Ε44

50

64

53

11

2

2.2

Agrotourism expansion

General

Ε45

51

69

47

12

1

2.1

Investors’ protection

General

Ε46

28

56

66

23

7

2.6

Reduction of local products

Sectorial

Ε47

75

57

42

6

0

1.9

Innovative companies

Sectorial

Ε48

30

59

56

31

4

2.6

Special skills of the staff

Sectorial

Ε49

58

47

56

19

0

2.2

Support new workplaces

General

Ε50

22

47

62

39

10

2.8

Well-trained staff

Sectorial

Ε51

27

52

77

24

0

2.5

Quality of roads

General

Ε52

25

56

71

25

3

2.6

Satisfied with the state of economy

General

Ε53

29

53

71

25

2

2.5

Companies are close to the consumer

Sectorial

Ε54

16

46

54

48

16

3.0

Intensity of local competition

Sectorial

Ε55

22

56

76

26

0

2.6

Possession of ISO or other quality certificates

Sectorial

Ε28

Question

Gen/Sec*

* Gen=General(for the local economy), Sec=Sectorial(for the specific sector)

1145

1146

Chapter 51

Agricultural Productivity in Indonesian Provinces Khee Giap Tan National University of Singapore, Singapore Nurina Merdikawati National University of Singapore, Singapore Ramkishen S. Rajan George Mason University, USA

ABSTRACT Indonesia has been recognized as a country with significant potential in agriculture, not only to be selfsufficient in terms of food, but also to be the “food basket” for the world. However, given limited and competing use of resources, raising agricultural productivity is of paramount importance. To date, most of the existing work on Indonesia’s agricultural sector is at the national level. Considering the extent of Indonesia’s regional diversity, a provincial-level analysis of the country’s agricultural sector would be more useful from a policy perspective. In this light, this paper examines agricultural productivity growth in Indonesian provinces during 2000-2011 and draws policy implications from such empirical analysis. The paper uses two methodologies, namely growth accounting and Malmquist index data envelopment analysis. Results suggest that technological change has been improving for most provinces, though there is wide variation in technical efficiency change which in turn is driving differences in total factor productivity growth across provinces.

1. INTRODUCTION Indonesia is a vast archipelagic country with tremendous potential in its agricultural output. Although agriculture’s contribution to the country’s gross domestic product (GDP) has steadily decreased from 35.3 percent in 1960 to 11.5 percent in 2012, the sector still employed about 35 percent of Indonesia’s labour force as of 2012. Within the agricultural sector, in terms of the contribution of each sub-sector, farm food crops and horticulture together contributed to nearly half of the agriculture’s share of GDP DOI: 10.4018/978-1-5225-9621-9.ch051

Copyright © 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Agricultural Productivity in Indonesian Provinces

in 2012. While estate crops1 and livestock represented about 22.8 and 12.6 percent, respectively, the remaining 17.6 percent came from fisheries and forestry (Biro Pusat Statistik, 2012). Indonesia’s trade surplus in agriculture is mainly a result of its exports of estate crops while its major imports include wheat, cotton, sugar, soybeans, and maize. In fact, Indonesia is one of the world’s major producers and exporters of estate crops such as palm oil, rubber, palm kernel, coffee, coconut (copra), cocoa, tea, and spices. Within Asia, Indonesia contributed to more than one third of total agricultural output of the Association of Southeast Asian Nations (ASEAN) (Food and Agriculture Organization, 2012). Agricultural development policy in Indonesia has evolved in four significant phases (Fuglie, 2010). During 1961-1967, Indonesia had poor macroeconomic performance characterized by slow output growth with very few modern inputs and small improvements in productivity. From 1968-1992, a green revolution took place and agriculture was the top priority in the economic development agenda which gave rise to the invention and wide dissemination of a number of high-yielding varieties, as well as implementation of pro-agricultural policies. During 1993-2001, the agricultural sector faced stagnation, coupled with the Asian Financial Crisis (AFC) in 1997, with fewer sources for public spending in agriculture. Post AFC, the period of 2002-2006 marked the liberalization era of Indonesia’s agricultural sector, where import restrictions on food crops were removed. This was a period of significant diversification of agricultural output with land expansion mostly for estate crops. The agricultural value-added in Indonesia expanded by more than one-third from 1993 to 2006 (World Bank, 2012b). The trend for agricultural output remained positive as strong macroeconomic performance translated into more resources to pursue pro-agricultural policies. This was intertwined with the government’s pro-poor policy as agricultural growth and productivity were often cited as the means to reduce rural poverty. According to the OECD (2012), incidence of poverty in rural areas was twice as high as in urban areas and almost three-fifth of the poor depended on agriculture as the main source of income. Hence, continued progress in agricultural productivity and incomes from agriculture plays an important role in diminishing rural poverty. Indonesia has been recognized as a country with significant potential in agriculture, not only to be self-sufficient in terms of food, but also to be the “food basket” for ASEAN and the world. However, given limited and competing use of resources, raising agricultural productivity is of paramount importance. Indonesia has a considerably diverse agricultural sector and it is most evident when one compares the relative resource endowments and commodities across islands. Rice as a staple crop is widely cultivated in Java Island, with Sumatra being well known for its vast palm oil plantations and Sulawesi for cocoa. Beyond that, diversity persists in other aspects as well, such as in terms of the size of agricultural sector in their own economy and also their contribution to the national agricultural output. For instance, in terms of agricultural sector as a share of GDP in 2011, it was 46 percent in West Sulawesi GDP but a negligible 0.1 percent for DKI Jakarta. The Java Island -- consisting of East Java, West Java, Central Java, Banten, DI Yogyakarta, and DKI Jakarta -- contributed to just over two-fifth percent of national agricultural output in 2011 even though agriculture itself was no longer a prominent economic driver to the island, contributing to only 9.7 percent of Java’s GDP. On the contrary, agriculture is still the main economic driver for easternmost provinces such as North Maluku, Maluku, West Papua, and Papua. In fact, agriculture contributed to 20.5 percent of their GDP as a whole. However, their agricultural output only made up 2.5 percent of national agricultural output in 2011. Despite variations in agricultural contribution to GDP for each province, what persists is a sizeable share of employment in agricultural sector across provinces. In West Sulawesi for example, 59 percent of its labour force worked in agricultural sector and contributed to about 46 percent of its GDP in 2011. 1147

 Agricultural Productivity in Indonesian Provinces

Sizeable agricultural employment was also found in East Java and Central Java, at about 40 percent and 34 percent in 2011, respectively, even though the share of agriculture in their GDP was relatively small at 14 percent and 18 percent, respectively. While most of the existing work on Indonesia’s agriculture is at the national level, considering the extent of Indonesia’s regional diversity as outlined above, a provincial-level analysis of the country’s agricultural sector would prove to be more useful from a policy perspective. In this light, this paper examines agricultural productivity growth in Indonesian provinces during 2000-2011 and draws policy implications from such an empirical analysis. The remainder of the paper is structured as follows. Section 2 provides a literature review on the studies on Indonesia’s agricultural productivity to date. Section 3 details the methodology and data to be used in this paper. Section 4 discusses the findings. Section 5 concludes the paper with some policy implications.

2. LITERATURE REVIEW Various papers have examined agricultural total factor productivity (TFP) in Indonesia with largely varied findings owing to the use of different methodologies, time periods, specification of variables, and data sources, as summarized in Table 1. Relying on more than four decades of time series data, Avila & Evenson (2010) and Fuglie (2010) reported a relatively high TFP growth of 2 percent and 1.8 percent, respectively. They further decomposed the TFP growth into different periods of analysis. The authors found that TFP growth was higher in 1961-1980 at around 4.4 percent than during 1981-2001 with a negative productivity growth of -0.39 percent. Similar trends could be found in Fuglie (2010) who reported decadal TFP growth rates and found it to be around 3 percent during 1961-1970; followed by about 2 percent growth in the next decade; a little more than 1 percent during 1981-1990; a little less than 1 percent in 1991-2000; and finally about 2.4 percent between 2001 and 2006. A follow-up study by Fuglie (2012) covered close to five decades of data. The paper found that the most recent period 2001-2009 charted the highest TFP growth at around 3.7 percent. The steep decline in TFP growth from the 1980s till 2000 compared the period between 1960 and 1980 was triggered by period of economic stagnation, while the turnaround since 2001 could be attributed to more resources devoted to agriculture, as well as diversification towards estate crops. The papers listed in Table 1 employed either growth accounting, the Tornqvist-Thiel Index or the Malmquist Index to estimate TFP growth. They also used different sets of output and inputs. For instance, Mundlak et al. (2002) and Warr (2009) used broad agricultural GDP as their output that typically also included forestry and fishery from Indonesia’s Statistical Bureau, Biro Pusat Statistik (BPS). Meanwhile, Fuglie (2010) limited the output to only include crops, livestock, and aquaculture. Avila & Evenson (2010), Coelli & Rao (2005), and Suhariyanto & Thirtle (2001) used only production of crops and livestock to measure output. For inputs, these papers generally included land, labour, fertilizer, and machinery. National-level data were often sourced from FAO database, BPS, and/or estimated by the authors using available proxies. The literature listed in Table 1 revealed that most of the existing literature measuring agricultural TFP growth had been done at national-level. However, given the significant regional differences in Indonesia, as explained earlier, this paper will contribute to the growing literature by shedding light on the dynamics of agricultural TFP growth across provinces in Indonesia. 1148

 Agricultural Productivity in Indonesian Provinces

Table 1. Summary of literature Author

Methodology

Time Period

Specification of Variables

Data Source

TFP Growth

Output: Total value of agricultural production in crops and livestock; Input: land, labour, livestock, fertilizer, and machinery;

USDA World Agricultural Trends and Indicators; FAO Agrostat Database

0.17

BPS; FAO

1.49

Suhariyanto & Thirtle (2001)

Malmquist Index

Mundlak et al. (2002)

Aggregate production function similar to CobbDouglas with a major difference from constant coefficients function in that the coefficients in equation are functions of the state variables and possibly of the inputs.

1971-1998

Output: log of agricultural GDP; Input: irrigated land, rainfed land, fertilizers, capital, and labour; The state variables included: roads, measures of education, health, and incentives;

Coelli & Rao (2005)

Malmquist Index

1980-2000

Output: crops and livestock output; Input: land, tractors, labour, fertilizer, livestock, and irrigation.

FAO Agrostat Database

0.98

Warr (2009)

Growth accounting

1980-2006

Output: agricultural GDP; Input: land, labour, human capital, and physical capital.

BPS; SAKERNAS; Ministry of agriculture

0.90

1961-2001

Output: Output growth from FAO Laspeyres indexes using FAO dollar price; Input: for crops – cropland, labour, fertilizer, animal power, and machine services (tractors plus harvesters); for livestock: pastureland, labour, fertilizer, animal capital, and feed;

FAO

2.02

1961-2006

Output: crops, livestock, and aquaculture output; Input: land in crops and ponds, agricultural labour, education, and wages, fertilizer and chemicals, machinery, livestock, and poultry, and feed and seed;

Van der Eng (1996); FAO; BPS; SAKERNAS

1.82

Avila & Evenson (2010)

Fuglie (2010)

Fuglie (2012)

Growth accounting

Tornqvist-Thiel TFP Index

Growth accounting

1965-1996

1961-2009

Output: crop and livestock commodity production; Input: land, labour, livestock capital, fertilizer, and machinery resources;

FAO

1961-1970 (1.75); 1971-1980 (1.40); 1981-1990 (0.59); 1991-2000 (0.99); 2001-2009 (3.68)

1149

 Agricultural Productivity in Indonesian Provinces

3. METHODOLOGY AND DATA TFP growth can be measured using two major approaches - parametric and non-parametric. While more widely used, the accuracy of the parametric approach such as Cobb-Douglas heavily depends on the specification of the production function form. An inaccurate specification of the production function could likely result in a misinterpretation of TFP. Parametric approaches also make strict assumptions on the functional form, such as constant returns to scale and technological efficiency, which are difficult to justify in practice. In contrast, non-parametric approaches such as the Malmquist index methodology are sensitive to outliers and data quality (Tong et al., 2008) but not dependent on model specification per se. This paper applies both methodologies to gain a comprehensive understanding of the agricultural TFP growth in Indonesia. Given the lack of observations to conduct a panel analysis at the provincial-level, we applied the growth accounting method only at the national and regional level. The regional grouping is island-based and aligned with the Master Plan for Acceleration and Expansion of Indonesia’s Economic Development (MP3EI) initiated by Indonesia’s Coordinating Ministry for Economic Affairs (2011). In order to have a deeper understanding of the driving factors of TFP growth, we adopted the Malmquist index method at the provincial level, which allowed us to decompose TFP change into technological change and efficiency change.

3.1. Growth Accounting Methodology In this paper, the production function for Indonesia’s agricultural sector is defined using a Cobb-Douglas specification, given by: Yit = Ait X1it1 β

(1)

where i and t indicate economy and time respectively. Yit represents the agricultural value added per labour for economy i at time t. X 1it indicates land per labour for economy i at time t respectively. Ait is defined as the measure for TFP, which includes technology factors, and efficiency factors. By taking natural logarithms on both sides of Equation (1) one can obtain Equation (2), which determines the contribution of input to output and is used in calculating TFP growth. lnYit = β0 + β1 ln X1it + εit

(2)

TFP growth is the difference between real agricultural output growth and the weighted sum of input. Hence, TFP growth is calculated as the residual change in output. Therefore, TFP growth can be measured by Equation (3).2 TFP growthit  =yit −β ˆ1x 1it

1150

(3)

 Agricultural Productivity in Indonesian Provinces

3.2. Malmquist Index Data Envelopment Analysis Considering the various limitations of parametric approaches to estimating TFP and given the limited time series data available, this paper also applies non-parametric approaches to measure agricultural TFP growth in Indonesia in the form of the Malmquist index.3 The Malmquist index is defined in a distance function by Färe et al. (1994). The subscript y in Equation (4) shows that it is an output oriented Malmquist index.  D t (x t +1, y t +1 )  D t +1 (x t +1, y t +1 )   y   y t t +1 t t +1    M y (x , x , y , y )=  t +1 t t t t t     Dy (x , y )   Dy (x , y )   

1/2



(4)

By mathematical transformation, Equation (4) can be written in the form of Equation (5), which allows us to decompose the TFP change into technological change (TC) and technical efficiency change (TEC) (Färe et al., 1994). t

M y (x , x

t +1

t

,y ,y

t +1

Dyt +1 (x t +1, y t +1 )  Dyt (x t +1, y t +1 )   Dyt (x t , y t )     )=  Dyt (x t , y t )  Dyt +1 (x t +1, y t +1 )  Dyt +1 (x t , y t )  

1/2



(5)

TEC refers to activities which can enhance the efficiency of production, including better resource utilization and management. TC refers to a set of developments that can move the productivity frontier forward such as innovation. As specified by Färe et al. (1994), Equation (5) can be written in a more illustrative form as Equation (6). TFPC = TEC ×TC

(6)

The appendix to the paper describes this approach to TFP measurement in more detail.

3.3. Data Finding relevant data at provincial-level is challenging as there is no central database that provides all indicators. The data were collected from 2000-2011. For output, the paper used provincial agricultural GDP from World Bank (2012a), as part of Indonesia Database for Policy and Economic Research (INDODAPOER) that captures crops, livestock, forestry, and fishery. Labour and land are used as inputs. For labour, the data were also sourced from World Bank INDO-DAPOER that referred to a number of people employed in crops, livestock, fishery, and forestry sector. The land indicator covers wetland, garden, dry land, shifting cultivation, temporary/fallow land, and utilized land for main estate crops, sourced from BPS (2000-2012a; 2000-2012b; 2000-2012c) and Ministry of Agriculture (2012). Data on machinery are not available on a consistent time series basis. Fuglie (2010) used the number of tractors in use adjusted for size; 12 horsepower (hp) for two-wheel-tractor and 20, 33, and 50hp per small, medium, and large four-wheel tractor, respectively. Statistical Yearbook of Indonesia published these indicators only up to 2002. The data became available again in 2011, but did not report the four-

1151

 Agricultural Productivity in Indonesian Provinces

wheel tractor. The Ministry of Agriculture also reported the number of tractors but only documented those that were part of government assistance. For fertilizers, Ministry of Agriculture only released the statistics on subsidized fertilizer for recent period, from 2009 onwards. The publication on Farm Cost Structure of Paddy and Secondary Food Crops gave fertilizer application rates per hectare for rice and secondary food crops, however, such data were only available in 2008 publication for paddy, 2009 for corn, and 2010 for soybean (BPS, 2008-2010). Nevertheless, such information was only available for half of the provinces. Since the goal of the paper was to cover as many provinces as possible and finding proxies to fill in unavailable data across provinces over time could further distort the results, the data used in the paper was limited to two input variables including labour and land, which had comprehensive time series and provincial coverage. As of 2014, Indonesia has 34 provinces. The newest province is North Kalimantan which was created in 2012 and hence not included in our analysis. During the period of analysis in the study -- 2000-2011 -- there were seven newly created provinces: North Maluku (carved out from Maluku in 1999), West Papua (carved out from Papua in 1999), Banten (carved out from West Java in 2000), Bangka Belitung (carved out from South Sumatra in 2000), Gorontalo (carved out from North Sulawesi in 2000), Riau Islands (carved out from Riau in 2002), and West Sulawesi (carved out from South Sulawesi in 2004). For some indicators that were not adjusted at source reflecting these changes, data points were estimated based on their past growth trend and relative proportion to their parent province. DKI Jakarta was also not included in the analysis due to the negligible share of its agriculture in the Indonesian economy (0.1 percent).

4. FINDINGS 4.1. Labour Productivity In the case of Indonesia there were significant disparities across provinces in terms of labour productivity in agriculture. Labour productivity was calculated by dividing agricultural GDP by employment in agricultural sector. For average annual growth rate in labour productivity from 2000-2011 in Figure 1, most provinces in Java Island grew faster than the average rate of 4.5 percent, except East Java where more than seven million people were still employed in agricultural sector. There were wide variations of labour productivity within provinces in each region. When the figures were aggregated at the regional level, labour productivity in Java was actually lower than that of Kalimantan, Sumatra, and Sulawesi where expansions in high value estate crops such as palm oil, rubber, and cocoa took place. In fact, the highest labour productivity growth was found in Gorontalo (9.2 percent). Other provinces in Sulawesi also reported favourable labour productivity growth rates of 6.9 percent for Central Sulawesi, 6 percent for North Sulawesi, and 5.6 percent for Southeast Sulawesi. On the other hand, the highest labour productivity growth rates in Sumatra and Kalimantan were found in Bangka Belitung Islands (7.3 percent) and South Kalimantan (5.1 percent), respectively. In contrast, labour productivity for Bali–Nusa Tenggara and Maluku–Papua were lower than the national average. From these two regions, Bali was the only province with higher than average labour productivity growth. Among the eastern provinces, North Maluku reported the highest average of labour productivity growth of 4.1 percent while its neighbors recorded much lower rates; Maluku (1.3 percent), West Papua (2.3 percent), and Papua (0.4 percent). International Fund for Agricultural Development 1152

 Agricultural Productivity in Indonesian Provinces

Figure 1. Labour productivity across provinces (average annual growth rates from 2000-2011)

(2011) has cited a number of ingrained issues found in Maluku and North Maluku that led to poor productivity in agricultural sector such as local conflicts, poor marketing and infrastructure, and insufficient natural resource management.4

4.2. Total Factor Productivity (TFP) Based on panel data analysis using growth accounting, as shown in Table 2, TFP growth for 2000-2011 was 3.1 percent for Indonesia as a whole. Further analysis at the regional level revealed that Sulawesi had the highest TFP growth at 3.5 percent. Other regions which reported higher than national TFP growth were Sumatra (3.3 percent), Java (3.3 percent), and Bali–Nusa Tenggara (3.2 percent). Kalimantan and Maluku-Papua were the laggards with 2.0 percent and 1.5 percent of TFP growth, respectively. The recent initiative to push for Merauke Integrated Food and Energy Estate (MIFEE) that will cover over a million hectares of plantations and industrialised agriculture may contribute to higher TFP growth in Maluku-Papua region in the future.5 Due to limited sample size we did not calculate TFP growth at provincial-level using the growth accounting method. Based on the Malmquist–DEA results, TFP grew at an annual average rate of 3.2 percent from 20002011, which was somewhat aligned with the estimation using growth accounting method. The TC’s contribution was 2.9 percent while TEC’s contribution was 0.3 percent. While this likely overstated the importance of TFP (since we have excluded other inputs for which data are not available), the TFP estimate was slightly below the 3.7 percent found by Fuglie (2012) during 2001-2009.6 1153

 Agricultural Productivity in Indonesian Provinces

Table 2. TFP growth using growth accounting method (2000-2011)

Note: ***, **, and * indicate statistics significance at the 1, 5 and 10 percent levels respectively.

There remained significant variations in TFP growth across provinces as can be seen from Figure 2 which is sorted from the highest to lowest TFP. Banten recorded the highest TFP – a 6.4 percent increase -- and Papua the lowest – attaining a status quo or zero change. Banten performed equally well both in TEC (2.2 percent) and TC (4.1 percent). On the other hand, Papua’s low TEC, a decrease of 2.3 percent, drove down its TFP while its TC grew at about 2.3 percent. Figure 2. Average TFPC and its decomposition from 2000-2011 for 32 provinces

1154

 Agricultural Productivity in Indonesian Provinces

The majority of provinces with high labour productivity growth also reported high TFP growth. For instance, the ten-highest TFP growth provinces recorded labour productivity growth of above 5.1 percent. In fact, the range is between 5.1 percent and 9.2 percent. For the top 10 TFP growth, four provinces were from Sulawesi, three provinces from Sumatra, one from each of Java, Kalimantan, and Bali–Nusa Tenggara. Across the provinces, results suggest that TFP growth could be predominantly attributed to TC with the growth in TEC being marginal and even negative in most provinces (such as Papua and West Sulawesi with a decrease of 2.3 percent). The fact that TC was relatively similar across provinces might be mainly due to the fact that R&D and innovation was still driven by the central government. The funding would typically be allocated to Ministry of Agriculture, Indonesian Agency for Agricultural Research and Development (IAARD) in particular, and then distributed to its local offices in each province. For estate crops, Indonesian Research Institute for Estate Crops (IRIEC) has mainly been funded by the plantation sector itself, through Indonesian Planters Association for Research and Development (IPARD). IRIEC was relatively better funded as research expenditures per scientist were about four times higher than that of IAARD (Fuglie & Piggott, 2006). TEC largely lagged in provinces with profound infrastructure bottlenecks, such as East Nusa Tenggara, West Nusa Tenggara, West Sulawesi, West Papua, Maluku, and North Maluku, all of which reported negative growth. The regional TFPC, TEC, and TC were calculated based on the weighted average of provincial contribution to the region’s agricultural output. Based on Figure 3, Sulawesi outperformed the rest with TFP growth of 3.9 percent, with 1.2 percent coming from improvements in TEC and 2.7 percent from TC. The results corroborated the findings using growth accounting method. Four out of six provinces in Sulawesi were also part of those that registered the ten-highest TFP growth rates. This supports the region’s designated role as a center for production and processing of national agriculture, plantation, and fishery, as stipulated in MP3EI (Coordinating Ministry of Economic Affairs, 2011). Figure 3. Average TFPC and its decomposition from 2000-2011 for six regions

1155

 Agricultural Productivity in Indonesian Provinces

Similar to the estimation by the growth accounting method, Maluku-Papua became the laggard with the lowest TFP growth of 0.6 percent. Based on further decompositions we found out that the TC grew at 2.2 percent, however, its TEC decreased by 1.6 percent. As the easternmost region, Maluku-Papua faces perennial challenges of rudimentary hard and soft infrastructure that hampers its agricultural productivity growth.

5. CONCLUSION AND POLICY IMPLICATIONS The new leadership under President Joko Widodo has emphasized the importance of achieving food sovereignty in Indonesia. The MP3EI also stressed agriculture as one of the eight main programs, with the production of palm oil, rubber, cocoa, animal husbandry, timber, fishery, and food crops as part of 22 main economic activities. Such policies signal the importance of agricultural productivity to the country, especially given the significant regional variations in terms of productivity. In this light, this paper has provided the most recent analysis on estimating agricultural productivity in Indonesia, focusing on the dynamics at the provincial-level. From 2000-2011, TFP grew on average by 3.1 to 3.2 percent using both the growth accounting methods and the Malmquist index. TFP growth at the regional-level is also broadly consistent, indicating the robustness in the estimates. According to the Malmquist index, TFP growth was predominantly due to improvements in TC which was broadly uniform across provinces. This uniformity is not very surprising as TC is driven primarily by R&D, new innovations, and technology under the provision of the central government. It is important to recognize the role of the IAARD in this context, especially for food crops and livestock research, as IRIEC has been driving the research in estate crops. Going forward, IAARD should continue building its technological capacity to gradually strengthen its focus on non-staple foods with higher value-added and its interaction with the private sector. For estate crops that are still dominated by small farms, the challenge is to address the low productivity of smallholders with limited access to high quality inputs. Developing effective systems for small farms is key to improving productivity in estate crops such as in the case of nucleus-plasma program based on partnerships between large estates and smallholders.7 According to World Bank (2010), the intensity with which Indonesia invests in agricultural research, even after adding the R&D spending from private sector, is relatively low (0.22 percent) which is on par with that of Lao PDR (0.24 percent), and much lower than Malaysia (1.92 percent) and the Philippines (0.44 percent). The budget allocation for agricultural R&D in Indonesia tends to be volatile, especially when time gets tough, as in the case of AFC when the budget was cut by more than 60 percent (Fuglie & Piggott, 2006). In addition to increasing R&D funding, it is important to forge greater collaboration with the private sector, involvement of universities, and linkages with those of international R&D providers. Various incentives can be set by the government to encourage private investments in agriculture, such as intellectual property protection and provision of tax concessions to make private investment in agricultural R&D and knowledge creation in better farming techniques more appealing. The role of extension services is crucial to ensuring effective adoption and adaptation of new technology at the local level. There is

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room for improvement in enhancing extension service delivery such as using performance-based budgeting, training and ICT utilization to stay abreast with the latest developments as well as reforming the institutional and management of agricultural extension system to improve efficiency and clarity of direction and roles. As the empirical results point out, the main differences of TFP growth across provinces arise from TEC which can be improved in lagging provinces through better resource utilization. With provinciallevel analysis there is an opportunity for inter-province learning to enhance more efficient resource deployment and management techniques. For many lagging provinces, if they are able to learn from high-performing provinces and enhance TEC, overall agricultural sector can be expanded with minimal increase in resources. Lastly, it is essential to improve the provision of reliable and timely statistics across provinces and over time. With better quality and availability of appropriate data, more evidence-based policy decisions can be made and eventually enhance policy performance.

REFERENCES Avila, A. F., & Evenson, R. E. (2010). Total Factor Productivity Growth in Agriculture: The Role of Technological Capital. In P. L. Pingali & R. E. Evenson (Eds.), Handbook of Agricultural Economics (Vol. 4, pp. 3769–3822). Amsterdam: Elsevier. doi:10.1016/S1574-0072(09)04072-9 Biro Pusat Statistik. (2012). Regional GDP according to Industrial Origin. Jakarta: Biro Pusat Statistik. Biro Pusat Statistik. (2008-2010). Farm Cost Structure of Paddy and Secondary Food Crops. Jakarta: Biro Pusat Statistik. Biro Pusat Statistik. (2000-2012a). Land size according to its utilisation. Jakarta: Biro Pusat Statistik. Biro Pusat Statistik. (2000-2012b). SAKERNAS (National Labour Force Survey). Jakarta: Biro Pusat Statistik. Biro Pusat Statistik. (2000-2012c). Statistical Yearbook of Indonesia. Jakarta: Biro Pusat Statistik. Coelli, T. J., & Rao, D. P. (2005). Total factor productivity growth in agriculture: A Malmquist Index analysis of 93 countries, 1980–2000. Agricultural Economics, 32(Suppl. 1), 115–134. doi:10.1111/j.01695150.2004.00018.x Coordinating Ministry for Economic Affairs. (2011). Masterplan for Acceleration and Expansion of Indonesia’s Economic Development. Jakarta: Coordinating Ministry for Economic Affairs. Färe, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries. The American Economic Review, 84(1), 66–83. Food and Agriculture Organization. (2012). FAOSTAT Database. Rome: Food and Agriculture Organization of the United Nations Statistics Division. Fuglie, K. O. (2010). Sources of growth in Indonesian agriculture. Journal of Productivity Analysis, 33(3), 225–240. doi:10.100711123-009-0150-x

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Fuglie, K. O. (2012). Productivity Growth and Technology Capital in the Global Agricultural Economy. In K. O. Fuglie, V. E. Ball, & S. L. Wang (Eds.), Productivity Growth in Agriculture: An International Perspective (pp. 335–368). Oxfordshire: C.A.B. International. doi:10.1079/9781845939212.0335 Fuglie, K. O., & Piggott, R. (2006). Indonesia: coping with economic and political instability. In P. G. Pardey, J. M. Alston, & R. R. Piggott (Eds.), Agricultural R&D in the developing world: too little, too late? (pp. 65–104). Washington: International Food Policy Research Institute. International Fund for Agricultural Development. (2011). Smallholder Livelihood Development Project in Maluku and North Maluku. Asia and the Pacific Division Programme Management Department. Ministry of Agriculture. (2012). Agriculture Statistics Database. Jakarta: Ministry of Agriculture. Jakarta. Retrieved from http://aplikasi.deptan.go.id/bdsp/index.asp Mundlak, Y., Larson, D., & Butzer, R. (2004). Agricultural dynamics in Thailand, Indonesia and the Philippines. The Australian Journal of Agricultural and Resource Economics, 48(1), 95–126. doi:10.1111/ j.1467-8489.2004.00231.x OECD. (2012). OECD Review of Agricultural Policies: Indonesia 2012. Paris: OECD Publishing. Suhariyanto, K., & Thirtle, C. (2001, September). Asian Agricultural Productivity and Convergence. Journal of Agricultural Economics, 52(3), 96–110. doi:10.1111/j.1477-9552.2001.tb00941.x Tong, H., Fulginiti, L. E., & Sesmero, J. P. (2009). Chinese Regional Agricultural Productivity: 1994-2005 (Working Paper No. 89). University of Nebraska-Lincoln, Nebraska, Agricultural Economics Department. Warr, P. (2009). Aggregate and Sectoral Productivity Growth in Thailand and Indonesia (Working Papers in Trade and Development No. 2009/10). Canberra: Australian National University, The Arndt-Corden Division of Economics, ANU College of Asia and the Pacific. World Bank. (2010). Indonesia Agriculture Public Expenditure Review 2010. Jakarta: World Bank. World Bank. (2012a). INDO-DAPOER (Indonesia Database for Policy and Economic Research). Jakarta: World Bank. Retrieved from http://databank.worldbank.org/data/reports.aspx?source=1266 World Bank. (2012b). World Development Indicators. Washington, DC: World Bank. Retrieved December 1, 2014, from http://data.worldbank.org/data-catalog/world-development-indicators

ENDNOTES 1



2



3

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Estate crops, called perkebunan in local term, refer to rubber, coconut, palm oil, coffee, tea, pepper, clove, cocoa, cashew nut, sugar cane, tobacco, and cotton. yit = lnYit  − lnYi,t −1

The other commonly used nonparametric measure is the Törnqvist Index. However, this methodology has rather strict data requirements, including prices and quantitative data of both inputs and output. In addition, it also has some assumptions such as a perfectly competitive market and profit maximisation, which are not suitable for agricultural studies.

 Agricultural Productivity in Indonesian Provinces

4



5



6



7

8



On top of that, other issues included limited knowledge of modern agricultural practices and lack of effective extension services, research outreach, supply of production input, and financing. As a result, most agricultural output was of poor quality with low market value as there was no local value addition through processing and marketing. Hence, it was not surprising that most food crop production solely aimed for meeting subsistence needs. MIFEE is part of the MP3EI projects which designate Merauke as the center of food and energy reserves in eastern part of Indonesia. It was reported that the program has attracted a dozens of domestic and foreign investors who were interested in growing rice, corn, soybean, sugar cane, and palm oil. Another study by Fuglie (2010) found 2.4 percent TFP growth from 2001-2006. Under this program, large estates (nucleus) will be provided subsidized capital and long-term leases to state land for crop production with the conditions that they provide inputs, credit, and other services such as technical and marketing services to smallholders (plasma) surrounding their plantations. TEC can be further decomposed into two parts which are Pure Technical Efficiency Change (PTEC) and Scale Efficiency Change (SEC) as illustrated by Equation (A10).

This research was previously published in the International Journal of Asian Business and Information Management (IJABIM), 7(3); edited by Patricia Ordóñez de Pablos, pages 26-39, copyright year 2016 by IGI Publishing (an imprint of IGI Global).

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APPENDIX The Malmquist Index Data Envelopment Analysis (DEA) Methodology According to Färe et al. (1994), the change of TFP can be decomposed into TC and TEC through the Malmquist index. Every time point has its specific technology level. Therefore, if a selected time point is represented by t, its corresponding technology level can be labelled as St . In this context, x t can be used to represent all inputs of the production activity, and y t can be used to represent all outputs of the production activity. Under these circumstances, St can be defined in the form of equation (A1) which captures all possible combinations of inputs x t and outputs y t under the available technology at time t. St = {(xt , yt ), xt produce yt }

(A1)

Since the agricultural production activity in the real world can hardly fully achieve and implement all cutting edge technologies in a specific time point t, a differentiation between the actual output and the ideal output could be spotted. According to Färe et al. (1994), the differentiation can be defined as Equation (A2).

D

t y

= inf{θ : (xt , yt / θ) ∈ St } = {sup[θ : (xt , θ yt ) ∈ St ]}−1

(A2)

Equation (A2) is an output-oriented distance function, in which Dyt represents the reciprocal of the maximum change in output y through fully exploiting the input x. Given the input level x t at time t, Equation (A2) can be used to measure the maximum expansion θ of the output y t . Meanwhile, Dyt can also be interpreted as the reciprocal of the maximum efficiency change of the output y t by fully exploiting input x t . Similarly, as shown in Equation (A3), the input-oriented distance function can measure the change of inputs given the output level. Dxt = sup{λ : (x t / λ, y t ) ∈ S t }

(A3)

Dyt = inf{θ : (x t +1, y t +1 / θ) ∈ S t } = {sup[θ : (x t +1, θy t +1 ) ∈ S t }−1

(A4)

Equation (A4) represents the reciprocal of maximum change of output, given input x t +1 , to make y t +1 feasible at time t. Hence, the Malmquist index can be written in the form of Equation (A5) and Equation (A6). t y

M =

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Dyt (x t +1, y t +1 ) Dyt (x t , y t )



(A5)

Agricultural Productivity in Indonesian Provinces

M

t +1 y

=

Dyt +1 (x t +1, y t +1 ) Dyt +1 (x t , y t )



(A6)

If a specific time t is selected, the corresponding technology level will become the reference technology level. Under these circumstances, Equation (A5) can be used to measure the necessary change to generate the output y t +1 through utilizing the input x t +1 with the feasible technology S t . In order to avoid choosing an arbitrage benchmark, the geometric mean of the two Malmquist indices can be calculated to form a benchmark (Färe et al. 1994). M y (x t , x t +1, y t , y t +1 ) = M yt ∗ M yt +1  D t (x t +1, y t +1 )  D t +1 (x t +1, y t +1 )   y   y    =  t +1 t t t t t     Dy (x , y )   Dy (x , y )   

1/2



(A7)

Equation (A7) can be decomposed into two parts through mathematical transformation as illustrated by Equation (A8). t

M y (x , x

t +1

t

,y ,y

t +1

Dyt +1 (x t +1, y t +1 )  Dyt (x t +1, y t +1 )   Dyt (x t , y t )     )=  Dyt (x t , y t )  Dyt +1 (x t +1, y t +1 )  Dyt +1 (x t , y t )  

1/2



(A8)

Equation (A8) can be perceived as two components. The first component represents the technical efficiency change between time t and time t+1, and the second component represents the technological change between time t and time t+1. The practical meaning of this transformation is that, the Total Factor Productivity Change (TFPC) can be decomposed into Technical Efficiency Change (TEC) and Technological Change (TC), as shown in Equation (A9) (Färe et al. 1994). TFPC = TEC ×TC

(A9)

TEC is broadly related to better resource utilization or deployment as well as more efficient management. TC broadly refers to the technology innovation or progress, which can shift the production frontier. For example, an invention of new technology could shift the agricultural production frontier. Thereafter, the true driving factor could be identified through the decomposition of TFPC, which may potentially draw valuable lessons for future development of the agriculture sector.8 Linear Programming approach is used to calculate the Malmquist index in this paper. In short, the Malmquist index methodology not only allows us to decompose TFPC into TEC and TC, but also provides relative rankings of economies based on their distance to the efficiency frontier.

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(

M y x t , x t +1, y t , y t +1

)

 D v,ty+1 (x t +1, y t +1 )  Dyv,t (x t , y t )  = D v,ty (x t , y t )  Dyv,t +1 x t +1,y t +1 

(

1162

)

  D c,t +1 (x t +1,y t +1 )  D c,t (x t +1, y t +1 )   D c,t (x t , y t )  1/2       y y y   c,t +1 t +1 t +1   c,t +1 t t    c ,t t t     Dy (x , y )   D y (x , y )  D y (x , y )  

(A10)

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Chapter 52

Importance of Sustainable Rural Development Through Agrarian Reforms: An Indian Scenario

Partha Mukhopadhyay National Institute of Technology Durgapur, India Madhabendra Sinha National Institute of Technology Durgapur, India Partha Pratim Sengupta National Institute of Technology Durgapur, India

ABSTRACT The chapter tries to find out the relationship between public expenditures on infrastructure related to agriculture and allied factors and agricultural sustainability in Indian context. India has been suffering from appalling chronic poverty and to reduce the same, we need to focus on rural development, particularly in agriculture as it is unavoidable relation with economic development. Gini index of India is 33.9 (2011) i.e. asymmetrical wealth distribution exists. India is being burdened with a population of 1.2 billion as in 2015. The reciprocal relationship between agrarian reform and democratic development is pronounced. Agrarian reform was one of the focal points around which social mobilization occurred. Sustainable rural development could be achieved by a new balance as we find from some econometric model, which is being sought between agriculture and public expenditure and also export of agricultural produce. Adopting bottom-up agricultural development approaches which emphasize the involvement of the rural people in the implementations of different development programmes may escalate agrarian reforms.

DOI: 10.4018/978-1-5225-9621-9.ch052

Copyright © 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Importance of Sustainable Rural Development Through Agrarian Reforms

INTRODUCTION Development is a concept construing changes in the conditions of well being of the people irrespective of income level. It is generally evaluated in terms of changes in aesthetic qualities of the community, i.e. demographics, housing, employment, income, market effects, public services etc. Of late India shows as one of the fastest growing economies in the world. This chapter brushes one more stroke the emerging relationship of infrastructure availability and productivity growth. This analysis relies on both qualitative and quantitative measures of impacts. Infrastructure, no doubt, is the backbone of any society. Infrastructure development is a sine qua non for accelerating progress of the quality of human life. Though infrastructure projects, involve huge initial capital investments, high incremental capital output ratio, high risk with long gestation periods, and low rate of returns on investments but infrastructure development particularly, rural infrastructure encompass economic development of the country. Rural infrastructure has a direct and strong relationship with farmers. Rural infrastructure development is supposed to be a benchmark to transform the existing traditional agriculture or subsistence farming into a most modern, commercial and dynamic farming system so that India could oust the surplus labourers to any other productive jobs. We can group infrastructure under some categories as given in Table 1.

Role of Agriculture in Infrastructure Development Agriculture ensures supply of food to industrial sector (Lewis, 1954) and hence it is a driving force of overall economic development (Mellor, 1966; Schultz, 1964). Technology spillovers also increase in productivity of Land and labour and as a result income of farmers increase which enhance their purchasing powers. A number of empirical studies (Hazell & Roel, 1983; Hammer & Hazel, 1991; Delgado, 1998; Zhang, 2002) ensured that multiplier effects of agricultural growth are greater than two. Table 1. Categorization of infrastructure Based

Resources

Rural Sector

Urban Sector

Input Based

-

Agricultural input like Seed, Fertilizer, Pesticides, Farm equipment and machinery etc.

-

Water

Irrigation and Drinking

Drinking

Electricity

Pump and Household

Household and Industrial Purpose

Physical Infrastructure:

Telecommunication, Road connectivity, Transport, storage (including Cold storage), processing, preservation, and Sanitation etc.

Required all Resources

Required all Resources

Institutional Infrastructure:

Education, research, information & communication services, financial services, market, etc.

Required all Resources

Required all Resources

Resource Based:

Source: Authors’ Own Observation

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Several studies explain the elasticity of poverty reduction with respect to agricultural productivity is significant ((Thirtle, Lin & Piesse, 2003). Some econometric studies (Binswanger & Rosenzweig, 1993; Butzer, 2002; Zhang, 2004) estimated that there is a positive significant relationship between agricultural output and infrastructure investment. Agricultural sector has also played an important role as foreign exchange earner too. Agricultural exports accounted for 44 percent of India’s total merchandise export during 1960-61and in 2013-14 it is more than 17 percent of export earnings of India. There is a positive correlation between GDP and Public Expenditure on Agriculture (0.98) and similarly, GDP to export of Agricultural and allied product (0.96). So, agricultural infrastructural growth plays a significant role to the economic development in the context of India in particular.

A Brief Discussion on Indian Agriculture Agriculture is consistently losing its importance in India’s economic growth. According to CIA Factbook-2014, agriculture sector contributes 17.9 percent of India’s Gross Domestic Product (GDP), and in 2015, in the Budget it is reported that more than 50 percent of the population is still dependent on it. The farm sector, including forestry and fishing, grew by 3.2 percent in the quarter ending September, as compared o 3.8 percent in previous quarter and 4.7 percent in 2013-14. For the entire financial year, it was 1.4 percent. Backed by continued technological innovations in the sector, India’s food grain production has more than doubled over the decades to a record 264 million tons in 2014, but the same is not being

Figure 1. Role of Infrastructure in Agricultural Development

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 Importance of Sustainable Rural Development Through Agrarian Reforms

Figure 2. GDP of Agriculture and Allied Services

Source: CSO, Government of India, Annual Data from 1990-2015

capitalized to increase the profit margins and revenue of farmers. There is still a large dependency on rainfall and other climatic conditions for good yield, and post-harvest logistics remains an area of concern. In the post-1990s period, there has been a continuous decline in government support in the form of declining investments in agriculture. The withdrawal of the State has led to a much greater dependence of farmers on private sources. Very unfortunate to say that there has also been an upward trend in the cases of farmer suicides over the years and the victims have largely been marginal and small farmers. Increasing costs of cultivation leading to higher indebtedness, crop failures, inability to face price rise with greater liberalization of the agricultural sector and profile of gobbling up of lion’s share of profit margin by the marketing middleman have forced farmers to take this extreme step a death trap to speak of. A report was published by zee news exclusive of union budget-2015 that it’s a fact in India; farmers are receiving only around 25 to 30 percent of the price paid by the consumers. The loss appears not due to their inefficiencies but also for unwanted role of middlemen. Farmers in developed economies of Europe and the United States, in contrast, receive around 75 percent of the price that consumers pay. The wide gap between ultimate sellers of agricultural goods and the ultimate purchasers of the same makes the system vulnerable in view of sustainability when market is treated as an institution in the age of globalization. The entire system is likely to be changed without any more delay. The growth performance of the agriculture sector has been fluctuating across the time periods 1990 to 2015. Inflationary trend of food items has got a close link with the supply crunch, triggered by the international market. To deal with this type of vulnerability, there is also a need to make long-term plan. India is still dependent on the other Countries for some commodities such as edible oil (mostly palm oil) and pulses, despite the prevailing agriculture-intensity profile of India. India imports more than 50 percent of its cooking oil. Long-term approach in trade policy and lack of consistency make us dependable for these commodities on overseas market. Government of India generally reduces the import duty of a particular commodity to tame price rise but in the long run escalates the inflow of that commodity in the domestic market and increase our dependability. While taking a decision on duty, the government should take into account the concerns of all stakeholders related to that commodity, mainly producers,

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 Importance of Sustainable Rural Development Through Agrarian Reforms

Figure 3. Pattern of growth of GDP and GDP of agriculture Source: CSO, Government of India, Annual Data from 1990-2015

exporters and consumers too. When the government reduces import duty, it impacts all stakeholders simultaneously. Cutting of import duty makes the same domestic commodity uncompetitive. But consumers get that international commodity at a lower price. When government decides to increase import duty, the same impact appears. In that situation, at the best competitive price, the produce for which import duty is increased minimizes the only option for consumers to get same international commodity. As export is one of components of GDP the growth by export led hypothesis postulates that export expansion is one of the main determinants of growth. India’s export performance is fluctuating in nature from 1990-2015. In 1997, for the first time after liberalization, India’s exports registered with negative growth of 2.33 because of the East Asian Crisis. Since the ASEAN countries and Japan were most acutely affected by the crisis, their respective currencies lost value, which also meant that the Indian rupee appreciated against these currencies (due to interest rate differentials). Agricultural export of India faces the impact of negative growth in the year 1999-2000 than previous year. The next major setback for India’s exports was the global crisis of 2008. India’s trade deficit dampened in 2009-10 with a negative import growth (-0.78 percent) were also impacted with a negative growth rate of 2.9 percent in 2008-09 than Figure 4. Agricultural export as a share of agricultural GDP

Source: DGCIS and CSO, Government of India, Annual Data from 1990-2015

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previous years. India has been following overall an increasing path in agricultural exports throughout the period from1990 to 2015 except the years 1999-2000 and 2009-2010. Some commodities such as wheat, sugar, cotton, edible oil, rubber etc are directly related to the government’s trade decisions and control. It is observed that in the past few years, the government’s approach to deal with the trade of the commodities has been widely exposed. Indian Government has to adopt bottom-up agricultural approaches which emphasize the involvement of the rural people and first prioritize the concerns of our own farmers. Composition of exports means goods that we are selling to other countries. At the time of Independence, exports of India were consisted of agricultural products like tea, spices, tobacco and other raw materials etc. We were also exporting cotton textiles and jute products in large quantities. We are now exporting large quantities of items such as machinery and transport equipment, chemicals allied products, marine products, and handicrafts, however export of items such as fish, cotton, fabric, tea, Jute, manufactures spices etc.

Rural Infrastructure Rural infrastructure is a major bottleneck in achieving the potential growth-path under globalization. In a Study, (Oshikoya & Hussain, 2002) it is revealed that better rural infrastructure improves pricecompetitiveness and attracting Foreign Direct Investment (FDI). In their studies (Wheeler & Ashoka, 1992; Asiedu & Donald, 2004) they found that status of domestic infrastructure is an important determinant of the magnitude of private capital inflow such as FDI. Efficient transportation system with modern telecommunication facilities, reliable energy supply and access to safe water are the essential conditions for attracting investments from outside the country.

Market Market integration over space and time requires sound infrastructure with all other facilities. Market integration is assumed to be poor in India resulting in drastic drops in local prices and restricted access to commercial finance. We are suffering from poor transport, storage capacity and weak form of communication infrastructure. Rule of law hardly works due low quality of governance; effective competition among the markets is absent. Hence market transaction is highly non-transparent in India. So, development of transparent rules and regulations is essential for infrastructure development as everything is hanging together. As the economic environment becomes adverse, then global financial crisis arises (J.N. Verma, W.P. No. 2009-02-06). Despite the bottleneck of agrarian crisis, India’s food grain production has more than doubled over the decades to a record 264 million tonnes in 2014 because of technological spillover and other factors too, whereas the wellbeing of the growth of output is not transmitted to the farmers with a same rate, a gross inequality. There is still a large dependency on rainfall and other climatic conditions for better yield and post-harvest logistics remains an area of concern. Over the years, marginal and small farmers’ suicidal upward trend is observed due to increasing costs of cultivation, higher indebtedness, crop failures and inability to get adequate price.

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Figure 5. Infrastructure as a base of overall development including agricultural development Source: Authors’ Own Observation

Problem Background Does investment in “Infrastructure” is beneficial? Govt. of India invests Rs. 12810.22 billion in 2013-14 Union Budget and Rs. 4845.33 Billion in 2014-15 Union Budget for total Infrastructure Development. Only a few researches are available in investment in infrastructure. Bennathan and Canning (2000) indicate that investments in electricity generating and paved roads are more profitable than other public investments. But the question is why the investment is low? In the view of agrarian crisis, India’s food grain production has more than doubled over the decades to a record 264 million tonnes in 2014 backed by Technological spillover, but the same is not being capitalized to increase the revenue and profit margins of farmers. There is still a large dependency on rainfall and other climatic conditions for good yield and post-harvest logistics remains an area of concern. Farmers are greater dependence on private sources led by withdrawal of state. Over the years, marginal and small farmers’ suicidal upward trend is observed due to increasing costs of cultivation, higher indebtedness, crop failures and inability to get adequate price. 1169

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REVIEW OF LITERATURE Tripathi (2008) examined the performance of agricultural productivity in India during the last 37 years, and found stagnation of TFP growth in Indian agriculture. Using the time series data for the period from 1970 to 2005, Shombe (2005) investigated causal relationships among agriculture, manufacturing and exports in Tanzania. The empirical results show that the evidence of Granger causality but agriculture causes both exports and manufacturing. It is really an interesting study where scenario of exports and manufacturing sector become better off with the progress of agricultural activities in developing nation. Khalafalla and Webb (2000) empirically tested the growth hypothesis of export leading for Malaysian economy undergoing major structural changes. Khalafalla and Webb also investigated the relationship between the exports and economic growth in Malaysia using the quarterly data from 1965-1996. Bashir (2003) studied the Pakistan’s impacts of economic reforms and trade liberalization on agricultural export performance. He suggested that economic reforms affected the agricultural export performance which is more sensitive to the domestic factors. Shirazi and Manap (2004) re-investigate the exports-economic growth nexus, using the data from 1960 to 2003 period and the results strongly support a long-run relationship among the three variables (imports, export and output). As far as the causality between the exports and output growth is concerned, exports cause output growth, but converse is not true. Khan et. al. (1995) investigated the export- growth and economic growth using the granger causality test and co-integration methods and found stable long-run two way relationship between total exports and output while one way relationship between output and primary exports. In their findings, there is a bi-directional causality between total exports growth and economic growth exclude. Huges and Penson (1985) have shown a marked increase in volume of agricultural exports over the years. The authors measured the effects of GDP movements on agriculture. In his research, Chandra (2000) found the bi-directional causal relationship between the growth of exports and GDP growth; short run causal relation is pronounced, because co-integration between GDP growth and growth of exports was not found. Sharma and Panagiotidis (2005) test the export-led growth hypothesis in the Indian context, and the results strengthen the arguments against the export-led growth hypothesis in the context of India. Raju and Kurien (2005) analyzed the relationship between exports and economic growth in India over the period of pre-liberalization (1960-1992), and found strong support for unidirectional causality from exports to economic growth. They have use Granger causality regressions based on stationary variables, with and without an error-correction term. The causal relationship between growth of exports and economic growth in India for the post-liberalization period 1992-2007, analyzed by Dash (2009) ; the results indicate that there exists a long-run relationship between output and exports, and it is unidirectional from growth of exports to output growth.

RESEARCH OBJECTIVE We are estimating the relationship between public expenditures on infrastructure related to agriculture and allied factors and agricultural sustainability measured in terms of production and export for a given period.

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It is an attempt to provide the emerging relationship of infrastructure availability and productivity growth. By measuring the impact of availability of different type of infrastructural facilities on growth of total factor productivity in state economies in India we may conclude whether the trend is sustainable or not.

HYPOTHESES On the basis of introductory background, following two null hypotheses are to be tested for achieving the above mentioned objective of the study. They are categorized as following: H1: Public expenditure on agriculture does not cause output of agriculture in terms of market value. H2: Public expenditure on agriculture does not have any impact on agricultural export.

DATA SOURCES The study relies on secondary data compiled from various published sources such as RBI Handbook, World Bank Data etc. The other major sources for the collection of the information are found to be available literature as, journals, books, and news of Government of India and states Governments related to the agriculture, energy, transport, education etc. For trend analysis, we are collecting data from the year 1970-71 to 2014-15. GDP data and export of agriculture and allied product data of same time span are collected for comparing the trend also.

RESEARCH METHODOLOGY A large number of methods or econometric tools are used in the literature to study the relationship, including infrastructural growth, agricultural-export and GDP. The independent variables used, as a proxy for infrastructure is either some measure of investment or a physical indicator (Straub, 2008). We know that time series data on any quantitative character or variable may contain either deterministic trend or stochastic trend or both. But implications are obviously different in nature. The time series with deterministic trend follows trend stationary process (TSP), while a non-stationary time series showing stochastic trend is a difference stationary process (DSP). The issue whether a macroeconomic time series is of DSP or TSP is extremely important because the dynamic properties of the two processes are different (Nelson & Plosser, 1982). While the former is predictable, the latter is completely unpredictable. In a series following TSP, cyclical fluctuations are temporary around a stable trend, while for DSP any random shock to the series has a permanent effect. The cyclical components of a TSP originate from the residuals of a regression of the series on the variable time, and a DSP involves regression of a series on its own lagged values and time. A TSP has a trend in the mean but no trend in the variance, but a DSP has a trend in the variance with or without trend in the mean and here it should be mentioned that a random walk without drift has no trend in the mean values of the variable. The most widely used model to take over stochastic trend is autoregressive of order p [AR(p)]:

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Xt = α + β1Xt −1 + β2Xt −2 + β3Xt −3 + ............ + βp Xt −p + εt

(1)

Xt gives values in log form in time t and εt is a stationary series with mean zero and variance σ2. This model can generate the trend behaviour of macroeconomic time series and the randomly fluctuating behaviour of their growth rates. If, for example, Xt is generated by the model: Xt = α + Xt −1 + εt

(2)

Equation (2) is AR (1) with β1=1, accumulating Xt starting with an initial value X0 we get, t

Xt = X 0 + αt + ∑ εj j =1

(3)

The Equation (3) has the same form as the conventional log-linear trend equation, excepting for the fact that the disturbance is not stationary. One important property of time series data, not usually present in cross-sectional data, is the existence of correlation across observations. Income today, for example, is highly correlated with income of the last year. Thus Xt tends to exhibit trend behaviour and to be highly correlated over time. The nonstationary time series containing a unit root will give a stochastic trend. If β1 = 1 for the AR(1) model, then Xt has a unit root and exhibit trend behaviour, especially when α ≠ 0. Unit root series contain a so called stochastic trend. The Augmented Dickey-Fuller (ADF) test is performed for unit root hypothesis. The more appropriate model for testing a unit root is the AR(p) with deterministic trend: ∆Xt = α + ρXt −1 + η1∆Xt −1 + η2∆Xt −2 + ........... + ηp−1∆Xt −p +1 + δt + εt ,

(4)

A series belongs to the class DSP exhibiting stochastic trend if ρ =0, δ=0, and the TSP class if ρ < 0. If ρ = 0, then Xt contains a unit root. In this case we cannot perform hypothesis testing by utilising the usual distributions appropriate for least square. Thus we have to follow ADF test. If the t-statistics on ρ are less negative than the Dickey-Fuller critical value, we conclude that the series Xt has a unit root. To test whether the series has a unit root, we have to choose lag length (p). Many sophisticated statistical criteria and testing methods are available to determine the appropriate lag length in an AR(p) model. But we have performed a simple route by choosing a maximum lag length and then sequentially drop lag lengths if the relevant coefficients are insignificant. The maximum lag length is chosen by following Schwert (1989) rule: Pmax = integer part of [12(T/100).25].

(5)

AIC is also used for selecting the appropriate lag length. By following such criteria, the maximum lag length is found to be 1. Thus our model would be:

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 Importance of Sustainable Rural Development Through Agrarian Reforms

∆Xt = α + ρXt −1 + η1∆Xt −1 + δt + εt ,

(6)

The stochastic properties of the time series data in this study have been examined by carrying out Augmented Dickey Fuller (ADF) and Phillips-Perron (PP) unit root tests. Both the intercept and trend components have been incorporated in the ADF estimated relation as following: P

∆Xt = ϕ0 + βt + ρXt −1 + ∑ γi ∆Xt −1 + εt i =1

(7)

The ADF statistic is the t-value associated with the estimated coefficient of ρ, the probability distribution of which is a functional of the Weiner process, the process used in explaining Brownian motion of a particle with large number of molecular shocks (Maddala & Kim, 1998). The PP test is the nonparametric extension of the DF unit root test by adding a correction factor to the DF t statistic. The tests have been performed for all the logarithmic series and their first differences. The choice of lag length is very much crucial at this stage and the number of lags used in the ADF regressions is selected by the Akaike (1969) Information Criterion (AIC). We have applied cointegration theory developed in Engle and Granger (1987) by utilizing the methodology developed by Johansen and Juselius (1990). The concept of cointegration, first developed in Granger (1981), is relevant to the problem of the determination of long-run equilibrium relationships in economics in a sense that the variables move together over time so that short-term disturbances from the long-term trend will be corrected (Manning & Andrianacos, 1993). Engle and Granger (1987) have shown that if two time series are cointegrated there will be a causal relation in at least one direction. Furthermore, the Granger Representation Theorem demonstrates how to model cointegrated I(1) series in the form of vector autoregression (VAR). In particular, the VAR can be constructed either in terms of the levels (logarithmic values) of the data, the I(1) variables; or in terms of their first differences, the I(0) variables, with the addition of an error correction mechanism (ECM, which is first used by Sargan (1984) and later popularized by Engle and Granger (1987)) to capture the short-run dynamics. If the data are I(1) but not cointegrated, causality tests cannot accurately be performed unless the data series are transformed into stationary series. For two variables Y and X, the model can be presented either of the following form: p

r

i =1

j =1

m

n

i =1

j =1

ln Xt = θ + ∑ πi ln Xt −i + ∑ ϕ j lnYt − j + vt

lnYt = α + ∑ βi ln Xt −i + ∑ γ j lnYt − j + ut

(8)

(9)

or,

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 Importance of Sustainable Rural Development Through Agrarian Reforms

p

r

i =1

j =1

m

n

i =1

j =1

∆ ln Xt = θ + ∑ πi ∆ ln Xt −i + ∑ ϕ j ∆ lnYt − j + λECM t −1 + vt (8.a)

∆ lnYt = α + ∑ βi ∆ ln Xt −i + ∑ γ j ∆ lnYt − j + δECM t −1 + ut (9.a) Where ut and vt are zero-mean, serially uncorrelated, random disturbances, error-correction mechanism is denoted by ECM. If the data are I(1) but not cointegrated, valid tests may be done by using the first differences without the error correction term: p

r

i =1

j =1

m

n

i =1

j =1

∆ ln Xt = θ + ∑ πi ∆ ln Xt −i + ∑ ϕ j ∆ lnYt − j + vt

(10)

∆ lnYt = α + ∑ βi ∆ ln Xt −i + ∑ γ j ∆ lnYt − j + ut

(11)

RESULTS AND DISCUSSION We present our results of unit root test on the basis of methodology taken in our study as mentioned in earlier.

Unit Root Test Table 2 represents the ADF and PP test statistics for testing unit roots of all the series. Unlike most of the time series analysis, here the null hypothesis of the presence of unit roots is rejected in the original series indicating that all the series are stationary at level in case of both ADF and PP test. Table 2. Estimated Statistics of Unit Root Tests Series

Augmented Dickey-Fuller Test Statistics Level

First Difference

Level

First Difference

GDPAGR

0.05

-2.04***

-0.33

-4.78***

PEAGRT

0.31

-5.15***

0.29

-5.15***

EXAGR

-0.07

-4.14***

-0.11

-4.15***

Note: ***, ** and * denote the level of significance at 1%, 5%, and 10%, respectively Source: Authors’ own estimation by using data from HBSIE, RBI database, in E-views 7

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Phillips Perron Test Statistics

 Importance of Sustainable Rural Development Through Agrarian Reforms

To find the dynamic relationships between agricultural export and different measures of India’s public expenditure on agriculture as mentioned above we have used cointegration theory developed in Engle and Granger (1987). The ADF and PP unit root tests suggest that the all the series of the variables are integrated of order one I(1). All the stationary variables at same order of integration may have a common trend and it is reasonable to search for a possible cointegrating relationship among them. In this context we plan for co-integration test. We can also argue that agricultural exports from India continuously follow a time trend.

Cointegration Test The estimated results of Johansen’s cointegration tests have been shown by Table 3. Both the trace or LR test statistic and the eigenvalues are used for testing the hypothesis of presence of cointegrating relation, against the alternative hypothesis of full rank. Findings suggest that are three cointegrating equations as trace statistic reports at 5 percent level. But maximum eigenvalue test indicates no cointegration at the 5 percent level, also denotes the rejection of the hypothesis in case of at most two hypothesized number of cointegrating equations. So we think there may have a long run relationship between India’s agricultural export and India’s public expenditure on agriculture. Now we have to test the long run dynamic relationship among the variables by utilizing the structure of vector error correction mechanism (VECM) by incorporating two period lag as suggested by the minimum AIC rule If a set of variables have one or more cointegrating vectors then a suitable estimation technique is a VECM (Vector Error Correction Model). VECM adjusts to both short run changes in variables and deviations from equilibrium. The vector error correction model (VECM) is a special case of the VAR for variables that are stationary in their differences (i.e., I(1)). The VEC can also take into account any co-integrating relationships among the variables.

Table 3. Estimated statistics of Johansen Cointegration Test Unrestricted Cointegration Rank Test Tests

Trace

Maximum Eigenvalue

Hypothesized No. of CE(s)

Eigenvalue

Statistic

5% Critical Value

Prob.**

None *

0.588955

31.39727

29.79707

0.0324

At most 1 *

0.299622

9.170966

15.49471

0.3498

At most 2 *

0.010646

0.267572

3.841466

0.605

None*

0.588955

22.22631

21.13162

0.035

At most 1*

0.299622

8.903394

14.2646

0.2943

At most 2 *

0.010646

0.267572

3.841466

0.605

Trace test indicates 3 cointegrating eqn(s) at the 0.05 level Max-eigenvalue test indicates 3 cointegrating eqn(s) at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values Source: Authors’ own estimation by using data from HBSIE, RBI database in E-views 7

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 Importance of Sustainable Rural Development Through Agrarian Reforms

Table 4. Results of Vector Error Correction Model Error Correction: CointEq1 D(GDPAGR(-1)) D(GDPAGR(-2)) D(PEAGRT(-1)) D(PEAGRT(-2)) D(EXAGR(-1)) D(EXAGR(-2)) C R-squared

D(GDPAGR)

D(PEAGRT)

D(EXAGR)

-0.71822

-1.17944

2.661093

[-2.76333]

[-1.61121]

[ 2.62920]

0.52214

0.928719

-1.00734

[2.46658]

[ 1.25972]

[-0.98822]

-0.06179

0.085089

0.342979

[-0.35720]

[ 0.17465]

[ 0.50915]

-0.16023

-0.92865

0.314009

[-1.92889]

[-3.96931]

[ 0.97071]

0.866918

-0.61785

0.225633

[ 3.77236]

[-2.53196]

[ 0.66876]

-0.25396

-0.53041

0.411644

[-2.34835]

[-1.74146]

[ 0.97748]

-0.26477

-0.45654

0.288386

[-3.36582]

[-2.06067]

[ 0.94144]

0.001782

0.006193

-0.005

[ 0.22709]

[ 0.28027]

[-0.16366]

0.814224

0.584802

0.517655

Adj. R-squared

0.727529

0.391043

0.29256

Sum sq. resids

0.020508

0.162677

0.310994

S.E. equation

0.036976

0.10414

0.143989

F-statistic

9.391802

3.018194

2.299723

Log likelihood

48.12225

24.3065

16.85439

Source: Authors’ own estimation by using data from HBSIE, RBI database in E-views 7

Table 4 shows the estimation of coefficients with corresponding t statistics in [] from the mechanism of vector error correction. Results indicate that only the GDP growth of India is significantly determined by the India’s Agricultural export with one period lag.

CONCLUSION AND POLICY SUGGESTION The chapter tried to contribute a new dimension to the study of sustainable rural development through agrarian reforms by investigating the impact of public expenditure on agriculture in terms of production and export empirically in India for a long period from 1970-71 to 2014-15. Our findings, by applying Johansen cointegration tests on the basis of unit root test results, imply that there is at least one cointegrating equation as suggested by both trace and maximum eigen value statistics. So there may have a long run equilibrium relationship among variables. The results of vector error correction mechanism model to find the long run dynamics show that growth of agricultural output is significantly influenced by public expenditures on agricultural and allied sectors with one period lag.

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Low productivity with high cost of production and absenteeism of labour are the important barriers to the Indian agriculture. To develop agricultural market, value addition in the current infrastructure, such as more number of cold storage, roads, green mandi are urgently required. Currently India is facing some problems in productivity gain and in lowering cost of production. FAO suggested that the unit cost must be reduced through productivity gain. It is most challenging time for introduction of energy and cost effective technology and equipment so that long-term strategy with a good infrastructure only pays the agricultural sustainability. There is also a huge scope to carry forward this research study further by looking at the aspects of long run relationship with direction of causality between agricultural performance and private investment in Indian agriculture in India. This would ensure more robust results and much more meaningful analysis which could be helpful for the policymakers as well as researchers in India to frame an Infrastructure led growth policies in the years to come.

REFERENCES Ahmad, S. (1966). On the theory of induced innovation. The Economic Journal, 76(302), 344–357. doi:10.2307/2229720 Alston, J. M., George, W. N., & Philip, G. P. (1995). Science under Scarcity: Principles and Practice for Agricultural Research Evaluation and Priority Setting. Ithaca, NY: Cornell University Press. Antle, J. M., & Capalbo, S. M. (1988). An Introduction to Recent Developments in Production Theory and Productivity Measurement. Agricultural Productivity: Measurement and Explanation. Washington, DC: Resources for the Future. Arnade, C. (1998). Using a Programming Approach to Measure International Agricultural Efficiency and Productivity. Journal of Agricultural Economics, 49(1), 67–84. doi:10.1111/j.1477-9552.1998.tb01252.x Bashir, Z. (2003). The Impacts of Economic Reforms and Trade Liberalisation on Agricultural Export Performance in Pakistan. Pakistan Development Review, 42(4), 941–959. Bhaumik, S. K. (2015). Principles of Econometrics: A Modern Approach using E-views. Oxford University Press. Bhushan, S. (2005). Total Factor Productivity Growth of Wheat in India: A Malmquist Approach. Indian Journal of Agricultural Economics, 60(1). Binswanger, H. P., & Ruttan, V. W. (1978). Induced Innovation: Technology, Institutions and Development, Baltomore and London. The John Hopkins University Press. Bradshaw, G., & Orden, D. (1990). Granger Causality from the Exchange Rate to Agricultural Prices and Export Sales. Western Journal of Agricultural Economics, 15(1), 100–110. Chambers, R. G., & Just, R. E. (1991). Effects of Exchange Rate Changes on U.S. Agriculture. American Journal of Agricultural Economics, 73, 33–43.

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Chandra, R. (2000). The Impact of Trade Policy on Growth in India (Unpublished PhD Thesis). Department of Economics, University of Strathclyde, Glasgow, UK. Chandra, R. (2002). Export Growth and Economic Growth: An Investigation of Causality in India. The Indian Economic Journal, 49, 64–73. Dickey, D. A., & Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series with a Unit Root. Journal of the American Statistical Association, 74, 427–431. Engle, R. F., & Granger, C. W. J. (1987). Co-integration and Error Correction Representation: Estimation and Testing. Econometrica, 55(2), 251–276. doi:10.2307/1913236 Fan, S., Hazell, P., & Thorat, S. (1999). Linkages Between Government Spending, Growth, and Poverty in Rural India. Research Report 110. Washington, DC: International Food Policy Research Institute. Fischer, A., Petersen, L., Feldkötter, C., & Huppert, W. (2007). Sustainable Governance of Natural Resources and Institutional Change: An Analytical Framework. Public Administration and Development, 27(2), 123–137. doi:10.1002/pad.442 Government of India. (2015). Agricultural Statistics at a Glance, Directorate of Economics and Statistics. New Delhi: Ministry of Agriculture. Gujrati, D. N. (2003). Basic Econometrics. McGraw Hill Education, 4, 696–702. Hughes, D. W., & Penson, J. B. (1985). Effects of Selected Macroeconomic Policies on Agriculture: 1984-1990. Agricultural Financial Review, 45, 81–91. Johnson, P. R., Grennes, T., & Thursby, M. (1977). Devaluation, Foreign Trade Control, and Domestic Wheat Prices. American Journal of Agricultural Economics, 59(4), 619–627. doi:10.2307/1239389 Khalafalla, K. Y., & Webb, A. J. (2001). Export-led Growth and Structural Change: Evidence from Malaysia. Applied Economics, 33(13), 1703–1715. doi:10.1080/00036840010015066 Mellor, J. W. (1966). The Economics of Agricultural Development. New York: Cornell University Press. Oshikoya, W. T., & Hussain, M. N. (2002). Infrastructure for Economic Development in Africa. In J. B. de Macedo & O. Kabbaj (Eds.), Regional Integration in Africa. OECD. Pindyck, R. S. (1998). Irreversible Investment, Capacity Choice, and the Value of the Firm. The American Economic Review, 78, 969–985. Pinstrup-Andersen, P. (2002). Food and Agricultural Policy for a Globalizing World: Preparing for the Future. American Journal of Agricultural Economics, 84(5), 1201–1214. doi:10.1111/1467-8276.00381 Pinstrup-Andersen, P., & Shimokawa, S. (2002). Rural Infrastructure and Agricultural development (pp. 185–203). Rethinking Infrastructure for Development.

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Rao, K. S. C., & Dhar, B. (2011). India’s FDI Inflows- Trend and Concepts. Working Paper No. 01. Institute for Studies in Industrial Development. Razin, O., & Collins, S. M. (1997). Real Exchange Rate Misalignments and Growth. In The Economics of Globalization: Policy Perspectives from Public Economics. Cambridge, UK: Cambridge University Press. RBI handbook data for GDP growth, export and total public expenditure on agriculture. (n.d.). Retrieved from https://rbi.org.in/Scripts/AnnualPublications.aspx?head=Handbook%20of%20Statistics%20on%20 Indian%20Economy Schultz, T. W. (1964). Transforming Traditional Agriculture. New Haven, CT: Yale University Press. Sinha, M., & Sengupta, P. P. (2016). Post Reform Trends in India’s Foreign Exchange Rate: Testing the Role of Agricultural Exports. Presented at National Symposium on Statistics for Sustainable Agricultural Development, Kolkata, India. Tripathi, A., & Prasad, A. R. (2008). An Overview of Agrarian Economy in India: Then Performance and Determinant. Retrieved from http://blogs.wsj.com/indiarealtime/2013/08/26/where-are-the-onions/ Zee News. (2015). Exclusive Union Budget. Available at: http://zeenews.india.com/exclusive/budget2015-the-need-for-an-overhaul-in-indian-agriculture-sector_1541831.html

KEY TERMS AND DEFINITIONS Agrarian Reform: Agrarian reform is government-initiated or government-backed redistribution of agricultural land. Agricultural Development: Agricultural development includes providing assistance, employing latest techniques, controlling pests and facilitating diversity to the crop producers with the help of various agricultural resources. Agriculture: Agriculture is the cultivation of plants and animals for food, fiber, bio fuel, medicine and other products which are used to sustain and enhance human life. Econometric Model: Econometric models are based on statistical models used in econometrics which specifies the statistical relationship to hold among the various economic quantities pertaining to a particular economic phenomenon under study. Economic Development: Economic development is the efforts that seek to improve the economic well-being and improve quality of life for a community by creating jobs and supporting or growing incomes and the tax base. Implementation: The process of execution of a decision or plan into effect. Infrastructure Development: For economic development and prosperity of a country, infrastructure development is essential. Infrastructure includes the basic physical systems of a nation communication, transportation, sewage, water and electric systems etc.

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 Importance of Sustainable Rural Development Through Agrarian Reforms

Policy: A course or principle of action adopted or proposed by an individual or organization. Public Expenditure: When spending is made by the government of a country based on collective needs and wants such as pension, provision, infrastructure, etc. Rural Development: Rural development is the process of improving the quality of life and economic well-being of people living in sparsely populated areas. Social Mobilization: Social mobilization is the primary step of community development for awareness and to organize and initiate action for their recovery with their own initiative and creativity to protect from disasters etc.

This research was previously published in Social, Health, and Environmental Infrastructures for Economic Growth edited by Ramesh Chandra Das, pages 290-306, copyright year 2017 by Business Science Reference (an imprint of IGI Global).

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Chapter 53

Mitigation of Climate Change Impacts Through Treatment and Management of Low Quality Water for Irrigation in Pakistan Ghulam Murtaza University of Agriculture Faisalabad, Pakistan

Muhammad Zia-ur-Rehman University of Agriculture Faisalabad, Pakistan

Muhammad Saqib University of Agriculture Faisalabad, Pakistan

Muhammad Naveed University of Agriculture Faisalabad, Pakistan

Saifullah University of Dammam, Saudi Arabia

Abdul Ghafoor University of Agriculture Faisalabad, Pakistan

ABSTRACT The Indus Plains of Pakistan are situated in arid to semi-arid climate where monsoon rains are erratic and mostly fall in the months of July and August. These rains are not only insufficient to grow even a single crop without artificial irrigation but also cause flood havoc very frequently that is associated with the climate change. The Indus river transports water for agriculture, industry and domestic usage within the basin and downstream. The Indus Basin is among the few basins severely affected by global warming and resulting climate change. The alteration in temporal and spatial patterns of rainfall has resulted in unexpected drought and floods. About 70 to 80% of total river flows occur in summer season due to snow melt and monsoonal rainfalls. Lack of storage reservoirs has decreased the ability to regulate flood water as well as its potential use during the drought season along with cheap hydro-electricity generation. The sedimentation in the system has limited the storage capacity of the existing three reservoirs by 28%. Consequently carry over capacity of these storage structures is only 30 days compared to 120 to 220 days in India and 900 days in Colorado Basin. Pakistan is facing shortage of good quality water

DOI: 10.4018/978-1-5225-9621-9.ch053

Copyright © 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Mitigation of Climate Change Impacts Through Treatment and Management of Low Quality Water

due to competition among agricultural and non-agricultural sectors, this scenario will continue rather will further aggravate in future. According to the climate change scenario, the warming is reflected in the river-flow data of Pakistan, especially during the past 2-3 decades. To bridge the gap between fresh water availability and demand, ground water is being pumped to meet the irrigation requirements of crops. The pumped ground water (70-80%) is brackish and could become a sustainability issue in the long run. The prolonged agricultural uses of such water will deteriorate soils, crops and human living environments. Water quality parameters usually considered include electrical conductivity (EC) for total soluble salts, and sodium adsorption ratio (SAR) and residual sodium carbonate (RSC) reflect the sodicity hazards. In order to limit or even to eliminate adverse effects of such waters, certain treatment and/or management options are considered as important pre-requisites. For bringing down high concentration of total soluble salts, dilution with good quality water is the doable practice. To decrease high SAR of irrigation water, a source of calcium is needed, dilution (with good quality water) will decrease SAR by the square root times of the dilution factor, while use of acids will be cost-intensive rather may adversely impact the soil health. For high RSC, dilution with low CO32-+HCO3- water will serve the purpose, addition of Ca-salts will raise Ca2++Mg2+ to bring a decrease in water RSC, while acids will neutralize CO32-+HCO3- to lower water RSC. Gypsum is the most economical and safe amendment while acids could also decrease RSC but at higher relative cost. City wastewater and seed priming in aerated gypsum solution is also presented. Such practices at small and/or large scale surely will help a lot to sustain the food security and the environment in the days to come where climate change has to be experienced round the world. Therefore, a well-coordinated program is necessary to create awareness among different sections of the society including the policy makers, general public, organizations, industrialists and farmers.

INTRODUCTION The Indus Plains of Pakistan are situated in arid to semi-arid climate zones where rains during monsoon are erratic and mostly fall during the months of July to September. These rains cause flood havoc very frequently that is associated with the climate change; floods during the years of 2010, 2011 and 2014 are very good examples to such climate change impacts those resulted in hundreds of human and animal deaths as well as caused billion dollar loss to infrastructures, soil quality and crops. The Indus river transports water for agriculture, industry and domestic usage within the basin and downstream. About 70 to 80% of total river flows occur in summer due to snow melt and monsoonal rains. The effect of climate change is not limited to water availability only but it also affects crop yields and thus the food security and worsens the human living environments. The increasing soil salinity might cause additional harm in future, if less annual rainfall and higher temperatures prevailed at the current rate in future due to climate change. Due to reduction in annual rainfall, sufficient leaching of salts will not be achieved and higher temperatures will further aggravate the salt stress in regions already threatened by soil salinity (Sommer et al., 2013). The availability of water in Pakistan has decreased from 5300 m3/ year/person in 1950’s to 1066 m3/person/year in 2010 and it is estimated to be < 850 m3 per capita by the year 2025 (WAPDA, 2011). The World Bank has included Pakistan in the list of 17 countries predicted to encounter severe water shortages by 2025. There is immense need and scope to develop additional surface water storage for drought periods since a plenty of river water is discharging into the Arabian Sea, ≈ about 34 to 37 million acre foot (MAF) water is discharged into the sea. Such policy issues have

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to be decided by overlooking the political interests and giving priority to national interests by all the sections of society including politicians, policy makers and techno-crates. An additional option is ground water (unfortunately poor quality) that may supplement growing irrigation needs because of increased cropping intensity and competition for fresh water by non–agricultural sectors. At present, > 1.07 × 106 tube wells are pumping 9.05 × 106 ha–m ground water in Pakistan (Federal Bureau of Statistics, 2011-12), of which≈ 70-80% is unfit for agriculture because of high EC, SAR and/or RSC (Ghafoor et al., 2004). The irrigation with poor quality water may cause soil salinity/ sodicity, poor infiltration, hard setting of soils, specific ion toxicity in plants; all combined to adversely affect the growth and economic yields of crops along with human living environments. Further to this, sub-soil drying due to draw-down of water table could be an important future concern (Wichelns and Qadir, 2015). The ground water, storm water during floods and raw city sewage (from industry-mix) may pose serious hazards because of high EC (≥1.0 dS m-1), SAR (≥10.0), RSC (≥2.5 mmolc L-1), heavy metals, high Mg to Ca ratio, diseases, pathogens, detergents, azo-dyes and pesticide residues (Murtaza et al., 2010; Qadir et al., 2010). However, management or treatment depends upon many factors like crop type, plant growth stage, physical/chemical properties of soils, and reactions between water and soil solids, climatic factors, farmers’ skills, drainage water quality, requirements of consumers and socio-economic conditions and acceptable decrease in produce yield as well as quality. Recently United Nations Climate Change Conference (COP21, 2015) was held in Paris ended up with the conclusions to decrease global greenhouse gases (GHGs) emission to zero level and to limit the average rise in global temperature to 2 degrees Celsius. To follow the goals and accomplish them saline water can be used for irrigation to bring more lands under cultivation. Bio saline agriculture can help in improving salt-affected soils such as cultivation of salt tolerant crops and growing of forest trees in barren lands instead of leaving them fallow. This would help in sequestering environmental CO2 and alleviates global temperature rise. Deserts can also be made productive by installing solar energy panels. Recently, Morocco has floated a tender for 400 MW solar power project (COP21, 2015). In Pakistan a solar power project has also been installed in Bahawalpur with a capacity of 100 MW. This chapter describes efforts related to brackish water treatment and/or management that must be critically examined to learn lessons and shape the future for safe and sustainable use of brackish water. This chapter also highlights the economic feasibility of using gypsum, acids and/or acid formers and like amendments for brackish water treatment with least disturbing the biosphere equilibrium.

Brackish Water Brackish water is a general term for water having high EC, SAR and/or RSC. Canal water supply has become short to cope with the crop requirements because of prolonged and un-expected droughts mostly in response to climate change, silting of water reservoirs, competition between agricultural and non-agricultural demands and increased cropping intensity. As a result, pumping of ground water has increased tremendously over the years. Due to canal water shortage, number of tube wells is increasing at an alarming rate, i.e. 3000 in 1950 to > a million in 2014. Unfortunately, the pumped ground water is unsuitable for irrigation, since ≈ 70-75% tube wells were and are pumping brackish water (high EC, SAR and/or RSC) during the period of 1995 to 2014 (personal communication from Directorate of Soil Fertility Res. Inst., Lahore). Continued use of such waters for irrigation is one of the major reasons to induce soil salination/sodication along with hard setting, deterioration in produce quality/shelf life, and 1183

 Mitigation of Climate Change Impacts Through Treatment and Management of Low Quality Water

creating environment problems (Ghafoor et al., 2001a). In addition, sub-soil drying due to draw-down of water table is another future concern and must be addressed immediately and wisely. Indiscriminate pumping of ground water is also deteriorating the ground water quality, particularly under the decreased of ground water recharge due to lining of water courses, canals and increasing water use efficiency leading less leaching fraction; a minimum leaching fraction is the key to arrest the salt accumulation in the root zone under arid and semi-arid climates even with canal water irrigation. It is the rule of thumb that as one goes deeper into subsoil and away from rivers, ground water quality becomes poorer and poorer. The shortage of quality irrigation water in Pakistan has attracted the international interest. Some private organizations are trying to market their products for the treatment of brackish water without proper testing to prove validity/usefulness under local agro-climatic conditions as explained in a later section.

Water Quality Criteria for Irrigation Numerous water quality guidelines have been proposed by various scientists in Pakistan (Hussain, 1978; Sheikh, 1989; Yunus, 1977) and India (Gupta, 1990) but lack support of experimental data. The guidelines developed by the US Salinity Lab. Staff (1954) and Ayers and Westcot (1985) have been most commonly followed which more accurately predict the effect of water quality on soils and crops. Extensive experimentation is required to develop water quality guidelines keeping in view the physical and chemical properties of soils and agro-climatic conditions of Pakistan. Depending upon the degree of restriction, the three poor quality water classes (saline, saline-sodic and sodic) could be further grouped each into three homogenous subgroups (Table 1), since each subgroup needs specific management practice(s). This classification also helps to serve the purpose at regional levels.

Table 1. Grouping ground water for quality parameters Water Quality E. Good

ECiw (dS m-1)

SARiw

RSC (mmolc L-)

< 1. 5

1. The use of such water for irrigation and reclamation may increase exchangeable Mg2+ in soils (Karajeh et al., 2004). Exchangeable Mg2+ at excessively high levels may result in soil degradation because of its adverse effects on physical properties of soils. According to McNeal et al. (1968) soils having mixed Na+–Mg2+ will have lower hydraulic conductivity than did soils with Na+–Ca2+ under similar conditions. This could be due to the fact that t the hydration energy as well as hydration radius of Mg2+ are greater than that of Ca2+ (Strawn et al., 2015). Thus soil surface retains more water than where exchangeable Ca2+ is present, causing weakening of forces that stabilize soil structure. This, in turn, decreases the amount of energy needed to break down soil aggregates (Oster & Jayawardane, 1998). Further to this, at low levels of exchangeable sodium percentage (ESP), Mg2+ also exaggerates the effects of Na+ on clay dispersion and hydraulic conductivity (Qadir & Schubert, 2002). Oster (2001) reported that when Mg2+ proportion compared to Ca2+ increases than exchangeable Mg2+ resulted in greater dispersion thus causing a larger decline in hydraulic conductivity. Similarly, at a given ESP, replacing the exchangeable Ca2+ with Mg2+ decreased the infiltration rate of soils (Rengasamy et al., 1986). A recent review (dating back to the 1930s) by Smith et al. (2015) supports the general conclusion that the relative order of deleterious effects on soil hydraulic properties of the four common cations in soils was in the order of Na+ > K+ > Mg2+ > Ca2+. It was concluded that Mg2+ was significantly less effective than Ca2+ in improving soil structure and water permeability. The achieved results from the above stated brackish water quality improvements, several other untested technologies by some vested interest people are claiming. These technologies include Sulphurous Acid Generator (SAG) by Sweet Water Solution of USA, EM/BM technology from Japan, RISTECH Technology from UK, and Electro-Magnetic Membrane technology from Germany. Novel claims of these technologies are to desalinate the brackish water, convert sodium into nitrogen, change in soil texture over a period of 2-3 years, and bacteria in these recipes eat salts as well as sodium present in water or soils. Unfortunately, none of these have been demonstrated at any university or research farm. In spite of this fact, they are be-fooling the farmers at a very large scale to make money. Government should give attention immediately to stop their business and save hard earnings of farmers since farmers are drowning and try to catch a straw to save themselves.

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ECiw to SARiw Ratio Low ECiw or ECe at a given SARiw or SARss tends to decrease soil infiltration through decreasing the thickness of Diffused Double Layer (DDL) (Ayers & Westcott, 1985; Ghafoor et al., 2004). Water having low SARiw and high ECiw was found better for normal and salt-affected soils because of favorable effects of electrolytes on soil infiltration and hydraulic conductivity, while reverse was true for high SARiw with low ECiw. Therefore at start of reclamation of saline-sodic or sodic soils, waters having high EC: SAR ratios were found equally useful (Ghafoor et al., 2001b) but has to switch to better quality water (low ECiw, low SARiw) with the advancement of soil reclamation (Murtaza et al., 2009). It is important to consider this quality parameter for sustainable management of brackish water in order to maintain a leaching fraction as well as if used for reclaiming salt-affected soils. Some studies were conducted by authors in the Fourth Drainage Project Area (FDPA), Faisalabad using brackish water, wherein it was concluded that such waters can be used safely at the early stages of reclamation (Ghafoor et al., 2008, 2011, 2012; Murtaza et al., 2009). However, presently this parameter is not given very much importance and must be considered for future irrigation water quality guidelines.

PERMEABILITY PROBLEMS Permeability refers to the percolation of infiltrated water through soils. Doneen (1975) suggested a formula to predict the infiltration rate which was designated as Permeability Index (PI). PI = [100 {Na+ + (HCO3-)1/2}/{Na+ + Ca2+ + Mg2+}]

(6)

where ionic concentrations in water are in mmolc L-1. This relationship is quite useful in predicting the effect of water on permeability of soil and also this does not need extra determination in routine water analysis.

INFILTRATION PROBLEM The rate at which water enters into soils is referred to as the rate of infiltration. An infiltration rate (IR) as low as 3 mm h-1 is considered low while a rate > 12 mm h-1 is high (US Salinity Lab. Staff, 1954). This parameter is affected by many factors other than water quality, like soil physical characteristics (soil texture, type of clay minerals) and chemical characteristics (exchangeable cations). The IR generally increases with increasing salinity (EC) and decreases with either decreasing EC or increasing Na+ concentration relative to Ca2+ and Mg2+, i.e. SAR (Murtaza et al., 2006). Therefore, EC and SAR must be considered for a proper evaluation of the ultimate effect of water on its infiltration rate.

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SPECIFIC ION EFFECTS It is the concentration of an ion relative to total concentration which when exceeds beyond a certain limit cause specific ion effect. If Na+ concentration is > 60% of the total cations, water becomes hazardous for irrigation because it induces K+ and/or Ca2+ deficiency and scorching of leaf tips in addition to deteriorating physical and chemical properties of soils. It is worth mentioning that deterioration in physical properties of soils starts much earlier than specific ion effects of Na+ on plant growth. The concentrations of Cl- and SO42- strongly correlate with EC of irrigation water (ECiw). About 5-10 mmolc L-1 Cl- becomes harmful to sensitive plants. However, relatively wide range of sensitivity to Na+ and Cl- effects among different plants exists which is more pronounced under sprinkler irrigation. Woody plants are more sensitive to Cl- than annual crops. If Cl-: SO42- ratio becomes greater than 1: 3, the water is considered more hazardous than that where this ratio is 3: 1. The SO42- ions are considered more harmful for roots and disturb internal metabolism of plants. These ions induce precipitation of Ca2+ as CaSO4 which causes a rise in soil pH and SAR, and thus make the soil environment unfavorable for nutrient availability to plants. Generally waters having high EC under arid to semi-arid conditions may contain Mg2+> Ca2+. Magnesium >50% among Ca2+ + Mg2+ adversely affects soils and plants. Increasing Mg2+ over Ca2+ in irrigation water increased the sodicity in soils at a given SARiw and ECiw and its effects were more pronounced at higher than that at lower SARiw. Release of Ca2+ from the in-situ soil weathering and native lime increased with increasing Mg2+: Ca2+ ratio in irrigation water. With an increase in Mg2+: Ca2+ ratio and SAR of soil and/or irrigation water, the degree of dispersion increased significantly. The Ca2+: Mg2+ ratio ≥ 1.0 is considered safe for most of the crops and soils. Generally, grasses are more sensitive to Mg2+ than other plants since former crops acquire high Mg2+ in living tissues. From previous studies, it was also noted that high Mg2+ water is relatively more harmful to affect rice yield as compared to wheat and cotton crops (Ghafoor et al., 1997). This aspect needs further research since a lot of ground waters contain Mg2+ higher than Ca2+ under arid regions of the world. However, the productivity of Mg2+ dominated soils can be improved by increasing levels of Ca2+ on the cation exchange complex to counter the adverse impacts of Mg2+. This could be accomplished by applying sufficient amount of Ca2+ to soils (Vyshpolsky et al., 2008).

SEED PRIMING Seed priming is a process where seed is hydrated for specified time periods under controlled conditions followed by re-drying that allows all the pre-germination metabolic activities but prevents radicle protrusion (Khan et al., 1992). Poor stand establishment is a widespread constraint for crop production in salt-affected soils (Harris et al., 1999; Saifullah et al., 2002). Presence of excessive soluble salts and/ or exchangeable Na+ may adversely impact the physical, chemical and nutritional properties of soil that in turn may lead to lower plant population (Qadir et al., 2014). Moreover, such plants after emergence often grow slowly and are highly susceptible to stresses such as drought, salinity, pests and diseases (Francois et al., 1986). Under such conditions farmers may choose to re-sow, although this entails severe yield penalties, increased labor and financial losses. Pre-sowing seed treatments with salts, nutrients or hormones have been advocated to enhance seed germination in saline medium (Afzal et al., 2013; Ashraf & Foolad, 2005). However, it fails in saline-sodic or sodic soils due to poor physical condition. In these soils, seeds fail to emerge out of soil due to surface crust. Gypsum helps to improve soil physical and 1190

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chemical properties. In this backdrop, a three years project was initiated on salt-affected soil to monitor the effect of combined application of seed priming and soil-applied gypsum on growth and yield of wheat and rice crops using brackish water for irrigation. The results indicated that combined application of gypsum and seed treatment with saturated solution of gypsum was the best treatment in terms of soil health improvement, yield enhancement and economic output. Priming enhanced the seed germination through protein synthesis, repair of nucleic acid and membranes (Hameed et al., 2010; Fujikura & Karssen, 1995). In a recent study (Saifullah, 2012), it was concluded that sowing of wheat seed soaked for 24 hours in aerated gypsum saturated solution + gypsum at 50% of soil gypsum requirement helped better crop stand and ultimately the economic yields.

WASTEWATER In developing countries including Pakistan, it is a common practice to discharge domestic and industrial effluent (premixed due to common water carrying channels) directly to a sewer system, a natural drain or water body, a nearby field or an internal septic tank. Unfortunately, this wastewater is not properly treated because of non-functioning and/or availability treatment plants. The sewage in drains is mostly have high EC, SAR, RSC and elevated levels of several metals, organics and associated pathogens that warrant site-specific management strategies. The wastewater used for irrigation is becoming an attractive commodity for farmers mainly because of its nutrient contents and reliability of supply (Ensink et al., 2004; Murtaza et al., 2010). It can have positive impacts on agriculture and monthly income despite producing adverse effects on soil physical and chemical properties in addition to contamination of human food chain and related health risks (Hanjra et al., 2012; Qadir et al., 2010; Vincent, 2014). Recent estimates depict (Table 2) that total volume of wastewater generated in Pakistan is about 962,335 million gallons (4.369 × 109 m3/yr) out of which 674,009 million gallons (3.060 × 109 m3/yr; and 5.54 × 109 m3/ yr for the year 2011) are shared by municipalities and 288,326 million gallons (1.309 × 109 m3/yr) from industries. As with other developing countries, in Pakistan, wastewater is not subjected to any treatment and none of the cities have any biological treatment process except Islamabad and Karachi, and even these cities treat only a small proportion before disposal (Table 3). Estimates suggest that the amount of treated wastewater is not > 1% (Murtaza & Zia, 2012). The treated wastewater generally flows into open drains, and there are no provisions for its reuse for agriculture. Table 2. Sector-wise wastewater production in Pakistan in the year Sr. No. 1

Volume

Source Industry

10 m y 6

395

3

Percent (%)

-1

6

2

Commercial

266

5

3

Urban residential

1,628

25

4

Rural residential

3,059

48

5

Agriculture

1,036

16

Total

6,414

100

Source: Murtaza & Zia (2012)

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Table 3. Wastewater produced annually from major cities of Pakistan City   Lahore

Total Wastewater Produced (106 m3/y)

Urban Population (1998 Census) 5,143,495

287

% of Total 12.5

% of Treated 0.01

Receiving Water Body River Ravi, irrigation canals, vegetable farms

  Faisalabad

2,008,861

129

5.6

25.6

River Ravi, River Chenab and vegetable farms

  Gujranwala

1,132,509

71

3.1

-

SCARP drains, vegetable farms

  Rawalpindi

1,409768

40

1.8

-

River Soan and vegetable farms

  Sheikhupura

870,110

15

0.7

-

SCARP drains

  Multan

1,197,384

66

2.9

-

River Chenab, irrigation canals and farms

  Sialkot

713,552

19

0.8

-

River Ravi, irrigation canals and farms

  Karachi

9,339,023

604

26.3

15.9

Arabian Sea

  Hyderabad

1,166,894

51

2.2

34.0

River Indus, irrigation canals and SCARP drains

  Peshawar

982,816

52

2.3

36.2

Kabul River

  Other

19,475,588

967

41.8

0.7

-

Source: Master Plan for Urban Wastewater (Municipal and Industrial) Treatment Facilities in Pakistan. Final Report, Lahore: Engineering, Planning and Management Consultants, 2002.

It is highly recommended that the wastewater should be treated at source. Different chemical and plant based technologies are available for the remediation of wastewater (Murtaza et al., 2014). One opportunity to address these concerns is the use of low cost agrowaste adsorbents for the treatment of urban wastewater for irrigation of crops, trees, forests and greenbelts (Abdolali et al., 2013). There seems week national policy and implementation on sustainable use of wastewater in developing countries including Pakistan. The problems of wastewater disposal emerge from distortions due to economy-wide policies, failure of targeted environmental policies and institutional failures. Therefore, a well-coordinated program is necessary to create awareness among different sections of the society including the policy makers, general public, organizations, industrialists and farmers to save future of nations.

