Theories and Methods for Minimizing Cadmium Pollution in Crops: Case Studies on Water Spinach 9811677506, 9789811677502

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Zhongyi Yang Chuntao He Junliang Xin   Editors

Theories and Methods for Minimizing Cadmium Pollution in Crops Case Studies on Water Spinach

Theories and Methods for Minimizing Cadmium Pollution in Crops

Zhongyi Yang • Chuntao He • Junliang Xin Editors

Theories and Methods for Minimizing Cadmium Pollution in Crops Case Studies on Water Spinach

Editors Zhongyi Yang School of Life Sciences Sun Yat-sen University Guangzhou, Guangdong, China

Chuntao He School of Agriculture Sun Yat-sen University Shenzhen, Guangdong, China

Junliang Xin School of Chemical and Environmental Engineering Hunan Institute of Technology Hengyang, Hunan, China

ISBN 978-981-16-7750-2 ISBN 978-981-16-7751-9 https://doi.org/10.1007/978-981-16-7751-9

(eBook)

© Springer Nature Singapore Pte Ltd. 2022 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Preface

Theories and Methods for Minimizing Cadmium Pollution in Crops: Case Studies on Water Spinach covers a range of topics related to the pollution-safe cultivar (PSC) strategy in minimizing cadmium (Cd) contaminations in crops. The contents include the continuous research works of the co-authors and provide valuable theoretical and practical understandings for controlling Cd pollution in edible agricultural products. Since the Cd-PSCs of water spinach have been intensively focused in our nearly 20 years research works, the understandings involved in the Cd-PSC strategy of water spinach were particularly displayed as a typical case. The contents of each chapter are summarized as follows. Chapter 1: This chapter introduces the current status of Cd contamination in agricultural soil worldwide, which was mainly ascribed to the anthropogenic sources of fertilization, mining, agricultural application of sewage sludge, and wastewater irrigation. Diversified Cd contamination is also summarized in different crop species such as leafy vegetables, cereal, and other crops. Different factors affecting Cd accumulations in crops, including soil physico-chemical characteristics, species, and cultivars of different Cd tolerance are illustrated to provide comprehensive insight on Cd accumulations in the crops. Chapter 2: Traditional methods to deal with heavy metal contamination on agricultural soils usually take long time and high cost. Therefore, Cd pollutionsafe cultivars (Cd-PSCs) strategy is thus proposed based on the cultivar-dependent Cd accumulation. The method facilitates the minimization of Cd pollution in leafy, cereal, and other crops in a low cost and efficient way. In this chapter, the traditional methods for remediating heavy metal-contaminated soils and their limitations, and the wide variations of Cd concentrations among cultivars in various crops as the basis of the Cd-PSC strategy are documented. Chapter 3: The great difference in Cd accumulation among different cultivars has facilitated the selection and breeding of Cd-PSCs of water spinach. Selecting process of water spinach low-Cd cultivars was introduced in this chapter, and an identified low-Cd cultivar (QLQ) and a high-Cd cultivar (T308) were studied in detail to verify the feasibility of the Cd-PSC strategy in water spinach. The stabile differences of Cd v

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Preface

uptake, translocation, and distribution between different cultivars of numerous crop species were also compared. Chapter 4: Rhizosphere properties have exerted remarkable effects on Cd uptake and translocation of plants. In this chapter, the differences in rhizosphere microbe properties and rhizosphere chemical properties between the QLQ and T308 of water spinach are compared. The contents include the effects of activity of rhizosphere microbial community, rhizosphere inorganic chemical performances, and organic compositions on the cultivar-dependent Cd accumulation of water spinach. Feasible methods for the improvement of rhizosphere properties to reducing crop Cd accumulation were also summarized. Chapter 5: Root plays important roles in Cd uptake and translocation in plant by affecting root-to-shoot Cd translocation through root morphology and anatomy. In this chapter, the understandings involving in the relationships between the root morphology or anatomy and the cultivar-dependent Cd accumulation in water spinach obtained from a series of experiments, such as dithizone histochemical experiment and reciprocal grafting experiments, are summarized. Chapter 6: The subcellular concentrations and proportions as well as chemical formations are related to Cd uptake, translocation, and detoxification in plants. This chapter introduced different patterns in subcellular distribution and chemical forms of Cd between QLQ and T308 of water spinach are introduced, and the subcellular and biochemical mechanisms of the cultivar-dependent Cd accumulation are discussed. Chapter 7: Selection and breeding of pollution-safe cultivar has been considered as a practical method for minimizing the concentrations of heavy metals in crops. In order to combine the low-Cd and low-Pb accumulation traits of QLQ with the high yield property of T308, a hybrid is created through continuous selfing followed by crossing of QLQ  T308. The theoretical model, breeding process, properties of the hybrid as a new cultivar, including biomass, Cd and Pb concentrations, and contents of nutritional compositions, are introduced in this chapter. Chapter 8: Molecular mechanisms responding to biotic and abiotic stresses have been investigated using suppression subtractive hybridization in water spinach. The SSH method has identified different responsive genes in shoots and roots between QLQ and T308 under Cd stress. The results are summarized in this chapter, and some proofs of the molecular mechanisms involving the cultivar-dependent Cd accumulation in water spinach are provided. Chapter 9: In this chapter, the transcriptome and microRNAs analyses between QLQ and T308 of water spinach were focused. The Cd-induced genes, such as GAUT, laccase, three Cd efflux genes, and the genes involved in sulfur and glutathione metabolism pathway, e.g., sulfate transporter and cysteine synthase, and the relevant miRNAs have been identified. The relationships between the molecular responses and the transcriptomic or post-transcriptional regulation mechanisms in cultivar-dependent Cd accumulation of water spinach as well as other species are discussed. Chapter 10: This chapter mainly focuses on the future research directions on the breeding of Cd-PSC through marker-assisted breeding technology. The Cd-PSC

Preface

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including durum wheat, sunflower, rice, and water spinach achieved by traditional hybridization were introduced in detail, which has verified the feasibility of Cd-PSC breeding. Molecular technologies involved in marker-assisted selection were systematically summarized. The further creative applications of MAS combining with sequencing and other developed technology are suggested for promising future in Cd-PSC breeding. These book chapters were composed by eminent authorities who have focused on the Cd contamination in crops for the past decades, and the details of authorships are listed in each chapter. I am grateful for timely efforts of all the co-authors to finish the compositions and modifications of the book. Also, we do appreciate the kind and generous work of editorial personnel at Springer Nature Publisher. Finally, I wish the book would bring comprehensive and valuable thoughts to our book readers, who care about the agricultural quality, food safety management, heavy metal contamination, remediation of contaminated soils, and other fields in environmental science. Guangzhou, China

Zhongyi Yang

Acknowledgments

The work was supported by grants from the National Natural Science Foundation of China (Grant No. 21277178, 21707177, 21777195, 20877104, and 41977147), and the Fundamental Research Funds for the Central Universities Sun Yat-sen University (No. 19lgpy182).

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Contents

1

Cadmium Contamination in Agricultural Soils and Crops . . . . . . . Yingying Huang, Samavia Mubeen, Zhongyi Yang, and Junli Wang

2

Intraspecific Variations in Cadmium Accumulation Capacity of Crops and Application of Pollution-Safe Cultivar . . . . . . . . . . . . Hui Yu, Zhongyi Yang, Huixia Duan, Mengyuan Huang, Jin Zhao, and Chuntao He

3

4

5

Cultivar-Dependent Cadmium Uptake and Translocation of Water Spinach and Its Stability . . . . . . . . . . . . . . . . . . . . . . . . . Chuang Shen, Yingying Huang, Huiling Fu, Baifei Huang, Junli Wang, Zhongyi Yang, and Junliang Xin The Effects of Rhizosphere Properties on Shoot Cd Accumulation of Water Spinach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yulian Gong, Zhongyi Yang, Huixia Duan, Jin Zhao, Mengyuan Huang, and Chuntao He A Decisive Role of Roots on Shoot Cd Accumulation of Water Spinach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Qiong Liao, Baifei Huang, Yulian Gong, Chuang Shen, Yingying Huang, Huiling Fu, Zhongyi Yang, and Junliang Xin

1

31

53

65

91

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Subcellular and Chemical Mechanisms Affecting the Cultivar-Dependent Cd Accumulation of Water Spinach . . . . . . . . 105 Huiling Fu, Junli Wang, Baifei Huang, Yingying Huang, Chuang Shen, Zhongyi Yang, and Junliang Xin

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Breeding of New Cultivar of Water Spinach with Low Shoot Cd and Pb Accumulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 Junliang Xin, Yangxiu Mu, Baifei Huang, Chuang Shen, Huiling Fu, Zhongyi Yang, and Yingying Huang

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Contents

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Differences of Cd-Induced Gene Expressions Between Low- and High-Cd Accumulating Cultivars of Water Spinach: A Case Using Suppression Subtractive Hybridization (SSH) Method . . . . . 147 Baifei Huang, Xiaojun Liu, Yingying Huang, Chuang Shen, Huiling Fu, Zhongyi Yang, and Junliang Xin

9

Comparative Transcriptome and MicroRNAs Analyses Between Low- and High-Cd Accumulating Cultivars of Water Spinach . . . . 173 Yingying Huang, Wenjuan Ni, Huiling Fu, Baifei Huang, Zhongyi Yang, Junliang Xin, and Chuang Shen

10

Perspectives on the Marker-Assisted Breeding of the Cd-PSCs . . . . 197 Chuntao He, Huiling Fu, Baifei Huang, Zhongyi Yang, Junliang Xin, Yingying Huang, and Chuang Shen

Editors and Contributors

Editors Zhongyi Yang School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China Chuntao He School of Agriculture, Sun Yat-sen University, Shenzhen, Guangdong, China Junliang Xin School of Chemical and Environmental Engineering, Hunan Institute of Technology, Hengyang, Hunan, China

Associate Editors Yingying Huang School of Chemical and Environmental Engineering, Hunan Institute of Technology, Hengyang, Hunan, China Hui Yu School of Life and Health Science, Hunan University of Science and Technology, Xiangtan, Hunan, China Junli Wang School of Public Health, Guizhou Medical University, Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guiyang, Guizhou, China Huiling Fu School of Chemical and Environmental Engineering, Hunan Institute of Technology, Hengyang, Hunan, China Chuang Shen School of Chemical and Environmental Engineering, Hunan Institute of Technology, Hengyang, Hunan, China Samavia Mubeen School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China

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Editors and Contributors

Yulian Gong College of Biology and Food Engineering, Guangdong University of Education, Guangzhou, Guangdong, China

Contributors Baifei Huang School of Chemical and Environmental Engineering, Hunan Institute of Technology, Hengyang, Hunan, China Wenjuan Ni School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China Gannan Medical University, Ganzhou, Jiangxi, China Xiaojun Liu Quatech Consulting Co., Ltd., Guangzhou, Guangdong, China Qiong Liao School of Chemical and Environmental Engineering, Hunan Institute of Technology, Hengyang, Hunan, China Yangxiu Mu Ningxia Center of Agricultural Organic Synthesis, Agricultural Resource and Environment Institute of Ningxia Academy of Agriculture and Forestry Science, Yinchuan, Ningxia, China Mengyuan Huang School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China Huixia Duan School of Life Science, Sun Yat-sen University, Guangzhou, Guangdong, China Jin Zhao School of Life Science, Sun Yat-sen University, Guangzhou, Guangdong, China

Abbreviations

ABA ABCC1/2 AGO AIC AMF APS 1, 3, and 4 APX APX AWCD BY-2 Ca CAC CaCO3 CAXs Cd CEC CesA CHI CIMMYT Cu CV DCL1 DEGs DHAR DOM EC10, 50 FDA FI FII FIII

Abscisic acid ATP-binding cassette, subfamily C 1/2 ARGONAUTE Akaike’s information criterion Arbuscular Mycorrhizal Fungus ATP sulfurylases 1, 3, and 4 Ascorbic peroxidase gene Ascorbate peroxidase Average well color development Bright yellow-2 Calcium Codex Alimentarius Commission Calcium carbonate Cation/H+ antiporters Cadmium Cation exchange capacity Cellulose synthase Chalcone isomerase International Maize and Wheat Improvement Center Copper Coefficient of variations DICER-LIKE1 Differentially expressed genes Dehydroascorbate reductase Dissolved organic matter Effective concentration of 10% and 50% Food and Drug Administration Fraction I Fraction II Fraction III xv

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FTIR GAUT GGT GR GSH HE HMA3 HMAP HST IARC ICARDA IPT ISSR JSA LAC LMWOA MATE9 MDHAR miRNAs MLV MRP7 MTP3 MTs Na NGS n-HA NHE Nramp1/5 PCs PME POD pri-miRNAs PSCs QTL RADseq RAPD RFLP ROS Se SOD SOM SS STTMs SULTR2;1

Abbreviations

Fourier transform infrared spectroscopy Galacturonosyltransferase Glutathione-γ-glutamylcysteinyl transferase Glutathione reductase Glutathione Hyperaccumulating ecotype Heavy metal ATPase 3 Heavy metal accumulating plant HASTY International Agency for Research on Cancer International Center for Agricultural Research in the Dry Areas Isopentenyl transferase Inter-simple sequence repeat Joint segregation analysis Laccase Low molecular weight organic acid Multidrug and toxic compound extrusion 9 Monodehydroascorbate reductase MicroRNAs Maximum log-likelihood values Multidrug resistance protein 7 Metal tolerance protein 3 Metallothioneins Potassium Next-generation sequencing Nano-hydroxyapatite Non-hyperaccumulating ecotype Natural resistance-associated macrophage protein 1/5 Phytochelatins Pectin methylesterase Peroxidases Primary miRNAs Pollution-safe cultivars Quantitative trait loci Restriction site-associated DNA sequencing Random amplified polymorphic DNA Restriction fragment length polymorphism Reactive oxygen species Selenium Superoxide dismutase Soil organic matter Sewage sludge Short tandem target mimics SULFATE TRANSPORTER 2;1