CONCLUSION AND RECOMMENDATIONS It is important to consider and adopt preventive measures immediately to avoid the disaster of soil salination and sodication in response to poor quality tube well water irrigation. The deterioration of soils adversely affects the ambient environments for all the living organisms including human beings. Thus, it seems essential and wise to reclaim the saline and/or sodic soils and adopt measures to limit the adverse

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effects of hazards associated with low quality irrigation waters in favor of crops/plants growth in order to keep the environment clean. The best economical solution to high SAR and/or RSC waters is to soil-apply gypsum along with farm manure or green manure before each crop, considering the delta of water of a crop and gravity of SAR and/or RSC problem. Blended/mixed use of canal and brackish waters is not possible under our conditions since canal water supplies are not at the disposal of farmers. The cyclic (alternate irrigation, or one crop with canal and next with brackish water) are already in practice (Oster & Grattan, 2002; Rhoades et al., 1992). The farmers should try to avoid irrigation with brackish water at critical crop growth stages. They should also try to use good water on good soils and poor quality water on poor soils. There is an immense need to initiate the tube well water analyses for appropriate and site-specific advice by soil and water experts, and simultaneously it must be made mandatory and legal for tube well owners to get the water analyzed and act upon the advice. Assuming 70% pumped ground water hazardous which require addition of gypsum at 4 mmolc L-1 of irrigation water, 400 kg for each acre-foot and 15.6 million tons gypsum for 39 MAF tube well water annually will be required, i.e. 234 million tons quality gypsum will be essential to soil-apply in order to mitigate the adverse effects of high SAR/RSC tube well water. For a door-step supply of this much gypsum has to be ensured on credit for sustainability of irrigated agriculture and safe environment since the salt-stress land and tube well owners might not be in a position to purchase gypsum on cash payment. The potential of virtual use of water could be exploited at regional/provincial/national levels. The idea of virtual use of water compares the amount of water embodied in a crop that can be purchased at regional/provincial/international levels with the amount of water that should be required to produce that crop natively. For example, transferring every kilogram of wheat into water stress area means to transfer about 1000 L of virtual water at a much less price than the price of the same quantity of water from the native water resources in the area itself (Qadir et al., 2003). There is significant loss in storage capacity of water reservoirs which is increasing gradually and this loss will become about 33% of the designed capacity by the year 2020. It is strongly recommended that additional storage facility is developed, and the silt load of in-coming water into existing dams is decreased through controlling/ promoting vegetation with or without the help of engineering structures in the catchment areas. Seed priming in saturated gypsum solution for 4-8 hours did help early and enhanced germination of cereal crops which latter improved crop stand for better yield since as plants grow older, their performance in salt-stress environment (saline and/or sodic soils or irrigation waters) become promising. The city wastewater poses threats of heavy metals. Under such situations, metals could be made less available with the soil-applied gypsum, mono-ammonium phosphate, DAP or some other economical Ca-salts. The metals could also be removed by enhancing their availability through soil-application of acids, acid formers and EDTA salts with crops not directly consumed by human beings. However, growing leafy vegetables with sewage water must be banned. Another feasible practice for brackish water irrigation is to cultivate salt-tolerant crops requiring less irrigation, particularly to decrease the input of chemicals into soils and ground water contamination. This practice will also help decrease the problem of waterlogging. The breeders should come forward and conduct research in the fields of genomics, proteomics, biotechnology, and nanotechnology to breed salt-resistant and drought-tolerant crops (Roy et al., 2014; Seabra et al., 2014).

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The allocation of irrigation water is not uniform in various provinces of Pakistan. The water allocation is more in Sindh compared to Punjab. Moreover, water allocation is higher in Southern Punjab as compared to central and upper Punjab. Improvement in water allocation is required to achieve sustainable irrigation and to avoid salinity and waterlogging.

POLICIES To tackle the water quality problems some policies are suggested 1) give priority to increasing irrigation efficiencies, essentially with allowance for salinity/ sodicity control through effective leaching of in-coming salts, 2) move towards a demand based irrigation water supply, 3) promote water use associations (WUA) and thereafter Federation of WUA, 4) maintain the existing drainage infrastructure with site-specific emphasis on new projects, 5) strengthen the advisory service to farmers and training to extension staff.

MEASURES Some specific measures for the safe use of brackish water on sustainable basis are 1) take incremental but specific measures towards volumetric consumption as the ultimate basis for water charges, 2) undertake studies in community management of a few distributaries on a pilot scale, 3) address problems of water table draw-down by holistic approaches, encompassing both the demand management and methods to increase water recharge, 4) promote farmer education and extension activities as well as in-service training of staff, 5) review funding, goal should be 60:40 ratio for research: administration, 6) in kind credit facility for gypsum in time and space, particularly to small and resource poor farmers, 7) make it legal for farmers to get their tube well water analyzed, mobile teams of experts be organized to collect, analyze and advice solutions for tube well water quality.

REFERENCES Abdolali, A., Ngo, H. H., Guo, W. S., Lee, D. J., Tung, K. L., & Wang, X. C. (2014). Development and evaluation of a new multi-metal binding biosorbent. Bioresource Technology, 160, 98–106. doi:10.1016/j. biortech.2013.12.038 PMID:24405652 Afzal, I., Basra, S. M. A., Cheema, M. A., Farooq, M., Jafar, M. Z., Shahid, M., & Yasmeen, A. (2013). Seed priming: A shotgun approach for alleviation of salt stress in wheat. International Journal of Agriculture & Biology, 15, 1199–1203. Ahmad, N. C., & Chaudhry, M. R. (1997). Review of research on reclamation of salt-affected soils in Pakistan (Publication No. 175). Lahore, Pakistan: International Waterlogging And Salinity Research Institute, Water And Power Development Authority. Ashraf, M., & Foolad, M. R. (2005). Pre-sowing seed treatment-a shotgun approach to improve germination growth and crop yield under saline and none-saline conditions. Advances in Agronomy, 88, 223–271. doi:10.1016/S0065-2113(05)88006-X

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Ayers, R. S., & Westcott, D. W. (1985). Water quality for agriculture. Irrigation and Drainage Paper 29. Rome, Italy: Food and Agriculture Organization of the United Nations. COP21 (Conference of Parties 21). (2015). United Nations Climate Change Conference. Retrieved from http://www.scoop.it/t/cop21news Doneen, L. D. (1975). Water quality for irrigated agriculture. In A. Poljakoff-Mayber & J. Gale (Eds.), Plants in saline environments (pp. 56–79). Springer-Verlag. doi:10.1007/978-3-642-80929-3_5 Eaton, F. M. (1950). Significance of carbonate in irrigation waters. Soil Science, 69(2), 123–133. doi:10.1097/00010694-195002000-00004 Ensink, J. H. J., Simmons, R. W., & van der Hoek, W. (2004). Wastewater use in Pakistan: The cases of Haroonabad and Faisalabad. In C. A. Scott, N. I. Faruqui, & L. Raschid-sally (Eds.), Wastewater use in irrigated agriculture (pp. 91–99). Wallingford, UK: CAB International. doi:10.1079/9780851998237.0091 Federal Bureau of Statistics. (2011–12). Pakistan statistics year book, Statistics Division. Islamabad, Pakistan: Planning Commission Government of Pakistan. Francois, L. E., Maas, E. V., Donovan, T. J., & Youngs, V. L. (1986). Effect of salinity on grain yield and quality, vegetative growth, and germination of semi-dwarf and durum wheat. Agronomy Journal, 78(6), 1053–1058. doi:10.2134/agronj1986.00021962007800060023x Fujikura, Y., & Karssen, C. M. (1995). Molecular studies on osmoprimed seeds of cauliflower: A partial amino acid sequence of a vigour- related protein and osmopriming-enhanced expression of putative aspartic protease. Seed Science Research, 5(03), 177–181. doi:10.1017/S0960258500002804 Ghafoor, A., Gill, M. A., Hassan, A., Murtaza, G., & Qadir, M. (2001a). Gypsum: An economical amendment for amelioration of saline-sodic waters and soils, and for improving crop yields. International Journal of Agriculture & Biology, 3(3), 266–275. Ghafoor, A., Murtaza, G., Ahmad, B., & Boers, Th. M. (2008). Evaluation of amelioration treatments and economic aspects of using saline-sodic water for rice and wheat production on salt-affected soils under arid land conditions. Irrigation and Drainage, 57(4), 424–434. doi:10.1002/ird.377 Ghafoor, A., Murtaza, G., Maann, A. A., Qadir, M., & Ahmad, B. (2011). Treatments and economic aspects of growing rice and wheat crops during reclamation of tile drained saline-sodic soils using brackish waters. Irrigation and Drainage, 60(3), 418–426. doi:10.1002/ird.577 Ghafoor, A., Murtaza, G., Rehman, M. Z., Saifullah, & Sabir, M. (2012). Reclamation and salt leaching efficiency of treatments for tile drained saline-sodic soil using marginal quality water for irrigating rice and wheat crops. Land Degradation & Development, 23(1), 1–9. doi:10.1002/ldr.1033 Ghafoor, A., Nadeem, S. M., Hassan, A., & Sadiq, M. (2001b). Reclamation response of two different textured saline-sodic soils to ECiw to SARiw ratios. Pakistan Journal of Soil Science, 19, 92–99. Ghafoor, A., Qadir, M., & Murtaza, G. (1997). Potential for reusing low quality drainage water for soil amelioration and crop production. In Proceedings of the International Symposium on Water for the 21st Century: Demand, Supply, Development and Socio-Environmental Issues (pp. 411-20). Lahore, Pakistan: Centre of Excellence in Water Resources Engineering, University of Engineering and Technology.

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Ghafoor, A., Qadir, M., & Murtaza, G. (2002). Agriculture in the Indus Plains: Sustainability of land and water resources. International Journal of Agriculture & Biology, 4(3), 429–437. Ghafoor, A., Qadir, M., & Murtaza, G. (2004). Salt-affected soils: Principles of management. Lahore, Pakistan: Allied Book Centre. Gupta, I. C. (1990). Use of saline water in agriculture. Bombay, India. Oxford, UK: IBH Publishing House Co, Pvt. Ltd. Hameed, A., Afzal, I., & Iqbal, N. (2010). Seed priming and salinity induced variations in wheat (Triticum aestivum L.) leaf protein profile. Seed Science & Technology, 38(1), 236–241. doi:10.15258st.2010.38.1.25 Hanjra, M. A., Blackwell, J., Carr, G., Zhang, F., & Jackson, T. M. (2012). Wastewater irrigation and environmental health: Implications for water governance and public policy. International Journal of Hygiene and Environmental Health, 215(3), 255–269. doi:10.1016/j.ijheh.2011.10.003 PMID:22093903 Harris, D., Joshi, A., Khan, P. A., Gothkar, P., & Sodhi, P. S. (1999). On-farm seed priming in semiarid agriculture: Development and evaluation in maize, rice and chickpea in India using participatory methods. Experimental Agriculture, 35(1), 15–29. doi:10.1017/S0014479799001027 Hussain, G. (1978). Determination of irrigation water quality standards. (Unpublished doctoral dissertation). Colorado State University. Karajeh, F., Suleimenov, M., Karimov, A., Vyshpolsky, F., Mukhamedjanov, Kh., Bekbaev, U. (2004). Technology of irrigation, water saving and improving soil fertility in Arys Turkestan canal command zone. Kazakh Research Institute of Water Management: Taraz, 18. (in Russian). Khan, A. A., Maguire, J. D., Abawi, G. S., & Illas, S. (1992). Matriconditioning of vegetable seed to improve stand establishment in early field planting. Journal of the American Society for Horticultural Science, 117, 41–47. McNeal, B. L., Layfield, D. A., Norvell, W. A., & Rhoades, J. D. (1968). Factors influencing hydraulic conductivity of soils in the presence of mixed-salt solutions. Soil Science Society of America Proceedings, 32(2), 187–190. doi:10.2136ssaj1968.03615995003200020012x Murtaza, G., Ghafoor, A., Owens, G., Qadir, M., & Kahlon, U. Z. (2009). Environmental and economic benefits of saline-sodic soil reclamation using low-quality water and soil amendments in conjunction with a rice-wheat cropping system. Journal Agronomy & Crop Science, 195(2), 124–136. doi:10.1111/j.1439037X.2008.00350.x Murtaza, G., Ghafoor, A., & Qadir, M. (2006). Irrigation and soil management strategies for using salinesodic water in a cotton-wheat rotation. Agricultural Water Management, 81(1-2), 98–114. doi:10.1016/j. agwat.2005.03.003 Murtaza, G., Ghafoor, A., Qadir, M., Owens, G., Aziz, M. A., Zia, M. H., & Saifullah. (2010). Disposal and use of sewage on agricultural lands in Pakistan: A review. Pedosphere, 20(1), 23–34. doi:10.1016/ S1002-0160(09)60279-4

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Murtaza, G., Murtaza, B., Niazi, N. K., & Sabir, M. (2014). Soil contaminants: sources, effects and approaches for remediation. In Improvement of crops in the era of climatic changes (pp. 171–196). Springer Science, Business Media. doi:10.1007/978-1-4614-8824-8_7 Murtaza, G., & Zia, M. H. (2012). FAO Report - UNW-AIS. Individual’s capacity development on the safe use of wastewater in agriculture in Pakistan. Available at http://www.ais.unwater.org/ais/pluginfile. php/232/mod_page/content/124/pakistan_murtaza_finalc ountryreport2012.pdf Oster, J. D. (1994). Irrigation with poor quality water. Agricultural Water Management, 25(3), 271–297. doi:10.1016/0378-3774(94)90064-7 Oster, J. D. (2001). Magnesium effects on soil physical properties—Hydraulic conductivity and infiltration rate. SLPHYCHM. Available online at http://esce.ucr.edu/oster/SLPHYCb.html Oster, J. D., & Grattan, S. R. (2002). Drainage water reuse. Irrigation and Drainage Systems, 16(4), 297–310. doi:10.1023/A:1024859729505 Oster, J. D., & Jayawardane, N. S. (1998). Agricultural management of sodic soils. In M. E. Sumner & R. Naidu (Eds.), Sodic soil: Distribution, management and environmental consequences (pp. 126–147). New York: Oxford University Press. Qadir, M., Ghafoor, A., Boers, Th. M., & Murtaza, G. (2003). Agricultural water management in water starved countries: Challenges and opportunities. Agricultural Water Management, 62(3), 165–185. doi:10.1016/S0378-3774(03)00146-X Qadir, M., Quillérou, E., Nangia, V., Murtaza, G., Singh, M., Thomas, R. J., ... Noble, A. D. (2014). Economics of salt-induced land degradation and restoration. Natural Resources Forum, 38(4), 282–295. doi:10.1111/1477-8947.12054 Qadir, M., & Schubert, S. (2002). Degradation processes and nutrient constraints in sodic soils. Land Degradation & Development, 13(4), 275–294. doi:10.1002/ldr.504 Qadir, M., Wichelns, D., Raschid-Sally, L., McCornick, P. G., Drechsel, P., Bahri, A., & Minhas, P. S. (2010). The challenges of wastewater irrigation in developing countries. Agricultural Water Management, 97(4), 561–568. doi:10.1016/j.agwat.2008.11.004 Rengasamy, P., Greene, R. S. B., & Ford, G. W. (1986). Influence of magnesium on aggregate stability in sodic red-brown earths. Australian Journal of Soil Research, 24(2), 229–237. doi:10.1071/SR9860229 Rhoades, J. S., Kandiah, A., & Mashali, A. M. (1992). The use of saline waters for crop production. Irrigation and Drainage Paper 48. Rome, Italy: Food and Agriculture Organization of the United Nations. Roy, S. J., Negrão, S., & Tester, M. (2014). Salt resistant crop plants. Current Opinion in Biotechnology, 26, 115–124. doi:10.1016/j.copbio.2013.12.004 PMID:24679267 Saifullah, G. A., Murtaza, G., & Qadir, M. (2002). Brackish tube well water promotes growth of rice and wheat and reclamation of saline-sodic soils. Pakistan Journal of Soil Science, 21, 83–88.

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Saifullah. (2012). Enhancing crop productivity on salt-affected soils through combined use of soil applied gypsum and pre-sowing seed treatments. Final Technical Progress Report for Endowment Fund Secretariat (EFS) funded project (July 2008 – June 2011). Institute of Soil & Environmental Sciences, University of Agriculture. Seabra, A. B., Rai, M., & Durán, N. (2014). Nano carriers for nitric oxide delivery and its potential applications in plant physiological process: A mini review. Journal of Plant Biochemistry and Biotechnology, 23(1), 1–10. doi:10.100713562-013-0204-z Sheikh, I. A. (1989). Country report on problems of waterlogging and salinity in Pakistan. In Proceeding Information Seminar on Waterlogging and Salinity Research in Some Major Problem Countries (pp. 1-10).Lahore, Pakistan: International Waterlogging And Salinity Research Institute. Smith, C. J., Oster, J. D., & Sposito, G. (2015). Potassium and magnesium in irrigation water quality assessment. Agricultural Water Management, 157, 59–64. doi:10.1016/j.agwat.2014.09.003 Sommer, R., Glazirina, M., Yuldashev, T., Otarov, A., Ibraeva, M., Martynova, L., ... de Pauw, E. (2013). Impact of climate change on wheat pro-ductivity in Central Asia. Agriculture, Ecosystems & Environment, 178, 78–99. doi:10.1016/j.agee.2013.06.011 Strawn, D. G., Bohn, H. L., & O’Connor, G. A. (2015). Soil chemistry. New York, NY: Wiley-Blackwell. US Salinity Lab. Staff. (1954). Diagnosis and improvement of saline and alkali soils (Agriculture Handbook 60). Washington, DC: United States Department of Agriculture. Vincent, S. (2014). Environmental health monitoring: A pragmatic approach. International Journal of Waste Resources, 4(4), 164. doi:10.4172/2252-5211.1000164 Vyshpolsky, F., Qadir, M., Karimov, A., Mukhamedjanov, K., Bekbaev, U., Paroda, R., ... Karajeh, F. (2008). Enhancing the productivity of high-magnesium soil and water resources in central Asia through the application of phosphogypsum. Land Degradation & Development, 19(1), 45–56. doi:10.1002/ldr.814 WAPDA (Water And Power Development Authority). (2011). Hydro potential in Pakistan. Water And Power Development Authority, Pakistan. Retrieved from http://www.wapda.gov.pk/pdf/BroHydpwrPotialApril2011.pdf Wichelns, D., & Qadir, M. (2015). Achieving sustainable irrigation requires effective management of salts, soil salinity, and shallow groundwater. Agricultural Water Management, 157, 31–38. doi:10.1016/j. agwat.2014.08.016 Yunus, M. (1977). Water quality in The Indus Plains. In Proceedings of the Seminar on Water Management for Agriculture (pp. 283-292). Lahore, Pakistan: Exxon Chemicals Pakistan Ltd.

This research was previously published in Reconsidering the Impact of Climate Change on Global Water Supply, Use, and Management edited by Prakash Rao and Yogesh Patil, pages 84-101, copyright year 2017 by Information Science Reference (an imprint of IGI Global).

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Chapter 54

Rural Innovations: Text and Cases

Roopesh Rao Shri Ramdeobaba College of Engineering and Management, India

ABSTRACT In a country like India innovations are more referred as “jugaad”. Though the dictionary does not explain such kind of words, but every person in India understands the importance of jugaad. India has one of the largest systems for agricultural research in the world. However this system has focused predominantly on strengthening of cereal production under irrigated conditions. It would be essential that they participate in all decision making which cater to overall development of rural India. India also needs to increase its efforts to tap into the rapidly growing stock of global knowledge through channels such as FDI, technology licensing, importation of capital merchandise that embody knowledge, as well as advanced products, components, and services. This chapter analyses and focuses on various innovative practices done with the help of Government, Public Private Partnership, private Players, Individuals, NGOS, etc.

BACKGROUND Innovation is increasingly being seen as the currency of 21st century. The future prosperity of India in the new knowledge economy will increasingly depend on its ability to generate new ideas, processes and solutions, and through the process of innovation convert knowledge into social good and economic wealth. (India Innovation Portal Decade of Innovation 2010-20) India lives in numerous villages scattered thorough out the country. Rural areas are nearly three-fourth of the country of India and accounted for more than half of economic consumption. In spite of urbanization about 63 percent of population will continue to live in rural areas in year 2025. And the total potential of Indian rural market will reach to about 500 billion by 2020. According to 2011 census there is 640000 villages in India. India has substantial population below poverty line and having literacy level.

DOI: 10.4018/978-1-5225-9621-9.ch054

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 Rural Innovations

INNOVATION “The process of translating an idea or invention into a good or service that creates value or for which customers will pay. To be called an innovation, an idea must be replicable at an economical cost and must satisfy a specific need. “Innovation involves deliberate application of information, imagination and initiative in deriving greater or different values from resources, and includes all processes by which new ideas are generated and converted into useful products. In business, innovation often results when ideas are applied by the company in order to further satisfy the needs and expectations of the customers. ‘Innovation is defined as a process by which varying degrees of measurable value enhancement is planned and achieved, in any commercial activity. This process may be breakthrough or incremental, and it may occur systematically in a company or sporadically; it may be achieved by introducing new or improved goods or services and/or implementing new or improved operational processes and/or implementing new or improved organizational/ managerial processes in order to improve market share, competitiveness and quality, while reducing costs.’ Business Dictionary (2014) Innovation and competitiveness have a dynamic, mutual relationship. Innovation thrives in a competitive environment and in turn, plays a key role in the achievement of such an environment. Innovation generates economic value, new jobs in the economy and cultures of entrepreneurship. By virtue of its relationship with competitiveness, Innovation emerges as a factor in promoting economic growth. Given the fact that the Indian economy is growing at 6-8% per year, while exports are growing at 30% Cumulative Annual Growth Rate (CAGR), India Innovation (2014) and many Indian firms are successfully competing against international firms and brands, it can be concluded that this has been made possible by a combination of factors, including enabling environment, rising capital and labor productivity as well as improved quality of goods and services at lower costs. In a social context, innovation helps create new methods for alliance creation, joint venturing, flexible work hours, and creation of buyer’s purchasing power. Innovator need not be a person who comes from a wealth background, with a huge credential and qualification. Innovation can be done and are happening at grass-root levels. The story of Mandar Talukar, a small town boy from Nagpur winning the “best innovator in the world” award at USA for his innovation mobile shoe charger, show that innovators are not born; they are developed in adversity thus proving that “necessity is the mother of invention”. Rao et al (2012) In a country like India innovations are more referred as “jugaad”. Though the dictionary does not explain such kind of words, but every person in India understands the importance of jugaad. The classic examples of jugaad are the use of washing machine to make huge amount of “lassi” (sweet butter milk, sold in northern part of India), pressure cooker used for making espresso coffee, etc. As we can see India is the land of innovation (jugaad) and innovation is here to stay for a long time. Innovations have become a way of life and life without innovations is unimaginable. To its credit, India has been taking bold steps to strengthen its R&D infrastructure, developing technological innovations and altering the mind-set of its people toward better creation, acquisition, and use of technology. It is endowed with a critical mass of scientists, engineers, and technicians in R&D and is home to dynamic hubs of innovation, such as Bangalore and Hyderabad. It also has vast and diversified publicly funded R&D institutions, as well as world class institutions of higher learning, all of which provide critical human capital. India is also emerging as a major global R&D platform; about 100 multinational corporations (MNCs) have already set up R&D centers in the country, leading to the deepening of technological and innovative capabilities among Indian firms.

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AUTOMATED TELLER MACHINES IN RURAL PARTS OF INDIA Though it has given its remarkable footprints in rural development but still there are some parts were there are lack of facilities in rural parts and remote areas. When studied awareness of ATM facilities in rural part we come to know that, within two decades, ATM technology development is happening at an alarming rate. Qureshi, Kumar, Jhunjhunwala (2002). Gone are the days when customers were limited to only withdrawing cash from ATM’s. We have now reached an era, where we can use multi function and biometric ATM, (See Figure 1) equipped with touch sensitive and user friendly options to transfer funds, book air and train tickets, go for mobile recharge, and even deposit cheque with scanning. The consumers in the rural areas lack awareness about various schemes and e-banking services of bank. The emergence of new technology allows to access the banking service without physical direct re-course to the bank premise by the customer at present atm is city oriented in the country. Agarwal (2012) The growth of rural it industry fosters financial inclusion by providing financial services to people in the farthest reach of the country. Qureshi, Kumar, Jhunjhunwala (2002) Rural marketing plays an important role in development strategy, particularly in the areas of diversification, modernization, globalization and self-reliance. 70% of Indian population belongs to rural part of the country. When it specifically comes to contribution of information technology ATM (automated teller machine) had played a very important role in rural development. The emergence of new technology has effect the consumer awareness in rural parts to a remarkable extent. (Srinivasa Rao, 2013) (See FIGURE 2) It has also give awareness and education to undeveloped part of the region. It has also influenced over the population with financial support. Agarwal, Dadhich (2012) India lives in numerous villages scattered thorough out the country. Rural areas are nearly threefourth of the country of India and accounted for more than half of economic consumption. In spite of urbanization about 63 percent of population will continue to live in rural areas in year 2025. And the total potential of Indian rural market will reach to about 500 billion by 2020. According to 2011 census there is 640000 villages in India. India has substantial population below poverty line and having literacy level. Rural banking system with emergence of information technology is influencing the population Figure 1. An ATM (automated teller machine) in a small village in INDIA

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towards banking services like ATM cards, credit cards and other quick and easy services. Even now, rural development defies any clear definition as it has gone through a number of changes over a period of time. Persuasive communication for rural development has been given highest priority for bringing about desirable social and behavioral change among the most vulnerable rural poor and women. Initially, the approach lacked gender sensitivity and empathy of the communicators and development agents who came from urban elite homes. Agarwal, Dadhich(2012) Added to these constraints is political will that still influences the pace and progress of rural development. We are one of the world’s oldest and ancient civilizations that evolved, matured and decayed over several millennia. After independence we have been experimenting and carving a path of revitalization for development through democracy. The existing sharp divide between the small but economically, politically and socially “rich elite ruling class” and a very big but “economically poor and socially deprived” continue to persist as a legacy of the past. After independence, the government took upon itself the major responsibility of development. Hence, the central and state governments carried out development projects. The experiment was carried out from February to April 1956 in five districts of Maharashtra state by all India radio (air). Rao (2013) Rural listener groups were organized, who would listen to radio broadcasts twice a week. The summative impact evaluation indicated positive outcome of radio rural forum. Impressive knowledge gains as a result of radio listening were reported across illiterates and literates, agriculturists and non-agriculturists, village leaders and others. Almost all healthcare projects for rural poor, especially women and children have used demand driven social marketing approach for rural the development.

HDFC Bank ‘Project Jharkhand’: An IT Enabled Financial Inclusion Program HDFC Bank, launched ‘Project Jharkhand’ a financial inclusion program. As part of the program, the Bank launched its world class services at a Common Service Center in Kanke comprising over 1.5 lac households spread across 100 villages in 30 Panchayats. The Bank also adopted Chakala village near Ranchi as part of the Common Service Center program. Under Project Jharkhand HDFC Bank will Figure 2. A solar operated ATM – innovation for greener tomorrow

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look to cover over 45 lac households in the state through both the Common Service Center and village adoption models, subject to regulatory provision.CSC is an integral component of the Central Government’s National e-Governance Plan (NEGP) that seeks to set up over 5000 CSCs in Jharkhand and about 100,000 in the country. These Common Service Centers will make available to the rural population a slew of services ranging from public information services, e-governance services, educational services to agri related and financial services. Common Service Center will also work like a ‘Human ATM‟ that the rural people can use to withdraw and deposit cash. (HDFC Bank launches ‘Project Jharkhand 2008, http://www. hdfcbank.com/htdocs/common/pdf/Project_Jharkhand.pdf)

TRANSFORMING RURAL INDIA THROUGH AGRICULTURAL INNOVATION “Agricultural jeopardy is related with undesirable outcomes that shoot from badly expectable biological, climatic, and price agents. These variables include natural calamities and climatic factors not within the control of agricultural producers.” Shanmugam, Chandrasekaran, Vijayasarathy. (2011) They also include adverse changes in both input and output prices. To set the stage for the discussion on how to deal with risk in agriculture, we classify the different sources of risk that affect agriculture. Agriculture is often characterized by high variability of production outcomes or, production risk. Unlike most other entrepreneurs, agricultural producers are not able to predict with certainty the amount of output that the production process will yield due to external factors such as weather, pests, and diseases. Agricultural producers can also be hindered by adverse events during harvesting or collecting that may result in production losses. Agriculture community (2014)

Figure 3. Some Agricultural Innovations

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Input and output price volatility is important sources of market risk in agriculture. Prices of agricultural commodities are extremely volatile. Output price variability originates from both endogenous and exogenous market shocks. Segmented agricultural markets will be influenced mainly by local supply and demand conditions, while more globally integrated markets will be significantly affected by international production dynamics. In integrated markets, a reduction in prices is generally not correlated with local supply conditions and therefore price shocks may affect producers in a more significant way. Another kind of market risk arises in the process of delivering production to the marketplace. The inability to deliver perishable products to the right market at the right time can impair the efforts of producers. The lack of infrastructure and well-developed markets make this a significant source of risk in many developing countries. The ways businesses finance their activities is a major concern for many economic enterprises. However, in this respect, agriculture also has its own peculiarities. Many agricultural production cycles stretch over long periods of time, and farmers must anticipate expenses that they will only be able to recuperate once the product is marketed. This leads to potential cash flow problems exacerbated by lack of access to credit and the high cost of borrowing. These problems can be classified as financial risk. Agriculture community (2014) Another important source of uncertainty for agricultural producers is institutional risk, generated by unexpected changes in regulations that influence producers’ activities. Changes in regulations can significantly alter the profitability of farming activities. This is particularly true for import/export regimes and for dedicated support schemes, but it is also important in the case of sanitary regulations that can restrict the activity of producers and impose costs on households. Like most other entrepreneurs, agricultural producers are responsible for all the consequences of their activities. However, the growing concern for the impact of agriculture on the environment, including the introduction of genetically modified organisms (GMO), may cause an increase in producer liability risk. Finally, agricultural households, along with other economic enterprises, are exposed to personal risks to the wellbeing of people who work on the farm, and asset risks, the possible damage or theft of production equipment and assets. With a majority of its population living in villages, rural poverty is a major problem in India. The disparity between the urban and rural incomes is also on the rise. This leads to migration to urban areas resulting in urban blight as well. Therefore addressing the problem of rural poverty assumes urgency. Agriculture community (2014) Rural innovations has been involved in a range of interventions—infusion of technology, soil enrichment, efficient farm and water management, improved cattle development, functional literacy, rural sanitation and public health, human resource development, establishment of self-help groups particularly among women, self-employment opportunities and facilitating institutional credit—to address the problem of farm productivity in India. Rural innovations focus on the poor and marginal farmers, women, unemployed youth, and depressed communities. Rural innovations work in about 250 villages in tamil nadu and have reached 30,000 rural families. A large part of rural innovations’ effort with farmers is to help break their initial emotional barriers to new technologies. This has provided the platform to launch into other initiatives. The success of these measures has had a demonstrative impact on the farmers’ willingness to adopt and internalize new technologies. This may be considered an attitudinal breakthrough (Figure 3). Another initiative, the center for rural development (CFRD), a training cum village knowledge center, has been established in illedu village of kancheepuram district with classrooms, computer lab with internet facilities, input and product handling center, farm machinery workshop, model experimental farm, residential complex for trainees and an open air theatre to cater to the needs of various sections of

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rural community. Rural innovations also helps in housing a comprehensive soil testing laboratory, food safety and standards laboratory and a plant tissue culture lab to provide agriculture support services. Agriculture productivity improvements through resource conserving “lean farming”: paddy (55%), groundnut (113%), vegetables (116%), sugarcane (40%), and corn (150%). Through successful lead farmers, technology transfer has been effected over an area of 10,000 acres with a “lead farmer—lead village” concept. Addressing the agriculture value chain—soil testing, facilitation of inputs and credit, market linkage, and field advisory services—is part and parcel of agriculture development initiatives. Promotion of climate resilient agriculture, resource conserving technologies and promotion of use of information communication technology (ICT) in agriculture are being attempted too. Watershed and natural resource management initiatives have resulted in increase in water table ranging from 3.5 meters to 5 meters in the project area of over 6,000 hectares. Cropping intensity has been doubled (two crop cultivation in a year instead of one crop) and about 20% additional area which had been left fallow has also been brought under cultivation. Soil erosion, nutrient loss, damage due to flooding during rainy seasons has reduced significantly. Agriculture community (2014) To sustain the benefits derived, the social development initiatives of rural innovations have helped village communities in establishing community-based institutions like farmers clubs, self help groups and joint liability groups, farmers producer organizations, watershed committees, etc for collective decision and action. India has many of the key ingredients for making this transition. The time is very appropriate for India to make its evolution to the knowledge economy—an economy that creates, disseminates, and uses knowledge to enhance its growth and development. It has a critical mass of skilled, English-speaking knowledge workers, especially in the sciences. Its local market is one of the world’s largest. The knowledge economy is often taken to mean only high-technology industries or information and communication technologies (ICTs). It would be more appropriate, however, to use the concept more broadly to cover how any economy harnesses and uses new and existing knowledge to improve the productivity of agriculture, industry, and services and increase overall welfare. In India, great potential exists for increasing productivity by shifting labor from low productivity and subsistence activities in agriculture, informal industry, and informal service activities to more productive modern sectors, as well as to new knowledge-based activities—and in so doing, to reduce poverty and touch every member of society. India should continue to leverage its strengths to become a leader in knowledge creation and use. To get the greatest benefits from the knowledge revolution, the country needs to press on with the economic reform agenda that it put into motion more than a decade ago and continue to implement the various policy and institutional changes needed to accelerate growth. It has a large and impressive Diaspora, creating valuable knowledge linkages and networks. The list goes on: macroeconomic stability, a dynamic private sector, institutions of a free market economy, a well-developed financial sector, and a broad and diversified science and technology(S&T) infrastructure. In addition, the development of the ICT sector in recent years has been remarkable. India has created profitable niches in information technology (IT) and is been remarkable. India has created profitable niches in information technology (IT). Rapid advances in ICTs are dramatically affecting economic and social activities, as well as the acquisition, creation, dissemination, and use of knowledge. The use of ICTs is reducing transaction costs and lowering the barriers of time and space, allowing the mass production of customized goods and services. Some of the examples of rural innovations which are changing the lifestyle, business and way of life are as follows

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INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) GYANDOOT Situated in Dhar district of Madhya Pradesh, Gyandoot is an Intranet based Government to Citizen (G2C) service delivery portal it was launched in January 2000. Gyandoot aims to create a lucrative, replicable, economically independent and financially viable model for the rural population to take the benefits of Information and Communication Technology (ICT). Gyandoot: The Purveyor of Knowledge (2014)

E-CHOUPAL BY ITC Choupal is a Hindi word which means “village meeting place”. Market is a meeting place where vendors and customers come together to do transactions. e-choupal is a virtual market place where farmers can transact directly with a processor and can realize better price for their produce. The main charisma of e-choupal is that it can be used for connecting large producers/small producers and small users/large users, thereby eliminating the need for chain of command of brokers. Geographical distances do not restrict participation in the e-choupal. E-choupal has the advantages of the market but spans very large varieties of vendors and customers. The main disadvantage of Traditional market is that information asymmetry is inherent in the market where as e-choupal provides for transparent transactions. This enables the participation of smaller as well as larger players. Exclusion of intermediaries allows for larger share of profits to reach the bottom end of value chain.(https://www. echoupal.com/)

UNIQUE IDENTIFICATION PROJECT In a country like India, absence of social security number or its equivalent has made more than 380 millions of poor suffer in the hands of the existing corrupt system because they are unable to participate in the official financial system of the country. The government of India’s Unique Identification (UID) project has created avenues for this people to become a part of the different projects and plans developed for self sufficiency, growth and improvement in living standards. This innovation has revolutionized the way Identification is done. The linking of bank account to the card has helped government send direct subsidy to the poor and the needy, thus removing the middle men and barriers. The gas subsidy is directly transferred to the card holders every time they purchase a cylinder thus creating a barrier for black marketing of gas cylinders. Adhar card (2014)

INNOVATION FOR IMPROVING HEALTH IN RURAL INDIA Innovation is required to address health needs at the bottom of the pyramid. Delivering affordable and quality health care to India’s billion-plus people presents enormous challenges and opportunities. Innovations could be a way out for a large number of people get quality care at a cost that the nation can afford. Addressing healthcare challenges in rural India is a complex proposition. Healthcare starts with generating awareness of risk factors, disease symptoms and the benefits of healthy living to the rural masses for the betterment of the rural population. Measures are taken to convert these messages into actions 1206

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resulting in the prevention of disease or morbidity. Patients suffering from disease would then require provision of primary, secondary or tertiary care. This is followed by protection of patients from relapse or future risks through management of disease, regular monitoring and health maintenance. Addressing this continuum of care is more complicated owing to the ‘double burden of disease’ i.e. the co-existence of both communicable and non-communicable diseases. While the country is still dealing with the issue of communicable diseases, the share of non-communicable diseases is also increasing rapidly requiring the health system to come up with a wide range of diverse interventions to address the varying financing, prevention, provision and protection needs of the diseases. Governments schemes (2012) In addition, a number of other external factors have a bearing on health and health seeking behavior. Recent research increasingly relates health inequalities to social factors such as poverty, nutrition, hygiene, water and sanitation, education, empowerment of women and living space. This would mean that to make any lasting impact on population health outcomes, addressing issues along the complete gamut including these social determinants of health is essential.

TOTAL SANITATION CAMPAIGN In spite of noteworthy investments over the last 20 years, India faces the most daunting sanitation challenge in any region in the world. The Total Sanitation Campaign in Ahmednagar (Maharashtra) has bought innovation into Sanitation systems. Innovation in the Ahmednagar pilot project is in its use of conditional financial incentives. Most sanitation front individual household subsidies used to assist private toilet construction. Yet stopping open defecation requires collective action, which suggests that the financial incentives would be more effective if used to encourage the attainment of community, rather than individual, goals. In Ahmednagar, every household has to fund its own toilet. Governments schemes (2012) However, the BPL households do so on the understanding that they will be paid US$ 8.10 if everyone builds a toilet and the community is declared ‘open defecation free’. The remainder of the TSC subsidy (US$ 2.69 per BPL household), paid to the GP on achieving universal access, thus acts as an incentive for the GP to assist in stopping open defecation, including the promotion and facilitation of the construction of toilets by the landless, the very poor, and those unwilling to invest. A similar financial incentive is provided to the NGO working in the village. It is paid US$ 1.07 commission for every household that builds a toilet (from the IEC funds), but does not receive any of this money until the village is declared ‘open defecation free’. For more than 800 million men, women and children across India living on USD 1-3 a day, the idea of accessible and affordable medicines is often as remote as their rural homes. Arogya Parivar (“Healthy Family” in Hindi): A social initiative developed by Novartis to reach the underserved millions living at the bottom of the pyramid in rural India. After just five years, Arogya Parivar is proving to be both a force for improving health in rural communities and a sustainable business. Arogya Parivar provides opportunities to expand business in an innovative and responsible way. The program offers education on diseases, treatment options and prevention as well as increases access to affordable medicines. Health educators, usually local women, raise awareness about local diseases and preventive health measures. They also refer sick people to doctors and cooperate with local NGOs to further spread their message. Each educator covers a few villages every day, with an Arogya Parivar branded cap, shirt and banner, making them easily recognizable. Sales supervisors serve as the initiative’s local sales force. They interact with local pharmacies and collaborate 1207

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with doctors, hospitals and NGOs to organize health camps where villagers can receive treatment and preventive care. Arogya Parivar focuses on the diseases most prevalent in rural India. Further, products and services are tailored to meet the needs of underserved rural populations with a low disposable income, usually earned on a daily basis. Novartis arogya (2014)

IKURE TECHSOFT Delivering affordable healthcare to the doorsteps of rural masses, India continues to face enormous challenges. With a population over one billion, rural India comprising of 840 million people are served by only 30 per cent of the country’s combined medical force. Out of which, three per cent of India’s physicians live in rural areas, and 25 per cent in semi-urban areas. This is disproportionate, and an example of the Pareto Principle – where 20 per cent of the doctors serve 80 per cent of the population. This is disproportionate, and an example of the Pareto Principle – where 20 per cent of the doctors serve 80 per cent of the population. Moreover, the morbidity rate in people reporting the same, in rural areas increased to 70 per cent in 2011 against 64 per cent in 2004. Rural India is critically flawed with inefficient heath care system. They either remain short of medical personnel or untrained officers. According to NRHM report, out of 22,000 primary healthcare centers, eight per cent do not have a doctor, 39% remain unattended without a lab technician and 17.7% without a pharmacist, and this is when, each primary health center is supposed to have at least one medical practitioner. Based in Kolkata ikure sets up rural health centers across India. with an initial funding of Rs 45 lakh from Intellecap Impact Investment Network and Calcutta Angels; Rs 70 lakh from WEBEL iKure Techsoft has built a network of rural health centers where doctors are available through the week and pharmacists dispense only ac. (http:/www.ikuretechsoft.com)

DRINKING WATER QUALITY IN RURAL INDIA: ISSUES AND APPROACHES The rural population of India comprises more than 700 million people residing in about 1.42 million habitations spread over 15 diverse ecological regions. It is true that providing drinking water to such a large population is an enormous challenge. Our country is also characterized by non-uniformity in level of awareness, socio-economic development, education, poverty, practices and rituals which add to the complexity of providing water. The health burden of poor water quality is enormous. It is estimated that around 37.7 million Indians are affected by waterborne diseases annually, 1.5 million children are estimated to die of diarrhoea alone and 73 million working days are lost due to waterborne disease each year. The resulting economic burden is estimated at $600 million a year. The problems of chemical contamination are also prevalent in India with 1,95,813 habitations in the country are affected by poor water quality. The major chemical parameters of concern are fluoride and arsenic. Iron is also emerging as a major problem with many habitations showing excess iron in the water samples. Transforming rural India, (2014) The provision of clean drinking water has been given priority in the Constitution of India, with Article 47 conferring the duty of providing clean drinking water and improving public health standards to the State. The government has undertaken various programs since independence to provide safe drinking water to the rural masses. Till the 10th plan, an estimated total of Rs.1,105 billion spent on providing 1208

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safe drinking water. One would argue that the expenditure is huge but it is also true that despite such expenditure lack of safe and secure drinking water continues to be a major hurdle and a national economic burden.

COMMUNITY BASED MAINTENANCE OF WATER SOURCES MAINTENANCE OF WATER SOURCES Ramakrishna Mission Lokasiksha Parishad (RKMLP) is one of the biggest units of the Ramakrishna Mission Ashram, Narendrapur. It has done remarkable work in the field of maintaining water sources and has successfully demonstrated community based maintenance of 800 hand pumps in Medinipur. To carry out this process, a seven-member ‘water committee’ with four female and three male members from the beneficiary families were formed for each hand pump. These members were trained in operation and maintenance by the RKMLP. A maintenance chest fund was developed for individual pumps, with each family contributing one rupee per month. The money is collected once or twice a year depending on the paying capacity of the family. An innovative strategy developed is to collect the money during religious ceremonies after the harvest season as people have money during this time of the year. In this way, the water committee was able to collect Rs. 300-500 from the beneficiary families. The members of the committee also organized awareness generation activities relating to safe collection, storage and handling of drinking water simultaneously promoting sanitation and personal hygiene practices. Transforming rural India (2014) & Indian rural water supply (2014)

DUAL WATER SUPPLY AND WASTE WATER TREATMENT To reduce the burden on fresh water sources, the option of dual water system is being worked out in several parts of the country. The success of this system lies in the fact that filtered purified water is used only for drinking purposes while other source of water may be used for purposes other than drinking. This is also is cost saving measure as resources spent on providing clean water is saved by using alternate sources. Waste water treatment can also be another effective means of reducing the burden on freshwater sources. The treated waste water can be used for purposes other than drinking. One example of effective wastewater treatment is in Mehsana district of Gujarat where wastewater from homes in villages is used for agriculture. The wastewater coming out of homes is collected in a pond which is then auctioned to farmers for use in agriculture. Magod Dungri village in Valsad district in Gujarat has a population of 4,264. An old well served as a water source, but the water was saline and not potable. In 2006, this village was brought under the Bigri Malwan group water supply scheme of the GWSSB and it started getting safe drinking water. But in-village distribution of water continued to pose difficulty. Under the Swajaldhara programme, the village community decided to develop a system of household connections. The entire community made a 10 per cent contribution towards capital costs and the responsibility of collecting the contribution was taken up by one individual in each habitation. In the process, a 5,000 liter water tank in the village school, electricity connections, a 2,208 meter distribution pipeline, a 318 meter gravity pipeline and 15 stand posts were made. Out of a total expenditure of Rs.5, 20,000, the community contributed Rs.80,000. The foremost priority of the village was to get regular and safe water to meet their drinking water require1209

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ments. As far as water for other purposes was concerned, this need could easily be met from the village well. For drinking water, the villagers make use of the treated water supplied through the regional water supply scheme. This is accessed from the 15 stand posts constructed in the 15 habitations in the village. Drinking water is received for about 30-45 minutes every day Thus by making use of dual sources of water, the community has ensured that treated water is not wasted and is used only for drinking purposes. Indian rural water supply (2014) The villagers regularly pay water tariff fixed by the Pani Samiti. The Pani Samiti regularly pays Rs 14 per person as water tariff to the water supply department and if need be the villagers are ready to contribute more. The villagers also contribute Rs.16 per person towards electricity and maintenance charges.

SOLAR HOME SYSTEMS FOR RURAL ELECTRIFICATION Lack of access to electricity is one of the biggest issues facing the world’s poor, with over 1.6 billion left in the dark globally. The vast majorities of these people live in rural areas of developing countries because they are too poor and may be in too remote a location to be reached by the national grid. For their lighting needs they rely on candles, kerosene lanterns, and firewood which results in a daily expense that is expensive in the long run. Furthermore, this type of indoor lighting causes indoor pollution and chronic lung problems. Long-term, solar energy is the most practical and economical way of bringing power to poor and remote communities. Small-scale, distributed solar home systems provide an effective and affordable way to bring light to people without electricity. A basic system consists of a small solar panel, a battery, a charge controller, LED lights, and a universal outlet for charging cell-phones or other small appliances.(See Figure 4) A basic system can be made affordable through microfinance options. Partnering with local banks and/or microfinance organizations to create payment plans can help overcome the large initial investment associated with purchasing a system. Energy savings result from not having to buy candles or kerosene fuel, and can make the monthly payments affordable. When proposing this technology to a new area, it is important to target a community that has expressed a need and desire for solar electricity. Identifying and allying oneself with a respected community leader who is receptive and supportive is a good idea.

THE CLASSIC CASE OF SELCO IN SOLAR ELECTRIFICATION SELCO’s pioneering efforts with microfinance in rural India is a large reason why they have become a world leader in the field. However, their case also brings to light another issue relating to “free riders.” Innovative companies willing to be first in the game can be put at a competitive disadvantage when they spend resources on innovation and capacity building. This is due to other companies taking advantage of their earlier efforts, getting a “free-ride.” For example, after SELCO spent many years and dollars on developing India’s rural financial infrastructure, other companies benefited from it. There were even some banks that, after giving out successful loans for SELCO systems, started selling their own systems for personal social development programs. Broadly speaking this isn’t a bad thing, as it results in greater adoption of the technology and increased electrification for the poor. However, it does result in a decreased incentive for individual companies to innovate if their competitors are accruing benefits from their investment. To overcome the free-rider problem, governments and non-profit development 1210

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institutions should provide funding and incentives for enterprises to innovate. This could be in the form of technical and financial support for businesses entering a not served geographical area. Furthermore, a government or non-profit could provide financing for early-stage systems, which would allow local banks in the private sector to see the technology successfully implemented before they decide to take on the risk of loans. (http:/www.selco-india.com)

Sunkalp Energy A solar power company Sunkalp Electricity is launching a project called Solar Soldiers to involve people in Rural Electrification in Uttar Pradesh through the innovative use of Solar Power. A number of corporate are stepping up the green ante this day. This is what Sunkalp asks, “No TV. No internet. No AC. In fact, no LIGHT!!! Can you imagine a world without electricity? Not for a minute, an hour– but for 25 years. This Indian village in Uttar Pradesh has lived without power for so long that they can’t remember what electricity means. We are here to bring them back from the past.” Hence the idea is to rescue a forgotten community from the clutches of darkness. With this mission, it is building a solar mini-grid to power the lives of around 200 villagers without access to electricity. About 93% of the villagers in Gulabganj have already signed up for an electricity connection from the mini-grid. Sunkalp Energy has developed a low cost micro grid tailored to the needs of off-grid villages. Sunkalp Energy is constructing and will operate a pilot project initially in a small village of 25 households and will approximately extend to 4 new village-level micro grid lighting facilities to reach 300 new customers and 1,800 new beneficiaries in Hamirpur districts of Uttar Pradesh, India (http:/www.sunkalp.com).

DRAWBACKS OF RURAL INNOVATION While innovation helps in attaining cost efficiency, reliability and ease of use, the investment in terms of land, labor, machinery and other fixed assets may be huge. As far as Innovations in electrification

Figure 4. Some Solar Instruments for electrification

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and water purification is concerned, it requires huge initial investments. Implementation part is also a major concern when it comes to government policies. Challenges are huge when we talk about the implementation part. How much work is actually done on ground will be a million dollar question. Moreover if private investors are encouraged to invest in these rural innovations sector will inculcate in drawing quickly the return on their investment. This may hamper the main concern of helping the rural people for which the process was started altogether. Moreover less private players would like to put their liquidity into these matters as they may not find the area interesting for their bottom line. Minor drawbacks can be catered to in long term but projects like solar electrification, water purification and rural electrification may also lead to environmental hazards which can be cause of great concern.

CONCLUSION So after going through various context, cases, contention and issues we can conclude that many innovations are coming up for the agricultural sector but they are not widely known nor have they been systematically monitored and evaluated. Many of the innovative models are still relatively new, but through time and the use of appropriate systems to monitor and evaluate their achievements, we will be able to draw more complete lessons that can help in scaling up and replicating them. This will help us better understand what works and what does not, and under what conditions. What seems to be missing at this point is some repository of innovative models, systems to monitor, and methodologies to evaluate them. In addition, we need to think of incentives to strengthen existing innovative models and also promote further innovation As said early in the chapter ‘Innovation is defined as a process by which varying degrees of measurable value enhancement is planned and achieved, in any commercial activity. This process may be breakthrough or incremental, and it may occur systematically in a company; it may be achieved by introducing new or improved goods or services and/or implementing new or improved operational processes and/or implementing new or improved organizational/ managerial processes in order to improve market share, competitiveness and quality, while reducing costs.’ India has one of the largest systems for agricultural research in the world. However this system has focused predominantly on intensification of cereal production under irrigated conditions. There has been criticism that this research system enabled an exploitative agriculture without a proper understanding of the various consequences of every one of the changes introduced into traditional agriculture. So it becomes imperative, based on previous experience of change in Indian agriculture to empower the resource poor smallholder and marginal farmers to be able to negotiate with stakeholders to their development their needs for political, social, economic and technological development. It would be essential that they participate in all decision making. The technologies they need will not therefore be limited to those related to agriculture alone but also to politically, socially and economically aggregate and collectively decide. Those who will generate enable adoption and, if need be, adaptation and innovation, will need to understand how development works along with how technology works and adapt each other for success. The has to be focus on innovation and the rebuilding will be based on social research of the needs of small holder farmers and that includes the study of socio-economics of the new technologies of Agriculture, ICT, Irrigation technologies, Solar

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Electrification that are developed to meet the needs of smallholder farmer. But, more important, it will be important to understand how development and technology, with all its facets and components, work side by side. And within this context, this would need entire communities, especially agricultural, to be included in decision making through participation. In cases where the total sanitation approach had been used, program managers and local government officials were aware that their main objective was to stop open defecation, and that this required community-wide action, universal toilet use, and hygiene behavior change. Opinion was divided as to how these changes should be effected, but there was little argument about the approach. In this respect, the ‘total sanitation’ concept is a major step forward, as this level of shared understanding and purpose was sadly lacking in many earlier sanitation programs. It would be also important to redirect research for agriculture so that its purpose is to provide the innovations needed by small holder farmers as a direct product and not as a spillover or trickledown effect. The system has to recognize that a large number of technologies influencing each other and working together and in tandem contribute to agricultural development and all these need to be brought about appropriately. It can also be concluded that no single innovation can be considered the miracle or “silver bullet” solution, and this is despite the various calls over time to come up with grand schemes and search for big solutions. Creation of a forum of large agribusinesses that could be encouraged to leverage their networks in emerging markets and create openness that could be encouraged to leverage their networks in emerging markets and create opportunities for attracting financial institutions that could fund parts of their value chain, like local small traders, processors, farmers, etc. Financing could be linked and become the catalyst for technology improvements and promotion of environmental and social standards along specific value chains. Based on the current state of healthcare system in rural part of Indian States the scope for Innovation is there. Through Government sponsored schemes, private sector interventions and the recent string of PPP Projects are intervening and trying to build up an infrastructure to make possibilities of inroads for betterment of facilities, it is understood that there is still a long way to go in terms of uplifting of the healthcare sector and reaching the desired health goals. It is very much evident that huge investment will be required in developing upgrading of healthcare infrastructure, in order to improve accessibility and quality of care. The private sector must consider this as business opportunity to establish their presence and expand their operations/ market share in the healthcare delivery market in India either by partnering with the different state governments or pursuing a pure private model. The government at the same time needs to understand the issues faced by private sector currently (working independently or in the existing PPP programs) and take measures to improve the investment climate in the respective states. The states will need to put in place clear policies and guidelines in the healthcare sector which will enable to attract large private investments in the health care industry In the end it can be concluded that Rural Innovation will envision what is there in store for India as a country to develop as the next super power which will dominate the Subcontinent and create inroads and benchmarks for countries to follow. Under developed countries in Africa and other parts of the world are looking forward towards India to create a magnum opus so that the same model can be followed and replicated in their countries.

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REFERENCES Adhar card. (2014). Retrieved from, http:/www.uidai.gov.in Agarwal, M. D. (2012). Online banking services: An empirical study of banker’s and customer’s awareness about obs. Journal of Exclusive Management Science, 1(7), 25–35. Agriculture community. (2014). Retrieved from http://data.gov.in/community/agriculture-community/ blog/national-agricultural-innovation-project Annual Report of State Bank of India 2011-2012. (n.d.). Retrieved from http://www.sbigroup.co.jp/ english/investors/library/filings/pdf/2012_en.pdf Bhatnagar, S. C. (2004). E-Government: From Vision to Implementation – A Practical Guide with Case Studies. New Delhi: SAGE Publications Pvt. Ltd. EchoupalI. T. C. (n.d.). Retrieved 2 July 2014 from https://www.echoupal.com/) Governments schemes. (2012). Retrieved from http://yojana.gov.in/CMS/(S(y4dqrc55g1m1qhnd4soqih45))/ pdf/Kurukshetra/English/2012/January.pdf Gyandoot: The Purveyor of Knowledge. (2014). Retrieved from http://gyandoot.nic.in/ HDFC Bank launches ‘Project Jharkhand’ – an IT enabled Financial Inclusion program. (n.d.). Retrieved from http://www.hdfcbank.com/htdocs/common/pdf/Project_Jharkhand.pdf iKure. (2014). Solar Soldiers. Retrieved from http:/www.ikuretechsoft.com India Innovation. (2014). Retrieved from http:/www.IndiaInnovationPortalDecadeofInnovation2010-20. com Indian Rural Water Supply. (2014) Retrieved from, http:/www.worldbank.org/projects/.../india-ruralwater-supply-sanitation-project Innovation. (n.d.). Retrieved from) http:/www. Businessdictionary.com Kumar, R., & Jhunjhunwala, A. (2002). Taking Internet to Village: A case study of Project at Madurai Region. TeNeT Group of IIT Madras. Novaritis arogya. (2014) Retrieved from www.novartis.com/downloads/corporate.../arogya-factsheet.pdf Planning Commission. Government of India. (n.d.). Retrieved 2 July 2014 from http:/www.planningcommission.gov.in Qureshi, T. M. (2008). Customer Acceptance of Online Banking in Developing Economies. Journal of Internet Banking and Commerce, 13(1), 13–20. Rao, C. S. (2013). Consumer awareness in rural India with special reference to E-Banking services in SBI. Indian Journal of Research, 2(2), 46–48. Rural Finance Learning Center. (n.d.). Retrieved 2 July 2014 from http:/www.ruralfinance.org

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Satyanarayana, J. (2004). E-Government. The Science of the Possible. New Delhi: Prentice Hall of India Pvt. Ltd. SELCO. (2014). Rural financial infrastructure. Retrieved from http:/www.selco-india.com Shanmugam, T. R., Chandrasekaran, M., & Vijayasarathy, K. (2011). Economic Analysis of Farm and Market Risk. Saarbrücken: LAP Lambert Academic Publishing. Sustainable Access in Rural India. (2014) Retrieved from http://www.tenet.res.in/rural/sari.html The World Bank. (n.d.). Retrieved 2 July 2014 from http:/www.worldbank.org Transforming rural India. (2014). Retrieved from http://blogs.hbr.org/2014/02/transforming-rural-indiathrough-agricultural-innovation/ United Nationals Conference on Trade and Development. (n.d.). Retrieved 2 JULY 2014 from http:/ www.unctad.org White paper. (n.d.). Retrieved from http://edevelopment.media.mit.edu/SARI/papers/uncrd_report.pdf Rao, R., Menaria, D., Maurya, A., & Parashar, A. (2012). Video Case on Social Innovation. Retrieved from https://www.youtube.com/watch?v=CA4Q2sEcsg0

KEY TERMS AND DEFINITIONS ATM (Automated Teller Machines): Machines with the help of which money can be stored by a bank and retrieved by the customer of a bank without any human intervention. ICT: Information communication technology helps in connecting people with the help of tools like telephone, mobile phones and Internet. Innovations: Innovation is defined as a process by which varying degrees of measurable value enhancement is planned and achieved, in any commercial activity. Rural Innovations: Innovations happening in underdeveloped and rural parts of a country. Sunkalp Energy: A solar power company Sunkalp Electricity is launching a project called Solar Soldiers to involve people in Rural Electrification in Uttar Pradesh through the innovative use of Solar Power. UID (Unique Identification Project): The government of India’s Unique Identification (UID) project has created avenues for this people to become a part of the different projects and plans developed for self-sufficiency, growth and improvement in living standards.

This research was previously published in Promoting Socio-Economic Development through Business Integration edited by Shalini Kalia, Bhavna Bhalla, Lipi Das, and Neeraj Awasthy, pages 275-291, copyright year 2015 by Business Science Reference (an imprint of IGI Global).

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Chapter 55

Low Carbon Energy Innovations Systems in Natural Resource Rich Developing Countries: The Case of Brazil André Tosi Furtado University of Campinas, Brazil

ABSTRACT The transition to low carbon economy requires deep changes in the energy systems of the great majority of developing countries. However, only a small group of these countries is engaging significant efforts to develop renewable energies. The success in the diffusion of renewable energy technologies requires dynamic systems of innovation. In this chapter we analyze the recent evolution Brazilian sugarcane innovation system that was pioneering in the development and diffusion of bioethanol. This system is increasingly challenged by the acceleration of the technological regime, which is provoked by the energy crisis and the transition to the low carbon economy. The Brazilian innovation system has different capacities to cope with this challenge. In this chapter we differentiate the agriculture subsystem, which function in a STI (Science, Technology, and Innovation) mode from the industrial subsystem, which operates in a DIU (Doing, Using, and Interacting) mode. The agricultural subsystem has demonstrated a better ability to cope with the technological challenges of the new biotech research methodologies while the capital goods industry has much less propensity to deal with the second generation technologies for bioethanol. We describe also the present ethanol supply crises and its probable causes.

INTRODUCTION The transition to Low Carbon Economies entails significant challenges for most of the developing countries. Their future seems to be related to fossil fuels by two main reasons. At one side their energy demand is increasing rapidly, in part because important sectors of their population are excluded from modern energy welfare benefits, and at the other side most of their energy supply lend on fossil fuels1. DOI: 10.4018/978-1-5225-9621-9.ch055

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 Low Carbon Energy Innovations Systems in Natural Resource Rich Developing Countries

As it is unfair to suppose that energy demand in developing countries could be contained, even if energy efficiency has an important contribution to give2. Thus we should expect that fossil fuel consumption will continue to increase if nothing happens at the side of renewable sources of energy. These dynamics makes the non Annex I countries responsible also by most of the increase in the world CO2 emissions since 1990 (IEA, 2012). In present days most of the renewable used by developing countries are related to biomass. Biomass accounts for 10% of the global primary energy supply, mostly (6%) related to traditional uses of biomass like cooking and heating in the rural areas of developing countries. The share of traditional biomass is expected to decline since urbanization increases and modern energy carriers penetrate in poor households. Otherwise modern renewable energies technologies are projected to increase their share in future energy system. The main new sources are modern biomass, wind, photovoltaic, thermal solar, geothermal, and hydropower. Their share in the world energy supply was 10% in 2012 (REN 21, 2014). Modern renewable have progressed impressively in developed countries during the recent years due to their environmental policies that determined quantitative targets for renewables, and also because of their innovation and industrial policies related to these technologies. In 2013, European Union and United States had 58.6% of the world renewable electric power generation capacity without hydro. However we notice also that a group of emerging economies is well positioned in the promotion of these new sources of energy. BRICS countries have a 28.9% share that is rapidly increasing mainly due to China. This country alone has the world largest wind power capacity (28.6%) in 2013. For solar thermal heating the Chinese hegemony is impressive with 64% of the world capacity. In hydroelectricity China also is first placed with 26% of the generation capacity, followed by Brazil (8.6%). More than being a world leader in power generation capacity, China also is at the forefront position for equipment supply. In Photovoltaic and Wind energy, Chinese companies are among the world leaders (REN 21, 2014). Biomass is a very promising primary energy source for many developing countries. It is already an important energy source mainly due to traditional Biomass. In the future, modern biomass will increase its presence in the energy matrix (Goldemberg & Coelho, 2004). The leadership in modern biomass always belonged to developed countries. However, Brazil had been longtime the world leader for liquid biofuels. Nevertheless, more recently the Brazilian sugarcane ethanol lagged behind the USA corn ethanol. In 2013, US and Brazil accounted for 57.6% and 29.4% of the world bioethanol production. In the other kinds of biomass, developed countries still the world leaders like in biomass power generation, biogas and wood pellets, where European Union and United States are the world leaders (Ren 21, 2014). In this paper, we would like to consider the effective potentials of a resource rich developing country to become a world leader in modern biomass supply and technology. Our argument is that, alongside favorable resources endowment, national innovation system requires continuous learning in order to advance in the absorption and the development of new technologies.

BIOMASS IN THE BRAZILIAN ECONOMY Brazilian economy has a very dynamic biomass production system. Biomass commercial production, not only connected with energy, and related industries had an impressive evolution in the present century. The production of grains rose from 100 million tons in 2000/2001 harvest to 198 million tons in 2014/2015, most of it soya and corn. Sugarcane expanded impressively from 254 to 642 million tons in the same period (CONAB, 2015). Other biomass activities are also expanding quickly. Cellulosic Pulp 1217

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production has almost doubled in more than a decade from 2000 until 2013 from 7.4 to 15.1 million tons. These figures illustrate the productive dynamism of the Brazilian agro-industrial system. They result from land expansion but also of a deep increase in the land productivity, which is connected to an important process of technological learning. Crop varieties had to be adapted to the Brazilian soil and climate conditions, which varies impressively according to the region, state or even locally. At the other side Brazilian tropical climate conditions like the very high level of sun exposure or the lack of a cold winter season gave the opportunity to develop new agriculture technologies. The dynamism of the Brazilian agriculture is also fostering renewables technologies in the National Energy Matrix. Renewable energy had, in 2012, 42.3% of the country energy supply (EPE, 2014), which is much higher than world (13.5%) and OECD (9%) averages (IEA, 2014). This involvement is firstly related to biomass (27.5%), but unlike many others developing countries the greatest share (23.4%) belongs to modern biomass, which is deeply integrated in the agro-industrial production system. Brazil is the third in the world ranking of electricity biomass generation after United States and Germany, and almost 7.6% of all its domestic electricity supply is related to biomass conversion3, where sugarcane has a dominant role. The vitality of the Brazilian agriculture can be attributed to the junction of several factors. At one side there is a large potential of available land, even without the appropriation of forest and savannas ecosystems. There is close to 100 million hectares of degraded pasture lands that can be used by the agriculture. At the other side, Brazil has an innovation system formed by a set of public and private actors cooperating to develop new technologies or adapt the existing technologies to new ecosystems. The leading actor of the Brazilian agriculture – Embrapa - is a federal organization in charge of the main research efforts in this sector, but there are also several others state and private organization working for the development and adoption of new technologies.

THE BRAZILIAN SUGARCANE INNOVATION SYSTEM Sugarcane is a very active segment of the modern biomass agro-industry, which dynamism lends on a long-lasting technological learning process. The dynamic trajectory of the sugarcane agro-industry in Brazil started when this culture was progressively transferred from the Northeast region to the state of São Paulo. In the Northeast, sugarcane created a very conservative sociotechnical system based mainly in slavery, which was preserved with small changes after the end of this social regime. This sociotechnical system had a limited ability to introduce technological innovation and to produce local development. Because of its restricted food supply capacity, it became a serious constraint for the development the urbanization and the industrialization of this region (Furtado, 1959). Things started to change when this culture was introduced in the State of São Paulo, where capitalist social relations were better established. In this region sugarcane agroindustry emerged more dynamically, based in modern production techniques, surrounded by an industrial complex of equipment producers and by significant research institutions as the Agronomic Institute of Campinas (IAC) and the Agronomic School of Piracicaba (ESALQ). The expansion of the sugarcane production in Brazil was supported by the state of São Paulo. The sectoral innovation system for sugarcane production tended to expand more dynamically in the richest region of the country. And the dynamism of the São Paulo region was based in the conjunction of several factors from which one can emphasize the abundant good quality natural resources, better transport and 1218

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energy infrastructure, nearness to the country’s biggest market and, above this all, the insertion into a regional system of innovation which congregate producers, capital goods manufacturers, research institutes and universities. The region experimented gradual increases in its sugarcane productivity based on the varieties developed in the same region. For this reason, the Brazilian sugarcane innovation system is essentially from São Paulo. This region supports and sustains important institutions that are behind the dynamism of this system. The originality of the sugarcane innovation system in São Paulo is the supremacy of private research over the public one, although it was not always like this, contrary to the rest of the agro industry. Brazilian agricultural research is predominantly financed by the public sector. A study conducted by Embrapa (Beintema, N. M.; Avila A. F. D.; Pardey, P. G. 2001) estimated that Federal research institutions (mostly Embrapa) as well as the state ones and universities were responsible for 89% of the Brazilian research efforts on agriculture and cattle-raising. This does not seem to be the situation of the sugarcane sector. The most important sugarcane research center, the Centro de Tecnologia Canavieira - CTC, is a private institution. Federal Government has a limited contribution in this area, since the extinction of the IAA (Institute of Sugar and Ethanol), in the beginning of the Collor Government in the 90’s. The leading players of the São Paulo innovation system do research mainly in agriculture developing new sugar cane varieties. The increase of sugar cane yields measured by tons by hectare or the sugar content of the sugarcane were obtained developing new varieties more adapted to Brazilian weather and soil conditions, and also more resistant to plant diseases. This improvement allowed to reduce the ethanol cost, and to increase its production. However, important advances were also obtained in industrial plants by improving sugar juice extraction, vinasse reuse for land fertilization, improvements in the fermentation process and in the energy co-generation of bagasse. Alongside with research centers, the federal and São Paulo research funding organizations are also important to fund innovation and organize sugarcane and bioethanol technological programs. The innovation activities were mainly directed towards improving and perfecting the large sugar mills productive system, which was already established since mid of the last century. There wasn’t any radical innovation that could change drastically the productive process of sugar and ethanol. However, the productivity gains were expressive and placed Brazil at the first level in terms of production costs, while the use of bagasse reduced dramatically the fossil fuels and external electricity needs in the industrial process. Thus mainly based in an incremental technological trajectory, Brazil sugarcane ethanol became competitive in terms of costs, and also in terms of environmental sustainability, because of its low green house gas emissions (Macedo & Nogueira, 2004; EPA, 2010; Wang et al. 2012). As it was analyzed in a previous article (Furtado et al., 2011) and by several others authors (Dunham et al. 2011; Andersen, 2015) the Brazilian sugarcane innovation system have undergone several important steps and transformations since its constitution. Even though the production of biofuels was already in place almost since the 1930, the system was technologically laggard until the Proalcohol program was launched in 1975. Since that, the sugarcane production started to grow regularly. The program created a new market4 for sugarcane – biofuels – and at the same time directed credit facilities to fund new mills and land expansion. This favorable environment changed deeply in the middle of the 80’s when oil prices dropped and the Brazilian economy went through a deep crisis. Ethanol loosed its attractiveness, while government abandoned progressively its policy to promote biofuels supply and demand. Because of this political dismiss, local market ethanol scarcity happened in the beginning of the 90’s and resulted in the collapse of the new ethanol cars demand. However, the deepest change came in 1990 when the main public organization in charge of the sector, the Sugar and Alcohol Institute– IAA, was shut down. 1219

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The main public research program – Planalsucar - in charge of the modernization of the industry was also discarded. The bioethanol did not collapse because the sectoral innovation system was able to create new opportunities. Hydrated ethanol, used by pure ethanol cars, was progressively substituted by anhydrous ethanol consumed melted with gasoline. Sugarcane production was diverted to sugar external market that increased strongly since the 90’s. Almost at the same time private and public actors replaced the federal IAA system in its promoting role of the sugarcane agro-industry. The Planalsucar plant breeding program was replaced by Ridesa, a network of Universities that continued the previous public program with private funds from sugar mills. At the other side CTC private breeding program continued its development, and the Campinas Agronomic Institute breeding program recovered after a longstanding stagnation. The engagement of the State of São Paulo Research Agency – FAPESP - funding sugar cane basic research expanded. All this aspects demonstrated the great resilience of the Brazilian sugarcane innovation system that was able to adjust to new circumstances and finance with private funds its own research. In the years 2000, when the oil prices peaked again, making more attractive ethanol to car owners, the sugarcane innovation system and also the car industry were able to respond quickly to the new reality. The automotive industry introduced the flex fuel cars, solving the problem of the missing demand policy for pure ethanol, since the end of the Proalcohol program. This technology, by reducing the risk of the consumers, allowed the pure ethanol car market to increase again. The sugarcane production was able to expand quickly and the investments in sugar and ethanol mills started to grow again. These favorable conditions created the circumstances for a new cycle of expansion of ethanol and sugarcane (Figure 1). Figure 1. Brazil Sugarcane, Sugar and Ethanol Production Source: UNICA

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Thus, the technological trajectory of the Brazilian sugarcane innovation system rests mostly on incremental innovations, which means the improvement and adaptation of existing technologies inside a dominant technological system. Several authors (Dahlman & Westphal, 1982; Lall, 1982; Katz, 1987) studied this kind of technological change in developing countries, which initiates by a cumulative learning process on the implementation and use of imported technologies. Firms and others research institutions of the innovation system have to devote increasing technological efforts to improve the existing technologies and also to create the new ones. However, the possibility to maintain the technological capabilities created in the local learning process is allied to the relative stability of a dominant design or of a certain technological paradigm (Dosi, 1982). If the technological trajectory switches significantly, the capabilities connected with the prior technological system can easily be lost. According to this assertion, the fastening of the technological frontier can impair local capabilities and also make more difficult to follow up the technological frontier. Some authors in development economics diverge from this view about the real chances of latecomers to catching up advanced countries (Soete, 1985; Perez & Soete, 1988). According to them there is a great advantage to be a latecomer in times of important technological ruptures. They recognize that technological development has a cumulative nature, but asserts that when radical technological changes happens, newcomers are less engaged in large investments in the previous dominant technological paradigm than the leading countries. Because they can commit larger amount of resources in new dynamic technologies, technological ruptures can be windows of opportunity for latecomers. Other factors can contribute to these to these windows of opportunity as demand changes and policy-based regulatory changes (Lee & Malerba, 2013). In our opinion this approach is useful to explain how in XIX Century happened the catching up of Great Britain by Germany and United States, and in XX Century how North America and Europe were catch up by Japan and after by South Korea. China more recently seems to be reproducing this same evolution. However this kind of evolution poorly concerns much of the technological learning cases that happens in developing countries. It often occurs in mature sectors and are of an incremental and adaptive nature. In this context, as we will see as follows, changes in the selection mechanisms can jeopardize local learning process. In the present context, energy crisis and the challenges of a new low carbon economy are fastening the international technological regime and improving the technological efforts of developed countries and of some emerging countries in renewable energies. In this sense, the actors of the Brazilian sugarcane sectoral innovation system are trying to cope with these new challenges but there seem not always be prepared to it.

TECHNOLOGICAL DISCONTINUITIES IN BIOFUELS The energy prices upswing in the present century together with changes of the energy policy in several developed and developing countries has hastened technological change in new renewable energies. The very fast evolution in wind power and photovoltaic power generation technologies has impressively dropped the production costs in many countries, and they are becoming more and more competitive with the dominant fossil fuels technologies. Liquids biofuels have a similar challenge. Important technological discontinuities need to be introduced to make biofuel competitive with fossil fuels and to improve its supply at the size required by liquid fuel markets.

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The analysis about energy transition agrees that mature renewables energy technologies, called first generation, will not be enough to face this challenge. The first generation technologies applies fermentation to convert sugarcane juice or cornstarch into ethanol5. These technologies are almost mature and can be considered as the main factors of recent expansion of supply. However, these technologies are bounded by raw materials supply, and also by the fact that these cultures also compete for land against food and others industrial crops. To overcome the limits of first generation technologies, disruptive technologies called second or third generation technologies need to be developed and diffused (Johnstone et al., 2008). In the case of liquid biofuels, the most representative second generation biofuels technologies are enzymatic hydrolysis and biorefineries. In both cases, a greater diversity of raw material like biomass cellulose and agriculture residues are used to produce liquid biofuels. This promise has increased the technological efforts in second generation biofuels, especially because developed countries are feeling more deeply the constrain of raw material supply in the first generation biofuels. Second generation can process others biomass raw materials than food crops like cellulose rich crops, or treat the part of the biomass food crops that is not directed towards food consumption like straw and bagasse, commonly called agricultural residues. Cellulose rich biomass requires an additional conversion process into biofuels. Several possible technological routes can allow this conversion. One of the most promising technological process is hydrolysis, which can convert cellulose and hemicellulose into glucose. The acid trajectory is used since more than a century by chemical and food industry, but is not considered economically feasible because of its worse process conditions and a great quantity of residues. Meanwhile the enzymatic hydrolysis is a much more promising route. The developed countries like United States and Europe Union are investing large amounts of resources in this emerging technology (Pereira, Bomtempo & Chaves, 2015). At the other side, sugarcane plant breeding is also submitted to a similar technological evolution. The conventional methodologies used in sugarcane breeding are long lasting. A new sugarcane variety takes almost 12 years to be developed. New biotechnologies can shorten this period of time and be more precise in the development of more performing new plant varieties. In this sense, the use of gene markers can help to identify specific characters in new plants. New plants can also be genetically engineered. However, this kind of technology requires long legal tests process, which finally can last more time than conventional breeding methodologies. The transition to second generation technologies is changing the technological regime of liquid biofuels agro-industry. The hastening of the international technological frontier makes more difficult for developing countries, which accumulated local technological capabilities based on incremental innovations, to follow-up new technological developments (Katz, 1987). Thus, this quickening of the technological regime increasingly challenges the Brazilian sugarcane system of innovation, which was very successful in the first generation technologies. The Brazilian innovation system has different capabilities to cope with this challenge. Innovation system are defined as a set of technologies, actors of different natures as firms, universities, research centers and government, networks and institutions that are engaged in the generation, adoption and diffusion of new technologies (Lundvall et al., 2009). These innovation systems especially in developing countries can have missing links, weak institutions or missing organizations (Chaminade et al., 2009). Our main assumption in this chapter is that shorter the network of actors, greater are difficulties to follow-up the technological frontier.

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To understand the evolution of the Brazilian sugarcane system of innovation we separate the agriculture subsystem from the industrial subsystem. In the agriculture subsystem research efforts are higher and the linkages with basic research done in universities are stronger while in the industry side the R&D efforts and the connection with academic research are weaker. The agriculture subsystem functions in a STI (science, technology and innovation) mode while the industrial subsystem, which operates in a DIU (doing, using and interacting) mode (Jensen et al., 2007; Varrichio, 2012). In this sense, the agricultural subsystem demonstrated a better ability to cope with the technological challenges of the new biotech research methodologies while the capital goods industry has weaker propensity to deal with the second generation industrial technologies for bioethanol.

BRAZILIAN SECTORAL INNOVATION SYSTEM RESPONSE The years 2000 have brought new dynamics to the Brazilian innovation systems. At one side, there was an increasing concern from Federal and State Governments about the sugarcane and renewable bioethanol relevance for the national economic wealth. Federal Government decided to create the Centre of Bioethanol Technologies (CTBE) at the side of UNICAMP in 2009 and enlarged dramatically the funding channels to finance the productive expansion and the innovation in the sugarcane agro-industry. BNDES, the Brazilian National Development Bank, financed new mills, requiring more energy efficient co-generation facilities in these projects6. At side FINEP (Federal Innovation Agency) launched in 2006 the economic subvention program, a special non reimbursable account to finance innovation in firms. In 2007 and 2008 14 firms received R$ 65 million7 to develop new technologies, mostly second generation industrial technologies, biotechnologies applied to sugar cane, and new crop technologies. The federal government funding policy get a step forwards recently in 2011 when the PAISS program was launched. The BNDES in charge of funding new plant facilities, and FINEP financing innovation and R&D had their instruments put together in this program, allowing government to support radical innovations at a deeper level. Before, new technologies were only financed at the federal level until the laboratory stage but faced great difficulties to reach the preindustrial or industrial stage. With the new program, large firms have engaged innovation efforts towards the industrial plants in second generation technologies, making more feasible the whole innovation process. In this sense Federal Government innovation policy has learned from the past failures, and is trying to improve its efficacy. The change in the direction of the Brazilian biofuels innovation policy is also influenced by the USA and European experience at the same level. The financial amounts, the variety of funding instruments and the mechanism of coordination are larger and much more sophisticated in the similar American and European programs than in Brazilian case (Nyko et al., 2010). Trying to respond to this new technological challenge, the two federal agencies assigned R$ 1,57 billion to the PAISS program. The program is directed to 3 areas: 1) second generation biofuels; 2) new sugar cane products; 3) gasification. In the first call, 25 firms had their business plan approved mostly in the first and second areas (Table 1). The State of São Paulo is also a central actor of the sugarcane innovation system. Since the 1990, FAPESP (São Paulo Research Agency) has an increasing role funding basic research mostly in biotechnologies related to this cultivation. The Sugarcane Genome Project started in 1998. The advances made by this project were fundamental for the surge of a biotech firm like Alellix. After 2000 the agency engaged in the funding of industrial technologies as the Dedini HDR project of fast acid hydrolysis. FAPESP made several partnerships with important national firms like Braskem, ETH-Oderbrecht, Oxiteno and 1223

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Table 1. PAISS List of Firms with Selected Business Plan in 2011/12/16 by Funding Line Companies Abengoa Bioenergia Agroindustrial Ltda.

Line 1

Line 2

x

Agacê Sucroquímica Ltda.

x

Amyris Pesquisa e Desenvolvimento de Biocombustíveis

x

Barauna Comércio e Indústria Ltda.

x

BioFlex Agroindustrial Ltda.

x

BIOMM S/A

x

Bunge Açúcar e Bioenergia Ltda.

x

Butamax Biocombustíveis Avançados

x

CTC – Centro de Tecnologia Canavieira S.A.

x

x

Dow Brasil S/A

x

x

DSM South America Ltda.

x

x

Du Pont do Brasil S/A

x

Eli Lilly do Brasil Ltda.

x

ETH Bioenergia S.A.

x

x

Ideom Tecnologia Ltda.

x

Kemira Chemicals Brasil Ltda.

x

LS9 Brasil Biotecnologia Ltda.

x

Mascoma Brasil

x

Methanum Engenharia Ambiental Ltda. Metso Paper South America Ltda.

x x

Methanum Engenharia Ambiental Ltda.

x

Metso Paper South America Ltda.

x

Novozymes Latin America Ltda.

x

Petróleo Brasileiro S/A

x

PHB Industrial S/A

x x

Solazyme Brasil Oleo Renováveis e Bioprodutos VTT Brasil – Pesquisa e Desenvolvimento Ltda.

Line 3

x x

x

Line 1: second generation biofuels; Line 2: new sugar cane products; Line 3: gasification. Source: BNDES (available at http://www.bndes.gov.br/SiteBNDES/bndes/bndes_pt/Institucional/Apoio_Financeiro/Plano_inova_ empresa/paiss/resultado_planos_de_negocio.html); access in 2013/08/18.

Dedini for funding academic research. The more recent initiative was the FAPESP and ETH partnership, which approved in 2011, 11 research project amounting R$ 20 million. There is no doubt that at the side of innovative funding, new instruments were created to face the industry technological challenges. The problems came from the main actors of the industry itself and the lack of a demand policy for biofuels. To better understand this evolution, the sugarcane innovation system can be split in 2 main subsystems: The agriculture and the industrial subsystem. Agriculture subsystem concerns technology and knowledge related to sugarcane plantation and harvesting, while industrial subsystem is associated to sugarcane processing, and to sugar, ethanol and electricity production.

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The agronomic research is much stronger in the agriculture subsystem. There are already four sugarcane plant breeding programs (Ridesa, CTC, IAC, Alellix/Canavialis) that have in a way or another strong contact with academic research. Thus, the sugarcane agriculture subsystem can be labeled as a Science, Technology and Innovation system by the terms of Jensen et al. (2007), in which there is a strong linkage between academic and firm research. The discontinuity introduced by the genetic engineering technologies could be assimilated without great harm, in part due to the Fapesp Genoma project. The main problem came with the financial crisis of 2008, when Votorantin Group decided to sell Canavialis and Alellix to Monsanto. The acquisition of the two start-ups by the American multinational has broken the links between the academic research and the private sector in an important Brazilian initiative especially for genetic engineering. The strong tendency of privatization in the technological research has also provoked relational problems between Brazilian private and public research. CTC, which is a private R&D company, roughly restrained the access of its agronomic station for seedlings hybridization at Camamu in the State of Bahia to IAC program. The Agronomic institute of São Paulo had to create its own hybridization station near CTC to maintain its own genetic breeding activities. The industrial research is facing a similar technological discontinuity. The transition from 1st to 2nd generation means an important rupture with the previous technological base. However, the capital goods industry is the weakest actor of the national system of innovation. Even if Brazil is almost self-sufficient in capital goods for first generation bioethanol technologies, a study in 10 representative firms of these industries oriented to sugarcane industry revealed very limited technological efforts, especially in R&D (Varrichio, 2012). While 7 out 10 of this representative sample were large firms with more than 500 employees, only 2 had R&D activities. There innovation were mostly of an incremental nature and resulted from their close interaction with sugarcane mills. In the terms of Varrichio (2012), the maturity of 1st generation technologies almost of public nature makes the adaptive kind of innovation much more based on tacit knowledge. Thus, the industrial innovation subsystem is based in Doing, Using and Interacting mode of learning (Jensen et al., 2007). In this sense while having a great mastery of the 1st generation technologies, the local capital goods industry seems not to be prepared to face the 2nd generation challenge. The main reason is that the new knowledge related to second generation comes from biotech and chemical industry, while first generation is a traditional agriculture capital good industry. The only capital goods firm that was making significant technological efforts in this new area was Dedini. However the company for reasons related to the financial crisis interrupted its Acid Hydrolysis HDR semi-industrial project. This project in spite of having technical interest was outdated because of the dominant bet of the industry is in enzymatic hydrolysis technology (Silva, 2013). The way that the Brazilian industry is facing the scientific and technological challenge is by the entrance of new actors. Few local firms were engaged in the 2011 PAISS public offer (Table 1). In this program only Petrobras and CTC are committed with significant technological efforts of the 2nd generation biofuels and green chemistry. At the other side a great number are foreign owned firms like Abengoa, Amyris, Bunge, Dow, Dupont, Mascoma, Novozymes, Solazyme, had their own project approved in the program. Dedini, the capital goods national leader, couldn’t get inside in spite of its association with Novozymes. The loose of national control over the second generation technologies can be perceived in new biofuels industrial plants. These industrial projects are owned by local companies, but these firms have weak control over the main technologies. There are 2 important second generation industrial projects that have

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already started their activities in Brazil, which are using enzymatic hydrolysis to transform sugarcane bagasse and straw into bioethanol. The first case is Granbio, which is a private national group without industrial tradition that created a technology driven bioethanol company. This company launched in 2014/09 the first Brazilian enzymatic hydrolysis industrial plant at San Matheus, Alagoas. In spite of important efforts done in the development of new sugarcane cellulose oriented varieties and yeast for the conversion of the pentose into glucose, all the technology concerning the industrial process from pretreatment, hydrolysis until fermentation were transferred from an Italian company named Beta Renewables. The industrial capital goods were purchased from Biochemtex, and Novozymes has an exclusive supply contract of the enzymes. The yeast technology is licenced from DSM (Corrêa, 2014). Cosan, the Brazilian largest sugar and ethanol Company, has merged with Shell do Brasil establishing a new company called Raizen. Raizen wined the last subvention call of 2010 to build a flexible 2nd generation industrial plant and started producing 40 million litres of ethanol per year 2014/11. Iogen, a Canadian Company, licensed to Raizen all the process technology from pretreatment to fermentation. Novozymes has also an exclusive supplier contract for the enzymes (Corrêa, 2014). In this two cases, while the companies are totally or partially national owned, the control of the most important process technologies like pretreatment, hydrolysis and fermentation are completely controlled by new biotech foreign companies. The advances of the national companies happens in peripheral or complementary technologies like new sugar cane varieties or yeast. The only case of a greater control of national technology is CTC, the private research organization located in Piracicaba. CTC has already a patented hydrolysis process and is running a 1,000 liters by day pilot plant. However, in spite of being sponsored by PAISS program the industrial plant has no fixed date to be launched. Thus, it is clear the increasing difficulty of the Brazilian national industrials firms to cope alone with the technological discontinuity of the 2nd generation biofuels. Even in the case of strategic alliances, the level of technology transfer of core technologies is limited. This evolution is happening in spite of the federal government efforts to create appropriate funding and credit conditions for the Brazilian firms and new research organizations like CTBE (Centre of Bioethanol Technologies). The presence of foreign firms in the control of sugar and ethanol mills increased dramatically. In 2010, foreign firms controlled 28% of the Ribeirão Preto region in the State of São Paulo and 23% of the Unica mills (Folha de São Paulo, 03/11/2010). Informal estimate calculate that in 2013 this share has increased until 40%.

WHY THE BRAZILIAN SUGAR CANE PRODUCTION IS LAGGING? The technological evolution does not completely explains why the Brazilian sugarcane and particularly bioethanol production is lagging behind. These elements are connected to the business cycle that happened in sugarcane agroindustry during the last decade. In the beginning of the decade, there was a widespread expectation that Brazilian sugarcane production could increase continuously several times (CTBE, 2009). Effectively, the production more than double in a decade, rising from 254 million tons in 2000/2001 to 624 million tons in 2010/2011. However, thereafter the sugar cane production oscillated stabilizing in 650 millions in the last harvest (Table 2). Brazil lost its first place as a bioethanol producer

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to United States. Only after seven years of crisis Brazilian ethanol production is increasing reaching the score 29 billion liters in 2015/2016 harvest. Several factors can explain the slower evolution of the sugarcane agro industry since the 2008 crisis. At the first level, the Government has abandoned an effective demand policy since the end of Proalcohol at the beginning of the 90’s. During the program, IAA set ethanol prices in an advantageous parity with gasoline and guarantee the purchase of a predefined ethanol volume, like in the Feed-in tariff system, which was used by several countries to promote their renewable energies. However since the 90`s liberal reforms, the sugarcane industry had to face a competitive environment with no guarantee of fixed prices. This lack of demand policy was one of the main reason for the crisis because during a certain period of time, before and after the financial crisis of 2008, ethanol prices dropped dramatically in the internal market. The mills, which largely run into debt for expanding their activities in the previous period, get in red and had to cut their investment in the agriculture treatment. The result was a drop of the sugarcane land productivity. The second challenge, also related to a lack of an ethanol demand policy, is the Federal Government control of gasoline prices. Because of the widespread of flexfuel cars, ethanol price need to be competitive with gasoline prices. Given that Government determined the gasoline price under the general prices index, especially since 2010, the ethanol prices has gown down in real terms. Meanwhile sugarcane production cost increased substantially eroding the profitability of the industry. This lack of demand policy confronted bioethanol with a third challenge, which is the competition with sugar market for the use of sugarcane. A large portion of the mills in Brazil produces simultaneously ethanol and sugar. When ethanol prices dropped in the internal market the sugar prices raised at the international level. Thus the share of sugarcane processed for sugar production increased and the sugar production did not declined as much as ethanol (see Table 2). At the fourth level, the expansion of the sugarcane production motivated deep changes in the geographic distribution of this crop. Until the middle of the last decade, sugarcane was restricted to regions with high soil fertility and good weathers conditions, mainly the central and the Northern regions of the State of São Paulo. Since then sugarcane culture expanded to western areas of this State and to outside in the Middle West States of Brazil (Goiás, Mato Grosso do Sul, Minas Gerais) where the weather and the soils conditions are very different from the previous regions. These new expansion areas are mostly located in the Cerrado region, which is a certain kind of savanna that occupies the central part of Brazil. The adaptation of São Paulo sugarcane varieties to Cerrado’s weather and soil conditions do not seem to be an easy task. This requires important efforts of the sugarcane breeding programs. The largest Brazilian programs are attending to this challenge by displacing their agronomic research activities to central part of the country. The results are beginning to emerge. CTC has launched 3 new sugarcane varieties adapted to Cerrado’s conditions. The other challenge came from harvest mechanization. The use of mechanical harvesting in place of the hand cut traditional method is mainly the result of the evolution of São Paulo’s environmental legislation that obliged sugarcane growers to avoid sugarcane burning, which is a necessary step before hand cut harvesting. The mechanization became inevitable and disseminated very fast but it brought several problems like soil compression and the lack of qualified personnel to operate the harvest machines. Sugarcane varieties need also to be adapted to mechanical harvesting because machines can more easily cut erected plants. Sugarcane culture is incurring deep changes in its main work methodologies and in the natural environment where it is cultivated. The impact of these changes was translated in reduced productivity yields. 1227

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Another element contributing to the drop of crop yields was the more adverse climate conditions. These changes can be attributed in part to global climate change. The future climate scenarios point out that São Paulo weather conditions will be closer to the today’s Cerrado conditions.

FINAL COMMENTS The transition to a low carbon economy is a great challenge for the great majority of the developing countries. Most of their energy matrix is based in non renewable energy sources and their internal energy demand is increasing very quickly. Only a small group of the leading developing countries is making significant efforts to master and innovate in renewable sources of energy. China and at a lesser length India have great relevance in the wind and photovoltaic energies, but Brazil has a longstanding position in biomass, especially in bioethanol. This leadership is related to the strong technological dynamism of the Brazilian agro-industrial productive system. Renewables sources of energy, and specially biomass, have a strong share of the Brazilian energy matrix. Based on favorable natural resources endowments alongside with long term innovation policies the Brazilian sugarcane innovation system bring about a longstanding learning process in bioethanol that gave an important leadership to Brazil in the 1st generation bioethanol. However the Brazilian leading position in bioethanol is challenged by the speeding-up of the technological frontier motivated by the transition from 1st generation to 2nd generation biofuels technologies, and also from traditional breeding technologies to modern biotechnologies. The Brazilian sugarcane innovation system is losing its coherence and its leadership. The difficulty seems higher in the industry subsystem of innovation, which is oriented towards incremental innovation and is based in doing and using kind of learning. In this subsystem the Brazilian capital goods industry are little alike to follow-up fast changes in the technological base. The only local industrial firms that are intending to move behind like Oderbrecht, Braskem, Raizen and Petrobras belongs to chemical and oil industry and are acquiring hydrolysis technology from foreign sources. At the other side foreign companies infiltrated deeply the Brazilian innovation system. This entrance of external influences cannot only be considered negative for Brazil because it’s allowing the national system to cope with modern technologies, nevertheless it reveals clearly the increasing difficulties of the traditional Brazilian capital goods firms to become players in this new innovative environment. In the agriculture subsystem the situation seems more favorable. The connection between industry, agronomic research centers and universities is much more intense. Several public and private initiatives are intending to introduce new biotech technologies in the sugarcane breeding programs. However, the transfer of Alellix and Canavialis to Monsanto control has also weakened the cohesion of this subsystem. Thus the main assumption that shorter the network of actors, greater are difficulties to follow-up the technological frontier was confirmed in the two different technological subsystems. In the agricultural subsystem the larger network of innovation, including research institution, makes it more adaptable to the technological transition to the biotechnology, while in the industrial subsystem limited capabilities and short network restrained the ability of capital good industry to attend to the challenge of second generation technologies.

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The problems of the Brazilian innovation system are not limited to the loose of national control. The stabilization of the ethanol production in the last years reveals a structural fragility of the energy policy that was unable to create appropriate conditions for a regular expansion of the supply. The increase of the production requires the displacement of the sugarcane culture to new area, which are creating new technological challenges that needs also to be faced.