Abbreviations

SVI TB YSL ZIP Zn

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Seedling vigor index Torubamubiga Yellow stripe-like protein Zinc-regulated transporter/iron-regulated transporter-like protein Zinc

Chapter 1

Cadmium Contamination in Agricultural Soils and Crops Yingying Huang, Samavia Mubeen, Zhongyi Yang, and Junli Wang

Contents 1.1 Cd Contamination in Agricultural Soils Worldwide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.1 Background Cd Concentrations in Soils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.2 Current Status of Cd Contamination in Soils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.3 The Anthropogenic Sources of Soil Cd . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 The Situations of Cd Contamination in Crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.1 Cd Contamination in Leafy Vegetables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.2 Cd Contamination in Cereal Crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.3 Cd Contamination in Other Crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Exogenous Regulation of Cd Uptake and Accumulation in Crops . . . . . . . . . . . . . . . . . . . . . . . . 1.3.1 Leafy Vegetables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.2 Cereal Crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.3 Fruit And Root (Tuber) Crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2 2 2 4 6 9 11 12 14 15 19 19 20

Cadmium (Cd) is a highly toxic heavy metal belonging to Group 1 human carcinogen (IARC) (Chaney 1980). Cd contamination is a worldwide problem, especially for the mining and wastewater-irrigated areas (Huang et al. 2017a, b, Zhao et al. 2014). Although Cd is unessential to plant growth, it can be easily absorbed by crops and transferred to human bodies through food chain (Clemens et al. 2013). The accumulation of Cd by crops depends on the availability of Cd in the soils as well as the genetic characteristics of crops (Grant et al. 2008; Roberts 2014).

Y. Huang School of Chemical and Environmental Engineering, Hunan Institute of Technology, Hengyang, Hunan, China S. Mubeen · Z. Yang School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China J. Wang (*) School of Public Health, Guizhou Medical University, Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guiyang, Guizhou, China © Springer Nature Singapore Pte Ltd. 2022 Z. Yang et al. (eds.), Theories and Methods for Minimizing Cadmium Pollution in Crops, https://doi.org/10.1007/978-981-16-7751-9_1

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1.1 1.1.1

Y. Huang et al.

Cd Contamination in Agricultural Soils Worldwide Background Cd Concentrations in Soils

Cd is a trace element in the geological parent materials, with a mean value of 0.2 mg kg 1 (Lindsay 1979). The minerals on earth contain Cd with different levels, which became the source of Cd through weathering process (Alloway 2012). As reviewed by Kabata-Pendias and Pendias (1992), the average background Cd concentrations of soil in the world lie in the range 0.06~1.1 mg kg 1, with a minimum of 0.01 mg kg 1, and a maximum of 2.7 mg kg 1. Soil Cd levels vary in different areas in the United States, with an average value of 0.27 mg kg 1 (Holmgren et al. 1993) or 0.32 mg kg 1 (Burt et al. 2003), which is similar to that of Europe (0.30 mg kg 1) (Alloway 2012), such as Italy (0.3 mg kg 1, Angelone et al. 1995) and Spain (0.3 mg kg 1, Cal-Prieto et al. 2001; 0.5 mg kg 1, Sanchez-Camazano et al. 1994). In the Netherlands, soil Cd levels is 0.04–14.0 mg kg 1, with a mean value of 0.5 mg kg 1 and a median of 0.4 mg kg 1 (Wiersma et al. 1986). Average soil Cd level in Denmark and New Zealand is 0.2 mg kg 1 (Wakelin et al. 2016). In China, a survey on background values of soil elements was conducted by the Ministry of Environmental Protection and China National Environmental Monitoring Centre (1990), which displayed that the Cd concentration background values of topsoil ranged from 0.001 mg kg 1 to 13.430 mg kg 1 with an average of 0.074 mg kg 1. As shown in Table 1.1, the southwestern provinces (including Guizhou, Guangxi, and Yunan) exceed the national average, indicating the different contributions of geological parent materials to the variable soil Cd concentrations in different regions. According to Teng and Liu (2010), the average Cd concentrations of uncontaminated soils in China is 0.163 mg kg 1 (ranging from 0.01 mg kg 1 to 1.80 mg kg 1), lower than the average values of other regions of the world above mentioned.

1.1.2

Current Status of Cd Contamination in Soils

As reported by many researchers, Cd could be released to soil via natural and anthropogenic activities, resulting in Cd contamination in many regions, especially in mining and wastewater-irrigated areas (Bourioug et al. 2015; Six and Smolders 2014; Zhao et al. 2014). Cd contamination in agricultural soils and its health risks from contaminated food consumption has already attracted broad attention around the world, such as Jinzu River basin of Japan (Ishihara et al. 2001; Uetani et al. 2006) and northwestern Thailand (Kosolsaksakul et al. 2014) As reported by Rawlins et al. (2012), 45% and 20% of the soils were polluted by Cd in England and Wales, respectively. In the United Kingdom, the average Cd concentration is 0.7 mg kg 1 (McGrath and Loveland 1992), which is similar to another study that shows an average Cd concentration in United Kingdom agricultural soils of 0.6 mg kg 1 with

1 Cadmium Contamination in Agricultural Soils and Crops

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Table 1.1 Average soil background values and Cd concentrations in agricultural and urban soils (mg kg 1) in different provinces from China (Wang et al. 2015) Region China North

Northeast

East

South central

Southwest

Northwest

Province

Agricultural soil

Urban soil

Beijing Tianjin Hebei Shanxi Inner Mongolia Liaoning Jilin Heilongjiang Shanghai Jiangsu Zhejiang Anhui Fujian Jiangxi Shandong Henan Hubei Hunan Guangdong Guangxi Hainan Chongqing Sichuan Guizhou Yunnan Tibet Shaanxi Gansu Ningxia Xinjiang

0.200 0.278 0.169 0.170

0.172 0.250

0.144 0.047 0.078 0.196 0.182 0.207 1.328 0.376 0.175 0.128 0.067 0.513 1.019 0.313

1.254 0.367 0.179 0.391 0.131 0.853 0.288 0.350 0.400 0.239 1.138 0.148 4.667 0.299

0.144 0.285 1.121 0.323 0.761 1.507 0.193 0.779 0.120

0.208

0.357

3.561

Background 0.074 0.074 0.090 0.094 0.128 0.053 0.108 0.099 0.086 0.138 0.126 0.070 0.097 0.074 0.108 0.084 0.074 0.172 0.126 0.056 0.267 0.027 0.133 0.079 0.659 0.218 0.081 0.094 0.116 0.112 0.120

a range of 1~10.5 mg kg 1, and a median of 0.5 mg kg 1 (McLaughlin and Singh 1999). In 2014, the Ministry of Environmental Protection and the Ministry of Land and Resources of China published a report on the current soil pollution status of China, named National Soil Pollution Survey Bulletin, based on extensive surveys of eight inorganic pollutants (Cd, mercury, arsenic, copper, lead, chromium, zinc, and nickel) and three organic pollutants (hexachlorocyclohexane, dichlorodiphenyl trichloroethane, and polyaromatic hydrocarbons) from 2005 to 2013 covering 6.3 million km2 of mainland China. This report has attracted wide attention since

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it disclosed a serious situation of soil quality in China. According to the report, the overall situation of soil quality in China is not optimistic, especially for the mining and industrial wastelands, and the farmland soil quality also arouse concerns. The report suggested that 16.1% of surveyed soils exceeded the environmental quality standard, including 19.4% farmland soils. Among these contaminated soils, inorganic contaminants account for the majority (82.4%), and Cd ranks first in the percentage of contaminated soils (7%). Wang et al. (2015) reviewed the soil Cd contamination problems in China covering 190 publications from 2001 to 2010, in which topsoil Cd concentrations were employed to reflect Cd contamination. As shown in Table 1.1, urban soil Cd concentrations in Liaoning, Henan, Hunan, and Gansu provinces were much higher than that of agricultural soils and the limitation of the environmental quality standard for soils, indicating these urban soils are mainly contaminated by the more extensive anthropogenic activities in these provinces. Generally, these results were comparable to the soil Cd concentrations in other countries, e.g. Canada (3.5 mg kg 1 in remote areas and 5 mg kg 1in contaminated soils), Scotland (0.25~1.5 mg kg 1), and the United States (0.25 mg kg 1 in remote areas and 4 mg kg 1 in contaminated soils) (UNEP 2010).

1.1.3

The Anthropogenic Sources of Soil Cd

Except for the natural sources, anthropogenic activities had become the primary sources of soil Cd contamination since the establishment of industrial revolution. Anthropogenic activities, such as fertilization, mining, and sewage irrigation, had contributed three to ten times more Cd to the environment than natural process (Huang et al. 2017a, b, Liu et al. 2005, Thornton 1992, Zhang et al. 2015a, b). It is estimated that millions of tons of toxic heavy metals are released into the environment every year (Nriagu and Pacyna 1988). In China, over the past 60 years, more than 125.893 tons of Cd has been discharged into the environment by sewage irrigation, and most of them are accumulated in soils and thus cause serious Cd contamination (Shi et al. 2019). 1. Fertilization Many researchers have shown that the application of Cd-contaminated fertilizers (including nitrogen, phosphorus, and potassium fertilizer) may increase Cd concentrations in soils of many regions around the world, including the United States (Mulla et al. 1980), Norway (Baerug and Singh 1990), Denmark (Christensen 1991), Finland (Makela-Kurtto 1991), and China (Shi et al. 2019). In Australia, Cd concentrations in topsoil were increased 5~12 folds attributed to phosphorus fertilization (Williams and David 1976). It has been estimated that fertilizer application has increased Cd in soils by 7~43% over the past few decades, in some Europe countries (including the United Kingdom, Ireland, Denmark, Austria, Greece, and Finland) (UNEP 2010). In Australia and

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New Zealand, the application of fertilizers is considered to be the primary source of heavy metals released to soil, especially for Cd (Bolan and Duraisamy 2003). As reported by Shi et al. (2019), agricultural soil Cd concentrations significantly correlate with fertilizer application amounts ( p < 0.05) in China. Hajar et al. 2012) found that soil Cd concentration was significantly correlated with potash fertilizer application amounts. Huang et al. (2017a, b) also suggested that the phosphate fertilizers containing Cd were a main pollutant source of Cd in paddy soils. In many long-term field studies, the increase of soil Cd concentrations contributed by phosphate fertilization can result in the increase of plant Cd concentration (Basta et al. 1998; Mulla et al. 1980; Oliver et al. 1993; Williams and David 1976), indicating that the fertilizer application can affect either soil Cd concentration or crop Cd accumulation (Grüter et al. 2017; Zhang et al. 2015a, b). On the other hand, long-term fertilization may result in changes of the soil characteristics, including soil pH, contents of organic matter, cation exchange capacity (CEC) and complex formation, and further influence the phytoavailability of the soil Cd (Grant and Sheppard 2008). 2. Mining Many studies have shown that mining is one of the major contributors to soil Cd contamination due to the discharge and diffusion of mine wastes. Increasing Cd can be found in the farmlands nearby the abandoned metal tailings (Navarro et al. 2008). It has been estimated that approximately 240,000 km2 of lands in the world have been contaminated by mining activities by the year 2000 (McLaughlin and Singh 1999). In the United Kingdom, about 40 km2 of soil land has been polluted by metalliferous mining activity (Mitchell and Atkinson 1991). In China, about 15,000 km2 of land has been contaminated by mining, and it increases by 467 km2 per year (Zhuang et al. 2009a). It has been reported that Cd concentrations of the soils nearby the Pb-Zn mines (3.8 mg kg 1) were much higher than that of the upstream control sites (0.90 mg kg 1) in Northern Vietnam (Bui et al. 2016). High levels of Cd were also found in other mine tailings, such as the former Jebel Ressas mine in Northeast Tunisia (89 mg kg 1) and the Jebel Ressas mining area (53 mg kg 1) (Elouear et al. 2016). The average Cd concentrations of paddy soil around Dabaoshan mine (Guangdong province, China) was 3.92 mg kg 1 (Zhuang et al. 2009b). As reported by Yuan et al. (2012), Cd contamination was mainly found in Yunnan, Guangdong, Hunan, and Guizhou, which possess abundant minerals and intensive mining and smelting activities are continued. 3. Agricultural application of sewage sludge Sewage sludge (SS) was widely used in agricultural production due to its beneficial contents such as N, P, and organic matter. However, sewage sludge also contains heavy metals, including Cd, and it has been reported that about 80~90% of the metals in wastewater were accumulated in SS. As reported by Alloway (2012), average Cd concentration in SS in Europe is 2.0 mg kg 1. García-Delgado et al. (2007) investigated heavy metal concentrations in SS from seven wastewater treatment plants of Salamanca (Spain); the results showed

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that Cd concentrations in SS were 1.63~2.40 mg kg 1. Cd concentrations in SS collected from different wastewater treatment plants in five cities of Pakistan ranged from 0.32 to 3.29 mg kg 1 (Riaz et al. 2020). In South Africa, Cd concentrations in SS of 18 wastewater treatment plants using different treatment processes ranged from 0.3 to 167 mg kg 1 (Badza et al. 2020). As reviewed by Guo et al. (2014), SS Cd concentrations in China ranged from 0.4 to 39.9 mg kg 1, with a mean value of 2.1 mg kg 1. 4. Wastewater irrigation Irrigation by wastewater containing Cd is proved to be a main source of soil Cd contamination from industrial activities by previous studies (Huang et al. 2017a, b). Huang et al. (2017a, b) have compared soil Cd concentrations in some wastewater irrigation regions across the world (Table 1.2). Cd concentration in wastewater-irrigated soils in Serbia and Jordan are 1.1–1.5 mg kg 1 and 2.0 mg kg 1, respectively, and those in Lahore, Hyderabad, and Sialkot of Pakistan are 3.15 mg kg 1, 4.30 mg kg 1, and 9.15 mg kg 1, respectively, which were comparable to those in Tianjin (1.24–2.58 mg kg 1), Kaifeng (1.70 mg kg 1), and Dunhua (1.25 mg kg 1) of China. Surprisingly, soil Cd concentrations in wastewater-irrigated areas in Titagarh (India) and Sizhuangding (China) reach up to 22.2–51.0 mg kg 1 and 65.3 mg kg 1, respectively.