REFERENCES Andersen, A. D. (2015). A functions approach to innovation system building in the South: The preProálcool evolution of the sugarcane and biofuel sector in Brazil. Innovation and Development, 5(1), 1–21. Beintema, N. M., Avila A. F. D., & Pardey, P. G. (2001). P&D Agropecuário no Brasil. Política, Investimentos e Perfil Institucional [Agricultural R&D in Brazil. Policy, Investments and Institutional Profile]. Washington, DC: Instituto Internacional de Pesquisas sobre Políticas Alimentares, Empresa Brasileira de Pesquisa Agropecuária, Fundo Regional de Tecnologia Agropecuária, August. CGEE (Centre of Management and Strategic Studies). (2009). Bioetanol combustível: uma oportunidade para o Brasil [Bioethanol fuel: an opportunity to Brazil]. Brasilia, DF: CGEE. Corrêa, C. (2014). Parcerias Estratégicas Tecnológicas em Projetos de Etanol Celulósico: Oportunidades e Desafios Para as Firmas Nacionais. [Cellulosic Ethanol Strategic Technological Partnerships Projects: opportunities and challenges for the national firms]. (Unpublished master dissertation), University of Campinas, Campinas, Brazil. Dahlman, C., & Westphal, L. (1982). Technological effort in industrial development – an interpretative survey of recent research. In F. Stewart & J. James (Eds.), The Economics of New Technology in Developing Countries (pp. 105–137). London: Frances Pinter. Dosi, G. (1982). Technological paradigms and technological trajectories: A suggested interpretation of the determinants and directions of technical change. Research Policy, 11(3), 147–162. doi:10.1016/00487333(82)90016-6 Dunham, F. B., Bomtempo, J. V., & Fleck, D. L. (2011). A Estruturação do Sistema de Produção e Inovação Sucroalcooleiro como Base para o Proálcool [The Structuration of Sugar and Alcohol Production and Innovation System as the Base for the Proalcohol]. Revista Brasileira de Inovação, 10(1), 35–72. EPA (Environmental Protection Agency). (2010). EPA Lifecycle Analysis of Greenhouse Gas Emissions from Renewable Fuels. Regulatory Announcement, Office of Transportation and Air Quality, EPA-420-F-10-006, February 2010. Furtado, A., Scandiffio, M., & Cortez, L. (2011). The Brazilian sugarcane innovation system. Energy Policy, 39(1), 156–166. doi:10.1016/j.enpol.2010.09.023 Furtado, C. (2001). Formação Econômica do Brasil. [Economic Formation of Brazil]. São Paulo, SP: Companhia Editora Nacional. Goldemberg, J., & Coelho, S. T. (2004). Renewable energy—traditional biomass vs. modern biomass. Energy Policy, 32(6), 711–714. doi:10.1016/S0301-4215(02)00340-3 1229

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IEA (International Energy Agency). (2012). CO2 Emissions from fuel Combustion – Highlights. Paris: IEA-OECD. IEA (International Energy Agency). (2013). World Energy Outlook 2013. Paris: IEA-OECD. IEA (International Energy Agency). (2014). Key Energy Statistics 2014. Paris: IEA-OECD. Jensen, M. B., Johnson, B., Lorenz, E., & Lundvall, B. A. (2007). Forms of knowledge and modes of innovation. Research Policy, 36(5), 680–693. doi:10.1016/j.respol.2007.01.006 Katz, J. (1987). Domestic Technology Generation in LDCs: A Review of Research Findings. In Technology Generation in Latin-American Manufacturing Industries (pp. 13–55). London: Macmillam. doi:10.1007/978-1-349-07210-1_2 Lall, S. (1982). Technological learning in the Third World: some implications of technological exports. F. Stewart & J. James (Eds.), The Economics of New Technology in Developing Countries (pp. 157179). London: Frances Pinter. Lee, K., & Malerba, F. (2013). Changes in Industrial Leadership and Catch-Up by Latecomers: Toward a Theory of Catch-up Cycle from Eight Sectoral Studies. Proceedings of Globelics, 13, 11. Macedo, I., & Nogueira, L. A. (2004). Biocombustíveis, Cadernos NAE, nº2, julho. Brasília: Núcleo de Assuntos Estratégicos da Presidência da República, Secretaria de Comunicação do Governo e Gestão Estratégica. Milanez, A. Y., & Nyko, D. (2012). O Futuro do Setor Sucroenergético e o Papel do BNDES [The Future of Sugar cane industry]. BNDES Setorial. Retrieved May 15, 2015, from: http://www.bndes.gov. br/SiteBNDES/export/sites/default/bndes_pt/Galerias/Arquivos/conhecimento/livro60anos_perspectivas_setoriais/Setorial60anos_VOL2Biocombustiveis.pdf Nelson, R., & Winter, S. (1977). In search of a useful theory of innovation. Research Policy, 6(1), 36–76. doi:10.1016/0048-7333(77)90029-4 Nyko, D., Garcia, J. L. F., Milanez, A. Y., & Dunham, F. B. (2010). A corrida tecnológica pelos biocombustíveis de segunda geração: uma perspectiva comparada [The second generation biofuels technological race: a comparative perspective]. BNDES Setorial, 32, 5-48. Retrieved May 15, 2015, from: http://www.bndes.gov.br/SiteBNDES/export/sites/default/bndes_pt/Galerias/Arquivos/conhecimento/ bnset/set32101.pdf Pereira, F. S., Bomtempo, J. V., & Alves, F. C. (2015). Programas de subvenção às atividades de PDI: uma comparação em biocombustíveis no Brasil, EUA e Europa [RD&I subvention programs: a comparison between Brazil, USA and Europe in biofuels]. Revista Brasileira de Inovação, 14, 61-84. Perez, C., & Soete, L. (1988). Catching up in technologies: entry barriers and windows of opportunity. In G. Dosi, C. Freeman, R. Nelson, G. Silverberg, & L. Soete (Eds.), Technical Change and Economic Theory (pp. 454–479). London: Pinter Publishers. REN 21. (2013). Renewables Global Futures Report. Paris: REN21.

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Silva, G. (2013). Aprendizado do etanol celulósico no Brasil: o caso do projeto Dedini Hidrólise Rápida (DHR) [The Cellulosic Ethanol Learning in Brazil: the case of Dedini Fast Hydrolisis Project]. Univerersity of Campinas. Soete, L. (1985). International Diffusion of Technology, Industrial Development and Technological Leapfrogging. World Development, 13(3), 409–422. doi:10.1016/0305-750X(85)90138-X Varrichio, P. V. (2012). Uma análise dos condicionantes e oportunidades em cadeias produtivas baseadas em recursos naturais: o caso do setor sucroalcoleiro no Brasil [An analysis of the opportunities and conditioning factors in resource based production chain: the case of sugarcane industry]. (Unpublished doctoral dissertation). University of Campinas, Campinas, Brazil. Wang, M., Han, J., Dunn, J. B., Cai, H., & Elgowainy, A. (2012). Well-to-wheels energy use and greenhouse gas emissions of ethanol from corn, sugarcane and cellulosic biomass for US use. Environmental Research Letters, 7(045905). Retrieved from stacks.iop.org/ERL/7/045905

ENDNOTES

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In 2012, fossil fuels satisfied 80% of the total energy needs of non OECD countries, while renewables responded for 16.3% (IEA, 2014). Even in its 450 Scenario, IEA estimates that non OECD energy demand will increase 7.4 billons toe in 2011 to 9.6 in 2035 (IE, 2013). The biopower capacity in United States was 15.8 Gw that produced 60 TWh in 2013, Germany had an 8.6 GW capacity with an 48 TWh electricity supply while Brazil had 11.4 GW capacity that generated 46.4 TWh. (Ren 21, 2014). The market wasn’t completely new because ethanol was mixed to gasoline in small proportion (E05) since the 1930’s. However Proalcohol program established a E20 mixture and afterwards created the pure ethanol market. Cornstarch need previously to be converted into glucose before being fermented. Total BNDES disbursements to sugarcane industry amounted 42.8 billions reals (2011 values) between 2000 and 2011 (Milanez e Miko, 2012). The exchange rate is approximately 2 reals = 1 US$.

This research was previously published in the Handbook of Research on Driving Competitive Advantage through Sustainable, Lean, and Disruptive Innovation edited by Latif Al-Hakim, Xiaobo Wu, Andy Koronios, and Yongyi Shou, pages 228-243, copyright year 2016 by Business Science Reference (an imprint of IGI Global).

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Section 5

Organizational and Social Implications

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Chapter 56

The Collective Aestheticization of Farming as Participatory Civic Engagement Cala Coats Stephen F. Austin State University, USA

ABSTRACT This chapter is a case study that traces the life of a young artist farmer who developed a community-based educational farm. The case study illuminates networked connections between small-scale farming, a revitalized interest in handmade production, and a burgeoning desire for a living ethics rooted in direct engagements. This chapter reveals the breadth of the handmade revolution, tracing a singular example to investigate the desire to become a small-scale farmer; the network of apprenticing makers, farmers, and artists; the necessary participatory aestheticization of the farm as a marketing strategy and mode of cultural consumption; and the ethical complexity of sustaining the life of a young farmer in the current organic and locally-grown marketplace.

I drove up the path to Amanda’s new house. Typically, there were volunteers, friends, or the other farm staff there. Today, she was home alone. I went into the kitchen, and she was warming butternut squash soup and cornbread that she made the day before. We took our bowls outside and sat on a park bench in the lawn. We talked about what was happening in our lives, and she explained how different she felt now that she owned her own home. She told me she needed to move some greenhouses that had been donated from a church nearby, so I offered to help. We drove to a field, where five large greenhouse frames stood. They were composed of rows of steel beam arches fixed into pegs in the ground. I had never been in a greenhouse, much less a constructed one. Amanda needed help dismantling two of them, and her farm apprentice would be out soon. My job was to remove a series of rusted bolts from a bar that ran down the center and connected all of the arched poles. It was relatively dangerous. I had to stand atop a ten-foot ladder and repeatedly use my left hand to hold a nut in place, while unscrewing a rusted bolt from the bar with my right hand. DOI: 10.4018/978-1-5225-9621-9.ch056

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 The Collective Aestheticization of Farming as Participatory Civic Engagement

Up to that point, I had developed a relationship with Amanda through her role as a research participant in the work that led to this paper. Over the year that we had been working together, I had joined her CSA and my son had attended her Young Farmers classes. Our friendship always felt mediated by her as research participant or me as researcher, customer or client. The research seemed to structure the relationship, but the work on the greenhouses—outside in a field, as a friend—that was different. It was how I had wanted to be involved. I think I wanted her to see that I was not some bullshit academic, buried in books and theory. Construction and manual labor were common weekend activities for my family when I was growing up. We often came together to help whomever was moving or improving their house. Work was compensated with chicken and beer for the adults, and the kids would help if they were old enough. I had not lived near my family for over a decade and had forgotten about those experiences until I started this research on DIY practices and artists’ homes. This day with Amanda reminded me how much I learned through those experiences with my family. I got all the bolts out, and the next step was dismantling the whole thing. I was there for four hours. It was a big task. I felt strong and proud. I had almost passed on the chance to help her that day because I felt overwhelmed with the stress of work, school, and family. All of that swirling in my mind from the morning had stopped. This felt like doing something that mattered.

INTRODUCTION Amanda developed a working and educational farm in 2010 called, Cardo’s Farm Project (CFP). My work with her was one of a group of case studies that focused on the homes of artists and makers to consider how their current art practice was shaped, in part, by histories of formal and/or informal arts education. Amanda was a young artist, who had recently graduated with a degree in painting and drawing. The site of CFP was a working farm, residence, and educational center. Through the farm, she offered educational programming, which “uses sustainable agriculture to engage the community, empowering youth adults to learn the source of our food, connect with the land, and to take responsibility for positive change” (Cardo’s Farm Project, 2014). Amanda was interested in the educational and communitybuilding potential of environmentally conscious agricultural work. As the quote suggests, she is focused on individuals’ potential to realize their role in affecting “positive change.” CFP is one example of an increasing interest in localized agricultural work, urban farming, and hands-on production in response to factory farming, increasing globalization of food systems, and genetic modification. Post-Fordism1 and our globalized economy have exacerbated physical and cognitive disconnects from agricultural and textile production that was born from industrialization (Hardt & Negri, 2004; Jeppesen, 2011; Thrift, 2012) – facilitating the often-overlooked exploitation of many life forms. This chapter explores one example of a renewed and expanding interest from artists in local farming and agriculture as an ecological expression of their art practices. By tracing Amanda’s early influences, her choices during art school, internship at a social justice farm, work with contemporary artists in New York, and finally developing her own educational farm, this paper illuminates farming as one offshoot of participatory aesthetics (Bishop, 2012b) in response to neoliberal globalized capitalism.

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Over the last three decades, a movement merging craft and activism has grown in popularity. These material practices stem from a shift in values and are part of broader activist efforts for human and animal rights, environmentalism, and food justice as modes of cultural resistance to corporate globalization (Holtzman, et. al, 2005; McKay, 1998; Spencer, 2005). These modes of resistance are not without contradictions, as many of these practices have been co-opted by corporate entities to develop lifestylemarketing campaigns based on a craft aesthetic and embedded in neoliberal rhetoric about individuation, choice, freedom, and a knowledge economy (Bishop, 2012a). Small-scale and local farming have gained broad attention (Inwood, 2010; Meehan, 2012; Spaid, 2012) as part of this broader craft and hands-on revolution, as some call it (Levine, 2008). In Amanda’s story, we see networks of apprenticing makers, farmers, and artists that illuminate the local/global relationship of agriculture-cum-art in response to the increasingly biopolitical terrain of food, art, and education. By mapping her process, the complexity of resisting global capitalism through localized, hands-on efforts with an emphasis on embodied learning and collective action is illuminated. Moreover, her story is an illustration of the contemporary cultural desire for participation and consumption as event (Bishop, 2012b; Dunlap, 2013; Kalin, 2014; Kester, 2011). Amanda frequently incorporates hands-on experiences for visitors, customers, and students as a form of cultural participation; the act of farming, selling, and teaching become communal and aestheticized, and her agricultural output, farm, home, and lifestyle become commodities (Schaefer, 2013). But just as in my narrative, brief evens of direct engagement can produce the shallow satisfaction that we have performed a civic duty, overlooking vast systemic inequality that has become invisible through globalization. The farm illuminates the messy spectrum between resisting neoliberal capitalism and becoming subject to it, considering how the farm owner must negotiate and perform to our globalized economy to stay viable. The chapter is ordered through education, art, and farming. I focus on themes of collective effort, fundamental skills, participatory civic engagement, and sacrifice to explore contemporary social conditions produced from neoliberal global capitalism through Amanda’s story. I start by contextualizing the growing popularity of small scale farming in relation to histories of craft and community engagement as an art of resistance. Then, I trace Amanda’s process of coming to and developing the farm through her art practice. Finally, I analyze ways that Amanda’s experiences illuminate the complexity of the current relationship between craft activism and neoliberal capitalism, where “so many other aspects of this art practice dovetail even more perfectly with neoliberalism’s recent forms (networks, mobility, project work, affective labor)” (Bishop, 2012a, p. 39).

AESTHETIC ACTIVISM IN RESPONSE TO INDUSTRIALIZATION At each historical moment participatory art takes a different form, because it seeks to negate different artistic and sociopolitical objects. In our own times, its resurgence accompanies the consequences of the collapse of really existing communism in 1989, the apparent absence of a viable left alternative, the emergence of contemporary “post-political” consensus, and the near total marketization of art and education. The paradox of this situation is that participation in the West now has more to do with the populist agendas of neoliberal governments. Even though participatory artists stand against neoliberal capitalism, the values they impute to their work are understood formally (in terms of opposing individualism and the commodity object), without recognizing that so many other aspects of this art practice

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dovetail even more perfectly with neoliberalism’s recent forms (networks, mobility, project work, affective labor). (Bishop, 2012a, p. 39) As early as the Arts and Crafts movement, William Morris used creative and material practices to question capitalism, industrialization, and the increased fragmentation of humans from nature (Efland, 1990; Zabel, 1993). Dewey (1916/2007) later questioned how the spaces of institutional education and pedagogical content of public schooling were intrinsically removed from everyday life and argued for an enlivened way of being in the world as a form of living aesthetics (Efland, 1990). Progressive education of the 1930s was a form of social reconstruction encouraging skills and practices, including arts and craft production as part of everyday life, unifying communities through a pragmatic and problem-based education (Efland, 1990). Similar efforts to merge craft production as way of being in the world can be seen at the Bauhaus, Jane Addams Hull House, the Owatonna Project, and Black Mountain College. Each of these sites used craft as a form of education and civic engagement, where creative participation in the everyday functioned collectively and as a certain amount of political resistance. A similar form of social reconstructivism emerged in the 1960s and 70s as part of the arts-in-education movement. Again, proponents argued against the fragmenting force of “disciplining” education, where art is set apart as a creative practice (Efland, 1990). They promoted problem-based learning in local environments, through activities that functioned as necessary skills for life, and saw art as integral to all subjects. Unlike the Progressivist efforts of the 1930s, arts-in-education advocates of the 1960s and 70s looked to the work of performance artists and encouraged the direct involvement of practicing artists in educational settings (Efland, 1990). Since the 1970s, politically active cultural groups driven by a DIY ethic have revealed alternatives to the increasing power of corporate capitalist structures often using participatory approaches to intervene in daily acts of consumption (Duncombe, 1997). These types of interventions in state and civil society are geared at changing or highlighting inequality in the everyday. Artistic interventions in the everyday become increasingly visible primarily during times of broad social upheaval or political transition. This ethic has reemerged in the last two decades in response to the ubiquitous nature of corporate capitalism in every aspect of life. Unlike previous public efforts to combat unjust labor conditions and social inequality that took the form of labor unions and public protests, the networked nature of our contemporary global economy has produced the necessity for equally networked forms of resistance. These efforts attempt to intervene on individual, grassroots, and systemic levels. In the late 1990s, Green (1999) identified new genre public art education as a combination of traditional and non-traditional art methods merging art and life to make socially-conscious art. She promoted socially-based pedagogy through constructive projects with the use of critical thinking strategies in community-based art education that work with and in the community to develop problem-solving skills that are socially relevant and merge art and life. Neoliberal capitalism today makes resistance different than it has been in previous generations. An increasing desire for post-politics and anti-intellectualism have created conditions where creative resistance must tactically engage participants and viewers in activities that open new modes of understanding without overtly supporting a political agenda. Many artists and activists start with their local environment, focusing on place as a generative concept. Pedagogies of place (Callejo Perez, Fain, & Slater, 2004; Ellsworth, 2005; Gruenewald, & Smith, 2008) draw attention to the vitality of a physical setting to instruct, oppress, structure, and inspire. In art education, place-based studies often focus on the potential of learning beyond the institutional setting, into domestic spaces (Ballengee Morris, 2000; 1236

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Congdon, 2006), public places (Duncum, 2011; Trafi-Prats, 2006, 2009), in the natural environment (Blandy & Hoffman, 1993; Garoian, 1998, jagodzinski, 1987), and through direct engagements with built environments (Gude, 2004; Powell, 2008, 2010). Others argue the institutional environment’s potentially negative impact across ecologies (Graham, 2007; Wallin, 2007). Environmentally-conscious research in art education has questioned the hierarchy of humans over the environment (jagodzinsky, 1987) and “demonstrate the interdependence of all living and non-living things” (Blandy & Hoffman, 1993, pp. 24-25). Scholarship about place is often rooted in environmental awareness and the desire to affect change in local and global communities.

ART AS PARTICIPATORY CULTURAL ENGAGEMENT First, there is growing interest in collaborative and collective approaches in contemporary art. And second, … there is a movement toward participatory, process-based experience and away from a ‘textual’ mode of production in which the artist fashions an object or event that is subsequently presented to the viewer. (Kester, 2011, pp. 7-8) Kester (2011) describes two modes of participatory art, collaborative and participatory, that have emerged in part from the fragmented character of our contemporary society embedded in neoliberal conditions. Kester (1998) claimed, “the current political moment demands an activist aesthetic based on performativity and localism…. An activist art…defined as an intersubjective ‘communicative action’” (p. 15). Kester positions activist art as performative act in the local. This approach also parallels a shift to the relational in contemporary art considered by Bourriard (2002) as, “the realm of human interactions and its social context” (p. 14). Similarly, Bourriard (2002) highlights contemporary possibilities of work that addresses “learning to inhabit the world in a better way, instead of trying to construct it based on a preconceived idea of historical evolution” (p. 13). Such a conception of the centrality of newly generated forms of social relations is essential to the idea of an activist art that engages questions of politics and power relations. Art based in relational encounters can have a superficial effect, though, of lulling viewers and participants into the notion that they have become politically active, or performed as active members of society. Bishop (2004) argues that the very messiness of contemporary artistic activism is critical to its efficacy, embracing the destabilizing meaning of relational aesthetics, and claiming that congenial encounters are not enough to produce critical affects. Instead, a critical situation must express a relational antagonism that troubles customary modes of representation “going to public space to engage with ways that participants perceive ‘conflict, division, and instability’” (Bishop, 2004, p. 65) in local communities. The resulting discomfort of defamiliarized experience can trouble subjectivities in ways that illuminate new possibilities. Artist activists have become interested in Socially Engaged Art, which embodies a pedagogy of ethical encounters that rely on the performative aspects of our lives in the world and an emphasis on affect. Helguera (2011) describes a social interest in contemporary art, where artists are “interested in creating a kind of collective art that affects the public sphere in a deep and meaningful way” (p. 7). A shift to a socially engaged art involves a focus on public participation that is local, performative, and often political. These political and public shifts to a performative action are emerging in response to increased private ownership of all public space, as well as an institutional critique of the state, the school, and the art 1237

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world. Artists, educators, and scholars are coming together publicly as members of larger communities to enact change and attempt to produce a collective intersubjective shift in our global society through direct engagement (Thompson, 2014). Socially engaged art aims to disrupt and transform “through a form of practical or experiential production, the outcome of which is not predetermined” (Kester, 2011, p. 185).

Farming as Socially Engaged Art Small local and urban farms operate through the same hands-on ethos that is driving craftivism and socially engaged art. Today, common public spaces, such as malls, parks, and shops are typically constituted at least in part by capitalist forces. In response, the handmade revolution described above along with other forms of craft activism have made an effort to intervene in these sites to resist globalized capitalism. Farmer’s markets and local or urban farms have become popular spaces of civic engagement through interactions directly with farmers, craft artisans, and their land. Participatory and socially engaged art have infiltrated the public sphere in an effort to activate political discourse in the commons. Practitioners, which are often artists, are interested in bringing people together through collective, firsthand engagements with agricultural work to eliminate the cognitive and corporeal fracture historically constituted through capitalist production. While the popularity of farming and local agriculture has increased, artists are also responding to and engaging with farming. Farms have been represented in artwork for centuries, from pastoral landscape paintings to the photographs created by the WPA. Paralleling contemporary shifts toward participatory art, farms have taken on a performative role for artists today. Links between art and farming are now being investigated in relation to similarities of process and activities of production, and less for as commodities or modes of representation (Barney, 2009). Contemporary artists are using processes embedded in farming and the construction of farms in a variety of ways and locations, including urban lots, abandoned fields, and community sites (Meehan, 2012; Spaid, 2012). Sue Spaid curated an exhibition addressing forty years of farming as art in the Contemporary Arts Center in Baltimore in 2012. Art dealer Cynthia Mulcah, and artist Robert Hamilton developed a farm as a community center in the middle of an urban area in South Dallas. These are just two examples among many of ecologically minded artists and cultural workers developing green spaces and/or educational programming around combined efforts between art and farming. As I introduce Amanda’s narrative in the following sections, I view her farming practice and her aesthetic practices as performative craft production. In her story, we see networks of apprenticing makers, farmers, artists, and educators that illuminate the local/global relationship of agriculture-cum-art in response to the increasingly biopolitical terrain of food, art, and education.

Methodology This research was part of a two-year inquiry that considered how narratives embedded in the objects and material elements of artists’ and makers’ homes might teach about ways that subjectivity was produced through their social and material practices. To understand the singular and systemic aspects of Amanda’s farm project, I approached the research through a methodological bricolage (Kincheloe, 2005) that included traditional ethnographic methods, cultural and historical research, and autoethnography. Over the course of two years I made initial formal visits to the original site of her farm project to administer two formal interviews with tours of the site and many informal visits and interactions during which I learned 1238

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how the ideas shared in the initial visits were lived. During the research, my children took part in the educational programming offered at CFP, and I joined her community farm share program, which is a form of Community Supported Agriculture (CSA). I also volunteered time to help with tasks associated with the farm, such as the experience described in the opening of the chapter. In addition to experiences on the farm, I interacted with Amanda in public spaces, such as the local farmer’s market. Data included interview transcripts, photographs, personal reflections, publicly posted and online artifacts produced to advertise her project, and historical and cultural research. Amanda was the last participant I met, and her home was an anomaly for a number of reasons. Amanda’s domestic space, which shifted during the research process, was unusual because the home was on the farm that also served as the site of her small business. In the two years that we worked together, she moved from a trailer located on the original site of CFP to her own home on acreage that would continue to serve as Cardo’s Farm Project but as a more independent business venture. As a result of this overlap, I was able to learn about Farm Based Education, the small farmers movement, and challenges of developing a local agricultural operation. All of these factors intersected with her background as an artist and her interest in histories of female farmers. I use Amanda’s narrative to consider how the farm project as business and educational site illuminates the complexity of neoliberal globalization, where participation is both aesthetic and civic engagement and simultaneously a marketing strategy. To analyze the data in response to these questions, I consider how Amanda’s choices, sacrifices, opinions, and material practices highlight potential for broader collective efforts and illuminate the systemic conditions that limit them.

ARTIST-CUM-FARMER In this section, I describe Amanda’s influences, education, and experiences that produced the shift from being a practicing artist to a developing CFP. As noted earlier, a renewed interest in craft has emerged in part as a response to global capitalism. Many artists are drawing attention to the importance of fundamental skills, such as gardening and sewing as a way of developing a sense of agency in relation to material necessities and of living with less dependency on globalized capitalist production. The argument exists that there is no way to live outside of capitalism, but many artists and makers feel that highlighting the significance of skills in fundamental material production is one small mode of resistance.

Art and Education but Not Art Education Women’s narratives and an interest in fundamental skills fueled Amanda’s concentration on craft and agricultural knowledge, but her institutional education in art in public school and the university have equally influenced her desire to become an educator, artist, and farmer. A nurturing art teacher, Ms. Wilson, helped Amanda develop confidence in her drawing skills. As she thought about going to college, she saw Ms. Wilson as a model for future potential. Amanda decided to pursue art education and studio courses in painting and drawing at the university. She considered art education a subject that was about usable skills that were physical and productive—information that could be applied. After one art education course, she decided not to continue a traditional certification route. As she explained,

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And then I dropped the art education. Because I, well, I took one class, and I was like, ‘these people are going to educate children about art? We’re not even making art.’ They don’t know anything about art. It didn’t make any sense to me. (Amanda, personal communication, February 19, 2013) As I heard Amanda say this, I wondered what would have turned off someone who genuinely cared about making art and had a sincere desire to educate. What is art education training? I will explore possible answers to this question and how this experience is not unusual in the discussion at the end of this chapter. Amanda decided to take her desire to educate to community work instead, focusing on farm-based education and craft in community settings.

Hidden Villa and Social Justice To learn about farm-based education while finishing her art degree, Amanda took an internship at an educational farm outside of San Jose, California. “Hidden Villa is a nonprofit educational organization that uses its organic farm, wilderness, and community to teach and provide opportunities to learn about the environment and social justice” (Hidden Villa, 2014). Hidden Villa invited school and community groups out to engage in learning experiences through direct contact with animals and agriculture. Its approach is rooted in farm-based education (FBE). FBE is, ...a form of experiential, interdisciplinary education that connects people to the environment, their community, and the role of agriculture in our lives. Farm-based education promotes land stewardship, the value of meaningful work, and supports the local food systems that sustain us. (Farm Based Education Network, 2014) This focus on direct engagement with the land through experiential and interdisciplinary learning was critical to Amanda. Just as Amanda was drawn to the stories of her grandmother’s large family where each sibling played a role in the family’s well-being, FBE can instill a sense of purpose in students. This type of education does not just take place at farms. We can see similar experiences in urban and school-based gardens (Inwood, 2010). Students are able to take ownership over something and nurture its growth. I think kids are really good at picking up on where they are in the world and in a system whenever they are asked to be the caretaker of the animal or the plant. And then they know that this is my responsibility to care for this and then they are working next to each other and they are trying to figure it out and how to do and how to use the tools – like all of this confidence building. (Amanda, personal communication, April 5, 2013) In addition to developing sensitivity to all life forms, FBE promotes social justice through the experience of being on the land together and in teaching about what it means to take only what you need and build consideration for the larger global community through a collective responsibility. The founder of Hidden Villa started the first multi-racial summer camp in 1944 with the idea that children playing outside together might be able to forget their socially constructed differences at least temporarily. The Duvenecks, who had purchased Hidden Villa in 1924, had an ongoing mission of using the land to advance social justice. 1240

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In addition to starting the first multiracial summer camp, they “sheltered refugees fleeing from the Nazis, assisted Japanese-American families returning from internment camps, and hosted groups for social and educational reform.” Later the family “opened their home to the United Farm Workers movement in the 1960s and provided a safe space for Cesar Chavez to organize California’s first farm workers strike” (Hidden Villa, 2014). Social justice is woven into farm-based education as people come together to care for the environment and for each other through direct engagement and personal responsibility. Amanda highlighted the kind of camaraderie that develops among those who are working together to build a local garden or a large farm. It is a kind of camaraderie that children and adults alike often lack in our globalized and media-driven society.

Performing the Farm Through Collective Responsibility and Fundamental Skills When Amanda returned for her last year of school, she visited Cardo’s Sprout Farm. She had other friends who had volunteered there and thought it might be a good place to continue exploring FBE. During her final year of school, Amanda was growing and delivering sprouts for Cardo while pulling together her final work for her BFA show. Her internship in California the previous summer revealed to her the potential for teaching and learning through work on the farm. There she saw a new domain for teaching. Amanda’s grandmother influenced both the subject matter and ethical drive for her shift to farming and her art practice. Her grandmother was a seamstress who lived on a small farm. Amanda learned to sew from her when she was young. Together they would crochet and make quilts. As a young art student, Amanda took an interest in histories of female farmers. Her work dealt with what it might means “to be a farmer and have a life that was so different and to be a woman who was working physically as hard as the man” (personal communication, February 19, 2013). Amanda spent a lot of time on her grandmothers’ farm growing up, and a map of that farm (Figure 1) was the visual and conceptual inspiration for Amanda’s BFA show. Amanda’s grandmother drew the map, illustrating the layout of the farm (refer to Figure 1). The details of the drawing provide insight to the life of her farm with a variety of crops, a garden, calves and chickens, and also a number of different physical structures. Through her time with her grandmother, Amanda learned the importance of individual responsibility and collective effort. Collective engagement by all members of the family was critical to the operation of a farm. As she described, [My grandma] had a real role – she was a kid and her siblings were kids but they had a real contribution to the existence of their families. And I don’t think they were resentful at all. Like she talks about doing the work and being so excited they could go out and swim in the river that afternoon. And before school you milk the cow and then you come home and do whatever chore you have to do. I think that would help me appreciate what it means to be here and to be part of the world. (Personal communication, April 5, 2013) With a life engaged in the direct production of food and other necessities came purpose as well as the joyful reward of leisure thereafter. For Amanda, collective processes of coming together through essential and direct practices are the root of subsistence and survival.

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Figure 1. Close-up of map drawing Amanda’s Grandmother’s house

I just wanted so badly to have the simplified version – I guess it was a kind of romanticism, but these foundational or fundamental skills – all of it – all of the DIY skills, crafting, sewing, weaving, growing food, building, cooking – I just really wanted to know those things – for me it meant some kind of simplification – like a simpler form of living. (personal communication, April 5, 2013) As we discussed learning fundamental skills in Amanda’s trailer, I noticed a spinning wheel (Figure 2), but I was not sure of its purpose. Juxtaposed against the prefabricated walls of the trailer, the wooden apparatus seemed both a living being and a relic simultaneously. I asked her what it was, and the concept of fundamental skills was instantly clear. Amanda explained that she was constructing pieces for her BFA show that would be an installation work that addressed life on the farm and stories she had heard, she repeatedly asked her grandmother for hand-spun yarn. Finally, her grandmother introduced her to a woman who taught her to spin her own yarn from animal hair. She used it to produce string installations (Figure 3) that would represent the crop rows from her grandmother’s drawn map (Figure 1). The work in Amanda’s senior show wove together her interests in women’s histories, a lifetime of developing skills in craft and making, memories of experience on her grandma’s farm, the visual inspiration of her grandmother’s hand-drawn map, and her recent embodied knowledge of farm work. She was becoming the subject of her memories and realized a parallel in her life and the research on female farmers’ memoirs she had studied. The desire that fueled her work on the farm was the same passion that drove her artwork—a desire to make, teach, and learn. So it just kind of evolved out of a practice from where I was drawing fields to where I was working in the fields. And then it was, like I would take vegetables that I was growing here and put them in my artwork. And then eventually it was like – a lot of it was time – I was working from sun-up to sun-down, but I have always thought of this like it was kind of like it was a big performance of the work that I had been making on paper for so long. It felt that way because it was kind of self-centered – like I was making

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Figure 2. Spinning wheel in Amanda’s trailer

Figure 3. Small part of Amanda’s large crop installations

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these artworks and it was all kind of the same thing for me, and then I started going through the motions of becoming a farmer that I had been making this art about because I felt like I kind of idolized it. (Amanda, personal communication, April 19, 2013)

Common Ground and Contemporary Art After graduation, Amanda served as an apprentice at Common Ground Farm outside of Beacon, NY for six months. Like Hidden Villa, the farm provided educational programming for all ages and it emphasized food justice as part of its mission. Possibly because of its proximity to New York City and only a few miles from the Dia, Beacon was a large artist presence between volunteers, workers, and CSA members at Hidden Villa. I asked Amanda why there seems to be such a strong overlap between artists and the young farmers movement. Having attended conferences and coming to know the farmer community, she explained that many young farmers are either the artist or the scientist type. She saw similarities between farming and art making in the way that both elicit a sensitivity to connect and exchange ideas, and require using your hands and mind to problem solve. For a young artist, farming can be much more rewarding than administrative or managerial jobs. Furthermore, Amanda stressed the potential for change that can come from agricultural work—change that might take the form of a week’s vegetables, developing a community supported agriculture program, or a summer camp that introduces kids to the roots of much of their food. During her apprenticeship at Common Ground, Cathy Lebowitz was the artist in residence on the farm. Lebowitz was an editor for Art in America. She introduced Amanda to a number of artists who would visit the farm, and they would attend shows in New York City together. Amanda’s background as an artist opened doors to expand and become part of the larger community involved with Common Ground. While interning at Common Ground, Simon Draper, a contemporary artist who was developing an artists collective called Habitat for Artists (Lipton, 2014), was also working there. Amanda explained that Draper wanted to take artists from their traditional studios and put them out in the community or in nature because he was interested in how that shift might affect an artist’s consciousness. With a team of artists, he built small mobile studios and placed them around the Hudson Valley, allowing artists to use them. This work was collective and environmentally conscious, in the sense that the spaces were not based on profit, but on a shared time and labor to produce a different sense of connection with the world and question how that might affect their artistic production. His work was a response to global capitalism in its resistance to the privatization of time, space, and knowledge production. After finishing her apprenticeship at Common Ground, Amanda apprenticed with Draper. She took testimonies of the artists who were occupying the spaces he built as part of her work with him, again blurring the lines between art, anthropology, education, design, and science. “I remember whenever I came home from New York, I was like, I’m an artist, and I just didn’t know. I am an artist and I am a farmer and I’m a teacher.” (Amanda, personal communication, April 5, 2013).

PRODUCING CARDO’S FARM PROJECT Amanda returned home motivated to expand Cardo’s Farm from a sprout farm into a local working and educational farm. She quickly realized that she was running a business and must learn how to manage it as such by teaching herself accounting and inventory software and honing her negotiation skills. Amanda’s 1244

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experience building the farm project highlights the complexity of developing ethical business practices that rely on and are responsible to a community and the environment. The first summer, the temperature rose to over one hundred degrees for sixty days. She worked with another farmer she had met in California to put on a makeshift summer camp with a surprisingly large turnout. The camps were full and the kids were excited. They also held adult workshops on gardening and farming. By the end of the summer, they were committed to seeing the Farm Project grow. Amanda raised $15,000 through a successful Kickstarter campaign. With the capital in place, she renovated the barn to make it a more functional education center (see Figure 4) and community kitchen, expanded the growing space to another plot of land, put in irrigation, and started their first CSA. The capital campaign allowed them to develop a business model that could function as a more self-sustaining system.

Sacrifice, Communal Living, and Collective Responsibility While the Farm Project has been successful, Amanda was honest about sacrifices she felt she had to make to maintain its integrity. She was forthright about her fatigue with living outside and often without hot water. During their first winter, Amanda moved to the farm and lived in the small (approximately four foot by four foot inside) dome structure that Cardo built years earlier (see Figure 5). Amanda lived in the dome for over a year. There was no indoor restroom facility and no hot water. She would start a fire to use the shower and it was still not in a walled structure. The kitchen in their barn is the only kitchen on the land, so they share it with Cardo and any of his guests as well. She eventually saved up the money to buy the trailer she was living in during the interview (see Figure 6). She said, “Sometimes I am just like, ‘When, when can I have a normal house? Turn on the faucet and have hot water came out” (Amanda, personal communication, April 5, 2013). Figure 4. Chalkboard inside renovated education center at Cardo’s farm in Ponder

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Figure 5. Small dome structure built by Cardo

Figure 6. Exterior of trailer Amanda lived in during first visit

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Outside of the broader community in town, life on the farm was its own living system that relied on sharing, moderation, respect, and a collective responsibility. Amanda was only able to keep the farm going because it was based in a material form of communalism. With Cardo’s land also came all of his equipment, barns, and fences. That kind of infrastructure would have cost far more than the cost of rent to start up. Amanda shared the land with two farm managers. They shared an outdoor solar shower. They bought food staples in bulk for the farm based on a strict shared budget, and they ate all meals together because the cost of each member to eat individually would have been too high to manage with the resources they earned from produce. She explained that the cooking also operated on a rotation, It’s like you work your ass off every day and then to cook every night, it just gets really hard, I remember last summer before we had a system like this. Then it was just me and Dan, and Dan didn’t cook very much so I was really just cooking for myself, and I pretty much lived off fried egg sandwiches. (Amanda, personal communication, April 5, 2013) While I am focusing on farm production in this paper, many artist cooperatives are realizing that they must make similar sacrifices to resist neoliberal capitalism and exist in a world dominated by corporations. The micro-community of CFP reflects what needs to happen on a global scale to affect significant change. Amanda’s sacrifice on the farm is one example of ways that people can live more ethically through communalism and limiting their use of natural resources. I recognize that few people would make the choice to live in a hut without hot water for a year, but the sacrifices made to conserve food and share responsibilities are examples of everyday changes that could make a broad impact.

Exploiting Rhetoric Through our conversation, I learned about the realities of organic and locally grown produce sales. As we talked about sustainable practices and organic farming, Amanda spoke with disdain about a local organic grocer. As she described, “he’s a peddler in town who hides under fancy words like organic, sustainability, and community” (Amanda, personal communication, April 5, 2013). Essentially, he was using marketing rhetoric for a disingenuous practice. He does not grow anything himself. He drives to a number of local farms and buys the most visually appealing produce wholesale. It’s so hard for us to compete with because he can drive all over and take out the stuff that looks bad, and we’ve worked our asses off and we’re next to his glorious stand with our little bruised vegetables…. I just realized how many people are buying his stuff because of the words – sustainable and organic – we don’t have any of those words. I refuse. You can talk about our growing practices, but I’m not interested in being associated with Monsanto and sustainability. It’s a load of shit. But he’s totally capitalizing on it. (Amanda, personal communication, April 5, 2013) Amanda explained that wholesale distribution that relies on the middleman kills small farms because they do not get market value for their produce. Without the middleman distributor, farmers get market value for their food. In addition, when you buy directly from farmers, you may also have a better understanding or appreciation of what goes into growing it. Industrialized global agricultural production has exacerbated the struggles of small farms. 1247

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Amanda and I repeatedly talked about food justice and the challenges with providing healthy foods to low-income populations. Thinking about what it means to feed people who cannot afford to buy food introduces much broader issues about education. Eating healthy food often costs more than industrialized food, and it can take more time to cook and a familiarity with the produce being grown. Kale and rhubarb are commonly sold to her CSA members, but donating these to low-income families is not beneficial if they do not know what to do with them. These are some of the challenges that food justice efforts are facing. Solutions are not as simple as giving out free vegetables. Amanda sees ways that after-school programs on a farm, where students are paid with the food they have grown, could be one positive approach that is educational, service-oriented, and purpose-driven.

Participatory Pedagogy and Affective Potential Since that first summer, Amanda ran summer camps for children ages Kindergarten through 6th grade annually. She served approximately eighty kids in each summer session, and activities include planting, working with animals, drawing, mapping, and tending the chickens, among other programming. They use multi-sensory investigations to learn about plants and other elements of the farm environment. She also teaches adult and children’s classes at a community center, and invites local schools to visit the farm. She explained that her approach to teaching is embedded in the belief that embodied learning and a focus on problem solving builds confidence in kids. By being able to see a direct connection between themselves and food and plants grown in the ground or to work closely with animals teaches kids a sense of responsibility and place. Amanda also frequently incorporates hands-on experiences for visitors, customers, and students as a form of cultural participation. Even for myself, my first real physical work was on a day that I volunteered to help dismantle greenhouses, described in the reflection that opened the chapter. I learned something every time I visited the farm for interviews, to pick up vegetables, or drop off my kids.

DISCUSSION Amanda’s process coming to and developing Cardo’s Farm Project as a business and educational site illuminates the complexity of art, education, and community building in a period of increasing neoliberal globalization, where participation can become both civic engagement and simultaneously marketing strategy. Amanda’s narrative reveals the potential of aesthetic practices to affect change in individuals and presents the challenges and possibilities of collective efforts in the face of an increasingly globalized economy. To analyze her process, I consider how participation as direct engagement produced a sense of agency and became an index of collective force through each aspect of her development from artist to farmer-educator.

Leaving Institutional Education I realized that what was different in Amanda’s direction with the farm and her misgivings about institutionalized art education were the lack of direct engagement and teacher preparation’s increasing focus on corporate time in the form of accountability measures and the commodification of knowledge. Education courses are often based in decontextualized pedagogical methods. Students are disconnected 1248

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from lived experiences, often thinking through detached representations of classroom practices, where humans and experiences are generalized into procedures and data. Effects of neoliberal policies on education have resulted in exponential increases in assessment measures in an effort to produce data. With more focus on assessment, education has become increasingly fractured and mediated by codes and rules. Through his explanation of the corporatization of universities, Giroux (2003/2006) describes the difference between what he calls corporate time versus public time. In this argument, the corporate university is “wedded to a notion of accelerated time in which the principle of self-interest replaces politics, and consumerism replaces a broader notion of social agency” (Giroux, 2003/2006, p. 260). Public time, on the other hand, “demands and encourages forms of political agency based on a passion for self-governing, actions informed by critical judgment, and a commitment to linking social responsibility and social transformation” (Giroux, 2003/2006, p. 261). When the possibility of knowing outside of what already exists is foreclosed by codification of methods and the commodification of time, education becomes a product rather than a process. Amanda’s frustration with and abandoning of institutionalized teacher preparation was in part recognition of this condition. Her experience in a formalized teacher education program was embedded in training rather than in the development of social agency. On the other hand, Amanda’s community-based education at Common Ground and Hidden Villa operated entirely through what Giroux (2003/2006) described as public time: embedded in self-governing, social responsibility, and social transformation. While Amanda’s educational work at her current residence and at Cardo’s Farm is not operating in a public space, it is open to the public where kids work both agriculturally and creatively to develop critical thinking skills about processes of production, natural resources, and the roots of material goods. For children, such as my son, her educational programming produced a different kind of subjectivity in relation to the natural environment, where the fruits of their labor are realized as plants grow and eggs hatch over multiple visits. When kids attend Amanda’s young farmers classes, she has to spend time helping students understand the difference in expectations on the farm from those in a traditional classroom because most are embedded in an institutional disconnect from life that is too often produced in public education. She feels that children are given little opportunity to take responsibility in a classroom, particularly with experiences dealing directly with living organisms. Amanda shifted her focus to farm-based and community-focused education to return to a model closer to that which she experienced with her grandmother. Farm Based Education continues a mode of progressive education that Dewey (1934) encouraged a century ago. Amanda described how artists and scientists are drawn to the hands-on and problem-solving aspects of farming. Local, community-supported farms provide a place to practice ethical behavior through collective efforts with a visible community. In this sense, farms like Common Ground, Hidden Villa, and Cardo’s Farm Project can be seen as sights of community based education through socially-engaged pedagogy, and if we view farming as an aesthetic practice, they intersect with and expand the potential of art education. While artists have been drawn to this kind of embodied learning historically, Amanda’s experience of working with Draper and Lebowitz in New York exemplifies ways that links between arts-based thinking and authentic learning exist today. Amanda’s experience echoes that of performance artist and art educator, Charles Garoian, who described feeling “like a fish out of water” as a student at Stanford where “much of my studies there were based in academic models of pedagogy and curriculum” (Cempellin, 2013, 83). Garoian described (1999), “From the beginning, I wanted to teach in a way that invited the creative disruptions I found so valuable from my days growing up on my parents’ farm and in my art 1249

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education” (p. 201). Garoian realized his interest in the performative process of art was the necessary component for powerful teaching: The best teaching occurs when you are engaged with your students in exploratory, experimental, and improvisational processes; in the liveness of what art does, its conceptual operations, rather than illustration and representation. Academic representations will always constitute schooling, but what emerges from creative activity in the classroom is the source from which transformation and agency are made possible. (As cited in Cempellin, 2013, p. 83) Amanda’s decision to leave institutional education was a result of the absence of what Garoian calls “liveness of what art does.”

Farming as Hands-On Resistance to Globalization Neoliberal policies and practices have exacerbated modes of injustice through the exploitation of environmental and human resources, often in third world countries. A primary of globalization has been the move of manufacturing operations to countries with less human rights regulations. Moving these industries to less developed locations makes the effects of capitalist exploitation invisible to consumers in large industrialized nations. As one way of reconnecting with skills that have been lost in over two generations of outsourcing manual labor, the growing maker’s movement has reinvigorated interest in craft, electronics, gaming, design, music, cooking, and much more. Artistic, DIY, and educational responses to globalization have embraced first-hand experiences focused on process and direct engagement. Like the Arts and Crafts movement at the end of the 19th century, the farm movement is rooted in resisting the fragmenting nature of capitalism to separate laborers from their products. The ethic that girds many of the efforts of young farmers attempting to develop their own sustainable agricultural operations aligns with the anti-capitalist work and a sincere belief in importance of teaching fundamental skills through direct engagements and experiential learning. Amanda learned this ethic early on from life on her grandmother’s farm. Life on the farm allowed Amanda to see the importance of collective effort and communal practices. Moreover, Amanda’s grandmother taught her how to work through necessities, such as spinning yarn and knitting rather than purchasing mass-produced products. Contemporary artists’ “growing interest in collaborative and collective approaches in contemporary art…. toward participatory, process-based experience” (Kester, 2011, p. 7-8) were evidenced through Amanda’s work at Common Ground. There, she witnessed a growing force of artists turning to agriculture and craft production embedded in a revolutionary spirit that connects art, activism, and education (Campana, 2011).

Participation as Ethical and Aesthetic Encounter An ethic embedded in living as a form of art is becoming more relevant, where artists are illuminating vital interconnections of material practices or aesthetics as encounters with the world, where participatory engagement become aesthetic event (Thompson, 2014). With this in mind, I am viewing the farm as an aesthetic site, where Amanda’s work performs Kester’s (1998) claim for “collaborative and collective approaches…toward participatory, process-based experience” (p. 7-8).

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In this way, the aesthetic engagement with the farm is profoundly creative. jagodzinski (2009) describes that the force of the artistic event is its ability to change, rupture, and transform a system of set relations. If a traditional formal aesthetics engages with the ways art allows us to see beauty as a transcendental force, then couldn’t this participatory approach to aesthetics grounded in the “dynamics of being” and the “performative affect of becoming” describe engagements with natural spaces through farming as aesthetic experiences? Encounters with the vitality of her farm become art events that can teach us about a more ethical way of living. Eyermen suggests art as ‘experiential space’: A form of social activity through which new kinds of identities and practices emerge… as a cognitive praxis, art is a space for individual and collective creation that can provide society with ideas, identities, and ideals… like a social movement, art opens space for experimentation, social and political, as well as aesthetic. (as cited in Campana, 2011, p. 281) Amanda’s individual and collective practices on the farm engage with this kind of experimental, social, and political activity. Moreover, the farm as participatory aesthetic space aligns with Green’s (1999) characterization of new genre public art education merging life and material production as a socially-engaged pedagogy. Through my embodied participation with Amanda and CFP, I was able to recognize effects of industrialized agriculture that I had never seen before, rupturing my habituated understanding of agricultural production. While I experienced a shift in consciousness from even brief encounters with farm work, brief, enjoyable experiences do not engage with the much more complex and challenging issues of inequality embedded in the broader system of factory farming, such as migrant labor, environmental destruction, animal cruelty, and genetic modification. We must be careful to not become blind to broader forms of exploitation Moreover, the limited time involved in brief, privileged encounters of “playing farmer” (Dunlap, 2011), rather than farming out of necessity, provides a sense of civic engagement while being spared from the messiness, struggle, and sacrifice that go along with actually running a small farm. Amanda’s years of sacrifices and significant lifestyle changes were also invisible. Unfortunately, the reality becomes more equivalent to pseudo-ethnographies (Desai, 2002) or edutainment (Kalin, 2014) because the event being consumed is so far removed from the challenges that go into the process. In her analysis of the ethnographic turn in art, Desai (2002) examines the complex and problematic relationship between experience, interpretation, and representation when the public sphere becomes an arena for active investigation. Desai (2002) especially scrutinizes the weakness of “pseudoethnography,” wherein an artist enters a community for a day or week to engage in a brief cultural investigation, leaving “the socio-economic and political relations, which underscore the representation . . . hidden” (p. 314). Bishop (2004) addressed this kind of superficiality with relational encounters in art of the 1990’s, concerned that viewers and participants were lulled into thinking that they have become politically active. She argued instead for “relational antagonism” that might produce discomfort among participants to illuminate new possibilities. While I would argue that the exhausting work on Amanda’s farm goes some way in affecting new ways of understanding the plight of small farms, participation on a large industrial agricultural operation might go a lot further in understanding the impact of globalization.

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Participatory Engagement as Neoliberal Practice and Collective Resistance As many young people choose to become farmers in an effort to act as individually responsible agents for a more environmentally sustainable future, they are often unknowingly buying into the system they are resisting. The maker’s movement, in large part, privileges local markets, handmade products, efforts for more ethical forms of consumption, and a resistance to corporate production, but as Bishop (2012a) describes, one characteristic of neoliberal capitalism is its ability to co-opt modes of resistance into profitable commodities. One way of co-opting modes of resistance is through Post-Fordist tactic of marketing a lifestyle over individual material objects. This phenomenon highlights the complexity of cultural participation. For instance, Amanda invites clients to pick their own vegetables and flowers. On the one hand, this is not unlike bagging one’s own groceries. In the grocery store, the quick check out can be seen as a form of convenience or freedom from the line. We often fail to think that we are helping the grocery store increase their profits by working for them for free and eliminating a cashier’s position. At CFP, picking one’s own flowers or vegetables can be viewed as freedom, choice, or cultural participation. It works as a marketing strategy and as a mode of resistance-as-hands-on engagement to people interested in cultural participation. Her invitation is both a reaction to globalized agricultural production and a need to exist within that market. By making the farm a participatory site, Amanda has “infiltrated the world of market and social relations” (Ranciere, 2010, p. 149) because the customer is, to a certain degree, becoming producer. At the same time, this strategy is now part of the neoliberal nexus. Collective participatory on the farm exists somewhere on a continuum between neoliberal marketing strategy and mode of cultural consumption as collective resistance. Furthermore, Amanda’s Community Supported Agriculture (CSA) program and Farmer’s Market stand can be viewed as another performative public intervention in inequitable capitalist practices. There are 80 members of the CSA, but she did not have specific figures for the average weekend sales at the local Farmer’s Market. As a CSA member, I would drive to Amanda’s house one time per week to pick up a load of vegetables. I paid Amanda directly. I feel that on a micro level, this mode of direct exchange is one way to intervene in the capitalist drive for surplus. The exchange also became personal, local, and embodied. If we view processes of consumption as political acts, then my choice to buy directly from Amanda was a community-building act in opposition to neoliberal privatization that views all objects and relations as potential profit. My act of consumption shifted to a focus on communication, interpersonal relations, and local investment. Even as I was helping the farmers at the local farmer’s market and CSA, the privileged position of buying food direct from farmers often reifies racial and ethnic divides in local populations (JoassartMarcelli & Bosco, 2014). For instance, the location of farmers markets driven by primarily Caucasian artisans and craft makers are often not the same as those that are driven by minority populations, such as Bazaars in Latino neighborhoods. This is the case of the Farmer’s Market where Amanda sells produce. While there are Latino grocery stores nearby that sell local produce, the Saturday Farmer’s and Artisans market in the center of town is frequented by primarily middle to upper middle class Caucasian clients. The differences point to a continued class-based and ethnic segregation. Finally, through Amanda’s challenges, I was better able to understand how rhetoric is exploited to appeal to the lifestyle politics of well-intentioned consumers. Amanda’s frustration over the local wholesale produce dealer stemmed from the disingenuous use of popular rhetoric misleading well-intentioned consumers into thinking they were buying directly from a small farmer. The conflation of terms like 1252

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sustainable and organic again becomes a tool to attract people who don’t know the processes embedded in their production. Many people attracted to those labels have good intentions. I would never have known about these unfair market practices. I thought that the local distributor was good because he was “local.” She pointed out how people like me think they are doing the right thing because he uses misleading labels. Amanda’s small operation was compromised by buyers’ desire for more ethical modes of consumption while also wanting aesthetically pleasing produce, not realizing that the rhetoric used to sell the products was erroneous. Again, neoliberal policies and Post-Fordist capitalism have produced a complex network of relations between production and consumption, commodifying desire, lifestyle, and rhetoric to make traditional models of resistance feel nearly impossible.

CONCLUSION People need to be educated for democracy not only by expanding their capacities to think critically, but also for assuming public responsibility through active participation in the very process of governing and engaging important social problems. (Giroux, 2003/2006, p. 276) To conclude this chapter, I return to the narrative that opened it. Our time spent on the greenhouses that day produced a connection with Amanda and the farm that transcended our intellectual or academic work. Through a pedagogy of participation, I realized how little I knew about the breadth of manual labor required to run a farm. Amanda taught me how the daily physical engagement of agricultural production could be an activist art practice embedded in the community-building force of direct engagements. When I left that day, I felt a sense of agency and hope for the power that collective efforts might make against the exploitative conditions of globalized corporate capitalism by taking even a small amount of responsibility for the success of the farm through my time and physical effort. Her farm helped me see how a shift in cultural values is performed through the ways we spend our time, money, energy, and knowledge. Amanda’s participatory aestheticization of farming through Cardo’s Farm Project represented a site of resistance to industrialized farming practices as a way to teach daily methods of making that enact a DIY ethic of liberation from neoliberal capitalism (Holtzman, et. al, 2005; Kester, 2011; Levine 2008).

REFERENCES Ballengee Morris, C. (2000). A sense of place: The Allegheny Echoes Project. In P. E. Bolin, D. Blandy, & K. G. Congdon (Eds.), Remembering others: Making invisible histories of art education visible (pp. 176–187). Reston, VA: NAEA. Barney, G. (2009). Art and farming in Britain. Arts Council England. Retrieved from http://www.faceonline.org.uk/art/art-and-farming-in-britain Beaver, T. D. (2012). By the skaters, for the skaters the DIY ethos of the roller derby revival. Journal of Sport and Social Issues, 36(1), 25–49. doi:10.1177/0193723511433862 Bishop, C. (2004). Antagonism and relational aesthetics. October, 110, 51-79.

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Bishop, C. (2012a). Participation and spectacle: Where are we now? In N. Thompson (Ed.), Living as form: Socially engaged art from 1991-2011 (pp. 34–45). New York, NY: Creative Time. Bishop, C. (2012b). Artificial hells: Participatory art and the politics of spectatorship. Brooklyn, NY: Verso. Blandy, D., & Hoffman, E. (1993). Toward an art education of place. Studies in Art Education, 35(1), 22–33. doi:10.2307/1320835 Bourriard, N. (2002). Relational aesthetics. Dijon-Quetigny, France: Les presses du Reel. Callejo Perez, D., Fain, S. M., & Slater, J. J. (2004). Pedagogy of place: Seeing spaces as cultural education. New York, NY: Peter Lang. Campana, A. (2011). Agents of possibility: Examining the intersections of art, education, and activism in communities. Studies in Art Education, 52(4), 278–291. Cardo’s Farm Project. (2014). Who We Are. Retrieved from: http://www.cardosfarmproject.com/ Cempellin, L. (2013). Charles R. Garoian: Exploring the in-between. Juliet Art Magazine, 165, 83. Congdon, K. G. (2006). Folkvine.org: Arts-based research on the web. Studies in Art Education, 48(1), 36–51. Congdon, K. G., Blandy, D., & Bolin, P. E. (Eds.). (2001). Histories of community-based art education. Reston, VA: National Art Education Association. Cornelius, A., Sherow, E., & Carpenter, S. B. II. (2010). Water: Social issues and contemporary art education. Art Education, 63(6), 25–32. Desai, D. (2002). The ethnographic move in contemporary art: What does it mean for art education? Studies in Art Education, 43(4), 307–323. doi:10.2307/1320980 Dewey, J. (1934). Art as experience. New York, NY: Perigee. Dewey, J. (2007). Democracy and education. Middlesex, UK: Echo Library. (Original work published 1916) Duncombe, S. (1997). Notes from underground: Zines and the politics of alternative culture. London, UK: Verso. Duncum, P. (2011). Engaging public space: Art education pedagogies for social justice. Equity & Excellence in Education, 44(3), 348–363. doi:10.1080/10665684.2011.590400 Dunlap, R. (2013). Playin farmer: Leisure experiences in a craft-based community of practice. International Journal of Qualitative Studies in Education, 26(1), 118–137. doi:10.1080/09518398.2011.604648 Efland, A. (1990). A history of art education: Intellectual and social currents in teaching the visual arts. New York, NY: Teachers College. Ellsworth, E. (2005). Places of learning: Media, architecture, pedagogy. Falmer Routledge. Farm Based Education Network. (2014). What is farm-based education? Retrieved from: http://www. farmbasededucation.org 1254

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Garoian, C. R. (1998). Art education and the aesthetics of land use in the age of ecology. Studies in Art Education, 39(3), 244–261. doi:10.2307/1320367 Garoian, C. R. (1999). Performing pedagogy: Toward an art of politics. Albany, NY: State University of New York Press. Giroux, H. A. (2006). Youth, higher education, and the crisis of public time: Educated hope and the possibility of a democratic future. In C. G. Robbins (Ed.), The Giroux reader (pp. 253–281). Boulder, CO: Paradigm. (Original work published 2003) Graham, M. A. (2007). Art, ecology, and art education: Locating art education in a critical place-based pedagogy. Studies in Art Education, 48(4), 375–391. Green, G. (1999). New genre public art education. Art Journal, 58(1), 80–83. doi:10.1080/00043249. 1999.10791924 Gruenewald, D. A., & Smith, G. A. (Eds.). (2008). Place-based education in the global age: Local diversity. New York, NY: Taylor & Francis. Gude, O. (2004). Psycho-aesthetic geography in art education. Journal of Cultural Research in Art Education, 22, 5–18. Hall, S. (1991). Brave new world. Socialist Review, 91(1), 57–58. Hardt, M., & Negri, A. (2004). Multitude: War and democracy in the age of empire. New York, NY: Penguin. Helguera, P. (2011). Education for socially engaged art: A materials and techniques handbook. New York, NY: Jorge Pinto Books. Hidden Villa. (2014). Hidden Villa. Retrieved from: http://www.hiddenvilla.org/ Holtzman, B., Hughes, C., & Van Meter, K. (2005). Do it yourself… and the movement beyond capitalism. Radical Society, 31, 719. Inwood, H. (2010). Shades of green: Growing environmentalism through art education. Art Education, 63(6), 33–38. jagodzinski, j. (1987). Toward an ecological aesthetic: Notes on a “Green” frame of mind. In D. Blandy, & K. Congdon (Eds.), Art in a democracy (pp. 138-164). New York, NY: Teachers College Press. jagodzinski, j. (2009). Beyond aesthetics: Returning force and truth to art its education. Studies in Art Education, 50(4), 338-351. Jeppesen, S. (2011). The DIY post-punk post-situationist politics of CrimethInc. Anarchist Studies, 19(1), 23–55. Joassart-Marcelli, P., & Bosco, F. J. (2014). Alternative food projects, localization and neoliberal urban development: Farmers’ markets in Southern California. Metropoles, 15, 1-23. Retrieved from https:// metropoles.revues.org/4970 Kalin, N. (2014). Art’s pedagogical paradox. Studies in Art Education, 55(3), 190–202.

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Kester, G. (1998). Afterimage and activist art. In G. Kester (Ed.), Art, activism, and oppostionality: Essays from Afterimage (pp. 1–19). Durham, NC: Duke University Press. Kester, G. (2011). The one and the many: Contemporary collaborative art in a global context. Durham, NC: Duke University Press. doi:10.1215/9780822394037 Levine, F. (2008). Handmade nation: The rise of DIY, art, craft, and design. New York, NY: Princeton Architectural Press. Lipton, A. (2014). Simon Draper: Habitat for artists. Retrieved from: http://www.liptonarts.com/simondraper-habitat-for-artists-2/ McKay, G. (Ed.). (1998). DIY culture: Party & protest in nineties Britain. New York, NY: Verso. Meehan, M. (2012). Seventeen hundred seeds: Cultivating community as art. Glasstire. Retrieved from http://glasstire.com/2012/06/02/seventeen-hundred-seeds-cultivating-art-and-community/ Powell, K. (2010). Viewing places: Students as visual ethnographers. Art Education, 63(6), 44–53. Powell, K. A. (2008). Remapping the city: Palimpsest, place, and identity in art education research. Studies in Art Education, 50(1), 6–21. Rancière, J. (2010). Dissensus: On politics and aesthetics. New York, NY: Continuum International. Schaefer, B. (2013). The commodification of the American farmer. The Society Pages. Retrieved from http://thesocietypages.org/sociologylens/2013/10/11/the-commodification-of-the-american-farmer/ Spaid, S. (2012). Green acres: Artists farming fields, greenhouses, and abandoned lots. Baltimore, MD: Contemporary Arts Center. Spencer, A. (2005). DIY: The rise of lo-fi culture. London, UK: Marion Boyers Publishers. Thompson, N. (Ed.). (2012). Living as form: Socially engaged art from 1991-2011. New York, NY: Creative Time. Thrift, N. (2005). Knowing capitalism. Thousand Oaks, CA: Sage. Trafi-Prats, L. (2006). ABC Milwaukee: The visual culture literacies of growing up urban. Retrieved from: http://www.inter-disciplinary.net/wp-content/uploads/2009/06/trafi_vl3_draft.pdf Trafi-Prats, L. (2009). Destination Raval Sud: A visual ethnography on pedagogy, aesthetics, and the spatial experience of growing up urban. Studies in Art Education, 51(1), 6–20. Wallin, J. (2007). Between public and private: Negotiating the location of art education. International Journal of Education & the Arts, 8(3), 1–15. Zabel, G. (Ed.). (1993). Art and society: Lectures and essays by William Morris. Medford, MA: Geoge’s Hill Publications.

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KEY TERMS AND DEFINITIONS Aestheticization: The application of an aesthetic lens to analyze contemporary shifts toward local farming as a political act by farmers and artisans. This term is historically related to the work of Walter Benjamin in an analysis of the political nature of art and a broader analysis of life as being innately aesthetic. Civic Engagement: Citizen participation for the betterment of a community. Collective Responsibility: Group effort toward a collectively determined goal that is based in democratic membership and individual responsibility. Farm-Based Education: Community-focused, interdisciplinary education based in farming and agricultural processes aimed at teaching about connections between living organisms, as well as links between nature and industrialization. Teaching methods are primarily experiential, hands-on, and student centered. Globalization: Process of integration across global nations. The term often relates to trade markets, but also ideas, cultural artifacts, and worldviews spread through the development of new technologies, increases in international migration, and international trade policies. Localized Agriculture: Shifts to smaller farms run by one or a few farmers in a region near or within urban areas, primarily in response to industrialized agriculture. Neoliberalism: An economic philosophy that relates to market policies focused on deregulation and a laissez-faire capitalist approach. Since the 1970’s this term relates to broader social shifts that emphasize individualism, free enterprise, accountability, privatization, and a focus on profitability. Participatory Action: This term relates to collective action in terms of art, activism, research, and everyday community involvement aimed at human agency and social transformation.

ENDNOTES 1



Stuart Hall (1991) defines Post-Fordism in this way: “’Post-Fordism’ is a broader term, suggesting a whole new epoch distinct from the era of mass production…. It covers at least some of the following characteristics: a shift to the new information ‘technologies’; more flexible, decentralized forms of labor process and organization; decline of the old manufacturing base and the growth of the ‘sunrise,’ computer-based industries; the hiving off or contracting out of functions and services; a greater emphasis on choice and product differentiation, on marketing packaging, and design, on the ‘targeting’ of consumers by lifestyle, taste, and culture rather than by the categories of social class; a decline in the proportion of skilled, male, manual working class, the rise of the service and white-collar classes and the ‘feminization’ of the work force; an economy dominated by multinationals, with their new international division of labor and their greater autonomy from nation-state control; and the ‘globalization’ of the new financial markets, linked by the communications revolution.

This research was previously published in Convergence of Contemporary Art, Visual Culture, and Global Civic Engagement edited by Ryan Shin, pages 185-209, copyright year 2017 by Information Science Reference (an imprint of IGI Global).

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Chapter 57

Inter Linkages of Water, Climate, and Agriculture Sunil Londhe World Agroforestry Centre (ICRAF), India

ABSTRACT Climate is the primary determinant of agricultural productivity and evidence shows possibility of shifts in earth’s climate. Concern over the potential effects of long-term climatic change on agriculture has been raised over the past decade. Change in the climatic conditions on the globe created threat to the availability water for agriculture production. The present chapter is an attempt to distil what is known about the likely effects of climate change on water availability to agriculture for food security and nutrition in coming decades. Apart from few exceptions, the likely impacts of climate change on agriculture water resources in the future are not understood in any great depth. There are many uncertainties as to how changes in various environmental parameters will interact with the availability of water and further agriculture production. The future consequences of water resources on agriculture are discussed and summarized. Possible mitigation and adaptations to changing water availability for agriculture are also discusses.

INTRODUCTION The world population, which took more than 50,000 years to reach the first billion, has just surpassed 7 billion. Even if fertility continues to decline at the world level and with it population growth rates, the United Nations projects that the world population could reach 9.3 billion by 2050 and surpass 10 billion by the end of the century (United Nations, 2011). If fertility were to be higher than in that projection, the population may surpass 10 billion by 2050 and may be several billions higher by 2100. To feed a growing world population, we have no option but to intensify agriculture and crop production. Further, numerous factors shape and drive the agricultural sector and climate is the primary determinant of agricultural productivity. Given its inherent link to natural resources, agricultural production is also at the compassion of uncertainties driven by climate variation, including extreme events such as flooding and drought. The fundamental role of agriculture in human welfare, concern has been expressed DOI: 10.4018/978-1-5225-9621-9.ch057

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by federal agencies and others regarding the potential effects of climate change on agricultural productivity. Interest in this issue has motivated an extensive of research on climate change and its impact on agriculture production over the past decade. There may be increasing threat to agriculture production due to climate change which is now largely accepted as a real, pressing and truly global problem. There is also increasingly aware that the risks of climate change are so great, that ignoring or delaying in addressing them would be far more costly than not doing so. Climate change is now global problem for the agriculture production and food security on the globe. The long-term climatic risk to agricultural assets and agricultural production may be linked to availability of water which is known with great uncertainty. There may be threat to risk of loss of rural livelihoods and income due to insufficient access to drinking water. The risk of alarms for agricultural irrigation and reduced agricultural productivity, particularly for farmers and pastoralists in semi-arid regions. There may be risk of loss of terrestrial and inland water ecosystems, biodiversity, and the ecosystem goods, functions, and services they provide for human being and their livelihoods. In general agriculture production and food security may face serious consequences due to inadequate water resources. Apart from this increasing demand for water from urban, industry, etc. has exaggerated the problem in many folds. From the available literature overall demand and supply relationship with linkage to risk for overall development is compiled and presented in Figure 1. It is well known fact that agriculture production is dependent on set of climatic conditions. Climatic resources are the deciding factor for successful cultivation of any crop and which cannot be manipulated by the human beings. The availability of water for irrigation and the source of the water both are climate dependent factors. Both shortage and excess of water will interfere the agriculture production Figure 1. Water demand and supply relationship

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to greater loss. The latest reports (FAO, 2013) of statistics of utilization of world land says that thirty percent of the earth’s land is used for crops and pastures and seventy percent of all abstracted freshwater is directed towards irrigation to produce the food that people and livestock need for a stable food supply. This large-scale utilization of land and water resources is increasingly threatening environments. Furthermore, farming is important because it provides the livelihood of hundreds of millions of people. Water resources are important for agriculture production in all the regions of the globe. Agriculture system is vulnerable because of too hot and dry climate, limited and variable water supply, low and degraded soil quality and lack of adaptive capacity. The chapter “Inter linkages of water, climate, and agriculture” discuss about the probable impacts of climate change on availability of water for agriculture. The document encompasses not only irrigation, but also other forms of water control intended to optimize growing conditions for crops, livestock and pasture. Change in climatic conditions like precipitation, temperature, Carbon dioxide (CO2), etc. may be having adverse effect on global agriculture production. Hence the core of the document concerns adaptive and mitigation options and activities that can contribute to maintaining global food security and supporting farmers’ livelihoods in changing water availability. Keeping in the view the challenges of availability of quality water for agriculture in changing climate, the chapter focuses on the impact of climate change on agriculture, knowledge on the relationship between climate change, water and food security and how agriculture is able to adapt such climate change. The chapter also explores future availability of water and what will be the impending impact of availability and what mechanisms can be implemented to mitigate the resulting impact? In order to meet the elevated flow of agricultural production further research and extension activity need to be focused keeping in mind the changing climatic situations. Hence, at the end, the chapter discuss about the latest trends in the water and agriculture research for changing climatic situations. However, the impact on agriculture and its ability for adaption may vary with different parts of world. The purpose of the chapter is to enrich the current state of knowledge of readers on the relationship between water availability, climate change and food security and nutrition to provide an evidence base discussion. The chapter provides an analysis of empirical evidence results to highlight the relationship between water for agricultural production in climate change situations and food security.

Background Survival of human and livestock on the globe is highly dependent on the agriculture. Agriculture and allied activities are highly climate dependent and change in the climatic parameters may severely affect food security on the globe. Apart from few exceptions, the likely impacts of climate change on agricultural sector in the future are not understood in any great depth. There are many uncertainties as to how changes in temperature, rainfall and atmospheric carbon dioxide concentrations will interact in relation to agricultural productivity (Londhe, 2016). Lobell & Gourdji (2012) noticed that climate trends over the past few decades have been fairly rapid in many agricultural regions around the world, and increases in atmospheric carbon dioxide (CO2) and ozone (O3) levels have also been ubiquitous. The virtual certainty that climate and CO2 will continue to trend in the future raises many questions related to food security and health. One of the important research question mingling in agriculture research environment across globe is weather agricultural production will affect due to changing climatic conditions. One of the most important input for agriculture is availability of sufficient quantity of quality water. Change in climatic condition may result some regions with scarcity of water where as others with excess water. Both the 1260

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situations are not cozy for agriculture and will having serious impacts on global agricultural production and livelihood of rural poor and marginal farmers in various agro-ecological regions. In addition to water many factors will shape global food security over the next few decades which includes increasing human population, agricultural productivity, income growth and distribution, dietary preferences and disease incidence. Apart from agriculture, there will be increased demand for land and water resources for nonagricultural uses also. In this situation, maintaining increased flow of agricultural production is important to meet the need of growing population and new food habits. The main question of interest here is: how important will climate change in the contest of quality and timely water availability in shaping future crop yields and other agricultural production at the global scale. This question helps to set the challenge of climate change adaptation in context. Apart from these important climatic parameters like atmospheric concentrations of carbon dioxide (CO2) and Ozone (O3), and changes in temperature and precipitation conditions will be having direct or indirect impact on water availability and agriculture production. It may be expected that due to climate change there is possibility of change in climatic regimes and shift in seasons. This will create need based on the water availability to change in cropping patterns in some of the regions. The vast majority of the Earth’s water resources are salt water, with only 2.5% being fresh water. Approximately 70% of the fresh water available on the planet is frozen in the icecaps of Antarctica and Greenland leaving the remaining 30% (equal to only 0.7% of total water resources worldwide) available for consumption. From this remaining 0.7%, roughly 87% is allocated to agricultural purposes (IPCC, 2007). According to the Comprehensive Assessment of Water Management in Agriculture, one in three people are already facing water shortages (CA, 2007). Further FAO and UN Water (Anonymous, 2007) reported that around 1.2 billion people, or almost one-fifth of the world’s population, live in areas of physical scarcity, while another 1.6 billion people, or almost one quarter of the world’s population, live in the developing country that lacks the necessary infrastructure to take water from rivers and aquifers which is known as an economic water shortage. Projections of climate change are inherently uncertain, due to the natural variability in the climate system, imperfect ability to model the atmosphere’s response to any given emissions scenario. Taken in to consideration the recommendations of Intergovernmental Panel on Climate Change (Christensen et al., 2013) with identified model agreement on future changes, the global monsoon, aggregated over all monsoon systems, is likely to strengthen in the 21st century with increase in its area and intensity, while the monsoon circulation weakens. Monsoon onset dates are likely to become earlier or not to change much and monsoon retreat dates are likely to delay, resulting in lengthening of the monsoon season in many regions. The Predictions of Intergovernmental Panel on Climate Change may further increase the complexity of food security many folds. Again these uncertainties are compounded by the paucity and unreliability of basic information related to agricultural production. Water resource availability may be altered by changed rainfall patterns and increased rates of evaporation. Changes in rainfall will also increase variability in groundwater recharge and river flow, thus may affect all water sources. For many of the world’s poorest people, rainfall variability may be a major impediment to their livelihoods. The inability to predict and manage rainfall, and consequent runoff, variability is a key contributing factor to their food insecurity and poverty. Frequent periods with too much water are followed by periods with too little and intermittent water scarcity is often a direct consequence of rainfall variability. National economies, highly dependent on rain-fed agricultural production, are exceedingly vulnerable to fluctuations in rainfall. Although there are opposing views, there is little evidence that water 1261

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scarcity by itself is a major factor limiting economic growth in most countries (Barbier, 2004). However, in contrast, rainfall variability has been shown to be a significant factor that has an effect on economic growth (Brown & Lall, 2006). Under these circumstances, water storage can, by safeguarding domestic supplies and supporting crops and/or livestock during dry periods, significantly increase agricultural and economic productivity and enhance people’s well-being. Sector-wise utilization and per capita water consumption is given in Figure 2. Water storage can also contribute to electricity generation and providing water supply to commercial and industrial enterprises. Consequently, it has an important role to play in poverty reduction, sustainable development and adaptation to climate change. Yet, despite greater rainfall variability than many other places, per capita water storage is lower in Africa and Asia than elsewhere in the World. Lack of water storage infrastructure is posited by some as a major constraint to economic development in many developing countries (Grey & Sadoff, 2006). Physical water storage, for the future needs to rethink water storage in a future of rapidly rising population and increasing uncertainty related to climate change, and for better planning and management large dams are often the first thing that comes to mind when “water storage” is mentioned. Mainly because of their considerable financial requirements, as well as the political opportunities that they represent, large dams (defined as those greater than 15 meters (m) high or with storage capacity exceeding 3 million cubic meters (Mm3) for heights between 5 and 15 m (ICOLD, 2003) have often been the principal focus of water storage efforts in recent decades. Just under 50% of the 50,000 large dams constructed globally - since the 1950s - have been built to support irrigation.

Figure 2. Per capita water storage in cubic meters (m3) in human-made reservoirs by continent Source: White, 2005 *For a more accurate representation of this figure, please see the electronic version.

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Many others have been built to provide hydropower and domestic and industrial water supply as well as to provide flood protection. In many cases a single dam supports many of these functions (ICOLD, 2003). Numerous large dams have brought significant social and economic benefits. The broad links between infrastructure development (including dams), increased agricultural productivity and economic growth have been documented (Hanjra et al., 2009; Hussain & Hanjra, 2004). However, having a high per capita storage in large reservoirs is no guarantee of national economic development. In common with all human development, large dams also have costs. Still water storage is important because in changing climatic situations, the water requirement of agriculture may be more and the stored water in the large dams may be having the potential for fulfilling the water scarcity. From the available literature it is not very clear that the large dams will fully satisfy the future need completely in climate change situations.

Agricultural and Water Management Increasing agriculture production with population growth is the most important issue in almost all over the globe. In order to achieve this objective, the immediate solution to the farmer is enhancing the inputs to the agriculture which may not always proper for environmental health. One of the study (Fuglie, 2012) analyzed that how much of the growth in output is due to increased resources, and how much of it is due to improved productivity? After nearly four decades, of primarily resource-driven growth, a dramatic shift to productivity-driven increases in global agricultural output began around the early 1990s (Figure 3). Between 1961 and 2009, total resources and inputs grew about 60 percent as fast as growth in total agricultural output, implying that improvement in Total Factor Productivity (TFP) accounted for only 40 percent of total output growth. But TFP’s contribution to output rose over time, and between 2001 and 2009 it accounted for about 75 percent of the growth in global agricultural production. The contribution of natural resources (including land and water) to output growth has decreased gradually over time while that of input intensification (including the amount of labor, capital, and materials per hectare of land) has fallen sharply. Water management in agriculture production is one of the important parameter for high and sustainable yields. Water requirement for growth and development of every crop is different. Some crops like paddy requires more water for the growth as compared with others like sorghum and bajara. Crop stress at critical growth stages my severely reduce yield of crops or completely failure of the crop. The water requirement also vary with region as well as season. It depends on the other environmental parameters like temperature, CO2 etc. along with type of soils they grow. Rain-fed agriculture can be severely affected by long dry spells and uneven distribution of rainfall. Hence water management in agriculture depends on many parameters. Some of the environmental factors which influence crop water requirement are described briefly in below paragraphs.

C3 and C4 Plants Most agricultural plants are categorized by their photosynthetic mechanisms that control the chemical processes in their glucose manufacture from CO2 and H2O (water) as C3 and C4 species because of their photosynthetic pathways. Other plants are called CAM that stands for Crassulacean Acid Metabolism after the plant family in which it was first found (Crassulaceae) and because the CO2 is stored in the form of an acid before use in photosynthesis. Common C3 species include wheat, cotton, soybean, and 1263

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Figure 3. Sources of growth in global agricultural production

Source: Fuglie, 2012

most legumes like alfalfa while common C4 crop species include sorghum, corn, and sugarcane. Some grass species are either C3 or C4 types. C3 plants fix atmospheric CO2 directly onto 5 carbon sugar RuBP (ribulose bisphosphate) and thus into glucose. C4 plants first fix atmospheric CO2 into 4-carbon acids in the mesophyll of the leaf and decarboxylate the 4-carbon acids in the bundle sheath cells where the CO2 is then fixed by RuBP carboxylase (all of this takes place during the day). CAM plants first fix atmospheric CO2 into malic acid and other 4C-acids at night. During the day, malic acid is decarboxylated and the CO2 released is then fixed by rubisco (all of this takes place in the same cell). Generally, the C4 photosynthetic pathway is considered more water efficient than C3 species. However, C3 species typically are more sensitive to elevated CO2 (Rosenberg et al., 1988). The carbon-fixing efficacy of Rubisco depends on the ratio of CO2:O2. For C3 plants, this is closely coupled to ambient conditions, and efficacy is approximately 2/3 while for C4 plants, the CO2:O2ratio is much greater and carboxylation efficacy is nearly 100% (Ainsworth & Rogers, 2007). Therefore, increased CO2 in air should directly increase assimilation for plants with C3 physiology. For C4 plants, the elevated CO2 effects are indirect due to increased stomatal resistance and reduced transpiration. Climate change (changes in temperature and/or precipitation regimes) would likely lead growers to change crops, cultivars, and management practices, including irrigation, to mitigate any adverse effects or to take advantage of more favorable conditions. Peterson & Keller (1990) suggested that higher temperatures and reduced precipitation could increase crop water demand in some areas and prompt the development of irrigation in regions previously devoted to dry-land or rain-fed cropping.

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CLIMATE CHANGE IMPACTS ON AGRICULTURAL WATER MANAGEMENT Agriculture encompasses various activities including raising crops, raring livestock, poultry, fisheries etc. Availability of water for successful agriculture production is very important. As discussed above each crop water requirement is specific which is based on soil and various climatic parameters. Cropping pattern of any region is established over period of time based on available soil and climatic situation and farmer’s knowledge base. Scientific evidences shows that due to global warming the climatic parameters are changing which may be having direct or indirect impact on global agriculture production. Plant systems, and hence crop yields, are influenced by many environmental factors, and these factors, such as moisture and temperature, may act either synergistically or antagonistically with other factors in determining yields (Waggoner, 1983). In most land regions the frequency of warm days and warm nights may likely increase in the next decades, while that of cold days and cold nights will decrease. The impact of various climatic parameters on global agriculture from available literature is summarized in table 1.The below discussion is trying to analyze the impact of climate change on water availability to agriculture and its production.

Precipitation Precipitation that regulates life on Earth and soil moisture is essential to sustain plant growth and biodiversity flourishes where water is abundant. Precipitation also has a bearing on local climate (Priestley, 1966). Variation in the precipitation may be having large impact on agriculture production on the globe. The general pattern of wet-get-wetter (also referred to as ‘rich-get-richer’, e.g., Held & Soden 2006; Chou et al., 2009; Allan et al., 2010) and dry-get-drier has been confirmed, although with deviations in some dry regions at present that are projected to become wetter by some models. It has been demonstrated that the wet-get-wetter pattern implies an enhanced seasonal precipitation range between wet and dry seasons in the tropics, and enhanced inter-hemispheric precipitation gradients (Chou et al., 2007). Intergovernmental Panel on Climate Change in AR5 report (Kirtman et al., 2013) presented results of Coupled Model Intercomparison Project (CMIP5) for projections of near-time changes in precipitation (Figure 4). It is clear from the Figure 4 that the basic pattern of wet regions tending to get wetter and dry regions tending to get dryer is apparent. There may be some regional deviations in the precipitation pattern. There may be possibility of the uncertainty in the substantial spread in the magnitude of projected change based on the simulation models used. The Figure 4 also highlight the large amplitude of the natural internal variability of mean precipitation. On regional scales, mean projected changes are almost everywhere smaller than the estimated standard deviation of natural internal variability. For zonal means and at high latitudes, the projected changes relative to the recent past exceed the estimated standard deviation of internal variability. The Figure 4 also depicts that the overall, zonal mean precipitation will very likely increase in high and some of the mid latitudes, and will more likely than not decrease in the subtropics. In case of the regional scales precipitation changes may be influenced by anthropogenic aerosol emissions and may be strongly influenced by natural internal variability. Figure 4 Time series of relative change relative to 1986–2005 in precipitation averaged over land grid points over the globe in October to March. Thin lines denote one ensemble member per model, thick lines the CMIP5 multi-model mean. On the right-hand side the 5th, 25th, 50th (median), 75th and 95th percentiles of the distribution of 20-year mean changes are given for 2081–2100 in the four RCP scenarios. 1265

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Table 1. Climate change fact and impact on crop production Parameter

Temperature

Water Cycle

Extreme Events

Sea Level

GHG

Land Use Change

Earth’s Energy Budget

Fact

Effect

Global Mean Surface Temperature

Has increased since the late 19th century.

Comparison with past

Each of the past three decades has been successively warmer at the earth’s surface than all the previous decades in the instrumental record, and the first decade of the 21st century has been the warmest.

Global Mean Temperatures

Will continue to rise over the 21st century if Greenhouse Gas (GHG) emissions continue unabated.

Impact on different regions

Temperature change will not be regionally uniform.

Temperature extremes

In most places, there will be more hot and fewer cold temperature extremes.

Global temperatures rise.

Mean sea level pressure is projected to decrease in high latitudes and increase in the mid-latitudes.

Precipitation

In the long term, global precipitation will increase with increased global mean surface temperature.

Average precipitation in warmer world

Will exhibit substantial spatial variation. Some regions will experience increases, other regions will experience decreases and yet others will not experience significant changes at all.

Annual surface evaporation

Projected to increase as global temperatures rise over most of the ocean and is projected to increase over land.

Humidity

Global near surface and tropospheric air specific humidity have increased since the 1970s.

Day and night temperature

It is very likely that the numbers of cold days and nights have decreased and the numbers of warm days and nights have increased globally since about 1950.

Warm days and warm nights

In most land regions the frequency will likely increase in the next decades.

Cold days and cold nights

In most land regions the frequency will likely decrease in the next decades.

Precipitation

Since about 1950 the number of heavy precipitation events over land has increased in more regions than it has decreased.

The rate of sea level rise

Increased from the early 19th century to the early 20th century, and increased further over the 20th century.

CO2

Increased by 40% from 278 ppm about 1750 to 390.5 ppm in 2011.

CH4

Increased by 150% from 722 ppb about 1750 to 1803 ppb in 2011.

N2O

Increased by 20% from 271 ppb about 1750 to 324.2 ppb in 2011.

Radiative Forcing (RF)

There is robust evidence that anthropogenic land use change has increased the land surface albedo, which leads to Radiative Forcing (RF) of – 0.15 ± 0.10 W m–2.

Zonal mean precipitation

Will very likely increase in high and some of the mid latitudes, and will more likely than not decrease in the subtropics.

Specific humidity

Increases in near-surface over land are very likely.

Evaporation

Increases in over land are likely in many regions.

Independent estimates of effective RF of the climate system

The observed heat storage, and surface warming combine to give an energy budget for the Earth that is closed within uncertainties (high confidence), and is consistent with the likely range of climate sensitivity.

continued on following page

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Table 1. Continued Parameter

Monsoon Systems

Fact Future changes

The global monsoon, aggregated over all monsoon systems, is likely to strengthen in the 21st century with increases in its area and intensity.

Monsoon circulation

The global monsoon circulation weakens.

Monsoon onset and retreat dates

Onset likely to become earlier or not to change much and monsoon retreat dates are likely to delay, resulting in lengthening of the monsoon season in many regions.

Annual precipitation change

Follows a ‘warmer-get- warmer’pattern, increasing where warming of sea surface temperature exceeds the tropical mean and vice versa.

Projections

It is likely that the global frequency of occurrence of tropical cyclones will either decrease or remain essentially unchanged, concurrent with a likely increase in both global mean tropical cyclone maximum wind speed and precipitation rates.

Regional projections

The future influence of climate change on tropical cyclones is likely to vary by region.

Crop yield

In developing countries, climate change will cause yield declines for the most important crops. South Asia will be particularly hard hit.

Irrigated crop

Will have varying effects on yields across regions, but yields for all crops in South Asia will experience large declines.

Higher maximum temperatures, more hot days and heat waves over nearly land areas

Increased risk of damage to a number of crops

Increased summer drying over most mid-latitude continental interiors and associated risk of drought

Decreased water resource quantity and crop yields.

Intensified droughts and floods associated with El niño events in many different regions

Decreased agricultural and rangeland productivity in drought- and floodprone regions.

Increased intensity of midlatitude storms

Increased damage to coastal ecosystems.

Food price

Will result in additional price increases for the most important agricultural crops–rice, wheat, maize, and soybeans.

Fodder price

Higher feed prices will result in higher meat prices. As a result, will reduce the growth in meat consumption slightly.

Calorie

Calorie availability in 2050 will not only be lower than in the no-climatechange scenario-it will actually decline relative to 2000 levels throughout the developing world.

Calorie and child nutrition

By 2050, the decline in calorie availability will increase child malnutrition by 20 percent relative to a world with no climate change. Climate change will eliminate much of the improvement in child malnourishment levels that would occur with no climate change.

Higher maximum temperatures, more hot days and heat waves over nearly land areas

Increased heat stress in livestock and wildlife

Cyclones

Crop Yield

Livestock

Effect

Source: Hartmann et al., 2013, Collins et al. 2013, Rhein et al. 2013, Myhre et al., 2013, Christensen et al., 2013, Nelson et al. 2009 & IPCC, 2001

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In response to GHG forcing, dry land areas tend to show a reduction of evaporation and often precipitation, accompanied by a drying of the soil and an increase of surface temperature, in response to decreases in latent heat fluxes from the surface (e.g., Fischer et al., 2007; Seneviratne et al., 2010).

Evapotranspiration The main source of water for agriculture production is through precipitation and the loss of water in the form of evaporation depends on the climatic conditions of the region. It has long been recognized (Priestley, 1966) that the availability of surface water regulates evaporation and local temperature. Where there is abundant surface water and plant growth, the local evaporation constrains temperature and in hot climates temperatures are very much higher in the absence of surface evaporation. So it is necessary to have proper balance between precipitation and evaporation for agriculture production. The evaporation of surface water and condensation of atmospheric water vapor to form clouds and precipitation, is an essential component of energy flow through the climate system. This phenomenon may be explained by the Clausius-Clapeyron relationship which is the rate of increase of saturated vapor pressure with temperature and is important in regulating many of the processes of the hydrological cycle. The global atmospheric water content is constrained by the Clausius–Clapeyron equation to increase at around 7% K-1; however, both the global precipitation and evaporation in global warming simulations increase at 1 to 3% K-1 (Lambert & Webb, 2008; Lu & Cai, 2009). Consideration of hydrological drought conditions employs a range of different dryness indicators, such as soil moisture or other drought indices that integrate precipitation and evaporation effects (Seneviratne et al. 2012). In order to provide an indication of future changes of water availability, figure 4 (b) presents zonal mean changes in precipitation minus evaporation (P - E) from Common Management Information Protocol CMIP5 (Kirtman et al., 2013). As in the case of precipitation (Figure 4), the uncertainty is Figure 4. Multi-model projections of changes in annual and zonal mean (a) precipitation (%) and (b) precipitation minus evaporation (mm day–1) for the period 2016–2035 relative to 1986–2005 under RCP4.5. The light blue denotes the 5 to 95% range, the dark blue the 17 to 83% range of model spread. The grey indicates the 1σrange of natural variability derived from the pre-industrial control runs

Source: Kirtman et al., 2013

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dominated by model differences as opposed to natural variability (compare blue versus grey shading). The results are consistent with above discussion on the wet-get-wetter and dry-get-drier pattern. In the high latitudes and the tropics, most of the models project zonal-mean increases in P – E, which over land would need to be compensated by increases in runoff. In contrast, zonal mean projected changes in the subtropics are negative, indicating decreases in water availability. Evapotranspiration is the combined effect of evaporation and transpiration, and it is a key part of the hydrologic cycle. Evaporation is simply the phase change from liquid water to water vapor as temperature increases. Transpiration involves the uptake of water in soil by plants, the transport of water through the plant, and its eventual evaporation from plant leaves and other surfaces. Evapotranspiration is a natural cooling process because heat at the earth’s surface is captured by water droplets, which, through evaporation, disperse the heat out of the atmosphere and into space.

Change in CO2 Levels The prevailing view among researchers is that global climate change may prove beneficial to many farmers at least in the short term. The logic is straightforward: Plants need atmospheric carbon dioxide to produce food, and by emitting more CO2 into the air will cause some crops and trees to grow bigger and faster. The latest analysis of observations from the Global Atmosphere Watch (GAW) Programme (WMO 2014) shows that the globally averaged mole fractions of Carbon dioxide (CO2), Methane (CH4) and Nitrous Oxide (N2O) reached new highs in 2013, with CO2 at 396.0±0.1 ppm, CH4 at 1824±2 ppb and N2O at 325.9±0.1 ppb (Table 2). The change in atmospheric CO2 levels will have impact on the vegetation. Changes in evapotranspiration over land are influenced not only by the response to Radiative Forcing (RF), but also by the vegetation response to elevated CO2 concentrations. Physiological effects of CO2 may involve both the stomatal response, which acts to restrict transpiration (Cao et al. 2009; Field et al. 1995; Hungate et al. 2002; 2010; Lammertsma et al., 2011), and an increase in plant growth and leaf area, which acts to increase evapotranspiration (Bounoua et al. 2010; El Nadi, 1974).

Table 2. Global annual mean abundances (2013) and trends of key greenhouse gases. Units are dry-air mole fractions, and uncertainties are 68% confidence limits CO2

CH4

N2O

396.0 ± 0.1 ppm

1824 ± 2 ppb

325.9 ± 0.1 ppb

142%

253%

121%

2012–2013 absolute increase

2.9 ppm

6 ppb

0.8 ppb

2012–2013 relative increase

0.74%

0.33%

0.25%

2.07 ppm/yr

3.8 ppb/yr

0.82 ppb/yr

Global abundance in 2013 2013 abundance relative to year 1750a

Mean annual absolute increase during last10 years

Assuming a pre-industrial mole fraction of 278 ppm for CO2, 722 ppb for CH4 and 270 ppb for N2O. Stations used for the analyses numbered 124 for CO2, 121 for CH4 and 33 for N2O. [Source: WMO (2014)] a

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PROSPECTS FOR ADAPTATION MITIGATION Intergovernmental Panel on Climate Change (IPCC, 2001), suggested that adaptation is gaining attention as an expected answer to the challenges posed by climate change. The increasingly uncertain climatic conditions to which actors are exposed may becoming a constraint for their well-being. Given the range of warming predicted by the scientific community, regional and local variation in impacts on the agricultural production may likely to be high. A critical challenge for farmers in developing countries is how to cope with increased variability and uncertainty in current and future rainfall patterns, a phenomenon which is affecting rain-fed and irrigated farming alike. Further, the concern with climate change is sensitive given the linkage of the agricultural sector to the poverty. It may be anticipated that adverse impacts on the agricultural sector will exacerbate the incidence of rural poverty. Hence, improved water resource management will be vital to sustaining crop productivity in the face of climate variability. Food insecurity may continue to be a serious issue in coming decades. Climate change may significantly increase production risk and rural vulnerability, particularly in regions that already suffering from chronic soil and water resource scarcity, high exposure to climatic extremes including droughts, flooding, poverty and hunger. In order to sink with the climatic variability and retain enhanced flow of food production, some measures in the form of adaptation and mitigation will be required. Adaptation to climate impacts in the agricultural sector is not a new phenomenon. According to Rosenzweig & Liverman (1992) and Rosenberg (1992) natural systems have continuously been adapting autonomously, or in accordance with a plan, to a changing environment throughout history. Adaptation may be defined as a process or action of adjusting to different circumstances or conditions, in this case as a result of a changing climate. Availability of water for agriculture depends on many climatic parameters like precipitation, temperature, atmospheric CO2, etc. Hence judicious management of water resource for sustainable agriculture development may require proper adoption to the changing climatic parameters. The adaptations includes several steps starting from micro level adaptation as farm production adjustments such as diversification and intensification of crop and livestock production; changing land use and irrigation; and altering the timing of operations. The adaptations can also include numerous market responses that have emerged as potentially effective adaptation measures to climate change, development of crop and flood insurance schemes, innovative investment opportunities in crop shares and futures, credit schemes, and income diversification opportunities. The options of adaptations may include government responses and institutional changes, pricing policy adjustments and technological developments. Hence, adaptations can be broadly grouped in to Short-Term and LongTerm adaptations (Figure 5).

Short-Term Adaptations The short- term adaptations to the climate change may be having benefits to the farmers for shorter period of time and can be implemented immediately. Existing literature suggests that such types of adaptations are more appropriate to address short-term climatic concerns. These adaptations may include the following.

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Figure 5. Apaptations in agriculture

Farm Responses Among the most important and direct current adaptations to climate variability are some of the farm level responses. The farm response adaptations can include the crop and livestock diversification as well as changes in timings of various farm operations. Improved nutrient and pest control management can also be part of adaptation in farm response.

A. Crop and Livestock Diversification and Changes in Timing of Farm Operations Crop diversification refers to the addition of new crops or cropping systems to agricultural production on a particular farm taking into account the different returns from value-added crops with complementary marketing opportunities. Diversification may be a key factor in reducing risk and means of coping with an uncertain climate and further unpredicted water for agriculture production. Crop is the major activity worldwide for livelihood followed by livestock production. Diversification of crop and livestock varieties, having the potential to increase productivity in the face of temperature and moisture stresses may be helpful. Diversity in seed genetic structure and composition may be an effective defense against numerous factors, including water stress, disease and pest outbreak and importantly climate hazards. It is also predicted, there may be shift of cropping seasons and adjusting to such situations options include changes in the timing and intensity of production. Delcourt & Van kooten (1995), Brklacich et al. (2000), de Loe et al. (1999) have given following options for addressing impacts on yields and soils from climate change. • • • •

Changing land-use practices such as the location of crop and livestock production. Rotating or shifting production between crops and livestock. Shifting production away from marginal areas can help reduce soil erosion and improve moisture and nutrient retention. Altering the intensity of fertilizer and pesticide application as well as capital and labor inputs.

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• • •

Adjusting the cropping sequence, including changing the timing of sowing, planting, spraying, and harvesting, to take advantage of the changing duration of growing seasons and associated heat and moisture levels. Altering the time at which fields are sowed or planted can also help farmers regulate the length of the growing season. Changing the timing of irrigation.

Many researchers suggested various adaptation measures for livestock and rangeland management. Following are few suggestions for livestock and rangeland management outlined by Baker and Viglizzo (1998), Chiotti et al. (1997), IPCC (1996). • • • • • • • • • • •

Change in grazing timing, duration, and location. Varying supplemental feeding. Changing the location of watering points. Altering the breeding management program. Changes in rangeland management practices. Modifying operation production strategies as well as changing market strategies. In temperate climatic areas, planned adaptation measures in livestock management that are advocated include the use of vegetative barriers or snow fences to increase soil moisture, or windbreaks to protect soil from erosion. In warmer climates, adverse climatic conditions such as heat stress can be moderated by the adoption of appropriate technology such as the use of sprinklers in livestock buildings or feedlots. Adjusting livestock stocking rates. Implementing feed conservation techniques and fodder banks to moderate the consequences for animal production during periods of poor crops. Increasing native rangeland vegetation or plant-adapted species.

Working with various adoptions there may be numerous constraints farmers and livestock holders may encounter which make these farm level adaptations difficult. The short term adaptations are not costless. For example (Skees et al. 1999) the most significant problem to overcome is that diversification is costly in terms of the income opportunities that farmers forego (that is, switching crop varieties can be expensive, making crop diversification typically less profitable than specialization). In addition to this traditions can often by difficult to overcome and will dictate local practices. In such situation, if a local region has a long and rich tradition of planting a particular crop variety, the change to newer and more suitable varieties can be hard.

B. Improved Nutrient and Pest Control Management Increased CO2 levels and higher temperatures are likely to create stress in crops and livestock and may induce a need for more plant protection. Changes in the application of various chemicals may further enhance the problem. For the climate change situation alternative production techniques and crops, as well as locations, that are resistant to water stress, infestations and other risks may also be relied upon as effective response strategies. Following are a range of management practices have emerged that can

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assist farmers adapt to loss of soil moisture and organic carbon contents and increased soil erosion as a result of changing climate situations (Erda 1996 and Parry 2000). • • • • • • •

Improved nutrient management techniques to maintain soil fertility and prevent erosion. For the increased frequency of droughts, farmers can further adapt by changing the selection of crops. Introduction of management techniques that conserve soil moisture, such as reduced or no tillage, in order to maintain soil organic carbon contents can result in improved soil structure and fertility. Increasing production per unit of evapotranspiration with the use of new and improved varieties. Reducing water use in land preparation as well as loss (through seepage and percolation) during the crop growth period. Adoption of efficient water use methods. The diffusion of appropriate technology to enhance greater water use efficiency like drip-irrigation.

C. Temporary Migration Temporary migration is also called circular migration in agriculture. It includes seasonal migration, where workers undertake off-farm or non-farm activities for some part of the year, and returning back during harvest time. The temporary migration is the movement of labor from one agricultural area to another area, or across sectors. This also includes migration between and within urban and rural to ensure security in livelihood. It is not much clear from the available literature to what extent climate change per se can be attributed as the primary factor in the decision making process of households engaged in agriculture on whether or not to migrate. But in case of adverse climate the livelihood of poor and marginal household families may be difficult. However, in such situation the temporary migration to the other agriculture or nonagriculture areas for the period of adverse condition may be an option of livelihood. The option of such types of migration for livelihood may be useful for extreme events in climate change.

D. Insurance There may be much uncertainty about the agriculture production as successful crop yield depends on the availability of water and climate of the region. So the households engaged in agriculture may face problem for the livelihood in case of crop failure and inherently need insurance mechanisms to cope with income risks. The types of risks faced by the agricultural sector are outlined below (Moreddu 2000). • • • •

Production risks due to weather variation, crop disease and various other causalities, Ecological risks from climate change, pollution, and natural resource management, Market risks, which depend on input and output price variability, and Regulatory or institutional risks due to state intervention in agriculture.

Furthermore, households with extremely low incomes may be at highly risk and will limits their financial ability and willingness to adopt new technologies that can maintain and enhance crop productivity. In such situation, the insurance will help farmers to reduce the financial risk when they adopt for

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new technology or adaptation. The insurance may encourage the farmers to with stand in small climatic variations by reducing financial risk of livelihood in case of failure of the crops.

Long-Term Adaptations Efforts are necessary to withstand and minimize the adverse impacts of short term climate variability and uneven water availability for agriculture. The measures will be necessary to reduce vulnerability to anticipated future impacts of climate change. So the combination of adaptations both at farm and policy level will be necessary for long term adaptation for future water related consequences scarcity due to climate change. Following paragraphs describes a range of adaptation options as most relevant in water availability and overall climate change. The interaction of water for agriculture production is governed by climatic situation. However, given that warming is largely a concern of the future, long term adaptation must also be in the future. Kurukulasuriya and Rosenthal (2003) also reported that addressing climate change- a long term phenomena, should entail a comprehensive long term response strategy at the national or local level but will require a dynamic approach. Some of the important long term strategies for adaptation of availability of water for agriculture and climate change are discussed below.

A. Changing Crop Type and Location The main purpose of changing the crop types or location of cultivation of crops is to cultivate stress resistant crops on its suitable location. The potential options include switching to more robust varieties that are better suited to the changing environment. Agricultural analyses of future climates indicate also that crops will move poleward with warming (Mendelsohn and Neumann 1999). The extent of this migration depends upon the severity of the warming. This types of adaptation require a number of underlying prerequisites are in place. Obviously, the scope for shifting production to new lands, particularly in developing countries where, may be limited because of population pressures and the availability of cultivable land. There may be another constrain that farmers may not be willing and ability to move. Further, land use regulations on agricultural production are governed by country laws and may hinder such adaptations in some of the countries. In such situation, crop rotations that may not be optimal in interest of available water for agriculture production and a changed environment may be persisted. This may consequence in severe losses in the long term. Appropriate land reform policies that establish or strengthen property rights in changing demand of water for agriculture need to be enforced. It is also necessary that appropriate measures that boost farmer’s financial ability to undertake the necessary adaptation may be necessary. These financial measures may include improving access to credit and banking facilities in rural areas. Furthermore, investment in diffusion of access to sufficient and timely irrigation is important. Appropriate institutional support to promote the dissemination of knowledge through dedicated extension network may play important role in such situations. There is good amount of debate in agriculture research that the new crops are equally (if not, more) profitable to the farmer. There is also serious concern that changing crop types will not automatically maintain previous levels of food production as well as or nutritional quality levels. While the national objective may be to grow crops that will fulfill food security with minimum water requirement.

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B. Development of New Technologies and Modernization Agriculture research on the globe has crossed many milestones and has many success stories. Research and technological innovation in crop and animal productivity is important to achieve food security in changing environmental conditions. This will enable farmers to cope with various climatic conditions and may be fundamental to the growth and development of agriculture. There are two basic types of technological options (Smithers and Blay-Palmer 2001), important for agriculture viz. mechanical and biological. Mechanical innovations include irrigation, conservation tillage, and integrated drainage systems. On the other hand, biological options also have an important role in enabling cropping systems to adapt to a wide range of climatic conditions. Investment in crop breeding, the promotion of climateresistant varieties that offer improved resistance to changing diseases and insects, breeding of heat- and drought-resistant crop varieties, the use of traditional varieties bred for storm and drought resistance, and investment in seed banks may be necessary for success in overcoming vulnerability to climate. Further, advances in science and biotechnology offer much powerful tools that hold promise to overcome the challenges posed by scarcity of water resources and threats posed to the agricultural production. However, it is not very clear that how much role the advocacy of biotechnology will play as adaptation in climate change scenario. In addition to this the issue of affordability of new technology to poor farmers may be serious concern for effective climate change. Several innovative concepts and technologies like geographical information systems, software-based weather systems, low-cost and decentralized technologies, industrial symbiosis (Rao & Patil, 2015) and as well as innovative waste treatment with simultaneous resource conservation method have also been reported (Patil & Rao, 2015).

C. Improving Water Management Availability of water is most important for successful agriculture production. Improved water resource management will be vital to sustaining crop productivity levels in the face of both climate variability and longer-term change. In areas that are currently dependent primarily on rain-fed agriculture, the conjunctive use of surface and ground water resources will play an increasingly important role in enabling farmers to adapt to fast changing climatic conditions. However, it is also clear that in the face of rising domestic and industrial demand, additional efforts are necessary to ensure efficient management of water resources. With climate change and variability increasing pressure on available water resources, improved water management is one of the most important long-term adaptation options that countries must pursue. According to recent estimates, irrigation efficiency in developing countries is extremely low. The average efficiency of irrigated agriculture in developing countries is very low. Preserving water resources using suitable storage may play a crucial role in availability of water in changing climate. However, if the planning of water storage is not improved, it may likely that many investments may fail to deliver intended benefits. McCartney et al. (2013) reported that, national economies, highly dependent on rainfed agricultural production, are exceedingly vulnerable to both intra-annual and inter-annual fluctuations in rainfall and hydrology. In addition to this traditional adaptation techniques may also be effective to deal with shortages in water. Apart from water storages there may be challenges with regard to water use and availability that also need to be overcome. Increased demand for water by municipal and industrial sectors may further become serious issue in future. Un-sustained and over exploited irrigation may lead to groundwater depletion, soil salinization and water-logging. In some regions, numerous challenges need to be overcome in order 1275

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to increase water supply. As emphasized by Dinar (2000), these challenges include financial crises; lowcost recovery of the investment in the water system; the role of political parties, electoral systems and interest groups. Dinar argues for improved forecasting procedures, simulation models, and improved data monitoring systems. Other necessary preconditions include overcoming economic constraints. The improvements in irrigation and other high-efficiency water conservation technology require major, long-term and costly investments. Furthermore, undertaking requisite institutional reforms that hinder the pursuit of effective water resource management strategies may also be helpful. However, given the uncertainty surrounding forecasts of regional changes in precipitation, it has not yet been proven that making water adaptations in advance of climate changes is in fact very practical.

D. Permanent Migration of Labor Encompasses permanent migration in the form of the movement of migrants into new economic areas. The possible reasons for migration may be possibly due to policies or permanent changes in their previous environment. The agriculture labor migration may be from poorer agricultural areas in one region to lowlands in other regions. Desanker (2002) stresses, long-lasting climate pressures, such as prolonged drought, which increase the vulnerability of migratory groups to climate change (by limiting the scope of areas to move to), can be disastrous. Short-term migrants may be forced into becoming more permanent migrants, resulting in dire consequences such as pressures on land and water resources. The adaptations outlined in the above sections may not fully address the concerns of permanent labor migration with short term climate variability may not be adequate in the face of new and long lasting climate conditions. Reilly et al. (2003) reported that even insurance programs will not be sufficient if productivity of land becomes unviable and may in fact act as a deterrent to change despite market signals that indicate otherwise. If unmanaged or uncontrolled, large-scale migration of this type may have consequence in significant impacts on the environmental resource bases as well as indigenous societies. In such complex situations, a clearly defined system of property rights and enforcement may be necessary to prevent potential stress. The establishment of an appropriate system of property rights both at the individual or community level may be part of the likely solution. Well placed training and extension services may be act as other solutions that would be needed based on the situations.

E. Adaptations Irrespective of the Temporal Dimension of Climate Impacts Non-climatic parameters are also equally important for agriculture production on sustainable basis. Suitable policies aimed at growing the resiliency of the agriculture sector to other, including non-climatic factors may be necessary and may help in improving capacity to cope with both climate variability and climate change. Further, Smit and Olga (2001) emphasized on solving immediate concerns facing domestic agriculture sectors do not delay the formulation and implementation of efficient responses to promote long term sustainability issues. Such effective adaptation may also depend considerably on primary local environmental, institutional, and socio-economic conditions. Both domestic, and regional cooperation in science, resource management, and development may be extremely important. Some of the major economic and institutional issues may likely to be beneficial irrespective of the nature of the climate change are as follows.

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• • •

Investment and accumulation of capital. Reform of pricing schemes, development of open markets, and other reforms. Adoption of new technologies.

F. Promotion of Trade Suitable market and appropriate return to the agriculture produce is the key to success for the farmers. Suitable market for agriculture produce is important for both buyers and consumers. Here suitable trade may play an important role during periods of variable climatic. There may be possibility that agricultural trade may moderate impacts by enabling farmers in regions less adversely affected to sell their produce in areas more severely affected by climate change. The role of trade policy may important because of repercussions on the prospects for adaptation. Further, regional and international trade may lead to improvements in access to international markets, which in turn may help a country diversify and reduce of risk of food security from water scarcity and climate change.

G. Extension Services Extension services have played a key role in promoting agricultural productivity in developing countries. Their role in promoting various adaptations to climate change may be very important. Traditionally, extension services have generally been in the purview of services provided by government, given that agricultural research is typically a public good. However, private and non-governmental agencies or the formation of research cooperatives do play a significant role in some countries. Crucially, as Evenson (1997) notes, the economic contribution of extension services is governed by location-specific factors. In this regard, numerous programs have been found to be ineffective given the underperformance of agents, design limitations, and management failures. Overall, efficient, farmer friendly extension policies may coup farmer’s efforts to maintain sustainable flow of agriculture production in uneven availability of water in changing climate.

H. Diversification of Income-Earning and Employment Opportunities Seasonal effects and climatic uncertainty that characterize the agricultural sector effectively mean that diversification of income and employment opportunities may be an important adaptation strategy for households in the agriculture sector. In dryland areas, traditional practices to help cope with drought include the accrual of a surplus in a superior year, in the form of cash or assets (for example, cattle) for use in poorer years (Burton 2001). While measures such as crop storage, sales, and household savings can and do offer relief from temporary or seasonality effects, risk and market imperfections that abound in rural settings render diversification into off-farm opportunities necessary to reduce income instability (Alderman and Paxson 1992). Consequently, policies that provide the opportunities to pursue alternative livelihood options need to be encouraged.

I. Dissemination of Climate Data A reason in literature frequently cited for not adapting in time to climatic impacts is the lack of reliable climate monitoring and forecasting data. Barnett (2001) argues that an increase in the availability of 1277

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information to understand the biophysical and social environment is necessary. The timely dissemination of climate forecasting information and early warning to farmers including information on risks can strengthen the ability of farmers to cope and optimize the management of hydrological variability and change. Monitoring data and indicators of change are also necessary across all sectors in society, not just policy makers. Along with information on risks, the information on suitable mitigation measures may be helpful to farmers.

J. Institutional Planning and Implementation Insufficient institutional and decision making structures to support long-term planning in governments in developing countries has long been recognized to be a problem in pursuing general development objectives. At World Bank report underscored the finding that in some countries, such as Bangladesh, planning for climate change is not even mandatory, an outcome of planning agencies’ being “formed not by law but by administrative resolution” (Kurukulasuriya and Rosenthal 2003). Long term institutional planning related to climatic variability and suitable implementations are important.

Mitigation Mitigation is human intervention to reduce the extent of climate change. It includes strategies to reduce greenhouse gas sources and emissions, and enhancing greenhouse gas sinks. A number of mitigation strategies in the agriculture and forestry sectors have been identified as useful in achieving the goal of stabilization of atmospheric concentrations between 450-550 ppm CO2. These include reduced deforestation and degradation of tropical forests (REDD), sustainable forest management (SFM) and forest restoration (FR), including afforestation and reforestation (A/R). In agriculture, they involve reduction of non-CO2 gases through improved crop and livestock management and agroforestry practices, enhanced soil carbon sequestration in agricultural soils via reduced tillage and soil biomass restoration (Table 3). Table 3. Mitigation potential in agriculture and forestry in 2030 Sr. No. 1

2030 Reductions

G tonnes CO2 e yr-1

Global

15-25

2

Agriculture

1.5-5.0

3

Methane, N2O

0.3-1.5

4

Agroforestry

0.5-2

5

Agricultural soils

0.5-1.5

6

Forest

2.5-12

7

REDD

1-4

8

Sustainable forest management (SFM) SFM

1-5

9

Forest Restoration (FR)

10

Bioenergy Total

Source: IPCC (2007)

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Global reductions in 2030 correspond to those needed to achieve stabilization of atmospheric concentrations between 450-550 ppm CO2, under a mid-range IPCC SRES. In case of long term sustainable availability of water for agriculture can be achieved by investing in wider best practices. These practices can include the following.

I. Reducing Emissions of Green House Gases The greenhouse gases include CO2, methane and nitrous oxide and keep green gases under the limit, by adopting the effective ways. The practices that will help to reduce Carbon dioxide (CO2) levels may include land conversion, reduced deforestation, improved ways to manage wildfires and alternatives to the burning of crop residues. The Methane and Nitrous Oxide in the environment can be managed using practices like improved nutrition for ruminant livestock, efficient management of livestock waste, and efficient management of irrigation water on rice fields, efficient applications of nitrogen fertilizer on cultivated fields and reclamation of treated municipal wastewater for aquifer recharge and irrigation. The mitigation practice may also include reduction of emissions from commercial fishing operations and more efficient energy use by forest dwellers, commercial agriculture and agro-industries.

II. Sequestering Carbon Sequestering Carbon is fixing the excess of Carbon dioxide in to ecosystem. The some of the means for such sequestering CO2 includes improved management of soil organic matter, conservation agriculture involving permanent organic soil cover with minimum mechanical soil disturbance and appropriate crop rotation. The Carbon sequestering can also be achieved by reducing use of fossil fuel, improving management of pastures and sustainable grazing practices on natural grasslands. In the agriculture introduction of integrated agro-forestry systems, proper use of degraded and marginal lands and planting of carbon sink trees will also help in sequestering Carbon in the ecosystem.

FUTURE RESEARCH DIRECTIONS The increased demand for other uses coupled with recurrent drought and climatic changes in countries of limited water resources, is producing unprecedented pressure for reducing the share of fresh water used in irrigation. Many countries give priority of water allocation to the domestic sector followed by tourism and industry, and what is left is allocated to agriculture. At the same time that agriculture is asked to give water to other uses, the increasing population demand requires increase in food production. This creates a conflict that may be resolved and by examining different options of water uses for sustainable agriculture. Increasing the efficient use of water is a key non-structural approach to water resources management. The agriculture water use efficiency and water productivity is very important as they are largely inefficient in many countries due to poor distribution systems and excess irrigation. The average agricultural water use efficiency in developing countries is very poor. Water planners and decision makers as well as researchers are facing with difficulties and challenges. Some options for

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such constraint may be helpful to sustain agriculture in changing climate in the various regions on the globe. The probable solution to this conflict requires greater understanding and systematic research. The future agriculture production depends on water resources and their allocation and management in agriculture. The domains of future research may include: improving water use efficiency, reducing crop consumption of water, irrigation with reclaimed water, practicing deficit irrigation and irrigation with desalinated water. The research vision for the next few years could include the few set of actions viz. have more efficient use and allocation for water use in irrigation; improved water productivity by introduction of new management measures such as deficit irrigation; and introduction of high yielding low water demanding varieties. Desalination of brackish and sea water can offer limitless fresh water that can be used for agriculture. There is a need to find cheap methods of desalination such as the use of solar and renewable energy. Therefore, researchers should consider these needs in setting up their research priorities.

CONCLUSION The world’s climate is changing, and the changes will have an enormous impact on people, ecosystems, and energy use on the globe. There is threat that climate change will impact food availability, access, and utilization due to change in the climatic parameters like temperature, precipitation, CO2.etc. The change in environmental parameters may change availability of water for agriculture. The demand of growing population for food security is crucial and uneven availability of water due to climate change will exaggerate the problem to greater extent. The impact of non-availability of sufficient and timely water for agriculture will lead to more poverty and degradation of land resources. Apart from this there is also increasing requirement of water for urban and industries. So increasing agriculture production, sharing water for nonagricultural uses and uneven availability of water due to climate change may exaggerate the problem to the greater extent in the future. Though researchers and water managers are trying hard for the solution and the complexity of the issue will be more serious in coming decades. The aggregate impact of climate change on the water resources of the globe is not fully understood. The changing climate is playing central role in availability of water for agriculture production and individual climatic parameters and their interactions are equally important. There is an emerging consensus that changes in water resources can have detrimental impacts on the food security, in the absence of adaptation. Most of the impacts are not easy to quantify because they depend on a range of assumptions. The available quantitative scientific studies suggest that the wet regions will be more wet and dry will be more dry in coming decades which is serious concern for food security. This may reduce crop yields and the land suitable for agricultural production or change in cropping pattern and planting and harvesting schedules. Institutional development will have to play a greater role through polices supported by efficient extension programmes for mitigation of the future impact of climate change. Overall, the climate change may be having positive as well as negative effect on the water resources, agriculture production and food security of the world. This seems a huge challenge on the globe and require proper mitigations and adaptations measures.

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KEY TERMS AND DEFINITIONS Adaptation: Adaptation is the process by which living organism changes to become better suited to survive in their environment. Adaptation can be a physical or genetic trait that helps an organism to be better suited to survive in the environment. Agricultural Productivity: Agricultural productivity is the ratio of agricultural outputs to agricultural inputs. The agriculture inputs may include water, chemicals, fertilizers etc. used to grow crops to achieve desired yield as output. Climate: It can be described as average temperature and precipitation over a period of time. Climate can be defined as an area’s long-term weather patterns. The useful elements for describing climate include the type and the timing of precipitation, amount of sunshine, average wind speeds and directions, number of days above freezing, weather extremes, and local geography. Climate Change: Climate change refers to any significant change in the measures of climate parameters lasting for an extended period of time. Climate change includes major changes in temperature, precipitation, or wind patterns, among other effects, that prevailing in a region over several decades or longer. Mitigation: Mitigation in the context of climate change is an intervention intended to reduce adverse human influence on the climate system which includes strategies to reduce greenhouse gas sources, emissions and enhance greenhouse gas sinks. Resilience: Resilience is the capacity of organism or system to withstand stress and catastrophe. In case of climate change the capacity of crop and livestock to withstand and sustain in the changing environment is the resilience. Water Use Efficiency (WUE): Water use efficiency is the amount of water uptake by the plant and the amount of water used for metabolism and transpiration by the plant. WUE is simply ratio of water used in plant metabolism to water lost by the plant through transpiration.

This research was previously published in Reconsidering the Impact of Climate Change on Global Water Supply, Use, and Management edited by Prakash Rao and Yogesh Patil , pages 166-194, copyright year 2017 by Information Science Reference (an imprint of IGI Global).

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Does Nonfarm Income Affect Agricultural Income and Investment in Pakistan? Zia Ullah Khan University of Swabi, Pakistan Zahoor ul Haq Abdul Wali Khan University Mardan, Pakistan Khalid Khan Higher Education Department Peshawar, Pakistan Muhammad Ishaq Pakistan Agricultural Research Council, Pakistan Fazli Wahid University of Waterloo, Canada

ABSTRACT The study investigates the impact of nonfarm income (NFI) on agricultural income and investment using the Pakistan Social and Living Measurement survey data for the year 2005-06. Results show that NFI negatively affects agricultural income and investment whenever it is statistically significant; and these effects are not same across the four provinces of Pakistan. The one to one comparison between the four provinces of the country shows that the effects of NFI on agricultural income and investment differ across provinces. The policy implication is that as compared to other sectors of the economy, agriculture generates low returns and consequently NFI is invested in other more productive sectors of the economy.

DOI: 10.4018/978-1-5225-9621-9.ch058

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 Does Nonfarm Income Affect Agricultural Income and Investment in Pakistan?

INTRODUCTION Not all people receive their earnings from a single source, hold their wealth as one asset and employ their labor in one activity. Multiple motives encourage families and individuals to diversify their assets and income generating activities (Barett and Reardon, 2001). Participating in the nonfarm income (NFI) generating activities are one of the ways for rural households to diversify their earning sources and increase their gross income. In return, these earnings affect farm productivity by enhancing investment in farming. Studies show that NFI has positive effects on farm investment (Heartz, 2009) and increase expenditure on inputs (Kilic et al.,2009; Oseni & Winters, 2009; Pfeiffer et al., 2009). Consequently, farm productivity increases (Huang et al., 2009) and poverty reduces (Kijima et al., 2006; Ruben & Van Den Berg, 2001). NFI can also finance longer term on-farm capital investment such as construction of irrigation channels, purchase of machinery which can positively affect farm productivity (Barett and Reardon, 2001). Little et al. (2006) found that farm households diversify their earning sources to improve insurance against the risks of agro-climatic natural shocks, help overcome credit constraints and stabilize aggregate income flows. However, contrary to studies cited above, Pfeiffer et al. (2009) show that NFI negatively affects crop production, but positively effect the purchase of inputs. Hence, NFI has divergent effects on production and inputs use.It is the focus of this research in Pakistan, where agriculture is the second largest sector of country’s economy contributing 21 percent to the GDP and provides livelihoods to 40 percent of the population. It is generally believed that only poor households may diversify their earning sources to increase their aggregate income. However, this may not be true. Rich rural households diversify their earning sources to further maximize their profit while poor diversify to minimize risk, stabilize income and secure food access (Kilic et al., 2009). Haggblade et al. (2010) and Davis et al. (2007) identified the growth linkages between the agriculture sector and rural nonfarm employment. These linkages are: 1) the increase in income, increasing effective consumption of nonfarm products, affecting nonfarm employment; 2) the effect of demand-induced changes on downstream production linkages from processing and distribution; and 3) the changes in input-demand and its effect on production. This study focuses on the third linkage that is the nonfarm-income-induced demand for agricultural inputs and its effect on agricultural productivity. The selection is motivated by our lack of knowledge of the effect of NFI on agriculture sector in Pakistan. In an emerging economy like that of Pakistan, it is important to understand that why some farmer perform better than others? Does NFI create positive spillover effects on agriculture and livestock investment and consequently income? The four provinces of the country are agriculturally very different. Punjab and Sindh produce cash crops like cotton, rice and sugarcane while Baluchistan and Khyber Pakhtunkhwa have small natural resource base supporting livestock keeping. These differences raise the question that whether NFI have divergent effects on agriculture and livestock income and ivestment across these regions. This study estimates the effect of NFI on expenditure made on farm inputs and consequently farm income in Pakistan. Alternatively, the study investigates whether farmers who diversify their income have higher farm incomes as compared to other producers. The study makes a three important contributions to the existing literature. First, it develops empirical models illustrating the effect of NFI on agricultural income and expenditures on crops and livestock raising in the country. Second, these models are used to test specific hypotheses about the effect of NFI on agricultural income and expenditures on crops and livestock raising across the four provinces of Pakistan. It is also important to mention that understanding behavior of agricultural households with respect to income and investment is important to analyze the effects of government interventions (e.g., 1288

 Does Nonfarm Income Affect Agricultural Income and Investment in Pakistan?

pricing policies, investment projects) and external changes in market conditions on the rural economy and livelihoods. Such knowledge becomes more important for a country like Pakistan where agriculture is the second largest sector of the economy. Third, the study provides empirical evidence on the effect of NFI on agricultural income and expenditures on crops and livestock raising which can help in developing the relevant policies for creating and promoting opportunities of earning NFI. The next section presents the empirical model used to estimate the effect of NFI on agricultural income and investment, followed by discussion about data used in the analysis in section three. The estimated results are presented and discussed in section four, followed by conclusions given in section five.

The Agricultural Sector in Pakistan Pakistan has two seasons, namely the ‘kharif’ and ‘rabi’. Kharif begins in April-June and ends during October-December when rabi begins which ends in April-May. Kharif crops include rice, sugarcane, cotton, maize, mong and mash while rabi crops include wheat, gram, lentil, tobacco, rapeseed, barley and mustard. The agriculture sector is divided into crops, livestock, forestry and fishing sub-sectors. Crops sector is further divided into important crops, other crops and cotton ginning. Important crop sector includes cotton, sugarcane, wheat, rice and maize while the other crop sector consists of lentils, peas, potatoes, onions and chilies. The Agriculture sector accounts for 20.9 percent of the country’s Gross Domestic Product (GDP) in 2015. The crop sector accounts for 43.7 percent of the 20.9 percent agricultural sector contributions to a country’s GDP in 2015. In the crop sector, important crop subsector contributes 64.6 percent to the value added in the crops sector, followed by other crops (28.1%) and cotton ginning (7.3%). The livestock sector contributes 11.8 percent to the country’s GDP and 56.3 percent to the agricultural GDP (GoP, 2011). The collective contribution of forestry and fishing to a country’s GDP is less than one percent.

The Empirical Model Consider an agrarian household endowed with land, capital, and inputs. The household faces decision variables of consumption, investment, and purchase of inputs for production. The household is assumed to maximize profit as producer and utility as a consumer. In case of capital constraint, the household can get any amount of credit from a perfect financial market. However, given the imperfect financial market in a developing country like Pakistan, household faces credit constraint. In such a case, household production and consumption decisions are inseparable (Taylor and Martin, 2001; de Janvry and Sadoulet, 2003). Hence, the household sacrifices its leisure time and participate in the NFI generating activities to earn more income and overcome the credit constraint. The NFI is then available for investment in the crops and livestock sectors. Consequently, agricultural (collectively crops and livestock) investment and income are expected to increase. Our specification of the econometric model is based on Kilic et al. (2009), and Osenia and Winters (2009). The empirical model postulates that the variable of interest (Yi)in thousand rupees1 is the function of socioeconomic variables, NFI of household i ( NFIii ) in thousand rupees and regional dummies ( RD i). Regional dummies ( RDi ) represent the four provinces of Pakistan such that RDi1 . represents Punjab, RDi2 represents Sind, RDi 3 represents Khyber Pakhtunkhwa and RDi 4 represents Baluchistan. The variable of interest includes agricultural income and expenditure made on crops production and livestock keeping. In the empirical model, farm charac-

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 Does Nonfarm Income Affect Agricultural Income and Investment in Pakistan?

teristics such as land, poverty status (Evans and Nagau, 1991), education (Ellis, 2000), family size and marital status of the respondents are included. Marital status and family size are included in the model because these factors directly affect the supply of labor to NFI generating activities. Larger families can release more labor from farm production towards NFI generating activities. α0 + α1lNFI i + α2RDi 1 + α3RDi 2 + α4RDi 3 + α5RDi 3 + Yi = α6Poori + α7lAgei + α8lFSizei + α9lFAreai + α10Urbani +  α11lExpci + α12lExpli + α13Marriedi + α14Literatei + εi

(1)

where i indexes households, Agei represents age of the household head in years, FSizei is family size measured as number of family members, FAreai is farm area in hectares, Urbani is dummy, one representing urban areas zero otherwise, Expci represents expenditure on crops in thousand rupees, Expli is expenditure on livestock in thousand rupees, Marriedi is dummy, one for married household head zero otherwise, Literatei is a dummy, one for literate households zero otherwise, εi represents the random error assumed to be distributed normally with mean zero and variance σ 2 , l stands for logarithm and αi are the parameters to be estimated. The parameter α1 indicates the effect of NFI (in thousand rupees) on the variable of interest in Pakistan. It is interpreted as the elasticity of NFI with respected to either agricultural income or farm investment. Following Haq and Meilke (2010), and in order to compare the effects of NFI i on Yi across the provinces of Pakistan, regional (provincial) slope-shifters of NFI i . were derived using the following relationship. These slopes allow testing regional specific hypotheses about the effect of NFI i on variable of interest. NFI iP = Yi * RDi 1 NFI iS = Yi * RDi 2

(2)

NFI iK = Yi * RDi 3 NFI iB = Yi * RDi 4 where NFI iP represents nonfarm income of household i in Punjab, NFI iS represents nonfarm income of household i in Sind, NFI iK represents nonfarm income of household i in KP and NFI iB represents nonfarm income of household i in Baluchistan. Augmenting equation (1) with the regional NFI i shifters yields equation (3). δ0 + δ1lNFI ip + δ2lNFI iS + δ3lNFI iK + δ4lNFI iB + Yi = δ5Poori + δ6lAgei + δ7lFSizei + δ8lFAreai + δ9Urbani + δ10lExpci + δ11lExpli + δ122Marriedi + δ13Literatei + εi

(3)

Consider Yi Yi to be agricultural income than the following hypotheses are tested using equation (3).

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 Does Nonfarm Income Affect Agricultural Income and Investment in Pakistan?

H1: Nonfarm income does not determine agricultural income in the provinces of Pakistan. H2: The effect of NFI on agricultural income is similar across the four provinces of the country. Similarly other hypotheses are tested using the same equation, results of which are compiled in tables 5 and 6.

DATA This study uses the cross-sectional data collected under the Pakistan Social and Living Measurement Survey (PSLM) for the year 2005-06. The survey was carried in all the four provinces of the country. The survey is conducted by Federal Bauru of Statistics (FBS) bi-annually. FBS has developed its own sampling frame for urban and rural areas. Each frame is split into enumeration blocks. Each enumeration block consists of 200 to 250 households. Each block is divided into lower, middle and high income groups. FBS obtains list of villages from the Population Census Organization of the country. Urban domain consists of big cities like Islamabad, Lahore, Gujranwala, Faisalabad, Rawalpindi, Multan etc. Stratum from urban areas also classified according to income levels. After excluding population of the large sized cities, the remaining urban population in each defunct Division in all the provinces has been grouped together to form a stratum. Each district in the provinces are grouped to constitute a stratum, whereas defunct administrative division has been treated as stratum in Baluchistan province. FBS determined a sample size of 15512 households in the country. This sample size is obtained from 1113 sample enumeration blocks. Our sample includes only those households who cultivate land. In this way the sample reduces to 3704 households. Detail of the sample frame across the four provinces is given in Table 1.

RESULTS AND DISCUSSION This first part presents the effect of NFI on agricultural income and investment (Table 2), followed by similar effects estimated for crops (Table 3) and livestock (Table 4) sectors. Each table consists of four models, two each for expenditure and income both distinguished by the inclusion/exclusion of regional dummies. Table 1. Distribution of sample across provinces Province

Count

Percent

Punjab

1631.0

44.0

Sindh

844.0

22.8

NWFP

796.0

21.5

Balochistan

433.0

11.7

Pakistan

3704.0

100.0

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 Does Nonfarm Income Affect Agricultural Income and Investment in Pakistan?

Table 2. OLS estimates of the effect of nonfarm income on agricultural income and farm investment Variables

Poverty (Poor is 1, otherwise 0)

Age (Years) Family Size (No. of persons) Farm Area (Hectares)

Urban (Urban is 1, otherwise 0)

Expenditure on Crops (Rs/Year)

Expenditure on Livestock (Rs/Year)

Nonfarm Income (Rs (000)/Year)

Punjab (Punjab is 1, otherwise 0)

Sind (Sind is 1, otherwise 0)

KP (KP is 1, otherwise 0)

Married (Married is 1, otherwise 0)

Literate (Literate is 1, otherwise 0)

Nonfarm Income-Punjab (Rs (000)/Year)

Nonfarm Income-Sind (Rs (000)/Year)

Nonfarm Income-KP (Rs (000)/Year)

Nonfarm Income-Baluchistan (Rs (000)/Year) R-squared Number of observations F-Statistics

Model-1

Model-2

Agricultural Income

Model-3

Model-4

Agricultural Investmen

0.048

0.167***

0.004

0.410***

(0.066)

(0.030)

(0.098)

(0.044)

0.107

0.066

-0.005

0.037

(0.104)

(0.048)

(0.145)

(0.073)

0.089

0.159***

0.402***

0.337***

(0.057)

(0.026)

(0.087)

(0.050)

0.055*

0.017

0.301***

0.447***

(0.028)

(0.015)

(0.040)

(0.026)

-0.253*

0.025

-0.319*

-0.097

(0.141)

(0.055)

(0.172)

(0.102)

0.414***

0.485***

----

----

(0.029)

(0.014)

----

----

0.278***

0.214***

----

----

(0.042)

(0.016)

----

----

-0.032

----

(0.032)

----

0.068

----

0.178*** (0.048) 0.730*** (0.147)

----------

(0.111)

----

0.345**

----

(0.119)

----

(0.169)

----

0.202*

----

-0.478**

----

(0.121)

----

(0.163)

----

-0.09

-0.078

0.293

0.015

(0.125)

(0.069)

(0.196)

(0.111)

0.898***

-------

0.159

0.322

0.635

0.221

(0.337)

(0.233)

(0.626)

(0.314)

----

-0.042***

----

-0.005

----

(0.009)

----

(0.017)

----

0.023

----

0.009

----

(0.017)

----

(0.031)

----

-0.019*

----

-0.249***

----

(0.012)

----

(0.016)

----

-0.058

----

-0.275***

----

(0.039)

----

(0.046)

0.668

0.728

0.399

0.309

3704

3704

3704

3704

75.01***

373.2***

41.56***

88.6***

Note: *, ** and *** denote variables significant at 0.1, 0.05 and 0.01 level of probability respectively. All the standard errors are corrected for heteroscadasticity.

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 Does Nonfarm Income Affect Agricultural Income and Investment in Pakistan?

Table 3. OLS estimates of the effect of nonfarm income on crops’ income and expenditure Dependent Variable

Variable

Log of Crops Expenditure 0.115

0.530***

0.057

0.085***

(0.112)

(0.050)

(0.056)

(0.025)

-0.153

-0.045

-0.033

0.01

(0.154)

(0.080)

(0.077)

(0.039)

0.336***

0.294***

0.129**

0.177***

(0.096)

(0.050)

(0.052)

(0.023)

0.337***

0.577***

0.060**

0.065***

(0.050)

(0.027)

(0.022)

(0.011)

Poverty (Poor is 1, otherwise 0) Age (Years) Family Size (No. of persons) Farm Area (Hectares)

-0.252

-0.044

-0.158

0.039

(0.160)

(0.103)

(0.106)

(0.042)

----

0.715***

0.711***

----

(0.027)

(0.010)

0.182**

----

-0.052*

----

(0.057)

----

(0.029)

----

0.442**

----

-0.160*

----

(0.169)

----

(0.087)

----

0.789***

----

0.071

----

(0.188)

----

(0.100)

----

-1.023***

----

-0.008

----

(0.185)

----

(0.098)

----

Urban (Urban is 1, otherwise 0) Expenditure on Crops (Rs/Year) Nonfarm Income (Rs (000)/Year) Punjab (Punjab is 1, otherwise 0) Sind (Sind is 1, otherwise 0) KP (KP is 1, otherwise 0)

Log of Crops Income

Nonfarm Income-Punjab (Rs (000)/Year) Nonfarm Income-Sind(Rs (000)/Year) Nonfarm Income-KP (Rs (000)/Year) Nonfarm Income-Balochistan (Rs (000)/Year) Married (Married is 1, otherwise 0)

----

-0.019

----

-0.052***

----

(0.020)

----

(0.007)

----

0.024

----

0.012

----

(0.034)

----

(0.018)

----

-0.310***

----

-0.028**

----

(0.017)

----

(0.010)

----

-0.223***

----

0.012

----

(0.057)

----

(0.028)

0.487**

0.189

0.097

-0.037

(0.206)

(0.120)

(0.102)

(0.054)

0.815

0.074

0.498**

0.347**

(0.863)

(0.457)

(0.177)

(0.138)

Literate (Literate is 1, otherwise 0) Summary Statistics R-squared

0.449

0.385

0.774

0.818

Number of observations

3704

3704

3704

3704

F-Statistics

51.94***

137.50***

142.77***

778.36***

Note: *, ** and *** denote variables significant at 0.1, 0.05 and 0.01 level of probability respectively. All the standard errors are corrected for heteroscadasticity.

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 Does Nonfarm Income Affect Agricultural Income and Investment in Pakistan?

Table 4. OLS estimates of the effect of nonfarm income on livestock income and expenditure Variable

Dependent Variable Log of Livestock Expenditure -0.04

0.367***

-0.051

0.145**

(0.110)

(0.046)

(0.108)

(0.049)

0.151

0.123*

0.112

0.177**

(0.143)

(0.073)

(0.143)

(0.078)

0.210**

0.233***

-0.014

0.090**

(0.088)

(0.047)

(0.086)

(0.042)

0.200***

0.287***

0.019

-0.050**

(0.034)

(0.019)

(0.033)

(0.019)

0.326**

0.087

-0.417*

-0.079

(0.125)

(0.088)

(0.226)

(0.090)

0.601***

0.638***

(0.081)

(0.030)

Poverty (Poor is 1, otherwise 0) Age (Years) Family Size (No. of persons) Farm Area (Hectares) Urban (Urban is 1, otherwise 0) Expenditure on Livestock (Rs/Year) Nonfarm Income (Rs (000)/Year) Punjab (Punjab is 1, otherwise 0)

Log of Livestock Income

0.232***

0.031

(0.044)

(0.046)

0.723***

0.288*

(0.173)

(0.170)

0.574**

0.554**

(0.243)

(0.177)

-0.108

0.446**

(0.186)

(0.166)

Sind (Sind is 1, otherwise 0) KP (KP is 1, otherwise 0) Nonfarm Income-Punjab (Rs (000)/Year) Nonfarm Income-Sind(Rs (000)/Year)

0.079

-0.084

-0.208

-0.228**

(0.176)

(0.102)

(0.169)

(0.091)

-0.126

0.347

0.177

0.409

(0.449)

(0.300)

(0.432)

(0.374)

Nonfarm Income-KP (Rs (000)/Year) Nonfarm Income-Balochistan (Rs (000)/Year) Married (Married is 1, otherwise 0) Literate (Literate is 1, otherwise 0)

0

0

(0.016)

(0.015)

-0.058

0.079***

(0.061)

(0.024)

-0.170***

0.019

(0.016)

(0.015)

-0.255**

-0.06

(0.079)

(0.059)

Summary Statistics R-squared

0.262

0.209

0.339

0.341

Number of observations

3704

3704

3704

3704

F-Statistics

21.99***

52.13***

19.95***

64.97***

Note: *, ** and *** denote variables significant at 0.1, 0.05 and 0.01 level of probability respectively. All the standard errors are corrected for heteroscadasticity.

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 Does Nonfarm Income Affect Agricultural Income and Investment in Pakistan?

In case of agricultural income and investment, results are compiled in table 2. Model-1 shows the effect of NFI on agricultural income while Model-2 shows the same effect for the four provinces of Pakistan. Model-3 and 4 shows the effect of NFI on farm investment in the country and across the four provinces respectively. Results show that all the estimated models fit the data as well as the coefficient of determination ranges from 30.9% for model-4 to 72.8 for model-1. F-statistics show that all the estimated models are statistically significant, indicating that the hypotheses that the coefficients of regression models except the intercept are zero, is rejected at the 0.01 level of significance. Table 2 further shows that as compared to poor households, non-poor households invest more in agricultural production and generate more agricultural income. Non-poor invest 50.72 percent of agricultural production and generate 18.2 percent more agricultural incomes, keeping other variables constant. However, with the inclusion of provincial slope shifters in the model (Model-1 and 3), this effect fades away. Age of the household head does not statistically significantly affect agricultural income and farm investment. Family size is statistically significant determinant when NFI provincial slope shifters are included in the model (Model-2). The effect of farm area on agricultural income and farm investment is statistically significant, but inelastic implying that increase in the farm area increases investment cost more, but yields proportionately less income. Its coefficient in model-4 shows that a one percent increase in the farm area increases farm investment by 0.45 percent, keeping other variables constant. However, its effect on farm investment is high as compared to its effect on agricultural income. Households located in the urban areas invest 37.6 percent less (model-3) and generate 28.7 percent more income. The effect of marriage and literacy on agricultural income as well as investment is statistically insignificant in all the models. Further, the effect of NFI on agricultural income is statistically not significant (Model-1), however, it is an important determinant of the farm investment (Model-3). The regional dummies show that as compared to Baluchistan, agricultural income is high by 41.2 percent in Sind and 22.4 percent in Khyber Pakhtunkhwa. Similarly, as compared to Baluchistan, production costs are higher by 107.5 percent in Punjab, 145.5 percent in Sind and lower by 38 percent in Khyber Pakhtunkhwa. Hence, production costs and agricultural income vary across the provinces. The table also shows that the effect of Niño agricultural income in Punjab and Khyber Pakhtunkhwa (KP) is statistically significant while its effect on agricultural investment is also statistically significant and negative in KP and Baluchistan. The estimated results show that a ten percent increase in NFI decreases agricultural income by 0.4 percent in Punjab and by 0.2 percent in Khyber Pakhtunkhwa. Similarly, a ten farm increase in nonfarm in Khyber Pakhtunkhwa and Baluchistan decreases farm investment by 2.5 and 2.8 percent, respectively. The collective implications of these results are that returns in agriculture sector as compared to other sectors of the economy are low. Further, NFI may not be readily available to the farm sector for investment due to many reasons including the consumption, social and financial requirements of rural households. Also, the effect of the NFI on farm income and investment may be different not only across the crops and livestock sectors but also across time and regions. Hence, farm households do not invest the additional income in agriculture production and consequently its effect on agricultural income is negative. Agricultural income and investment are then split into crops and livestock income and investments and the effect of the NFI is separately estimated on these sectors. Estimated results for the crops and livestock sectors are given in tables 3 and 4 respectively. However, separately estimating the models for crops and livestock sectors did not change the effect of most of the variables on both income and investment. For both the sectors (Tables 3 and 4), the effect of NFI on the variable of choice is negative when statistically significant with the exception of livestock sector in Balochistan (Table 4). In Balochistan, 1295

 Does Nonfarm Income Affect Agricultural Income and Investment in Pakistan?

a ten percent increase in the NFI marginally (0.8%) increases investment in livestock sector. Hence, on an overall, the direction of the results presented in table 2 hold for both crops and livestock sectors. The estimated parameters of NFI are then used to estimate a number of hypotheses about agricultural income and investment and results are compiled in Tables 5 and 6, respectively. Results show that NFI is an important determinant of both agricultural investments (Table 5) and income (Table 6). The impact of NFI on agricultural investment (Table 5) and income (table 6) differs across the four provinces of the country. Its effect on agricultural income between Punjab and Sindh, Punjab and KP, Sind and KP and Sind and Baluchistan are statistically different. Similarly, the effect of NFI on agricultural investment is also statistically significant (Table 6). Its effect on agricultural investment between Punjab and KP, Punjab and Baluchistan and Sind and KP and Sind and Baluchistan are statistically different. Table 5. Test of the hypotheses about the role of nonfarm income in farm investment Hypothesis

F-Statistics

Nonfarm income does not affect agricultural production cost.

71.19***

The effect of nonfarm income on agricultural production cost is same across the provinces of Pakistan

56.93***

The effect of nonfarm income on agricultural production cost in Punjab is similar to its effect in Sind

0.17

The effect of nonfarm income on agricultural production cost in Punjab is similar to its effect in Khyber Pakhtunkhwa.

135.14***

The effect of nonfarm income on agricultural production cost in Punjab is similar to its effect in Baluchistan

31.39***

The effect of nonfarm income on agricultural production cost in Sind is similar to its effect in Khyber Pakhtunkhwa.

58.33***

The effect of nonfarm income on agricultural production cost in Sind is similar to its effect in Baluchistan.

26.88***

The effect of nonfarm income on agricultural production cost in Khyber Pakhtunkhwa is similar to its effect in Baluchistan.

0.28

Note: *, ** and *** denote variables significant at 0.1, 0.05 and 0.01 levels, respectively.

Table 6. Test of the hypotheses about the role of nonfarm income in agricultural income Hypothesis

F-Statistics

Nonfarm income does not affect agricultural income.

7.20***

The effect of nonfarm income on agricultural income is same across the provinces of Pakistan

4.44**

The effect of nonfarm income on agricultural income in Punjab is similar to its effect in Sind

11.66**

The effect of nonfarm income on agricultural income in Punjab is similar to its effect in Khyber Pakhtunkhwa.

2.83*

The effect of nonfarm income on agricultural income in Punjab is similar to its effect in Baluchistan

0.17

The effect of nonfarm income on agricultural income in Sind is similar to its effect in Khyber Pakhtunkhwa.

4.22*

The effect of nonfarm income on agricultural income in Sind is similar to its effect in Baluchistan.

3.74*

The effect of nonfarm income on agricultural income in Khyber Pakhtunkhwa is similar to its effect in Baluchistan.

0.93

Note: *, ** and *** denote variables significant at 0.1, 0.05 and 0.01 levels, respectively.

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 Does Nonfarm Income Affect Agricultural Income and Investment in Pakistan?

CONCLUSION Nonfarm income can be used to timely purchase crops and livestock inputs and undertake scheduled farm production and harvesting activities. However, there is no evidence suggesting that NFI has positive effects on agricultural income and investment in Pakistan. This study underscores the existing literature by providing the evidence on the effect of NFI on agricultural productivity in Pakistan using the Pakistan Social and Living Measurement survey. The econometric analysis investigating the effect of NFI on agricultural income and expenditure shows that nonfarm is an important determinant of agricultural income. The effect of NFI on agricultural income is not same across the four provinces of Pakistan. Its effect on agricultural income between Punjab and Sindh, Punjab and KP, Sind and KP and Sind and Baluchistan are statistically different. Similarly, the effect of NFI on agricultural investment is also statistically significant. Its effect on agricultural investment between Punjab and KP, Punjab and Baluchistan and Sind and KP and Sind and Baluchistan are statistically different. The authors highlighted that if there are negative linkages between NFI and agricultural production, then understanding the nature of these linkages could prove useful in designing programs to facilitate agricultural households’ adjustment to rural economic change.

LIMITATIONS AND FUTURE DIRECTION The study uses PSLM data in the analysis. PSLM data provides enterprise specific output data but does not provide similar data for inputs. Hence, using PSLM data it is not possible to determine the effect of NFI on major crops raised in different agro-ecological zones of the country. Hence, an investigation of the effect of NFI on major crops in different agro-geographical regions of the country is required. Further, since agriculture is one of the biggest sectors of the economy and is a source of livelihood for about one-half of the population, it is important to understand the effect of NFI on poverty in the country. This study also ignored the effect of NFI on variability and distribution of rural household’s income.

REFERENCES Barett, C. B., & Reardon, T. (2001). Asset, activity, and income diversification among African agriculturists: Some practical issues. UASID Basis CRSP. Davis, B., Winters, P., Carletto, C., Covarrubias, K., Quinones, E., & Zezza, A. (2007). Rural income generating activities: Across country comparison. World Development, 119–123. deJanvry, A., & Sadoulet, E. (2003). Progress in the modeling of rural households’ behavior under market failures. Chapters in Honor of Erik Thorbecke. New York: Kluwer Publishing. Ellis, F. (2000). Rural Livelihoods and Diversity in Developing Countries. Oxford, UK: Oxford University Press. Evans, H. E., & Ngau, P. (1991). Rural-urban relations, household income diversification and agricultural productivity. Development and Change, 22(3), 519–545. doi:10.1111/j.1467-7660.1991.tb00424.x

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GoP. (2011). Economic survey of Pakistan. Economic Advisory Wing. Finance division. Islamabad: MINFAL Pakistan. Haggblade, S., Hazell, P., & Reardon, T. (2010). The Rural Non-farm Economy: Prospects for Growth and Poverty Reduction. World Development, 38(10), 1429–1441. doi:10.1016/j.worlddev.2009.06.008 Haq, Z., & Meilke, K. (2010). Do the BRICs and Emerging Markets Differ in their Agrifood Trade? Journal of Agricultural Economics, 61(1), 1–14. doi:10.1111/j.1477-9552.2009.00229.x Hertz, T. (2009). The effect of nonfarm income on investment in Bulgarian. Agricultural Economics, 2(40), 161–176. doi:10.1111/j.1574-0862.2009.00367.x Huanga, J., Wu, Y., & Rozelle, S. (2009). Moving off the farm intensifying agricultural production in Shandong: A case study of rural labor market linkages in China. Agricultural Economics, 2(40), 203–218. doi:10.1111/j.1574-0862.2009.00370.x Kijima, Y., Matsumoto, T., & Yamano, T. (2006). Nonfarm employment, agricultural shocks, poverty dynamics: Evidence from rural Uganda. Agricultural Economics, 459-467. Kilic, T., Carletto, C., Miluka, J., & Savastano, S. (2009). Rural nonfarm income its effect on agriculture: Evidence from Albania. Agricultural Economics, 2(40), 139–160. doi:10.1111/j.1574-0862.2009.00366.x Little, P., Stone, P., Mogues, T., Castro, P., & Negatu, W. (2006). Moving in place drought and poverty dynamics in South Wollo, Ethiopia. Development Studies, (42), 200-225. Oseni, G., & Winters, P. (2009). Rural nonfarm activities and agricultural crop. Agricultural Economics, 2(40), 189–201. doi:10.1111/j.1574-0862.2009.00369.x Pfeiffer, L., Feldman, L. A., & Taylor, J. (2009). Is off-farm income reforming the farm? Evidence from Maxico., 2(40), 125–138. Ruben, R., & Van Den Berg, P. (2001). Nonfarm employment and poverty alleviation of rural farm households in Honduras. World Development, 3(29), 549–560. doi:10.1016/S0305-750X(00)00107-8 Taylor, J. E., & Martin, P. (2001). Human capital: Migration and rural population change. In B. Gardener & G. Rausser (Eds.), Handbook of Agricultural Economics (Vol. 1, pp. 457–511). Amsterdam: Elsevier.

ENDNOTES

1 2

One average, one US$ = 85.5 Rupees during the study period. Proportionate effect of a dummy variable is calculated as (Exponent (α)-1)*100. Hence, (Exponent (0.41)-1)*100=50.68 ≈ 50.7.

This research was previously published in Driving Agribusiness With Technology Innovations edited by Theodore Tarnanidis, Maro Vlachopoulou, and Jason Papathanasiou, pages 210-221, copyright year 2017 by Business Science Reference (an imprint of IGI Global). 1298

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Chapter 59

Social and Environmental Impacts on Agricultural Development Frances Bekele The University of the West Indies – St. Augustine, Trinidad and Tobago Isaac Bekele The University of the West Indies – St. Augustine, Trinidad and Tobago

ABSTRACT Addressing environmental and social impacts on agricultural development and food security is a global priority since increased food production of 60-70% is estimated to be required by 2050 to feed the growing world population. In developing nations, the situation is more acute since fewer social, technological and financial resources are available to combat climate change, which is expected to have negative effects on agricultural production, and there are other constraints to achieving food security. This chapter explores the social and environmental issues affecting agricultural production facing farmers and other agricultural practitioners, policy makers, institutions and stakeholders in the developing world. It will also address how progress in research in emerging economies can be put to maximum benefit in the face of these existing social and environmental challenges. A cohesive strategy to address these challenges is presented.

INTRODUCTION The world’s population is expected to increase to 9 billion by 2050 (Hubert, Rosegrant, Van Boekel & Ortiz, 2010), and it is estimated that a 60-70% global increase in food production is needed to feed this growing population (Consultative Group for International Agricultural Research (CGIAR), 2015; FAO, 2007, 2014; Mba, Guimaraes, & Ghosh, 2012). Currently, approximately 2 billion persons are food insecure since they do not meet one or several of the Food and Agriculture Organisation’s (FAO’s) dimensions of food security (access to adequate food, availability and utilization of nutritious food and stable supply (Hubert et al., 2010; Wheeler & von Braun, 2013)). Furthermore, 805 million persons did DOI: 10.4018/978-1-5225-9621-9.ch059

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 Social and Environmental Impacts on Agricultural Development

not have access to sufficient food during 2012-2014 (Maggio, Van Criekinge, & Malingreau, 2015). Food availability must increase to meet demand by 100% in developing countries (CGIAR, 2015). This can be achieved through increasing production as well as reducing losses (food waste). Improving agriculture1 to meet the Millennium Development Goals2 of the United Nations, which include halving extreme poverty and hunger by 2015 and eliminating it by 2030 (under the sustainable development agenda), requires optimisation of agricultural practices and systems, and dealing effectively with technological, social, environmental as well as economic issues that influence the sustainability of agricultural production. The United Nations Framework Convention on Climate change (UNFCCC) (2007) described the developing nations as most vulnerable to climate change impacts that are expected to have negative effects on agricultural production and food security, as described by the International Food Policy Research Institute (IFPRI, 2009). This is attributed to the limited social, technological and financial resources available to address climate change in these countries. Currently, sustainable food security and agricultural development are constrained globally by degradation and loss of agricultural land, the loss of biodiversity, depletion of water and other resources and pollution (Chaudhury, Vervoort, Kristjanson, Ericksen, & Ainslie, 2103; Sonnino, Moragues Faus, & Maggio, 2014). These factors are exacerbated by the negative impacts of climate change and may also contribute to climate change. This chapter explores the social and environmental issues facing agricultural practitioners (producers and entrepreneurs alike) in the developing world, who are striving to contribute to food security in their communities and, by extension, the world. It will also address how the progress in research in emerging economies can be put to maximum benefit in the face of existing social and environmental challenges in developing nations, as described by Ejeta (2009). Heat stress could affect developing countries by 2030 (Inter-Governmental Panel on Climate Change (IPCC), 2007, 2013). Expenditure of USD 200 and 250 billion a year may be required to address negative impacts of climate change in developing countries (Peterson, 2011). These impacts can significantly reduce sustainability of livelihoods and the well-being of citizens in developing nations (Noble et al., 2014). A multi-sector approach is advocated to deal with the challenges and potential impact of social and environmental factors such as climate change on food security. The proposed model encompasses the role of farmers, entrepreneurs, social policy makers, governments, the private sector, scientists and organisations in a cohesive strategy. The role of education and extension in preparing for the impacts of climate change, as described by Bekele and Ganpat (2014) in the context of small island developing states (SIDS), is also discussed. In order to illustrate the current situation, constraints and putative solutions to social and environmental impacts on agricultural development and food security in developing countries, several staple crops in Africa, Latin America and the Caribbean (LAC) and the commodity, cocoa, are highlighted in this chapter.

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CURRENT STATUS OF AGRICULTURAL DEVELOPMENT AND FOOD SECURITY IN DEVELOPING NATIONS 1. Africa In Africa, the agriculture sector employs 60% of the total population, contributes 20% to the gross domestic product (GDP) and earns more than 10% of export revenues (Sasson, 2102). It is expected that access to adequate and secure food would be a priority in Africa. However, in 2010, the number of food insecure persons in Sub-Saharan Africa was estimated at 239 million, and in North Africa it was 37 million (Sasson, 2012). The main cause of food insecurity in Africa was identified as insufficient food production (Beddington et al., 2012; Sasson, 2012). Soaring world food prices and rural migration have exacerbated the situation, and the impacts of climate change could be detrimental. High food prices have resulted in a significant percentage of the African population spending more than half their income on food. There have been recurrent droughts in the Horn of Africa since 2009 as well as a history of famines due to drought. Mba et al. (2012) described Africa as one of the most vulnerable continents to climate change and variability. The expected decrease in the length of the growing seasons of African crops (Thornton & Herrero, 2015) will result in the further loss of production in marginal agriculture. Crop yields in Africa can decrease by as much as 50% by 2020 due to climate change, and this could result in lower calorific intake by humans (by as much as 500 calories per capita in 2050, a 21% decline) (Toulmin, 2009). Jarvis, Ramirez-Villegas, Campo, and Navarro-Racines (2012) found that while cassava is likely be affected positively by climate change in many areas of Africa (−3.7% to +17.5% changes in climate suitability across the continent), other major food staples in Africa are expected to face negative impacts, with the most significant predicted for beans (−16% ± 8.8), potato (−14.7 ± 8.2), banana (−2.5% ± 4.9), and sorghum (−2.66% ± 6.45). For resource-poor farmers in developing countries such as Africa, the use of fertilizers that could improve plant vigour, root growth and access to soil moisture, and irrigation to combat drought may not be feasible options to address climate change (Beebe et al., 2011). Mixed farming (crop-livestock) systems form the mainstay of African agriculture and have certain benefits (Thornton & Herrero, 2015). The adaptation potential of these systems must be examined in the face of climate change since they are complex. Furthermore, there is very little data currently available on putative climate change impacts on these systems.

2. Latin America and the Caribbean In Latin America and the Caribbean (LAC), approximately 15.9% of the labour force is directly involved in agriculture (Andersen et al., 2014). LAC’s agricultural market share increased from 9.5% in 1980 to 18.1% in 2010 (Flachsbarth et al., 2015). The largest agricultural sectors in LAC are based on livestock, feedstuff and biofuel crops (Flachsbarth et al., 2015). The contribution of agriculture to overall GDP ranges from 3.1% in Mexico to more than 5.5% in Brazil and to 7.8% in Peru (Andersen et al., 2014). From 1961 to 2007, LAC had the highest growth rate in agricultural productivity among developing regions (1.9%) (Ludena, 2010). The LAC countries with the highest land availability, such as Brazil, Argentina, Chile, Colombia, Mexico and Venezuela, have the most significant agricultural production (Ludena, 2010). Caribbean countries experienced limited growth by comparison (0.5%) (Ludena, 2010). Most of that growth occurred in the livestock sector,

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especially for non-ruminants (pigs and poultry). The most valuable agricultural export products from LAC currently are soybeans and cane sugar (Flachsbarth et al., 2015). Wickham (1992) underscored the need for further development in vegetable production in the Caribbean to foster self-sufficiency in this area. Priority areas identified were germplasm enrichment and enhancement, selection of superior cultivars, development of more efficient production systems (including disease and pest management) and application of post-harvest technologies to promote the shelf-life of vegetables. Several other issues related to agricultural development and food security have been identified as requiring attention in LAC. These include improved partnerships among public sector, agencies, research institutions and the private sector to deliver food production programmes and transfer post-harvest and other technologies to farmers to assure food quality and availability (Roberts, Ganpat, Narine, Heinert, & Rodriguez, 2015). Farmer training through extension services is essential. Climate change can also adversely affect crop production in LAC. Andersen et al. (2014) modelled the impact of climate change in the major agricultural producing countries in LAC, viz., Brazil, Peru and Mexico. They projected that in Brazil, the effect on soybean production could be of the magnitude of –0.5 and +0.3% per annum. In Mexico, maize is the main agricultural product and accounts for 14 to 22% of the regional agricultural GDP. A decrease of 0.3% per annum was predicted for this crop. In Peru, the production of potatoes was forecasted to change by –0.6 to +0.2%. Jarvis et al. (2008) predicted reductions in rice yields in Latin America by the 2020s, but increases in soybean production due to possible increases in carbon emissions. They also forecasted: • • • •

Reduced acreage of land available for coffee production in Brazil, Lower coffee production in Mexico, Salinization and desertification of agricultural lands in drier areas of Latin America, and Probable increased incidence of the coffee leaf miner (Perileucoptera coffeella) and the nematode Meloidogyne incognita in Brazilian coffee-growing areas.

In addition, the risk of Fusarium head blight in wheat may increase under climate change in southern Brazil and Uruguay (Fernandes et al., 2004). Overall, the combined impacts of climate change are estimated to amount to less than 1% of household incomes during the next 40 years in Brazil, Peru and Mexico (Andersen et al., 2014). The negative impacts on agricultural production in these countries were forecasted to be somewhat balanced by increased commodity prices. This was based on the premise that any large increases in the global prices of agricultural products, caused by climate change, will tend to benefit these agricultural producers of the respective commodities. However, for the land-constrained Caribbean countries, any further reduction in agricultural productivity will restrict the likelihood of achieving food security and poverty reduction. These countries are currently mainly net food importers. The Windward Islands have suffered significantly with the removal of the European Union preferential trade tariffs for banana imports. According to Ganpat and Isaac (2014) and Hutchinson et al. (2013), these SIDS are very vulnerable to the impact of climate change.

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ENVIRONMENTAL ISSUES CRITICAL TO AGRICULTURAL DEVELOPMENT AND FOOD SECURITY The following are some of the pertinent environmental issues to be considered with regard to agricultural development and food security in developing nations: • • • •

•

Environmental impacts on production, productivity and product quality; ◦◦ Impacts of climate change on agriculture and post-harvest production; Ensuring a reliable supply of produce or commodity under climate change; Use of superior (in terms of yield/productivity, vigour and pest and disease resistance) and climate-smart crop varieties; Improving energy efficiency of crop and livestock production (reduction in carbon emissions and prudent use of energy): ◦◦ Application of eco-friendly sustainable practices such as organic fertilisation and pruning of crops; ◦◦ Choosing the most efficient crop production system for specific crops and environments (such as terrains on steep slopes and multi-cropping on impoverished soils (Bekele & Ganpat, 2014)); and Monitoring land conversion/biodiversity losses.

Climate-Change Impacts on Agricultural Development and Food Security According to FAO (2007), climate change impacts can be classified into two groups, viz., biophysical impacts: • • • • • •

Physiological effects on crops, forests and livestock (quantity, quality) and availability of fodder and pastures; Changes in land, soil and water resources (quantity, quality); Increased weed and pest challenges; Shifts in spatial and temporal distribution of impacts; Sea level rise, changes to ocean salinity and Sea temperature rise causing fish to inhabit different ranges.

and socio-economic impacts: • • • • • •

Decline in yields and production; Reduced GDP from agriculture; Fluctuations in world market prices; Changes in geographical distribution of trade regimes; Increased number of people at risk of hunger and food insecurity and Migration and civil unrest (increased crime).

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Climate Change Impacts on Crop Production Global Global warming and the El Niño effect, with the attendant drought, floods, increased temperature of the atmosphere and oceans and salinity and shifts in weather patterns, have the capacity to significantly reduce yields of food crops (refer to Figure 1) including staples such as rice, wheat, corn and barley (Beddington et al., 2012; Rosegrant, 2011). The potential impacts in small island developing states (SIDS) have been discussed by Roberts and Rodriguez (2014). The situation is compounded by the need to produce bio-fuels to reduce the carbon footprint of nations and meet the increasing demand for energy/ fuel. This implies competition for food crops with biomass attributes favoured for biofuel production. Crop production will also be constrained by the spread of invasive species such as pests and fungi that may proliferate under altered climatic conditions (Leishman & Gallagher, 2015). It has been reported that even a 2-degree change in temperature over time can affect agricultural productivity adversely in the absence of adaptation (Ramirez-Villegas & Thornton, 2015; Wheeler & von Braun, 2013). Figure 1. The effects of climate change on agricultural production

Source: http://croplife.org/news/infographic-how-does-climate-change-impact-agriculture/

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In Africa In a Working Paper of the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), Ramirez-Villegas and Thornton (2015) have provided a detailed overview of the potential (based on published studies) and projected (based on crop model simulations) effects of climate change (extreme and changing weather conditions) on the production of maize, common bean, sorghum, cassava, yam, pearl millet, groundnut, banana and coffee in rainfed Africa. Projections were analysed and it was concluded that climate change affects crops and regions differently in Africa. For instance, in the Sahel, it was predicted that some crops may no longer be suitable for cultivation and a shift to drought and heat-resistant varieties of crops such as cassava (Jarvis et al., 2012), yams and sorghum may be a necessary adaptation measure to consider. By comparison, the production of maize in South Africa may be reduced by 30% (Sasson, 2012), but northern South Africa, Botswana, Namibia, Zimbabwe and Lesotho are not expected to experience any significant change in maize production (Ramirez-Villegas & Thornton, 2015). The yield of common bean is very responsive to climate and the areas suitable for its cultivation in Africa can be reduced by unfavourable climatic conditions (Ramirez-Villegas & Thornton, 2015). The same applies for maize, banana and finger millet as well as coffee in different regions of Africa. For coffee, a reduction in suitable growing area for Coffea arabica in Ethiopia is projected with increased temperatures. Cultivation of this premium variety may need to be shifted towards higher elevations and more heat-tolerant Coffea robusta may be required at altitudes of less than 1500 m above sea level. Maize productivity (yield) could be reduced by 5-10% in Africa for every degree of warming (Knox, Hess, Daccache, & Wheeler, 2012). This is alarming since maize contributes the greatest portion of calories in the African diet (a mean of 16% and range of 0 – 60% across the continent). The current production is roughly 42 million tons per year (Ramirez-Villegas & Thornton, 2015). The most at risk area in terms of maize production under climate change is the Sahel.

STRATEGY TO MAINTAIN SUSTAINABLE CROP PRODUCTION INTENSIFICATION (SCPI) IN DEVELOPING COUNTRIES Increased agricultural production requires higher yields and improved management strategies to reduce abiotic and biotic stresses. However, in order to avoid the depletion of land, energy and water resources, sustainable intensification has become crucial (Flachsbarth et al., 2015). Achieving SCPI may be realised through the following practices: • • • • •

Maintaining healthy soil to enhance soil-related ecosystem services and crop nutrition; Cultivation of a wider range of species and varieties in rotations, sequences and combinations to minimize overall risk of crop failure; Using quality seeds and planting material of well-adapted, high-yielding varieties; Adopting integrated management of nutrients, pests, diseases and weeds; and Efficient water use (FAO, 2013).

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SCPI requires effective use of technological and scientific innovations so that food supply may be increased without converting larger acreages to agricultural production or unleashing negative impacts on the environment and human health (Dempewolf et al., 2014; FAO, 2011; Sonnino et al., 2014).

ADAPTATION AND MITIGATION STRATEGIES TO OFF-SET THE IMPACT OF CLIMATE CHANGE ON AGRICULTURAL DEVELOPMENT AND FOOD SECURITY Several adaptation strategies have been proposed to combat the potential negative impacts of climate change such as rising temperatures, intense and more frequent storms, droughts etc. These include diversification of livelihoods through agroforestry, integration approaches such as crop-livestock systems and rice-fish systems (Palombi & Sessa, 2013) and cultivation of heat, drought and other abiotic stress tolerant crops. The latter, described as climate-smart varieties, can be developed through crop varietal selection and breeding and should be cultivated under improved crop and eco-system management systems through precision agriculture, tailored to optimise production of particular crops under specific growing environments (FAO, 2009a; Palombi & Sessa, 2013). Improved crop production management techniques can contribute to mitigating climate change by reducing greenhouse gas (GHG) emission. This may be achieved by limiting the use of inorganic fertilisers, avoiding soil compaction or flooding to reduce methane emissions, as in paddy rice systems, and sequestering carbon by planting perennial crops, forest trees (Dawson et al., 2011) and grass species (Palombi & Sessa, 2013). The latter practices fall under the umbrella of conservation agriculture.

Agricultural Approaches and Practices That Contribute to Climate Change Adaptation Certain approaches and practices for sustainable crop production can contribute to climate change adaptation. They provide options for location-specific scenarios and should be adapted with local farmers/ farming communities. Examples, provided by Palombi and Sessa (2013, p. 203), include SCPI listed above (FAO, 2013) and others such as: • • •

Mulch and cover cropping; Landscape-level pollination management; and Land fragmentation (riparian3 areas, forest land within the agricultural landscape) (FAO, 2008, 2009b, 2012; FAO-PAR, 2011; Lin, 2011).

Tol (2002) presented comparative values of adopting versus not adopting measures to off-set climate change impacts on agriculture for a 2.5°C increase in global mean temperature. In LAC, the projected change in GDP from agriculture without climate change adaptation was –0.8 (0.6) whereas it was 0.6 (0.7) with adaptation measures. In Africa, the projected GDP adjustment was –0.2 (0.2) without adaptation measures compared to 0.5 (0.3) with adaptation measures. This research effectively underscores the value of adaptation measures.

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Agricultural Approaches and Practices That Contribute to Climate Change Mitigation As with climate change adaptation, approaches and practices for climate change mitigation can provide options for specific locations and should also be adapted in conjunction with local farmers/farming communities. Examples, provided by Palombi & Sessa (2013, 204), include in addition to some of the adaptation strategies listed above: • • • • • • • • • •

Soil compaction management; Promotion of legumes in crop rotations; Restoration of cultivated peaty soils and degraded lands; Soil management practices that reduce fertilizer use (e.g. deep placement of urea); Growing nutrient-use efficient crop varieties; Integrated crop and livestock systems (also recommended by Boland et al., 2013; FAO, 2010a); Dedicated production of energy crops to replace fossil fuel use; Emission control and reduction (combustion engines, animal waste); Improved rice cultivation techniques; and Agroforestry (FAO, 2004, 2008, 2009b, 2012).

FAO (2007) has also recommended harnessing the knowledge and experience of farmers to select types of animal breeds or varieties that can best withstand changing climatic conditions. In addition, FAO (2007) also advocated mitigating the negative impact of ruminants on GHG emissions via animal husbandry practices such as adjusting ruminant diets and stocking ratios. Monitoring and rapid appraisal of the impacts of disasters on local fishing communities and aquatic ecosystems so that immediate and longer-term remedial action could be implemented in a timely manner were also recommended. FAO has adopted an Ecosystem Approach to management of fishery resources and the ecosystems on which they depend, in the face of climate change. Climate-adapted companion cropping is another sustainable agricultural approach that can contribute to climate change mitigation. In sub-Saharan Africa, a push-pull companion cropping practice has been adopted to address constraints of the parasitic weed, Striga hermonthica, stem borer (lepidopterous insect) attack and poor soil fertility (Midega et al., 2015). The climate-adapted, drought-tolerant Brachiaria cv mulato (bred by the International Center for Tropical Agriculture (CIAT)) is used as a border crop with cereals such as maize, and greenleaf desmodium is used as an inter-crop. Desmodium fixes nitrogen, and thus provides some fertilizer to the crop. Highly significant reductions in Striga and stem borer damage to maize along with improved plant height, grain yield and soil fertility were achieved via this climateadapted, push-pull system studied (Midega et al., 2015). Brachiaria cv mulato also serves as feed for livestock and, as stated previously, is drought-tolerant unlike traditional fodder, Napier grass (Pennisetum purpureum). Similarly, in St. Vincent and the Grenadines, the research of Isaac, Brathwaite, Cohen, and Bekele (2007) demonstrated that Desmodium heterocarpon controls weeds such as Commelina diffusa and nematodes and improves soil fertility when intercropped with banana (Musa spp.). This push-pull approach provides a renewable, organic, affordable source of herbicide, insecticide, fertilizer and fodder for rural farmers such as those in sub-Saharan Africa and LAC. Thus it can improve food security, allow diversification of the farming system and contribute to poverty alleviation in the face of climate change. 1307

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Implementation of Early Warning and Risk Management Systems Early warning and risk management systems can facilitate the timely implementation of adaptation measures to address climate variability and change. These are listed by FAO (2007) as: • • • • • •

A historical climate data archive; an archive on climate impacts on agriculture; Monitoring tools using systematic meteorological observations; Climate data analysis (to determine the patterns of inter-annual and intra-seasonal variability and extremes); Information on the characteristics of system vulnerability and adaptation; Monitoring evidence of resilience under climate change as well as critical meteorological and environmental thresholds for manifestation of negative impacts of climate change; and Crop weather insurance indices to reduce the risk of climate impacts for lower-income farmers.

Adaptation Strategies for Crop Production in Africa The crucial role of adaptation in countering the putative negative impacts of climate change in Africa, particularly that of global warming, was emphasised by Ramirez-Villegas and Thornton (2015). In general, these authors advocated complex systemic and transformational changes in farming systems in Africa to cater for increased temperatures. Shifts in cropping patterns to allow for cultivation of new crops that are more drought-tolerant are recommended along with a concomitant adjustment in diets and trade policies. Yield losses for maize can be minimised by shortened cropping seasons and heat stress during the crop’s reproductive phase (Ramirez-Villegas & Thornton, 2015). For the common bean (highly sensitive to climate change), Ramirez-Villegas and Thornton (2015) projected decreases in yield across Africa. However, a heat-tolerant accession of a wild relative of the common bean (Phaseolus vulgaris), tepary bean (Phaseolus acutifolius) was identified at CIAT for use in breeding heat-tolerant common bean lines (Beebe et al., 2011). Thus far, breeding lines in the greenhouse have been found to maintain productivity at +3 °C over the current temperature limit of common bean. The potential for such heat tolerant lines will be achieved with further investment in research and incentives for farmers to test and adopt promising new varieties in developing countries.

THE ADOPTION OF CLIMATE-SMART AGRICULTURE Climate smart agriculture and landscapes are widely regarded as the panacea for addressing social and environmental impacts that threaten agricultural development and food security in the face of climate change. The widespread cultivation of climate-smart crops that are well-adapted to climatic change and changing growing environments will assure food security in a sustainable manner (Harvey et al., 2014; Neufeldt et al., 2013). Smart crops are better able to withstand drought than wheat or rice and do not require as much water to thrive (Swaminathan, 2012). They can be grown by rural families without irrigation. They are also nutritionally rich and have much higher protein and thus nutritional value. Consequently, these crops, many of them currently orphan crops (Cheng, Mayes, Dalle, Demissew &, Massawe, 2015), have ecological, social and nutritional benefits. Swaminathan thus recommended diversification

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of cropping patterns and the cultivation of more climate-smart crops to address the potential impact of climate change and year-to-year variability in weather patterns.

Features of Climate-Smart Agricultural Landscapes Climate-smart agriculture will mitigate against the impact of climate change by harnessing natural biological processes to improve production in a more environmentally-friendly way and avoiding degradation of natural resources (Branca, McCarthy, Lipper and Jolejole, 2011; Palombi & Sessa, 2013). This sustainable system will be less vulnerable to shocks and stresses. It will harness the best of crop varieties and livestock breeds under optimum agro-ecological and agronomic management (Beddington et al., 2012). Mba et al. (2012) recommended that in order to achieve food security under worsening climatic conditions and with constrained natural resources, higher yields must be achieved per unit of input; yield efficiency must be optimised. In Brazil, Martinelli, Naylor, Vitousek, and Moutinho (2010) emphasised the importance of this sustainable approach of increased productivity on existing agricultural land without further environmental degradation and deforestation. The cultivation of diverse, climate-smart crop varieties that can produce more with less is the objective of climate-smart agriculture. High yielding, well-adapted, resilient crop varieties that use inputs such as water and nutrients efficiently are required. They must combine superior genetic constitutions and be managed optimally. The case of the New Rice for Africa (NERICA) (West African Rice Development Association, 2001) was cited as an example of climate smart agriculture, which has already accounted for significant increases in rice production in sub-Saharan Africa.

Strategy for Achieving Climate-Smart Agricultural Landscapes CGIAR’s new strategy and research programmes: Answering to poverty, health and climate change (CGIAR, 2015) is an excellent example of a strategic and integrated approach towards achieving food security in developing countries (refer to Figure 2). Figure 2. CGIAR’s new strategy and research programmes: Answering to poverty, health and climate change (CGIAR, 2015)

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THE APPLICATION OF SCIENCE AND TECHNOLOGY AND KNOWLEDGE TRANSFER IN SECURING FOOD PRODUCTION Pollinator-Friendly Management Practices Pollinator-friendly management practices are also essential for climate-smart landscapes since they will enhance yields, quality, diversity and resilience of crops and cropping systems. Such practices include: • • • • • •

Conservation of wild habitats; Managing of cropping systems and environs to protect habitats and forage; Cultivation of shade trees; Protection of bee and other pollinator nest sites; Reduced applications of pesticides and other hazards in production systems and Establishing landscapes with natural habitats and resources that favour pollinator population survival and services (FAO, 2009a).

In Costa Rica, it was found that coffee farms located in close proximity to forested areas benefit from greater diversity and number of pollinators visiting the coffee plants. This translates into increased coffee yields and improved coffee quality (FAO, 2009a). Furthermore, the maintenance of forests provides other ecosystem services such as carbon sequestration. Maintaining pollination biodiversity in agricultural landscapes serves the dual role of ensuring pollination of crop species while serving as insurance against pest and disease threats among managed pollinator populations (FAO, 2009a). However, the system requires that farmers be trained about the value of adopting this strategy and the resources that pollinators require so as to encourage their proliferation in niches in the landscape.

Management of Soils: Nutrient Status, Porosity and Structure Climate-smart landscapes must be characterised by healthy, fertile soils that support intensive production systems. Optimal crop production cannot be achieved on degraded soils with nutrient deficiencies and soil-borne pests and diseases. The cultivation of pulses is recommended in climate-smart landscapes since legumes fix nitrogen and thus reduce the need for inputs such as nitrogen fertilizers. A case for conservation agriculture that includes zero soil tillage has been advanced by FAO (2007, 2012) and Mba et al. (2012). Reichert et al. (2015) recommended the latter for common beans based on their observations under highly variable weather conditions on sandy soils in a sub-tropical environment (Brazil). Conservation agriculture involves the maintenance of soils in an undisturbed state with a sufficient supply of organic matter that provides a good habitat for soil fauna. The avoidance of mechanical tillage increases the populations of earthworms, millipedes and other micro fauna that take over the role of tillage and build soil porosity and, with organic matter, improve soil structure. This makes land less susceptible to flooding and erosion (Palombi & Sessa, 2013). Knowledge transfer to farmers of these sustainable soil management practices is thus crucial.

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Developing Climate Smart Crop Varieties Through Research in Breeding and Technological Advances The threat of crop failures due to biotic and abiotic stress under climate change may be addressed through breeding climate-smart varieties (refer to Table 1). In 1982, Swaminathan advocated that Third World countries should master all recent developments in genetics. This should be widened now to embrace all areas of advanced crop breeding and biotechnology including molecular biology, next-generation sequencing (Bansal, Lenka and Mondal, 2014; Edwards & Batley, 2010); genomics, genomic selection and marker-assisted selection and breeding (Tester & Langridge, 2010), gene pyramiding (Gennaro et al., 2007) and tissue culture. Landscape genomics can be employed to identify the environmental factors that affect adaptive genetic variation and gene variants that facilitate local adaptation (Anami et al., 2015; Rellstab, Gugerli, Eckert, Hancock, & Holderegger, 2015). Mba et al. (2012) concluded that a re-invigorated plant breeding approach is necessary to translate climate-smart heritable variations into crop varieties to achieve increased yields and enhanced adaptation to abiotic and biotic stresses due to climate change. Fereres, Orgaz, and Gonzalez-Dugo (2011) identified the recommended strategy towards developing smart crop varieties as combining research on plant breeding, crop physiology, and agronomy, and exploiting their interactions. Furthermore, they advocated more balanced funding of agricultural research disciplines to achieve success.

Conservation of Biological Diversity: In Situ and Ex Situ, Protection of Landraces and Farmers’ Selections One of the strategies towards achieving climate-smart crop varieties is the widening of the genetic base or sources of heritable variations in crops (FAO, 2009c; Mba et al. 2012). This is in keeping with the Global Crop Diversity Trust’s efforts to promote the collection, conservation and use of wild relatives of crops in pre-breeding and breeding (Dempewolf et al., 2014; Guarino & Lobell, 2011). The value of national and national genebanks for ex situ conservation and conservation plots in farmers’ fields as well as of wild types in their natural habitats (in situ conservation) cannot be over-emphasised (FAO, 2010b). The advantage of using the tepary bean (a wild relative of the common bean) in developing heattolerant common bean lines at CIAT has already been discussed (Beebe et al., 2011). Gur and Zamir (2004) reported on the success achieved using a wild relative of tomato, Solanum pennelli, to introduce genes for drought tolerance into the commercial Solanum lycopersicum tomato variety with an attendant yield increase of 50%. At IITA, Nigeria, several genes of wild relatives of cassava were used to introduce genes to enhance cassava mosaic disease resistance, as well as to improve nutritional quality and extend shelf life of a commercial variety (Mba et al., 2012).

An Example of an Ex-Situ Collection Used to Cater for the Impact of Climate Change: The Seeds for Needs Project in Ethiopia The Seeds for Needs project in Ethiopia uses ex-situ collections to help farmers, mainly women, cope with impact of climate change on crop production (Bioversity International, 2013). Accessions, maintained at the Ethiopian National Genebank’s Institute of Biodiversity and Conservation, were catalogued

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Table 1. Adaptive traits to introduce through crop improvement/breeding in select climate-smart crop varieties Crop

Adaptive traits Drought

Rice

Early flowering, deeper and thicker roots, root pulling resistance, root penetration, osmotic adjustment (OA), rapid stomatal closure, water-use efficiency (WUE), membrane stability, leaf rolling score, and leaf relative water content

Wheat

Early flowering, stem water-soluble carbohydrate (SWSC), green flag-leaf persistence, WUE, transpiration efficiency (TE)

Maize,

Early flowering, anthesis silking interval (ASI), ears per plant, stay-green chlorophyll content, osmotic adjustment (OA), root traits, leaf abscisic acid (L-ABA)

Barley

Early flowering, plant stature, ear type, WUE, OA, high biomass combined with SWSC, water extraction, and transpiration efficiency (TE)

Sorghum

Early flowering, stay-green, SWSC, TE, rooting depth and patterns, epicuticular wax

Pearl millet

Early flowering, few tillers, low biomass and high harvest index including panicle harvest index, grain yield, individual grain mass Profuse rooting in the deeper layers of soil

Chickpea

Early flowering, deep rooting and higher root length density

Groundnut

Early flowering, WUE, transpiration, TE, specific leaf area (SLA), and chlorophyll meter reading

Rice

Time of day when flowering (TDF) commences (early TDF protects fertility from high temperature), high temperature tolerance at grain filling (pollen shedding, pollen germination and pollen tube extension) Higher leaf transpiration rate to maintain lower leaf temperature combined with opening of flowers in morning (O. glaberrima)

Rice

Early vegetative stage: salt exclusion or low uptake, compartmenting of toxic ions in structural and older tissues, higher tissue tolerance by compartmenting salt into vacuoles, stomata that close faster upon exposure to salt stress Reproductive development stage: salt exclusion from flag leaves and developing panicles

Wheat and barley

Na+ exclusion, K+/Na+ discrimination, sheath retention of ions, tissue tolerance, ion partitioning into different-aged leaves, OA, enhanced vigour, WUE, and early flowering

Maize

OA and abscisic acid (ABA)

Sorghum

Whole plant tolerance resulted from reduced shoot Na+ concentration, a major mechanism involved in salt tolerance

Pearl millet

Whole plant tolerance associated with reduced shoot N content, increased K+ and Na+ contents; with shoot Na+ concentration a potential non-destructive selection criterion at vegetative-stage screening

Chickpea

Ability to maintain large number of filled pods; shoot Na+ or K+ not related to salinity

Pigeon pea

Reduced shoot Na+ concentration

Groundnut

Pod numbers per plant

Heat

Salinity

Flood Tolerance/Submergence Rice

Vigorous seedling growth, elongation ability, submergence tolerance, resistance to lodging or recovery from lodging after water level reduction

(Adapted from Jarvis et al., 2008)

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in terms of climate profiles. Accessions most likely to be adapted to future growing conditions in areas with similar environmental profiles were identified using the collection, characterisation and evaluation data from germplasm collections and Geographic Information System (GIS) technology. Varieties were then tested by selected farmers under their respective growing conditions, and based on their indigenous knowledge and adaptation strategies. After the testing process, the best performing and most adaptable varieties were distributed to farming communities for multiplication and observation.

Utilisation of Crop Genetic Diversity in Selecting Climate Adaptation Traits Conservation, characterisation, evaluation and utilisation of diverse crop genetic resources should facilitate the identification (selection) and breeding of climate-smart crop varieties (Heisey & Rubenstein, 2015; McCouch et al., 2013). Plants under abiotic stress are affected physiologically and biochemically and undergo changes in gene expression and regulation, in the short and long term, in response to unfavourable environmental conditions (Saibo, Lourenço, & Oliveira, 2009). Adaptation to water deficits (drought stress) can thus be mediated through morphological, physiological and biochemical mechanisms in crops (Beebe et al., 2011) and requires a diverse genetic base for the identification of favourable genotypes with adaptive traits for drought tolerance. The latter includes deeper root systems, stomatal control and improved translocation of nutrients within the plant. Beebe et al., (2011) advocated research to fit the right root system to specific common bean production environments under drought conditions, and reliable screening methods to evaluate waterlogging tolerance of genotypes under flooded conditions. With regard to heat stress, acclimation to high temperatures in certain genotypes may favour selection of heat tolerant varieties. A method of screening pollen to determine heat tolerance in soybean was developed by Salem, Kakani, Koti, and Reddy (2007) and may be useful for screening of the common bean (Beebe et al., 2011). Detailed data on the responses to climate change (changing temperature and rainfall patterns) of the pests and diseases affecting crops in developing countries are necessary. An understanding of these phenomena and the identification of adapted or tolerant genotypes will facilitate the implementation of adaptation strategies to deal with the biotic stress due to pests and diseases.

Marker-Assisted Selection and Genomic Breeding Molecular markers are currently the most powerful tools for elucidating the inheritance of target regions of plant and animal genomes in breeding material, and environment-neutral markers allow marker-assisted selection (MAS) and genomic breeding (Edwards & Batley, 2010). Marker assisted selection could be a useful tool to identify (abiotic) stress tolerant traits such as specific rooting depth in common bean, once quantitative trait loci (QTL) for this quantitative trait have been located. It leverages the burgeoning available molecular data on completely or nearly completely sequenced plant genomes to select for candidate genes, protein sequences, and favourable genotypes, while taking into account genotype by environment interaction and targeting adaptive/morpho-physiological traits (Jha, Bohra, & Singh, 2014; Lasky et al., 2015). The advances in bioinformatics and computational molecular biology facilitate valid inferences to be made from the large and complex volumes of data involved in these processes. The usefulness of MAS is particularly outstanding in breeding programmes that involves polygenic traits. MAS allows quick progress in accumulating two or more genes (pyramiding) for desirable traits in segregating breeding material compared to conventional breeding methods. The latter is constrained 1313

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by the length of the breeding cycle and the dependence on screening, based on phenotypes, which often has to be conducted on mature plants when reproductive traits are involved. The time required to breed a new crop variety may be decreased by half when MAS is employed (Mba et al., 2012). The negative side is the cost involved (Ribaut, Vicente, & Delannay, 2010). However, high-throughput molecular biology assays are becoming increasingly available and costs are decreasing. Furthermore, human capacity building in using these techniques and putting the results at the disposal of farmers in developing countries is in progress.

High-Throughput Phenotypic Evaluations High throughput imaging of living plant organs can also be valuable for unravelling complex traits affected by climate change such as drought and salinity tolerances (Ghanem, Marrou, & Sinclair, 2015). Access to the technology required for thermal infra-red and near-infrared fluorescence spectrometry and magnetic resonance imaging allow non-destructive physiological, morphological and biochemical assays that can be used to investigate these complex traits (Fahlgren et al., 2015). However, the high establishment costs and technical expertise required to conduct high-throughput phenotyping may also restrict access to it, in the short-term, by developing countries.

CASE STUDY Harnessing Research and Technology to Combat Climate Change in Cacao (Theobroma cacao L.) Research and application of research findings and technology to combat the threat of climate change in cacao4 have been ongoing (Stigter, 2008). The impact of soil, water and climate (drought, flooding, high temperature and irradiance) pose a threat to sustainable cocoa production (Oyekale, Bolaji, & Olowa, 2009). There is a need to increase efficiency to manipulate water use, soil and microclimate and to use improved (climate-smart/well adapted) stress tolerant planting material. Technological approaches such as genome-wide association studies and breeding with genomics and other technological advances may be applied in developing superior cacao varieties to combat the impact of climate change. The completed mapping of the cacao genome will facilitate the identification of marker-trait associations in cacao germplasm that can be used to breed varieties with biotic and abiotic stress tolerance. The selection of well-adapted varieties with drought, heat (high irradiance) stress and other forms of abiotic stress tolerance is a major goal of cocoa breeding in West Africa (Läderach, Martinez-Valle, Schroth, & Castro, 2013). Studies on the effects of soil water deficit (Antwi, 1994) and irradiance (Galyuon, McDavid, Lopez & Spence, 1996a, b) have been conducted in Trinidad & Tobago, and an investigation on climate change adaptation to drought and heat in cacao is currently in progress. In Brazil, dos Santos et al., (2014) found that the best traits to screen for drought tolerance were leaf and total dry biomass, relative growth rate and magnesium content of leaves. These authors also found increased expression of drought tolerance candidate genes (as those associated with ABA biosynthesis and biosynthesis of proteins of PSII of the photosynthetic pathway) in genotypes classified as nontolerant after exposure to soil water deficit for a period of time. dos Santos et al. (2014) also observed that in tolerant genotypes, there were significant increases in guaiacol peroxidase activity, reflecting a 1314

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more efficient antioxidant metabolism. This increased activity of oxidative stress enzymes is a response to soil water deficit. In Ghana, where drought is the major abiotic stress affecting cacao (Anim-Kwapong & Frimpong, 2005), Ofori, Padi, Acheampong, and Lowor (2015) examined genetic variation and the relationship of traits associated with drought tolerance in cacao under shade versus non-shade conditions. These authors reported that stem growth, percentage survival, leaf chlorophyll content and plant vigour were important traits to screen for drought tolerance under these conditions. In order to mitigate the potential adverse effects of climate change in cacao, Stigter (2008) stressed the role of good managerial practices (proper shade management, application of organic fertiliser and bio-control of pests), inter-planting with agro-forestry species and extension to educate farmers on good agricultural practices (GAPs), in Climate Field School classes (CFSs), to cope with the impact of climate change. In addition, biodiversity friendly cacao cultivation can be practised such that a favourable balance between yield, farmer income and biodiversity conservation is achieved, as prescribed by Waldron, Justicia, Smith, and Sanchez (2015). Farmer income can be supplemented by sustainability certification (eco-labelling) and incentives awarded to small farmers for managing eco-friendly cacao agroforestry systems based on the United Nations REDD (reducing emissions from deforestation and forest degradation) initiative (Millard, 2011).