1.2

The Situations of Cd Contamination in Crops

Plant uptake of Cd from soil disturbs its growth, reduces crop yield, and affects food quality and safety, which raised public health concern due to Cd accumulation in the food chain (Yang et al. 2004). Worldwide, crops and vegetables are exposed to Cd pollutants by various means, and their consumption causes adverse health effects in humans. A well-known health problem caused by Cd “Itai-Itai disease” occurred in Japan in the 1950s due to the long-term intake of Cd-contaminated rice. At that time, the weekly average Cd intake was more than 3–4 mg kg 1 body weight in Japan (Horiguchi et al. 1994; Tsukahara et al. 2003). The average dietary Cd intake of the Chinese population was double during 1990 and 2015 (Song et al. 2017; Chen et al. 2018). In Huludao city in China, the concentration of Cd in vegetables ranged between 0.003–0.624 mg kg 1, and the maximum Cd limit exceeds the recommended values (Zheng et al. 2007). Similarly, Cd concentrations in Australian and Bangladeshi vegetables were higher than the Australian standard maximum limit (0.1 mg kg 1) (Rahman et al. 2014). U.S. Food and Drug Administration (FDA) total diet study found the highest concentration of Cd in iceberg lettuce (0.051 mg kg 1), leaf lettuce (0.064 mg kg 1), peanuts (0.054 mg kg 1), and spinach (0.124 mg kg 1). The Cd concentration in all vegetables ranged from 0.001 to 0.124 mg kg 1 (FDA 2010; Morrow 2000). Similarly, comparable Cd concentrations ranging from 0.228 to 0.42 mg kg 1 DW were found in chard, celery, leek, onion, and radish plants from five common locations in Dohuk city Iraq (Sulaivany

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Table 1.2 The Cd concentrations of wastewater-irrigated soils (Modified according to Huang et al. 2017a, b) Countries China

Pakistan

India

Zimbabwe Jordan Iran Serbia

Regions Beijing Beijing-Tianjin cluster Tianjin Baoding Shenyang Kaifeng Shenfu Xi’an Taiyuan (xiaodian region) Langfang Xinxiang Guixi Linfen Tongliao Dunhua Urumqi Area of Pearl River Delta Hyderabad Lahore Sialkot Delhi Nilothi Ranhola Mundka Bakarwala Hirankudna Dichaonkala West Bengal Titagarh Varanasi Ghaziabad Kolkata Harare – Tehran-Varamin Belgrade

Concentration (mg kg 1) Mean Min 0.18 0.1 0.46  0.02 – – 1.24 0.22 0.17 – 0.30 1.70 0.43 0.6  0.13 0.38 0.62 0.31 0.057 0.27  0.05 0.19 65.31 4.3 – 0.398 0.33 0.002 0.56 0.38 1.25 0.9 0.12  0.06 0.04 0.76  0.2 0.42 4.3  0.41 – 3.15  9.1 1.29 9.15  1.33 7.13 0.20 0.11 0.15 0.05 0.11 0.02 0.22 0.04 0.14 0.01 0.14 0.04 30.72 22.2 3.12  0.19 1.8 3.30 – – 8 – 0.5 – 1.2 0.67 – 2  0.2 –

Max 0.27 – 2.58 0.40 1.99 3.62 0.84 0.82 0.715 0.35 127.82 1.495 1.19 0.74 1.76 0.44 1.23 – 5.18 11.13 0.37 0.41 0.46 0.85 0.09 0.26 51.0 4.8 13 3.4 1.5 – –

and Al-Mezori 2007). A comparatively low Cd concentration ranging from 0.066 to 0.115 mg kg 1 in supplier samples and from 0.055 to 0.123 mg kg 1 in producer samples were found in different vegetables in Warmia/Mazury, Poland (Dymkowska-Malesa et al. 2007). Different national surveys in different regions of the world showed that the Cd concentration in wheat grain ranged from 0.002 to 0.21 mg kg 1 DW in the USA;

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0.024 to 0.41 mg kg 1 DW in the Netherlands; 0.004 to 0.31 mg kg 1 DW in UK; and 0.01 to 0.24 mg kg 1 DW in Canada (Wolnik et al. 1983; Wiersma et al. 1986; Chaudri et al. 1995; Gawalko et al. 2001). The Cd concentration for barley grain in the Netherlands ranged from 0.012 to 0.64 mg kg 1 DW (Wiersma et al. 1986). The Cd contents in the home-consumed rice grain from the paddy fields of Pha Te village Thailand ranged from 0.04 to 1.75 mg kg 1, which was higher than the CODEX standard level of 0.4 mg kg 1 polished rice (Sriprachote et al. 2012). A much high Cd concentration of 19.5 mg kg 1 was found in the maize grains in the UK (Retamal-Salgado et al. 2017). Apart from cereals grains, Cd concentrations ranging from 0.08 to 0.28 mg kg 1 for legumes, from 0.07 to 0.27 mg kg 1 for grasses, and from 0.001 to 0.054 mg kg 1 for nuts were found in different regions of the world (FDA 2010; Kabata-Pendias and Pendias 2001). In four different locations of North Dakota and Minnesota, the concentration of Cd in kernels of nine sunflower cultivars varied from 0.79 to 1.17 mg kg 1 (Li et al. 1995). Some phosphatic fertilizers are considered as the potential cause of Cd contamination in crops as they contain a high concentration of Cd (4.77 μg g 1) (Muramoto and Aoyama 1990). Under such conditions, different crops such as sunflower, wheat, flax, and rice can accumulate higher Cd than the proposed acceptable Cd concentration limits. An increased Cd concentration of 1.51–2.14 mg kg 1 was reported in four Brassica rapa L. var. perviridis cultivars after phosphate fertilizer application in Japan (Mar et al. 2012). Industrial activities such as wastewater irrigation and mining are also significant sources of Cd contamination in plants. The Cd contamination level of broccoli grown in the electronic waste processing site in China was 0.79 mg kg 1 (Luo et al. 2011), while the Cd content of radish grown in the waste-irrigated suburban area in Titagarh, India was 17.79 mg kg 1 (Gupta et al. 2008). The occurrence of higher Cd concentration (0.05 mg kg 1 FW) in potatoes was associated with saline water irrigation in areas of South Australia (McLaughlin et al. 1994). Comparative Cd contents were found in different plants grown in glasswork sites in Sweden (Augustsson et al. 2015), Shizhuyuan mine area in China (Zhou et al. 2016), and industrialized areas of Italy (Beccaloni et al. 2013). The industrial regions of Australia such as commercial farms and vegetable gardens are more contaminated by Cd as compared to other regions of Australia (Kachenko and Singh 2006). The plant species exhibited vast genotypic differences, so the behavior of heavy metal accumulation in plants also varies from cultivar to cultivar (Liu et al. 2007; Jamali et al. 2009). Some plants, including maize, pea, oat, and wheat, are low accumulators of heavy metals, while some of the leafy vegetables such as spinach, endives, lettuces, and related horticulture crops are considered as Cd hyperaccumulators due to the high Cd uptake, translocation, and accumulation potential (Peijnenburg et al. 2000; Puschenreiter et al. 2005). In general, much of the Cd accumulation is localized in leafy vegetables; low fractions are found in root vegetables and lowest in the grain crops (Bingham 1979). Indeed, although there are a few species of grain crops that show higher Cd accumulation than others. The grain crops species that exhibited Cd accumulation over the limit demonstrated by WHO are wheat, durum wheat, corn, barley, oat, rice, and peas (Greger and Löfstedt 2004;