SOCIAL REFORMS FOR OPTIMISED AND SUSTAINABLE AGRICULTURAL PRODUCTION AND DEVELOPMENT Scherr, Shames, and Friedman (2012) identified several key social factors required in strategies for securing food production and achieve food security. These include: • • • • •

Strengthened technical capacities; Institutional and political support for multi-stakeholder planning; Good governance; Spatial targeting of investments and Multi-objective impact monitoring.

Sasson (2012) identified several social constraints to be addressed in order to increase agricultural production and achieve food security. These include lack of easy access to land, lucrative employment opportunities in the rural environment, lack of proper access to local markets (with proper road infrastructure and loan arrangements) and inadequate access to training and technologies that will increase production, productivity, food safety, improve food handling and storage, post-harvest activities (including packaging), distribution and marketing and promote sustainable value-addition initiatives. Access to training in best practices and technology (including agricultural diagnostic applications on smart phones) is particularly critical to implement climate change adaptation techniques to address drought, extreme temperatures and other abiotic stresses. Research and development along with dissemination of the resulting information to agriculturists are thus crucial (Ejeta, 2009). Gender inequality was also regarded as a constraint to achieving food security (Flachsbarth et al., 2015; Perez et al., 2015). Thus a summary of social reforms that can impact positively on agricultural development and food security includes: 1315

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• • • • • • • • • • • • • •

• • • • • •

Poverty alleviation; Creating a shorter, more efficient supply and value chain for farmers Improving farmer livelihoods; Diversification of incomes; Adequate access to credit; Strengthening of women’s position; Greater access to social amenities; Greater access to an adequate and reliable labour force; Improvement in production standards with regards to child labour; Attracting youth to agriculture; Stability of land ownership rights and land tenure; Improving infrastructure (particularly of access roads and bridges); Access to equipment and technology for farm/production efficiency; Improvement of access to schooling and education; ◦◦ Access to extension services and training in GAPs and good manufacturing practices (GMPs) – through participatory learning; ◦◦ Improving the business acumen of farmers – through farmer field schools (FFS); Adoption of food safety and quality assurance practices; Avoiding trade-offs between quality of produce and short term revenues; Improving access to market information and support services; Access to efficient transport/wholesaling markets, refrigeration and post-harvest practices to avoid food spoilage and wastage; Creation and strengthening farmer’s organisations such as co-operatives to facilitate optimisation of all activities along the food value chain and facilitate sharing of costs among food producers and promoting value addition; and Addressing the disconnect between food producers and consumers.

Promoting food security is deemed feasible through the spread of modern farming, crop research and food processing in developing nations (Sasson, 2012). Farming communities must be educated in modern farming through knowledge and technology transfer and equipped to practise such methods. Investment and resources must be supplied to rural farming communities, particularly of small farmers, and policies implemented to bring about the requisite social and environmental changes and human capacity building to combat climate change. Policy, legal and market environments that encourage innovation and capital investment must be fostered. The role of the International Convention for the Protection of New Varieties (UPOV) is also critical so that there is an equitable balance between Intellectual Property Rights (IPR) and contributions to public good (Mba et al., 2012).

THE ROLE OF EDUCATION AND INSTITUTIONS Training and education are key catalysts to bring about environmental and social reform to promote agricultural development and food security, particularly in SIDS (Bekele & Ganpat, 2014). The areas of particular concern are:

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• • •

•

Participatory approaches to social learning to persuade farmers to adopt new and improved agricultural approaches such as the climate-adapted push-pull system (Isaac et al., 2007; Midega et al., 2015) and integrated pest management; Technology transfer to food producers along the value chain; Sensitization of rural and urban communities to encourage proper nutrition, avoidance of food wastage (according to the FAO, one third of the food produced globally is discarded or spoilt) and adoption of healthier and more energy efficient eating habits; ◦◦ including the acceptance of a diet with protein from vegan and non-red meat sources to reduce the consumption of red meat that contributes to carbon emissions (14% of the global total) and utilisation of large volumes of water; and Adoption of modified and healthy diets based on climate-smart agriculture.

Education to change public awareness and practices that affect agricultural production and food security is crucial. According to Bailey, Froggatt and Wellesley (2014), governments and environmental groups are reluctant to pursue policies or programmes to shift consumer behaviour. Much research has and is being conducted in developing nations to facilitate more sustainable food consumption patterns. Boland et al. (2013) and Lukefahr (2005) identified rabbits as a suitable alternative for animal protein in developing countries, but the populace has to be convinced to utilise this and other alternative animal protein sources such as the collared peccary/quenk and agouti (Mollineau, Garcia, Samayah, Kissoonsingh, & Procope-Garcia, 2000) in future animal protein production and consumption systems. Alternatives for imported staples such as wheat are available in the developing world and consumer appreciation for tropical food crops such as breadfruit (Artocarpus altilis, Moraceae) and chataigne (A. camansi) is already fairly high (in excess of 61% in Trinidad and Tobago) (Roberts-Nkrumah & Legall, 2013). In other cases, consumer acceptance will have to be encouraged, taboos and fear of the new (neophobia, as explained by Cox and Evans, 2008) will have to be displaced, and ethical issues resolved. A concerted education drive is thus required for potential producers and consumers. Furthermore, accountability and responsibility are necessary to preclude public distrust (Boland et al., 2013). Social systems could be valuable in addressing food waste. A well organised system for collection of food waste with acceptable nutritional value that is safe for animal consumption can serve the dual role of reducing food waste while providing a source of animal feed. There should be a review of legislation that currently forbids the use of human food waste in animal production (Boland et al., 2013). Education of personnel to sort and manage food waste and to monitor its safety for animal consumption is thus necessary. There will also be safety issues for humans operating the system and for consumers of the resulting animal products that will have to be addressed by research and knowledge transfer. A key role of education and institutional support is to link science and policy on food security under climate change. This requires multi-stakeholder, participatory scenarios to bring the diverse actors and organizations together to create the necessary policy-making tools, as described by Chaudhury et al., (2013). The knowledge made available by scientists can thus be transferred to policy makers to facilitate implementation of necessary changes and programmes to address food insecurity and the negative impacts of climate change. Institutions such as regional universities and international organisations based in the developing world can undertake the credible, salient and legitimate boundary work required in this process. They can provide fora for assembling farmer representatives, scientists, policymakers, civil society, government and private sector so that multiple perspectives may be aired, scenarios created and policies drafted to implement approved practices and technology. In East Africa, the CGIAR 1317

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programme on Climate Change, Agriculture and Food Security (CCAFS) has adopted this approach to promote climate-smart agriculture and food security, bridging science and non-science boundaries, and have forged the link between knowledge and action (Chaudhury et al., 2013). At multi-stakeholder workshops, they were able to determine common outcomes of interest for food security, viz., food affordability, regional production, food distribution and nutritional value for food security, water and soil quality, forest cover, biodiversity status, water sufficiency for environment, and financial wealth, social capital, health, and knowledge and skills for livelihood.

CASE STUDY: SOCIAL ISSUES AFFECTING COCOA PRODUCTION The cocoa industry, which supports the projected (by 2016) 98.3 billion USD chocolate and cocoa-based industry (World Cocoa Foundation, 2015), has been beleaguered by social as well as environmental challenges. Despite this, the International Cocoa Organisation (ICCO) recognised the importance of the cocoa sector for economic development and poverty eradication, particularly in West Africa, which produces 70% of the world’s cocoa. The ICCO affirmed that to secure this important role, stakeholders in the cocoa chain are jointly facing the challenge to promote sustainable development in cocoa production, commercialization, processing, manufacturing and consumption (Ebai, 2004). To rise to these challenges, ICCO launched a Roundtable on a Sustainable Cocoa Economy in 2007 in Accra, Ghana, and a Second Roundtable was convened in Trinidad in 2009. The social issues of serious concern in the cocoa sector pertain to labour, farmer well-being and livelihoods and training in best practices. There is justification in concluding that the monetary benefits of the thriving global cocoa and chocolate industry have not trickled down to the farming communities adequately.

Child Labour: A Serious Social Issue Child labour in cocoa production became the focus of international attention and disdain in 2002 (Mustapha, 2009). The International Labour Office (ILO) and the International Program on the Elimination of Child Labour (IPEC) presented statistics that indicated that 284,000 children were working under hazardous conditions in West Africa. Since then, the industry has made concerted efforts to address the situation and stop all forms of exploitative or the worst forms of child labour in cocoa production (Grossman-Greene & Bayer, 2009; Schrage & Ewing, 2005). Several initiatives have resulted and groups formed to achieve the goals of the Harkin-Engel law adopted in 2001 to address the worst forms of child labour (Berlan, 2009) as well as assure sustainability of cocoa production. These include the Sustainable Tree Crop programme (STCP) in West Africa and South-east Asia (Abbott, 2003), CocoaAction and Transforming Education in Cocoa Communities (TRECC), which was launched in May, 2015. CocoaAction was launched in May 2014 to deliver a comprehensive package of services in both productivity and community development to cocoa farmers, their families and their communities. TRECC will reach nearly 200,000 individuals through a series of interlinked interventions in research, capacity building, policy formulation and influence, fundraising, and supporting matching grants to complement CocoaAction. It is an initiative of the Swiss Charitable Foundation, The Jacobs Foundation that will be executed in Côte d’Ivoire. A key element will be education to restrict child labour, which is currently still a serious problem in Côte d’Ivoire.

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Farmer Education to Promote Sustainability in Cocoa Production Farmer education is included in the aforementioned CocoaAction, TRECC and STCP programmes. In addition, the Learn To Grow programme was launched by Hershey and will include more than 60,000 West African cocoa farmers. It is intended to create both better farming practices and better cocoa communities. Hershey has a goal to purchase 100% certified cocoa by 2020. This is envisaged to provide premiums to assist farmers and farmer organizations in adopting modern farming practices, including organic farming, and to develop their communities. In South-east Asia, (Sulawesi, Indonesia and Papua New Guinea), the Australian Centre for International Agricultural Research (ACIAR) conducted a project, SMAR/2005/074, entitled Improving cocoa production through farmer involvement in demonstration trials of potentially superior pest/disease resistant genotypes and IPM). The objectives were to select and test local cacao clones at different locations for disease and pest resistance (Vascular Streak dieback and Cocoa Pod Borer), evaluate IPM options and assess technology uptake by farmers (Neilson et al., 2014). The importance of addressing social and economic constraints in cocoa production, and in educating farmers on how to utilise the available information, based on empirical research as well as technology and improved methods, such as IPM, was emphasised.

Fairtrade in Cocoa Approximately eighty-five percent of the world’s chocolate comes from farms of 5 hectares or less, mainly in the developing countries of West Africa, South-east Asia and Latin America. Cocoa farming families earned as little as US$30 - $110 per family member per year, according to Knapp (2005). Fairtrade chocolate, made from Fair Trade certified cocoa, offers a solution for small farmers and their dependents to break the cycle of poverty. By cutting out middlemen and brokers, Fair Trade allows cocoa farmers to receive a fair share of the final market value of their products (Liu, Byers, & Giovannucci, 2008; Pay, 2009). Fairtrade certification creates direct trade links between farmer-owned cooperatives and buyers, and it provides access to affordable credit. Fairtrade gives farmers the tools to access the market and to farm in a sustainable manner. In addition, under the terms of Fairtrade, there are strict labour standards that foster healthy working conditions and allow children under the age of 15 to work on their family’s farm only if their education is not jeopardized. Children under the age of 18 are not allowed to work with machetes (or other dangerous tools) or to apply pesticides.

A Multi-Stakeholder, Cohesive Approach to Ensure Sustainable Cocoa Production A structured, multi-sector, international approach to conserve cacao germplasm as a safeguard against the impact of climate change and other threats and to meet emerging needs of cocoa farmers has already been adopted. The United Nations Common Fund for Commodities/International Cocoa Organisation/ Bioversity International (CFC/ICCO/BI) executed a project entitled Cocoa Germplasm Utilization and Conservation: A Global Approach (1998 – 2004) (Eskes, Engels, & Lass, 1998; Eskes & Efron, 2006). The main objective for this project at the Cocoa Research Unit (now Cocoa Research Centre, CRC), a partner in the project, was germplasm enhancement for Black Pod (BP) and Witches’ Broom (WB) dis1319

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ease resistance in cacao. Several primary germplasm varieties were identified, and enhanced genotypes (through pre-breeding (Guarino & Lobell, 2011)) produced at CRC with combined resistance to both WB and BP diseases. The yield potential, bean traits, precocity, vigour and flavour profiles of these individuals were or are still being assessed at CRC (Iwaro et al., 2010). The most promising enhanced cacao varieties were transferred to the International Cocoa Quarantine Centre, Reading University, U.K. to facilitate distribution to the other project partners in cocoa producing countries. Selected progeny are also being used in the Ministry of Agriculture, Trinidad and Tobago’s successful Trinidad Selected Hybrid cacao breeding programme (Maharaj et al., 2011) to accumulate resistance genes for BP. This will facilitate the development of further improved, superior planting material to distribute to cocoa farmers in Trinidad and Tobago. Launching of Farmer Field Schools (FFS) and Farmer Participatory approaches to improving cocoa production have also received considerable attention within the last decade. The CFC/ICCO/BI project entitled Cocoa productivity and quality improvement: a participatory approach was conducted from 2004 to 2009. This project was successful in educating farmers and assisting them in recognising and selecting the best trees within their fields for multiplication and conservation. Techniques to screen for disease and pest resistance and to assess traits of economic interest as well as quality and flavour of cocoa were also put at the disposal of rural cocoa farming communities (Eskes, 2011). These two, aforementioned CFC/ICCO/BI projects involved 14 cocoa-producing countries, including Trinidad and Tobago, as well as manufacturers (consumers), government bodies and institutions. They are models for a successful, cohesive approach towards achieving agricultural development and food security. In West Africa, South-east Asia, Latin America and the Caribbean, FFS are now routinely hosted. In Trinidad & Tobago, a project, funded by the Centre for the Development of Enterprise and implemented by the Cocoa Research Centre (CRC), resulted in the training of farmers and entrepreneurs in GAPs and GMPs practices (including for assuring food safety) in six Caribbean countries.

A COHESIVE APPROACH TO ACHIEVE AGRICULTURAL DEVELOPMENT AND FOOD SECURITY Any strategy to achieve social reform and to foster agricultural development and food security in developing nations requires: 1. 2. 3. 4. 5.

A cohesive approach to achieve agricultural development and food security in developing nations; Proper fiscal/economic planning; Social programmes and networking – encompassing collaborative, iterative social learning; A proper environmental framework and Public, private and community based approach.

A comprehensive, multi-sector approach towards addressing the challenges and potential impact of climate change on food security is advocated (Chaudhury et al., 2013; Maggio et al., 2015; Mba et al., 2012). Sonnino et al., (2014) urged that a sustainable food security framework should address the complex relationships between the various stages and actors in the food supply chain (refer to Figure 2) in a holistic manner. The conventional focus on individual components (supply and demand) will not ensure sustainable food security. Participatory, multi-disciplinary and demand-driven breeding programmes, 1320

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which are nurtured by appropriate policy and legal environments and utilise scientific and technological tools to exploit crop and animal genetic resources, are recommended (Mba et al., 2012). Governance and policy structures must be put in place to support food security and sustainability efforts (Sonnino et al., 2014). Without the social support of extensionists, financiers, administrators and policy makers, the positive outcomes of participatory food production initiatives will not become transformative across the agricultural sector, but be confined to isolated sections of the rural and research communities. Participatory breeding considers the views of farmers, consumers, extensionists, vendors, rural cooperatives and industry in crop improvement. The needs of the growers and stakeholders thus inform the design of the breeding activities, rendering them relevant and efficient. Furthermore, the role and achievements of farmers in selecting and conserving crop landraces can be harnessed in the process of selecting favourable candidates to use as parents in breeding. In addition, the adoption of improved varieties by farmers is facilitated and accelerated when farmers are part of the process. The benefits of such an integrated approach have been supported by research findings based on analyses of various scenarios (Vervoort et al., 2014). The latter authors advocated more effective and efficient transformation of scientific results into a policy agenda for adaptive action on food security under climate change. Such an approach in SIDS has also been recommended and outlined by Maximay (2014). Integrated adaptation and mitigation strategies, under the umbrella of integrated landscape level planning, were recommended by Harvey et al., (2014) in order to avoid trade-offs that limit success. There is thus compelling evidence that to achieve food security under climate change in developing countries, an organised programme to breed climate-smart varieties and practise climate-smart agriculture can only be achieved through collaboration. This should also involve international organisations such as the Global Crop Diversity trust, FAO, CGIAR and the Integrated Breeding Platform, the World Bank and the World Trade Organisation. Sonnino et al., (2014) presented a detailed graphic that depicts the key issues to be addressed for a future research agenda that can assure sustainable food security (refer to Figure 3). The broad scope of this agenda demands a multi-sector approach. McCouch et al. (2013) have costed the systematic, concerted, collaborative global effort to feed the future. They estimated it as US $200 million annually.

CONCLUSION It has been projected by Flachsbarth et al. (2015) that the progress of achieving food security will vary from one developing region to the next. Their outlook for LAC and Southeast Asia and the Pacific is better than for Central-West Africa and other regions of Sub-Saharan Africa. Lobell et al. (2008) also predicted that South Asia and Southern Africa will most likely face negative climatic impacts by 2030 on several important crops if adequate adaptation measures are not adopted. This scenario may be attributed to the fast population increase relative to food production growth, particularly in Africa, as well as continued lack of access to safe water along with limited improvement in female secondary education. Policies are required to remove gender bias that limits resilience of female farmers (Perez et al., 2015). The environmental and social priorities for increasing agricultural development and achieving food security in developing countries, which were identified in this chapter, are included in the CGIAR’s strategy (Rijsberman, 2015) (refer to Table 2). Thus, there are numerous factors that need to be urgently addressed in order to assure agricultural development and food security in developing nations. These include: 1321

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Figure 3. Sustainable food security pillars- key issues for future research (adapted from Sonnino et al., 2014)

Table 2. Consultative Group for International Agricultural Research (CGIAR’s) strategy for 2016-2030 Genetic improvement of crops, livestock, fish and trees, to increase productivity, resilience to stress, nutritional value and efficiency of resource use. Agricultural systems, adopt a systems approach to optimize economic, social and environmental co-benefits in areas with high concentrations of poor people. Gender and inclusive growth, creating opportunities for women, young people and marginalized groups. Enabling policies and institutions, to improve the performance of markets, enhance delivery of critical public goods and services, and increase the agency and resilience of poor people. Natural resources and ecosystem services, focusing on productive ecosystems and landscapes that offer significant opportunities to reverse environmental degradation and enhance productivity. Nutrition and health, emphasizing dietary diversity, nutritional content and safety of foods, and development of value chains of particular importance for the nutrition of poor consumers. Climate-smart agriculture, focusing on urgently needed adaptation and mitigation options for farmers and other resource users. Nurturing diversity, ensuring that CGIAR in-trust plant genetic resources collections are safely maintained, genetically and phenotypically characterized to maximize the exploitation of these critical resources for food security, productivity, nutrient rich crops and resilient farming systems. (CGIAR, 2015)

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Social Factors • • • • • •

Reform of social conditions for rural communities – improvement of basic amenities – health, education, housing and infrastructure; Technological knowledge transfer and farmer training and education in GAPs for primary production and GMPs for value chain initiatives along with training to ensure better health and fiscal management as well as socialisation; Support of rural communities in terms of financial aid and farmer livelihood enhancement programmes to optimise income generation, eradicate poverty and improve subsistence farming (as for the establishment of co-operatives and farming enterprises that shorten the value chain); Provision of technological tools to modernise food production; Public co-ordinated programmes to address inadequate access to credit and capital and insecurity of land tenure; and Application of science and technology in education to re-engineer the farming culture and inculcate innovative approaches to food production and value-addition enterprises that will attract the youth.

Environmental Factors • • •

Climate-smart agriculture and landscapes – identifying climate adapted or resilient planting material and adopting energy efficient, sustainable agricultural production practices; The application of technology in climate adaptation strategies (next-generation sequencing, genomic selection, marker-assisted selection and breeding with genomics to develop climate-smart varieties); and Harnessing conservation and utilisation of crop genetic resources in the face of climate change and other emerging threats such as new pests and diseases.

Meeting the challenges to secure agricultural development and food production in developing nations is indeed daunting. The complex social, environmental as well as economic issues that contribute to the dilemma cannot be addressed without a collaborative approach. Policies must be developed to engender trust and co-operation among the key stakeholders. Furthermore, an agriculture-energy-water nexus approach (Rasul and Sharma, 2015) must be adopted since the impacts of climate change dictate that agriculture can only develop and be sustainable when plant and animal genetic resources and materials, water, energy and land resources are not limiting (Hubert et al., 2010). Fiscal and rural planning is a key parameter for success in achieving agricultural development and food security in developing nations. The strategies to be adopted require adequate financing along with research and development to benefit concerted genetic conservation efforts, human capacity building, technological applications in plant breeding and selection of adapted and superior plant varieties and animals, ongoing applied research such as genomics and a sophisticated network of food quality, safety, handling, processing, storage, marketing and transportation facilities.

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The successful implementation of the aforementioned strategies should guarantee a stable supply of nutritious food, readily available to growing populations in developing countries into the future. Achieving food security cannot be accomplished without ending poverty in developing nations. Farming communities must be educated, well-equipped, able to access and utilise technology and superior planting material, livestock or fisheries, and practise sustainably intensive (based on natural agricultural processes and biodiversity), modern agriculture on a lucrative scale with the benefit of secure land tenure, co-operative structures, extension services and appropriate financial support.

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Rijsberman, F. (2015). CGIAR’s new strategy and research programs: Answering to poverty, health and climate change. News from the CGIAR Consortium. Retrieved August 3, 2015, from http://www. cgiar.org/consortium-news/cgiars-new-strategy-and-research-programs-answering-to-poverty-healthand-climate-change/ Roberts, T. G., Ganpat, W. G., Narine, L., Heinert, S. B., & Rodriguez, M. T. (2015). Trinidad Food Producers’ Training Needs for Food Security and Implications for Extension. Journal of International Agricultural and Extension Education, 22(1), 7–20. doi:10.5191/jiaee.2015.22101 Roberts, T. G., & Rodriguez, M. T. (2014). An Overview of climate change and impacts on food security in small island developing states. In W. Ganpat & W. P. Isaac (Eds.), Impacts of Climate Change on Food Security in Small Island Developing States (pp. 1–30). Hershey, PA: IGI Global. Roberts-Nkrumah, L. B., & Legall, G. (2013). Breadfruit (Artocarpus altilis, Moraceae) and Chataigne (A. camansi) for Food Security and Income Generation: The Case of Trinidad and Tobago. Economic Botany, 67(4), 324–334. doi:10.100712231-013-9250-7 Rosegrant, M. W. (2011). Impacts of climate change on food security and livelihoods. In Food security and climate change in dry areas (pp. 24-26). Aleppo: International Center for Agricultural Research in the Dry Areas (ICARDA). Saibo, N. J., Lourenço, T., & Oliveira, M. M. (2009). Transcription factors and regulation of photosynthetic and related metabolism under environmental stresses. Annals of Botany, 103(4), 609–623. doi:10.1093/ aob/mcn227 PMID:19010801 Salem, M. A., Kakani, V. G., Koti, S., & Reddy, K. R. (2007). Pollen-based screening of soybean genotypes for high temperatures. Crop Science, 47(1), 219–231. doi:10.2135/cropsci2006.07.0443 Sasson, A. (2012). Food security for Africa: an urgent global challenge. Agriculture & Food Security, 1(2), 1-16. Retrieved June 12, 2015, from http://www.biomedcentral.com/content/pdf/2048-7010-1-2.pdf Scherr, S. J., Shames, S., & Friedman, R. (2012). From climate-smart agriculture to climate-smart landscapes. Agriculture and Food Security, 1, 12. Retrieved June 17, 2015, from http://www.biomedcentral. com/content/pdf/2048-7010-1-12.pdf Schrage, E. J., & Ewing, A. P. (2005). The cocoa industry and child labour. Journal of Corporate Citizenship, 2005(18), 99–112. doi:10.9774/GLEAF.4700.2005.su.00013 Sonnino, R., Moragues Faus, A., & Maggio, A. (2014). Sustainable food security: An emerging research and policy agenda. International Journal of Sociology of Agriculture and Food, 21(1), 173–188. Stigter, K. (2008). Cocoa and climate change. Can the lame help the blind. Retrieved June 19, 2015, from http://sitp.rpn.co.id/uploads/riset/kakao/Prosiding%20Kakao%202008%20Cocoa%20And%20 Climate%20Change.pdf Swaminathan, M. (1982). Biotechnology research and third world agriculture. Science, 218(4576), 967–972. doi:10.1126cience.218.4576.967 PMID:17790573 Swaminathan, M. S. (2012). Role of genetic modification in developing climate smart agriculture to ensure sustained food security. Agricultural Research, 1(4), 295–298. doi:10.100740003-012-0041-7

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Tester, M., & Langridge, P. (2010). Breeding technologies to increase crop production in a changing world. Science, 327(5967), 818–822. doi:10.1126cience.1183700 PMID:20150489 Thornton, P. K., & Herrero, M. (2015). Adapting to climate change in the mixed crop and livestock farming systems in sub-Saharan Africa. Nature Climate Change, 5(9), 830–836. doi:10.1038/nclimate2754 Tol, R. S. J. (2002). Estimates of the damage costs of climate change, Part I: Benchmark Estimates. Environmental and Resource Economics, 21(1), 47–73. doi:10.1023/A:1014500930521 Toulmin, C. (2009). Climate change in Africa. London: Zed Books. UNFCCC (United Nations Framework Convention on Climate Change). (2007). Climate change: impacts, vulnerabilities and adaptation in developing countries. Bonn, Germany: UNFCCC Secretariat. Retrieved June 4, 2015, from http://unfcc.int/resource/docs/publications/impacts.pdf Vervoort, J. M., Thornton, P. K., Kristjanson, P., Förch, W., Ericksen, P. J., Kok, K., ... Jost, C. (2014). Challenges to scenario-guided adaptive action on food security under climate change. Global Environmental Change, 28, 383–394. doi:10.1016/j.gloenvcha.2014.03.001 Waldron, A., Justicia, R., Smith, L., & Sanchez, M. (2012). Conservation through chocolate: A win‐ win for biodiversity and farmers in Ecuador’s lowland tropics. Conservation Letters, 5(3), 213–221. doi:10.1111/j.1755-263X.2012.00230.x West African Rice Development Association. (2001). NERICA: Rice for life. WARDA/ADRAO, Bouaké. Retrieved June 18, 2015, from http://www.warda.org/publications/NERICA.pdf Wheeler, T., & von Braun, J. (2013). Climate change impacts on global food security. Science, 341(6145), 508–513. doi:10.1126cience.1239402 PMID:23908229 Wickham, L. D. (1992). The potential for increasing the productivity and quality of vegetables produced in the Caribbean region: UWI research and perspectives. In G. Villanueva, J. Corven & A. Campos (Eds.), Proceedings of Taller regional centroamericano y consulta sobre planificacion de investigacion horticola (pp. 245-251). San José, Costa Rica: IICA. World Cocoa Foundation (WCF). (2015). President’s message. Retrieved June 27, 2015, from: http:// worldcocoafoundation.org/wcf-may-june-2015-2/#2&utm_source=WCF+May+%26+June+2015+Ne wsletter&utm_campaign=WCF+Newsletter&utm_medium=email

KEY TERMS AND DEFINITIONS Climate Change Adaptation: Human actions or responses in nature taken to adjust to risks posed by climatic changes or to benefit from any advantages. Climate Change Mitigation: Action taken to permanently eliminate or reduce the long-term risk and hazards of climate change to the environment, human life and property. Climate-Smart Agriculture: Agricultural practices that sustainably increase agricultural productivity and incomes, facilitate adaptation and build resilience to climate change and reduce or remove emission of greenhouse gases.

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Conservation Agriculture: Encompasses cost-effective soil management practices that minimize the disruption of the soil’s structure, composition and natural biodiversity. It takes advantage of soil fauna and properties that improve fertility that can improve crop yields while protecting the environment. Ex Situ Conservation: Protecting species of a plant or animal outside its natural habitat (in situ). Functional Genomics: Study of genes, their resulting proteins, and the role played by the latter in the biochemical processes of plants and animals. Gene Pyramiding: A process of combining or assembling multiple desirable genes from multiple parents into a single genotype. Genomewide Association Analysis: Involves scanning markers across the complete sets of DNA or genomes for a particular species such as Oryza sativa subspecies (e.g. indica), examining many common genetic variants in different individuals to see if any variant is associated with a trait of interest. Genomic Selection: A process used to identify potentially favourable organisms (animals or plants) based on specific genetic information they harbour. Genotype: Genetic makeup of a particular organism or group of organisms. Marker Assisted Selection: A process where a trait of interest is selected, not based on the physical trait itself (such as plant height), but on a molecular or genetic marker linked to it. Phenotype: Observable characteristics of an individual (such as seed size) resulting from the interaction of its genotype with the environment.

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Agriculture includes food crops, pastures and livestock, industrial crops and biofuels, forestry (commercial forests), aquaculture. The Millennium Development Goals (MDGs) are the world’s time-bound and quantified targets for addressing extreme poverty, hunger, disease, lack of adequate shelter, and exclusion while promoting gender equality, education, and environmental sustainability. Riparian vegetation is composed of plant habitats and communities along river/stream margins and banks, and a riparian area is the interface between water and land. ‘Cacao’ is the term used to describe the plant of Theobroma cacao L. ‘Cocoa’ describes the commercial product - the nibs/seeds.

This research was previously published in Agricultural Development and Food Security in Developing Nations edited by Wayne G. Ganpat, Ronald Dyer, and Wendy-Ann P. Isaac , pages 21-56, copyright year 2017 by Information Science Reference (an imprint of IGI Global).

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Marketing of Agricultural Commodities in India Rakhi Arora Jaipur National University, India

ABSTRACT Commodity market is a fast paced dynamic market with liquidity and Commodity Exchange providing a platform for trading in various agri and non agri commodities at nationalized exchanges for discovering the price of agricultural goods in India since 2003. This also provides an opportunity to farmers, manufacturers or individuals for hedging and arbitrage to minimizes the losses due to fluctuations in the futures as well as spot prices. Though the Government has taken many steps time to time to control the prices of listed commodities by imposing restrictions like imposing daily margin limits and banning futures trading in speculative commodity/commodities if required but it is still being questioned. This chapter emphasizes on the working of the National Level Commodity Exchanges in India in general, the share of major agricultural commodities traded across National Level Commodity Exchanges in India, the marketing mix for agricultural commodities in India and the benefits and challenges of commodity futures derivatives for investors in India.

OBJECTIVES OF THE CHAPTER 1. Agricultural commodities are listed and traded at various commodity exchanges in India and globally as well. Readers would understand the working of the National Level Commodity Exchanges in India. 2. Readers would come to know about the share of major agricultural commodities traded across National Level Commodity Exchanges in India. 3. Readers would understand the marketing mix for agricultural commodities in India that how commodities are bought and sold at warehouses of commodity exchanges in India. 4. The commodity exchanges provide benefits and challenges of commodity futures derivatives for investors in India. DOI: 10.4018/978-1-5225-9621-9.ch060

Copyright © 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Marketing of Agricultural Commodities in India

CASE LET Commodity market is a place where listed agricultural and non-agricultural commodities are bought and sold. There are nationalized and regional commodity exchanges in India. Indian commodity sector has also been experiencing tremendous surge since its inception. This has given a new option to investors to hedge their positions against fluctuations in the prices of commodities in near future. People are also using this platform for gaining from ups and downs in the prices without having commodities in physical but it is more specifically beneficial for farmers, jewelers and manufacturers who require raw materials and want to take delivery of traded commodities but they face warehousing issues. There are other different kinds of issues faced by participants in commodity markets such as legal, regulatory, infrastructural and others. Earlier the commodity market was regulated by the Forward Markets Commission (FMC), which has recently been merged with Securities Exchange Board of India (SEBI) on 28th Sep., 2015 after the scam of National Spot Exchange Ltd.(NSEL). This risk was faced by all the investors in this market and their confidence was also shaken which resultant in the low business of commodity exchanges but now SEBI is regulating this market and building up the confidence of the investors while implementing the more strict rules and regulations for commodity market in India.

INTRODUCTION Indian markets have provided a new opportunity for retail investors and traders, who want to diversify their portfolios beyond shares, bonds and real estate, to participate on commodity exchanges. The spectacular growth of commodity markets has also attracted many investors around the world to expand their investment to emerging markets like India, as more and more investors are realizing the potential opportunities of these markets. Like any other market, the commodity market also plays a vital role in risk management of derivatives. It is well-known that commodities are the foundation of the economies of most developing countries by way of providing food, creating income generating opportunities and export earnings to the people directly involved in agricultural activities. In most of the agriculture driven economy, it has been commonly observed that the agricultural policy made by the Government tends to protect and promote the agriculture sector through different procurement and administered price mechanism. Historically, the Government intervention is found at every stage of the marketing of major agricultural products. These includes, setting Minimum Support Prices for selected commodities, regulation of every activity of marketing such as transportation, storage, credit supply and international trading of these commodities, etc. But Government intervention has significantly declined after the initiation of liberalization and economic reforms since 1991. The impact of agricultural commodity is of great importance in the stabilization of Indian economy, as reflected through the share of primary goods, especially the food items in derivation of the price indices like inflation based on Wholesale Price Index and Consumer Price Index in India. This clearly indicates the necessity of significant growth and stability of agricultural sector to foster the overall growth of Indian economy. For managing the risk of pricing of agricultural goods because of commodities futures trading, regular attempts are made worldwide. It has been clearly observed that prices of agricultural commodities are determined increasingly by market forces of demand and supply. Hence fluctuation in demand and supply of agricultural commodities is expected to result in high price risk for agri-business. Application of several market-based instruments to deal with the commodity price 1336

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risk basically focuses on the introduction of derivatives viz. futures and options contract on several commodities. In other words, it is widely proposed to setup an efficient derivative market for commodities to strengthen the agricultural market. Generally trading in commodity derivatives and futures is done to get the necessary support from any variation in the commodity prices. This is called as Hedging. This strategy helps to offset the loss expected to incur from the adverse price movements of the underlying commodities. Therefore it is very important to develop futures and other forms of derivative trading in all commodities.

Commodity Market Commodity market is a regulated place, in which listed commodities are bought and sold through the intervention of members (brokers) of commodity exchange, by following an open system of two way quotations; the settlement of trades is done according to the bye-laws of commodity exchange. A commodities market serves the purpose of allowing two individuals to exchange the rights to goods without visual inspection. Commodity markets require the existence of agreed standards opposed to spot markets where delivery either takes place immediately, or with a minimum lag and normally involves visual inspection of the commodity or a sample of the commodity. Figure 1. Sector wise growth rate in 2013-14 and 2014-15 Source: Testbook (2015).

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According to Indian Forward Contracts (Regulation) Act (FCRA), 1952 “goods” means “every kind of movable property other than actionable claims, money and securities”. Any product that can be used for commerce or an article of commerce which is traded on an authorized commodity exchange is known as commodity. The article should be movable of value, something which is bought or sold and which is produced or used as the subject or barter or sale. In short commodity includes all kinds of goods. A forward contract is an agreement between two parties to exchange at some fixed future date a given quantity of a commodity for a price defined today (buy now, pay later). Forward contracts have evolved and have been standardized into what we know today as futures contracts. A futures contract is a type of derivative instrument, or financial contract, in which two parties agree to transact a set of financial instruments or physical commodities for future delivery at a particular price. If you buy a futures contract, you are basically agreeing to buy something that a seller has not yet produced for a set price. But participating in the futures market does not necessarily mean that you will be responsible for receiving or delivering large inventories of physical commodities - remember, buyers and sellers in the futures market primarily enter into futures contracts to hedge risk or speculate rather than to exchange physical goods (Wilson, n.d.).

Commodity Derivatives Commodity derivatives have had a long presence in India and it provides opportunities to investors for minimizing their future price risk. A derivative is a product whose value is derived from the value of one or more underlying variables or assets in a contractual manner. The underlying asset can be equity, forex, commodity or any other asset (Bhat, 2009). Derivative contracts are of different types. The most common ones are forwards, futures, options and swaps. Participants who trade in the derivatives market can be classified under the following three broad categories - hedgers, speculators, and arbitragers. In India, the National Commodity Exchanges are Multi Commodity Exchange, Mumbai (MCX), National Commodity and Derivatives Exchange, Mumbai (NCDEX), National Multi Commodity Exchange, Ahmedabad (NMCE), Indian Commodity Exchange Ltd., Mumbai (ICEX), ACE Derivatives and Commodity Exchange, Mumbai (ACE) and Universal Commodity Exchange Ltd., Navi Mumbai (UCX) but ACE and UCX have suspended their operations in India recently. These exchanges are playing very important role in the trading of agricultural as well as non-agricultural commodities in India. Derivative contracts in 113 commodities are available for trading. National Commodity and Derivatives Exchange (NCDEX) is the largest commodity derivatives exchange. Forward Markets Commission (FMC) introduced futures contracts on these exchanges in new commodities time by time for increasing trading level. The Forward Markets Commission (FMC), established under the Forward Contracts (Regulation) Act, 1952, regulates commodity derivatives trading in India in the same way as Securities Exchange Board of India (SEBI) does for securities markets but FMC has been merged with SEBI on 28th Sep. 2015 and now SEBI will also regulate the commodity futures market in India. The commodities traded at these Exchanges comprise the following: • • • 1338

Edible Oilseeds Complexes: Mustard seed, Cottonseed, Soybean oil etc. Food Grains: Wheat, Bajra, and Maize etc. Metals: Gold, Silver, Copper, Zinc, Aluminium, Steel etc.

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• • • •

Spices: Turmeric, Pepper, Jeera, Chilli etc. Pulses: Chana. Fibres: Cotton, Jute etc. Others: Sugar, Gur, Rubber, Natural Gas, Crude Oil etc.

BACKGROUND Trading in derivatives started to protect farmers from the risk of the value of their crop going below the cost price of their produce. Derivative contracts were offered on various agricultural products like cotton, rice, coffee, wheat, pepper, etc. The first organized exchange the Chicago Board of Trade (CBOT) was established in 1848. In 1874, the Chicago Produce Exchange, which is now known as Chicago Mercantile Exchange, was formed (CME). These both are the largest commodity derivatives exchanges in the world. The Indian Commodity markets also have a long presence. The commodity derivative market has been functioning in India since the nineteenth century with organized trading in cotton through the establishment of Cotton Trade Association in 1875. Over the years, there have been various bans and suspensions on various contracts. Commodity futures, which were introduced for risk management purposes in 2003, are now catching the eyes of investors as an investment tool. People, who are not having commodities in physical form and even don’t require any commodity, are trading in the commodity derivatives market. They are just speculating in the direction of the prices of listed commodities for making money but it is affecting pricing of agricultural goods in India as many of the agricultural goods like pepper, jeera, channa, potato, guarseed, mustard oil, wheat are available for trading on commodity exchanges. Prices of these commodities are getting affected due to speculation done by the traders and it is leading to high inflation in India. These markets are basically used to hedge commodity price risks and also provide transparent mechanism for discovering future prices by providing a platform for exchanging demand and supply information about all listed commodities. The hedging and price discovery functions of future markets promote more efficient production, storage, marketing and agro-processing operations and help in improvement in overall agricultural marketing performance. Foreign institutional investors, banks and insurance companies are not allowed to trade on the Indian commodity Markets and a majority of volumes come from jobbers, arbitrageurs, retail traders and corporates for hedging. Although India has a long history of trade in commodity derivatives, this sector remained underdeveloped due to government intervention in many commodity markets to control prices. The production, supply and distribution of many agricultural commodities are still governed by the state. Free trade in many agricultural commodities items is restricted under the Essential Commodities Act (ECA), 1955 and Agriculture Produce Marketing Committees (APMC) Acts of various State Governments. The forward and futures contracts were, till April 2003, limited to only a few commodity items under the Forward Contracts (Regulation) Act (FCRA), 1952. However, in 2003, GOI removed all restrictions on commodities, which could be traded on commodity exchanges.

Important Milestones in Commodity Futures Trading in India •

1875 - Bombay Cotton Trade Association: While there is a viewpoint that Futures Trading has existed in India for thousands of years, the first organised futures market was established only in 1339

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•

1875 by the Bombay Cotton Trade Association to trade in cotton contracts. This occurred soon after the establishment of trading in Cotton Futures in UK, as Bombay was a very important hub for Cotton Trade in the British Empire. 1893 - Bombay Cotton Exchange Ltd: Following widespread discontent amongst leading cotton mill owners and merchants over the functioning of the Bombay Cotton Trade Association, a separate entity, by the name “Bombay Cotton Exchange Ltd.” was constituted.

Soon after the commencement of Cotton Futures, Futures trading in Oil Seeds was started by the formation of Gujarat Vyapari Mandali, which was established in the year 1900 in Mumbai. It is currently known as “The Bombay Commodity Exchange Limited” (BCE). Futures trading in Raw Jute and Jute Goods began in Calcutta with the establishment of the Calcutta Hessian Exchange Ltd., in 1919. Later East Indian Jute Association Ltd. was set up in 1927 for organising futures trading in Raw Jute. These two associations amalgamated in 1945 to form the present East India Jute & Hessian Ltd., to conduct organized trading in both Raw Jute and Jute goods. Futures trading in raw jute suspended in 1964 reportedly on the insistence of the then State Government (WB Govt.) as there were too many reports and allegations of price manipulations which left the farmer in the lurch. The Government had no other alternative but to suspend it. The announcement to reintroduce it was made in February 2003 after the Union Government had pressed for its return (Essays, 2015). The functioning of futures markets came under suspicion because of rising prices of some commodities during 2006–07 and the government ordered a possible delisting of futures contract commodities like Urad, Tur, Wheat and Rice to avoid the abnormal rise in their domestic spot prices. Followed by this, Sugar, Oil, Rice and Potato were also banned in 2007, but were subsequently delisted in 2008. In a similar way, the India Government again banned future trading in Chana, Potato and Soya oil in May 2008. However, a steady process of opening up has been visible in future market for commodities over the last two years. As a result of significant policy change, liberalization of world markets and other developments, Indian commodity markets have shown phenomenal growth in terms of number of products, participants, technology, transparency and volume of trade.

Characteristics and Scope • • •

Hedging is done in the commodity futures market with the objective of transferring risk related to the possession of physical assets through any adverse movements in futures and spot prices. Price stabilization along with balancing demand and supply position. Futures trading leads to predictability in assessing the domestic prices, which maintains stability, thus safeguarding against any short term adverse price movements. Flexibility, certainty and transparency in purchasing commodities facilitate bank financing. Predictability in prices of commodity would lead to stability, which in turn would eliminate the risks associated with running the business of trading commodities. This would make funding easier and less stringent for banks to commodity market players.

Scope Researches done in this field are mostly related to overview of commodity market, price discovery of various commodities, behavior of investors and price volatility of some agricultural commodities but 1340

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the problem of analyzing the impact of commodities trading on agricultural commodities at national level as a whole is still lacking. Bhagwat Shree Dr., Maravi Singh Angad, More Ritesh, and Chand Deepak (2015) in their research paper have discussed the growth of commodity futures market in India, taking into consideration the history of commodity futures market as well as the mechanism of trading, segments and regulatory framework of commodity market in India. According to them, commodity futures market has witnessed several developments since 2002-03. There has been tremendous growth in commodity futures market in terms of volume of trade, number of products on offer participants and technology. Commodity futures market is instruments to achieve price discovery and price risk management as futures markets provide liquidity and facilitated to hedge against future price risk. Commodity trading also offers a change for financial leverage to hedgers, speculators and other traders. A structural system has been created for commodity trades. There are 26 exchanges operating in India and carrying out futures trading activities in as many as 146 commodity items. As per the recommendation of the FMC, the Government of India recognized the National Multi Commodity Exchange (NMCE), Ahmedabad; Multi Commodity Exchange (MCX); National Commodity and Derivative Exchange (NCDEX), Mumbai and Indian Commodity Exchange (ICEX) as nationwide multi-commodity exchanges. MCX has a major market share and the exchange turnover has been increased on every year. The growth of commodity futures market of India will lead to further development in the field of electronic warehouse receipts which may facilitate seamless nationwide commodity spot market. It would strengthen the Indian economy to face the challenge of globalization. Dash, Solanki, and Shobana (2015) found in their study that derivative markets have attained more than eighteen times in trading volume when compared to the spot markets. They analyzed the impact of trading volume, inflation and other macroeconomic factors on spot and futures price movements using GARCH model. The study explored commodity prices from several different angles. First, they found the possibility of lead-lag relationships between commodity spot and futures prices of different categories of commodities such as Precious Metals, Base Metals and Agro products traded on MCX. Second, they analyzed the inter-relationship of spot and futures prices and trading volume, for the same commodity, and between substitute and/or complementary commodities such as between gold & silver, crude oil & natural gas, the base metals, and agricultural commodities. Third, another area they explored in the study was the impact of trading volume and inflation on commodity price volatility for selected commodities. While trading volume was found to have significant impact on volatility, inflation was found to have significant impact on crude oil price volatility only. Bansal Rohit, Dadhich Varsha and Ahmad Naveed (2014) in their study found that in its long history of trading in commodities and related derivatives, Indian commodity market has seen several developments between two extreme scenarios: protection of the essential commodity market through government intervention and the opening up of the sector and getting the necessary protection through market based instruments like commodity futures contract. After a long period of suspension commodity derivative market was reintroduced in India in early 2000s. Since its resumption, however, the market has been growing at a very high pace. The growth is evident in the spread of market network as well as in volume of trade. Almost 100 commodities (agricultural and non- agricultural) are traded in different exchanges. The volume of trade has increased from Rs. 34, 84,485 crore in 2006 to Rs. 11948942 crore in 2011. It indicates a positive growth in the commodity market sector in India. Dhole Suresh Sagar (2014) in his research paper investigated the antiquity of commodity futures market in India epoch back to the ancient times citied in Kautialya’s ‘Arthasastra’, and have been commodity heard in Indian markets for centuries, seems to be coined in 320 BC, referred in Forward Contracts 1341

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(Regulation) Act, 1952. They found the markets have made enormous advancement in terms of technology, transparency and the trading activity. Interestingly, this has happened only after the Government protection was removed from a number of commodities, and market forces were allowed to play their role. Rational Government policies and the plinth of effective laws have benefited in many ways like Credit accessibility, improved product quality, predictable pricing, Import-export competitiveness, and price risk management and price discovery. Rajamohan, Vethamanikam, Arul Hudson and Vijaykumar (2014) in their study examined that the commodity trading has a long history and it has been modernized in the market. The commodities trading are occupied an important place in the economy it depends on the international trade A structural system has been created for commodity trades. It is creating awareness and the more opportunity to the investors and public. They found the market volatility is based on these commodities performance. However the commodity market has provided huge support to the Indian economy. Brajesh Kumar and Pandy Ajay (2013) in their research work investigated the short run and long run market efficiency of Indian commodity futures market. They had tested four agricultural and even nonagricultural commodities for market efficiency and un biasedness. The result confirmed the long run efficiency of commodity futures prices and inefficiency of futures prices in short run. Chhajed and Mehta (2013) found that the price discovery mechanism is quite effective for most commodities, but may not be very effective for some commodities. In particular, causality in commodities markets can be used to either hedge or speculate price movements: if changes in spot prices drive changes in futures prices, efficient hedging strategies can be formulated; whereas if changes in futures prices drive changes in spot prices, efficient speculation strategies can be formulated. Further, causality can be used in forecasting commodity spot and futures prices. As majority of Indian investors are not aware of organized commodity market; their perception about is of risky to very risky investment. Many of them have wrong impression about commodity market in their minds. It makes them specious towards commodity market. Concerned authorities have to take initiative to make commodity trading process easy and simple. Along with Government efforts, NGO‟s should come forward to educate the people about commodity markets and to encourage them to invest in to it. There is no doubt that in near future commodity market will become Hot spot for Indian farmers rather than spot market. And producers, traders as well as consumers will be benefited from it. But for this to happen one has to take initiative to standardize and popularize the Commodity Market. Sehgal, Rajput, and Dua (2012) analyzed in their research study the destabilization effect which is a relationship of futures liquidity and spot market volatility by using Hedrick Prescott (HP) filter and unexpected variable (unexpected liquidity) on seven agricultural commodities. As per the results of the study, in case of Guarseed, Turmeric, Soybean, Maize and Castor Seed the study confirmed that Futures market liquidity (based on trading volume) tends to drive spot market volatility i.e. stating destabilizing effect. As futures and spot markets are interlinked, any information shock should affect both the markets. Results of the lead lag relationship between spot price volatility and futures trading activity (unexpected) suggested that in most of the commodities the unexpected futures trading volume causes spot price volatility confirmed by Granger causality test. In case of Black pepper reversed destabilization effect was observed because of strong speculative interest in the market and lack of transparency. In case of Barley the study confirmed that Futures market liquidity (based on trading volume) does not affect spot market volatility. Malyadri G. Dr. and Kumar Sudheer B. (2012) studied the history of commodity market. Commodity derivatives arrived in India as early as 1875, barely about decade after they arrived in Chicago. The 1342

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commodity market in India has experienced an unprecedented boom in terms of the number of modern exchanges, the number of commodities allowed for derivative trading as well as the values of futures trading in commodities. However, there are several impediments to be overcome and issues to be settled for a sustained development of the market. Agnihotri and Sharma (2011) studied the degree to which commodity spot prices have converged with future market with a view to measure this convergence, and to find out arbitrage opportunity in MCX, and NCDEX, the correlation, regression, and standard deviation was used for the period of five years from 2005 to 2010. The results indicated that correlation coefficients themselves are not capable of detecting convergence and that the regression – linear tests was more powerful detecting any convergence between the future and spot prices of Zeera, Zink, Chana, and natural gas. It was observed that there is a need of another commodity exchange to overcome many functional inadequacies of the existing three national online commodity exchanges, particularly with respect to delivery-based settlement as a mechanism of efficient price discovery as MCX and NCDEX do not trade in all the commodities and hence do not provide opportunity for arbitrage. There is a clear delinking of futures prices of commodities traded at these exchanges and the prevailing spot prices, thereby leaving arbitrage opportunities, because of which actual hedgers do not find these exchanges useful for managing their commodity price risks. Some commodities such as iron ore and coal, wherein India is a large producer, consumer, importer and exporter are not traded at these exchanges. Third, unlike the existing exchanges, which hardly promote delivery-based trading, the new exchange should aim to integrate warehouse delivery by providing an online trading platform so that it becomes a true platform for delivery-based hedging. All this has potential to improve India’s share in international trade substantially. The new exchange will provide not only arbitrage opportunity but also attract more investors. Dharmbeer and Singh Barinder (2011) emphasized the theoretical and empirical research on the growth and prospects of emerging commodity markets and the resulting implication on policy and regulation. They found from the previous studies that derivatives markets have supported the hedging role of emerging derivatives markets. All commodities are globally traded and the global demand-supply situation is widely known and available to anyone who reaches out for it. The commodity markets are nowhere as volatile as stock futures. Since commodity exchanges promote price transparency, he refuses to buy the story that commodity exchange fuel inflation. The scope of the study revolves around the parties like Govt. & Regulatory bodies, intermediaries, investors, trading exchanges and other researchers. Agricultural commodities depend on rain fall, weather conditions, seasons and government support in terms of subsidies and minimum support price extended by Government to help the farmers. There is a much scope for researchers to find out the linkage between pricing behavior of future contracts and nature of agricultural commodities traded on national level commodity exchanges. There is also a scope related to analyzing the impact on working and efficiency of commodity exchanges after the merger of FMC with SEBI.

Growth of Traded Commodities at All National Commodity Exchanges and Share of All National Commodity Exchanges to Total Value Traded From 2004-14 The year 2003 was a watershed in the history of commodity futures market. The group of 54 prohibited commodities was opened up for forward trading, along with establishment and recognition of three new national exchanges with on-line trading and professional management in the year 2003. Not only 1343

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prohibition on forward trading was completely withdrawn, including in sensitive commodities such as wheat, rice, sugar and pulses which earlier committees had reservations about, the establishment of new exchanges brought capital, technology and innovation to the market. Futures contracts are available for major agricultural commodities, metals and energy. Commodity group-wise value of trading since 2004-05 is given below in the table. During the year 2013-14, forward trading in 113 commodities, was regulated at the 6 National Exchanges, viz. Multi Commodity Exchange, Mumbai; National Commodity and Derivatives Exchange, Mumbai, National Multi Commodity Exchange, Ahmedabad, Indian Commodity Exchange, Gurgaon, and ACE Derivatives & Commodity Exchange Limited (ACE). Besides, there were 11 regional exchanges recognized for regulating trading in various commodities approved by the Commission under the Forward Contracts (Regulation) Act, 1952. The total value of trade in agricultural commodities at all the exchanges during the year was 16.02 lakh crore as against 21.56 lakh crore in 2012-13 indicates a decline of 21.7% over the year. During 2013-14, NCDEX accounted for 11.30% of the total value of trade in the commodity market. It is clearly shown in the above graph that MCX contributed major share 84.89% in terms of value in the total value traded across at commodity exchanges in the year 2013-14 and NCDEX accounted 11.30% during the year.

Challenges and Benefits Commodity exchange is a platform for trading of agri and non agri commodities and providing a transparent price discovery to all the investors. Though it is beneficial for the participants, but commodity exchanges are also facing following challenges: 1. Lack of Knowledge About Commodity Futures Trading: Investors are finding commodity markets as an investment option where they can hedge their risk like farmers can hedge physical positions of their crops but they don’t have proper knowledge about commodity futures trading. This is one of the disadvantages of commodity market otherwise more participation of the investors can be seen. Table 1. Commodity group-wise value of trade (Rs. Lakh Crores) Commodity Groups

2004-05

2005-06

2006-07

2007-08

2008-09

2009-10

2010-11

2011-12

2012-13

2013-14

Bullion and other metals

1.80 (31.47)

7.79 (36.15)

21.29 (57.90)

26.24 (64.55)

44.00 (67.14)

49.66 (63.97)

81.82 (68.47)

130.79 (72.00)

111.23 (65.00)

60.07 (60.00)

Agriculture

3.90 (68.18)

11.92 (55.31)

13.17 (35.82)

9.41 (23.15)

6.64 (10.13)

12.18 (15.69)

14.56 (12.19)

21.96 (12.00)

21.56 (13.00)

16.02 (16.00)

Energy

0.02 (0.35)

1.82 (8.45)

2.31 (6.28)

5.00 (12.30)

14.89 (22.73

15.78 (20.34)

23.11 (19.34)

28.51 (16.00)

37.68 (22.00)

24.72 (24.00)

Others

0.00 (0.00)

0.02 (0.09)

0.001 (0.00)

0.00 (0.00)

0.00 (0.00)

0.00 (0.00)

0.00 (0.00)

0.000 (0.00)

(0.00) (0.00)

(0.00) (0.00)

Total

5.72 (100.00)

21.55 (100.00)

36.77 (100.00)

40.65 (100.00)

65.53 (100.00)

77.62 (100.00)

119.49 (100.00)

181.26 (100.00)

170.47 (100.00)

100.81 (100.00)

Source: FMC Annual Report from 2004 to 2014. Note: Figures in parenthesis indicate percentage to total value.

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Figure 2. Percentage of commodity exchange to the value traded during 2013-14 Source: FMC Annual Report 2013-14. Note: Annual Report of FMC 2014-15 is not available.

Figure 3. Challenges of commodity futures market

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2. Price Volatility: People do futures trading on commodity exchanges to minimize their risk from the price fluctuations but as we know that no one can predict the future. Hence they incur loss sometimes. 3. Hurdles in Clearing, Settlement, and Delivery: The traders have to give intention to the exchange for taking/giving delivery for the commodities before expiry of a futures contract. In this context, they should know about warehouse clearing and settlement of commodities in physical form otherwise they face hurdles in this. 4. Severe Competition: Everyone has to face severe competition in this cut throat competition. There are regional and commodity exchanges in the market but existence of local commodity players can not be avoided in terms of brokerage and delivery charges. 5. Surveillances Problems: Monitoring of commodity futures market is necessary to avoid frauds such as scam of National Spot Exchange Ltd. in 2014-15. After this scam, the regulatory authority of commodity market Forward Markets Commission (FMC) has been merged with Securities Exchange Board of India (SEBI) on 28th Sep. 2015. So the surveillance problems faced by the participants in commodity derivatives market are one of the main issues. 6. Difficulties in Predicting Future Market Trends: No one can predict trends of futures market even though futures trading is based on technical and fundamental analysis but they also provides the support and resistance levels for trading in volatile futures market. 7. Lack of Technical Expertise: Experience is required to predict the trends of futures market. Technical expertise should be there to deal with high volumes of trading on the basis of market knowledge which is a lacuna and due to this; most of the investors don’t get benefit from trading in commodity market. 8. Margin Money Requirements: Risk management is very important aspect of trading in futures market. Margin money is required for this purpose and it is fixed by the exchange for every traded commodity. A special margin is imposed by the exchange in case of volatility. So the investors and traders have to pay additional margin money in this case. 9. Price Discovery: Based on inputs regarding specific market information, the demand and supply equilibrium, weather forecasts, expert views and comments, inflation rates, Government policies, market dynamics, hopes and fears, buyers and sellers conduct trading at futures exchanges. This transforms in to continuous price discovery mechanism. The execution of trade between buyers and sellers leads to assessment of fair value of a particular commodity that is immediately disseminated on the trading terminal. 10. Price Risk Management: Hedging is the most common method of price risk management. It is strategy of offering price risk that is inherent in spot market by taking an equal but opposite position in the futures market. Futures markets are used as a mode by hedgers to protect their business from adverse price change. This could dent the profitability of their business. Hedging benefits who are involved in trading of commodities like farmers, processors, merchandisers, manufacturers, exporters, importers etc. 11. Import- Export Competitiveness: The exporters can hedge their price risk and improve their competitiveness by making use of futures market. A majority of traders which are involved in physical trade internationally intend to buy forwards. The purchases made from the physical market might expose them to the risk of price risk resulting to losses. The existence of futures market would allow the exporters to hedge their proposed purchase by temporarily substituting for actual

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purchase till the time is ripe to buy in physical market. In the absence of futures market it will be meticulous, time consuming and costly physical transactions. 12. Predictable Pricing: The demand for certain commodities is highly price elastic. The manufacturers have to ensure that the prices should be stable in order to protect their market share with the free entry of imports. Futures contracts will enable predictability in domestic prices. The manufacturers can, as a result, smooth out the influence of changes in their input prices very easily. With no futures market, the manufacturer can be caught between severe short-term price movements of oils and necessity to maintain price stability, which could only be possible through sufficient financial reserves that could otherwise be utilized for making other profitable investments. 13. Benefits for Farmers/Agriculturalists: Price instability has a direct bearing on farmers in the absence of futures market. India is traditionally an agricultural economy and fluctuation in prices during the harvesting period has always been a major concern for the farming community. Futures trading have emerged as a viable option for providing a greater degree of assurance on the price front. For instance, a farmer growing soybean is exposed to risk of fall in prices when his harvest comes out. Using futures market, he can sell the soybean contract today at the futures platform and lock in the price which could eliminate his risk from price fluctuations. Further, farmers sometimes go for distress selling during the harvest time due to lack of storage facilities. Using the futures platform, farmers can store their produce in the exchange designated warehouse till the time their produce fetches reasonable returns. 14. Credit Accessibility: The absence of proper risk management tools would attract the marketing and processing of commodities to high-risk exposure making it risky business activity to fund. Even a small movement in prices can eat up a huge proportion of capital owned by traders, at times making it virtually impossible to pay back the loan. There is a high degree of reluctance among banks to fund commodity traders, especially those who do not manage price risks. If in case they do, the interest rate is likely to be high and terms and conditions very stringent. These possess a huge obstacle in the smooth functioning and competition of commodities market. Hedging, which is possible through futures markets, would cut down the discount rate in commodity lending. 15. Improved Product Quality: The existence of warehouses for facilitating delivery with grading facilities along with other related benefits provides a very strong reason to upgrade and enhance the quality of the commodity to grade that is acceptable by the exchange. It ensures uniform standardization of commodity trade, including the terms of quality standard: the quality certificates that are issued by the exchange-certified warehouses have the potential to become the norm for physical trade. Commodities have become an established asset class in the Indian markets in the past few years. While a future trading is relatively new to the Indian commodity markets, the global commodity futures exchanges have been functioning for several decades. What has attracted investors to trading in commodity futures is the transparency in the price mechanism, low margins, risk management, benefits to farmers by way of price clarity and an organized marketplace. Other than these, commodities also offer a different investment avenue, are less volatile when compared with equities and bonds, are a highly liquid asset class and offer investors an opportunity to gain from the price movements in the commodity space. 1347

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Figure 4. Benefits of commodity futures market

Marketing Mix The government intervened at every stage of the marketing of major agricultural commodities during last three decades. In order to protect farmers from risks and to maintain price stability, every activity of marketing of essential commodities such as procurement, distribution control and administrated price mechanism is under Government control. Government regulation has declined after implementation economic reforms in 1991. Agriculture sector in India has always been a major field of government intervention since long back. Government tries to protect the interests of the poor Indian farmers by procuring crops at remunerative prices directly from the farmers without involving middlemen in between. This way Government maintains sufficient buffer stocks and at the same time provides the farmers safeguard against the fluctuating food crop prices. But government at the same time has restricted this traditional sector by fixing prices of crops at a particular level and also by imposing several other restrictions on export and import of agricultural commodities.

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Agricultural marketing is mainly the buying and selling of agricultural products. In earlier days when the village economy was more or less self-sufficient the marketing of agricultural products presented no difficulty as the farmer sold his produce to the consumer on a cash or barter basis. Today’s agricultural marketing has to undergo a series of exchanges or transfers from one person to another before it reaches the consumer. There are three marketing functions involved in this, i.e., assembling, preparation for consumption and distribution. It is done under the Agricultural Produce (grading and marketing) Act of 1937. In India, there are several central government organizations, who are involved in agricultural marketing like, Commission of Agricultural Costs and Prices, Food Corporation of India, Cotton Corporation of India, Jute Corporation of India, etc. Marketing Mix involves the decisions regarding product, place, price, promotion, people, process, and physical evidence.

Product It is related to the design of the services offered to a customer according to the need as well as demand. Indian economy is based on agriculture. Farmers produce different agricultural products like cereals, pulses, spices etc. These are traded at commodity exchanges as well. The products or agricultural commodities traded at National Exchanges comprise the following: • • • • • • •

Edible Oilseeds Complexes: Mustard seed, Cottonseed, Soybean oil etc. Food Grains: Wheat, Bajra, Maize etc. Metals: Gold, Silver, Copper, Zinc etc. Spices: Turmeric, Pepper, Jeera etc. Pulses: Channa. Fibres: Cotton, Jute etc. Others: Sugar, Gur, Rubber, Potato, Natural Gas, Crude Oil etc.

Place It is related to the location for offering agricultural products. This involves all the regional and national commodity exchanges. Online and offline trading of agricultural commodities are done at these exchanges. Currently 4 national exchanges are working in India and rests are regional commodity exchanges. • • • •

Multi Commodity Exchange, Mumbai (MCX). National Commodity and Derivatives Exchange, Mumbai (NCDEX). National Multi Commodity Exchange, Ahmedabad (NMCE). Indian Commodity Exchange Ltd., Mumbai (ICEX).

Price It is related to the price charged for trading of listed agricultural products offered by the commodity exchanges. Such as brokerage, commodity transaction tax, delivery chargers, warehousing charges etc Brokerage is decided by the broking firms but all other charges are decided by the regulatory authority.

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Promotion It relates to the type of media to be chosen by the commodity exchanges to make customers aware about their products and services. It is necessary to take decisions about communication media channel, so as to bring out the salient features of the traded products. The promotion of the product can be done by advertising in media such as radio, newspaper, TV commercials to make customers aware.

People The target customers for all the regional and commodity exchanges are individuals, farmers, manufacturers, producers, and jewelers etc. who can invest in commodities.

Process It is related to the flow of activities, rules and regulations. All the major activities of regional and national commodity futures market are followed by regulatory authority. Earlier Forward Markets Commission (FMC) was the regulator of commodity futures market but it is merged with Securities Exchange Board of India (SEBI). Now SEBI will regulate the commodities future market from 28th Sep. 2015 to strengthen the rules and regulations and control the speculative practices. There has to be adherence to certain rules and regulations in trading commodities related to the standardization and customization. This involves commodity transaction tax, delivery charges, warehousing charges etc. Figure 5 gives a fair idea about working of the Commodity market.

Figure 5. Working of commodity futures market

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A commodity exchange is a market place like a stock market to buy and sell the listed and traded commodities. This market eliminates the need for middle men and allows the market to fix up a price that is driven by demand and supply of the particular commodity. Trading can be done in two ways:-cash/spot and futures market. The buyer and seller agree upon a common price of the commodity, and actual physical delivery of that commodity takes place in the cash/ spot market. Where as, Futures contract do not compulsory involve physical delivery of commodities. Delivery of commodities is fixed for a future date at a price agreed by both the parties but for this, buyer/ seller has to give intention before expiry of the futures contract to commodity exchange otherwise buyer or seller can close their positions by squaring off his buy/sell position. Squiring off is done by taking an opposite contract so that the net outstanding is nil. The broker maintains an account of all dealing parties in which the daily profit or loss due to changes in the futures price is recorded. For the purpose of delivery, a person deposits certain amount of say, good X in a warehouse and gets a warehouse receipt, which allows him to ask for physical delivery of the good from the warehouse. For commodity futures to work, the seller should be able to deposit the commodity at warehouse nearest to him and collect the warehouse receipt. The buyer should be able to take physical delivery at a location of his choice on presenting the warehouse receipt. But at present in India very few warehouses provide delivery for specific commodities. As spot prices are determined by supply and demand, they are very sensitive to various types of uncontrollable forces that affect commodity production. Bad weather conditions, political turmoil, government intervention, and changing consumer preferences are some of the factors that may contribute to a constantly fluctuating and unpredictable commodities market. To counter this unpredictability, buyers and sellers created the futures contract. A futures contract is simply an agreement made that will take place some time in the future. These agreements between buyers and sellers include the date the commodity will be delivered, the price to be paid on a specific date, and the quantity and quality of the commodity. A ten percent margin deposit is required of both buyers and sellers to insure that neither of the participants backs out of the contract. Trading in the spot exchanges is being done in the following ways: • • • • •

Farmer/Seller bring his goods to the warehouse. The stocks are assayed – Quality checked and the goods weighed. If the quality is validated, the warehouse receipt is issued. The seller goes to the designated Spot Exchange member with the receipt and a limit is opened for the quantity to be traded on the Exchange. Once the transactions are completed at the mutually agreed price between buyer and seller, the delivery and settlement aspects are done as per rules of the Exchanges.

Physical Evidence Physical evidence is the material part of a service. There are many examples of physical evidence such as Financial Reports, Brochures, Furnishings, Business cards, Building, logo, punch lines, employee’s dress code, other tangible items etc. But here in case of commodity futures market, financial reports and services provided by the broking firms in terms of protecting interest of the investors are considered in physical evidence.

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Service Quality and Customer Satisfaction Service Quality means the quality of service delivered by the commodity exchanges and how far the clients of broking firms are satisfied with that. As quality is an intangible concept therefore, it’s very difficult to measure. It can be measured by calculating the difference in the expectation of the client from the service delivered by the broking firms and the perception of the clients about the service rendered by the broking firms. Service quality of a product depends upon the reliability, responsiveness, assurance and empathy. In a broking firm, services like daily buy & sell call, margin requirements, risk management of their clients by tracking their open positions are rendered by the brokers on daily basis. So, every broking firm makes sure about these services rendered by the brokers.

Customer Satisfaction Investors always expect maximum return from their investment. So they should have an idea about the preferences available in the commodity market as investing in commodity market is one of the modes of investment which is catching eyes of the investors now a days. For which, it is required by the broking firms to assist the investors and bring out the knowledge of various investment opportunities available in the commodity market such as arbitrage, hedging etc. Investors are trading on commodity exchanges in online as well as offline mode as per their convenience. But they want proper follow up of their margin money as well as open positions because when they buy or sell an underlying asset, the value of that underlying asset is deducted from the margin money and profit or loss is also get adjusted. So the investors should know about their amount of margin money deposited and daily updates about market movements by the brokers on time to minimize their price risk.

FUTURE RESEARCH DIRECTIONS There is a much scope for doing research related to the linkage between pricing behavior of future contracts and nature of agricultural commodities traded on national level commodity exchanges. Forward Markets Commission (FMC) had merged with Securities Exchange Board of India (SEBI) in the month of sep. 2015. Now SEBI is regulating the commodity futures market to strengthen and prevent from speculative practices. SEBI has to look at delivery of commodities from the warehouses as there is no physical settlement of stocks in cash market. This can also be the area for further research to find out the effect of followed rules and regulations of SEBI in commodity futures market after FMC.

CONCLUSION Commodity Futures market has occupied a very important place in Indian economy. Agricultural commodity futures are market-based instruments for managing risks and they help in orderly establishment of efficient agricultural markets. Future markets are used to hedge commodity price risks. They also serve as a low cost, highly efficient and transparent mechanism for discovering prices in the future by providing a forum for exchanging information about supply and demand conditions. The hedging and price discovery functions of future markets promote more efficient production, storage, marketing and 1352

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agro-processing operations and help in improvement in overall agricultural marketing performance. Although India has a long history of trade in commodity derivatives, this sector remained underdeveloped due to government intervention in many commodity markets to control prices. The commodities derivatives market has seen ups and downs, but seem to have finally arrived now. The market has made enormous progress in terms of technology, transparency and trading activity. Interestingly, this has happened only after the Government protection was removed from a number of commodities, and market forces were allowed to play their role.

REFERENCES Agnihotri, A., & Sharma, A. (2011). Study of Convergence of Spot and Future Prices in Commodity Market (With reference to Zeera, Chana, Zink and Natural Gas for 2005-2010). ZENITH International Journal of Multidisciplinary Research, 1(2), 101–113. Bansal, R., Dadhich, V. & Ahmad, N. (2014). Indian Commodity Market – A Performance Review. International Research Journal of Management and Commerce, 1(5), 19-34. Bhagwat, S., Maravi Singh, A., More, R. & Chand, D. (2015). Commodity Futures Market in India: Development, Regulation and Current Scenario. Journal of Business Management & Social Sciences Research, 4(2), 215-231. Chhajed, I., & Mehta, S. (2013). Market Behavior and Price Discovery in Indian Agriculture Commodity Market. International Journal of Scientific and Research Publications, 3(3), 1-4. Dash, M., Solanki, A., & Shobana, T. (2015). A Study on Commodity Market Behaviour, Price Discovery and Its Factors. Retrieved from http://ssrn.com/abstract=1988812 Dharmbeer & Singh Barinder. (2011). Indian Commodity Market: Growth and Prospects. International Journals of Multidisciplinary Research Academy, 1(2), 78-85. Dhole Suresh Sagar. (2014). Commodity Futures Market in India: The Legal Aspect and its Rationale. International Journal of Research in Management and Business Study, 1(2), 38-45. Essays. (2015). Commodity Futures in India the Prospectus and Challenges –Finance Essay. Essays. Retrieved December 31, 2015 from https://essays.pw/essay/commodity-futures-in-india-the-prospectsand-challenges-finance-essay-146089 Kumar, B., & Pandy, A. (2013). Market Efficiency in Indian Commodity Futures Markets. Journal of Indian Business Research, 5(2), 101–121. doi:10.1108/17554191311320773 Malyadri, G., & Kumar Sudheer, B. (2012). A Study on Commodity Market. International Journal of Computer Science and Management, 1(5). Rajamohan S., Vethamanikam Arul Hudson G. & Vijaykumar, C. (2014). Commodity Futures Market in India. International Journal of Advanced Research in Management and Social Science, 3(10), 5258. Sehgal, S., Rajput, N., & Dua, R.K. (2012). Futures Trading and Spot Market Volatility: Evidence from Indian Commodity Markets. Asian Journal of Finance & Accounting, 4(2).

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Testbook. (2015). Indian Banking Sector: Getting to Newer Horizons in 2015. Testbook. Retrieved December 28, 2015 from http://testbook.com/blog/indian-banking-sector-getting-newer-horizons-2015/ Wilson, R. (n.d.). Future and commodities market. Hedge Fund Blogger. Retrieved from: http://richardwilson.blogspot.in/2009/07/futures-and-commodities-market.html

ADDITIONAL READING Agriculture Market Report. (2015-16). Retrieved January 14, 2016 from http://agriexchange.apeda.gov.in Agritech Portal, T. N. A. U. Agricultural Marketing & Agri Business. Retrieved January 15, 2016 from http://agritech.tnau.ac.in/agricultural_marketing/agrimark_India.html Biswas Anirban. (2004, July 13). Agricultural Marketing in India. Retrieved January 08, 2016 from http://www.domain-b.com/economy/agriculture/20040713_marketing.html Department of Economic Affairs, Ministry of Finance, Government of India, New Delhi, (April, 2014), Report of the Committee to suggest steps for fulfilling the objectives of Price-discovery and Risk Management of Commodity Derivatives Market. How Does A Commodities Exchange Function? Which Are the Major Commodity Exchanges in India. Retrieved January 08, 2016 from http://www.smarterwithmoney.in/Trading/Commodity/Articles/How_ Does_A_Commodities_Exchange_Function_Which_Are_the_Major_Commodity_Exchanges_in_India Forward Markets Commission (n.d.) Retrieved from: www.fmc.gov.in NCDEX (n.d.) Retrieved from: www.ncdex.com Mathur Naveen. (2013, November 11). Benefits of Trading in Commodity Futures. Retrieved January 15, 2016 from http://articles.economictimes.indiatimes.com/2013-11-11/news/43929989_1_commodityfutures-commodity-space-commodity-traders Ministry of Consumer Affairs, Food and Public Distribution Department of Consumer Affairs (201314), Annual Report. Ministry of Consumer Affairs, Food and Public Distribution Department of Consumer Affairs (201213), Annual Report. Ministry of Consumer Affairs, Food and Public Distribution Department of Consumer Affairs (201112), Annual Report. Ministry of Consumer Affairs, Food and Public Distribution Department of Consumer Affairs (201011), Annual Report. Ministry of Consumer Affairs, Food and Public Distribution Department of Consumer Affairs (200910), Annual Report. Ministry of Consumer Affairs, Food and Public Distribution Department of Consumer Affairs (200809), Annual Report.

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Singhal, K. Praveen (2015, March 24). Manage Commodity Price Risk via Derivative Exchanges Retrieved January 14, 2016 from http://www.dnaindia.com/money/column-manage-commodity-price-riskvia-derivative-exchanges-2071404 United Nations Conference on Trade and Development (Feb.2013), Recent developments and new challenges in commodity markets, and policy options for commodity-based inclusive growth and sustainable development.

KEY TERMS AND DEFINITIONS Arbitrage: It means the simultaneous buying and selling of securities, currency, or commodities in different markets or in derivative forms in order to take advantage of differing prices for the same asset. Derivatives: These are financial contracts, which derive their value from an underlying asset. (Underlying assets can be equity, commodity, foreign exchange, interest rates, real estate or any other asset.) Four types of derivatives are trades forward, futures, options and swaps. Derivatives can be traded either in an exchange or over the counter. Exchange: Central market place for buyers and sellers. Standardized contracts ensure that the prices mean the same to everyone in the market. The prices in an exchange are determined in the form of a continuous auction by members who are acting on behalf of their clients, companies or themselves. Futures Contract: It is an agreement between two parties to buy or sell a specified and standardized quantity and quality of an asset at certain time in the future at price agreed upon at the time of entering in to contract on the futures exchange. It is entered on centralized trading platform of exchange. It is standardized in terms of quantity as specified by exchange. Contract price of futures contract is transparent as it is available on centralized trading screen of the exchange. Here valuation of Mark-to-Mark position is calculated as per the official closing price on daily basis and MTM margin requirement exists. Futures contract is more liquid as it is traded on the exchange. In futures contracts the clearing-house becomes the counter party to each transaction, which is called novation. Therefore, counter party risk is almost eliminated. A regulatory authority and the exchange regulate futures contract. Futures contract is generally cash settled but option of physical settlement is available. Delivery tendered in case of futures contract should be of standard quantity and quality as specified by the exchange. Futures Market: It facilitates buying and selling of standardized contractual agreements (for future delivery) of underlying asset as the specific commodity and not the physical commodity itself. The formulation of futures contract is very specific regarding the quality of the commodity, the quantity to be delivered and date for delivery. However it does not involve immediate transfer of ownership of commodity, unless resulting in delivery. Thus, in futures markets, commodities can be bought or sold irrespective of whether one has possession of the underlying commodity or not. The futures market trade in futures contracts primarily for the purpose of risk management that is hedging on commodity stocks or forward buyers and sellers. Most of these contracts are squared off before maturity and rarely end in deliveries. Hedging: Means taking a position in futures market that is opposite to position in the physical market with the objective of reducing or limiting risk associated with price.

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Margin Money: Cash or equivalent posted as guarantee of fulfillment of a futures contract (not a down payment). Mark to Market: The practice of crediting or debating a trader’s account based on daily closing prices of the futures contracts he is long or short. Spot Market: Here commodities are physically bought or sold on a negotiated basis. Spot Price: The price at which the spot or cash commodity is selling on the cash or spot market.

This research was previously published in Strategic Marketing Management and Tactics in the Service Industry edited by Tulika Sood , pages 185-212, copyright year 2017 by Business Science Reference (an imprint of IGI Global).

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APPENDIX: ABBREVIATIONS FMC: Forward Markets Commission FCRA: Forward Contracts (Regulation) Act SEBI: Securities Exchange Board of India APMC: Agriculture Produce Marketing Committees NCDEX: National Commodity & Derivatives Exchange MCX: Multi Commodity Exchange NMCEIL: National Multi Commodity Exchange of India Ltd. ICEX: Indian Commodity Exchange Ltd. ACE: Ace Derivatives and Commodity Exchange Ltd. UCX: Universal Commodity Exchange Ltd.

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An Analysis of Mobile Phone Use in Nigerian Agricultural Development Osadebamwen Anthony Ogbeide Agribusiness Services, Australia Ideba Ele University of Calabar, Nigeria

ABSTRACT This study used 328 smallholder farmer respondents to investigate its objectives of how farmers use mobile phone technology, what benefits they have gained from the use, and the constraints encountered during the process. The quantitative data collected through a process of questionnaire administration were analysed using Stata 12 software. The results indicate that mobile phone usage for farm and other social purposes has increased with farmers. The farmers also spend almost 40% of their phone bills on farm-related activities and that seeking market information represented 17.32% of the total phone bill in a month. Increased efficiency in input delivery, market access, and output distribution were reported as some of the advantages of using mobile phones. This study was conducted in a region where its general characteristics may not reflect that of the entire country thus generalisation of the study may be limited, so the data should be cautiously use.

INTRODUCTION Sub-Saharan Africa’s rural economy remains agriculture dependent relative to other regions and it employed 62% of the population in 2005 (Staatz & Dembele, 2007). In Nigeria, agriculture employed 70% of the work force and accounted for more than 40% of the Gross Domestic Product (USAID, 2013). It is mainly characterised by subsistent farming. The efforts at developing agriculture in Nigeria have taken many approaches such as rural development strategies which included formation of cooperative organisations, provision of access to credit and technical information, and others (Ogbeide, 2014). DOI: 10.4018/978-1-5225-9621-9.ch061

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 An Analysis of Mobile Phone Use in Nigerian Agricultural Development

The process of actualising rural development has led to the adoption of mobile phone technology as a farming tool for contact and business transactions. This study investigates how much the farmers have taken advantage of this technology and the benefits derived from it. In considering these objectives, the study is to provide answers to such questions as: (1) do farmers practically use mobile phone for agricultural purposes in Nigeria? (2) does mobile phone usage drive improvement in productivity? (3) what benefits do the farmers derive using mobile phone? This study is important as it will help to capture and evaluate the progress of mobile phone adoption and uses and also identify, assess, and judge the benefits the smallholder farmers obtain with the device. It is critical that the success and use of this device be studied for improvement and adaptation purposes. The background to the study approach was to explore the three main interdependent players: the provider of inputs, the converter of inputs, and the users of the output and the relationships that exist among them. An understanding of the relationship amongst these players will help to show how important mobile phone is in the order. The providers of inputs in agriculture are diverse and often time distantly located away from the converters. Farm input providers such as financial institutions, agribusiness/farm management organisations, technical services, chemical and planting materials suppliers, and donor agencies are often situated in the cities or local government headquarters (Karamagi & Nalumansi, 2009). The physical distance between the input providers and the users creates a gap in access and communication. The input converters are the farmers. Farmers particularly in Nigeria are mainly small-scaled with limited contacts to exchange and share crucial information, knowledge and skills needed for production, processing and marketing (Alleman et al., 2002; FAO, 2005). Consequently, yields are low, and incomes from agriculture leave little for the farmer to turn over. Access to crucial inputs is poor or denied due to difficulty in information flow either from the provider of inputs or the users of output (FAO, 2005). The users of outputs include manufacturers that represent the secondary inputs providers and the final consumers of farm produce. The users of agricultural outputs in like manner to the input converters are most times geographically located far away from the farmers. The road network is poor and the distance from the farm to the market towns and other service providers is very long. The result of these slack relationships is high production cost, inefficiency, non-competitiveness, and corruption (Sebastian, 2008; Dorosh, 2009; WDI, 2010; Livingston et al., 2011). For example, fertilizer distribution to farmers in Nigeria was hijacked by middle men with no farming interest who either divert them to un-intended markets or resell to the farmers at exorbitant prices (Allafrica, 2013). The diversion results in farmers not receiving the fertilizer at all or on time, and in most cases at a higher price. The delay in getting the inputs, the corruption in the process, and the increase in cost creates inefficiency in the supply chain and causes production to be uncompetitive (Chorn, Sisco, & Pruzan-Jorgensen, 2010; Livingston et al., 2011).

LITERATURE REVIEW This study assumes readers have prior knowledge of the underlying theory of diffusion of innovation that defined how innovation is adopted by a social group with the result that the innovation becomes part of the existing social system. Adoption of a new technology does not happen instantaneously in a social system; instead, it is a process whereby some individuals are quicker to adopt the technology than others. However, innovation must have the capacity to improve and create better social economic 1359

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conditions for the adopters while leveraging on ability of the target group to apply it from an assumed or learned standpoint (Robinson, 2009).

Mobile Phone and Agriculture Improving efficiency in agriculture production processes is important to increasing productivity and reducing poverty. Creating a more efficient value chain involves productive engagement of the members of the chain and how information around these members is managed. One of the ways to improve efficiency in the agriculture is the use of mobile phone technology (Halewood & Surya, 2012). Mobile phone technology application in diverse agribusiness situations has recorded growth in Nigeria and many other developing countries; it provides different opportunities to transfer knowledge and information among players in the agribusiness value or supply chain, including government. Despite mobile phone being mainly used by urban residence, Aker and Mbiti (2010) found its social and economic usefulness for the rural populace in terms of information gathering on weather, market, and other related issues. The Syngenta Foundation (2011) reported adaptation of mobile phone technology for agricultural purpose has been boosted as manufacturers and software designers had either aligned their products to suit agricultural use or created specific products for agricultural use. For example, in Nigeria Nokia has focused since 2010 on providing mobile learning (mLearning) applications for the transfer of production skills in crops and livestock management, and fisheries using state-of-the-art technologies. Additionally, national governments have worked assiduously towards comprehensive internet platforms extended on mobile phone to provide farmers access to all relevant information (Syngenta Foundation, 2011). According to Qiang, Kuek, Dymond, and Esselaar (2011), and Martin and Abbott (2011), mobile phone applications usage in Nigeria has increased tremendously. The potential benefits to farmers is diverse, aiding connection and communication with different stakeholders in agricultural value chain.

Mobile Phone as an Important Tool in Nigeria Agriculture According to Livingston et al. (2011), more than one third of all Sub-Saharan rural Africans are so geographically and economically isolated from market towns that, at present, they are virtually condemned to a life of subsistence agriculture, regardless of their access to modern inputs, irrigation infrastructure or financial services. A spatial analysis of 5,000 people indicated 34% of the rural population in SubSaharan Africa live more than five hours from a market town (Sebastian, 2008). While Livingston et al. (2011) argued that the high price of road transport in Sub-Saharan Africa countries is widespread and that the high price of agricultural products has been attributed to the poor state of the transportation network, and inefficient logistics and endemic corruption. The density of Nigeria’s road network is low for agricultural purpose usually bush path or unsealed and with access difficulty. According to Tunde and Adeniyi (2012), and Ajiboye and Afolayan (2009), road transport despite its very poor state is the most readily available means of movement of goods and passenger traffic over short, medium, and long distances. Nigerian agriculture as the engine of economic growth runs below its potential because inputs, be they financial, agronomic or technical, are, all too often, not being delivered in a timely manner by the donor institutions, ministries of agriculture, the project implementation units, the banks or the agricultural cooperatives. This has had an extremely negative impact on productivity and decreased revenues of smallholder farmers. Therefore, successful 1360

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agricultural campaigns are all about planning and timing and rigorous project management, without which the farmers will not gain the full benefits of the new proffered solutions (FAO, 2009; Livingston et al., 2011; Inoncencio et al., 2007; World Bank, 2009).

Mobile Phone Innovation and Its Agricultural Usage The theory of diffusion of innovations is central to the adoption, use, and the attendant benefits of mobile phone application to agriculture particularly by smallholders (Martin & Abbott, 2011). Robinson (2009) noted that when an innovation is introduced into any settings, it offers three valuable intuitions into the process of social change. Such intuitions include what are the quality attributes in the innovation that will make it to spread, understanding the needs of the different user groups and the role played by peer networks in ensuring the spread of adoption of the technology. According to Avgerou (2010), understanding the use of mobile phones to aid agricultural development requires an adequate knowledge of the technology and the perceived impacts it possesses, as well as an assessment of the opportunities and barriers reinforced by the local social structure of the user communities. Aker and Mbiti (2010) and Aminuzzaman, et al. (2003) noted that mobile phone adoption by farmers is predicated on the perception that it is better than most other communication means, as it is convenient to handle, provides economic advantages, and enhances social status of users. The use of mobile phone rests within the core value of communities communicating within and between groups members for social or economic interactions. It enhances communication experiences by removing the cumbersomeness associated with other communication methods (Qiang, Kuek, Dymond, & Esselaar, 2011; Martin & Abbott, 2011). This perceived relative advantage of mobile phone arguably increases the rate of growth of mobile phone ownership among community members and farmers in particular.

Benefits of the Mobile Phone Agriculture as a business or at least as a means of earning income involves many interactions which can include hiring labour, gathering market and price intelligence, procurement of farm inputs, seeking technical assistance from the extension or expert agents, or obtaining weather information (Okello et al., 2012). However, the location of the parties in the interaction, travel distances, and ineffective and costly transportation all inhibit the ability of the farmers to improve productivity and improve the family and community wellbeing (Okello et al., 2012; GSMA, 2013). Important to these interactions is the need for them to be done in a manner that is timely, effective, and efficient. Farmers must adopt a means by which they are able to gain access to required information and inputs at the appropriate time in a cost-effective manner. According to FARM-Africa (2007) and Martin and Abbott (2011), the mobile phone is a handy tool for identification and management of livestock diseases, and for coordinating greater attendance and participation in organisations’ meetings. Karamagi and Nalumansi (2009) noted that in Central Uganda, farmers adopting the use of mobile phones were able to connect to FoodNet – a service that supplies current price information on agricultural commodities, as well as contact details for interested buyers via short message service (SMS). Mobile phones have been found to help improve the productivity of individuals and organizations within resource-constrained environments as it increases efficiency, effectiveness, and reach (Burrell, 2008; Qiang, Kuek, Dymond, & Esselaar, 2011; Hudson, 2006). The rapid uptake and popularity of 1361

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mobile phone applications by rural farmers have led to the development of unique and innovative approaches to using these applications in solving some salient issues faced by farmers. Several studies have revealed some innovative examples; it has been reported that farmers use mobile phones to coordinate access to agricultural inputs (Martin & Abbott, 2011; Ansari & Pandey, 2013; Syngenta Foundation, 2011; Das, Basu & Goswami, 2012); accessing market information (Odhiambo, 2014; Das, Basu, & Goswami, 2012; Martin & Abbott, 2011); for financial transactions (Qiang, Kuek, Dymond, & Esselaar, 2011; Martin & Abbott, 2011; Kirui, Okello, & Nyikal, 2010); and to seek agriculture emergency assistance and expert advice (Qiang, Kuek, Dymond, & Esselaar, 2011; Martin & Abbott, 2011; Churi, Mlozi1, Tumbo, & Casmir, 2012). Mobile phones assist in mining information. According to Wyche and Steinfield (2015), efficient market information provision has positive benefits for farmers, traders, and policymakers. Current and updated market information is more easily obtained and enables farmers to negotiate with traders from a position of strength. It also facilitates spatial distribution of products from rural areas to urban areas and between urban markets by sending clear price signals from urban consumers to rural producers regarding quantities and varieties required. Studies have been conducted on ways and which system applications best suit the rural dwellers for social and business communication. Martin and Abbott (2011), Okello et al. (2012), and GSMA (2013) argued that the mobile phone is best suited for rural people including the farmers. Interactions with mobile phones are cost effective ways for smallholder farmers to stay connected with other stakeholders while the phone itself provides them with a sense of security and social status. Other studies have also analysed mobile phone to be a beneficial product whose access can be limited to socially excluded community members, and as a hazardous consumption (Moisio 2003; Chigona, Beukes, Vally, & Tanner, 2009). Moisio (2003) argued that the perceived negative consequences of mobile phone as a hazardous consumption is not a reflection of the properties of technology, but rather the ways in which it was consumed. While mobile phones may foster negative experiences on health, crime, and physical interaction, they merely do so in a set of categories of thought and practice that enable or disable particular consumption practices and their experiences. However, inequality among the farmers can hinder the use of mobile phone. Chigona, Beukes, Vally, and Tanner (2009) noted that for the socially excluded people in a community, the use of mobile technology may still be limited because the majority of people in that category cannot access or afford it (Chigona, Beukes, Vally, & Tanner, 2009).

Factors That Influence Mobile Phone Technology Application by Smallholder Farmers In the review of the relevant literature, a number of factors were noted to affect the use the mobile phone by farmers for both social and agriculture related purposes. Mobile phone ownership in developing countries is still low despite the increase in the past several years. However, gender plays a role in mobile phone ownership and use. In short, a woman is still 21% less likely to own a mobile phone than a man and this figure increases to 23% if she lives in Africa (GSMA, 2013). Closing this gender gap would bring the benefits of mobile phones to an additional 300 million women, and by extending the benefits of mobile phone ownership to more women a host of social and economic goals can be advanced (GSMA, 2013). According to Okello, Kirui, Njirani, and Gitonga (2012), young persons are more servile with technology irrespective of their locality and therefore have a positive correlation with the use of the mobile phone. Therefore, it is expected that young farmers will be inclined to use this technology for most of 1362

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the day-to-day transactions. Kirui et al. (2010) noted the education level of smallholder farmers was low and had thus created challenges to adoption and use of modern technology such as mobile phones. The work of Kirui et al. (2010) corroborated that of Okello et al. (2009) which suggested the literacy level of the farmers was important to the use of mobile phones for information access and can also impact their level of difficulty in navigating through the phone menus, often written in international languages like English. Therefore, the level of literacy and social inclusion of farmers had affected mobile phone use differently (Chigona, Beukes, Vally, & Tanner, 2009) and can influence the level of adoption across the various Nigerian communities. The high usage of mobile phone by adopter farmers buttressed its capability to act as a tool for education and gaining knowledge as well as spreading viewpoints and communication with family members and the larger social community (Okello et al., 2012).

CONCEPTUALISATION OF THE MOBILE PHONE ENVIRONMENT FOR THE STUDY The essence of adopting an innovation such as mobile phone technology applications for agricultural purposes hinges on its ability to transform an existing way of doing things into a better and more efficient one. The ultimate result is to provide increased and quality output to the market, guaranteed income for farmers and a dynamic and prosperous community (see Figure 1). The mobile phone use by farmers is well-known as an exemplary case of a technology enabling bottom-up empowerment through information access, driven by agribusiness and end-user innovation (GSMA, 2013; Sherry, n.d.). The major mobile phone functionalities applicable are the voice call, SMS,

Figure 1. Mobile phone application environment in agriculture

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multimedia service (MMS), and the internet. The use of these functionalities is impacted by users’ level of literacy generally and the specific knowledge of the technology available to the consumers. The farmers often originate communication, but are generally in the middle of the communication chain transforming the information and inputs they source into products for the market. In this model, the inputs environment relates to where farmers and secondary producers are able to access inputs critical to production. Inputs such as weather information, insurance, localised geospatial and real time information, technical knowledge, and stock and machineries are not only required but must be acquired in a quick, easy, and inexpensive manner (Szilagyi & Herdon, 2006; Lio & ChunLiu, 2006). This creates efficiency leading to decreased cost of doing business, improved revenue and better market knowledge. The farmers apply the inputs obtained from the different input providers and transform them into output. With the mobile phone, farmers and other stakeholders in the value chain can make a call or send SMS or MMS to each other. In this regard, inputs and outputs information are obtained faster with little or no travel time involved (Qiang, Kuek, Dymond, & Esselaar, 2011; Martin & Abbott, 2011). Farmers are able to convert the inputs on time; plant the seeds at the right time, get weather warnings before disaster happens and are able to communicate to the technical expert of any anomalies observed in their farms for quick intervention. Market information obtained on time helps the farmers to determine the cropping pattern, estimate inputs price, plan what to sell and at what price (Qiang, Kuek, Dymond, & Esselaar, 2011). Obtaining and utilising inputs at the appropriate time is crucial to the success of any enterprise, particularly the ones that can be influenced adversely by weather. Mobile phone enables farmers to obtain quickly information that impacts on inputs transformation, thus causing them to act on time. The result is that all things being equal, maximum and quality yield can be reasonably guaranteed. The farmer can take advantage of the best market price leading to increased income, better social and community life (Odhiambo, 2014; Das, Basu, & Goswami, 2012; Ansari & Pandey, 2013).