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Cajuste et al. 2006; Tsyganov et al. 2007). Therefore, Cd contamination in agriculture soil and the use of the contaminated soil for cereal crops, fruits, vegetables, and other commercially important plants has aroused considerable attention in recent years (Zhuang et al. 2009a, b; Liu et al. 2010).

1.2.1

Cd Contamination in Leafy Vegetables

Vegetables are essential edible crops and are an integral part of the human diet. They are rich in nutrients required for human health and are essential source of carbohydrates, vitamins, minerals, and fibers (Hu et al. 2013; Yang et al. 2009). Heavy metals, especially Cd, can be readily taken up by vegetable roots and accumulated at high levels in the edible parts of vegetables, even present at a low level in the soil (Yang et al. 2009; Jolly et al. 2013). The human consumption of leafy vegetables increases the health risks associated with Cd (Huang et al. 2017a, b). Plant response to Cd uptake, accumulation and toxicity differ greatly among vegetables, genotypes, and cultivars among the same species (Zhu et al. 2007; Säumel et al. 2012). Alexander et al. (2006) reported that Pb significantly accumulated in lettuce and onion, while Cd accumulated to the greatest extents in spinach and lettuce. Leafy vegetables such as Chinese leek, pakchoi, lettuce, and spinach can accumulate higher concentration of Cd in their aerial edible parts as compared to other vegetables that belong to solanaceous and cucurbit crops and root groups such as cucumber, carrot, and tomato (Yang et al. 2009, 2010; Younis et al. 2015). The trends of Cd accumulations in vegetable species are observed as leafy vegetables > solanaceous vegetables > root vegetables > alliums vegetables > melon vegetables > legumes vegetables (Yang et al. 2010). Cd toxicity disturbs the plant morphology, growth, biomass production, photosynthesis rate, quality, and yield (Gharaibeh et al. 2015; Mombo et al. 2016). The application of 0.5 mg kg 1 Cd in hydroponic conditions showed a significant decrease in total leaf area and dry weight of root, stem, and leaf of the cabbage (Brassica oleracea L.) variety, Pluto, as compared to the control (Jinadasa et al. 2016). Cd inhibited various growth and biochemical parameters such as seedling vigor index (SVI), leaf and root elongation, chlorophyll, and carotenoids contents in seedlings of five cultivars of Brassica juncia L (Bauddh and Singh 2011). Similarly, Cd significantly affected the uptake and accumulation of different mineral nutrients in vegetables (Zhi et al. 2015; Li et al. 2015). Cd caused nutrients imbalance in root and leaves of lettuce (Lactuca sativa L.), decrease in the rate of photosynthesis and enhancement in lipid peroxidation, which culminated in a reduction in growth and biomass of lettuce (Monteiro et al. 2009). Cd-mediated decrease in the concentration of mineral elements including Ca, Zn, Cu, Fe, and Mn was reported in roots, stem, and leaves of cabbage (Brassica oleracea L.) (Jinadasa et al. 2016). Recently, Khan et al. (2015) reported that Cd is responsible for the significant decrease in mineral elements (N, P, K, Ca, Fe, and Mn) in lettuce, depending upon the species.

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Similarly, Cd uptake varies considerably among different leafy vegetables grown in different Cd-contaminated soils. For example, Cd concentration differs significantly in five leafy vegetables, namely leaf mustard, morning glory, leaf lettuce, bitter lettuce and lettuce collected from two sites of Guangzhou, South China, among which leaf mustard and leaf lettuce accumulated the highest and lowest Cd accumulation respectively (Li et al. 2015). Cd accumulation in vegetables might be dominantly ascribed to Cd from irrigation using wastewater and sewage sludge in peri-urban areas (Ahmad and Goni 2010; Anwar et al. 2016; Baldantoni et al. 2016). Cd concentrations exceeded the recommended level in the five leafy vegetables, namely spinach, lettuce, celery, coriander and parsley grown in the wastewaterirrigated agricultural field of Titagarh, West Bengal, India than those from ecological forms and markets (Gupta et al. 2008). Similarly, Cd and other toxic metals can increase in vegetables grown in soils of former mining and industrial areas and soils exposed to long-term fertilization (Alvarenga et al. 2014; Bui et al. 2016; Antoniadis et al. 2017). The Cd concentrations varied not only among vegetable species but also among the cultivars of the same species. The accumulation of Cd in leafy vegetables differed significantly among different cultivars (Yu et al. 2006; Zhu et al. 2007). Shoot Cd concentrations were about 1.4-fold different between selected high- and low-Cd-accumulating cultivars of 28 Chinese kale (Brassica alboglabra L.) cultivars (Guo et al. 2018). Similarly, among 28 cultivars of lettuce, the four cultivars of SJDT, YLGC, N518, and KR17 showed less Cd accumulation abilities in shoots as compared to the control (Zhang et al. 2013). In another study, pot experiment confirmed that the two pakchoi cultivars of Hualv 2 and Huajun might be safe for food consumption when grown in lower Cd treatment (1.052 mg kg 1) (Wang et al. 2014a). Wang et al. (2009) performed a pot experiment on 30 water spinach (Ipomoea aquatica Forsk) cultivars and found out that the maximum difference in Cd concentration was 3.0–3.9 folds under low-Cd treatment (0.593 mg kg 1). Six cultivars, such as Daxingbaigu, were identified as Cd-PSCs for their low Cd concentration under permissible limit (0.2 mg kg 1), the Codex Alimentarius Commission (CAC). Similarly, in another experiment, 38 water spinach cultivars were screened and the four cultivars of JXDY, GZQL, XGDB, and B888 were found to have low Cd-accumulation (stems>leaves. In all the green leafy vegetables, Cd concentrations were higher in roots as compared to stems and leaves. However, in several leafy vegetables, the translocation of Cd from roots to

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shoots varies considerably, and Cd primarily accumulates in leaves (Kabata 2011; Rizwan et al. 2017).

1.2.2

Cd Contamination in Cereal Crops

Cereals have been the staple food for humans from pre-historic times. The most cultivated cereal crops around the world are wheat, rice, maize, jawar, barley and sorghum, etc. Among them, wheat and rice account for 4/5 parts of the total food consumption of the world’s population (Tejera et al. 2013). Total wheat consumption in Iran has risen from 15.8 MT to 17.5MT during 2010–2015 (USDA Foreign Agricultural Service 2015). However, the accumulation of heavy metals in the cereals crops more than the permissible limit leads to an adverse effect on human health. There have been multiple studies available on the levels of heavy metals concentration in cereals around the world and their risk to human health (Moradi et al. 2013; Salehipour et al. 2015). The Cd uptake by cereal crops depends on several factors, including soil type, soil pH, level of soil contamination, and type of cultivar (Harris and Taylor 2013). Wenzel et al. (1996) revealed the effect of soil chemical properties and cultivar type on Cd accumulation in wheat grains at seven different experimental sites in Australia and over 80% variations were associated with cultivar type, soil Cd level, and organic carbon. Adams et al. (2004) revealed that 22% and 53% variance in Cd accumulation of barley and wheat depended on the soil Cd level and soil pH. Increasing pH favored the adsorption of Cd and deceases the partition of Cd to soil (Li et al. 2010a, b). In an acidic environment, at pH 7–6, most of the Cd was in the available form to plant (Smolders and McLaughlin 1996). Apart from soil pH, Cd uptake and accumulation is greatly affected by excretion/presence of organic acids in the rhizosphere that manipulate the soil pH, redox potential, and activity of microbes in the rhizosphere and chelating capacity of Cd ions. It is worth observing that the higher Cd concentrations are not always depend upon high Cd contamination in soil. Phenotypic variations are more dominant to control Cd accumulation in crops under field conditions as compared to soil factors (Zeng et al. 2008; Li et al. 2018). After absorption from the soil, Cd is either translocated to the grains via xylem transport or as a part of photosynthate from leaves to grains via the phloem (Greger and Löfstedt 2004; SONG et al. 2015). Chan and Hale (2004) found that a combination of lower root to shoot and higher shoot to grains Cd translocation is responsible for higher Cd concentration in grains of durum wheat cultivars. (Kato et al. 2010) found the higher Cd concentration in phloem sap and observed that the concentration of Cd in the phloem sap determined the intraspecific variation of grain Cd concentration. However, the mechanisms behind the Cd uptake and translocation in cereal crops is still unclear and further needed to be explored. Responses of Cd uptake in cereal crops have been investigated using shoot/root elongation, seedling growth and biomass/yield production as an indicator (Rehman

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et al. 2015; Mostofa et al. 2015; Wang et al. 2014b). The study by SONG et al. (2015) showed that the relative root elongation of rice cultivars decreased with an increased Cd concentration. The Cd effective concentration of 10% and 50% inhibition (EC10, 50) for rice ranged from 1.4 to 8.2 mg kg 1 and 17.83 to 68.16 mg kg 1 respectively, depending upon the soil and cultivar type. Rebekić and Lončarić (2016) quantified phenotypic variation of 51 winter wheat cultivars under the Cd treatment of 20 mg kg 1. Their investigation concluded that high Cd concentration caused a significant reduction of 27%, 5.2%, and 23%, in seed weight per spike, kernel weight, and seed number per spike, respectively, as compared to the control. Besides, a significant decrease in Fe and Mn concentration were detected with increasing Cd concentration in 32 tested varieties of rice (Li et al. 2012). Other studies also reported decreased levels of Fe in wheat and corn roots and shoots under Cd stress (Bao et al. 2012). It has been observed that Cd responses varied significantly among different crops and among cultivars within the same species (Grant et al. 2008; Liu et al. 2010; Sebastian and Prasad 2015). In a meta-analysis on phenotypic variation in Cd accumulation of rice and wheat cultivars, Xiaofang and Dongmei (2019) found a general pattern in almost all the tested cultivars that higher Cd concentrations are present in root as compared to shoot and least Cd contents are present in grains. Similar results were also found in a pot experiment with maize variety “Fuyou1,” with Cd concentration ranked in order of root >down-leaf >stem >up-leaf>grain and jointing stage >flowering stage >ripening stage (Cao et al. 2006). Conflicting reports are present in the literature about whether leaves, roots, and grains accumulate higher Cd content (Li et al. 2006; Uraguchi et al. 2009; Xu et al. 2013; Fässler et al. 2010). The Cd uptake, accumulation, and stress response varies with the cultivar, dose, and duration of Cd stress (Cao et al. 2014; Uraguchi et al. 2009).and the uptake of Cd was more elevated in low Cd-accumulating cultivar Sasanishik as compared to highCd-accumulating cultivar Habataki, while the higher root to shoot Cd translocation was responsible for higher Cd content in the grains of cultivar Habatakin (Uraguchi et al. 2009). Numerous studies reported that Indica cultivars of rice had high Cd concentration in shoot and grains as compared to japonica rice cultivars (He et al. 2006; Uraguchi et al. 2009; Ye et al. 2012; SONG et al. 2015). Furthermore, the much higher concentrations of Cd have been recorded in some specific cultivars among Indica rice (Uraguchi et al. 2009; Ye et al. 2012). Similarly, Vergine et al. (2017) conducted an experiment with two durum wheat near-isogenic lines and 12 commercial varieties, with Svevo and Cirillo identified as high Cd-accumulating and Iride as low-Cd-accumulating cultivar.

1.2.3

Cd Contamination in Other Crops

Several studies were conducted to investigate the Cd accumulation patterns in different plants. The root-to-shoot ratio of Cd translocation was almost similar and