METHODOLOGY The study involved a quantitative analysis of data collected through a process of questionnaire administration that yielded 328 smallholder farmer respondents. The study was conducted in the Cross River State of Nigeria which politically has 18 Local Government Areas (LGAs). Agriculturally, the Cross River State is divided into three zones: the Calabar, the Ikom, and the Ogoja. A multi-stage sampling procedure was adopted to select the respondents for the study (see Figure 2). First, a random sampling of the LGAs yielded two LGAs from each of the agricultural zones giving a total of six LGAs (Akpabuyo, Calabar Municipal, Abi, Yakurr, Bekwarra, and Ogoja). The second stage was comprised of a purposive sampling of five communities from each LGA. These communities are among those connected to the various mobile phone networks. A total of 30 communities were identified from the purposive sampling. Stage 3 involved the purposively selection of 12 farmer respondents from the communities based on ownership of mobile phones and engagement in agricultural production. The list of respondents from each community was compiled by the community leaders. Data analysis included sample descriptive statistics and regression model analyses and were all conducted using Stata 12 software.

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Figure 2. Map of survey area: Cross River State of Nigeria

RESULTS AND DISCUSSION The results presented in the study were comprised of descriptive statistics of the surveyed farmers, their mobile phone ownership status, and the associated operating cost and its structure. Others include an analysis of the benefits of using mobile phone and the factors that influence mobile phone usage by smallholder farmers.

Descriptive Analysis of Respondents This study found there was an active involvement of people in the use of mobile phone for agricultural purposes across the age groups particularly the younger farmers, a majority of whom were married and educated. It is not uncommon that farmers within the combined age group of 18 – 49 will generally be mobile phone servile as they are young and would take advantage to apply the skill and technology in any situations. This is consistent with the finding of Okello, Kirui, Njirani, and Gitonga (2012).

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As more young people enter agriculture, it is expected that mobile phone use for its related activities will continue to increase. More and new applications will be utilised by farmers making them take advantage of the ever-increasing technology offerings available. Young farmers are more socially active and can share knowledge faster, thus creating a learning environment for themselves and the older farmers. Under this circumstance, the older farmers can break away from their traditional or conservative ways of interaction. The older groups of farmers can be driven by the need to be more efficient in doing business and will apply every measure including mobile phone technology to improve efficiency. Table 1 also shows that more than 82 percent of the survey possess at least secondary school certificate; an indication that the farming population is increasingly becoming literate. This may not reflect the educational pattern across the entire country; however, a series of programs adopted by governments and other stakeholder are attracting more young people into agriculture. Therefore, the use of the mobile phone will not be a difficult task to learn and adopt for all purposes including agriculture. The farmers can read, understand, and apply instructions manually on how to use the various functionalities of the phone.

Mobile Phone Ownership and Duration of Ownership/Usage This study investigated the farmers’ mobile phone ownership and the duration of ownership/use of mobile phone to determine its acceptance as an essential tool for agricultural development (see Figure 3). The result shows that all the surveyed farmers possessed a mobile phone and more than 65 percent of the surveyed farmers had used mobile phones for more than six years. This is an indication of strong adoption of the technology and confirmed Qiang, Kuek, Dymond, and Esselaar (2011) finding that the adoption of information technology in agriculture is increasing in Sub-Saharan Africa. Table 1. Descriptive analysis of respondents. Sample size = 328 Variable Gender Age Group

Educational qualification

Marital Status

Variable characteristics

Frequency

Percentage of respondents

Male

248

75.610

Female

80

24.390

18 - 29 years

3

0.910

30 - 39 years

112

34.150

40 - 49 years

45

13.720

50 - 59 years

45

13.720

60 years and over

123

37.500

First School leaving certificate

57

17.380

Secondary School certificate

118

35.980

OND/NCE

24

7.320

Bachelor’s degree/HND

114

34.760

Higher degrees

12

3.660

Others (Please specify)

3

0.910

Single

51

15.550

Married

277

84.450

Note: OND/NCE = Ordinary National Diploma/National Certificate of Education; HND = Higher National Diploma

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Figure 3. Duration of mobile phone ownership/usage

Ownership is one of the major attempts toward the use of mobile phones. Ownership creates the willingness/power to explore the product and its functionalities, and increases the willingness/ability to use them for diverse situations. This ‘use’ process resulting from ownership increases the farmers’ product knowledge. This long period of ownership/usage is also inferred to be predicated on the benefits accrued to the farmers not just in the economic sense alone, but also the cultural transformation of the business environment and the community’s communication settings. Ownership of a mobile phone also symbolises high social status in the farming communities. It is not uncommon for people in the cities and major towns to buy a mobile phone for their parents to stand out among their contemporaries in the community. This social symbolism of the mobile phone is consistent with the studies by Martin and Abbott (2011), Okello et al. (2012), and GSMA (2013).

Farmers’ Mobile Phone Bill and Use Pattern While Figure 3 showed mobile phone ownership/usage, Figures 4 and 5 below show farmers mobile phone bill and the apportionment to activities consumed respectively. More than 88% of the surveyed farmers spend a maximum ₦6,000.00 or less per month on a mobile phone bill. Despite this study not investigating the amount spent in relation to total income or cost, the mobile phone bill can be a measure of the farmers’ need-to-call, network coverage, and projected amount to be spent on the service. The farmers’ phone bills structure can also be influenced by the number of inbound calls received from farm business stakeholders like input suppliers, extension agents and customers. Competitive input suppliers are more likely to initiate contacts to farmers to market their products. Such contacts reduce the amount of outbound calls the farmers make.

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Figure 4. Farmers’ mobile phone bill. (₦1.00 = $0.007 USD)

Farmers’ Mobile Phone Bill According to Use Pattern As interesting as the result is in Figure 4, more importantly are the components of the phone bill in Figure 5. Family and community uses accounted for about 62 percent of the phone bill. This indicates a higher usage compared to the farm related use. The high domestic usage is sequel to its capability to act as a tool to educate and gain knowledge as well as spreading viewpoints with family members and the rest of the larger community. Mobile phone interactions are cost effective ways to stay connected with others and provide the user with a sense of security and social value. The result was consistent with the findings of Okello et al. (2012) and GSMA (2013). Despite the fact that approximately 62% of the surveyed farmers’ mobile phone bills were incurred through family and other social interactions, the remaining part of the bill goes into several agriculture related activities. The farmers spent more than 17% of the mobile phone bill seeking market information about agricultural products. This represented the largest agriculture related component of the bill. The high percentage of farmers using mobile phone to source input and output markets was consistent with the result of Odhiambo (2014), Das, Basu, and Goswami (2012), and Ansari and Pandey (2013). This is an important result, considering the capability for mobile phones to bridge the wide divide that exists between the various players in the agricultural landscape. The input and output markets can be several kilometres apart and it can be time consuming and mentally draining for the smallholder farmers to make travel trips for every transaction. Although the sourcing of inputs, outputs, and markets information represented the largest single agriculture related activity for which a mobile phone was utilized, this study found that farmers’ phone bill on financial transactions with lenders represented almost 11% of the total mobile phone bill. Smallholder farmers require financing to purchase inputs and are known to have financial relationships with banks, particularly agricultural and community banks. Produce buyers also provide credit to smallholders to

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Figure 5. Farmers’ mobile phone bill according to use pattern

purchase inputs and to cover some operating cost in exchange for a promise to purchase the crops upon maturity or harvest. These kinds of transaction are enabled through mobile phone discussion without the farmers having to make physical presence. The almost 11% of the total mobile bill spent on agricultural financial related interaction showed the reliance of the farmers on it as an effective way of business interaction and was consistent with Qiang, Kuek, Dymond, and Esselaar (2011), Martin and Abbott (2011), and Kirui, Okello, and Nyikal (2010). The percentage of mobile phone bill the smallholder farmers incurred on gathering weather information represented less than two percent of the total phone bill per month. The justification for the low spending will be revealed when the discussion on benefit of the use of the mobile phone by farmers is presented.

The Agricultural Uses of Mobile Phone The various agricultural purposes to which smallholders use mobile phone were also tested. No specific research result exists for this test in the study area; a theoretical consideration was adopted that the t-test result for each variable will be the same as the assumed (hypothesised) mean value. The t-test test statistics result is shown in Table 2. The result shows that for two variables – “Use of mobile phone to access market information”, and “Use mobile phone for financial transactions” – the p-value associated with the t-test was 0.001 which is evidence that the mean of the two variables was different from the hypothesized value. For the variables “Use mobile phone to coordinate access to agricultural inputs”, “Use mobile phone to seek agriculture emergency assistance”, and “Use mobile phone to obtain expert advice”, the p-value associated with their t-tests were 0.594, 1.000, and 0.512, respectively. Using the decision rule, “if the p-value associated with the t-test is not small (p > 0.05), then the null hypothesis is not rejected”, it was concluded that the mean of each of these variables was not different from the hypothesized value.

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Table 2. The agricultural uses to which mobile phone was put Variable Use mobile phone to coordinate access to agricultural inputs

mean

standard deviation

t - statistics

P-Value

17.384

8.783

16.430

0.594

Use mobile phone to access market information

30.036

5.063

29.485

0.001

Use mobile phone for financial transactions

22.292

7.375

21.487

0.001

Use mobile phone to seek agriculture emergency assistance

14.573

6.538

13.863

1.000

Use mobile phone to obtain expert advice

17.486

8.119

16.602

0.512

Sample size = 328

The result indicates the use of a mobile phone to access market information has increased and this emphasised how important access to market information is to farmers. Effective and efficient market information provision has benefits for smallholder farmers, inputs suppliers, and consumers. When farmers have up-to-date market information; are better able to negotiate with other stakeholders. Relating the result from output sales perspective, the increased use of mobile phones for market information facilitates spatial distribution of products from production areas to consumer market with a clear price signals from the consumer market to farmers. With this information, farmers are able to adjust product quantity, quality, and variety as required according to their target markets. Furthermore, due to the increasing need for market intelligence, farmers use their mobile phones more often to obtain current relevant information and well-analysed historical market information to make production decisions, such that relate to what and when to plant or breed, at what stage should harvesting be done or what market should production be directed. Considering the magnitude of the effort required to obtain market information across regional, national and at time international boundaries, mobile phone technology can be widely deployed by smallholder farmers in the study area to ensure they are current with market environments. The number of farmers that use mobile phone for financial transactions has also increased, as indicated in the result in Table 2. Governments, financial institutions, and other private lenders of fund are located often time remotely away from the smallholder farmers. In some States in Nigeria, for example, some smallholder farmers obtain their loan through the ministry of Agriculture and the FADAMA program. They are able to use the phone to make quick calls to arrange loans and contracts that enable them to expand an existing farm enterprise or form new ones. Smallholder farmers can also explore the advantage mobile phone provides, to perform their social responsibility of paying the relevant taxes without making any travel to the Tax Office.

Benefits of Using Mobile Phone by Farmers The surveyed farmers were presented with benefits options and were asked to agree or disagree with the options base on how these perceived benefits applied to them. Table 3 shows the result; a mean value that was “more than 4” indicated that more smallholders agreed the mobile phone provided the benefits for which investigation were made while a mean value of “less than 4 suggested otherwise. Aside from the “Gets advance warning of weather risks” for which the surveyed farmers indicated no benefit, the farmers agreed to all the other benefits. The study does not explain why getting advance weather warning benefit was disagreed upon, despite it been one of the main benefits as shown in other

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Table 3. Benefits of using mobile phone by farmers Variable

Obs

Mean

Std. Dev.

Min

Max

Timely acquisition of price, market and farming practice information.

328

5.920

0.923

1

7

Facilitates access to technical and financial services

328

3.909

2.505

1

7

Easy to connect with other farmers for more effective collective action as producers, traders and buyers

328

5.979

1.277

1

7

Reduced cost of doing business

328

6.253

0.746

2

7

Reduced travel hours

328

6.289

0.707

1

7

Increased social networks

328

4.301

2.418

1

7

Empowers negotiations with wholesalers, traders and transport providers

328

5.526

1.786

1

7

Easier to link my products to distant markets and higher-end agricultural value chains

328

4.832

2.237

1

7

Gets advance warning of weather risks.

328

2.088

1.916

1

7

Enabled faster response to situational changes

328

5.655

1.246

1

7

studies such as Churi, Mlozi1, Tumbo, and Casmir (2012), Qiang, Kuek, Dymond, and Esselaar (2011), and Martin and Abbott (2011). However, it can be inferred that in the study area, the meteorology services to farmers is still in its infancy. The weather information could be available yet not accessible to the farmers due to inability to gather, harmonise, and provide location specific information to the farmers. Effective weather services rely upon locally relevant data tailored to farmers’ needs. When the meteorological service providers are deficient in capacity, they are not able to provide the relevant services to farmers as precisely and accurately to be useful for agricultural planning and operations. Another inference regarding the response to receiving advanced weather warning benefit is that over an extended period of time, farmers have used local knowledge and traditional coping strategies to adapt to changes in weather conditions. For instance, they can predict the arrival of the rainy season by a change in wind patterns and imminent rain fall event by changes in cloud colour.

Factors That Influence Mobile Phone Usage This study also investigated the influencer of adoption of mobile phone usage. The education status of farmers, their gender, mobile phone ownership, and usage knowledge of the farmers were tested to determine their influence on the farmers’ use of the phone for agricultural purposes (see Table 4). The four predictors of mobile phone ownership, mobile phone usage knowledge, gender, and the educational status of farmers were statistically significant. This result indicates that the use of a mobile phone and its functionalities by farmers has been influenced by these variables. The farmers’ knowledge of the use of the phone has increased enabling them to use the functionalities of the phone to meet agricultural purpose. One of the ways farmers acquired knowledge of how to the use mobile phone is through their children. Adult children teach their parents, particularly the less educated ones, how to make and receive calls, store and retrieve data, send, and receive MSM and MMS. The gender of the farmer plays a part in the usage of a mobile phone for agriculture. Cultural issues, such as traditional roles of men and women in Nigeria affect, delay or even prevent women’s acquisition

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 An Analysis of Mobile Phone Use in Nigerian Agricultural Development

Table 4. Factors that influence mobile phone usage. N = 328 Variable

coefficient

P-Value

Mobile phone ownership

3.696117

0.001

Mobile phone usage knowledge

6.631437

0.001

Gender

16.40994

0.001

Educational status of farmers

5.047578

0.001

Note: 0.001 Indicates estimated coefficient is significant at the .01 level; coef. indicates coefficient.

of mobile phones. Agriculture is still a male-dominated sector in which the head of household often determines what goes on in the family and their means of livelihood. The relationship usually impacts women in many ways such that Martin and Abbott (2011) concluded that women are later adopters of technology than their male counterparts. The male dominance in the use of mobile phone also corresponds with the overall levels of economic development and women’s role and participation in farming environment. The level of educational attainment of the farmers had an effect on their ability to read, comprehend, and apply knowledge. The educational status of the farmers was instrumental to the adoption and use of mobile phone. As more and more educated smallholders are involved in agriculture, so will the use of mobile phone technology increase.

CONCLUSION Nigeria has a larger rural population than the urban and is very agrarian. The agriculture is dominated by smallholder farmers who are positioned to become a key driver of future economic growth and prosperity if the confronting challenges are overcome. The spirit of this study looked into the contribution of mobile phone as an input-of-change for the country to achieve its agriculture and development potentials. This study investigated the extent to which farmers have taken advantage of mobile phone technology and the benefits they have derived from it. In view of these objectives, the study sought and provided answers to the questions raised in the objectives. Mobile phone created many benefits for the smallholder farmers aside from its unique characteristics of being handy, customised content delivery and convenience. As mobile phone providers continue to penetrate their services into the rural communities where farming is predominant, the tendency is that there will be expansion in the adoption of mobile phone and increased use of the product to cover more aspects of agricultural activities. The impact of geographic isolation, high transport costs, time lost to poor road networks and conditions, and the failure to deliver inputs on-time to farmers, or from the farmers to the market when prices are more favourable, can significantly impact revenue, profitability, and the overall social economic wellbeing of the rural communities. Considering all these issues, the use of the mobile phone technology has reasonably reduced most of these problems. It has assisted farmers to gain easy and timely access to market, market information and financial institutions – formal or informal. However, the low use of mobile phones for obtaining weather information is worrying. Weather information is an important detail upon which modern agriculture relies. Apart from providing normal agricultural weather information, it is relied upon to provide sudden

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extreme weather forecast that can be devastating. This study did not investigate the reason for the low mobile phone use to obtain this service; however, smallholder farmers generally are conservative and would often rely on tradition and local intuition to predict weather patterns. Moving forward, a review of the use of weather predicted data is first necessary to ascertain the availability of the data to farmers, secondly whether the farmers can access the data, and finally whether the data can be made available through mobile phone applications. Cogitating the benefits farmers claimed to have obtained from the use of a mobile phone, the realisation of the full potential of mobile phones usage can be constrained by lack of social inclusion and physical infrastructure. Electricity is a critical infrastructure for this service for both the phone service providers and the user farmers. The farmers rely on electricity to charge their phones and often it is not available or epileptic in supply; however, farmers are excited about the benefits a mobile phone provides. The role of the extension service/agents cannot be overstated; it often involves the visit to the farmers at home or on the farm by the extension agents. The discussions in such meetings often can be managed via mobile phone. Adoption of mobile phone for this purpose will save time and enable targeted messages to reach more farmers within the shortest possible time. The role of weather information in agriculture in modern time cannot be overestimated considering the volatility in the weather conditions due to the effects of climate change. It is important that every government should intensify effort to improve weather advice systems and to ensure the advice gets to the farmers. Governments in collaboration with mobile phone producers and network providers should develop applications that can provide weather information to farmers. The study has limitations; despite the similarity generally in mobile phone adoption and use in the survey area, the information may not be sufficient to generalise. Therefore, caution should be taken when using the data. The depth of the agricultural activities for which the mobile phone is used could vary considerably within and between the States in Nigeria. This study presented results on female mobile phone users, thus it did not specifically examine the differences in adoption rate and ownership between men and women smallholder farmers. Furthermore, the study is a cross sectional one, so it may not be capable of providing consistent information about the study population over time. Future studies should be directed towards determining female farmers’ adoption and use of mobile phone and a longitudinal survey should be conducted to confirm this study’s outcomes.

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Alleman, J., Hunt, C., & Michaels, D. (2002). Telecommunications and Economic Development: Empirical Evidence from Southern Africa (Technical Report). Sydney: International Communications Society. Retrieved from http://www.colorado.edu/engineering/alleman/print_files/soafrica_paper.pdf Aminuzzaman, S., Baldersheim, H., & Jamil, I. (2003). Talking back! Empowerment and mobile phones in rural Bangladesh: A study of the village phone scheme of Grameen Bank. Contemporary South Asia, 12(3), 327–348. doi:10.1080/0958493032000175879 Ansari, M. A., & Pandey, N. (2013). Assessing the potential and use of mobile phones in Agriculture. Kamantaka Journal of Agricultural Science, 26, 388–392. Avgerou, C. (2010). Discourse on ICT and development. Information Technologies & International Development, 6, 1–18. Burrell, J. (2008). Livelihoods and the mobile phone in rural Uganda. Retrieved from http://www.grameenfoundation.applab.org/section/ethnographic-research Chigona, W., Beukes, D., Vally, J., & Tanner, M. (2009). Can mobile internet help alleviate social exclusion in developing countries? The Electronic Journal of Information Systems in Developing Countries, 36(7), 1–16. Chorn, B., Sisco, C., & Pruzan-Jorgensen, P. M. (2010). The Business Case for Supply Chain Sustainability: A Brief for Business Leaders. Retrieved from http://www.bsr.org/reports/Beyond_Monitoring_Business_Case_Brief_Final.pdf Churi, A.J., Mlozi, M.S., Tumbo, S.D., & Casmir, R. (2012). Understanding Farmers Information Communication Strategies for Managing Climate Risks in Rural Semi-Arid Areas, Tanzania. International Journal of Information and Communication Technology Research, 2(11), 838–845. Das, A., Basu, D., & Goswami, R. (2012). Accessing Agricultural Information through Mobile Phone: Lessons of IKSL Services in West Bengal. Indian Research Journal of Extension Education, 12(3), 102–107. Dorosh, P., Wang, H.-G., You, L., & Schmidt, E. (2009). Crop Production and Road Connectivity in Sub-Saharan Africa: A Spatial Analysis. Africa Infrastructure Country Diagnostic. Retrieved from http:// infrastructureafrica.org/system/files/library/2011/05/WP19_Crops_roads.pdf FAO. (2005). Nigeria’s Agriculture and Food Security Challenges. Retrieved from http://www.fao.org/ tc/tca/work05/nigeriappt FAO. (2009). How to Feed the World in 2050. Forum Background document. Retrieved from www.fao. org/wsfs/forum2050/wsfs-background-documents/hlef-issues-briefs/en/ FARM-Africa. (2007). Keeping up with technology: The use of mobile telephony in delivering community based decentralized animal health services in Mwingi and Kitui Districts, Kenya. Retrieved from http://www.farmafrica.org.uk/view_ publications.cfm?DocTypeID_11

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GSMA. (2013). Women and Mobile phone: A Global Opportunity, A study on the mobile phone gender gap in low and middle-income countries. Retrieved from http://www.gsma.com/mobilefordevelopment/ wp-content/uploads/2013/01/GSMA_Women_and_Mobile-A_Global_Opportunity.pdf Halewood, N. J., & Surya, P. (2012). Mobilizing the Agricultural Value Chain. Retrieved from http:// siteresources.worldbank.org/EXTINFORMATIONANDCOMMUNICATIONANDTECHNOLOGIES/ Resources/IC4D-2012-Chapter-2.pdf Hudson, H. (2006). From rural village to global village: Telecommunications for development in the information age. Danbury, CT: Lawrence Erlbaum. IFAD. (2014) Investing in smallholder family farmers… for the future we want. Retrieved from http:// www.ifad.org/events/gc/37/doc/concept%20note_e.pdf Inoncencio, A., Kikuchi, M., Tonosaki, M., Maruyama, A., Merry, D., Sally, H., & de Jong, I. (2007). Costs and Performance of Irrigation Projects: A Comparison of Sub-Saharan Africa and Other Developing Regions. IWMI Research Report 109. IWMI, Colombo, Sri Lanka. Retrieved from http://www. ifad.org/events/hs/doc/irrigation_projects.pdf Karamagi, H., & Nalumansi, L. (2009). No more spilt milk: Mobile phones improve the supply of milk to the market in Uganda. ICT Update, 47. Retrieved from http://ictupdate.cta.int/ index.php/en/layout/ set/print/Feature-Articles/No-more-spilt-milk Kirui, O. K., Okello, J. J., & Nyikal, R. A. (2010, September 19-23). Awareness and use of m-banking services in agriculture: The case of smallholder farmers in Kenya. Contributed Paper presented at the Joint 3rd African Association of Agricultural Economists (AAAE) and 48th Agricultural Economists Association of South Africa (AEASA) Conference, Cape Town, South Africa. Lio, M., & Chun Liu, M. (2006). ICT and Agricultural Productivity: Evidence from Cross Country Data. Journal of Agricultural Economics, 34(3), 221–228. doi:10.1111/j.1574-0864.2006.00120.x Livingston, G., Schonberger, S., & Delaney, S. (2011, January 24-25). Sub-Saharan Africa: The state of smallholders in agriculture. Paper presented at the IFAD Conference on New Directions for Smallholder Agriculture. Retrieved from http://www.ifad.org/events/agriculture/doc/papers/livingston.pdf Martin, B. L., & Abbott, E. (2011). Mobile Phones and Rural Livelihoods. Diffusion, Uses, and Perceived Impacts Among Farmers in Rural Uganda Information Technologies & International Development, 7, 17–34. Moisio, R. J. (2003). Negative Consequences of Mobile Phone Consumption: Everyday Irritations, Anxieties and Ambiguities in the Experiences of Finnish Mobile Phone Consumers. In P. A. Keller & D. W. Rook (Eds.), Advances in Consumer Research (Vol. 30, pp. 340–345). Valdosta, GA: Association for Consumer Research.

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Odhiambo, F. (2014) Unlocking the market. Retrieved from http://ictupdate.cta.int/Feature-Articles/ Unlocking-the-market Ogbeide, O. A. (2014). An Assessment of Cooperative Society as a Strategy for Rural Development in Edo State of Nigeria. Journal of Rural and Community Development, 9(4). Okello, J., Kirui, O. K., Njirani, G. W., & Gitonga, Z. M. (2012). Drivers of Use of Information and Communication Technologies by Farm Households: The Case of Smallholder Farmers in Kenya. The Journal of Agricultural Science. Okello, J. J., Okello, R. M., & Adera-Ofwona, E. (2009). Awareness and use of mobile phones by smallholder farmers in Kenya. In B. Maumbe (Ed.), E-Agriculture and E-Government for Global Policy Development: Implications and Future Directions. Hershey, PA: IGI Global. Qiang, C. Z., Kuek, S. C., Dymond, A., & Esselaar, S. (2011). Mobile Applications for Agriculture and Rural Development. Retrieved from http://siteresources.worldbank.org/INFORMATIONANDCOMMUNICATIONANDTECHNOLOGIES/Resources/MobileApplications_for_ARD.pdf Robinson, L. (2009). A summary of Diffusion of Innovations. Retrieved from http://www.enablingchange. com.au/Summary_Diffusion_Theory.pdf Sebastian, K. (2008). GIS/Spatial Analysis Contr ibution to 2008 WDR. Market Access dataset. Retrieved from http://siteresources.worldbank.org/INTWDRS/Resources/477365-1327599046334/8394679-1327599874257/SebastianK_ch2_GIS_input_report.pdf Sherry, J. M. (n. d.). Mobile Phone Applications: Information Technology For Individuals In The Developing World. Retrieved from http://www.eecs.berkeley.edu/~justine/taskforce.pdf Staatz, J. M., & Dembele, N. N. (2007). Agriculture for Development in Sub-Saharan Africa. Background Paper for the World Development Report 2008. Retrieved from http://siteresources.worldbank.org/ INTWDR2008/Resources/2795087-1191427986785/StaatzJ&DembeleN_AgriForDevtInSSve19.pdf Syngenta Foundation. (2011). Mobile Applications in Agriculture. Retrieved from http://www.syngentafoundation.org/__temp/Report_on_mAgriculture_abridged_web_version.pdf Szilagyi, R., & Herdon, M. (2006, July 24-26). Computers in Agriculture and Natural Resources. Paper presented at 4th World Congress conference, Orlando, Florida United States of America. Tunde, A. M., & Adeniyi, E. E. (2012). Impact of Road Transport on Agricultural Development: A Nigerian. Ethiopian Journal of Environmental Studies and Management, 3(5), 232–238. USAID. (2013). Agriculture and Food Security. Retrieved from https://www.usaid.gov/nigeria/agricultureand-food-security

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World Bank. (2009). World Development Report 2009. Washington, DC: World Bank. Retrieved from http:// siteresources.worldbank.org/INTWDRS/Resources/477365-1327525347307/8392086-1327528510568/ WDR09_18_GIM04web.pdf World Development Indicators. (2010). Washington, DC: World Bank. Retrieved from http://data.worldbank.org/sites/default/files/wdi-final.pdf Wyche, S., & Steinfield, C. (2016). Why Don’t Farmers Use Cell Phones to Access Market Prices? Technology Affordances and Barriers to Market Information Services Adoption in Rural Kenya. Journal of Information Technology for Development, 22(2), 320–333. doi:10.1080/02681102.2015.1048184

This research was previously published in the International Journal of ICT Research in Africa and the Middle East (IJICTRAME), 6(2); edited by Alice Etim, pages 29-46, copyright year 2017 by IGI Publishing (an imprint of IGI Global).

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Chapter 62

Farmer Suicides in India: A Case of Globalisation Compromising on Human Rights Saloni Jain National Law University Delhi, India Khushboo Sukhwani National Law University Delhi, India

ABSTRACT Indian farmers are facing a crisis of their extinction caused by their suicides. A suicide, every thirty minutes, reflects towards a deeply rooted structural and policy defect in the country. A defect so extreme that many call the same to be state genocide. The State has several obligations towards its farmers, both nationally and internationally. However, the pressures of globalization combined with the influence of bodies like the WTO and IMF has managed to defeat these obligations. This has resulted in a state where ideas like profit, free trade and removal of barriers are being forced upon ‘sovereign’ States, who have allocated their power to decide on economic issues to supranational bodies due to their inability to operate in isolation like a Westphalian State. The aim of this chapter is to explore and elaborate upon the adverse consequences of globalization on the lives of farmers in India due to enhanced competition and policies which have been influenced by MNCs such as Monsanto and capitalist, north dominated supranational bodies like the WTO and World Bank.

I. INTRODUCTION Indian farmers are facing a crisis, a crisis of their extinction caused by their suicides. The region of Vidharba in India is infamous for its suicide rate. In the two years preceding 2015, about three thousand farmers have committed suicide in the six districts of Vidharba itself (Purohit, 2015). Studies have found that over nine hundred, or nearly one in three farmers, had debts ranging between ten to fifteen thousand rupees. (Purohit, 2015). In the year 2009 itself, over seventeen thousand farmers had committed suicide (Ministry of Home Affairs, 2009). In other words, one famer died every thirty minutes. DOI: 10.4018/978-1-5225-9621-9.ch062

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 Farmer Suicides in India

A suicide, every thirty minutes, reflects towards a deeply rooted structural and policy defect in the country. A defect so extreme, whether by way of active acts or omissions, that many call the same to be State genocide. The State has several obligations towards its farmers, both under the Constitution of India and under international conventions like ICCPR and ICSCR, which it is deplorably deflecting. However, busy with crafting a pleasant picture of “shining” India, the media too, barring a few rural journalists like P. Sainath, has neglected its duty to report on the lives and livelihoods of the largest group of working people in India, the farmers. Agriculture has transformed into a negative economy which is reflected in the rapid increase in indebtedness faced by the farmers (Katakam, 2009). Policies of trade liberalization and corporate globalization are at the root of the farmer distress. The pressures of globalization combined with the influence of bodies like the WTO and IMF has managed to defeat the human right obligations. The influence of these bodies on national economies so extreme that a Mexican farmer had to stab himself to death to hinder the world trade talks in Cancun in September 2003 (Watts, 2003). The farmer was protesting against the north’s efforts to open agricultural trade, whilst the global south wanted to deliberate on older issues that affected them the most, especially the impact of European and U.S. subsidies on their own agriculture and lack of access to those markets (Watts, 2003). Globalization and liberalization has resulted in a state where ideas like profit, free trade and removal of barriers are being forced upon ‘sovereign’ States, who have allocated their power to decide on economic issues to supranational bodies due to the current trade scenario where a country cannot operate in isolation like a Westphalian State. The aim of this chapter is to explore and elaborate upon extensively the adverse consequences of liberalization and globalization on the lives of farmers in India due to enhanced competition and policies which have been influenced by MNCs such as Monsanto and capitalist, global north dominated supranational bodies like the WTO and World Bank.

II. BACKGROUND Recently, a lot of reliable studies have reported the rate of farmer suicides in India. The rate of farmer suicides reported in the region of Vidarbha is alarming. The Indian Government compiled statistics for farmer suicides between 1995 and 2009 and according to the report, over two lakh forty five thousand farmers had committed suicide in that period of time (Ministry of Home Affairs, 2009). In the year 2009 itself, over seventeen thousand farmers had committed suicide (Ministry of Home Affairs, 2009). In other words, one famer died every thirty minutes. The hypothesis of this chapter is that the problem of farmer suicides in India is a result of the policy of the Indian state which is influenced by global pressure. The globalization of agriculture has resulted in this situation of producers of our food dying of hunger. The problem of farmer suicides in India can be addressed by way of states asserting their sovereignty, the developing and under-developing countries asserting and negotiating their rights and not succumb to the pressures of the international bodies like WTO, IMF, World Bank and the MNCs.

III: INDEBTEDNESS: THE ROOT CAUSE OF FARMER SUICIDE There is no dispute to the fact agricultural growth is required for overall economic development in a country like India where 2/3rd of the people are involved in the agricultural sector (Singh, 2015). Agri1379

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cultural growth depends upon the growth of productivity (Chand, 2005). Productivity in turn requires infusion of capital (Chand, 2005). Farmers in most developing countries require more capital than they can afford to generate through their savings (Chand, 2005). Agricultural Credit Review Committee projected the demand for credit both for production and investments at Rs. 389990 million by 2000 (Reddy & Reddy, 2003). This demand has just been steeply increasing since. As can be seen, farmers require huge credit. A startling 48.6% of the farmer households are in debt according to the 66th NSSO survey (Indian Sociology Institute, 2009). A farmer is unable to meet the exigencies of cash requirements due to several factors. Most of them are directly a result of globalization and active State policies influenced by supranational bodies, while some are omissions or failures on part of the State to adequately remedy this problem by provision of credit facilities which aren’t exploitative in nature.

1. Factors Leading to Indebtedness As stated in the previous head, globalization and supranational bodies are the main cause for the indebtedness leading to farmer suicides. The economic growth that India is witnessing is indeed a result of its supra-nationally influenced policies, but the very same policies have led to an uneven growth and pushed the farmers to a stage where they want to end their lives (Motlagh, 2008). The factors identified in this chapter are as follows,

2. Market Access The Agreement on Agriculture under the WTO regime, aiming at liberalized trade in agriculture and for a ‘fair’ international market for agricultural products, is resulting into upheaval in the lives of farmers (Aksoy & Beghin, 2004). Market Access is an essential ingredient of the Agreement on Agriculture (Smith, 2009). The clauses on market access require that the countries open up their economies and allow a free flow of agricultural products. There are two basic elements attached to it: 1. The non- tariff barriers are to be replaced by tariffs. Non- tariff barriers are in the nature of quantitative restrictions, licensing etc (WTO Legal Affairs Division, 2011); 2. Maintaining a minimum level of imports (WTO Legal Affairs Division, 2011). The implication of the Agreement on Agriculture is that India and other developing countries had to do away with the quantitative restrictions on market access (Order & Josling, 2011). This resulted in increasing the competition many fold, often to a level where domestic players could no longer compete, and the State couldn’t implement protectionist strategies (Order & Josling, 2011). Most policies aimed at promoting the domestic sector were violative of the WTO regime. This also made farmers vulnerable to price volatility. India was undergoing a balance of payment crisis, which was worsening with increased imports into the country (McCalla & Nash, 2007). The exports weren’t able to keep up due to decreased subsidies, and lack of the same amount to market access in other developed nations (Order & Josling, 2011). Also, the entrants to Indian markets were able to set the price of products artificially low due to subsidies available in their home country. (Chand, 2005). These points will be elaborated upon in the next heading. Consequently, India attempted to continue some quotas and import restrictions which were challenged by the United States in the India Quantitative 1380

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Restrictions on Imports of Agricultural, Textile and Industrial Products case. After failed consultations, a panel was set up by WTO to resolve the issue. India argued that the quantitative restrictions were to protect its balance of payment situation which was permitted under GATT Article XVIII (Westin, 2001). The GATT Panel held that there is a general prohibition on quantitative restrictions under Article XI:1 and India’s measures such as its import licensing system were quantitative restrictions which were inconsistent with Article XI:1 (Westin, 2001) . The panel concluded that the monetary reserves were adequate and there was no threat, or serious decline in reserves within the meaning of Article XVIII:11, to afford India its exception (Thomas, 2001). Naturally, when these quantitative restrictions were abolished in 2001, a standing committee of group of concerned ministers was established to deal with the crisis that ensued (Stern & Mattoo, 2005). With phasing out of these restrictions, India had to re-negotiate tariff concession for several agricultural items. As many as 715 agricultural items were freed from quantitative restrictions in 2000 (Goldar, 2005). The result was that the aggregate of imports of such commodities increased by 70% in 2003-04 from the level of imports in 1999-2000 (Goldar, 2005). The Indian farmers all of a sudden were facing an exponentially high level of competition. Even if WTO didn’t consider India’s import licensing system as consistent with the GATT agreement, WTO could have allowed India some time to bring about changes so that the agricultural sector is not in a state of crisis post its finding. Certainly there is no room for socio-economic and human rights considerations under the WTO decision making framework. An interesting pointer hinting towards WTOs bend towards the developed countries is its decision making process. In the above mentioned quantitative restrictions case, the dispute brought by the US against India, the panel had this to say: “Article 13.1 of the DSU entitles the panel to consult with the IMF in order to obtain any relevant information relating to India’s monetary reserves and balance-ofpayments situation which would assist us in assessing the claims submitted to us.”(Schott & Watal, 2000). However, in the United States — Rules of Origin for Textiles and Apparel Products, the dispute was brought by India against USA’s rules of origin on textiles and the panel held that India hasn’t substantiated its claims while recognizing that the information was readily available with IMF and other international bodies (Schnitzer, 2007).

3. Fall in Prices of Produce, Subsidies, and Other Domestic Support In order to industrialize more and comply with IMF and World Bank dictates, fiscal reforms took place in India which had an adverse consequence on public investment in critical areas like agriculture. The public expenditure on agriculture as a percentage of GDP fell significantly. There was decline in institutional credit to famers as a result of financial policies of the government (Reddy & Reddy, 2003). There was overall decline in expenditure on agriculture in the budget which was garbed in the name of fiscal constraint. Similarly, opening up India’s markets resulted in banks wanting to enhance their performance to compete globally. 4750 branches of rural schedules banks were closed (Chand, 2005). Loans given to the agricultural sector decreased from 18% to 12% almost immediately (Chand, 2005). Another pressure Indian farmers started facing was the dramatic fall in prices of farm produce as a result of the WTO’s free trade policies. The WTO rules for trade in agriculture are, in essence, rules for dumping. They have allowed wealthy countries to increase agribusiness subsidies while preventing other countries from protecting their farmers from artificially cheap imported produce. Four hundred billion dollars in subsidies combined with the forced removal of import restriction is a ready-made recipe for 1381

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farmer suicide. Global wheat prices have dropped from $216 a ton in 1995 to $133 a ton in 2001; cotton prices from $98.2 a ton in 1995 to $49.1 a ton in 2001; Soya bean prices from $273 a ton in 1995 to $178 a ton in 2001 (Diao & Somwaru, 2001). This reduction is due not to a change in productivity, but to an increase in subsidies and an increase in market monopolies controlled by a handful of agribusiness corporations. Subsidies under the framework of agreement on Agriculture can be in the nature of subsidizing production as one the domestic support measure or can be in the nature of export subsidies (Orden & Josling, 2011). In fact, domestic support and export subsidies are two of the three pillars of the Agreement on Agriculture (the third being market access) (Smith, 2009). Under GATT 1947 -which governed the international trade in agriculture before Agreement on Agriculture came in force- the restrictions on subsidies on export of primary agricultural products were ineffective (Orden & Josling, 2011). The result was that quantum of export subsidies being offered by a country was dependent upon the money in the national treasury. The Agreement on Agriculture, which marked a shift, requires direct export subsidies to be reduced to a level of 36% of the 1986-1990 base year over a span of six years (Orden & Josling, 2011). The developing countries are subject to lesser reduction levels over a span of ten years and the least developed countries are not required to commit anything (Aksoy & Beghin, 2004). This appears good for the developing countries, but is again ineffective like GATT 1947. The exporters in India do not get any direct export subsidy (Chand, 2005). The national treasuries of India and many other developing and least developed countries can’t afford subsidizing export marketing cost or transport charges. The high level of subsidies given by developed countries to its agricultural products is one of the major problems in international trade in agricultural products. If the products are subsidized and consequently cheaper than the domestic products of the developing countries, the farmers in those countries can’t compete. As is stated above, the agreement on agriculture, very good in its intentions, aims at resolving this problem by calling for commitments on reduction of domestic support. But at some level, the fairness of the agreement itself is questionable as well. Countries giving subsidies on their agricultural products have to reduce them over time while the countries not giving subsidies at all can’t beyond the de-minimus limit (Rosset, 2008). There is no parity. Cotton producers in the US are given a subsidy of $4 billion annually (Rosset, 2008). This has artificially brought down cotton prices, allowing the US to capture world markets previously accessible to poor African countries such as Burkina Faso, Benin, and Mali (Rosett, 2008). This subsidy of $230 per acre in the US is untenable for the African farmers. African cotton farmers are losing $250 million every year (Rosett, 2008). That is why small African countries walked out of the Cancun negotiations, leading to the collapse of the WTO ministerial conference in 2003 (Watts, 2003). While MNCs like Monsanto pushes the costs of cultivation up, agribusiness subsidies drive down the price farmers get for their produce. The rigged prices of globally traded agriculture commodities steal from poor peasants of the South. A study carried out by the Research Foundation for Science, Technology and Ecology (RFSTE) shows that due to falling farm prices, Indian peasants are losing $26 billion annually (Reddy & Mishra, 2009). This is a burden their poverty does not allow them to bear. As debts increase — unpayable from farm proceeds — farmers are compelled to sell a kidney or commit suicide (Reddy & Mishra, 2009). Further there is misclassification, underreporting and omission from notifications to WTO regarding the domestic support given by USA. Members of WTO have to notify the WTO about domestic support they give (Smith, 2009). The Domestic Support clauses in the Agreement for Agriculture are a guide to the quantum of domestic support that a country can give to its farmers. The method through which the 1382

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quantum of domestic support is ascertained is by quantifying the total of the domestic support which is given by the country to a specific category of agricultural product (WTO Legal Affairs Division, 2011). Countries, based on whether they are developed or developing had committed reduction in the total Aggregate Measurement of Support (AMS), which is the quantity of support given by each country (WTO Legal Affairs Division, 2011). Domestic support under the Agreement on Agriculture is subject to three exceptions (Smith, 2009). These are: 1. Green Box Measures: These are measures which have a minimum impact on trade. These include measures like direct payment for relief from natural disasters (Smith, 2009); 2. Special and Differential Treatment Box: These are available to developing countries. Example of this is investment subsidies (Smith, 2009); 3. Blue Box Measures: They are relevant for developed countries only (Smith, 2009); The domestic support in the nature of traditional price and income support programs (direct payments, countercyclical payments, and loan rate program benefits) (Hoekman & Olareagga, 2002). The US notifies various types of disaster payments in the green box as product specific support, and as nonproduct specific support (Orden & Josling, 2011). The Canadian request for establishment of a panel in the Total Agreegate Measure of Support case (TAMS) case (WTO 2007) case listed forty-eight separate disaster programs over the period 1999-2005 (Orden & Josling, 2011). Crop insurance and disaster relief payments in the green box range from a low of $100 million in 1995 to a high of $2.3 billion in 2008 (Orden & Josling, 2011). Important questions are whether all disaster programs have been included in the US notifications, whether those notified in the green box satisfied the relevant criteria and whether annual support through these programs has been measured correctly (Orden & Josling, 2011). Some disaster relief programs could be judged to provide product specific payments that do not qualify for the green box (Orden & Josling, 2011). The EU has also provided the highest level of trade distorting domestic support among WTO members to its agricultural sector (Smith, 2009). The European Union has a Common Agricultural Policy (CAP) for its member states. The level of farm support in the EU has been historically high (Frandsen & Birgitte 2003). The Agreement on Agriculture was negotiated to bring restraints on policies as the EU’s CAP (Frandsen & Birgitte 2003). The EU notifications to the WTO about its domestic support reflect that the it has switched its support away from the trade distorting categories under the Agreement towards those deemed to be non or minimally distorting categories (Frandsen & Birgitte 2003). The notifications from 2008/09 to 2015/16 show that the payments have been decoupled from production and prices. There is clear manipulation of policy instruments to take advantage of the method of calculation. Further there is increased expenditure on initiatives such as rural infrastructure which falls outside the scope of Agreement on Agriculture (Orden & Josling, 2011). The net result is an increase in domestic support. Subsidies and other domestic support given by US to its farmers is also the center of attention in the ongoing Doha negotiations (Anderson & Martin 2015). The US position has also been to acquire increased market access in the emerging markets (Anderson & Martin 2015). The problematic nature of the Domestic Support by US has emerged in the US-Cotton case (WTO 2005) and the Total Agreegate Measure of Support case (TAMS) case (WTO 2007) (Orden & Josling, 2011). In the US Cotton Case, the appellate body held that USA’s measures were causing significant price suppression, violated Agreement on Agriculture and were causing serious prejudice to Brazil’s interests (Orden & Josling, 2011). 1383

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In the 9th conference of the WTO at Bali, India demanded that it should be allowed to extend its domestic agricultural subsidies (Food Security Schemes) indefinitely (Basu, 2013). The US opposed it, as they are trade distorting subsidies (Basu, 2013). They eventually reached a compromise that the subsidies will remain, but with future negotiations, and the developed nations will not complain on this issue for the next four years (Basu, 2013). This however, is not a permanent solution and till now there is no move by the WTO/Developed nations/US towards framing the guidelines for a permanent solution to subsidies issue. In the same Bali conference, Trade Facilitation Agreement (TFA) for an easy trade worldwide has also been declared (Jaipuria, 2015). India is aware that once it signs the Trade Facilitation Agreement (TFA) it will be obliged to ease its trade at any cost under which circumstances it will be forced to give up or reduce the minimal level subsidies that it has negotiated to give to its debt ridden farmers (Jaipuria, 2015).

4. Production of Cash Crops: Recolonization of India From growing wheat and barley, farmers were forced to shift to growing cash crops like tobacco and cotton (Reddy & Reddy, 2003). When the Indian Rupee devalued due to sudden liberalization and opening up of the market, Indian goods became cheaper, which made products them appealable in the international market (Reddy & Reddy, 2003). The State trying to tap this revenue source profitably, urged the farmers to grow cash crops. When India was under the British colonial rule, farmers were forced to grow cash crops, for foreign nations (Reddy and Reddy, 2003). Again after more than fifty years of Independence of India, India returned to the same state of being subservient to the interests of others. So, farmers, at the behest of market demands, stopped producing for self-consumption. What is important to note is that an average farmer holds approximately an acre of land, which makes profitable cultivation of cash crops and the like impossible (Indian Sociology Institute, 2009). Moreover, the cultivation of cash crops requires pesticides, fertilizers and other inputs much more than the traditional inputs (Indian Sociology Institute, 2009). The subsidies on pesticides was reduced dramatically when India liberalized in the 1990s due to pressure from IMF, as already discussed above (Deshmukh, 2010). Further, the inputs like fertilizers and pesticides were sold in the Indian market by the multinational corporations at costs which made cultivation unviable to farmers (Deshmukh, 2010). Thus the costs increased significantly and there was reduction in subsidies. This put the farmer in a debt trap.

5. Genetically Modified Crops MNCs sought to benefit from India’s structural adjustment policies and the LPG regime by assertively lobbying for the introduction of genetically modified seeds. Global corporations changed the input economy overnight. In 1998, the World Bank’s structural adjustment policies forced India to open up its seed sector to global corporations like Cargill, Monsanto and Syngenta (Sengupta, 2011). The farm saved seeds started getting replaced by corporate seeds, which need fertilizers and pesticides and cannot be saved (Sengupta, 2011). Corporations prevent seed savings through patents and by engineering seeds with non-renewable traits (Gilbert, 2013). As a result, poor peasants have to buy new seeds for every planting season and what was traditionally a free resource, available by putting aside a small portion of the crop, becomes a commodity. This new expense increases poverty and leads to indebtedness.

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In early 2000s, Monsanto’s Bt cotton and several other variants were approved by the Genetic Engineering Approval Committee (Indian GMO Research Information System, 2010). Bt cotton is a modified to produce the Bacillus Thuringiensis toxin, and the market cost of Bt cotton is at least double that of normal cotton seeds. Several reports indicate the market cost of these seeds to be much greater than five times (Qayum & Sakhari, 2005). Without availability of bank loans due to lack of collateral, farmers resorted to money lenders offering loans are exorbitant interest rates, which coupled with such high capital outlays put the farmers under severe pressure to generate high yields just to recover their costs of production (Gilbert, 2013). Bt cottonseeds also need a higher amount of water. What makes the situation worse is how the option to purchase non-Bt seeds is no longer available in some regions, nor in government seed banks. This forced farmers to get stuck in an endless debt cycle. The Monsanto bt-cotton mayhem is perfectly captured by the region in India with the highest level of farmers suicides: the Vidharbha region in Maharashtra — 4000 suicides per year, 10 per day (Purohit, 2015). This is also the region with the highest acreage of Monsanto’s GMO Bt cotton. Monsanto’s GM seeds create a suicide economy by transforming seed from a renewable resource to a non-renewable input which must be bought every year at high prices. Cotton seed used to cost Rs 7/kg. Bt-cotton seeds were sold at Rs 17,000/kg (Indian GMO Research Information System, 2010). Indigenous cotton varieties can be intercropped with food crops (Qayum & Sakkhari, 2005). Bt-cotton can only be grown as a monoculture (Qayum & Sakkhari, 2005). Indigenous cotton is rain fed. Bt-cotton needs irrigation (Qayum & Sakkhari, 2005). Indigenous varieties are pest resistant (Qayum & Sakkhari, 2005). Bt-cotton, even though promoted as resistant to the boll worm, has created new pests, and to control these new pests, farmers are using 13 times more pesticides then they were using prior to introduction of Bt-cotton (Indian GMO Research Information System, 2010). And finally, Monsanto sells its GMO seeds on fraudulent claims of yields of 1500/kg/year when farmers harvest 300-400 kg/year on an average. High costs and unreliable output make for a debt trap, and a suicide economy (Sengupta, 2011).

6. Reduction of Biodiversity and Crop Failure The shift from saved seed to corporate monopoly of the seeds also indicates a shift from biodiversity to monoculture in cultivation. The district of Warangal in the State of Andhra Pradesh used to grow diverse legumes, millets, and oilseeds (Shiva, 2004). The imposition of cotton monocultures has led to the loss of wealth of farmer’s breeding and nature’s evolution. Monocultures and uniformity increase the risk of crop failure, as diverse seeds adapted to diverse to eco-systems are replaced by the sudden introduction of untested and uniform seeds into the market. When Monsanto first introduced Bt Cotton in 2002, the farmers lost 1 billion rupees due to crop failure. Instead of 1,500 kilos per acre as promised by the company, the harvest was as low as 200 kilos per acre. Instead of incomes of 10,000 rupees an acre, farmers ran into losses of 6,400 rupees an acre (Shiva, 2004). In the state of Bihar, when farm-saved corn seed was displaced by Monsanto’s hybrid corn, the entire crop failed, creating 4 billion rupees in losses and increased poverty for desperately poor farmers (Shiva, 2004). Poor peasants of the South cannot survive seed monopolies. The crisis of suicides shows how the survival of small farmers is incompatible with the seed monopolies of global corporations.

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7. Spiral of Indebtedness: Credit Games So while all the above discussed was taking place, and when effective credit was most needed, the State did not take any steps. It chose to neglect the needs and rights of the farmers. Government’s inaction resulted in furthering of the agrarian crisis being faced by India. Changes in the pace and composition of agricultural credit emerged as a significant issue in the context of farmers’ distress in India. The problem arose due to: 1. Lack of access to credit; 2. Inadequate supply of institutional credit particularly to small, marginal and semi-medium farmers. This forces the farmers to rely on informal sources accompanied by hefty rates of interest. Prabhakara Reddy rightly noted the near absence of cheaper institutional credit and the rise of suicides in the regions in which input markets, output markets and credit markets are handled by the traders/moneylenders (Reddy, 2013). Financial institutions do not necessarily prefer to lend to the agricultural sector as can be seen from the number of banks that have reached the stipulated 18% lending requirement to the agricultural sector (Deshpande & Shah, 2012). The total investment to the GDP ratio has declined from 1.6% to 1.3%. The supply of institutional credit works out to just 11%. Thus, of the total short-term credit requirement, nearly 90% of the same is being met by private moneylending (Jaipuria, 2015). Farmers are unable to avail loans from the institutionalized sector because: 1. 2. 3. 4. 5.

In the farm sector, the possibility of assured income is quite low- the banks refuse to give loans; The poor farmers have no collateral to offer; Absence of commercial banks; Lengthy procedures to avail loans; Lack of awareness on part of small, marginalized farmers.

The informal sector lenders exploit the farmer. Indebtedness is not an overnight phenomenon. It is nothing but the result of faulty credit policies followed over the years. Unlike industrialists, farmers do not have access to debt relief under any law. Being indebted to the private moneylenders, they cannot go to public authorities to declare themselves insolvent or to get any kind of debt relief. With the tentacles of usurious moneylenders spreading fast, the absence of an effective and comprehensive law to curb harassment of borrowers seems to have emboldened the unscrupulous private financiers (Srivastava, 214). Exorbitant rates of interest, at times 10 per cent a day, harassment, threats and physical assault of borrowers for default in repayment to “discipline them” and to serve as a “lesson to others,” have come to stay in the `trade’, which strangely involves no paper work at all (Srivastava, 2014). As no worthwhile document is involved in the transaction and lenders’ muscle power alone works, complaints by unsuspecting borrowers are far and few in between (Indian Sociology Institute 2009). Those who obtain money, who include the poor and the prominent in society, would have to suffer in silence to protect their honour.

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In fact, according to a petition filed before the State Human Rights Commission, the producer, G. Venkateswaran, committed suicide because of the humiliation suffered by him at the hands of a Maduraibased moneylender (Indian Sociology Institute 2009). Informal sources of credit need to be substituted and the best alternative according to Ravikesh Srivastava is credit management through formation of Farmers’ Groups or Farmers’ Self-help Groups at the village level (Srivastava, 2014). The government has failed in addressing the situation of such debt- ridden farmers. Though several debt waiver schemes have been launched by the Indian government, they have been ineffective. Moreover, the Governor of RBI, the Central Bank of India, at a conference of the Indian Economic Association questioned the effectiveness of the debt waiver schemes by stating, “In some states on certain occasions we have had debt waivers. How effective these debt waivers have been? In fact the studies that we have typically show that they have been ineffective. In fact they have constrained the credit flow post waiver to the farmers,” Governmental steps to provide debt relief or compensation to farmers have not reached those in need and have seen very limited results (Press Trust of India, 2014). In 2008, the then government at Centre had come out with Agricultural Debt Waiver and Debt Relief Scheme (ADWDRS) 2008 under which 3.69 crore small and marginal farmers and 60 lakh other farmers were given debt relief to the extent of Rs 52,516 crore (Press Trust of India, 2014). Government auditor CAG had found in several cases that ineligible farmers were given benefit while deserving were left out, pointing to large-scale possibility of fraud (Press Trust of India, 2014). Complete waivers were available to small farmers, who were described as owning less than two hectares of land (Press Trust of India, 2014). Very little waiver was available to other farmers, who also suffered from extreme indebtedness. This two-hectare limit was arbitrarily fixed without any insight into the plight of the farmers. The other problem was that this scheme applied to bank loans only. Farmers who were indebted to money lenders, which comprised a majority of them, were excluded from any sort of governmental assistance. Further, while the State has introduced financial assistance schemes for the families of the farmers who commit suicide out of helplessness, such schemes have been intermittently and haphazardly implemented. They have served only as short-term solutions limited to very few affected families (Indian Sociology Institute, 2009).

8. State’s Obligations Under the Indian Constitution So far the chapter has discussed how the government’s policies, which in turn have been influenced by international pressure for bodies like IMF and WTO, have been responsible for the condition of farmers in India. In this section, it is discussed how the government is not complying with its Constitutional Obligations which obligates it to address the distress of the farmers. Article 21 of the Constitution of India states that no person shall be deprived of his life or personal liberty except according to procedure established by law. The Supreme Court i.e. the apex court in India, in numerous decisions has held that the right to life under Article 21 includes the right to livelihood. It includes the right to live with dignity. No person can live without means of subsistence and hence right to life would not make much sense if right to livelihood is not a part of it. The plight of farmers in India is contrary to what is guaranteed under Article 21 of the Indian Constitution. In 2004 an Organic Farming association had written to Bombay High Court over the situation of farmers in the country (Katakam, 2006). The court treated this as a Public Interest Litigation and observed The Constitution guarantees the right to life and to personal liberty. The values which underlie Article 21 of the Constitution are seriously eroded by deaths on such a systemic scale, as the facts before the

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court in relation to the State of Maharashtra demonstrate…. The suicides that have occurred are as much due to the failure of social and economic development to reach the poor, the landless and those on the margins of existence as it is due to natural calamities. (Katakam, 2006) This was the first case in India against the plight of farmers. The court had also held that Article 21 is inviolable and the state is the bound to address the condition of farmers and ensure them their right to life enshrined under Article 21 (Katakam, 2006). In 2006 another PIL was filed in the Supreme Court, the apex court of the country. The petition stated that in the last five years (2001-2006) 5910 farmers ended their life in Karnataka, 1835 in Andhra Pradesh, 981 in Maharashtra and 201 in Kerala (Saxena, 2006). The Supreme Court held that the suicide of farmers is a result of the structural deficiencies in the National Agricultural Policy. In March 2015, a Public Interest Litigation petition was filed by the Punjab based NGO. The petition stated that the state has failed to address the issue of farmer suicides. Farmers are forced to buy seeds at high costs, every planting season which has resulted in a debt trap for them compelling them to commit suicides (Press Trust of India 2015). It also stated that state’s inaction in implementing the recommendation of the National Commission on Farmers is responsible for non-alleviation of the farmers’ distress (Press Trust of India 2015). On the filing of this petition, the court sought the government’s response on why it has not made any amendments to the National Policy on Farmers which has structural deficiencies causing farmer suicides (Press Trust of India 2015). The government argued that there had been a decrease in farmers. Court though did not believe this assertion to be true, yet remarked, “Decrease in number (of suicides) is not enough, there should be no case of farmer suicide in the country.” (Press Trust of India 2015). The court passed an order on October 30th, 2015 slapping fine on the government for not filling affidavit despite Court’s direction (Press Trust of India 2015). The matter is now due to hearing on January 15. The laxity of state in the matter before the court reflects how much the government cares about farmers. Besides Article 21, two more articles under the Indian Constitution impose an obligation on the Indian State to address the condition of Indian farmers. Article 47 of the Indian Constitution states that it’s the duty of the State to raise the level of nutrition and the standard of living and to improve public health. The State shall regard the raising of the level of nutrition and the standard of living of its people and the improvement of public health as among its primary duties and, in particular, the State shall endeavour to bring about prohibition of the consumption except for medicinal purposes of intoxicating drinks and of drugs which are injurious to health. Article 39 is of pertinence too. It states some principles of policy to be followed by the State. The State shall, in particular, direct its policy towards securing that the ownership and control of the material resources of the community are so distributed as best to subserve the common good;And that the operation of the economic system does not result in the concentration of wealth and means of production to the common detriment

IV. TIMES TO COME… What would be WTO perspective on agriculture and farmers’ distress be in future? Would it address the present concerns? The Doha Round is the latest round of trade negotiations among the WTO membership. The Round was officially launched at the WTO’s Fourth Ministerial Conference in Doha, Qatar, 1388

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in November 2001. The Doha Ministerial Declaration provided the mandate for the negotiations, including on agriculture. What does the WTO draft on agriculture in Doha Rounds mean for farmers? In substance, the negotiations on agriculture focus on more market access, eliminating export subsidies, reducing distorting domestic support and sorting out a range of developing country issues (Anderson and Martin, 2015). To trade- offs being offered for more liberalized trade in agriculture are in the nature of supporting rural development. Moreover, the draft on agriculture amongst other things states that wide range of support for agriculture as a whole would be allowed without limit under the “Green Box”, ie, for development, infrastructure, research, agricultural extension, structural adjustment, etc. This in a way would mean that the developed countries can continue to manipulate the domestic protection to their farmers in the way they had been doing and a more liberalized trade in agriculture would worsen the situation of farmers in developing countries. The draft on key issues related to Blue Box, Green Box, Export Subsidies and Export Credit that continues to distort trade, manipulate price promote dumping is not very different from the text brought to Cancun which led to the collapse of the WTO Ministerial and suicide by the Korean farmer, Mr. Lee Kyung-hoe, the President of the Korean Advanced Farmers Federation. At the domestic front, the Indian Government apathetic to the condition of farmers. An example of it is how it is trying to amend its land acquisition legislation which has been met by a lot of opposition by farmers. The land market in India is byzantine, with an absence of reliable official ownership records, competing claims for the same property and complicated government rules over who can buy land and how it can be used. To overcome these difficulties, MNCs and Indian businessmen grew dependent on the government, which used its powers to force compulsory sales by farmers, and then sold the land on to businesses. The presently in force land acquisition law limits the government’s land acquisition powers by requiring that most of the affected population consent to any government acquisition of their land (Venkatesan, 2015). It also required a social impact assessment for any proposed project that would dispossess farmers. In August 2015, farmers from across India gathered in the capital city Delhi to protest against the land bill (Ghosh, 2015). Waving flags, and screaming anti-government slogans, they described the neo-liberal government policies as “pro-industrialist and anti-farmer.” Farmers demanded proper compensation to farmers, if land is acquired; insurance against crop loss; minimum wage guarantee for the farmers; social security to landless farmers and agricultural labourers and right price for the produce. At the protest site, farmers pledged, “No to suicides; Onwards to united struggles” (Ghosh, 2015). In light of all this, it doesn’t seem that there is any genuine ongoing effort to address the issue of farmer distress.

V. SOLUTION AND RECOMMENDATIONS The WTO perspective on agriculture and the international discipline that is evolving on agriculture is detrimental to the interest of the vast majority of small and marginal peasants, the agricultural workers, the rural and urban poor. The Government of India must recognize the crisis situation in agriculture and put an end to its anti-people policies. The Indian Government must strike a balance between its constitutional obligations and obligations under the other international covenants like ICCPR and ICESCR on one hand and the pressure of WTO, IMF and other such organizations on the other hand. India is party to a plethora of human right treaties including the ICCPR and ICESCR. Under Article 11 of the ICESCR, the Indian government is obligated to “recognize the right of everyone to an adequate standard of living 1389

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for himself and his family, including adequate food, clothing, housing, and to continuous improvement of living conditions,” and to “take appropriate steps to ensure the realization of this right.” The ICCPR recognizes that “every human being has the inherent right to life” and obligates States to ensure that “no one shall be arbitrarily deprived of his life”. WTO should allow India and other developing countries to protect its agricultural sector. Review of the Agreement on Agriculture requires reviewing the forced removal of quantitative restrictions (QR’s) on agricultural commodities. Indian farmers are annually losing Rs. 100,000 crores due to falling prices. Bringing back QR’s is the only real effective safeguard. Developing countries should firmly reclaim and assert their unqualified right to impose quantitative restrictions on imports to promote the development of our agriculture and to safeguard the livelihood of majority of their population, which is seventy percent in the case of India. Farmer suicide is a national security emergency and government must negotiate keeping farmer suicides in mind. The crisis and distress that countries like India are facing in agriculture is a national emergency. The suicides of thousands of farmers and the starvation deaths of thousands of tribals are the direct result of trade liberalization and the commoditization of food and agriculture. The government of India and other countries need to invoke Article 19 of the GATT on “Emergency action on imports of particular product” which states that, “If, as a result of unforeseen developments and of the effect of the obligations incurred by a contracting party under this Agreement, including tariff concessions, any product is being imported into the territory of that contracting party in such increased quantities and under such conditions as to cause or threaten serious injury to domestic producers in that territory of like or directly competitive products, the contracting party shall be free, in respect of such product, and to the extent and for such time as may be necessary to prevent or remedy such injury, to suspend the obligation in whole or in part or to withdraw or modify the concession.” Further, Article 20 on “General Exceptions” states that Subject to the requirement that such measures are not applied in a manner which would constitute a means of arbitrary or unjustifiable discrimination between countries where the same conditions prevail, or a disguised restriction on international trade, nothing in this Agreement shall be construed to prevent the adoption or enforcement by any contracting party of measure: 1. Necessary to protect public morals; 2. Necessary to protect human, animal or plant life or health; 3. Relating to the conservation of exhaustible natural resources if such measures are made effective in conjunction with restrictions on domestic production or consumption;

VI. FUTURE RESEARCH DIRECTIONS There can be future research on how the international framework and policies of IMF, WTO and other bodies shape agricultural policies of countries other than India and how such policies are interlinked to the conditions of farmers in those countries. Future studies can also focus on the ongoing negotiations on agriculture in WTO and whether the demands of the developing and under-developed world would address the issues that farmers are facing.

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VII. CONCLUSION The suicide economy of industrialized, globalised agriculture is suicidal at 3 levels — it is suicidal for farmers, it is suicidal for the poor who are deprived of food, and it is suicidal at the level of the human species as we destroy the natural capital of seed, biodiversity, soil and water on which our biological survival depends. The country is preparing for a severe drought. The vulnerability to drought has increased as globalisation has replaced our drought resistant crops like millets, pulses and oils seeds with water intensive hybrid cotton and water intensive vegetables and fruits for exports. Conservation of our water resources are soil and our biodiversity demands that we make a general exception to trade liberalization in agriculture using Rule 20. The protection of human life and the prevention of farm suicides is another reason to invoke this exception. The globalization of agriculture has resulted in this situation of producers of our food dying of hunger. But states should assert their sovereignty, the developing and under-developing countries should assert and negotiate their rights and not succumb to pressures of the north coming to them via the international bodies like WTO, IMF and World Bank and the MNCs. The WTO ministerial meeting in Nairobi in December 2015 is the litmus test of whether India will be able to make the lives of its farmers better or would succumb to the International pressure again. The tussle at Nairobi is between India and other developing and under-developing countries on one hand and the USA and the industrialized world on the other hand. India and other developing countries want to increase the subsidies that these countries can give to their farmers. The suicide economy is definitely not an inevitability. The transformation from Seeds of Suicide to Seeds of Hope requires: 1. A shift from GM crops and non-renewable seeds to organic, open pollinated seed varieties which the agriculturists can save and share; 2. A shift from chemical farming to organic farming; and 3. A shift from unfair trade based on false prices to fair trade based on real and just prices. India and other developing countries and under-developed countries need to ensure the seed of hope to their farmers in this globalized world by bargaining for these shifts in the WTO framework.

REFERENCES Aksoy, A., & Beghin, J. (2004). Global Agricultural Trade and Developing Countries. Washington, DC: World Bank Publication. Anderson, K., & Martin, W. (2015). Agricultural Trade Reform and the Doha Development Agenda. World Economy, 28(9), 1301–1327. doi:10.1111/j.1467-9701.2005.00735.x Basu, N. (n.d.). India agrees to WTO’s 4-year peace clause,. Business Standard.

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Chand, R. (2005). India’s Agricultural Challenges, Reflections on Policy, Technology and other issues. Center for Trade and Development, 10, 77–82. Deshmukh, N. (2010). Cotton Growers: Experience From Vidarbha. In Agrarian Crisis And Farmer Suicides. Delhi: Sage Publications. Deshpande, A., & Shah, V. (2012). Globalisation, Agrarian Crisis and Farmers’ Suicides: Illusion and Reality, Agrarian Crisis and Farmers Suicides. Indian Sociology Institute Journal, 14, 137-147. Diao, X., & Somwaru, A. (n.d.). A Global Analysis of Agricultural Reform in WTO Member Countries. Columbia Journal of Trade Law, 34, 56-70. Frandsen, S., & Birgitte, G. (2003). The Impacts of Redesigning European Agricultural Support. Review of Urban and Regional Development Studies, 15(2), 106–131. doi:10.1111/j.1467-940X.2003.00068.x Ghosh, A. (2015, August 21). 5,000 farmers begin march to Delhi over land acquisition ordinance. The Indian Express. Gilbert, N. (2013). A hard look at GM Crops. Nature, 497(7447), 23–35. doi:10.1038/497024a PMID:23636378 Goldar, B. (n.d.). Impact On India Of Tariff And Quantitative Restrictions Under WTO. Indian Council For Research On International Economic Relations, 172, 5-27. Hoekman, B., & Olareagga, B. (n.d.). Reducing Agricultural Tariffs versus Domestic Support: What’s More Important for Developing Countries? World Bank Policy Research Working Paper, 2918, 1-21 Indian GMO Research Information System. (2010). Year wise List Of Commercially Released Varieties Of Bt Cotton Hybrids By Geac. Indian GMO Research Information System Press, 20, 120–135. Indian Sociology Institute. (2009). Human Rights Documentation: Agriculture-Farmer Suicide. Indian Sociology Institute Journal, 6, 67–77. Jaipuria, T. (2015, November 19). Food subsidies will continue until a permanent solution is reached. Hindustan Times. Katakam, A. (2003). The Death Trap. Frontline, 19(26), 23–27. Katakam, A. (2006). The Bombay High Court directs the State government to take more responsibility regarding farmers’ suicides. Frontline, 23(17), 23–27. McCalla, A., & Nash, J. (2007). Reforming Agricultural Trade for Developing Countries. Washington, DC: World Bank Publication. Ministry Of Home Affairs. (2009). Accidental Deaths And Suicides In India. Nat’l Crime Records Bureau, 23, 278–289. Motlagh, J. (2008). India’s Debt-Ridden Farmers Committing Suicide. San Francisco Chronicle, 33(2), 43-48.

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Orden, D., & Josling, T. (2011). WTO disciplines On Agricultural Support, Seeking a fair basis for Trade. London: Cambridge University Press. Press Trust of India. (2014, December 28). RBI Governor questions debt waiver schemes. The Indian Express. Press Trust of India. (2015, October 30). PIL on farmer suicides: SC imposes Rs 25,000 cost on Centre. The Indian Express. Purohit, K. (2015, July 21). 1 in 3 farmer suicides in Vidarbha over Rs 10,000 debt: Study. Hindustan Times, p. 9. Qayum, A., & Sakkhari, K. (2005). Bt Cotton In Andhra Pradesh: A Three-Year Assessment. Deccan. Development and Society, 8(2), 52–63. Reddy, N., & Mishra, S. (2009). Agriculture in the Regime: Agrarian Crisis in India. Delhi: Oxford University Press. Reddy, P. (n.d.). Distress and deceased in India: An analysis of Causes of Farmers’ Suicides, Agrarian Crisis and Farmer Suicides. The Chronicle, 23(2), 45–65. Reddy, R., & Reddy, P. (2003). Domestic Price Policies In The Context Of Trade Liberalization, Indian. Journal of Agricultural Economics, 11(3), 28–35. Rosett, P. M. (2008). Food is different: why we must get the WTO out of agriculture. London: Zed Books. Saxena, R. (2006, August 2). PIL filed in SC to take check suicide by debt-ridden farmers. The Indian Express. Schnitzer, S. (2007). Understanding The International Trade Law. Delhi: Universal. Schott, J. J., & Watal, J. (2000). Decision making in WTO. London: Cambridge University Press. Sengupta, D. (2011). Bt cotton and farmer suicides in India: An evidence-based assessment. The Journal of Development Studies, 29(3), 143–157. Singh, S. (n.d.). State Of The Indian Farmer- A Millennium Study- Agricultural Credit In India. Frontline, 7(9), 33-38. Smith, F. (2009). Agriculture and the WTO: Towards a New Theory of International Agricultural Trade Regulation. London: Edward Elgar Publication. doi:10.4337/9781848449411 Srivastava, R. (2014). Credit through Participatory Management: The Way For Rural Smile”, Agrarian Crisis And Farmer Suicdes. Center for Trade and Development, 56, 120–133. Stern, R., & Mattoo, A. (2003). India and the WTO. New York: Oxford University Press. Thomas, C. (2001). Balance-of-Payments Crises in the Developing World: Balancing Trade, Finance and Development in the New Economic Order Symposium: Interfaces: From International Trade to Economic Law. American University of International Law Review, 15, 45-59.

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Vanda. (n.d.). The Suicide Economy of the Corporate Globalisation. Frontline, 11(5), 119-130. Venkatesan, V. (2015). State and Land. Frontline, 35(12), 54–58. Watts, J. (2003, September 16). Field of tears. The Guardian. Westin, S. (2001). World Trade Organizations: Issues in Dispute Settlement. WTO Publications. WTO Legal Affairs Division. (2011). WTO Analytical Index 2 Volume Set: Guide to WTO Law and Practice. WTO Publications.

This research was previously published in Defending Human Rights and Democracy in the Era of Globalization edited by Christina Akrivopoulou, pages 280-301, copyright year 2017 by Information Science Reference (an imprint of IGI Global).

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Chapter 63

Environmental Change and the Emergence of Infectious Diseases: A Regional Perspective From South America

Ulisses Confalonieri René Rachou Research Center - Oswaldo Cruz Foundation, Brazil Júlia Alves Menezes René Rachou Research Center – Oswaldo Cruz Foundation, Brazil Carina Margonari René Rachou Research Center - Oswaldo Cruz Foundation, Brazil

ABSTRACT In South America in the past decades several infectious diseases have emerged or re-emerged either as part of larger pandemics or as local processes involving autochthonous pathogens. These included arthropod-borne viral diseases, such as Dengue Fever, Chikungunya and Zika as well as viral hemorrhagic fevers, such as Hantavirus Pulmonary Syndrome, Junin, Machupo and Guanarito viruses. Parasitic disease was also important such as Malaria, endemic in the northern part of the continent, Leishmaniasis and Chagas Disease. Carrion disease, a bacterial infection originally from the Andes region, also seems to be expanding geographically. Several social and environmental processes have contributed to the emergence of these pathogens, including human migration, deforestation, road and dam building and climate shifts. Due to its high biological diversity of wildlife, arthropods and virus species in still untouched natural ecosystems in the Amazon has the greatest regional potential for the emergence of new human infections.

DOI: 10.4018/978-1-5225-9621-9.ch063

Copyright © 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

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INTRODUCTION South America is at the Southern part of the America Continent (10ºN; 55ºS) spanning an area of 17,819,000 million km2, which includes 12 countries and an independent territory (French Guyana). The regional climate is predominantly hot and humid, but subtropical climate is found in mountain regions (e.g. The Andes) and temperate and polar climates occur in the southern tip of the continent, in Chile and Argentina (Canziani & Dias, 1998). There is a high diversity of ecological areas and ecosystems such as the desert areas in northern Chile; the large plains in Venezuela and Colombia and the vast Amazon forest, which is shared by eight countries. The region has the largest freshwater system in the world due to the network formed by the Prata, Orinoco and Amazon River basins (Comisión Económica para América Latina y el Caribe [CEPAL], 2014). The regional population is about 410 million people with about 83% living in cities. The regional life expectancy reached 73 years in 2010 (Teixeira, Paixão, & Costa, 2013). According to the Pan-American Health Organization [PAHO] (2014), safe water access reaches 89% of people in the Andes. However, this is not consistent across the region. Bolivia has sewage collection and treatment covering only 46% of households. Gross income per capita ranged from US$12,470 for Chile and Argentina to US$7,784 in Andean countries. Between 1990 and 2010, regional infant mortality rates dropped by 50%; for Brazil it was 14,6/1000 and for Chile 7,8/1000, in 2012 (PAHO, 2014; Teixeira et al., 2013). Several endemic infectious diseases occur in South America, some with high annual incidence such as Malaria and Dengue Fever; in 2013, Brazil alone reported a total of 1,470,487 cases of Dengue Fever (PAHO, 2014). Several other endemic infections are autochthonous to the region such as Carrion Disease in the Andes and different forms of hemorrhagic infections caused by Arenavirus, such as Junin, Machupo and Guanarito hemorrhagic fever. South America is considered vulnerable to climatic conditions, especially when combined with land use and land cover changes (Caqui, Quispe, & Zegarra, 2013; Magrin et al.; 2014). The aim of this chapter is to show the impact of environmental change and human activities on the dynamics of some infectious diseases of major importance to public health in South America.

BACKGROUND The emergence of infectious diseases was identified as a major global health threat in the last quarter of the 20th century. Zoonotic pathogens from wild animals formed the majority of newly emerged human pathogens in the past few decades (Jones et al., 2008). Several factors have been pointed as major contributors to human infectious disease emergence: new strains of the pathogens, increased resistance to antibiotics, reduced resistance of hosts (e.g. infection by HIV), variations in human populations densities, shifts in diversity of populations of vectors and hosts, hunting of wild animals for food, deforestation and loss of biodiversity and climatic anomalies (Jones et al. 2008; Keesing et al, 2010; Pongsiri et al, 2009; Wilcox & Gubler 2005). In general, it is acknowledged that, for disease emergence to take place, an association of different drivers is necessary. In South America, since the middle of the last century, several diseases have emerged caused by different etiological agents, from Protozoa to viral infections. Some of these were part of larger epidemics/pandemics (e.g. Cholera; Dengue Fever) but other diseases have emerged as autochthonous 1396

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local processes and became endemic, such as viral haemorrhagic fevers caused by Junin and Guanarito Viruses. While some of those that have emerged or re-emerged became widely distributed (e.g. Dengue Fever), others occurred as local outbreaks with a small number of cases, restricted in time, and no more cases were reported (e.g. Sabiá Virus infections). Field observations by scientists early in the 20th century in some regions of South America (associated with the expansion of economic activities) reported changes in the transmission of human tropical diseases as a consequence of human-induced changes to the natural environment. A classic example was the observations by Brumpt and Pedroso (1913) of outbreaks of Cutaneous Leishmaniasis in the state of São Paulo, Brazil, following the opening of a new railway to the centre of the country. The association between the natural environment and the - then poorly known- parasitic infection can be illustrated by the naming of the disease by these authors: “American Forest Leishmaniasis”. These early authors have also observed that Cutaneous Leishmaniasis was more prevalent during the hottest period of the year, from November to April. Another example of early observations of the linkage between tropical diseases and environmental factors in South America was given by Carlos Chagas, the discoverer of the American Trypanossomiasis. Also in the context of opening up of a new railway in Central Brazil, in 1905, he observed that the incidence of malaria among railroad workers was high during the summer and dropped to almost zero during the cold and dry winter (Chagas, 1907). Since these early observations, about a century ago, the environment in the South America region has undergone dramatic changes due to human encroachment on the natural ecosystems. Road buildings, deforestation for the expansion of agriculture, urban growth, and the building of dams have been the main drivers of environmental changes. In the following section, representative groups of infectious diseases endemic to South America will be discussed in aspects of dynamic epidemiological shifts in relation to continuous changes in the physical and biological environments.

ENVIRONMENTAL CHANGES AND THEIR LINKAGES TO RELEVANT INFECTIOUS DISEASES IN SOUTH AMERICA 1. Malaria Malaria is an endemic parasitic disease in the northern part of the South American continent, from where it extends up to the southern parts of Mexico. The disease occurs under two main forms in its various localities and sub-regions: stable transmission of endemic character and sporadic transmission of epidemic type (Cabral, Fé, Suarez-Mutis, Boia, & Carvalho-Costa, 2010). Among the environmental changes usually associated with Malaria dynamics in South America, two process are considered most important: forest conversion due to deforestation and climatic variability in different scales such as seasonal or inter-annual, El Niño phenomenon, for example. El Niño corresponds to the warming phase of El Niño–Southern Oscillation (ENSO), an irregular and periodical variation in winds and sea surface temperatures over the tropical eastern Pacific Ocean. The cooling phase is known as La Niña. There has been some debate as to the relative importance of El Niño phenomenon in shaping the dynamics of this disease in specific areas of the Amazon. Several authors consider that changes in transmission patterns are more dependent on local aspects, such as failure of preventive measures or human population migration, than on large scale climatic phenomena (Cabral et al., 2010; Conn et al., 1397

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2002). However, in Colombia and Venezuela, local studies were able to demonstrate a significant influence of the El Niño on the transmission of Malaria (Delgado-Petrocelli et al., 2012; Mantilla, Oliveros, & Barnston, 2009). In Peru, the larvae of the main Malaria vector in the Amazon region, Anopheles darlingi, was shown to be associated with deforestation. Sites with A. darlingi larvae had an average of 24.1% of forest cover, compared with 41% for sites without A. darlingi (Vittor et. al., 2009). In the eastern part of the Brazilian Amazon region, culicid surveys performed in a pristine national forest revealed no species of Malaria vectors, among twenty-five thousand specimens collected (Confalonieri et al., 2013; Confalonieri & Costa-Neto, 2012). Using a geospatial model to map Malaria hotspots in the Brazilian Amazon, Valle and Lima (2014) observed that, on a large scale, forest cover and the proximity to gold mining operations were important drivers of disease risk. They have also found that areas with a longer dry season and areas with higher average rural income tended to have highest Malaria risk. The former is related to the creation of water bodies suitable to Anopheles sp. breeding when the rivers recede in the dry season and the latter, may be due to greater access to health services available to the high income population, which potentially increases the reporting rate. In Western Brazilian Amazon, da Silva-Nunes et al. (2008) observed, in a frontier settlement, that Malaria morbidity was strongly associated with land clearing and farming and decreased after five years of residence in these areas due to the development of immunity. A spatial clustering of Malaria was observed in the area of most recent occupation, indicating that the influx of non-immune settlers to forest fringe areas perpetuates the cycle of environmental change that favors Malaria transmission. It was also shown that the place of residence – distance of the dwelling from the forest - was important in determining risk. Using a negative binomial model of Malaria for municipalities in the Brazilian Amazon – the model associated the number of cases of Malaria to covariates as sociodemographic characteristics of the population and land cover – researchers were able to show the influence of logging, road building and forest fires on the incidence of Malaria. The overall incidence rate of Malaria was higher in the states were logging is an important activity. The influence of unpaved roads was higher in the municipalities with rates of deforestation higher than 75% (Hahn, Gangnon, Barcellos, Asner, & Patz, 2014).

2. Chagas Disease Chagas disease, discovered in 1909 in Brazil, has been extensively studied and the knowledge about the eco-epidemiology of this disease is vast (Teixeira et al., 2001). The adaptation of the different species of disease vectors to human dwellings and man=made environments is well known. In the Amazon region, different mechanisms play a role in the increased risk of Chagas disease infection: deforestation (causing the displacement of wild animal reservoirs of the infection), adaptation of wild species of triatomine vectors to man-made structures, and the migration of susceptible hosts, both humans and domestic animals (Coura & Junqueira, 2012). Recent studies in Panamá (Central America) have shown that anthropogenic landscape disturbance – forest fragments and peridomiciliary sites - increased vector infection with the Trypanosoma cruzi, the etiological agent of Chagas disease. Vector infection rates were significantly greater in deforested habitats as compared to contiguous forests. This was due to a combination of factors: although the modified environments have a low diversity of vector species they have a high abundance of mammal reservoirs of the infection and suitable conditions for the reproduction of the insect vectors and, therefore, 1398

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of maintenance of the cycle of the parasite (Gottdenker, Calzada, Saldaña, & Carrol, 2011; Gottdenker, Chaves, Calzada, Saldaña, & Carrol, 2012). Several decades ago, reports of the influence of temperature on the biology of a major Chagas disease vector – Triatoma infestans – found that for the same period of time, two generations of this species occurred in areas with high temperatures and only one generation in the cooler regions (Hack, 1955). Costa, Dornak, Almeida, and Peterson (2014) have modeled the distribution of T. brasiliensis complex of vector species according to projected temperatures and precipitation under conditions of climate change in Brazil, for the years 2020 and 2050. Triatoma brasiliensis is an important intra-domiciliary and peridomiciliary transmitter of T cruzi in the semi-arid region of Brazil (Coura, 2015). Under scenarios of temperature increase of up to 1,72ºC and a precipitation decrease of 55,6mm, the overall distribution of the species was projected to remain stable. However, the model was able to indicate a great potential for the colonization of new areas by this vector species, a fact important for the planning of epidemiological surveillance. In Venezuela and Argentina, the study of the future distribution of the species Rhodnius prolixus and T. infestans using the ecological niche approach, has indicated a possible reduction of the area of distribution of these species under a climatic scenario for 2050 (for future climate conditions, two scenarios were considered: the representative concentration pathways (RCPs) 4.5, 6.0 and 8.5 (hereafter scenarios), which were nested to HadGEM2-ES models and bioclimatic projections for 2050) (Medone, Ceccarelli, Parham, Figuera, & Rabinovich, 2015). Cordovez, Rendon, Gonzales, and Guhl 2014 obtained similar results in Colombia. These authors have concluded that, under scenarios of increased temperature for 2035, as a result of global climate change, a reduction of the area of transmission of Chagas disease currently known in Colombia would be observed.

3. Leishmaniasis Leishmaniasis, specially the cutaneous forms of the disease, transmitted by vectors of the genus Lutzomyia in South America, are known to respond to different types of environmental changes. One aspect frequently reported is the impact of agricultural encroachment in natural forests on the formation of ecological niches for the sandfly vectors of the disease. In Brazil, coffee plantations using traditional cultivation systems were reported to facilitate the transmission of cutaneous Leishmaniasis. This occurs because coffee trees provide shadow and the decaying leaves of these trees in the soil create adequate niches for the reproduction of sandfly vectors (Alexander et al., 2001, 2009). Other types of plantations such as sugar cane, bananas and cocoa were also reported to increase the risk of Leishmaniasis transmission (Azevedo et al., 1996; Azevedo & Rangel, 1991; da Silva et al., 1999). De Araújo Pedrosa and Alencar Ximenes (2009) and Membrive et al. (2012) reported the high risk of transmission to humans in banana plantations in Brazil due to the proximity of banana trees to the dwellings of peasants. In French Guyana, Fouque et al. (2007) have reported an expansion of Leishmaniasis transmission into areas of environmental modifications linked to gold mining, agriculture and military training. Also in the Guyana region, an increased rate of cutaneous Leishmanasis transmission was associated with deforestation (Rotureau, 2006). Although in Colombia both the population density and the number of species of sandfly vector were higher in forested areas when compared to degraded areas, in the latter the risk of Leishmaniasis transmission to human and domestic animals was higher due to the adaptation of the most important vector species to the anthropic environment. 1399

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In Brazil, shifts in the epidemiology of cutaneous Leishmaniasis were associated with building of dams (Vilela, Azevedo, Carvalho, & Rangel, 2011) and also roads and railways (Gonçalves Neto et al., 2013). Factors influencing incidence increases and the spread of Leishmania spp. range from habitat changes for vectors (as they frequently adapt to man-made buildings) to human population displacements associated with infrastructure projects Climatic variations have also been associated with epidemiological changes of Leishmaniasis in the Americas (Chaves & Pascual, 2006). In Colombia, associations of El Niño and La Niña climatic phenomena and the incidence of Leishmaniasis in endemic regions of the country showed variable linkages: in some areas El Niño has had a positive correlation with cases of the disease while in others, the cases were influenced by La Niña (Cárdenas, Sandoval, Rodriguez-Morales, & Vivas, 2008). The authors have stressed the need for further studies and emphasized the role of climatic factors in the dynamics of Leishmaniasis in different areas of Colombia.

4. Bartonellosis American Bartonellosis, also named Carrión Disease, caused by the bacterium Bartonella bacilliformis and transmitted by the sandfly species Lutzomyia verrucarum, occurs in the region of the Andes, being endemic in altitudes between 800m and 3000m. Environmental factors were reported to influence the dynamics and the spatial distribution of this disease. Chinga-Alayo, Huarcaya, Nasarre, Del Aguila, and Llanos-Cuentas (2004) have reported a positive association between disease transmission and El Niño climatic phenomenon in endemic areas of Peru. The mechanism involved is the increase in vector populations influenced by higher temperatures. Also in Peru, Zhou et al. (2001) have observed a doubling in the number of new cases of the disease during the months of El Niño, in addition to an expansion of the disease to areas not previously affected. High correlations were observed between higher incidence and increased temperatures three months before the outbreaks (Zhou et al., 2001). Recent reports of human cases of Carrión Disease outside the well-known endemic areas, such as cases in the forest areas and on the coast, indicate a trend of geographic expansion, probably influenced by both the adaptation of the vectors to new niches and human contact during population movements for commercial activities (Maco, Maguiña, Tirado, Maco, & Vidal, 2004).

5. Viral Diseases In South America, two major groups of endemic viral diseases are reported to be influenced by climatic shifts and environmental changes: arboviral infections and viral haemorrhagic fevers. Some of these diseases have been established in this continent for several decades such as Yellow Fever and, more recently, Dengue Fever. Others seem to be autochthonous to the region, such as the Mayaro and Oropouche fever in the Amazon (Vasconcelos et al., 2001). In the past few years, new viral introductions were reported, such as the West Nile virus (Morales et al., 2006) and Chikungunya virus, which occurred either as isolated cases or slowly expanding to become endemic (Figueiredo & Figueiredo, 2014; Carbajo & Vezzani, 2015). The emergence of the Hantavirus Pulmonary Syndrome virus in the Americas has been associated with human disturbances of the natural systems, affecting the composition of biodiversity. This is also true for infections caused by arenaviruses, which typically occur in South America: Junin, Machupo and Guanarito (Simpson, 1978; Mills, 2006). These infections have different species of wild rodent reservoirs 1400

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and those considered to be opportunistic – more adaptable to peri-domiciliary environments and presenting high fecundity and shorter life cycles – tend to predominate in the anthropic environment (Mills, 2006). Most outbreaks have been reported in anthropic environments where these species predominate, in a context of reduced diversity of potential host species (Mills, 2006). In the years 1940-1960, the emergence of rodent-borne arenavirus infections causing hemorrhagic fevers in Argentina and Bolivia, have followed a similar mechanism. Agricultural encroachment to natural pastures used for livestock production have caused a change in the local dominant species of rodents: Calomys musculinus in the maize crops of Argentina and Calomys callosus in the subsistence crops near small forested areas in Bolivia. These two species had their populations numbers greatly increased as well as adapted to the human dwellings where they have shed the virus in the urine (Johnson, 1993). Consequently, outbreaks of Machupo’s disease occurred in the northern part of Bolivia during 1960 and Junin viruses have been clinically described since 1953 in Argentina. The population dynamics of the reservoir rodents also play a role in outbreaks and in the case of the Junin virus in Argentina (Simpson, 1978), it was observed that the clustering of human cases during the harvest of maize was linked to a peak in rodent abundance. In a study of wild reservoirs of hantavirus in Paraguay, a higher rate of infection of rodent species in anthropic landscapes (e.g. agriculture) was found. When compared with areas of low infection, this high infection rate seems to be linked to habitat fragmentation, which changes the mobility of the rodents and facilitates virus transmission due to increased encounters between different rodent species, capable of increasing the probability of virus transfer from an infected animal to an uninfected member of a host population (Goodin, et. al., 2006). The role of climatic change in modulating Hantavirus infection was modeled in Argentina in regard to spatial distribution of the main reservoir rodent species. Different results were obtained according to different climatic scenarios used and for different parts of the country, but the overall distribution of the host was projected to be reduced due to changes in precipitation and temperature (Carbajo, Vera, & Gonzalez, 2009).

6. Arboviruses The most important arboviral diseases in South America are Dengue Fever and Yellow Fever, because of the high incidence of Dengue, and the high fatality rate of Yellow Fever (Cunha & Nogueira, 2005; Tauil, Santos & Morais, 2005). Both are influenced by climatic variability and change, and Yellow Fever, which is a focal disease rooted in natural ecosystems, is also influenced by changes in land use and land cover (e.g. deforestation) (Monath & Vasconcelos, 2015; Bryant et. al., 2003; Vasconcelos et. al., 2001). Several authors have reported the influence of climate, to variable degrees, on the epidemiology of Dengue Fever in tropical America (Chowell, Cazelles, Broutin, & Munayco, 2011; Herrera-Martinez & Rodriguez-Morales, 2010; Ibarra et al., 2013; Thai & Anders, 2011). Some of these are the higher Dengue incidence during El Niño periods in Venezuela, the rainfall and minimum temperature as a predictor of Aedes aegypti oviposition activity in Ecuador and the influence of seasonal temperature in Dengue epidemics in Peru. Reports were also made on the influence of specific types of natural ecosystems on the production of outbreaks of Yellow Fever (Degallier et. al., 1992) and of the micrometeorology of forest on the population dynamics of mosquito’s vectors of this disease (Pinto, Confalonieri, & Mascarenhas, 2009). In regard to Dengue Fever, models have pointed out that, although climate has a role in Dengue increase in the “Southern Cone” (Argentina), other geographic factors (e.g. distance to water bodies) and 1401

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demographic variables have a stronger influence on the determination of disease incidence (Carbajo, Cardo, & Vezzani, 2012). The most critical factor in the emergence/re-emergence of Dengue fever in South America is considered to be the widespread adaptation of its main vector, the mosquito Aedes aegypti, to artificial containers in urban settings, a fact observed in most countries of the region. This vector could also pose a major threat for the transmission of urban yellow fever in major cities of the region, a situation reported for the last time more than half a century ago (Downs, 1981). In Brazil, for example, the disease has caused major urban epidemics from the colonial period to the first decades of the 20th century when it was recorded the last urban outbreak in Rio de Janeiro, 1929; sporadic cases appeared in Acre state, in 1942 (Ferreira, Rocha, Caputto, Fonseca, & Fonseca, 2011). Since then, the successful control of the urban form of Yellow Fever, both in Brazil and in the Americas, was made possible for two reasons: the eradication of A.aegypti vector and the widespread use of 17D vaccine. The former occurred through the Rockefeller Foundation and the Pan American/ World Health Organization initiative which, between the years 1930 and 1950, have implemented successful programs of eradication of the vector in the Americas (Braga & Valle, 2007). The vaccine appeared in 1937, also through the Rockefeller Foundation with the involvement of Oswaldo Cruz Institute (Ferreira, Rocha, Caputto, Fonseca, & Fonseca, 2011). Two other frequently reported arboviral infections in the region are the Oropouche and the Mayaro fever viruses. Oropouche virus infections have been epidemic in the Amazon – Brazil, Peru, Colombia – and Panama and Trinidad. Its sylvatic cycle of transmission is poorly understood and involve multiple hosts and vectors, such as sloths, monkeys and birds (Pinheiro, Travassos da Rosa, & Vasconcelos, 1998). Still, epidemics of Oropouche as an anthroponosis are well characterized, with the involvement of a single species of vector – Culicoides paraensis (Carpenter, Groschup, Garros, Felippe-Bauer, & Pruse, 2013). Evidence points to an adaptation of the viruses to the peri-urban habitats since their midge vector species breed in holes thumbs and roots of planted trees, and they can bite inside houses. Outbreaks are associated with periods of high rainfall intensity and can reach thousands of cases in short periods of time in the Brazilian Amazon (Pinheiro et al., 1998). In the case of Mayaro fever, outbreaks were also reported from Amazonian countries, especially Brazil, Colombia, Venezuela and Bolivia. It is considered a forest disease similar to Yellow Fever, having the same mosquito species as vector – Haemagogus janthinomys - as well as primates as wild reservoirs, but cases transmitted in rural areas have been also reported (Travassos da Rosa et al., 1998). In the Amazon region, the main driver for Mayaro virus occurrence is deforestation, causing limited outbreaks (Vasconcelos et al. 2001). Although few studies have addressed the role of climatic variables in Oropouche and Mayaro fever epidemiology, Vasconcelos et al. (2001) observed that increased precipitation, especially in the first half of the year for the Amazon, seems to favor the reproduction of the vectors of both diseases. In fact, other environmental factors, such as temperature and humidity, play an important role influencing mosquito competence for arboviruses and its population abundance (Aybar, Juri, Santana, Grosso, & Spinelli, 2012; Tabachnick, 2013). Given the projections of temperature rise and reduced precipitation in the Amazon region, the distribution of cases of these two diseases can reduce or increase depending on the site studied. In regard to other less important arboviral infections in South America, the detection of West Nile virus infections from horses in Argentina was probably associated with migratory birds (Morales et al., 2006). The same mechanism was proposed for a newly emerged infection in forests of Southern Brazil, the Rocio Virus, which was detected by immunological tests in sylvatic birds captured in São Paulo state, Brazil (Lopes, Coimbra, Sacchetta, & Calisher, 1978; Ferreira et al., 1994). The Rocio virus appeared in Ribeira Valley, São Paulo state, Brazil, causing encephalitis epidemics in 1975-1976 – around 1000 1402

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cases and 10% fatality rate (Monath, 1993). A newly emerged arboviral infection in South America is Chikungunya virus, an infection also transmitted by Aedes mosquitoes, mainly A. aegypti. It is believed to have originated in Africa, where it still circulates enzootically among nonhuman primates, whereas in the Americas it was reported for the first time in 2013 (Vega-Rúa, Zouache, Girod, Failloux, & Lourenço-de-Oliveira, 2014). As of the year 2015, the South American countries Colombia, Venezuela, Brazil, Ecuador and Paraguay have reported local transmission (Carbajo & Vezzani, 2015). Since it is a disease transmitted by urban vectors, its emergence has been associated to urbanization and human migration (Figueiredo & Figueiredo, 2014). Regarding West Nile Virus, the influence of climate on its occurrence is well stablished in temperate countries, where warm winters and spring droughts are pointed out as capable of amplifying the transmission (Epstein, 2001; Paz, 2006). For Chikungunya, as for other diseases transmitted by the Aedes genus of mosquitoes, models projecting the distribution of A. aegypti vector show a potential for its advance toward South America centre, colonizing areas where the vector is absent (Campbell et al., 2015).

7. Cholera Cholera, a gastrointestinal infection caused by the bacterium Vibrio cholera, has re-emerged in Peru, South America, in 1990. Although strongly influenced by socioeconomic conditions, due to its marked seasonal occurrence in endemic regions, former studies have pointed out to the influence of climatic variability in the dynamics of this disease, especially in Asia (Pascual, Bouma, & Dobson, 2002). In Peru, its emergence has been associated with the 1991-1992 El Niño climatic phenomenon (Pascual et al., 2002). It seems that the bacterium has been present in the environment months before the beginning of the outbreak in Peru and marine ecosystem changes associated with El Niño led to the propagation of V. cholera along the coast (Seas et al. 2000). Recent reassessment of cholera emergence in Peru has indicated that the epidemic may have been linked to ENSO through multiple pathways, including elevated temperatures, rainfall extremes, La Niña phenomenon (cold phase of the ENSO cycle) and social vulnerability (Ramírez, Grady, & Glantz, 2013). A local study in Piura, one of the most affected districts in Peru, showed significant cholera association with sea surface temperatures in the Central Pacific Ocean and on the coast, as well as with rainfall and minimum and maximum temperatures with varying lag times (0-5 months); the strongest consistent impact was with rainfall (Ramírez, 2015).

CLIMATE AND INFECTIOUS DISEASES: ADAPTATION OPTIONS 1. Infectious Disease Control Regardless of what models project in terms of future infectious diseases profiles, as a consequence of climactic shifts, current actions targeted to the reduction of incidence and geographical expansion of endemic infectious diseases should be considered as part of the adaptation processes. This is particularly critical for those diseases known to be affected by climate variability, such as most vector-borne and water-borne infections (Smith et al., 2014). These control strategies vary according to disease cycles and the available technologies for their control. The following are some examples of diseases endemic to the South American region: 1403

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• •

•

•

Leptospirosis: Usually associated to urban floods following tropical storms (Dutra et al., 2015). The control strategies focus on improvement of drainage of rain water as well as on the control of rodent populations (rats), which are the main reservoirs of the pathogen; Dengue Fever: A viral disease transmitted by the urban vector species Aedes aegypti, a mosquito which also transmits the Zika virus and the Chikunguya virus (Ibarra et al., 2013; Musso, Nilles, & Cao‐Lormeau, 2014; Roth et al., 2014; Staples & Fischer, 2014). Since there are no vaccines against these viruses, the main strategy for their control depends on the reduction of the vector populations. This can be more effective through the reduction of the breeding sites for the vector: trash in backyards, discarded tires, flowers pots and other man-made structures that accumulate rain water (Tauil, 2002); Malaria: A vector-borne disease restricted to the natural environment. The main strategy for its control is the early treatment of the infected human hosts. A secondary strategy, at the local level, is the emergency spraying of insecticides to reduce the vector population (World Health Organization [WHO], 2014); Yellow Fever: A vector-borne disease known to be associated to climate variability and forest micrometeorology (Vasconcelos et al., 2001; Bryant et al., 2003; Pinto et al., 2009). Its control depends on the preventive vaccination of the population at risk in endemic areas (Ferreira, Rocha, Caputto, Fonseca, & Fonseca, 2011).

2. Healthcare, Education, and Adaptation Future Public Health impacts of climate change on the epidemiology of infectious diseases and on health care systems are well acknowledged (Confalonieri, Menezes & Margonari de Souza, 2015; Costello et al., 2009; Pereira & Barata, 2014; WHO, 2009). However, current health policies and strategies do not address possible changes to the epidemiological profile of the populations to be affected by climatic change. Adaptation strategies should be focused on both populations currently under climatic stress as well as those expected to be affected by future shifts to the global climate system (Ebi, Lindgren, Suk, & Semenza, 2013). The first step towards this end would be strengthening of the health care systems in order to facilitate the development of adequate responses to climatic hazards (Costello et al.; 2009). The promotion of secure infrastructure, not affected by extreme weather, is essential for the provision of health care services on a continuous basis. Several Latin American countries have built health care installations resilient to disasters such as Peru, Colombia, Equador, Chile and Costa Rica (WHO, 2009). In the urban environment in South America events like storms, floods and landslides are responsible for a high burden of morbidity and mortality. These require comprehensive preventive actions ranging from public health monitoring and disaster preparedness, in the context of community-based risk reduction strategies (Keim, 2008). In the municipality of Nova Friburgo, Rio de Janeiro, Brazil, heavy rains (182.8 mm/24 hours) have killed 429 persons, mostly due to trauma, in January 2011. Despite the interruption of several basic services – energy, water, transportation – an efficient health surveillance intervention was able to prevent deaths after outbreaks of dengue fever, leptospirosis and waterborne diarrhea (Porto, 2012; Pereira & Barata, 2014). This can be considered as an example of successful intervention – or reactive adaptation – in the context of climate-associated disasters causing infectious disease epidemics. Educational approaches are also an important part of the adaptation process. Lima and Layrargues (2014), have emphasized the need for a more comprehensive understanding of the impacts of climate, 1404

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associating the knowledge of climatic hazards and risks to the daily life of the population and also the need for environmental conservation as part of the adaptation strategy. Since risks associated to climate change are socially and spatially different, a revision of the practices of governance is needed. This entails both individual adaptation strategies that respect the social and economic characteristics of the affected people, especially those more directly dependent on natural resources (Adger, 2001) and an open and participatory decision making processes involving the actors concerned with the impacts, in order to complement the necessary technical knowledge (Jacobi, 2014).] Some local initiatives have demonstrated positive results in regard to public policies targeted to climate change. In the megacity of São Paulo, Brazil, Landin and Giatti (2014) have demonstrated the existence of a positive cross sectoral dialogue in the implementation of policies targeted to climate protection, in the context of a highly complex urban area. A survey of the population of different countries has found that middle income countries tend to favor technological solutions while developed countries are more skeptical in this regard and people believe the solutions should come from changes in habits and individual behavior (Echegaray & Afonso, 2014). Of great importance is the need to recognize that adaptation to climate change is also a social process, involving cultural aspects, beyond the economic strategies. Adger, Barnett, Brown, Marshall and O’Brien (2013) have demonstrated that the values adopted by the human groups can influence their interpretation of the problems, their motivation and their ways to respond and adapt to climatic risks; adaptation policies that ignore cultural aspects of the population affected by climate change can fail to increase the resilience of the targeted populations.

DISCUSSION Infectious disease emergence in South America has been driven by different factors and these depend, in a large extent, on the life cycle of the causative pathogens, their arthropod vectors and animal hosts. Also important are the environmental settings where the infections develop: processes affecting strictly urban disease cycles (e.g. Dengue fever) are quite different from those found in foci historically rooted in pristine natural ecosystems. This is due to the epidemiological complexity of the latter, which can embrace a wider variety of competent hosts and vectors as well as be more influenced by environmental and climatic factors. On the other hand, in urban cycles new human infections usually depend on the massive exposure of the susceptible human population to a high burden of pathogens in the environment or to a high density of insect vectors (e.g. mosquitoes). In the case of vector-borne diseases, emergence is usually associated with environmental shifts, such as changes in temperature or rainfall, that create new ecological niches for both adults and immatures vector species. This applies to man-made environments, such as households and buildings (e.g. in Dengue fever) and also areas with natural vegetation, as in the case of Malaria (Travassos da Rosa, Pinheiro, & Vasconcelos, 2005; Vittor et al, 2009; Carbajo et al., 2012; Hahn et al., 2014). Another important aspect is the biodiversity richness natural ecosystems. Pathogens circulating in wildlife, independent of the human host, can “spillover” and reach humans, following changes in the animal populations or encroachment of humans into natural systems, or both (Daszak, Cunningham, & Hyatt, 2000). Therefore, areas with rich assemblages of vectors and animal pathogens have a higher potential to support shifts in hosts and emergence of new human infections. In South America, one such region is the Amazon basin, which has the largest extension of tropical forests in the world and harbors 1405

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a rich biological diversity. To date, more than 180 species of arboviruses were identified in animals and insects of the Amazon and around 30 of them infect humans (Gubler, 2002). A recent review has pointed out the role of changes of the Amazon environment, such as those linked to deforestation, road building and hydroelectric dams, in driving the emergence of parasitic infections in humans (Confalonieri, Margonari, & Quintão, 2014). The Amazon region is one of the most vulnerable part of South America. Major projects in the area are impacting the natural ecosystems and causing alterations in land cover (e.g. forest conversion to pastures, dams), which present great opportunities for infectious disease emergence (Confalonieri et al., 2014). Encroachment to areas where endemic infections are present is also a cause of concern due to the risk of disease spread. For example, the construction of roads linking the Amazon to the Pacific Coast could facilitate the emergence of Bartonellosis – a disease originally restricted to the Andes Mountains – in lowland areas (Cesario & Cesario, 2005). International travel is thought to be the main mechanism involved in the most recently introduced viral infections in South America - Zika and Chikungunya viruses (Figueiredo & Figueiredo, 2014) - a mechanism already identified in other continents (Cordel, Quatresous, Paquet, & Couturier, 2006; Weaver & Reisen, 2010). Specifically, in relation to disease emergence in the Amazon, monitoring and surveillance strategies necessary to tackle processes leading to regional disease emergence were discussed recently (Confalonieri et. al, 2014). An interdisciplinary approach comprising control measures and clinical management combined with an integrated international surveillance is needed to manage the environmentally driven changes in the disease dynamics in the Amazon in the near future. One important strategy would be to enhance regional epidemiological surveillance, especially to sub-regions where social-environmental modifications are occurring, as is mentioned in the “Amazon Malaria Initiative” (U.S. Agency for International Development [USAID], PAHO, 2010). The epidemiological impacts of environmental change in other parts of the South American continent could also be surveyed using the same association of interdisciplinary studies (parasitology, epidemiology, ecology, land use, climatology) and epidemiological surveillance in hotspot areas. Further investigations in specific scientific areas - parasitology, epidemiology, climatology, geoprocessing, etc – should be pursued for a broader assessment of risks of infectious disease emergence in South America. Two topics deserve special attention. First, the role of cross-immunity of the population as a “barrier” to the introduction and persistence of new viruses to the region. Herd immunity for Dengue Fever viruses, endemic in this part of the world, could prevent taxonomically close viral species (e.g. West Nile Fever Virus) from becoming endemic in the human population. Cross immunity between different flaviviruses such as those causing dengue fever and the Zika virus is well known, a fact that makes the diagnosis of past infections with these pathogens using immunological tests more complex. Second, the significance of climate warming in the emergence of pathogens in the tropics. The potential to expand the distribution of vectors and enhance the transmission potential through alterations in the life cycle (e.g. shorter gonotrophic cycles and extrinsic incubation periods) of pathogens and vectors are likely to occur in temperate climates. However, in most of the tropics, suitable temperatures and humidity for endemic disease transmission are readily available and global warming may not be a critical factor in epidemiological shifts in this region.

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CONCLUSION Infectious disease emergence in Latin America, as a consequence of environmental changes, is a complex issue. A high diversity of natural ecosystems and a vast extension of still pristine environments are important sources of microbes that circulate in wild animals and insect vectors and can potentially spill over to the human population due to encroachment of habitats following human activities to expand infrastructure and promote economic growth. Besides changes in land use practices and in land cover, climatic shifts are also expected to facilitate the emergence of pathogens in South America in the next few decades. A high degree of human population density in urban areas in this continent poses an additional risk factor for disease emergence in this region.

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KEY TERMS AND DEFINITIONS Anthropic Environment: New spaces formed by human actions that transforms the natural environment, such as large cities and agricultural fields. Arboviruses: Viruses transmitted to humans by hematophagous insects and that are kept in natural or urban environment by vertebrate hosts. 1416

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Emerging Infectious Diseases: Diseases that had never been detected in humans before or which have affected a very small number of people in isolated places, such as Hantavirus Pulmonary Syndrome. Epidemics: A higher than expected incidence of a given disease, when compared to the historical average, that occurs in a short period and in a specific geographic region. Infectious Diseases: Diseases caused by pathogenic agents such as bacteria, protozoa and viruses that can spread from one individual to another, directly or indirectly. Peridomiciliary: Spaces or environments surrounding human habitation, like backyard, henhouse, pigsty and barn. Re-Emerging Infectious Diseases: Diseases that have affected large populations (worldwide or in specific countries) in the past, but were controlled and, at the present, they reappear as a major public health problem, such as Dengue Fever and Malaria. Vector-Borne Diseases: Infections transmitted by the bite of blood-sucking arthropods such as mosquitoes, midges and bugs.

This research was previously published in Examining the Role of Environmental Change on Emerging Infectious Diseases and Pandemics edited by Maha Bouzid, pages 109-137, copyright year 2017 by Information Science Reference (an imprint of IGI Global).

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Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria Femi Titus Akande Librarian, Nigeria Akinade Adebowale Adewojo Nigerian Stored Products Research Institute, Nigeria

ABSTRACT The chapter present the report of a study that examined information needs and seeking haviour of farmers in Laduba community, Kwara State, Nigeria. This study adopted a survey research design using simple sampling technique to select 28 respondents from the population. Structured questionnaire was designed for the collection of data. It was discovered from the findings that majority of the farmers were illiterate of the middle aged group between 31-40. The farmers plant many crops, but it is noticeable that the farmers plant cassava mostly, the area which the farmers indicated they need information most is on agriculture, it was also observed that the farmers access information from colleagues (co-farmers), friends and relatives, agricultural extension workers. The information needs of the farmers in this study on agriculture includes how to prevent diseases for their crops on the farm and after harvesting, the farmers also stated that they need information on how to seek for loan, where to get the best market to sell their farm produce and how to get the best agro-chemical for effective use. In this study it was discovered that the challenges the farmers face in acquiring information includes, the inability to read and write in English language, lack of constant electricity supply, conflict among members of various associations and lack of access to agricultural extension workers. It is recommended that the farmers should be given effective adult education, provision of information centre with necessary personnel and information media to boost information accessibility. Also the government was encouraged to negotiate with mobile telecommunication operators to subsidize services so that the farmers who form majority in the rural areas can access information and communicate easily through their mobile phones.

DOI: 10.4018/978-1-5225-9621-9.ch064

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 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria

INTRODUCTION Information is quite indispensable to the progress of any business (Aziagba & Okede, 2011). The case of farmers is not an exceptional. Availability, accessibility of timely, concise and accurate information is a tool that has the capacity to reduce uncertainty. Hence it is an important resource in an economic planning and other life endeavor. According to Swanson, (2008) information needs assessment give programme designers the ability to develop interventions that target users with specific information needs. (Swanson & Rajalahli, 2010) explained that the level and effort to search for information either local, national and global information depend on the aspiration of the searchers and the authors added that farmers’ ability to search for information depends on the sources that are available to them. Hence, it is expected that local information needs of the farmers could be met by well-organized information acquisition and dissemination system that uses traditional and modern methods. In Nigeria, according to (Okunade & Williams, 2014) quite a number of Nigerians are rural farmers living in small farming communities. In line with Okunade’s view, Laduba is one of the Nigerian rural communities dominated by farmers. The community is subdivided into smaller clans and budoagun which has highest concentration of farmers in the community is one of them. The farmers’ population in this community is about 500, it is located in Asa Local Government Area of Kwara State, Nigeria. The farmers in this community practice subsistence agriculture, which (Okunade & Williams, 2014) described as small scale farming using simple implements like hoes and cutlasses to meet the farmer’s household needs and with very little for sale. However, the advantage of availability of vast land in Laduba community and its nearness to Ilorin, the Kwara State capital made the community to attract different categories of elite who wants to engage in farming from Ilorin. In view of its strategic location, the community was selected as an adopted village by Nigerian Stored Products Research Institute (NSPRI), a Research Institute with the national mandate to research into post-harvest management of agricultural crops. Hence, the Research Institute do give her developed technologies through research to farmers at Laduba to use, while personnel from the Institute do regularly visit the farmers using the technologies to determine the efficiency of their research work. This further made Laduba community an attractive farming and research environment.

STATEMENT OF PROBLEM Nigerian farmers are essentially rural dwellers; they live their lives based on their experiences and traditions that have been passed to them. However, the desire to increase productivity and make a better living through farming is making the scope and source of information required to extend beyond experience and tradition, so, it is observable that farmers now appreciate other sources to get information to improve their life, hence, there is a need to identify these sources and the type of information they get, so that their usage could be maximized or discouraged to enhance the productivity of farmers in Laduba and other similar communities, because without farming, man’s existence on the earth would have been a mirage rather than reality (Okunade & Williams, 2014). This study therefore wishes to further support existence of farming and increase in productivity of farmers through determination of information required by them to enhance their productivity.

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LITERATURE REVIEW Effort had been made through different studies to determine information needs and information seeking behavior of different groups of people and professionals. Momoh, et al. (2015) conducted a study on information seeking behavior in central hospitals in Delta State, Nigeria. The study showed that nurses needed information to carry out their professional duties like health development and current approach to medical treatment. Friends, colleagues, libraries and internet were the identified sources where the nurses got their information. (Aziagba & Okede, 2011) conducted a study on information seeking behavior of cassava farmers in Upata clan, Ekpeye community of Rivers State of Nigeria. The study confirmed that friends and colleagues are major sources of information for the cassava farmers. Discussion over the radio broadcast were equally strong source of information for the cassava farmers, most especially when it is broadcasted in their languages. The library, seminars, workshops and television broadcast, were revealed as sources where cassava farmers do not get needed information. The findings, equally established that these cassava farmers are still involved in sourcing for information mostly from friends and relatives within the locality. In the study conducted by Babu, et al. (2012) on information needs and search behavior among farmers in Tamil Nadu, India, the authors grouped the different information sources accessed by farmers into four searching groups based on type of medium which include: print, broadcast, electronic and interpersonal. The findings showed how searchers relied on interpersonal sources such as imprint dealers, state department of agricultural extension workers, family and relatives. Semi medium searchers, according to the authors, accessed all media with most of them using electronic sources. High and medium searchers are revealed to also get information through print and broadcast media. Irrespective of the source used by farmers to obtain information, Babu, (2012) highlighted that the major constraints to information access were poor availability and unreliable information. Also, noticeable constraint that cut across was lack of awareness of information sources available and untimeliness of information the farmers do get. Saravan R. et al (2008) carried the study on information pattern and information need of the tribal farmers in Arunachal Pradesh, India indicated that most of the farmers need information on various topics such as pest management, disease management. Tologbonse D, et al. (2008) carried the study of information need of rice farmers’ community in Niger state disclosed that majority of farmers need information about crop production. Meitei & Devi (2009) also conducted a study with farmer’s community in Manipur, India to find out the information need of rural farmers’ community in Manipur state. This result of the study shows that majority of the farmers did not get access to needed information for their activities. Hence, the farmers requested that ICT based agricultural information support systems should be developed for them. Byamugisha et al. (2009) conducted a study on information seeking and use of urban farmers in Uganda, the researchers found out from the study, that the information needs of the urban farmers in studied area seemed to be as varied as the farming activities and also appeared to vary from one urban farmer to another. Achugbue & Anie, 2011 carried the study in Delta State, Nigeria on Rural Female farmer’s information need and importance of ICT in delivering information needs of female farmers. The findings from the research shows that the female farmers do not have enough skills to access information through ICT. Akanda & Roknuzzaman Md (2012) surveyed agricultural information literacy of 160 farmers in the northern region of Bangladesh. The survey shows that farmers need information for various purposes of agricultural activities, and they use different sources and media to access information. The researchers, therefore concluded that conceptualizing information need is a very difficult task. This is because the needs of individuals usually vary from time to time due to several factors. 1420

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UNDERSTANDING INFORMATION SEEKING BEHAVIOUR OF USERS According to Wilson (1999, 2000), information-seeking behavior includes those activities a person may engage in when identifying his own information needs, searching for such information in any way, and using or transferring that information makes up the processes of information seeking behavior of an individual. Kakai, et al., (2004) have defined information-seeking behavior as an individual’s way and manner of gathering and sourcing for information for personal use, knowledge updating, and development. This author explained further that information-seeking behavior of students, researchers, and professors has been the focus of enquiry for decades. He added further that initially, user studies were conducted in libraries and information centres primarily to evaluate library collections. These were said to be followed by studies of the research on habits of individuals or groups that would lead to the design of appropriate information systems and services. According to Kakai, et al., (2004) in mid 1980s, the focus of research shifted to holistic approaches to information-seeking behavior. However, Adereti, et al, (2006), and Aina, (2004) described information need as a piece of information, whether recorded or not, which an individual or a member of a group requires for effective functioning in their daily activities. Information needs can be seen as a set data which enables the user to make appropriate decisions on any related problem facing him or her at a particular time (Solomon, 2002). In other words, information is needed because it enables individuals to make a decision that affects their living, just as Opeke, (2004) suggest that information represents an ordered reality about the nature of the world people live in. The need for information in any society is individualistic. Individuals need information depending on the motive for such information. Taking the right decisions depends on access to information on all the alternatives and their implications (Ajayi, 2003). Zhang (2001) is of the opinion that a thorough understanding of user information needs and information-seeking behavior is fundamental to the provision of successful information services. Anwar (2007) also reiterates that it is important to understand the information-seeking behaviours of different groups of people, as it helps in the planning, implementation, operation, designing of new information systems and the development of service programmes in the work environment for optimal performance. According to Line (2000), new studies of information users and their needs are even more necessary in the age of the Internet. Researchers such as (Callison, 1997, Devadason and Pratap, 1997, and Ellis, 1993) have explored quantitative and qualitative methodologies for user studies on how Information-seeking behavior differs among user groups. Librarians must understand the information needs of user in order to address those needs. This study explores the information-seeking behavior of farmers. Knowledge about the information-seeking behaviour and information use of individuals is crucial to effectively meet their information needs. The first basic user study in the broader sense was undertaken by Menzel in1966 and he defined information seeking behavior from three angles and they include; when approached from the point of view of the scientists or technologists, these are studies of scientists’ communication behaviour; when approached from the point of view of any communication medium, they are user studies; and when approached from the science communication system, they are regarded as studies in the flow of information among scientists and technologists.

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MODEL ON INFORMATION SEEKING The Information seeking behavior is sub-discipline within the field of library and information science. It describes how people need, seek, manage, give and use information in different contexts. It may also be described as information-seeking behavior or human information behaviour. Information carriers may be in different forms based on the ISB and information-needs studies of various groups. The Information carriers may include a variety of channels, a variety of sources within the channels, and a variety of messages contained within these sources Johnson et al. (2006). Wilson (1981) has noted that the information seeking results from the recognition of some need perceived by the user. The behavior may take several forms, such as demanding information from the library or from other people who know. The approach has however been criticized because of insufficient theories, concepts and research methods, and because it has not taken into consideration the needs of the information seekers (Dervin & Nilan, 1986; Wilson, 1994). Dervin illustrated information seeking behavior diagrammatically as shown below, illustrating it triangularly with situation for seeking for information at the peak, the base of the triangle has the gap and the outcome sections. The situation, is the information needed or being sought for, the gap is the challenge in retrieving or searching for the information and the outcome is the result of the whole process. However, Dervin explained this process further by using the illustration in Figure 2, according to him, it may be preferred to use the bridge metaphor more directly as presented in the model. The model revealed that the process of seeking for information has a bridge between the situation and outcome, which spans between time and space, which implies that the process of seeking for information has no time limit Meho & Tibbo (2003) revise Ellis’s study and give new model with more features. Among the researchers, Kuhlthau (1993) has conducted empirical research about students’ information seeking behavior and developed a general model of the information search process (ISP). The ISP consists of 6 stages as: initiation stage, selection stage, exploration stage, formulation stage, collection stage and presentation stage. Wilson (1999) believes in the strength of Ellis’ and Kuhlthau’s models as they are based on empirical research and have been tested in subsequent studies. Wilson, however reviewed Ellis model and created an illustration, it is diagrammatical explained in Figure 3. Figure 1. Dervin’s ‘sense-making’ triangle

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Figure 2. Dervin’s ‘sense-making’ model re-drawn

Figure 3. Wilson’s information behaviour model

The aim of Wilson’s model was to outline the various areas covered by what the writer proposed as information-seeking behaviour, as an alternative to the models indicated in Figures 1 and 2, but it is clear that the scope of the diagram is much greater and that it attempts to cover most of what is included here as information behaviour. The model also shows that part of the information-seeking behaviour may involve other people through information exchange and that information perceived as useful may be passed to other people, as well as being used (or instead of being used) by the person himself or herself. The limitation of this kind of model, however, is that it does little more than provide a map of the area and draw attention to gaps in research: it provides no suggestion of causative factors in information behaviour and, consequently, it does not directly suggest hypotheses to be tested (Figure 4). Hayden (1999) has studied the different information seeking models like Wilson’s model of 1981, Krikelas model of 1983, Kuhlthau model of 1992, Big Six Skills model of 1992 proposed by Eisenberg and Berkowitz. The author says that we need to question who the library community is; we also need to question how we can provide information skills that leads the students towards information literacy. Borgman (2000) defines information seeking as a continuous process, involving active and

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Figure 4. Wilson’s information-seeking behaviour model

passive behaviors, and formal and informal communication. She points out the cycle of creating, using and seeking information which can be viewed as series of stages which people move back and forth, and they may be actively, creating, using and seeking information concurrently. Therefore, information seeking behavior refers to the pattern of response to the information need by person or group of persons. (Jarvelin & Wilson, 2003) discuss the functions of conceptual models in scientific research, in IS&R research in particular. What kind of models are there and in what ways may they help the investigators? What kinds of models are needed for various? Loeber and Cristea (2003) have made an attempt at investigating, analyzing and modelling the visitor and website. Weiler (2004) observes that the first model for study of information-seeking behavior in the general population was developed by James Krikelas in 1983. This model suggestes the steps of information seeking as follows: 1. 2. 3. 4.

Perceiving a need, The search itself, Finding the information, and Using the information, which results in either satisfaction or dissatisfaction.

Based on Krikelas’ model, people begin to seek for information when they perceive that the current state of knowledge is less than that needed to deal with some issue (or problem). Butterworth (2006) argues that typically Information seeking and retrieval behaviour is a strongly social, but weakly collab-

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orative leisure activity. He discusses how these assumptions fit with the existing information seeking and retrieval (IS&R) models and proposes path for future work. The author touches on the browsing behaviour and searching behaviour and has made a sketch of the characteristics of ‘personal history’ researchers. Shah (2008) proposes a model that helps us to understand the requirements for a successful collaboration. The author attempts to formalize the notion of collaboration and proposes a model of Collaborative Information Seeking (CIS) that put collaboration in perspective. His model consists of four layers such as information, tools, user and results. Of all the models, Ellis model is very much applicable to the 21st century mode of seeking for information, it is in this mode that we adopt the Ellis model on information seeking behavior. Ellis et al. (1993) model on information seeking behaviour includes six generic features. (Ellis & Haugan, 1997) have attempted to propose and describe the characteristics of a general model of information seeking behaviors based on the studies of the information seeking patterns of social scientists, research physicists and chemists, engineers and research scientists in an industrial firm. Ellis’s elaboration model describes the features of information seeking activities as generic. These features are: Starting, Chaining, Browsing, Differentiating, Monitoring, Extracting, Verifying, Ending. • • • • • • • •

Starting: The means employed by the user to begin seeking information, for example, asking some knowledgeable colleague; Chaining: Following footnotes and citations in known material or ‘forward’ chaining from known items through citation indexes; Browsing: ‘Semi-directed or semi-structured searching’ (Ellis, 1989: 187); Differentiating: Using known differences in information sources as a way of filtering the amount of information obtained; Monitoring: Keeping up-to-date or current awareness searching; Extracting: Selectively identifying relevant material in an information source; Verifying: Checking the accuracy of information; Ending: Which may be defined as ‘tying up loose ends’ through a final search.

INFORMATION SEEKING IN DIGITAL LIBRARIES Digital Information Resources There are various researches have been conducted on information seeking of digital information resources by different researchers around the world. In 2013 Gakibayo et al. carried out a study at Mbrarar University Library Uganda regarding the use of digital information resources by university students. Results were tabularized and it shows that a large number of respondents were aware with the full use of technology in utilizing digital resources. Natarajan et al. (2008) revealed the users of Annamalai University library were aware of digital journals only among all the other digital resources and 50% of the users are fulfilled from digital resources and it was also observed that digital journals were only source used comprehensively by users and the digital dictionaries and digital encyclopedias were the digital resources with the least usage. The study tells that users are not well aware with the provided resources and they cannot identify their actual need properly because of which the satisfaction is below 1425

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average. The use of internet based digital resources at Manipur University, India. This study identified the utilization, rationale, difficulties and satisfaction level of users about internet based digital resources services provided by the library and they conclude that low speed internet, irregular power supply and lack of required full text journals. According to findings the use of internet based digital resources by the students of Manipur University is not found very significant. The reason might be those problems which they are facing while accessing these resources (Singh, et al., 2007). In 2008 a survey was completed by H.R. and Mudhol was completed a survey at College of Fisheries, India. The research study revealed that respondents were highly satisfied about the level of access for the use of digital information sources. The study confirmed that the digital information sources users are very satisfied with their retrieved results and as the sample is limited to faculty, research scholars and post graduate students to the main reason for using digital information sources is the research in which they are currently involved. It seems that they are well aware with the usage of such digital resources. Mostafa (2013) carried out a survey at some selected private universities of Bangladesh about the use and impact of digital resources. According to results, majority of the respondents gave preference to digital thesis among all other digital resources likewise digital books, digital newspapers and digital magazines. The study exposed the fact there are sufficient digital resources available in the campus and students use those digital resources frequently but is need to modify infrastructure and training courses as well. Okiki et al. (2011) had conducted a survey in Nigeria to determine the use of digital information sources by post graduate students in Nigeria. Results showed that a large number of respondents use digital information sources daily they are motivated to use digital information sources for their research projects. According to tabulated results show connection in a major problem faced by the respondents. The post graduate students in Nigeria are being motivated for the utilization of digital information resources because of which the use of digital information is found extraordinary among them. Information Needs: Fabritius (1997) investigated the information seeking behaviour of journalists. The main purpose of the study was to investigate the role of digital information in journalism, how journalists use latest information technology and how new digital technologies sustain news reporting. The journalists’ information searching behaviour was examined by means of major hierarchical aspects. Fabritius places information seeking and salvage into a wider framework which have an effect on the loom to information sources and application of information.

Digital Information Seeking Behavior Research in the domain of information needs, information seeking and information seeking behaviour started in early twentieth century. Whereas tracing the history of information seeking and behavioral studies, few studies were carried out in the early 1900s, Ayres and McKinnie in 1916 revealed the information seeking at the Cleveland Public Library. Tibbo informs that a distinguished production of studies on the subject take placed in the 1960s [e.g. a study by the American Psychological Association, 1963 -1969 and Earle and Vickery’s study in 1969]. Wilson (2000) discovered an early importance on the use of information systems with a more person-oriented approach growing later in the 1980s. Although early user-centred research concerted on the scientific community, it rapidly expanded to integrate educational institutions to investigate students and staff’s actions and inspirations when using the technology. According to Francis (2008), “Researchers and practitioners in the field of LIS have long held an importance in the information-seeking behaviour of diverse patron groups. Research in this part dates back to the 1940s and the deliberate was on scientists.” Since then, studies rapidly improved, preliminary with those proposed to get better collection development, followed by folks that investigated 1426

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the research behavior of individual’s approach that observed the system as seen by the user Studies on web information seeking behaviour emerged afterward, and many pen down the mid-90s as the exact initial point. Jansen & Spink (2004) propose that the most primitive studies of web searching behaviour in the mid -90s occurred as web search engine and web browser use began to grow, mainly in academic environments. Author discovered the behavioral outline with special reference to electronic databases and the World Wide Web. Different models of information seeking behaviour were presented and the complexities in the procedure of searching were explored. These researches offer insight into the seeking behaviour in the course of electronic systems (Wilson, 2006). Asemi (2005) agreed to understand the information searching habits of internet users at the Medical University of Isfahan. The purpose of the study was to examine the position of information searching character of the users on internet. Data was collected using a questionnaire trailed by interview with users from five faculties. 188 users responded to the study. Study revealed that students use internet extensively, and it inhabits an important position with diverse sources. Study also revealed that electronic media has not substitutes print media. A study of Brazilian social sciences scholars found that, while print resources are still the most frequently used, electronic resources are becoming more and more accepted. Access to networked computers is the main barrier to the use of databases and other electronic resources. Francis (2005) focused on a study that explained the information seeking behavior of social sciences faculty at the University of the West Indies (UWI). One of this 2005 study’s findings was that social scientists have a preference journal articles in electronic format over print. Wang (2007) wrote about disciplinary and cultural differences among information seekers in the Internet age, concluding that there are distinctions across disciplines and cultures in terms of how they rank the importance of these resources and how much they use them. Wang further discussed the information needs, information-seeking behaviors, and resource use of selected special interest groups. Electronic Information retrieval skills as noted by Tsakonas & Papatheodorou (2006), digital libraries, e-journal platforms, portals, e-prints and other web-based information systems provide services supporting users to perform intense work tasks that require complex interaction activities. This implies that users cannot access e-resources without adequate computer skills. According to Toner (2008), advances in technology have made possible virtual classrooms, online courses, and distance learning. This, coupled with the growth in society’s access to information via ICT, has altered student perceptions of what the library has to offer. If libraries are to maintain their relevance in the cycle of student needs, then they must adapt and change (Toner 2008). MacWhinnie, (2003) and Thachill (2008), argue that students sometimes lack technical and research skills and so do not find the best and appropriate information, tempting them to use whatever information they can find first, fast and full text. More importantly, even with a good easy to use integrated system, students very often need the expertise of a librarian to apply search techniques and find the information they need (Thachill 2008). Tella et tal (2007) argued that the students’ ability to find and retrieve information effectively is a transferable skill useful for their future life as well as enabling the positive and successful use of the electronic resources whilst at school. They noted that in this digital era any student at the higher level who intends to better achieve should have the ability to explore the digital environment. Students are increasingly expected to use electronic information resources whilst at the university. To make use of the growing range of electronic resources, students must acquire and practice the skills necessary to exploit them (Okello-Obura & Magara, 2008). Skills learning is essential in a technology driven environment but can be enhanced tremendously through the use of innovative learning strategies (Lawson 2005). Ray & Day (1998) suggested that the skills required to access the maximum potential of electronic resources are much greater than those required for searching printed sources. These skills include knowledge of the structure of the 1427

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database and the instructions which must be input into the computer by the searcher – as well as an understanding of the ways in which the instructions are linked to one another. Okon (2005) asserts that the core skills traditionally associated with information professionals, which include information handling skills, training and facilitating skills, evaluation skills and concern for the customer, are all still relevant. The ability to find and retrieve information effectively is a transferable skill for enabling the positive and successful use of electronic resources by students while they are at university - as well as in their future lives. As Brophy (1993) argues, libraries must “reach a position where the acquisition of information skills is acknowledged as one of the key learning objectives for every student entering a university, so that no student leaves without being fully equipped to cope up with the information intensive world – the information society - as an end-user.” The library has not only ready and free information highway, but also the adequate and efficient information transport means, which allows the readers to use the tools and obtain the information they need (Shuling, 2007). The literature highlights the advantages of electronic over printed sources of information, but also suggests the need for certain skills in order to access and use electronic resources effectively. Given their apparent lack of use of electronic resources, this study set out to determine if LIS postgraduate students at Makerere University have the required skills and ability to access and use electronic resources.

Why Electronic Information Resources? Higher education is changing rapidly with the advent of technology. According to Shuling (2007), in recent years, electronic information has gradually become a major resource in every university library. The growth and diversity of electronic resources, especially e-journals, in the past few years has led many to predict the extinction of the printed journal (Okello-Obura & Magara, 2008). It has been suggested that a new paradigm is sweeping scholarship (Liew, Foo and Chennupati, 2000; Harper et al, 2006). Majid et al (1999) argue that technological advancements opened up new horizons for the creation, storage, access, distribution and presentation of information. In the global information communications technology (ICT)-dominated world, “place” is much less important (Ferguson, 2006). “The impact of moving from text-based to resource-based learning has involved heavier use of library materials and a demand for more and varied media sources” (Kinengyere, 2007). This makes the provision and use of Electronic Information Systems (EIS) in academic libraries a critical issue for those working in information and library services (Armstrong....et al, 2001; Elam, 2007). The pace at which information resources are being produced and converted into an electronic form is greater today than in previous years (Armstrong ... et al 2001). In today’s information age it would seem that library users would not only be eager to take advantage of the convenience electronic resources have to offer, but would be fully immersed in the new technologies (Elam 2007). Electronic information resources offer today’s students different opportunities compared to their predecessors. Liew, Foo and Chennupati (2000:302) argued that while reading an e-journal is not the same as reading a printed one, many are beginning to acknowledge the possibility that electronic documents (e-documents) offer users advanced features and novel forms of functionality beyond what is possible in printed form. Years ago Brophy (1993), noted that the advantages of electronic resources over print include speed, ease of use, ability to search multiple files at the same time, ability to save, print and repeat searches, more frequent updating and the ability to access from outside the library (a particular advantage for the distance learner). According to Dadzie (2005), electronic resources are invaluable research tools that complement print-based resources in any traditional library. Their advantages include access to information that might be restricted to the user 1428

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because of geographical location or finances, access to current information, and provision of extensive links to additional resources or related content (Dadzie 2005). E-resources could be stored electronically thereby saving space, the risk of lost, theft or damage is lessened and costs significantly reduced. Attitude towards e-resources Academic libraries now live in a superior new world. The rapid advancement of Information and Communication Technology (ICT) has brought a revolutionary change in the information scenario giving rise to a number of options to the users’ community to handle varied information sources conveniently and effortlessly. As a result, e-resources have become the lively substance to the modern library’s reserves in satisfying varied needs of students, teachers, and researchers with minimum risk and time (Swain and Panda, 2009). For better planning, it is vital to have knowledge on the attitudes of users towards e-resources. Swain and Panda (2009), say the library users’ attitude to information is gradually shifting from the printed documents to electronic resources and thus, it has been their prerogative to know the details of the availability and organization of e-resources like online journals and databases, electronic theses and dissertations (ETDs), government publications, online newspapers, etc. in libraries. Given technology increased use, it is important to understand how technologically rich environments are influencing student attitudes toward e-resources access. Many factors influence attitudes. The introduction of open access journals and other resources for instance is creating another attitudinal tendency towards e-resources. Open access is one of the cheapest routes to electronic resources and over the last few years’ open access resources have grown and provided an affordable way to provide access to some journal content (Price, 2009). Supporters of open access argue that, when academic articles, dissertations and theses are put online and open to all, it helps in fighting duplication and plagiarism of other people’s intellectual works. Although the open access movement has brought access to many valuable resources, and provided libraries with an invaluable amount of resources, many open access projects still face an uncertain future (Price, 2009). Many critics are not sure that the open access model can survive because some are not considered “financially viable” or as high quality as traditionally purchased or subscribed content (Robinson 2006; Shao and Scherlen, 2007; Turk and Bjork 2008). Where do LIS postgraduate students fall in this case? What are their attitudes towards open access electronic resources? Attitudes towards e-resources access could be attributed to problems faced when accessing e-resources. For instance, in a situation where there are inadequate computer technologies to access e-resources or poor Internet connections, student’s positive attitudes could be affected. That is why the problems that affect e-resources access are addressed in higher learning institutions libraries. The arguments for students using electronic resources are compelling. An adequate knowledge of computers and retrieval techniques is desirable to search these resources effectively. It is necessary to establish what computer skills students require to access electronic information resources in libraries. Amidst all the efforts to access e-resources, LIS postgraduate students face a number of challenges. These are reported in another paper by the same author.

SCOPE OF THE STUDY The study is limited to farmers that cultivate land in Laduba community. Other inhabitants that engaged in other trades and other forms of farming apart from tilling ground were not included.

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Objective of The Study The specific objectives of the study are to: 1. Identify the information needs of farmers in Laduba community of Kwara State. 2. Determine the source of information and their preferences with regard to sources available to them. 3. Identify constraints the farmers face while searching for information.

Methodology The Laduba Community is located in Kwara State of Nigeria. They have various occupations, but the main occupation of the natives is farming. This study adopted a survey sampling technique. Structured questionnaire was designed as the instrument for data collection and was supplemented by personal interview with the expertise of the extension personnel of Nigerian Stored Products Research Institute (NSPRI). The population of this study is about 500 farmers who dwells in Budoagun Clan of Laduba community of Kwara State, Nigeria. The Budoagun clan is where this study is based, because the clan is a section of the Laduba community where farmers that cultivates land settled. To obtain information from the respondents, 40 copies of questionnaire were administered to the respondents while 28 copies were recovered and used for analysis. Agricultural extension workers from the Nigerian Stored Products Research Institute (NSPRI) were used as the research assistants to administer the questionnaire. The questionnaire was administered to the respondents who are mostly illiterate on one- to -one basis. The research assistants read the content of the questionnaire and the options available to each of the respondent and the answers from the respondents were reflected on the questionnaire. The questionnaire was divided into two broad sections. Section one deals with the bio data of the respondents. The other section has other units that examined the information seeking behavior of the respondents. The unit in the second section of the questionnaires are five and the sub heading of the units are arranged as follows from B to F respectively; types of crops planted, area of information needs, information need of farmers, medium of accessing information and challenges faced while seeking for information. Also the head of the community, noticeable leaders among the farmers and some youths were interviewed to compliment information gathered from the respondent through the questionnaire. Data collected for the study were subjected to analysis using frequency count, simple percentage and bar charts.

RESULTS AND DISCUSSIONS Bio Data of the Respondents • • •

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Age of the Farmers: The age of the farmers in the community of Laduba shows that 42.9% are between 31-40 years of age, followed by 32.1% of the respondents which is between 41-50 years of age, the research shows that 7.1% of the farmers are between 20-30 (Table 1 and Figure 5). Gender of the Farmers: From the result shown, 60.7% of respondents were male and 39.3% were females (Table 2 and Figure 6). Mode of Farming: In response to the mode of farming, it was discovered that 75% of the respondents are into fulltime, while 25% of the respondents are part-time farming (Table 3 and Figure 7).

 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria

•

• •

Level of Education: The level of education of respondents was grouped into non formal, primary and secondary. The response obtained shows that 50% of the respondents belongs to non-formal, while 35.7% attained the level of primary education, and 14.3% being the least attained the level of secondary education (Table 4 and Figure 8). Size of Farm: Majority of the farmers’ size of farm ranges from 1-2 acres (60.7%), the other size of farm used by other farmers include 2-4 and 4-6 acres with both with a percentage of 17.9% (Table 5 and Figure 9). How Frequent Do You Go to the Farm: Asked about how frequent they go to the farm, 92.9% of the respondents say they go to the farm every day, 3.6% of the respondents goes to the farm weekly and another 3.6% goes to the farm monthly (Table 6 and Figure 10).

Information on Other Types of Farming Apart from Tilling the Ground •

•

Type of Livestock: In response to types of livestock reared if any, 46.4% of the respondents engage in goat rearing, 39.3% of the respondents are into poultry farming, the percentage of those who are engaged in fish farming, pig rearing and cattle rearing is on the low side with 3.6%, 10.7% and 10.7% of the respondents respectively (Table 7 and Figure 11) Type of Crops Planted: Majority of the farmers’ plants cassava (71.4%), they also plant grain crops and melon with results stating 67.9% and 57.1% respectively, other crops planted include vegetables (50%), yam (42.9%), fruits (42.9%) and groundnut (32.1%) the least crop planted is rice (3.6%) (Table 8 and Figure 12)

Table 1. Age of the farmers Age Range

Frequency

Percent

Valid Percent

Cumulative Percent

20-30

2

7.1

7.1

7.1

31-40

12

42.9

42.9

50.0

41-50

9

32.1

32.1

82.1

51 and above

5

17.9

17.9

100.0

Total

28

100.0

100.0

Table 2. Gender of the farmers Frequency

Percent

Valid Percent

Cumulative Percent

Male

Gender

17

60.7

60.7

60.7

Female

11

39.3

39.3

100.0

Total

28

100.0

100.0

1431

 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria

Table 3. Mode of farming Mode

Frequency

Percent

Valid Percent

Cumulative Percent

21

75.0

75.0

75.0 100.0

Full time Part time

7

25.0

25.0

Total

28

100.0

100.0

Frequency

Percent

Valid Percent

Table 4. Level of education Education Level

Cumulative Percent

Non formal

14

50.0

50.0

50.0

Primary education

10

35.7

35.7

85.7

Secondary education

4

14.3

14.3

100.0

Total

28

100.0

100.0

Frequency

Percent

Valid Percent

Table 5. Size of farm Farm Size

Cumulative Percent

1-2 acres

17

60.7

60.7

60.7

2-4 acres

5

17.9

17.9

78.6

4-6 acres

5

17.9

17.9

96.4

6 acres and above

1

3.6

3.6

100.0

Total

28

100.0

100.0

Frequency

Percent

Valid Percent

Table 6. How frequently do you go to the farm? Time

Cumulative Percent

Everyday

26

92.9

92.9

92.9

Weekly

1

3.6

3.6

96.4

Monthly

1

3.6

3.6

100.0

Total

28

100.0

100.0

Areas of Information Needs Majority of the farmers stated that the area they need information most is on agriculture, about 89% of the respondents stated they needed information on agriculture, followed by education where 75% of the respondents also stated they need information in that aspect, about 71% of the farmers also stated they need information on health, 32.1% of the respondents stated they need information about community and rural development, 25% of the farmers said they need information on politics (Table 9 and Figure 13).

1432

 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria

Figure 5. ­

Figure 6. ­

1433

 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria

Figure 7. ­

Figure 8. ­

1434

 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria

Figure 9. ­

Figure 10. ­

1435

 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria

Table 7. Type of livestock Type of Livestock

Rating of Type of Livestock

Total

Very Highly

Highly

Fairly

Not at All

Cow

10.7%

7.1%

7.1%

75.0%

100.0%

Ram

21.4%

25.0%

17.9%

35.7%

100.0%

Pig

10.7%

7.1%

82.1%

100.0%

Goat

46.4%

21.4%

14.3%

17.9%

100.0%

Poultry

39.3%

28.6%

21.4%

10.7%

100.0%

Fish

3.6%

3.6%

7.1%

85.7%

100.0%

Total

22.0%

15.5%

11.3%

51.2%

100.0%

Table 8. Type of crops planted Crops Cassava

Rating of Crops Planted

Total

Very Highly

Highly

Fairly

Not at All

71.4%

21.4%

3.6%

3.6%

100.0%

Grains

67.9%

28.6%

3.6%

Melon

57.1%

7.1%

17.9%

17.9%

100.0%

100.0%

Rice

3.6%

3.6%

92.9%

100.0%

Groundnut

32.1%

21.4%

7.1%

39.3%

100.0%

Beans

14.3%

10.7%

32.1%

42.9%

100.0%

Yam

42.9%

39.3%

7.1%

10.7%

100.0%

Fruits

42.9%

25.0%

25.0%

7.1%

100.0%

Vegetable

50.0%

28.6%

17.9%

3.6%

100.0%

Total

42.5%

20.2%

13.1%

24.2%

100.0%

Information Need of Farmers on Agriculture The information needs of the farmers on agriculture which is their major area of information needs are categorized into disease prevention, knowledge of price of farm produce in the market, source of loan for farming, how to obtain fertilizer, location of market to sell their agricultural produce, best mode of storage, labour cost and land maintenance (Table 10). 82.1% of the farmers agreed that they need to know how to prevent diseases affecting their farm produce. 64.3% of the respondents claimed they need information on how to get best price for their farm produce, 53.6% of the respondents indicated they need information on the best place to seek for loan. 71.4% of the respondents stated they need information on how to get effective agro-chemicals to apply on their farms. 64.3% of the respondents claimed they need information for more locations to sell their agricultural produce. 75% of the respondents indicated they need information on the best available mode of storage for their farm produce. 50% of the respondents indicated that they need information on how they can get labour to till the ground for them. 64.3% of the respondents claimed they need information on how to get tractors to clear their land for farming (Table 10 and Figure 14). 1436

 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria

Figure 11. ­

Medium of Accessing Information On the topic of accessing information, the farmers were asked orally whether they were aware of the presence of the information center and the library in their locality and if they used the places to seek information. The response from them shows that a majority are aware of the presence of the building but do not go there to seek for information. the response from the respondents from the questionnaire shows that, (see Table 11) 17.9% of these farmers’ access information through the information center. 10.7% of the respondents were not aware of the information centre, 35.7% of the respondent who knew of the information centre occasionally use it. Another 35.7% said they don’t use the centre at all. On information seeking behavior of the farmers, 57.1%, 60.7% and 60.7% of the respondents claim that they mostly collect information through their colleagues(co-farmers), friends and Association Members, respectively (Table 11). Further results showed that there are other sources where the respondents obtain information apart from the ones earlier stated. The usage of such other means like Radio, community heads, Extension Workers, Newspapers and Magazines by the respondents was 57.1%, 50%, 34.5% and 28.6% respectively. (Table 11). From the oral interview conducted with the respondents, it can be noted that the discussion over the radio broadcast was a strong information source. The respondents value radio broadcasts highly, especially when the broadcast is delivered in their local languages. As shown in (Table 11) seminars and workshop were not popular medium for gathering information by the

1437

 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria

Figure 12. ­

Table 9. ­ Rating of Areas of Information Needs

Total

Very Highly

Highly

Fairly

Not at All

Politics

25.0%

39.3%

28.6%

7.1%

100.0%

Health

71.4%

25.0

3.6%

100.0%

Agriculture

89.3%

7.1%

3.6%

100.0%

Education

75.0%

21.4%

3.6%

100.0%

Community and rural development

32.1%

57.1%

10.7%

Total

58.6%

30.0%

7.9%

1438

100.0% 3.6%

100.0%

 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria

Figure 13. ­

respondents, only 25.9% of the respondents indicated that seminar and workshop had been a medium of getting information (Table 11 and Figure 15).

Challenges/Problems Highlighted by Respondents When Seeking Information On challenges faced by the respondents when seeking for information (Table 12) shows that the most common problem the respondents experienced in getting information from other sources apart from their colleagues, friends and relatives is the inability to read and write, with 67.9% of the respondents indicating that they cannot read and write, hence they are constrained in using any information that is in English language. Availability of limited time after farm work is also seen as a constraint to farmers to seek for needed information 46.4% of the respondent agreed very highly to it, while 32.1% of the respondent also agreed highly to it, making a total of 78.5% of the respondents. also other challenges faced by the farmers; another noticeable constraint faced by the farmers is the lack of money to purchase airtime for their mobile phone to obtain information. 32.1% of the respondents agreed very highly to this problem, while 10.7% agreed to it highly and 32.1% said it is occasional and 25.0% of the respondents did not agree at all. Similarly, 39.3% of the respondents indicated that inability to use mobile phone is a challenge, with 14.3% of the respondents agreeing to it highly and 32.1% of the respondents agree-

1439

 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria

Table 10. Information needs of farmers on agriculture Rating of Need of Farmers Very Highly

Highly

Fairly

Not at All

Total

How to take care of livestock

57.1%

21.4%

7.1%

14.3%

100.0%

Best price available for my farm produce

64.3%

21.4%

10.7%

3.6%

100.0%

How to prevent diseases for my farm produce

82.1%

17.9%

100.0%

How to get loans

53.6%

28.6%

7.1%

Best fertilizer for my farm

64.3%

25.0%

10.7%

10.7%

100.0%

100.0%

how to marketing my farm product

64.3%

25.0%

10.7%

100.0%

how to store my farm produce

75.0%

14.3%

7.1%

3.6%

100.0%

Cost of labour in my farming

50.0%

32.1%

14.3%

3.6%

100.0%

How to get tractors to clear my land

64.3%

21.4%

3.6%

10.7%

100.0%

How to get agro chemicals

71.4%

21.4%

7.1%

100.0%

How to treat myself from ailments

64.3%

32.1%

3.6%

100.0%

Education of my children

57.1%

39.3%

3.6%

100.0%

Where to get good treatment for my health problem

57.1%

39.3%

3.6%

100.0%

Political situation of the local/ state/federal government

39.3%

42.9%

17.9%

100.0%

Available workshop and capacity building

50.0%

28.6%

21.4%

100.0%

Total

61.0%

27.4%

8.6%

3.1%

100.0%

ing to it fairly, we can say the inability to use mobile phones can be seen as a challenge to accessing information. Also, 32.1% of the respondents indicated that language barrier is a hindrance because from the oral interview, it is noticeable that most of the information available to the respondents from radio, newspapers and documents from government extension officers are written in English language. 39.3% of the respondents indicated very highly that lack of constant electricity is a challenge, while 32.1% of the respondents indicated highly, 25% of the respondents indicated fairly, 3.6% of the respondents did not see it as a challenge at all. From the oral interview, the constraint of electricity was attributed to contribute to their inability to charge their mobile phones, watch television and listen to radio broadcast, 42.9% of the respondents agreed very highly that the fear of going to urban areas to seek for information is a challenge, while 25% of the respondents agreed highly, 25% of the respondents agreed fairly, 7.1% of the respondents did not agree at all. 42.9% of the respondents claimed very highly that lack of reliable source of information in the community is a challenge to accessing information, 25% of the respondents agreed highly, while 21.4% of the respondents agreed to it fairly, while 10.7% of the respondents did not agree at all. The next variable is to confirm how satisfactory the respondents get access to government extension worker so as to get information on issues relating to their farm, the results shows that 17.9% of the respondents indicated very highly that they do not have access to extension workers, while 10.7%

1440

 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria

Figure 14. ­

of the respondents also agreed highly to it, 28.6% of the respondents also agreed fairly to it, while 42.9% of the respondents indicated that they have access to government extension workers. The study also tried to find out if conflict among various associations that exist in the community has ever been a hindrance to seeking information by the respondents, the findings in this case shows that 28.6% of the respondents indicated very highly that conflict among association of farmers can prevent information from getting to each other, 15.7% of the respondents agreed highly to it, 10.7% of the respondents agreed fairly to it, while 45% of the respondents did not agree at all. It could be observed that cumulatively, the conflict in association could be a hindrance to seeking and accessing information. However, despite all the identified problems, it is noticeable that about three of the variables does not constitute any hindrance to the process of accessing information to the respondents. For example, availability of network for mobile communication was not seen as a problem for getting information, only 25% of the respondents agreed very highly that lack of network for mobile communication is a challenge, while 10.7% of the respondents also agreed to it highly, 7.1% of the respondents agreed to it fairly, and 57.1% of the respondents did not agree to it at all. Similarly, body disability of any form was not accepted by the respondent as hindrance to seek information, from the analysis, 3.6% of the respondents indicated very highly that body

1441

 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria

Table 11. Medium of accessing information Rating of Medium of Accessing Information Very Highly

Highly

Fairly

Not at All 96.4%

Total

Cyber café

3.6%

Colleagues

57.1%

39.3%

3.6%

100.0% 100.0%

Friends

60.7%

32.1%

7.1%

100.0%

Member

60.7%

28.6%

7.1%

3.6%

100.0%

Newspaper/magazine

28.6%

21.4%

50.0%

100.0%

Radio

57.1%

25.0%

17.9%

Centre’s in the town

17.9%

35.7%

10.7%

35.7%

100.0%

Television

42.9%

21.4%

17.9%

17.9%

100.0%

Library

10.7%

10.7%

78.6%

100.0%

seminar and workshop

25.9%

1.1%

8.5%

64.4%

100.0%

Extension office

34.5%

31.0%

31.0%

3.4%

100.0%

Community head

50.0%

32.1%

17.9%

Religion

53.6%

39.3%

7.1%

opinion leaders

39.3%

25.0%

28.6%

7.1%

100.0%

political leaders

28.6%

25.0%

42.9%

3.6%

100.0%

Total

38.1%

23.8%

15.5%

22.6%

100.0%

100.0%

100.0% 100.0%

disability is a challenge, 10.7% of the respondents also agreed highly that it is a challenge, while 3.6% of the respondents agreed to it fairly. However, 82.1% did not agree at all that body disability hinders them from seeking information. The study also endeavored to find out if cultural difference among the farmers has been a hindrance to seek information, the respondents’ response to this shows that 25% of the respondents indicated highly that cultural difference is a challenge faced by them in accessing information, 5.7% of the respondents also agreed highly, 15% of the respondents agreed fairly to it, however 54.3% of the respondents did not agree at all (Table 12 and Figure 16).

DISCUSSION OF FINDINGS Information Needs of Respondents Information on crops disease prevention, marketing agricultural products, agricultural loan and agro chemicals were the major information needs for farmers in the study area. This implies that farmers lack access to market information for their crops. This is consonance with Shepherd, (2000), who pointed out that information on, quantities traded, market prices and other marketing-related matters rarely reaches farmers in developing countries. Also, the study revealed that most farmers did not know where to get loans, similarly the study also indicated that the farmers need information on how to hire tractors to for land maintenance or purchase agricultural tools such as power tillers, which could be used to improve their agricultural productivity. Munyambonera et al., (2012) adds that availability and access to adequate,

1442

 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria

Figure 15. ­

timely and information on low cost credit from different institutional sources is of great importance especially to small and marginal farmers.

Medium of Accessing Information Colleagues (co-farmers), personal experience, neighbors or friends and agricultural extension officers were the major sources of information used by the farmers in accessing agricultural information. The implication here is that most of the respondents relied on interpersonal sources in accessing agricultural information, probably because of their regularly availability and accessibility. Lwoga et al., (2011) for instance stressed that interpersonal sources such as friends, relatives and neighbours are all the time become the main providers of the agriculture information due to their credibility, reliability and most of all, they are trusted by the rural community. However, none of the respondents reported to use neither internet nor library and information centres in accessing agricultural information. This is probably because of low level of education, lack of electricity, lack of libraries or information centres in the rural areas, lack of of the role of internet in provision of agricultural information to farmers and lack of lack

1443

 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria

Table 12. Challenges/problems faced Challenges/Problems Faced

Rating of the Challenges Faced Very Highly

Highly

Mobile communication

25.0%

Purchase credit

32.1%

Inability to use phone

Total

Fairly

Not at All

10.7%

7.1%

57.1%

100.0%

10.7%

32.1%

25.0%

100.0%

39.3%

14.3%

32.1%

14.3%

100.0%

Body disability

3.6%

10.7%

3.6%

82.1%

100.0%

Extension workers

17.9%

10.7%

28.6%

42.9%

100.0%

Language barrier

32.1%

3.6%

35.7%

28.6%

100.0%

No electricity

39.3%

32.1%

25.0%

3.6%

100.0%

Inability to read and write

67.9%

25.0%

7.1%

Limited time to seek for information

46.4%

32.1%

7.1%

14.3%

100.0%

Fear of going to urban areas

42.9%

25.0%

25.0%

7.1%

100.0%

Conflict among association member

28.6%

15.7%

10.7%

45.0%

100.0%

Lack of information center

35.7%

28.6%

17.9%

17.9%

100.0%

Unreliable source of information

35.7%

39.3%

17.9%

7.1%

100.0%

Lack of authentic transfer information

42.9%

25.0%

21.4%

10.7%

100.0%

Cultural difference

25.0%

5.7%

15.0%

54.3%

100.0%

100.0%

of ICTs infrastructure in rural areas. Finding of this study are not surprising as they are in line with what have been reported previously by Benard (2011), Mtega and Benard (2013); Shaffril et al. (2010) and Samah et al. (2011). For instance, have established a few reasons why farmers are reluctant to use advance technology in accessing agricultural information such as internet, and among the reasons are do not know the benefits of the advance technology; they are illiterates: do not have skills or expertise in using the advance technology; lack of time spent on ICT and difficulties in using ICT. This therefore, calls for the government to create enabling environment for the farmers to use this modern technology so as they can access timely and current agricultural information.

Challenges Faced by Respondents in Accessing Agricultural Information The majority of the respondents cited inability to read and write in English language in the study area was one the challenges facing farmers in accessing information. Through the oral interview with the key informants and personal observation via the researcher it was noted that there were no information services available in the area of the study such as village/ward libraries and the information centre in the community is only present but it is not utilized by the farmers. This is a common problem in most rural farmers. Therefore, agricultural extension workers should regard it as a challenge and provide farmers with access to current and relevant agricultural information. The findings further revealed the inadequate numbers of extension agents as major challenges constraining farmers from accessing information. For instance, in the study, the farmers indicated that lack or non-availability of extension officers is a challenge. In view of this, they do not have enough information to access from the agricultural extension

1444

 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria

Figure 16. ­

officers. This also is in line with what have been found by Aina’s (2006) findings, which revealed that the ratio of agricultural extension workers to the population in Africa is low. Similarly, inadequate funds were another challenge hindering farmers from accessing agricultural information as it was pointed by majority of the respondents. Due to financial problems, some of the farmers cannot afford to buy airtime, also, due to lack of electricity, the farmers are usually unable to charge their mobile phones to access and communicate information. Therefore, agricultural information sources and services where they exist should be widely published and promoted, not only to create awareness but also to promote and encourage usage by farmers.

CONCLUSION According to Sarah et al (2012) in recent decades the value of information has increased considerably as the agricultural systems in developing countries become knowledge intensive. Therefore, the need to determine how farmers access information, the medium they use and the constraint that hinders their free

1445

 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria

access to required information is very important because like any other business farmers need concise, timely and comprehensive information to avoid loss of their farm produce, both on the farm and storage level, and also require appropriate environment to sell their produce for profit, all these and others are important factors to increase farmers productivity and consequently availability of food for citizens and sustenance of the nation. It is in this regard that this research is very important and findings can be of immense importance to guide research institute, state agricultural policy makers and international agencies who are also interested in the farming system in Nigeria.

RECOMMENDATIONS It could be observed that from the age group, majority of farmers in laduba community are within the age range of 31-40, it is important that necessary incentives and encouragement is given to attract the youths of younger age to farming for availability of food for the nation. It is noticeable that females form part of the farming population in Laduba, this is quite encouraging, for the population of the female to be improved, adequate access to information that will educate them and invoke their interest in farming is necessary. The education status of farmers in in this study reveals that great percentage of them does not have formal education, only 14.3% of them had secondary education, this may hinder access to vital farming information from documentaries of national and international agricultural agencies. Hence, there is need for the farmers to be introduced to formal education through adult education programme on radio and television using the laduba information centre effectively. From the study, the farmers significantly declared that information in agriculture is their major area of interest, therefore it is now important that all media that will assist the farmers to get concise, accurate and comprehensive information be made available to them. This may increase their interest in farming and consequently boost their economic level and consequently eradicate poverty among them and the nation in general. Concerted effort should be made by government extension workers to provide the farmers information on how to prevent diseases on their crops on the field and also the best storage method for their farm produce, also they should be provided information on the best agro-chemicals to apply on their farm. The information centre presently in the village should be improved for farmers to use it, human resource personnel that will promote its usage should be employed, the information center should have medium of disseminating information like radio and television and a well-stocked library could be developed in the centre, stocked with information materials to promote adult education programmes and enlightenment on different areas of farming. The documents acquired for these purpose should be in local languages and those written in simple understandable English language words. The government should improve on the electricity in some of the rural areas including Laduba community and negotiate with operators of mobile communications, so that they can have subsidized airtime to communicate and receive information. The group of extension workers like those from Kwara State Agricultural development project (ADP) and Nigerian Stored Products Research Institute (NSPRI) should interact effectively to give the farmers timely and necessary information they require and the extension workers should endeavor to sustain friendliness among the members of associations that exist in the community so that any conflict will not arise among them that will disrupt information sharing. 1446

 Information Need and Seeking Behavior of Farmers in Laduba Community of Kwara State, Nigeria

REFERENCES Adereti, F. O., Fapojuwo, O. F., & Onasanya, A. S. (2006). Information on utilization on cocoa production techniques by farmers in Oluyole Local Government Area of Oyo State, Nigeria. European Journal of Soil Science, 3(1), 1–7. Aina, L. O. (2006, August 20-24). Information Provision to Farmers in Africa: The Library- extension service linkage. Proceedings of the World library and information congress, 72nd IFLA general conference and council ’06, Seoul, Korea. Retrieved from http://www.ifla.org/iv/ifla72/index.htm Ajayi, O.O. (2002). African Response to the Information Communication Technology Revolution: A case study of the ICT development in Nigeria (ATPS Special Paper Series No 8). Anwar, M. A. (2007). Research on information seeking and use in Pakistan: An assessment. Pakistan Journal of Library and Information Science, 8, 15–32. Aziagba, P. C., & Okede, G. W. (2011). information seeking behavior of cassava farmers in Upata clan, Ekpeye community of Rivers State, Nigeria. Babu, S. C., Glendenning, C. J., Asenso-Okyere, K., & Govindarajan, S. K. (2012). Farmer’s information needs and search behaviors. IFPRI Discussion paper 01165. Borgman, C. L. (2000). From Gutenberg to the global information infrastructure: access to information in the network world. Cambridge, MA: MIT Press. Brophy, P. (1993). Networking in British academic libraries. British Journal of Academic Librarianship, 8(1), 49–60. Butterworth, R. (2006, June 15). Information seeking and retrieval as a leisure activity. DL-CUBA 2006 - Workshop on digital libraries in the context of users’ broaden activities, Chapel Hill, USA. Proceedings of JCDL ’06. Retrieved from http://www.uclic.ucl.ac.uk/events/dl-cuba2006/papers/Butterworth.pdf Dadzie, P. S. (2005). Electronic resources: Access and usage at Ashesi University College. CampusWide Information Systems, 22(5), 1065–0741. Retrieved from http://www.emeraldinsight.com/Insight/ ViewContentServlet doi:10.1108/10650740510632208 Devadason, F. J., & Pratap, P. L. (1997). Methodology for the identification of information needs and uses of users. IFLA Journal, 23(1), 41–51. doi:10.1177/034003529702300109 Ellis, D. (1993). Modeling the information-seeking patterns of academic researchers: A grounded theory approach. The Library Quarterly, 63(4), 469–486. doi:10.1086/602622 Ellis, D., Cox, D., & Hall, K. (1993). A Comparison of the Information Seeking Patterns of Researchers in the Physical and Social Sciences. The Journal of Documentation, 49(4), 356–369. Ellis, D., & Haugan, M. (1997). Modelling the Information Seeking Patterns of Engineers and Research Scientists in Industrial Environment. The Journal of Documentation, 53(4), 384–403. doi:10.1108/ EUM0000000007204

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Hayden, K.A. (1999). Information Seeking Models. Retrieved from http://www.ucalgary.ca/~ahayden/ seeking.html Järvelin, K., & Wilson, T. D. (2003). On conceptual models for information seeking and retrieval research. Information Research, 9(1). Retrieved from http://InformationR.net/ir/9-1/paper163.html Kakai, J. M., Ikoja-Odongo, R., & Kigongo-Bukenya, I. M. N. (2004). A study of the information seeking behavior of undergraduate students of Makerere University, Uganda. World Libraries, 14(1). Retrieved from http://www.worlib.org/vol14no1/print/kakai_print.html Krikelas, J. (1983). Information-seeking behaviour: Patterns and concepts. Drexel Library Quarterly, 19(2), 5-20, 78. Kuhlthau, C. C. (1993). Seeking meaning: a process approach to library and information services. Norwood, NJ: Ablex Publishing. Lwoga, E. T., Stilwell, C., & Ngulube, P. (2011). Access and use of agricultural information and knowledge in Tanzania. Retrieved from http://ir.muhas.ac.tz:8080/jspui/bitstream/123456789/1368/1/ library_review_paper_lwoga_Stilwel_Ngulube.pdf Meho, L. I., & Tibbo, H. R. (2003). Modeling the information-seeking behavior of social scientists: Ellis’s study revisited. Journal of the American Society for Information Science and Technology, 54(6), 570–587. doi:10.1002/asi.10244 Menzel, H. (1996). Information needs and uses. In C.A. Cuadra (Ed.), Annual Review of Information Science and Technology (ARIST) (Vol. 1, pp. 41-69). USA: Interscience Publishers. Momoh, A. U, Osaheni, O & Oshioneb, F. (2015). Information seeking behavior of nurses in central hospitals in Delta State. Pyrex Journal of Library and Information Science, 1(3), 26. Mtega, W., & And Benard, R. (2013). The state of rural information and communication services in Tanzania: A meta-analysis. International Journal of Information and Communication Technology Research, 3(2), 64–73. Munyambonera, E., Nampewo, D., Adong, A., & Mayanja, M. (2012). Access and Use of Credit in Uganda: Unlocking the Dilemma of Financing Small Holder Farmers. Retrieved from http://ageconsearch. umn.edu/bitstream/150229/2/policybrief25.pdf Okunade, O. S. & Williams, J. O. (2014). Agriculture in Nigeria: problems, consequences and the way forward. Ilorin: Adewumi press. Price, A. C. (2009). How to make a dollar out of fifteen cents: Tips for electronic collection development. Collection Building, 28(1), 31–34. doi:10.1108/01604950910928493 Ray, K., & Day, J. (1998). Student attitudes towards electronic information resources. Information Research, 4(2). Retrieved from http://informationr.net/ir/4-2/paper54.html Robinson, A. (2006). Open access: The view of a commercial publisher. Journal of Thrombosis and Haemostasis, 4(7), 1454–1460. doi:10.1111/j.1538-7836.2006.02009.x PMID:16839337

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Saravan,, R., & Raja,, P., & Tayeng, S. (2009). Information input pattern and information need of Tribal Farmers in Arnuchal Pradesh, Indian Journal of Extension Education, 45(1&2), 51-54 Shaffril, H. A. M., Samah, B. A., Hassan, M. A., & Silva, J. L. (2010). Socio-economic factors that impinge computer usage in administration works among village leaders in Malaysia. Scientific Research and Essays, 5, 3623–3633. L. Shanta Meitei & Th. Purnima Devi. (2009). Farmers information Needs in Rural Manipur: an assessment. Annals of Library and information studies, 56(2), 35-40 Shao, X., & Scherlen, A. (2007). Perceptions of open access publishing among academic journal editors in China. Serials Review, 33(2), 114–121. doi:10.1080/00987913.2007.10765105 Sharma, P. S. K. (1990). Universe of knowledge and research methodology. Delhi: Ken Publications. Shuling, W. (2007). Investigation and analysis of current use of electronic resources in university libraries. Library Management, 28(1/2), 72–88. Retrieved from http://www.emeraldinsight.com/Insight/ViewContentServlet?Filename=Published/EmeraldFullTextArticle/Articles/0150280107.html doi:10.1108/01435120710723563 Solomon, P. (2002). Discovering information in context. Annual Review of Information Service and Technology, 36(1), 229–264. doi:10.1002/aris.1440360106 Stigter, C. J. (2002). Opportunities to improve the use of seasonal climate forecasts. Bangkok, Thailand: Asian Disaster Preparedness Center (ADPC). Swain, D. K., & Panda, K. C. (2009). Use of electronic resources in business school libraries of an Indian state: A study of librarians’ opinion. The Electronic Library, 27(1), 74–85. doi:10.1108/02640470910934605 Swain, D. K., & Panda, K. C. (2009). Use of electronic resources in business school libraries of an Indian state: A study. Collection Building, 28(3), 108–116. doi:10.1108/01604950910971134 Swanson, B. (2008). Global review of good agricultural extension and advisory service systems. Food and Agricultural Organization, Rome. Swanson, B., & Rajalahti, R. (2010). Strengthening agricultural extension and advisory systems: procedures for accessing, transforming and evaluating extension systems. Agricultural and rural development discussion (p. 45). Washington, DC: World Bank. Tella, A., Tella, A., Ayeni, C. O., & Omoba, R. O. (2007). Self-Efficacy and Use of Electronic Information as Predictors of Academic Performance. Electronic Journal of Academic and Special Librarianship, 8(2). Retrieved from http://southernlibrarianship.icaap.org/content/v08n02/tella_a01.html Thachill, G. (2008). Academic Libraries Redefined: Old Mission with a New Face. Scroll, 1(1). Tologbonse, D., Fashola, O., & Obadiah, M. (2008). Policy Issues in Meeting Rice Farmers Agricultural Information Needs in Niger State. Journal of Agricultural Extension, 12(2), 84–94.

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Toner, L. (2008). Non-use of Library Services by Students in a UK Academic Library. Evidence Based Library and Information Practice, 3(3). Retrieved from http://ejournals.library.ualberta.ca/index.php/ EBLIP/article/view/1330/1241 Tsakonas, G., & Papatheodorou, C. (2006). Analysing and evaluating usefulness and usability in electronic information services. Journal of Information Science, 32(5), 400–419. doi:10.1177/0165551506065934 Weiler, A. (2005). Information-Seeking Behavior in Generation Y Students: Motivation, Critical Thinking, and Learning Theory. Journal of Academic Librarianship, 31(1), 46–53. doi:10.1016/j.acalib.2004.09.009 Wilson, T. D. (1999). Models in information behavior research. The Journal of Documentation, 55(3), 249–270. doi:10.1108/EUM0000000007145 Wilson, T. D. (2000). Recent trends in user studies: Action research and qualitative methods. Information Research, 5(3). Retrieved from http://informationr.net/ir/5-3/paper76.html Zhang, Y. (2001). Scholarly use of internet-based electronic resources. Journal of the American Society for Information Science, 52(8), 628–654. doi:10.1002/asi.1113

ADDITIONAL READING Lenz, E. R. (1984). Information seeking: A component of client decisions and health behavior. ANS. Advances in Nursing Science, 6(3), 59–72. doi:10.1097/00012272-198404000-00010 PMID:6426379 Okwu, O. J., & Umoru, B. I. (2009). A study of women farmers’ agricultural information needs and accessibility: A case study of Apa Local Government Area of Benue St. Retrieved from http://www. academicjournals.org/AJAR Saima Sadaf, Asif Javed, & Muhammad Luqman. (n. d.). Preferences of Rural Women for Agricultural Information Sources: A Case Study of District Faisalabad–Pakistan. Journal of Agriculture & Social Sciences. Retrieved from http://www.fspublishers.org Sharma, A. K. (2007). Information Needs and Sharing Pattern among Rural Women: A Study. IASLIC Bulletin, 52(3), 156–167.

KEY TERMS AND DEFINITIONS Community: A group sharing a common understanding and often of the same language, manners, tradition and law. Farming: The act of cultivating land for the purpose of planting desired agricultural crops for sustenance of life and profit making.

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Information: A processed data being searched for to use to enhance occupation and other things that sustains life. Information Need: A piece of information, whether recorded or not, which an individual or a member of a group requires for effective functioning in their daily activities. Information Seeking Behavior: An individual’s way and manner of gathering and sourcing for information for personal use.

This research was previously published in Information Seeking Behavior and Challenges in Digital Libraries edited by Adeyinka Tella, pages 238-271, copyright year 2016 by Information Science Reference (an imprint of IGI Global).

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Chapter 65

Congo Basin’s Shrinking Watersheds: Potential Consequences on Local Communities

Bila-Isia Inogwabini Saint Pierre Canisius Institute of Agriculture and Veterinary Sciences (ISAV), Congo & Swedish University of Agricultural Sciences, Sweden

ABSTRACT Rainfall time series data from three sites (Kinshasa, Luki, and Mabali) in the western Democratic Republic of Congo were analyzed using regression analysis; rainfall intensities decreased in all three sites. The Congo Basin waters will follow the equation y = -20894x + 5483.16; R2 = 0.7945. The model suggests 18%-loss of the Congo Basin water volume and 7%-decrease for fish biomasses by 2025. Financial incomes generated by fishing will decrease by 11% by 2040 compared with 1998 levels. About 51% of women (N= 408,173) from the Lake Tumba Landscape fish; their revenues decreased by 11% between 2005 and 2010. If this trend continues, women’s revenues will decrease by 59% by 2040. Decreased waters will severely impact women (e.g. increasing walking distances to clean waters). Increasing populations and decreasing waters will lead to immigrations to this region because water resources will remain available and highly likely ignite social conflicts over aquatic resources.

INTRODUCTION Climate change is a scientifically established fact now (Walther et al., 2005), even though the magnitude of its multiple, diversified and multidimensional effects remain mostly in the domain of mathematical modeling. Discussions on the mitigation of climate change and adaptation processes (social, cultural and biological) remain at the core of scientific and political debates (Aiken et al. 1992; Fletcher, 1997; Fletcher, 2000; Hobbs & Knausenberger, 2003; Hughes, 1986; Inogwabini et al., 2006) because they are diversified and multidimensional, and will vary throughout the world (IPCC, 2007). The nature and the magnitude of these impacts have, however, yet to be described for different geographic environments DOI: 10.4018/978-1-5225-9621-9.ch065

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and locations. This is even more important for the tropical region of Central Africa where documented evidence is scanty (Halpin, 1998; Inogwabini et al., 2006; Sonwa et al., 2009). Informed guesses and mathematical projections convey the message that climate change’s effects in Central Africa may range from drier conditions in areas adjacent to as deserts (Sahara and Kalahari) where water occurs in shortage to high floods in coastal habitats directly adjacent to oceans due to increased water levels as a result of the melting of polar ice (Halpin, 1998). Unfortunately, however, long-term field data that can document changes which highlight the effects of climate changes over the past years are difficult to find for Central Africa (Edwards & White 2000; Pimm, 2007; Sonwa et al., 2009). Lack of data fosters the use of surrogate data that can predict the effects of climate variation in Central Africa. One of those surrogates has been the linking of phenological data to weather patterns (Tutin & White, 1998), direct measurements of water levels (Colombant, 2005), using direct meteorological data and looking at their trends (Inogwabini et al., 2006). The use of long time series meteorological data as a proper detector of the effects of the climate change is fully justified by the fact that if climate change will affect water level, then drier conditions in the terrestrial Central Africa region are, logically, linked to water cycles, especially rainfall regimes over the continent. However, continuous time series data on rainfalls are difficult to find in Central Africa to document the trends and extents of felt changes (Halpin, 1998). Furthermore, where there are continuous long time series data, the analytical capabilities have made it difficult to determine understandable trends that crude data can convey. Even less available are data on effects of climate change on local economies, health, security and biodiversity (Sonwa et al., 2009; Stern, 2007).

MAIN FOCUS OF THE CHAPTER This chapter presents three long term data from three locations in the western Democratic Republic of Congo (Figure 1), with the aim of presenting these long time series data in a single analytical framework and discussing patterns that emerge from that analysis in the context of global climate change. The chapter links trends in rainfall and surface area Congo Basin watershed and projects potential effects of these trends to the level of the central Africa region. Combining these projected effects with field data freshwater resources, the paper discusses inferred effects on climate changes on local populations.

STUDY SITES Rainfall data were collected from (1) Mabali, (2) Kinshasa and (3) Luki. Mabali is located near the equatorial line (Inogwabini et al., 2006). Located in the Cuvette Central, weather patterns are believed to be stable (Bultot & Griffiths, 1972). The Cuvette Central is a lowland, flat and heavily flooded equatorial region. It is characterized by terra firma forest (forest whose floor remains dry for most of the year), swampy forest, and diverse types of savannahs inundated and terra firma (Evrard, 1968; Leonard, 1951 & 1952; White, 1983). The Cuvette Central is the lowest point within the Congo Basin and once constituted a water retention point during the late Miocene when many African inland basins were still endorheic (Roberts, 1975; Thieme et al., 2005). Kinshasa is a town of nearly 9,000,000 people (Aveling et al., 2003) and located south-west of the Mabali. Adjacent habitats to this mega city are essentially composed of wooded savannas on a sandy soil. Kinshasa is located at Pool Malebo, an open water sur1453

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Figure 1. Locations from which weather data were collected

face leading to several multidirectional wind currents. These currents have an impact on rainfall regimes observed in Kinshasa. Luki are located further south and closer to the Atlantic Ocean. With a population of 150, 4361 people (Iloweka, 2004), Luki is a forest island within a predominantly human landscape and degraded forests. Its position near the Atlantic Ocean implies that rainfall regime and other climatic events occurring in that region are potentially influenced by climatic events affecting the Atlantic Ocean. The Congo Basin watershed covers 3,730,474 km2, and is home to ~60 to 78 million people (Sonwa et al., 2009; WRI, 1998). About 62% (37 – 48 million people) of that population is still rural (Sonwa et al., 2009), even though the urban growth rate of the entire region is high and estimated at 5% per year (Atsimadja, 1992; WRI, 1998). This vast zone covers different habitat types, with tropical forest representing ~40% (14,920,190 km2). The geography of the zone has an impressive biological diversity.

MATERIAL AND METHODS Rainfall data from Mabali have been collected continuously from 1970 through 2004 (Inogwabini et al., 2006) while those from Luki were collected between 1958 and 2004. The data set from Kinshasa covers the period between 1971 and 2004. Total annual rainfall intensities (mm) of were plotted over time, i.e. 34 years for the Mabali data set, 46 years for Luki and 33 years for Kinshasa (Figure 1). To detect the trends in these data sets, the linear regression was used on annual rainfall intensities (mm). Those data, particularly on the Mabali Scientific Reserve, were published earlier (e.g. Inogwabini et al., 2006).

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Other data came mainly from the search of existing literature. Human population data were gathered from Atsimadja (1992), Aveling et al. (2003), CEFDHAC (2001), and Sonwa et al. (2009), WRI (1998), Trends in populations were derived using the model presented by De Saint Moulin (1991 & 2003). Data on fish stocks were also gathered from different sources. Fish biomasses and estimated financial incomes generated from fishing were drawn from Bene (2005), CEFDHAC (2001), Corsi (1984a, b), Colom et al. (2006). Leonard (1987), and Data on the decline in fish stocks were those used by Inogwabini & Lingopa (2006). These data indicated that over a 34 year period reported by Inogwabini et al., (2006), the water depth of Lake Tumba decreased from 8 m down to 6 m, which is a 25% decrease over 34 years, leading to a rate of decrease of 0.0074%/year. This rate was used in combination with regional elevation data to produce the map depicting the future water situation in the Congo Basin watershed. Also, repeating a survey conducted by the Food Aid Organization (FAO) in 1998, Inogwabini & Lingopa (2006) reported a fish stock decrease of 4.5% for the fish stocks of Lake Tumba over a period of 17 years, which equals a decrease rate of 0.25%/year. As suggested by Huggett (1993) and Hulme et al. (2001), these rates, maintaining each of them as constants and assuming that they would apply to the whole basin, were used in linear regression models to project decrease in watersheds and fish stocks. The financial incomes generated by fish production provided by Bene (2005) were used to determine the per-ton cost of fish. Maintaining the price constant over years, I simply multiplied projected fish stocks per year to obtain trends in incomes. The rate of production was calculated to measure the trend in how many tons of fish will remain available to the increasing rural populations of the region over the next 60 years if current conditions remain constant. This important measure was defined as a simple ratio of projected tons of fish over projected total populations. Data on effects of shrinking waters in the study region on women were those that came from the socioeconomic study carried out by Colom et al. (2006). These included the gender-sorted fish market data, assessment of felt environmental threat disentangled between women and men, traditional work division, etc. They were collected through a variety of methods, including structured interviews, focus groups, and literature reviews Colom et al. (2006). These data are presented in this chapter as simple means and where projected, they were assumed to progress constantly over years. Data on health came from official reports of the provinces and particular health facilities (MSPPE, 2010; SS, 2007). To confirm that these data reflected the reality on ground, I have checked trends with medical doctors that worked in the health divisions of Bikoro, Ntondo and Mbandaka.

RESULTS The rainfall intensities decreased in all three sites over time for each sites following the regression equation y = -20.508x + 1723.5 (R2 =0.7011), y = -13.643x + 1175.4 (R2 = 0.5313) and y = -23.338x + 1426.6 (R2 = 0.6709) respectively for Mabali (Figures 1 and 2), Luki (Figure 1 and 3) and Kinshasa (Figure 1 and 4). The rainfall for Luki and mean rainfall for Kinshasa in 2004 represented only 59% and 61% of its levels 33 years earlier, in 1971 following the drought of 1970 when Luki received only 327.8 mm of rain. The situation has been even more dramatic for Mabali where the maximum rainfall represents > 25% of its levels in 1970 or 34 years earlier.

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If the rate of water loss in Lake Tumba is applied for the entire region and remains constant, watershed will decrease following the regression equation y = -20894x + 5E+07 (R2 = 0.7945). This model indicates that by 2025, the Congo Basin watershed will have lost 18% of its total water mass as compared with its 1998 levels. The loss will deepen to -26.6% by 2040, -39% by 2065 and then around -43% by 2070. Equally, if the loss in the fish biomasses in Lake Tumba are applied to the whole region and remain constant over years, the fish stock will decrease by 7% between 1998 and 2025. This decrease will deepen down to -11% by 2040, -16% by 2058 and by -20% in 2075. The same proportions will be observed if fish prices in the markets are constant, decreasing from 47.8 million American dollars/year in 2005 (Bene, 2005) down to ~42.5 million American dollars/year (~11%) by 2040. At the same time, the human population will grow from 60 – 78 million people to 109.6 million (or an increase of 40.5%) in 2025, then to 141.18 million in 2040 (an increase of 81.0%), 179.08 million in 2058 (129.6%) and 214.89 million (175.5%) in 2075. Combining trends in fish resources and human growth, these changes imply that there will be a decrease of ~70.1% of both tons/person/year, which parallels the projected magnitude of loss of income from 2009 through 2075. Figure 2. Rainfall trends in the Mabali Region between 1970 and 2004

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Figure 3. Rainfall trends in the Luki Region between 1958 and 2004

The 2005 socioeconomic data showed that 408,173 of ~1,012,000 all women (~51%) in the landscape were involved in fishing, and that each woman generated a mean annual income of ~2,100US$. This represented an overall income of 857,164,000 US$ annually; a significant % of the overall national budget for that year. In 2010, the fishing-generated financial income was estimated at ~ 1870 US$ per woman or a net decrease of 11%. If these trends are maintained constant, women generated income will decrease by 25% in 2020 and 59% in 2040 while the number depending on fishing for financial income will be 836,755 women, above the double of the women population in 2005. Even though the region is a swamped zone, the data showed that more women (85%; N= 360) and girls (90%; N= 200) were involved in the activities of fetching water than men (25%; N = 140) and young boys (50%; N=140). The same socioeconomic data showed that that on average women walked ~ 6 km (round trip) to fetch drinkable water; this was done twice daily. This daily 12-km trip consumed 4 hours on average, representing 40% of a ten hour working day. Logically, three quarters of women reported that fetching water from long distances impeded their ability to conduct more lucrative activities such as commerce or even fishing, which are the most important economic activities in the region. More than three quarters of the interviewed women were afraid of fetching water from long distance sources because they feared being raped by former army soldiers. Interestingly, the same data set also showed reversed trends in girl education patterns; in areas where water sources were far away from the villages,

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Figure 4. Rainfall trends in Kinshasa between 1971 and 2004

on average only 20% of girls had actually completed their secondary education while in towns where water sources are adjacent to houses, the figure increased to 45%. Published reports (Secrétariat à la Santé 2007) from the study region indicated a global increase in diarrheas (globally 2.7% for the province of Equateur and 3% for that of Bandundu) and amoebic dysenteries (globally 8% for the province of Equateur and 7.2% for that of Bandundu) at the end of January through the end of February and from end of May through end of July. When looking at reports from Bikoro and Ntondo (near Lake Tumba) these figures are even higher for the same diseases. Diarrheas increase by 25% (Bikoro) and 30% (Ntondo) while amoebic dysenteries increase by 15% (Bikoro) and 24% (Ntondo). Health reports from Bikoro and Ntondo also show an increase in what they call skin itching (40% and 30% respectively for children under the age of 18); and 2007 health report from Ntondo also mentioned an increase in what they shyly called women specific genital ailments and infections by 23.6% during the same periods of the year. Periods from at the end of January through the end of February and from end of May through end of July are dry seasons when clean water is in shortage in the region.

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DISCUSSION General Foresighted Effects The three data sets on rain intensities (Figures 1, 2 & 3) clearly indicate that there has been ‘continuous’ drying up of the zone over the last decades. The mean rainfalls for Luki and for Kinshasa in 2004 represented only 59% and 61% of its levels 33 years earlier while a more dramatic change was depicted for Mabali with the maximum rainfall in 2004 representing only > 25% of its levels in 1970. These inter-site variations would be logically expected, given the fact that weather patterns are functions of multiple parameters, including micro climates, which are ecosystem-dependent themselves (Salati, 1987). Conditions, ecological and climatic, in those three sites are widely different and therefore account for those differences. In-site changes are rather difficult to explain, even though they may easily be linkable to major human activities in some cases. Luki is an island of forest within the Bakongo Region, which is the most logged region of the Congo (Iloweka, 2004). With an estimated human density of 237 persons/km2 (Iloweka, 2004), the population struggles to make a living through agriculture and woodcutting, which are fostered in response to high demands for foodstuffs and the high consumption of wood (for energy and construction) in Kinshasa and the expanding towns of Matadi and Boma. Most of the demand is met by products coming directly from the adjacent Province of Bas-Congo. All these activities increased the deforestation rate and unbalancing of forest ecosystems, which may be feeding the climate changes. Even though there is a need to deepen our knowledge on the correlation between forest cover and rainfall regime in this region, it is fairly logical to infer, based on studies undertaken in other regions of the world (Eltahir & Bras, 1993 Gash & Nobre, 1996; Lettau et al.1979,), that changes in the rainfall in this region may be a consequence of deforestation, which is feeding into global climate change and its effects. The situation appears of Kinshasa seems to be similar to that of Luki. Kinshasa, with a currently estimated population of 9 million people, has seen its immediate environment stripped of all natural forests and bush due to the demand for land needed to accommodate a rapidly increasing population. Forested areas that were left to maintain a healthy urban environment have been either invaded by houses or have seen their trees cut down to provide charcoal for energy. Such is also the case for Luki and even though this question calls for more detailed information to help establish clear causation links, it remains reasonable, based on studies done elsewhere (Eltahir & Bras, 1993; Gash & Nobre, 1996; Lettau et al., 1979), to hypothesize that changes observed in rainfall patterns in Kinshasa may be subsequent to decreasing vegetation cover both within the town itself and its immediately adjacent areas. The 34-year data set from Mabali intrigues common wisdom and can be fully understood only in parallel with the overall climate change paradigm (Inogwabini et al., 2006). Mabali (Figure 1) is located 75km straight south of the Equator. Within this strip, climatic metrics are constant (Bultot & Griffiths, 1972; Evrard, 1968) there are constant temperatures, stable rainfall regimes and regular seasonal cycles. A first look at the data from Mabali questions the rationality of the data because the site appears to be in an ideal environment for a rainfall pattern to remain constant over years. This remains the question even when you consider the fact that Mabali is also surrounded by active logging activities and many forest clearings due to high human concentration around Lake Tumba because the extent of vegetation clearing are far from being of the same magnitude as in Luki and Kinshasa. Deconstructing the puzzle posed by the Mabali situation, Inogwabini et al. (2006), found that while the most acknowledged consequence of the climate change was global warming (Houghton et al., 1990), the Mabali long-term data indicated a 1459

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local cooling phenomenon, which they attributed to longer dry seasons. Longer dry seasons mean less precipitation; therefore it is understandable that rainfall had decreased over the period covered by the study. Following Bultot & Griffiths (1972), Inogwabini et al. (2006), explained that in equatorial Africa dry seasons are cooler than normal temperatures due to over-evaporation, leading to persistent clouds. However, while tracking the explanations for longer dry seasons, they concluded that they could be logically explained only by inserting the global climate into the equation. Overall, decreased rainfall in the western Congo (in the three locations of Kinshasa, Luki and Mabali), regardless of reasons that may explain them, do agree with patterns in the other regions of Africa and have been documented previously (IRD, 2002; Mahe et al., 2001), albeit at localized scales. In conclusion, these trends are clear and should ignite the will to establish causation links if they are to be managed appropriately. This is a call for appropriate research rather than depending on opportunistic data. There is also one precaution in trying to use these data sets and/or extrapolating them: decreased annual rainfall intensities may depict a phenomenon of a long term cyclical event whose frequencies may be difficult to decipher from such a short time-series data. Nevertheless, given the fact that human activities may have pushed natural environmental to the edges of irreversibility, the picture provided by these data series may convey an alarm signal given the fact that we may have gone beyond a certain resilience threshold. This is even more appealing when one considers that these climatic patterns agree with the overall picture of the Congo Basin and Africa, and may be attributable to the global climate change phenomenon (IRD, 2002; Inogwabini et al., 2006). Previous studies (Hulme et al. 2001; Pearce & Turner, 1990; Sonwa et al., 2009; Stern, 2007) have described effects of climate changes to include economic aspects (decrease in financial incomes), health and sanitation (water quality and decrease in intake of fish proteins) and loss in biodiversity. Inogwabini et al. (2006) argued that the observed decrease in water depth of the Lake Tumba (from maximum depth of 8 m down to 6 m over 34 years) was essentially linked to the dramatic decline in rainfall. They also suggested that, apart from intensive fishing described by Inogwabini et al. (2009), observed decreases in fish stocks may also be linked to climatic conditions prevailing in the lake such as loss of reproduction sites, cooler temperatures and losses in some critical foods due to prolonged dry seasons, as fishes of the region adapted to different conditions and exhibit different requirements to reproduce and grow (Bailey, 1986; Banister, 1986; Chapman, 2001). They also indicated that if the weather change patterns they described remain constant, there would be numerous ecological consequences on forest ecosystems of the western Congo Basin (IRD, 2002; Inogwabini et al., 2006) in the long-term future. Evidence of such effects of climates on biodiversity have been described on several occasions (Fernández & Vrba, 2006; Lemoine & Böning-Gaese, 2003; Lemoine et al., 2007a & Lemoine et al., 2007b) and will likely occur in this region whose biodiversity is one of the most important on earth. To highlight the magnitude of the land affected by drying, a decrease in 18% of the size of the Congo watershed between 1998 and 2025 represents 673,968 km2. This dried out area represents ~28% of the entire Democratic Republic of Congo and 23 times the size of Equatorial Guinea. Beyond those consequences on biodiversity, the projected economic effects a drying watershed would also strike human economic activities, not only in terms of fish markets and protein intake but also in terms of agricultural productivity in the whole region. Increasing human populations will need more food and cultivatable land. Shortages in water will push people to find water sources for agriculture where this key resource will still is available, which is in the Central Congo Basin. That pattern would, most likely, lead to conflicts over water resources in the region. Lovett (2006) established that rainfall is one of the main determinants of ecological productivity, which in turn is the basis of agricultural economies. 1460

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Shortages of rainfall will, therefore, undermine the rich cultural diversity as well by forcing people to migrate to regions that offer better agricultural production and sufficient water sources. The destruction of the resources that support traditional culture is, by any measure, the most dramatic effect of climate change in this region. Climate change would certainly precipitate dramatic, permanent shifts in local cultures. For example, all people in the Lake Tumba region prefer fish as their most important food item. Decreasing fish stocks will most likely push them to adopt new life styles and other techniques to extract natural resources to live on. The introduction of new techniques will affect community views, relationship to the environment and overall stability.

SPECIFIC EFFECTS OF WATER DECREASE ON WOMEN IN THE REGION Decreasing water levels would likely increase in walking distances to clean water sources, which will ipso facto increase time consumed to fetch water, reduce girls’ chances to attend formal education, decrease women’s economic powers and expose them to gender-based violence. While there might be other factors affecting gender-education patterns described in this study, increased walking distances to clean water sources, at least contributed to that picture and will very likely continue to reduce girls’ chances to attend formal education unless major cultural and social changes happen. This finding conforms to the results reported from Ethiopia, Ghana, Tanzania (Komba, 1995) and India (UN-DESA, 2005) and other areas across Africa (YPOW, 2006). As reported in many studies (Inter-Agency Commission, 1990; IIon, 1992; Kinyanjui, 1993), literacy of women is an important key to improving health, nutrition and education in the family and to empowering women to participate in decision-making in society. Naturally, according to the Childhood Engenderment Theories (Chafetz, 2006), impeded access to formal education will keep future women under the yoke of inequality and reduce their self-esteem, perpetuating the current imbalanced power toward women (Chafetz & Haggan, 1996). Socioeconomic data indicate that decreasing water levels will have more severe impact on women commercial activities than compared to the global effect. That the numbers of women will double provides a prelude of heighten conflicts over fishing points resulting from increased competition of fishing points. This, combined with reduced access to education caused by water shortage, will therefore further hinder women’s economic powers, limiting the contribution of more than 50% of the population to contribute to economic returns expected by their societies and impact on means of achieving sustainable development and economic growth, which agrees with findings by Hanjra and Qureshi (2010) who projected that climate change effects will hinder the contribution of women to the global development. Reduced economic power means, again, lost self-esteem and will keep the current paradigms of social inequalities between men and women. Ironically, this will happen though women will see their workload increased by doubling walking distances to fetch water. Indeed, the estimated workload for fetching drinking water was a daily 12-km trip, consuming 40% of women working day. This was higher than the average time spent by women across rural Africa (Blackden & Wodon, 2006), which had been estimated at 26% (Water Aid, 2012). Water Aid (2012) had suggested a cohort of effects of reduced water availability on women in developing countries, principally on their health and that of their families in general. Both structured interviews and focus groups with local communities were not able to document feeling of worsening human health conditions in the region, though 21% of interviewed people talked about health increasing costs. However, official health reports indicated that there was an increase in some diseases during dry seasons, a period 1461

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when clean water is in shortage in the study region. Diarrheas, amoebic dysenteries, skin and itching in young people are water-borne diseases; and the fact that they increase during the period of clean water shortage indicate that should water decrease, the health conditions of the populations of this region would be affected directly. Diarrheas and amoebic dysenteries and other forms of diseases enumerated above have been reported to be directly linked to quality of water under other circumstances (Fewtrell et al. 2005; Gundry et al., 2004). Hence, the fact both structured interviews and focus groups with local communities were unable to document feeling of worsening human health conditions in the region may, most probably, be due to the sense of plenty of water and the fact that people had many other concerns that were priority to their livelihood than water-borne diseases. Of particular note here is that women specific genital ailments and infections increased by 23.6% during the dry seasons. Though there is no specific name on what these are, it would be sensible to think that decreasing water levels in the region would affect women’s health conditions in a specific way. Aveling et al. (2003) and Inogwabini et al. (2009) documented the fact that people in the region of the study had no proper sewage treatment mechanisms and people have been used to dumping garbage into open water, which in turn they fetched for domestic needs. Decreasing water levels will reduce the potential that larger water masses have to dilute effects of dumped sewage and will, therefore, lead to unclean water, which will lead to unhygienic conditions. It has been shown in the arid African regions (Manyanhaire et al., 2009), decreased water levels will reduce the spread of water-dependent human activities in a limited surface; limited spread zone for human activities alone will likely worsen health conditions. Major human settlements in areas of limited water supplies are always accompanied by worsening health conditions stemming from varied causes such as poor sewage and water treatment infrastructures, people sharing water sources with herds of cattle and other domestic animals. As indicated above, characteristics of this region are that there is no proper sewage treatment mechanisms, people dump garbage into open water, and defecate directly in open water (MSPPE, 2010). Decreasing water levels will reduce the potential that larger water masses have to dilute effects of dumped sewage and will, therefore, lead to unclean water. This will affect, in unforeseen degrees, both human populations and livestock who will be sharing the same water points. It is worth repeating that in Central Africa, as most cultures, women and girls are primarily responsible for the use and management of water resources, sanitation and health at the household level (Seager et al., 2009; UN-DESA, 2005;); which facts will certainly expose them to gender-based violence. Waterdriven conflicts would very likely results in similar impacts, including rape. An important result of this study is that women in this region already torn-apart by armed conflicts of different nature in the recent past have an acute perception of the risks of being raped while going for search of water. Managing water at times of scarcity will bring women to the forefront of water-ignited conflicts. The recent history, with the Enyele Rebellion Movement on water pounds in the north-western part of the DRC provided proof to this situation (Guerra et al., 2010); decades-old suppressed conflict over fishing rights evolved into ethnic tussle for economic and political power in north-west. Some 200,000 refugees fled the fish-conflict violence since in 2009 (BBC, 2009) of whom 82% were women (IRIN, 2011). Unfortunately, the opportunity provided by the recent Conference of Parties to the Convention United Nations Framework Convention on Climate Change in Paris was not seized to discuss the implications of climate change on freshwater and its social consequences. The word water appears nowhere throughout the text of the Paris Agreement, the importance of water being inferred to only once in the preamble through the use of the word ocean, as a specific ecosystem. Without diminishing the value of other international mechanisms such as the International Water Management Institute and other conferences on the subject, this absence of water in the agreement shows how low the water issues are on the agenda of the global 1462

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decision-making processes and, hence, lack of global perspectives on how to handle potential conflicts over freshwater sources. Of course, it could easily be argued that water is inferred through article 1 (1) of the Paris Agreement, which refers to the 1992 New York Convention which, in its article 4(e), calls parties to cooperate in preparing for adaptation to the impacts of climate change develop and elaborate appropriate and integrated plans for coastal zone management, water resources and agriculture, and for the protection and rehabilitation of areas, particularly in Africa, affected by drought and desertification, as well as floods. However, this inference is no so obvious and would demand a more refined practitioner of natural resources management to dig it out and make connections. It is suggested here that the best way to account for water and consequences of lack of its proper management is to factor freshwater in the development of the nationally determined contributions (Paris Agreement, article 3). But that will need a much more developed advocacy on behalf of the practitioners of natural resources management toward political decision-makers.

ACKNOWLEDGMENT I would like to thank Laurent Nsenga for allowing me to use data from Luki. Data from Kinshasa were gathered by students from Institut Bâtiments et Travaux Publics through the supervision of Alpha Egbango. Dr Mwanza Ndunda who co-authored the paper on Mabali shared the data from Mabali scientific Reserve.

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Thieme, M. L., Abell, R., Stiassny, M. L. J., Skelton, P., Lehner, B., Teugels, G. G., ... Olson, D. (Eds.). (2005). Freshwater ecoregions of Africa and Madagascar: A conservation assessment. Island Press. Tutin, C. E. G., & White, L. J. T. (1998). Primates, phenology and frugivory: Present, past and future patterns in the Lopé Reserve, Gabon. In D. M. Newbery, H. H. T. Prins, & N. Brown (Eds.), Dynamics of populations and Communities in the Tropics (pp. 309–338). Oxford, UK: Blackwell Science. UN-DESA (United Nations Department of Economic and Social Affairs). (2005). A Gender Perspective on Water Resources and Sanitation. Background paper NO 2. Commission on Sustainable Development Twelfth Session DESA/DSD/2005/2United Nations, New York. Walther, G.-R., Hughes, L., Vitousek, P., & Stenseth, N. C. (2005). Consensus on climate change. Trends in Ecology & Evolution, 20(12), 648–649. doi:10.1016/j.tree.2005.10.008 PMID:16701450 Water Aid. (2012). Women’s issues. Retrieved from http://www.wateraid.org/documents/plugindocuments/women_and_wateraid_issue_sheet.pdf White, F. (1983). The vegetation of Africa, a descriptive memoir to accompany the UNESCO/AETFAT/ UNSO vegetation map of Africa. UNESCO. Natural Resources Research, 20, 1–356. YPOW (Young People of the World). (2006). Water rights and wrongs - A Young People’s Summary of the United Nations Human development Report 2006. Beyond scarcity: power, poverty and the global water crisis. Available at http://www.gm.undp.org/Reports/report_youth_hdr.pdf

This research was previously published in Reconsidering the Impact of Climate Change on Global Water Supply, Use, and Management edited by Prakash Rao and Yogesh Patil , pages 211-226, copyright year 2017 by Information Science Reference (an imprint of IGI Global).

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Nitrate, Total Ammonia, and Total Suspended Sediments Modeling for the Mobile River Watershed Vladimir J. Alarcon Universidad Diego Portales, Chile Gretchen F. Sassenrath Kansas State University, USA

ABSTRACT This paper presents details of a water quality model of the Mobile River watershed that estimates total suspended sediments at the outlet of the watershed. The model is capable of simulating Nitrate (NO3), Total Ammonia (TAM), and Total Suspended Sediments (TSS) for extended periods of time at a daily temporal resolution (1970-1995). The Hydrological Simulation Program Fortran is used for modeling the hydrological, nitrogenous constituents, and sediment processes. Based on the nutrient simulation and exploration of the effects of two management practices (filter strips and stream bank stabilization and fencing) on nutrient removal, the resulting sediment model is used to implement the most efficient nutrient management practice and explore its effects on TSS concentrations in the Mobile River. Results show that the implementation of the management practice “stream bank stabilization and fencing” to agricultural lands in sub-watersheds that had intense agricultural activities produced the highest reductions of NO3 concentration (up to 14.06%) and TAM concentrations (8.01%). Based on the nutrient simulation and identification of “stream bank stabilization and fencing” as the most efficient BMP for nutrient concentration reduction, the sediment model was used to explore its effects on TSS concentrations in the Mobile River. Implementing “stream bank stabilization and fencing” produced monthly median TSS concentration reductions ranging from 3.6% to 10.6% in the Mobile River.

DOI: 10.4018/978-1-5225-9621-9.ch066

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 Nitrate, Total Ammonia, and Total Suspended Sediments Modeling for the Mobile River Watershed

INTRODUCTION The US Gulf Coast receives inputs of nutrients and sediments from intensive agricultural activities in upland watersheds (McPherson, et al., 2003). Seasonal hypoxia and high sediment load events have occurred in recent years. Continued land development and conversion of natural landscapes to urban development will exacerbate pollution (Vitousek et al., 1997; Wiener & Sassenrath, 2012). Moreover, nutrient and sediment contributions from upland watersheds where the main economic activity is agriculture play an important role (Harmel et al., 2007). Nitrogenous constituents and sediments washed off by precipitation events from the croplands are loaded into streams (creeks, rivers) which take sediments and nutrients to coastal water bodies. Mobile Bay, an estuary located in the Alabama Gulf Coast, receives waters from one of the largest watershed in North America (Park et al., 2007): Mobile River Watershed. The estuary experiences regular hypoxic events during the summer (EPA, 2012). The Tombigbee watershed, one of the upland watersheds that drains into Mobile Bay via the Mobile River, has been identified as one of the sources of nutrient input due to its intensive agricultural activity (EPA, 2014). Increases in agricultural activities could potentially worsen the current situation. Alarcon & McAnally (2012) estimated that in a span of seventeen years some portions of the Tombigbee watershed underwent the following land-use/land-cover changes: 34% increase of agricultural lands, 263% increase of lands used for grazing or hunting animals (rangeland), and a 16% decrease of natural forest lands. With these significant changes in soil surface coverage, the transport of nutrient and sediments washed-off from this watershed to Mobile Bay and the Alabama Gulf Coast has increased proportionally. The increase of agricultural lands and agricultural intensification are anticipated to worsen the current situation (Matson et al., 1997; Harmel et al., 2006). Conversion of forest land into crop or pasture can substantially increase the loss of sediments and nutrients from the land (Foley et al., 2005; Harmel et al., 2006). The rates of soil loss in particular will depend on management practices, especially the degree of tillage (no-tillage or conservation tillage versus conventional tillage) (Parajuli et al., 2013), and can also impact the loss of nutrients. While pastures may have reduced sediment losses, animal manures will increase the nutrient runoff from the field. A recent study at a small geographical scale (Kleinschmidt, 2005) postulated several management scenarios that may be used for reducing the effects of nutrient and sediment contamination to some of the Tombigbee streams. For cropland, filter strips, reduced tillage, stream bank stabilization and fencing, and terraces were identified as being the most useful in that order. For pasture land, stream bank stabilization and fencing, and terraces were the most useful. The sources of nutrient and sediment loss in agricultural watersheds are mostly distributed in space (i.e., they are non-point sources). Non-point sources enhance the chances for complex physical and biochemical processes to occur during the transport of those contaminants through soil and water. Therefore, estimating the effects of nutrient and sediment wash-off from agricultural fields to streams and water bodies requires a complex quantitative approach. Watershed models are able to quantify those processes occurring either under natural conditions or due to anthropogenic activities. These models use mechanistic and empirical algorithms to calculate the hydrological processes within a watershed and also the migration of pollutants from point and non-point sources to water bodies. Previous research has shown the use of these types of models for quantification of processes in agricultural watersheds (Alarcon & Sassenrath, 2015). For the Mobile River watershed, an initial hydrological and nutrient model (Alarcon & Sassenrath, 2016) has been developed that covers all major streams in the watershed, including the

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Tombigbee River and the Alabama River watersheds. A sediment transport model for the entire watershed, however, has yet to be developed. In this research, an existing nutrient model of the Mobile River watershed (Alarcon & Sassenrath, 2016) is improved by including modeling of total suspended sediments. The Better Assessment Science Integrating Point & Nonpoint Sources, BASINS GIS system (EPA, 2008) and the Hydrological Simulation Program Fortran, HSPF (Bicknell et al., 2001) are used to geo-process the input data and water quality modeling respectively. Through nutrient modeling, the optimum Best Management Practice (BMP) for nutrient removal is identified and, subsequently, this BPM’s efficiency in terms of TSS removal is tested via simulation.

METHODS Watershed Under Study The Mobile River is a typical coastal river with mild slopes and meandering course. The river is seventytwo kilometers long and is the main contributor of fresh water to Mobile Bay. It carries waters coming from two important rivers: Tombigbee and Alabama rivers. The Upper and Lower Tombigbee rivers, which watersheds are located in northwest Alabama and northeast Mississippi, drain a catchment area of approximately 59000 square kilometers between both states. Fifty six percent of the watershed is in Mississippi and the rest (44%) lies in Alabama. The Alabama River catchment covers approximately 56000 square kilometers draining most of eastern Alabama, and portions of northwest Georgia and southeast Tennessee (Figure 1). The Mobile River has an average annual stream flow of 1840 m3/s. The Mobile River watershed (Figure 1) covers approximately 115,000 km2, extending into four southeastern states: Alabama, Mississippi, Georgia, and Tennessee. This drainage basin is the fourth-largest in the United States and the sixth-largest in North America. The river and its contributors have historically provided the principal navigational access for Alabama.

Physical Geography Characterization The topographical characterization of the study area was performed using National Elevation Data (NED) (30-m horizontal, 1-m vertical), and USGS DEM (300-m horizontal 1-m vertical) topographical datasets. The NED dataset provides a seamless mosaic elevation data having as the primary initial data source the 7.5-minute elevation data for the conterminous United States (Lent & McKee, 2011). NED has a consistent projection (geographic), resolution (1 arc second, approximately 30 m), and metric elevation units (Deliman et al., 1999). The land-use/land-cover within the Mobile River watershed was characterized using the USGS GIRAS digital map. The USGS-GIRAS is a set of maps of land use and land cover for the conterminous U.S. delineated with a minimum mapping unit of 4 hectares and a maximum of 16 hectares (equivalent to 400 m spatial resolution), generated using the Geographic Information Retrieval and Analysis System (GIRAS) software. Today, they are widely known as the USGS GIRAS land use data sets (Alarcon & O’Hara, 2010).

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 Nitrate, Total Ammonia, and Total Suspended Sediments Modeling for the Mobile River Watershed

Figure 1. Mobile River watershed. The drainage basin (fourth-largest in the United States) drains streams located in Alabama, Mississippi, Georgia, and Tennessee.

Modeling Tool Hydrological, nutrient and sediment modeling of the Mobile River watershed was carried out using the Hydrological Simulation Program Fortran (HSPF). The HSPF software is designed for modeling and simulating non-point-source and point-source watershed hydrology and water quality. Time-series of meteorological/water-quality data, land use and topographical data are used to estimate stream flow hydrographs and pollutant-graphs. The model simulates interception, soil moisture, surface runoff, interflow, base flow, snowpack depth and water content, snowmelt, evapo-transpiration, and groundwater recharge. Simulation results are provided as time-series of runoff, sediment load, and nutrient and pesticide concentrations, along with time-series of water quantity and quality, at any point in a watershed. Additional software (WDMUtil and GenScn) is used for data pre-processing and post-processing, and for statistical and graphical analysis of input and output data (Alarcon & O´Hara, 2010). The BASINS 4.1 GIS system (EPA, 2008) was used for downloading basic data and delineating the watershed included in this study. The creation of the initial HSPF model was done using the WinHSPF interface included in BASINS 4.1. Figure 2 shows the delineation of the Mobile River watershed and corresponding HSPF model, based on the watershed delineation. Locations of water quality stations (from McPherson et al., 2003) in Tombigbee and Alabama rivers are shown in both: the delineated watershed and the schematic HSPF representation of the watershed. Notice that the HSPF model schematic mirrors the arrangement of sub-watersheds. Water quality simulations were performed for the most downstream sub-watershed encompassing Mobile River.

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Figure 2. Delineated Mobile River watershed and corresponding HSPF model. Locations of water quality stations (from McPherson et al., 2003) in Tombigbee and Alabama rivers are shown. The corresponding HSPF watershed mode for Mobile River is also shown. Notice that the HSPF interface mirrors the arrangement of sub-watersheds. Water quality simulations were performed for the most downstream sub-watershed encompassing Mobile River.

Water Quality Management Modeling and simulation in this research was performed in two phases. First, to identify the best management practice in terms of nutrient removal, two types of BMPs were tested for reduction of Nitrate (NO3) and Total Ammonia (TAM). The BMPs considered in this first phase were filter strips, and stream bank stabilization and fencing (based on Kleinschmidt, 2005). In order to carry out this first computational exploration, a selection of sub-watersheds was performed to reduce computer processing time of water quality simulations. Figure 3 shows agricultural lands in the Mobile River watershed area (left). It is evident that most of the agricultural activity in the area is concentrated in an agricultural belt that originates in northeastern Mississippi, crosses mid-southern Alabama, and ends in southwestern Georgia. Therefore, the sub-watersheds to which these agricultural lands belong (right hand side of Figure 3) were selected for implementing the BMPs and their corresponding removal efficiency. Three levels of implementation (in terms of percent of agricultural acreage) were simulated: 25%, 50%, and 75%. Those percentages of BMP were selected for allowing comparison of HSPF-simulated results with results reported in Kleinschmidt (2005). Figure 3 shows locations where comparison of simulated and measured/reported concentration values was performed: most downstream outlet of Mobile River, and water quality stations at Tombigbee and Alabama rivers.

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Figure 3. Distribution of agricultural lands in the Mobile River watershed and selected sub-basins for sediment and nutrient simulation. BMP effects were assessed at the Mobile River (watershed outlet).

The second phase of this research consisted on simulating a sediment management practice and assessing its effects in total suspended sediment concentrations in the Mobile River. The BMP for suspended sediments management was applied after the most efficient BMP for nutrient removal was identified. Therefore, the optimum BMP for nutrient removal was also assessed in its efficacy for TSS removal. The BMP was applied to the same sub-watersheds to which nutrient removal management practices were applied (i.e., sub-watersheds where agricultural activity was extensive).

RESULTS Nutrient Modeling Simulated nitrate concentrations from 1970 through 1995 are shown in Figure 4. Daily, monthly and annual mean concentration values achieved after the application of two types of BMPs: filter strips, and stream bank stabilization and fencing are shown. The charts show simulated results for application of those BPMs at 25%, 50% and 75% coverage of agricultural land areas. As shown in Figure 4, most nitrate daily means range between 1 and 6 mg/L with seasonal peaks and minimums in summer and winter correspondingly. Monthly means follow the same seasonal pattern with concentration values ranging mostly between 1.3 and 5 mg/L. Daily and monthly means are mostly lower than the 10 mg/L criteria for nitrate in surface water bodies (EPA, 2016; Reilly et al., 1999). Spikes corresponding to summers of 1977, 1987 and 1988 coincide with low flow conditions reported by Alarcon et al. (2009). Annual mean concentrations range within 2.3 and 4.5 mg/L; 75% of the annual means are lower than 3 mg/L. The assessment of the effects of the application of the BMPs at different percent coverages is shown in Table 1. Percent reductions in nitrate concentrations at Mobile River were calculated having as a baseline the model-estimated median concentration of nitrate when no BMP was applied.

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Figure 4. Nitrate concentrations in the Mobile River. Reduction in Nitrate concentrations after application of filter strips (left) and stream bank stabilization (right) are also shown.

Table 1. Nitrate concentration reductions after implementation of a Filter Strip BMP or Stream Bank Stabilization and Fencing BMP to agricultural lands Filter Strip

Stream Bank Stabilization

NITRATE

NO3 mg/L

% NO3 Reduction

NO3 mg/L

% NO3 Reduction

NO BMP

2.86

0.00

2.86

0.00

BMP 25%

2.82

1.48

2.81

1.82

BMP 50%

2.70

5.56

2.68

6.25

BMP 75%

2.52

12.24

2.46

14.06

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 Nitrate, Total Ammonia, and Total Suspended Sediments Modeling for the Mobile River Watershed

As shown in Table 1, stream bank stabilization and fencing is the BMP that shows better results in terms of nitrate concentration reductions in the Mobile River. Sequentially applying this BMP to 25%, 50% and 75% of agricultural acreage, produced NO3 concentration reductions of 1.82%, 6.25%, and 14.06%, correspondingly. Simulated total ammonia (TAM) concentrations for the simulation period 1970-1995 are shown in Figure 5. Simulated TAM monthly means range between 0.005 and 0.1 mg/L with summer peaks and winter lows as in the case of nitrate. Yearly mean concentration values cluster around 0.01 mg/L with the exception of 1978 when dry conditions were exacerbated by scarce precipitation (Alarcon et al., 2009). The figure also shows daily, monthly and annual mean concentrations for TAM after application of two BMPs (filter strip, and stream bank stabilization and fencing) are applied to increasing area coverages (25%, 50% and 75%). Table 2 compares the efficiency of those BMPs in terms of reduction of TAM concentrations in the most downstream point of the watershed. Stream bank stabilization is again shown to have a better efficacy in the reduction of TAM concentrations in the Mobile River. Table 2 and Figure 5 show that stream bank stabilization and fencing is the BMP that is more efficient in terms of TAM concentration reductions in the Mobile River. Sequential application of this BMP produces 1.04%, 3.37%, and 8.01% reduction of TAM concentrations in the Mobile River, corresponding to 25%, 50% and 75% of this BMP application to agricultural lands.

Figure 5. Total Ammonia concentrations in the Mobile River. Reduction in TAM concentrations after application of filter strips (left) and stream bank stabilization (right) are also shown.

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Table 2. TAM concentration reduction after implementation of a Filter Strip BMP or Stream Bank Stabilization and Fencing BMP to agricultural lands Filter Strip TOTAL AMMONIA

TAM mg/L

Stream Bank Stabilization % TAM Reduction

TAM mg/L

% TAM Reduction

NO BMP

0.0240

0.00

0.0240

0.00

BMP 25%

0.0238

0.84

0.0237

1.04

BMP 50%

0.0230

3.16

0.0229

3.37

BMP 75%

0.0214

6.97

0.0212

8.01

Sediment Modeling Since there were no water quality stations in the Mobile River it was not possible to proceed with a calibration of the model for total suspended sediments. However, McPherson et al. (2003) provide ranges of measured TSS concentrations at water quality stations located on the Tombigbee and Alabama rivers (shown in Figures 2 and 3). Those stations are located upstream from the Mobile River but their data could be used to assess the constancy of TSS estimations produced by the model. Figure 6 shows a comparison of TSS concentrations at the Mobile River against concentrations measured (McPherson et al., 2003) at Tombigbee and Alabama rivers. Minimum, first quartile, median, third quartile and maximum measured and simulated TSS concentrations are shown. Figure 6. Comparison of total suspended solids (TSS) simulated and measured concentration. Measured concentrations at Tombigbee and Alabama Rivers were extracted from McPherson et al., 2003.

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As shown in Figure 6 median simulated TSS concentrations range between 133 to 195 mg/L while median concentrations measured at Tombigbee and Alabama rivers range between 13 and 21 mg/L. Measured concentrations at those rivers reach 500 and 185 mg/L, respectively, while simulated concentrations for Mobile River reach 269 to 2020 mg/L. Simulated concentrations seem to be higher than measured concentrations. This is because statistics for Mobile River were calculated using daily mean concentrations for the 1970-1995 simulation period (more than 9000 daily values), while statistics for measured data were calculated with less than 35 data records. Therefore, simulated data captured a higher number of extreme events and this fact has shifted median and quartile values towards higher concentrations. Also, since the watershed areas draining to those stations are roughly half of the total area that drains to Mobile River, it is expected for measured concentrations at those locations to be smaller than concentrations at Mobile River. The previous section identified stream bank stabilization and fencing as the most efficient BMP in terms of nitrate and TAM concentration reduction. The sediment model was set up such that it would test how efficient this BMP would be to reduce TSS concentrations in Mobile River. Figure 7 shows daily, monthly and annual average concentrations for the 1970-1995 simulation period. Table 3 summarizes monthly median TSS concentration reductions after the BMP application. The application of stream bank stabilization to agricultural lands within Mobile River watershed results in TSS concentration reductions in the Mobile River comparable in percentage to those achieved for nutrients. Sequentially applying the BMP to 25%, 50% and 75% of agricultural acreage reduces TSS concentrations by 3.6%, 7.1%, and 10.6%, respectively (Table 3). Figure 7. Total suspended sediments (TSS) concentrations in the Mobile River. Reduction in TSS concentrations after application of stream bank stabilization to agricultural sub-watersheds.

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Table 3. Total suspended sediment (TSS) concentration reduction after implementation of Stream Bank Stabilization and Fencing BMP to agricultural lands Stream Bank Stabilization and Fencing TOTAL SUSPENDED SOLIDS

TSS mg/L

% TSS Reduction

NO BMP

180.5

0

BMP 25%

172.5

3.6

BMP 50%

168

7.1

BMP 75%

161.5

10.6

CONCLUSION The nutrient model for the Mobile River Watershed estimates nitrate daily mean concentrations ranging primarily between 1 and 6 mg/L, with seasonal peaks and minimums in summer and winter, correspondingly. Monthly NO3 mean concentrations follow the same seasonal pattern with most values ranging between 1.3 and 5 mg/L. Daily and monthly means are lower than the 10 mg/L criteria for nitrate in surface water bodies. Peak concentrations (15.1 mg/L and 13.2 mg/L, respectively) corresponding to summers of 1977, 1987 and 1988 coincide with low flow conditions. Annual mean concentrations range within 2.3 and 4.5 mg/L, with 75% of the annual means lower than 3 mg/L. Simulated Total Ammonia concentrations are lower than NO3 concentrations as would be expected in surface waters. Simulated TAM monthly means range between 0.005 and 0.1 mg/L with summer peaks and winter lows as in the case of nitrate. Yearly mean concentration values are approximately 0.01 mg/L with the exception of 1978 where low flow conditions occurred and yearly mean concentration reaches 0.07 mg/L. Nutrient modeling and simulation of the application of two management practices (filter strips, stream bank stabilization and fencing) for nutrient removal in the Mobile River revealed that stream bank stabilization and fencing had greater impact on reducing nitrate and TAM concentrations than the application of filter strips to agricultural lands. The water quality model for the Mobile River Watershed developed in this research estimates that consecutive application of this BMP to 25%, 50% and 75% of agricultural lands within the watershed, reduces NO3 concentrations by 1.82%, 6.25%, and 14.06%, respectively. Similarly, TAM concentrations are decreased by 1.04%, 3.37%, and 8.01%. Based on the nutrient simulation and exploration of the effects of those two management practices (filter strips, stream bank stabilization and fencing) on nutrient removal, the sediment modeling portion of the water quality model was used to implement the most efficient nutrient management practice (streambank stabilization and fencing) and explore its effects on TSS concentrations in the Mobile River. Implementing stream bank stabilization and fencing produced monthly median TSS concentration reductions ranging from 3.6% to 10.6% in the Mobile River.

ACKNOWLEDGMENT Portions of this work were supported by a grant from CONICYT REDES 140045. This manuscript is contribution number 17-109-J from the Kansas Agricultural Experiment Station.

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REFERENCES Alarcon, V. J., McAnally, W., Diaz-Ramirez, J., Martin, J., & Cartwright, J. (2009). A Hydrological Model of the Mobile River Watershed, Southeastern USA. In G. Maroulis & T. E. Simos (Eds.), Computational Methods in Science and Engineering: Advances in Computational Science (Vol. 1148, pp. 641–645). doi:10.1063/1.3225392 Alarcon, V. J., & McAnally, W. H. (2012). A Strategy for Estimating Nutrient Concentrations using Remote Sensing Datasets and Hydrological Modeling. International Journal of Agricultural and Environmental Information Systems, 3(1), 1–13. doi:10.4018/jaeis.2012010101 Alarcon, V. J., & O’Hara, C. G. (2010). Scale-Dependency and Sensitivity of Hydrological Estimations to Land Use and Topography for a Coastal Watershed in Mississippi. In Computational Science and Its Applications, LNCS (Vol. 6016, pp. 491-500). Alarcon, V. J., & Sassenrath, G. F. (2015). Sensitivity of Nutrient Estimations to Sediment Wash-off Using a Hydrological Model of Cherry Creek Watershed, Kansas. In Computational Science and Its Applications, LNCS (Vol. 9157, 457–467. doi:10.1007/978-3-319-21470-2_33 Alarcon, V. J., & Sassenrath, G. F. (2016). Modeling and Simulating Nutrient Management Practices for the Mobile River Watershed. In Computational Science and Its Applications, LNCS (Vol. 9788, pp. 33–43). doi:10.1007/978-3-319-42111-7_4 Bicknell, B. R., Brian, R., Imhoff, J. C., Kittle, J. L., Jr., Jobes, T. H., & Donigian, A. S., Jr. (2001). HSPF Version 12 User’s Manual. National Exposure Research Laboratory. Office of Research and Development U.S. Environmental Protection Agency. Deliman, P. N., Pack, W. J., & Nelson, E. J. 1999. Integration of the Hydrology Simulation Program— FORTRAN (HSPF) Watershed Water Quality Model into the Watershed Modeling System (WMS) (Technical Report W-99-2). US Army Corps of Engineers. Reilly, J.F., Horne, A.J., & Miller, C.D. (1999, September). Nitrate removal from a drinking water supply with large free-surface constructed wetlands prior to groundwater recharge. Ecological Engineering, 14(1-2), 33–47. doi:10.1016/S0925-8574(99)00018-X EPA, Environmental Protection Agency. (2008). BASINS: Better Assessment Science Integrating Point & Nonpoint Sources: A Powerful Tool for Managing Watersheds. Retrieved from http://www.epa.gov/ waterscience/BASINS/ EPA, Environmental Protection Agency. (2012). National Coastal Condition Report IV. Retrieved from http://www.epa.gov/sites/production/files/201410/documents/0_nccr_4_report_508_bookmarks.pdf EPA, Environmental Protection Agency. (2014). Alabama & Mobile Bay Basin Integrated Assessment of Watershed Health. Retrieved from http://www.mobilebaynep.com/images/uploads/library EPA, Environmental Protection Agency. (2016). Table of Regulated Drinking Water Contaminants. Drinking Water Contaminants: Standards and Regulations. Retrieved from http://www.epa.gov/yourdrinking-water/table-regulated-drinking-water-contaminants

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Foley, J. A., DeFries, R., Asner, G. P., Barford, C., Bonan, G., Carpenter, S. R., ... Snyder, P. K. (2005). Global consequences of land use. Science, 309(5734), 570–574. doi:10.1126cience.1111772 PMID:16040698 Harmel, D., Potter, S., Casebolt, P., Reckhow, K., Green, C., & Haney, R. (2006). Compilation of measured nutrient load data for agricultural land uses in the United States. Journal of the American Water Resources Association, 42(5), 1163–1178. doi:10.1111/j.1752-1688.2006.tb05604.x Kleinschmidt Co. (2005). Tombigbee River Basin Management Plan. Alabama Department of Environmental Management. Retrieved from http://www.adem.state.al.us/programs/water/nps/files/TombigbeeBMP.pdf Lent, M., & McKee, L. (2011). Guadalupe River Watershed Loading HSPF Model: Year 3 final progress report. Richmond, CA: San Francisco Estuary Institute. Retrieved from http://www.sfei.org/sites/default/ files/Guad_HSPF_Model__forSPLRev_17Feb2012.pdf Matson, P. A., Parton, W. J., Power, A. G., & Swift, M. J. (1997). Agricultural intensification and ecosystem properties. Science, 277(5325), 504–509. doi:10.1126cience.277.5325.504 PMID:20662149 McPherson, A. K., Moreland, R. S., & Atkins, J. B. (2003). Occurrence and Distribution of Nutrients, Suspended Sediment, and Pesticides in the Mobile River Basin, Alabama, Georgia, Mississippi, and Tennessee, 1999 – 2001 (Water-Resources Investigations Report 03 – 4203). United States Geological Survey. Parajuli, P. B., Jayakody, P., Sassenrath, G. F., Ouyang, Y., & Pote, J. W. (2013). Assessing the impacts of crop-rotation and tillage on crop yields and sediment yield using a modeling approach. Agricultural Water Management, 119, 32–41. doi:10.1016/j.agwat.2012.12.010 Park, K., Kim, C., & Schroeder, W. W. (2007). Temporal variability in summertime bottom hypoxia in shallow areas of Mobile Bay, Alabama. Estuaries and Coasts, 30(1), 54–65. Retrieved from http://link. springer.com/article/10.1007%2FBF02782967 doi:10.1007/BF02782967 Vitousek, P. M., Mooney, H. A., Lubchenco, J., & Melillo, J. M. (1997). Human domination of Earths ecosystems. Science, 277(5325), 494–499. doi:10.1126cience.277.5325.494 Wiener, J. D., & Sassenrath, G. F. (2012, June 27-29). Landscaping the long-term: Water system and irrigation re-visions for sustainability. Proceedings of the AWRA 2012 Summer Specialty Conference, Denver, CO.

This research was previously published in the International Journal of Agricultural and Environmental Information Systems (IJAEIS), 8(2); edited by Petraq Papajorgji and François Pinet , pages 20-31, copyright year 2017 by IGI Publishing (an imprint of IGI Global).

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Chapter 67

Impact of Climate Change on Potato Production in India M. K. Jatav Central Institute for Arid Horticulture, India V. K. Dua Central Potato Research Institute, India P. M. Govindakrishnan Central Potato Research Institute, India R. P. Sharma National Bureau of Soil Survey and Land Use Planning, India

ABSTRACT Potato is a temperate crop and higher day temperatures cause some areas to less suitable for potato production due to lower tuber yields and its quality. Tuber growth and yield can be severely reduced by temperature fluctuations outside 5-30 °C. The rate of warming in last 50 years is double than that for the last century. Increase in temperature and atmospheric CO2 are interlinked occurring simultaneously under future climate change and global warming scenarios. If CO2 is elevated to 550 ppm the temperature rise is likely to be 3 ºC with decline in potato production by 13.72% in the year 2050. The changing climate will affect the potato production adversely due to drought, salinity, frost, flooding, erratic unseasonal rains etc. It may reduce seed tuber production, impact storage facility and potato processing industries. Therefore, the quantification of regional vulnerability and impact assessment is very important for the development of early warning on disease forecasting systems, breeding of short duration and heat, drought, salinity tolerant and disease resistant cultivars.

DOI: 10.4018/978-1-5225-9621-9.ch067

Copyright © 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Impact of Climate Change on Potato Production in India

INTRODUCTION The book chapter “Sustainable Potato Production and the Impact of Climate Change” deals with the possible impact of global warming and elevated CO2 on Potato production. The results presented in this chapter are summarized findings of the research conducted in India; its agricultural universities and Indian council of Agricultural Research (ICAR). The level of atmospheric temperature and carbon dioxide raised under controlled conditions to some possible changes in near future to assess the impact on climate change on potato production. Findings of various researchers of India are compiled in the form of book chapter for easy understanding and in line of future work. Mitigation of impact of climate change on potato is discussed in global context.

BACKGROUND The bottom-line conclusion of the Third Assessment Report of the Intergovernmental Panel on Climate Change (IPCC, 2001) is that the average global surface temperature will increase by between 1.4°C and 3°C above 1990 levels by 2100 for low emission scenarios and between 2.5°C and 5.8°C for higher emission scenarios of greenhouse gases and aerosols in the atmosphere. The effect of increased temperatures on potato production in specific areas will vary depending partly on the current temperature of that area. Temperatures above 30 °C can have several negative impacts on potato production like: slowing tuber growth and initiation, less partitioning of starch to the tubers, physiological damage to tubers (e.g. brown spots), shortened/non-existent tuber dormancy, making tubers sprout too early. These effects can reduce crop yield and the number and weight of tubers. As a result, areas where current temperatures are near the limits of potatoes’ temperature range will likely suffer large reductions in potato crop yields in the future. Potato farming is the most important economic activity in some parts of India. Uttar Pradesh, Punjab and West Bengal are the major potato producing states. There is direct effect of global warming and serious risk to future crop production and food security in the country. At high altitudes, global warming will probably lead to changes in the time of planting, the planting of late-maturing cultivars, and a shift of the location of potato production. In many of these regions in India, changes in potato yield are likely to be relatively small in initial stage but expected to trigger in coming era of global warming. Shifting planting time or location is less feasible at lower altitudes, and in these regions global warming could have a strong negative effect on potato production. It is likely that the currently observed trend of global warming, which has been 0.6 ºC + 0.2 since 1900, will continue and that the average global temperature will increase by between 1.4 and 5.8 ºC over the period 1990 to 2100. It is shown that heat-tolerant potato cultivars could be used to mitigate effects of global warming in (sub) tropical regions. Climate change is now an acknowledged fact and reality. The evidence gathered world over using state-of-the-art technology by various national and international agencies is irrefutable. Human activities like rapid industrialization, intensive agriculture, and indiscriminate use of fertilizers, deforestation and increasing use of fossil fuels during past 150 years are the major contributing factors for climate change. The continued effect of these activities resulted in increasing emission of CO2 and other greenhouse gases (GHG) leading to global warming as a ‘greenhouse effect’ due to entrapment of back radiation from earth by these gases. The increase in temperature due to global warming is 0.76 ºC since 1850. The rate of warming in last 50 years is double than that for the last century. The rate of warming is increasing. The 20th century’s last two decades were the hottest in 400 years and possibly the warmest for several millennia, according 1483

 Impact of Climate Change on Potato Production in India

to a number of climate studies. And the United Nations’ Intergovernmental Panel on Climate Change (IPCC) reports that 11 of the past 12 years are among the dozen warmest since 1850. The CO2 concentration is projected to double from the current level of 360 ppm in the atmosphere. Global warming is occurring along with shifting pattern of rainfall and increasing incident of extreme weather events like floods, droughts and frosting. Concentration of greenhouse gases on time scale is presented in Figure 1. Global annual average surface temperature in 2015 is looking set to reach 1°C above the pre-industrial average (as represented by the 1850-1900 reference period) for the first time, according to the HadCRUT4 dataset produced by the Met Office and the Climatic Research Unit at the University of East Anglia (Figure 2). This is based on the current January to September 2015 temperature anomaly, and is also expected to hold when the final full-year anomaly is calculated. The warmth of 2015 represents an important marker because it means we are reaching halfway to 2°C for the first time. In 2010, parties to the United Nations Framework Convention on Climate Change (UNFCCC) agreed warming should be limited to below 2°C to avoid dangerous climate change. The growth of potato in India has been phenomenal since 1950 with increase in area production and productivity by 6, 15 and 3 times, respectively. Globally India stands at 4th and 3rd position now with respect to acreage and production, respectively. The crop is mainly confined to Indo-Gangetic plains in Figure 1. Observed changes in atmospheric greenhouse gas concentrations. Atmospheric concentrations of carbon dioxide (CO2, green), methane (CH4, orange), and nitrous oxide (N2O, red). Data from ice cores (symbols) and direct atmospheric measurements (lines) are overlaid

Source: (IPCC 2014).

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mild and cool winters in India. The autumn/winter planted crop in northern plains of India comprising the states of Uttar Pradesh, West Bengal, Bihar, Punjab and Haryana contributes 84% of total potato production in India. Here, the crop is grown totally under irrigated conditions. It is also grown in small scattered areas as rainfed crop in hills during summers and as rainy (kharif) and winter seasons crop in plateau region. However, the climate change and global warming will have a profound effect on potato growth story in India impacting every aspect of not only production and profitability, but seed multiplication, storage, marketing and processing of this perishable vegetatively propagated crop. Under the impact of future scenarios of climate change, the growth projections of potato in India might be arrested or even reversed, unless effective adaptation measures are evolved for timely application.

IMPACT ANALYSIS Increase in temperature and atmospheric CO2 are interlinked occurring simultaneously under future climate change and global warming scenarios. Effect of their interaction on potato would be more relevant and of greater economic significance compared to their usually counteracting direct effects on crop growth, yield and quality. Potato is mostly grown in north India during winters usually receiving few scattered rains. Under future scenarios the global warming is projected to be more pronounced over land areas with maximum temperature increase over northern India. The winter and post monsoon seasons are likely to be more affected by warming. Therefore, potato in addition to direct effects on growth and yield may be subjected to indirect effects of warming. These are increasing drought due to reduction in precipitation accentuating salinity and unpredictable extreme events of erratic unseasonal rains, flooding and frosting etc. Figure 2. Observed global mean temperature difference from the 1850-1900 mean (°C) from HadCRUT4 Source: Morice et al 2012.

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Effect of Elevated CO2 and Temperature Productivity Effect of Elevated CO2 and Rise in Temperature on Potato Production in India All India estimates of potato production were made by INFOCROP-POTATO simulation model (Singh, 2005, 2008) without adaptations and assuming that area under the crop remains constant at current levels (1.2 m ha) in future climate scenarios (Table 1). Results showed that the potato production will increase by 11.12% at elevated CO2 of 550 ppm and 1 ºC rise ºin temperature. However, the future climate scenarios for India indicates that at elevated CO2 of 550 ppm the temperature rise is likely to be 3 ºC (IPCC, 2007), with decline in production by 13.72% in the year 2050. The 1 ºC rise in temperature is likely to be associated with only 400 ppm of CO2 to be assumed in the year 2020 (IPCC, 2007), with a decline in potato production by 3.16% (Table 1). Direct Effect of Elevated CO2 The effect of elevated CO2 concentration in controlled experiments conducted in OTC (Open top chambers), FACE (Free air carbon enrichment) and growth chambers overwhelmingly suggests positive effect on growth and yield with only few negative influences. The CO2 concentration and assimilation are positively correlated. Doubling the CO2 concentration from ambient level of 360 ppm to 720 ppm increased the total biomass by 27 to 66% (Collins, 1976; Heagle et al., 2003; Olivo et al., 2002; Donnelly et al., 2001; Miglietta et al., 1998; Van de Geijn & Dijkstra, 1995). The tuber yield increased from 32 to 85% (Collins, 1976; Wheeler et al., 1991; Heagle et al., 2003; Craigon et al., 2002; Olivo et al., 2002; Donnelly et al., 2001; Miglietta et al., 1998; Finnan et al., 2002). The increase in tuber yield is estimated to be approximately 10% for every 100 ppm increase in CO2 concentration (Miglietta et al., 1998). These positive effects are attributed to increased photosynthesis from 10 to 40% (Collins, 1976; Katny et al., 2005; Olivo et al., 2002; Vandermeiren et al., 2002; Schapendonk et al., 2000). The increase in photosynthesis was most marked in young leaves (Katny et al., 2005; Vandermeiren et al., 2002). This is attributed to phenomenon of photosynthetic acclimation later in the growing season particularly in old leaves (Vandermeiren et al., 2002; Schapendonk et al., 2000; Lawson et al., 2001). Varietal differences in response to elevated CO2 concentration exists (Olivo et al., 2002). Number of tubers remained unaffected under elevated CO2, but mean tuber weight Table 1. Change (%) in potato production in India from current levels as affected by elevated CO2 and rise in temperature without adaptations Atmospheric CO2 conc. (ppm)

Rise in temperature (ºC) Nil (current)

1 (2020)

2

3 (2050)

4

5 (2090)

369 (current)

0.0

-6.27

-17.09

-28.10

-42.55

-60.55

400 (2020)

3.40

-3.16

-14.57

-25.54

-58.63

-58.63

550 (2050)

18.65

11.12

-1.25

-13.72

-30.25

-49.94

(Values in parentheses are likely years for associated CO2 levels and temperature rise) Source: (Singh, 2009)

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 Impact of Climate Change on Potato Production in India

increased mainly through increase in number of cells in tubers without influencing the cell volume (Collins, 1976; Chen and Setter, 2003; Donnelly et al., 2001). However, an increase in tuber number has been also observed (Miglietta et al., 1998; Craigon et al., 2002). Elevated CO2 concentration reduces evapotranspiration (ET) resulting in water saving to the extent of 12 to 14%(Magliulo et al., 2003; Olivo et al., 2002). Elevated CO2 concentration advances the tuber initiation and flowering (Miglietta et al., 1998) but hastens senescence of leaves (Miglietta et al., 1998; Vaccari et al., 2001). The few negative effects of elevated CO2 concentration include reduction in chlorophyll content in leaves particularly during later growing season after tuber initiation (Bindi et al., 2002; Lawson et al., 2001). Direct Effect of Temperature Growth and development is affected at high temperatures encountered in the tropics. No potato crop growth is possible below 2 ºC and above 30 ºC (Van Keulen & Stol, 1995). The minimum (0-7 ºC), optimum (16-25 ºC) and maximum (40 ºC) temperatures for net photosynthesis are reported (Kooman & Haverkort, 1995). Potato requires cool night temperature to induce tuberization (Burt, 1964; Ku et al., 1977; Cutter, 1992). Although photosynthesis in potato is suppressed by high temperature (Ku et al., 1977), it is not as sensitive to temperature as tuberization and partitioning of photosynthates to tuber (Reynolds et al., 1990; Midmore & Prange, 1992). The radiation use efficiency (RUE) is suppressed under high temperatures (Allen & Scott, 1992). High temperature reduces tuber number and size (Ewing, 1997). High temperature brings about marked morphological changes like etiolated growth with smaller size of compound leaves and leaflets reducing the LAI (Ewing, 1997; Fleisher et al., 2006) in addition to reduction in tuber number and size (Peet & Wolfe, 2000; Khan et al., 2003). However, long day conditions and high temperature prevailing in spring season in Punjab state in plains of India favoured growth of foliage at the cost of tubers and improved processing quality of tubers (Marwaha & Sandhu, 2002). Potato requires cool night temperature to induce tuberization, which is inhibited by even moderately high temperatures (Ku et al., 1977; Ewing, 1997). Tuber initiation was most affected by high temperature (Ghosh et al., 2000). High temperature reduces the gross photosynthetic rate (Fleisher et al., 2006). Although photosynthesis in potato is suppressed by high temperature (Ku et al., 1977), it is not as sensitive to temperature as tuberization and partitioning of photosynthates to tuber (Reynolds et al., 1990; Midmore and Prange, 1992). Therefore, even moderately high temperature drastically reduces tuber yield without much affecting the photosynthesis and total biomass production (Peet & Wolfe, 2000). Interaction Effect of Temperature and CO2 Potato tuber yield of plants exposed to high temperatures (35 ºC) were extremely low regardless of CO2 treatment, while in a non-temperature stress treatment (25 ºC) doubling CO2 increased tuber yield significantly by 71.5% (Peet & Wolfe, 2000). In another study potato was grown for 35 days under CO2 concentrations (500, 1,000, 1,500 and 2,000 micromoles mol-1) at both 16 ºC and 20 ºC air temperature. The mean starch concentration increased with increasing CO2 concentration at both 16 ºC and 20 ºC and was consistently higher at 16 ºC than at 20 ºC (Cao & Tibbitts, 1997). The SLW (g.m-2) was positively related to the foliar starch concentration on the basis of leaf area or dry weight (Cao & Tibbitts, 1997). The CO2 enrichment does not appear to compensate for the detrimental effects of higher temperature on tuber yield, while the quality of potato is likely to be impacted severely in terms of marketable grade of tubers and internal disorders.

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 Impact of Climate Change on Potato Production in India

Quality Elevated CO2 increased the amount of dry matter and starch with decrease in glycoalkaloid and nitrates improving the quality of tubers (Vorne et al., 2002; Schapendonk et al., 2000; Donnelly et al., 2001). Nearly all the nutrient elements tend to decrease in tubersunder elevated CO2 (Cao and Tibbitts, 1997; Fangmeier et al., 2002) and the citric acid content decreases causing a higher risk of discoloration after cooking (Vorne et al., 2002). High temperature is associated with tuber disorder of internal necrosis (Sterrett et al., 1991). In a pot experiment in naturally lit glass house and phytotron, the high temperature (30 ºC) decreased the total dry matter and tuber yield and degraded quality by reducing specific gravity of tubers (Ghosh et al., 2000). Nitrate reductase (NR) activity was also decreased by high temperature. The inhibition of tuber yield was due to limited translocation of carbohydrates from leaves to tubers following the reduction of NR activity and carbohydrate expense for dark respiration (Ghosh et al., 2000). It can also affect tuber quality by causing ‘heat sprouting’ which is premature growth of stolons from immature tubers (Wolfe et al., 1983; Struik et al., 1989) and internal necrosis (Sterrett et al., 1991). Potato processing requires large size tubers with high dry matter. Warming may reduce proportion of marketable and processing grade tubers for table and processing purposes, though dry matter may increase.

Indirect Effects of Climate Change and Global Warming Draught Optimal water supply is essential for potato, because of its shallow root system. The potato plant generally roots rather shallowly 40-50 cm (Beukema & Van der Zaag, 1990). Potato is extremely sensitive to drought particularly at tuber initiation with substantial loss in tuber yield. Dry matter partitioning to root, shoot, leaf and stem as a function of development stage (DS) and the root:shoot ratio is affected by drought stress. Drought, while reducing dry matter production increases the root:shoot ratio indicating a shift in the balance of growth in favour of roots. Roots of plants grown in drought conditions also tend to be thinner. Both responses enable drought plants to exploit the available soil moisture more effectively (Vos, 1995). Tuber initiation and maturity under drought stress conditions is hastened (Beukema & Van der Zaag, 1990). 1. Salinity: Potato is highly sensitive to salinity and irrigation with saline waters with even moderate residual sodium carbonate (RSC) values (Singh & Trehan, 1993). 2. Frost: Potato is extremely sensitive to frost. Complete loss of foliage is reported below 2 ºC of ambient temperatures for 2-3 consecutive nights. More than 4-5 hrs. duration of temperature below 1 ºC may result in foliage loss of 50% in even one night exposure. However, yield losses depend on crop growth stage at occurrence of frost. Frosting late in the season from 80-90 days after planting (DAP) results in yield loss of 10-15%, while that at 50-60 DAP may cause yield loss of 30-50%. 3. Flooding: Flooding for even short period of 2-3 days during active vegetative phase affects growth and yield. Flooding before emergence severely affects emergence due to rotting of seed tubers and soil crust formation, while that near harvesting results in rotting and rupture of tuber lenticels affecting physical appearance and marketable quality. 1488

 Impact of Climate Change on Potato Production in India

4. Erratic Unseasonal Rains: Rains of even 10-15 mm during planting or immediately after planting affects emergence due to soil crust formation and delays planting operation with consequent loss in yield. Rains during active vegetative phase may promote incidence of late blight disease. 5. Seed Tuber Production: In vegetatively propagated potato crop, the disease free quality seed tubers as planting material has special and added significance. Tuber as seed material is the carrier of a host of fungal, bacterial and viral diseases, responsible for rapid and drastic reduction in yield in successive generations of clonal multiplication. Most importantly the seed tubers alone accounts for half of the cost of inputs in potato cultivation and the profitability of the cropping enterprise to a large extent depends on quality of seed used. Viral diseases transmitted by aphid and other vectors are mainly responsible for rapid degeneration of planting materials in potato crop. The technology of ‘seed plot technique’ was developed on the sole premise of growing seed tubers in relatively aphid free periods in plains during winters and termination of vines by dehaulming before aphid population crosses a threshold to minimize infection of viral diseases. The appearance of potato peach aphid (Myzus persicae) is reported to advance by two weeks for every 1oC rise in mean temperature and population build up is positively correlated with maximum temperature and minimum relative humidity (Biswas et al. 2004; Dias et al., 1980). Thus, under the impact of climate change and global warming the earlier appearance and increase in aphid population is likely to limit the aphid free period to the detriment of seed tuber quality and quantity, which will ultimately affect potato production in India. In many regions warming may abolish seed tuber production altogether, while in others it will involve extra cost on chemicals and pesticides treatment with increased cost of seed resulting in decline in profitability. 6. Storage: The harvesting of potato in plains of India coincides with onset of hot summer season. Cold storage of tubers is recommended by the end of February to prevent heavy weight loss and rotting. It is cold stored up to the end of October till withdrawal for human consumption and planting is accomplished. In certain regions relatively cooler climate permits on farm storage of tubers for short period for 80-90 days in improvised country stores, heaps and pits with acceptable losses. However, warming during the period from March to June may preclude this practice with increased cost of storage in the cold stores. On the other hand earlier cold storage than the recommended by the end of February and prolonged storage beyond October till weather is favourable for planting, might become necessary under global warming scenarios. This will increase the operational cost and energy use in cold stores with implied increase in cost of cold storage and enhanced market price of potato for table and seed purpose. More number of strategically located cold stores near production and consumption centers would be needed to maintain the supply chain during hot summer months from March to October under global warming. 7. Potato Processing Industry: The potato tubers stored in cold stores at 4 ºC is not suitable for processing purposes due to increase in reducing sugar content imparting undesirable attributes in various processed products. Potato tubers kept in low temperature stores at 10 ºC or in on farm country stores are utilized for processing. However, tubers kept in these low temperature and country stores suffer from sprouting and weight loss once the dormancy is broken rendering it relatively unfit for processing. Global warming will reduce the ‘time window’ of availability of potato suitable for processing and will result in enhanced cost of chemical treatment of tubers to prevent sprouting. This has implication for viability of potato processing industry for supply of raw material for extended periods to be economical.

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 Impact of Climate Change on Potato Production in India

Regional Vulnerability to Climate Change in India The entire Indo-Gangetic plains, where irrigated potato is mainly grown is vulnerable. However, the state of West Bengal with highest productivity and second largest potato producing state in India appears highly vulnerable. Winters are mild in West Bengal and ‘window’ of suitable growing period is small, any rise in temperature will severely impact productivity with associated problems of storage and post harvest handling of produce in warmer conditions. Other vulnerable states are Bihar and Uttar Pradesh, which contributes maximum in total potato production. The states of Punjab, Haryana, and adjoining areas in northern Rajasthan and western Uttar Pradesh, where winters are relatively severe experiencing occasional frost might benefit from global warming to certain extent. The rainfed crop in plateau regions and other areas in south India would be most vulnerable due to warming and associated drought conditions.

Observations on Aberrant Weather and Extreme Events • • • • • •

Rains in winter season received at planting affects emergence and delays planting with reduction in tuber yield. Heavy showers during the crops season resulting in flooding affects tuber yield. Heavy rains at the time of harvesting induce rottage in field and in temporary heaps of harvested potato in the field. Overcast sky and rains early in the crop season invariably increases the attack of late blight disease with severe reduction in yield. Early frosting received in last fortnight of December and first week of January damages the crop in North-Western plains and western UP. Relatively warmer winters in the year 2008 reduced tuber yield in West Bengal, UP and Bihar.

Adaptation Measures for Climate Change and Global Warming • • • • • • • •

Use of crop residue mulches for some time after planting. Using drip irrigation in place of furrow and basin methods. Alter cultural management in potato based cropping systems. Conservation tillage and on farm crop residue management. Improvement and augmentation of cold storage facilities and air conditioned transportation from producing to consumption centers. Subsidizing additional cost of pests and water management. Insurance against weather for the cash crop of potato with high cost of cultivation. Strengthen education, research and development in warm climate production technology for ware and seed potato crop.

Mitigation Measures to Reduce Emission of CO2/ghg and Carbon Sequestration Potential of the Crop Potato being a short duration annual crop with readily decomposable crop residues has very limited carbon sequestration potential. Other mitigation measures are as follows.

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 Impact of Climate Change on Potato Production in India

• •

Resource conservation techniques Organic farming

FUTURE STRATEGIES FOR RESEARCH • • • • • • •

Quantification of regional vulnerability and impact assessment. Development of early warning disease forecasting systems. Breeding short duration and heat tolerant cultivars. Mining biodiversity to heat tolerance on priority. Breeding drought, salinity tolerant and disease resistant cultivars. Advance planning for possible relocation and identification of new areas for potato cultivation. Improved agronomic management for water and fertilizer use efficiency. Development of agro-techniques for warm weather cultivation and potato based cropping systems.

CONCLUSION Potato a native of temperate region grown under long day conditions in mild and cool summer season in Europe and America was introduced and adapted to tropical short day conditions in India during the last century. The growth of potato in India has been phenomenal since 1950 with increase in area production and productivity by 6, 15 and 3 times, respectively. The crop is mainly confined to IndoGangetic plains in mild and cool winters in India. The autumn/winter planted crop in northern plains of India comprising the states of Uttar Pradesh, West Bengal, Bihar, Punjab and Haryana contributes 84% of total potato production in India, where the crop is grown totally under irrigated conditions. Growth and development is affected at high temperatures encountered in the tropics. No potato crop growth is possible below 2 ºC and above 30 ºC. The minimum (0-7 ºC), optimum (16-25 ºC) and maximum (40 ºC) temperatures for net photosynthesis are reported. Potato requires cool night temperature to induce tuberization. Although photosynthesis in potato is suppressed by high temperature, it is not as sensitive to temperature as tuberization and partitioning of photosynthates to tubers. The climate change and global warming will have a profound effect on potato growth story in India impacting every aspect of not only production and profitability, but seed multiplication, storage, marketing and processing of this perishable vegetatively propagated crop. Under the impact of future scenarios of climate change the growth projections of potato in India might be arrested or even reversed, unless effective adaptation measures are evolved for timely application and implementation. Increase in temperature and atmospheric CO2 are interlinked occurring simultaneously under future climate change and global warming scenarios. Effect of their interaction on potato would be more relevant and of greater economic significance compared to their usually counteracting direct effects on crop growth, yield and quality. It is estimated that due to global warming potato production in India may decline by 3.16 and 13.72% from current levels by the year 2020 and 2050, respectively. The potato production will be directly affected by climate change, while there would be several indirect effects on various facets of supply, storage, utilization and acreage of the crop in future climate scenarios.

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Magliulo, V., Bindi, M., & Rana, G. (2003). Water use of irrigated potato (Solanum tuberosum L.) grown under free air carbon dioxide enrichment in central Italy. Agriculture, Ecosystems & Environment, 97(13), 65–80. doi:10.1016/S0167-8809(03)00135-X Marwaha, R. S., & Sandhu, S. K. (2002). Yield, growth components and processing quality of potatoes as influenced by crop maturity under short and long days. Advances in Horticultural Sciences, 16, 47–52. Midmore, D. J., & Prange, R. K. (1992). Growth responses of two Solanum species to contrasting temperatures and irradiance levels: Relations to photosynthesis, dark respiration and chlorophyll fluorescence. Annals of Botany, 69, 13–20. Miglietta, F., Magliulo, V., Bindi, M., Cerio, L., Vaccari, F. P., Loduca, V., & Peressotti, A. (1998). Free air CO2 enrichment of potato (Solanum tuberosum L.), development, growth and yield. Global Change Biology, 4(2), 163–172. doi:10.1046/j.1365-2486.1998.00120.x Olivo, N., Martinez, C. A., & Oliva, M. A. (2002). The photosynthetic response to elevated CO2 in high altitude potato species (Solanum curtilobum). Photosynthetica, 40(2), 309–313. doi:10.1023/A:1021370429699 Peet, M. M., & Wolfe, D. W. (2000). Crop ecosystem responses to climate change: Vegetable crops. In K. R. Reddy & H. F. Hodges (Eds.), Climate Change & Global Crop Production (pp. 213–243). CAB International. doi:10.1079/9780851994390.0213 Reynolds, M. P., Ewing, E. E., & Owens, T. G. (1990). Photosynthesis at high temperature in tuber bearing Solanum species. Plant Physiology, 93(2), 791–797. doi:10.1104/pp.93.2.791 PMID:16667538 Schapendonk, A. H. C. M., Oijen van, N., Dijkstra, P., Pot, C. S., Jordi, W. J. R. M., & Stoopen, G. M. (2000). Effects of elevated CO2 concentration on photosynthetic acclimation and productivity of two potato cultivars grown in open-top chambers. Australian Journal of Plant Physiology, 27, 1119–1130. Singh, J. P., Govindakrishnan, P. M., Lal, S. S., & Aggarwal, P. K. (2005). Increasing the efficiency of agronomy experiments in potato using INFOCROP-POTATO model. Potato Research, 48(3-4), 131–152. doi:10.1007/BF02742372 Singh, J. P., Govindakrishnan, P. M., Lal, S. S., & Aggarwal, P. K. (2008). Infocrop-Potato a Model for Simulating Growth and Yield of Potato in the Sub-Tropics. Central Potato Research Institute, Shimla. Singh, J. P., Lal, S. S., & Pandey, S. K. (2009). Effect of climate change on potato production in India. Central Potato Research Institute, Shimla, Newsletter, 40, 17-18. Singh, J. P., & Trehan, S. P. (1993). A case study of soil and irrigation water related constraints in potato crop production: Cause and correction. National Seminar on ‘Developments in Soil Science, 58th Annual convention, Dehradun. Sterrett, S. B., Lee, G. S., Henninger, M. R., & Lentner, M. (1991). Predictive model for onset and development of internal heat necrosis of ‘Atlantic’ potato. Journal of the American Society for Horticultural Science, 116, 701–705. Struik, P. C., Geertsema, J., & Custers, C. H. M. G. (1989). Effects of shoot, root and stolon temperatureon the development of potato plant. III. Development of tubers. Potato Research, 32, 151–158. doi:10.1007/ BF02358227

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Vaccari, F. P., Miglietta, F., Giuntoli, A., Magliulo, V., Cerio, L., & Bindi, M. (2001). Free air CO2 enrichment of potato (Solanum tuberosum L.). Photosynthetic capacity of leaves. Italian Journal of Agronomy, 5, 3–10. Van de Geijn, S. C., & Dijkstra, P. (1995). Physiological effects of changes in atmospheric carbon dioxide concentration and temperature on growth and water relations of crop plants. In A. J. Haverkort & D. K. L. MacKerron (Eds.), Potato ecology and modelling of crops under conditions limiting growth (pp. 89–100). Dordrecht: Kluwer Academic Publishers. doi:10.1007/978-94-011-0051-9_6 Van Keulen, H., & Stol, W. (1995). Agro-ecological zonation for potato production. In A. J. Haverkort & D. K. L. MacKerron (Eds.), Potato Ecology and Modelling of Crops under Conditions Limiting Growth (pp. 357–372). Dordrecht: Kluwer Academic Publishers. doi:10.1007/978-94-011-0051-9_23 Vandermeiren, K., Black, C., Lawson, T., Casanova, M. A., & Ojanpera, K. (2002). Photosynthetic and stomatal responses of potatoes grown under elevated CO2 and/or O3 - results from the European CHIPprogramme. European Journal of Agronomy, 17(4), 337–352. doi:10.1016/S1161-0301(02)00070-9 Vorne, V., Ojanpera, K., De Temmerman, L., Bindi, M., Högy, P., Jones, M. B., ... Persson, K. (2002). Effects of elevated carbon dioxide and ozone on potato tuber quality in the European multiple-site experiment CHIP-project. European Journal of Agronomy, 17(4), 369–381. doi:10.1016/S1161-0301(02)00072-2 Vos, J. (1995). Nitrogen and the growth of potato crops. In A. J. Haverkort & D. K. L. MacKerron (Eds.), Potato ecology and modelling of crops under conditions limiting growth (pp. 115–128). Dordrecht: Kluwer Academic Publishers. doi:10.1007/978-94-011-0051-9_8 Wheeler, R. M., Tibbitts, T. W., & Fitzpatrick, A. H. (1991). Carbon dioxide effects on potato growth under different photoperiods and irradiance. Crop Science, 31(5), 1209–1213. doi:10.2135/cropsci199 1.0011183X003100050026x PMID:11537629 Wolfe, D. W., Fereres, E., & Voss, R. E. (1983). Growth and yield response of two potato cultivars to various levels of applied water. Irrigation Science, 3(4), 211–222. doi:10.1007/BF00272837

This research was previously published in Sustainable Potato Production and the Impact of Climate Change edited by Sunil Londhe, pages 87-104, copyright year 2017 by Information Science Reference (an imprint of IGI Global).

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Chapter 68

Rift Valley Fever and the Changing Environment: A Case Study in East Africa

Johanna Lindahl Swedish University of Agricultural Sciences, Sweden & International Livestock Research Institute, Kenya Bernard Bett International Livestock Research Institute, Kenya Timothy Robinson International Livestock Research Institute, Kenya Delia Grace International Livestock Research Institute, Kenya

ABSTRACT Rift Valley fever is a severe disease affecting both humans and animals. The Rift Valley fever virus can be transmitted by body fluids, and the most common way for humans to get infected is from animals. The virus is also vector-borne and can be transmitted by many species of mosquitoes. As with other vector-borne diseases, the epidemiology may vary in response to environmental changes. Here the effects of climate and land use changes on Rift Valley fever, as well as on other vector-borne diseases, are discussed. The effect of irrigation in East Africa on inter-epidemic transmission of RVF is discussed in greater detail, followed by recommendations for future research and actions.

INTRODUCTION The last century has seen a period of ecological change, unprecedented in recent times, with dramatic reductions in pristine habitats, ecosystem services and biodiversity along with equally dramatic increases in numbers of people and of domestic animals. Most land use practices change the environment and are due to human influence, often related to feeding the growing population, such as increased irrigation DOI: 10.4018/978-1-5225-9621-9.ch068

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and land deforestation to allow crop cultivation. Environmental change is ubiquitous, and new diseases continue to emerge, while concerns about the impact of environmental change on human health grow. However, while it seems intuitive that degradation of ecosystems will increase the risk of disease, detailed knowledge on how specific environmental changes in a given context affect disease transmission is often lacking. As a consequence, decision makers may inadvertently increase health risks. This chapter uses the example of Rift Valley fever (RVF) to explore relations between disease dynamics and environmental change. Two main drivers, climate and land use changes, can be identified. We focus on irrigation as a type of land use change. In addition, RVF is characterized, describing the knowns and unknowns about its epidemiology and recapitulating the history and impact of RVF outbreaks in east Africa. Next we discuss relations between RVF and climate and land use change. Findings from an ongoing study, which shows that an irrigated area can support endemic transmission of RVF, without any signs of outbreaks, are also presented and the relevance of this is discussed.

IMPORTANCE AND DRIVERS OF EMERGING DISEASE Emerging infectious diseases in both animals and humans cause major economic and health burdens in every part of the world. On average, a new human disease appears every four months and around 75% of emerging diseases are zoonotic (Jones et al., 2008). Most originate from wildlife, and the study of disease emergence has a strong focus on wildlife. However, economically important emerging diseases often involve domestic animals. For example, between 1997 and 2009, six major emerging diseases have together cost at least 80 billion USD: the Nipah virus outbreak in Malaysia, West Nile fever in the USA, severe acute respiratory syndrome (SARS, starting in Asia), highly pathogenic avian influenza (HPAI, starting in Asia), bovine spongiform encephalopathy (BSE, starting in the UK) and RVF in East Africa (World Bank, 2012). In all of these, livestock or animals farmed for human consumption provided either a reservoir or a bridge to transmit the disease to people. Later outbreaks of emerging infectious diseases, such as Middle East respiratory syndrome (MERS) and the Ebola outbreak in West Africa, were also caused by viruses with an animal reservoir; in the case of MERS livestock (camels) are an amplifying host, and in the case of Ebola a livestock interface has been suspected (Atherstone, Smith, Ochungo, Roesel, & Grace, 2015; Wong et al., 2015; Yuen, 2015). The burden of infectious diseases is not uniform, and in low-income countries a high proportion of disease stems from zoonotic diseases and diseases recently emerged from animals (Grace, Gilbert, Randolph, & Kang’ethe, 2012). In Africa, diseases affect poor people disproportionally and further contribute to their poverty in a vicious circle. In particular, zoonotic diseases have the potential to harm both the livelihoods and health of those depending on livestock. Africa is also the continent where more than half of all outbreaks of emerging infectious diseases verified by WHO between 1996 and 2009 occurred, and where the time lags between outbreak detection and public alerts are the longest (Chan et al., 2010). Moreover, demographic growth is predicted to remain high in Africa, with the continent’s population predicted to reach 4 billion in 2100 (from 1 billion in 2014) (Gerland et al., 2014). This rapid population growth is likely to drive equally rapid changes in ecosystems, including crop expansion into marginal areas, irrigation, deforestation, urban sprawl, road building, mining and bush meat harvesting (Grace & Bett, 2014). Depending on how these changes affect the number of susceptible animals and humans, their risks of exposure and the infectiousness of the infected individuals, they may either increase or decrease disease incidence (Lindahl & Grace, 2015). Land-use change often drives disease and has been 1497

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estimated to be responsible for more than 20% of disease emergence on the island continent of Australia (McFarlane, Sleigh, & McMichael, 2013). In addition, the risks of land use associated diseases are often exacerbated by change and variation in climate changes and the poor adaptive capabilities of communities.

Influence of Environmental Change on Arthropods and Arthropod-Borne Diseases The dependence of arthropod vectors on the surrounding environment makes them susceptible to change. Arthropods are exothermic, and thus their life cycles, as well as possible pathogen replication within them, are strongly affected by temperature (Khasnis & Nettleman, 2005; Kramer & Ebel, 2003). Vectors are also dependent on suitable habitats for breeding, determined by factors such as soil, land cover and use, temperature, moisture, rainfall patterns and vegetation. When climate changes, the consequence may be that a vector changes its potential distribution and seasonal pattern of activity (Githeko, Lindsay, Confalonieri, & Patz, 2000; Patz, Campbell-Lendrum, Holloway, & Foley, 2005; Russell, 1998). Climate change may also result in changes in precipitation with varying effects on vectors (Githeko et al., 2000). For example, drastically increased precipitation may flush out larval habitats (Impoinvil et al., 2011; Khasnis & Nettleman, 2005; Murty, Rao, & Arunachalam, 2010), but the long term effect might be establishment of more breeding grounds.

The Effect of Climate and Indirect Consequences Climate changes have direct and indirect impacts on vector-borne disease transmission. Changes in temperature can change vector competence, and thus cause mosquito species (that are minor or insignificant vectors) to become more important (Mellor & Leake, 2000; Tabachnick, 2013). Whether or not, and how efficiently, an arthropod can act as a vector depends on many factors. Temperature affects the longevity of the vector and the rate of virus multiplication within it (Kramer & Ebel, 2003; Tabachnick, 2013). In addition, humidity and wind could influence the longevity and dispersal of the vector, and precipitation may determine the spatial distribution and suitability of breeding grounds. So how will vector-borne diseases be affected when climate changes? The complex nature of vectorborne disease transmission makes predictions difficult. It is important to understand the impact of climate change on environmental factors that may influence vector dynamics (Tabachnick, 2010), such as changes in land use, population movements and interactions. Increased temperatures may increase the need for irrigation or dams, thus creating vector habitats, and movement and interactions between humans and different animal species bring new vectors into contact with new hosts. The transmission from the vectors depends on the vector capacity (Cohuet, Harris, Robert, & Fontenille, 2010), defined as the number of potentially infective bites an individual is exposed to during one day from one particular vector species (Black & Moore, 2005). Extrinsic and intrinsic factors needed to be estimated for the calculation of vector capacity: • • •

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The probability that a vector feeds on a specific host, which depends on the feeding frequency and the proportion of meals taken from that host. The vector density in relation to the host density. The probability that the vector survives each day.

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• •

The vector competence, which is the proportion of vectors taking an infected meal that become infected and can transmit the infection to another host. The duration of the vector’s life after the incubation period of the pathogen in the vector.

It is clearly an over-simplification, therefore, to equate increase in vector-borne transmission with increase in temperature. Temperature affects the intrinsic factors of the arthropods, such as development rate and longevity (and thus vector abundance), pathogen incubation period within the vector (extrinsic incubation period (EIP)), behaviour and reproduction. Increased temperatures speed processes up within the arthropods and thus decrease both the incubation period in the vectors and their longevity (Kramer & Ebel, 2003; Tabachnick, 2013). In general, all factors contributing to increased vector abundance, shorter incubation periods, and increased vector survival are likely to increase the disease transmission. However, factors contributing to an increased host density and proportion of suitable hosts could also result in increased disease transmission, and these factors may also be dependent on environmental changes, such as increased droughts making farmers keep more goats instead of relying on crop production. The indirect effects of climate change on ecosystems are thus also important. Decreased surface water availability may cause large numbers of potential hosts to aggregate closer to the water sources which could intensify transmission, and reduced availability of water bodies could negatively impact the predators that feed on mosquito larvae (Epstein, 2001). In addition, even when an increase in disease incidence is observed after climate change, there are many possible confounding factors such as droughts reducing crop yield and impacting the nutritional status of a community, interrupted infrastructure, which may for example make vaccination campaigns or health care impossible, or decreased social and health services. All these events may contribute to the subsequent increase in disease incidence (Lindahl & Grace, 2015). Due to these complexities, there are uncertainties as to how different vector-borne diseases may be affected by different aspects of climate change. Each vector-pathogen system has a different range of tolerated temperatures, with optimal transmission occurring within a tighter range (Mellor & Leake, 2000). Since minimum temperatures are predicted to change more than maximum temperatures, it has been suggested that the effects on vector-borne disease transmission are more likely to go from suboptimal to more optimal, than from optimal to temperatures higher than those ideal for transmission (Ostfeld, 2009). As an example, the lower temperature allowing malaria transmission is estimated to be around 14-18°C, whereas the upper limit is around 35-40°C. When changes occur, it is likely to affect disease transmission in borderline regions more than in areas of core suitability (Githeko, Lindsay et al. 2000), although temperature changes that could make transmission more optimal in the local setting are likely to have an impact. Cold temperatures affect the duration of the mosquito’s breeding season and some species are able to continue breeding at lower temperatures (Mogi, 1996). Increases in temperature could lead to a life span shorter than the incubation period, or higher mosquito mortality, therefore, limiting disease transmission. However, the capacity of mosquitoes to find suitable microhabitats to avoid heat is an efficient adaptation strategy. However, it is not certain that the increased potential for disease transmission caused by climate change will be observable. If the transmission of vector-borne diseases is already high, it may not be possible to observe small changes in transmission rates, and this could be the case especially in tropical low-income countries (Reiter, 2001). The opposite scenario may occur in developed countries, where socioeconomic factors may prohibit increased spread of diseases, in spite of climate becoming more permissive. Mosquitoes capable of transmitting malaria are present as far north as Scandinavia, but be-

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cause of improved living standards and healthcare, malaria disappeared from Europe in the 20th century (Hulden & Hulden, 2009), and is unlikely to return.

The Effect of Land Use Changes Climate changes, though an important contributor to mosquito habitat suitability, is not the only factor responsible for distribution changes of vector-borne diseases. Indeed, most of the new introductions of invasive mosquito species have not been related directly to climate change (Gubler et al., 2001). Globalization, increased travels and trade provide excellent means for transportation of adult mosquitoes, as well as their eggs. In spite of these risks, travels and trade are highly promoted and unlikely to be reduced (Lindahl & Grace, 2015). Vectors have different requirements for their breeding grounds, and these are often, but not always, dependent on meteorological factors. One of the major vectors for RVF in West Africa, Aedes vexans, breeds in seasonal ponds, which vary in size with the rainfall, since the mosquito eggs also require a period of draught before the rains in order to hatch (Vignolles et al., 2009). Some of the factors influencing the availability of suitable breeding grounds are, however, affected by anthropogenic activities, such as irrigation, agricultural intensification, urbanization, and deforestation. In addition, climate and land use changes interact with each other as well as other drivers. For example, climate induced deterioration of agricultural conditions may increase the rural-urban migration; it may initiate schemes for irrigation, or cause people to switch agricultural practices. Furthermore, large-scale changes in land use such as deforestation may contribute to climate change. Irrigation may be an especially potent driver of vector-borne disease in Africa given current forecasts for large-scale expansion. Irrigation has been associated with a plethora of diseases including malaria, schistosomiasis, and RVF (Keiser et al., 2005; Steinmann, Keiser, Bos, Tanner, & Utzinger, 2006). Africa has an enormous potential for irrigation: just 4% of the total cultivated area is irrigated compared to 37% in Asia and 14% in Latin America (You, 2008). It is expected that heavy investments in irrigation are likely to occur over the coming decades and smallholder irrigation could cover 30-40 million ha, benefitting 400 million people (Keiser et al., 2005; Xie, You, Wielgosz, & Ringler, 2014). However, it is possible that this may expose them to additional health risks.

RIFT VALLEY FEVER: AN EMERGING DISEASE Rift Valley fever (RVF) was identified in the 1930s in the Rift Valley region in Kenya, although probable outbreaks could be traced as far back as 1912 (Daubney, Hudson, & Garnham, 1931; Davies, 2010; Findlay, 1932). Analyses of the viral genome suggests that the original emergence of the virus, proposed to have evolved rather recently, might be due to early land use changes in the shape of colonial agricultural development with introduction of large scale ruminant farming (Pepin, Bouloy, Bird, Kemp, & Paweska, 2010). The virus was not known to be zoonotic until human cases were described in the 1951 South African outbreak (Davies, 2010), and the full zoonotic potential was realized only in 1977 when an outbreak in Egypt resulted in about 600 human deaths, among some 200,000 human cases (Nanyingi et al., 2015; Soumaré et al., 2012). Rift Valley fever is considered one of the emerging infectious diseases that is having the most severe impacts in the African continent, and is present in most of sub-Saharan Africa, 1500

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Figure 1. Map over the countries in Africa which have experienced extensive outbreaks of Rift Valley fever (grey); the insert of Kenya shows the study areas for the case study on Rift Valley fever, with dark grey for the pastoral areas in Ijara district, and light grey for the areas close to the irrigation scheme in Tana River district. Swanepoel & Coetzer, 2004.

with extensive outbreaks occurring in Kenya, Tanzania, Madagascar, Mauretania, Senegal, Namibia, Mozambique, South Africa, Zimbabwe, Zambia and Sudan (Figure 1), but additional countries have also experienced small outbreaks, or there has been evidence of virus circulation (Nanyingi et al., 2015; Swanepoel & Coetzer, 2004). With outbreaks extending outside sub-Saharan Africa and occurring as far north as Egypt and the Arabian Peninsula, it is feared that the virus has the potential to spread into Europe and to other parts of the world (Chevalier, Pépin, Plée, & Lancelot, 2010; Moutailler, Krida, Schaffner, Vazeille, & Failloux, 2008; Turell, Sardelis, O’Guinn, & Dohm, 2002; Turell et al., 2008). Within Africa, RVF strains seem to be circulating over large distances, with samples in Madagascar shown to be similar to both North and East African strains and to the strains causing outbreaks in the Arabian Peninsula (Sall et al., 1998; Shoemaker et al., 2002). Phylogenetic studies suggest that RVF virus has been introduced into West Africa from other parts of Africa on five different occasions (Soumaré et al., 2012). Trade and transport of infected animals has been suggested to be one of the mechanisms that allowed virus dispersal. The RVF virus belongs to the Bunyaviridae family, in the genus Phlebovirus. This is a large viral family with more than 300 disease-causing viruses which have tripartite single-stranded RNA. Although the viruses often are transmitted by vectors such as mosquitoes or ticks, they may also be transmitted directly by body fluids, especially fetal materials that may carry high loads of virus. The RVF virus can

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be transmitted by numerous mosquitoes from at least 6 genera and over 30 species (Pepin et al., 2010; Walter & Barr, 2011). However, even though many mosquitoes may harbour the virus, they may not all be important for the disease epidemiology, and different vectors are important in different parts of Africa. In East Africa, it is believed that the primary vectors maintaining the virus and starting outbreaks are floodwater breeding Aedes species, whereas secondary vectors fuelling the outbreak are likely to be Culex species (Anyamba et al., 2010; Sang et al., 2010; Vilaly et al., 2013). The virus has a predilection for the liver but spreads to many parts of the body after a host is infected (Pepin, Bouloy, Bird, Kemp, & Paweska, 2010). Clinical cases in humans are usually characterized by hemorrhagic fever and encephalitis, whereas animals abort or have hemorrhages and necrotic hepatitis (Elliott, 1997). Case fatality in young livestock can be high, and although it is difficult to assess accurately how many humans were actually infected in an outbreak, as many as 47% of confirmed and probable cases may succumb to the disease (Mohamed et al., 2010). In addition, the virus frequently causes abortion storms (Pepin et al., 2010). In the earlier outbreaks, it was reported that indigenous livestock were unaffected (Davies & Martin, 2006); however, breed has not been reported as one of the risk factors for animal infection, summarized by recent reviews (Nanyingi et al., 2015; Nicholas, Jacobsen, & Waters, 2014). Moreover, if indigenous breeds are as likely as exotic breeds to be infected, but not to develop disease, seroprevalence studies are unable to detect such a trait. Although much research has been conducted on RVF and its vectors, some uncertainties remain, especially as to how the virus is maintained during the periods between epidemics, which have been occurring every 5-15 years in East Africa. The vectors for RVF are divided into primary and secondary vectors, where the primary vectors are involved in the initial transmission of the virus to host animals, and the secondary vectors play a larger role later in the outbreak by propagating it. Aedes mosquitoes are believed to be most important for disease transmission, especially those breeding in flood water. In East Africa, these mosquitoes breed in depressions termed dambos, where the eggs diapause during the dry periods, and hatch during subsequent flooding that follows prolonged rain (Logan et al., 1991). Transovarial transmission has been shown in many mosquito species, and adult reared from larvae collected in naturally flooded dambos have been shown to contain the virus (Linthicum, Davies, Kairo, & Bailey, 1985). It is therefore believed that the virus may survive in the eggs for years while waiting to hatch, and that this could explain how the virus persists during the inter-epidemic periods. It is also possible that immature stages of mosquitoes can be infected by virus present in the breeding habitats, and it has been shown that larvae of Culex pipiens, Aedes mcintoshi and A. circumluteolus can become infected experimentally and subsequently transfer the virus when feeding as adults (Turell, Linthicum, & Beaman, 1990). Another explanation is that wildlife reservoirs maintain the virus in an endemic sylvatic cycle. A number of studies have shown that wild animals naturally seroconvert to RVF (Britch et al., 2013; Evans et al., 2008; Olive, Goodman, & Reynes, 2012). Sudden increases in rainfall could lead to more mosquitoes hatching, and the increased number of vectors cause spillover onto livestock and humans. Secondary vectors, such as other Culex species also multiply after the rains, which promotes the outbreak. It is even possible that the virus is maintained by a low level circulation among domestic animals. The epidemiology of RVF is further complicated because body fluids of infected animals (including fetal membranes) are infectious and this is the main cause of infection in humans, although they may still get infected from mosquitoes (Anyamba et al., 2009). Therefore, certain occupation groups such as herders, farmers, slaughterhouse workers and veterinarians are at greater risk of infection. Similar contacts may occur during care or slaughtering of infected animals or possibly from ingestion of raw milk. 1502

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Whereas RVF is mostly known for the severe outbreaks, it is believed to be endemic and circulating between the outbreaks. Molecular epidemiological estimates suggest that the virus may not only persist but also expand undetected during these periods (Pepin et al., 2010). Possible ways in which RVF could be maintained during epidemiological cycles are shown in Figure 2.

Rift Valley Fever Outbreaks in East Africa and Their Impacts Whereas RVF outbreaks have been associated with semi-arid or irrigated areas in West and North Africa, outbreaks in East Africa often occur in plateau grasslands (Martin et al., 2008). In 1997, Kenya experienced heavy rains, and this was followed by an outbreak of RVF, which may have infected as many as 27 000 humans (Woods et al., 2002). In this outbreak, the main risk factors for human infections were sheltering animals in the home and contact with sheep blood or body fluids. Farmers reported losing up to 70% of their sheep and goats, and as much as 95% of young lambs (Woods et al., 2002). The next major outbreak started in 2006 in Kenya and 2007 in Tanzania, continuing with Somalia and Sudan. While the Tanzania outbreak had a total number 511 suspected cases, it is unknown how many were really infected and it is believed that only severe cases were detected (Mohamed et al., 2010). For the outbreak in Sudan, up to 75,000 humans may have been exposed (Hassan, Ahlm, Sang, & Evander, 2011). It was estimated that more than 900 people died in the outbreak in the four countries affected (Nanyingi et al., 2015). Based on interviews, it was estimated that more than 400,000 livestock died in Kenya during the outbreak, with large economic consequences (Rich & Wanyoike, 2010). Also in Tanzania the economic consequences were severe, with exports of cattle decreased by more than 50% (Sindato, Karimuribo, & Mboera, 2012). Livestock production is crucial for the livelihood in the arid and semi-arid areas of East Africa, where many are pastoralists, and an outbreak of a severe infectious disease such as RVF can be devastating for the individual livestock holders; however, it will also have an impact on national economy (Anyamba,

Figure 2. Epidemiology of Rift Valley fever

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Linthicum, & Tucker, 2001). After the 2006-2007 outbreak in Kenya, pastoralists ranked RVF as the disease with the highest impact on livestock-derived livelihoods (Jost et al., 2010). This outbreak was estimated to have caused large economic losses to the region. The World Bank (2012) estimated that the entire outbreak in East Africa caused losses of 30 million USD, similar to estimates by Rich and Wanyoike (2010).

Rift Valley Fever, Climate, and Land Use Change RVF epidemics occur when environmental, ecological and climatic factors are conducive. Many studies have demonstrated the association with excessive rainfall, the El Nino Southern Oscillation (ENSO), changes in normalized difference vegetation index (NDVI) and presence of water bodies (Métras et al., 2011; Tourre, Lacaux, Vignolles, & Lafaye, 2009; Anyamba, Linthicum, & Tucker, 2001). However, the association with weather, which is very clear in East Africa where outbreaks occur after periods of above normal rainfall (in intervals of around 5-15 years) (Anyamba, Linthicum, & Tucker, 2001; Davies, Linthicum, & James, 1985), is not as evident in West Africa (Chevalier, Rocque, & Baldet, 2004). There have been several attempts to model how climate change impacts RVF; either using knowledgedriven spatial models, or mathematical dynamic transmission models (Métras et al., 2011). The results of some models are being made available online, such as the model by the healthy future project and University of Liverpool (http://www.healthyfutures.eu/ (Morper-Busch, Kienberger, & Hagenlocher, 2015)). The modelling commonly takes into account mosquito vectorial capacity with biting frequencies and life cycle dependent on temperature, and breeding dependent on precipitation. However, there is a need to incorporate other environmental factors, such as land use, human and animal densities, water storage and irrigation, in such models so as to predict RVF transmission more accurately. Although climate is a very important driver of vector dynamics, more factors may be of importance and we lack a complete understanding of the life cycles of the vectors (Tabachnick, 2010). The consequences of this may be suboptimal prediction models and inaccurate decisions taken in the face of outbreaks. Methods including remote-sensing have also proved very beneficial for studying spatial dynamics of RVF, and the influence of climate and environmental changes, and through this it has been possible to link the dynamics of Aedes vexans with rainfall and changes in water bodies (Tourre et al., 2009). Work in West Africa also shows the possibility of including these techniques in creating risk maps and early warning systems (Vignolles, Tourre, Mora, Imanache, & Lafaye, 2010). Land use changes may have similar effects to climate change, by providing increased mosquito breeding grounds, and changing the availability and movements of different hosts. Increased water storage and utilization along rivers, as well as development of dams and irrigation systems, enlarge the areas that could be suitable for mosquito development, which can increase the risk of RVF transmission. A few outbreaks have been associated with anthropogenic changes to water bodies, such as the 2000-2001 outbreak in Yemen (Abdo-Salem et al., 2006), and the 1987 epidemic in the Senegal River basin (Thonnon et al., 1999). However, it must also be remembered that the purpose of providing a community with irrigation or water reservoirs often is to improve the livelihood of the inhabitants, which may lead to socioeconomic improvements, including increased living standards, improved nutritional status and access to health care and prophylactic measures. These socioeconomic factors may reduce the exposure of humans to pathogens, and make them more resistant to disease, which is likely to reduce the risks of disease spread (Lindahl & Grace, 2015). In addition, agriculture increase, following irrigation, makes

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the communities more resilient to the devastating effect of a Rift Valley fever outbreak in cattle, by providing more diversified means of income and food sources (Figure 3).

Circulation of RVF Virus in Irrigated Areas During the InterEpidemic Period: A Case Study From Kenya Kenya has considerable potential to increase irrigation (You, Xie, Wood-Sichra, Guo, & Wang, 2014) and there are many ongoing and planned irrigation schemes. The Northeast part of Kenya has been the focus of the last outbreaks of RVF, and the first case in the 2006 outbreak was detected in Garissa (Sang et al., 2010). The land bordering the Tana River is semi-arid with increasing irrigation. This area, including Garissa, and Tana River counties, is a hot spot for RVF outbreaks (Martin et al., 2008), and is also high in biodiversity with many endangered species threatened by land use change (Medley, 1993, 2009). Figure 1 is showing the location of the study areas within Kenya. In this case study conducted in 2013-14, the aim was to study the circulation of RVF in an irrigated area by investigating seroprevalence of RVF in humans and animals; perform an entomological survey and interview actors in the animal value chains.

Figure 3. How environmental changes can affect Rift valley fever transmission

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Serum samples from humans, aged 5-90 years old, were collected in villages both from irrigated and non-irrigated, pastoral areas. In total, 303 people were sampled within the irrigation schemes in Bura and Hola in Tana River County, and 728 in the pastoral areas in Ijara district in Garissa County. Serum was tested using a commercial competitive enzyme-linked immunosorbent assay (ELISA) (Biological Diagnostic Supplies Limited, UK) according to manufacturer’s instruction, but with a modified conjugate dilution (1:12 000) and adjusted incubation time. The original protocol was modified after consultation with the manufacturer to allow controls to fall within the fixed range before analyses. This ELISA does not differentiate IgG and IgM antibodies (Kortekaas et al., 2013), and therefore it is not possible to tell if infections causing the seropositivity are old or new. Overall 21.5% (95% confidence interval 19-24%) were seropositive, with no significant difference between the areas. Significantly more adults (over 18 years) were seropositive (p