1 Cadmium Contamination in Agricultural Soils and Crops

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only 22% of the total absorbed Cd was transferred to shoots in most plants (de Andrade et al. 2008). In Kentucky bluegrass (Poa pratensis), more Cd has been translocated in stele resulting in higher Cd concentration in leaves as compared to tall fescue (Festuca arundinacea) where it is mostly excreted to the cuticle layer in leaves (Dong et al. 2017). In Sedum alferdii, high Cd concentrations were detected in vascular bundles of the young stem according to X-ray fluorescence images analysis and Cd mainly sequestered in vacuoles of the parenchyma cells (Tian et al. 2011). Balestri et al. (2014) observed Cd accumulation in less bioactive tissues of fern Pteris vittata such as fronds, trichomes, and scales under Cd treatment 60 μM. The knowledge of Cd accumulation and distribution in different plant organs and cell components is important to understand the tolerance mechanism of plants (Zhu et al. 2011). Cd has been reported to interfere in numerous metal uptakes including Ca, Mg, P, and K (Das et al. 1997; Song et al. 2017; Wu et al. 2015). In pea plants, Cd exposure to root strongly inhibited the Mn, Ca, P, K, S, B and Zn uptake. The decrease of mineral nutrients such as Fe, Mg, Cu, Mo, and B was also reported in sugar beet (Chang et al. 2003), tomato, and cucumber (Dong et al. 2006), and Atriplex halimus subsp. schweinfurthii (Nedjimi and Daoud 2009). In a study on tomato, an increase in Cu uptake was observed in the roots but a low amount of Cu was translocated to the shoots due to the competition with Cd or Cd toxicity on transport mechanism (Bertoli et al. 2012). A similar increase in Cu, Zn, and Fe was also observed in sunflowers due to the toxicity of Cd (Rivelli et al. 2014). The Cd toxicity could be observed on the morphological and physiological levels. In prolonged experiments, Cd significantly reduced plant growth in several non-Cd accumulator plants under 5–10 mM Cd treatment. On the other hand, plants are also exposed to higher concentrations of Cd (20–200 mM) (Huang et al. 2015; Benáková et al. 2017) but for a short time period ranging from several hours to few days (Rizwan et al. 2017). Under Cd exposure, lower mitotic activities of meristematic cells caused reduction in root length of plants and its dry mass, and increase in parenchyma cell size and cortical tissues are responsible for the increase in root diameter (Chaca et al. 2014; Ismael et al. 2019). Plant exposure to Cd also caused anatomical changes in plants that can change the Cd accumulation process and the vegetative growth of plants (Lux et al. 2015). Casparian strips and suberin lamellae development was observed in the root tips of Salix sp. clones of high Cd translocation as compared to those with low Cd accumulation and translocation (Lux et al. 2004). Similar root developments were also observed in the roots of Tritonia gladiolaris under Cd exposure (Lux et al. 2015). Additionally, Lux et al. (2010) also found Cd-induced hypodermal periderm formation in the roots of Merwilla plumbea under 5 mg kg 1 soil Cd treatment. Cd can cause severe damages in plant leaves such as chlorosis, necrosis, stunting, and desiccation. Cd induced changes are more significant on young leaves as compared to old leaves under Cd exposure (Xue et al. 2014). Cd is responsible for variable photosynthetic rates and chlorophyll contents in soybean cultivars (Shamsi et al. 2014). Ninety days old tomato leaves showed a decrease in chlorophyll and carotenoid contents under Cd treatment 100 mM while no effect was observed on

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photosynthetic pigments under Cd treatment 20 mM as compared to control (Hediji et al. 2010). Similarly, long- and short-term Cd exposure caused photosynthetic inhibition in Thlaspi caerulescens (Küpper et al. 2007), Dianthus caryophyllus (Serrano-Martínez and Casas 2011) pea (Popova et al. 2008), mungbean (Vigna radiate) (Wahid et al. 2008) and sunflower (Helianthus annuus) (Stritsis and Claassen 2013). The presence of Cd in plants also produces reactive oxygen species (ROS) including hydrogen per oxide (H2O2) originate in mitochondria and peroxisome by plasma membrane NADPH oxidase and then diffused to other parts of the plant cells (Zhao et al. 2012; Vestena et al. 2011). For instance, Cd treatment in pea plants stimulated the plasma membrane NADPH to generate ROS in peroxisomes (Dixit et al. 2001). Similarly, Cd-induced NADPH-oxidase-dependent generation of H2O2 caused cell death in bright yellow-2 (BY-2) tobacco cells (Gill and Tuteja 2010). Several studies have shown the direct effect of Cd on the expression and activity of antioxidative enzymes. The activity and expression of superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), monodehydroascorbate reductase (MDHAR), dehydroascorbate reductase (DHAR), peroxidases (POD), and glutathione reductase (GR) vary depending upon the plant species and Cd concentration. A sixfold increase in SOD activity was found in transgenic tobacco cultivar, while 60% reduction in CAT activity was recorded in the wild type under 100 mM and 500 mM Cd treatment (Iannone et al. 2010). In contrast, lower Cd treatments (1–10 mM) have also induced higher SOD activities in tomato plants as compared to control (Fidalgo et al. 2011). In addition, Cd treatment caused increase in CAT activity in chickpea, and black bean roots (Gill and Tuteja 2010) and its activity was reduced in Arabidopsis leaves, Pine and pea roots (Küpper and Andresen 2016). Different Pisum sativum cultivars showed variation in the activity of APX depending on their sensitivity to the Cd treatment (5 mg kg 1) (Metwally et al. 2004). Cd can also induce DNA damage by inhibiting DNA repairing enzymes and inducing ROS (Küpper and Andresen 2016). Such effects were consistently reported by many authors working with diverse heavy metals and plants. Therefore, Cd in plants causes serious effects including a reduction in shoot/root elongation, biomass production, seed germination, and ultimately crop yield. Plant response to Cd metal varies among plants, cultivars, and varieties. So, there is a need for screening low-Cd-accumulating cultivars due to the above-mentioned Cd characteristics.

1.3

Exogenous Regulation of Cd Uptake and Accumulation in Crops

A careful selection of pollution-safe cultivars (PSCs) being low pollutants enough for safe consumption of edible parts, is helpful in reducing Cd uptake in vegetables and its transfer to the human food chain (Yu et al. 2006). The detailed information

1 Cadmium Contamination in Agricultural Soils and Crops

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about Cd-PSCs is described in Chap. 2. However, the utilization of the Cd-PSCs might not be effective when soil Cd exceeded certain thresholds of contamination, and some other techniques should be employed simultaneously to regulate Cd uptake, translocation in various crops, and which included the application of organic and inorganic amendments, such as biochar, compost, manures and silicon, zin, selenium, nitrogen, phosphorus, zeolite, kaolinite, sepiolite, bentonite, and CaCO3. Other measures, e.g., the exogenous application of microbes, alternations of cropping or irrigation patterns, co-plantation, and so on, have also been adopted for the reduction of Cd uptake in crops. Therefore the proper utilization of the Cd-PSCs and the exogenous application of the regulation technologies would thus be a compound strategy to reduce Cd uptake by crops (Muhammad et al. 2017).

1.3.1

Leafy Vegetables

It has been observed that applications of nano-hydroxyapatite (5 g kg 1) + artificial zeolite (5 g kg 1) and nano-hydroxyapatite (5 g kg 1) + calcium superphosphate (4 g kg 1) significantly inhibited the absorption of the Cd, which resulted in the reduction of Cd contents of celery edible parts by 57.43% and 54.88%, respectively (Liu et al. 2011a, b). Pang et al. (2018) reported that although the additions of acetic acid, malic acid, oxalic acid, and citric acid into soils promoted accumulation of Cd in celery root, the supplements of acetic acid, malic acid, and citric acid decreased Cd concentrations in celery leaves by 44.62%, 26.86%, and 15.69%, respectively, and in celery stems by 7.53%, 7%, and 5.13%, respectively. It has been reported that the amendments of hydroxyapatite (HAP) with particle size larger than 80 mm at the rates of 0.5% and 3% in soil reduced Cd concentrations in celery shoot by 19.6% and 76.8%, respectively, as compared with the untreated soil (Yang et al. 2020). A lot of regulating methods were carried out to reduce Cd accumulation in Chinese cabbage. Qin et al. (2017) reported that nano-zeolite was better in increasing the biomass and decreasing Cd accumulation in Chinese cabbage when compared with ordinary zeolite. It had been reported that biochar, sodium metasilicate, and their mixtures with lime could inhibit soil Cd availability and Cd uptake of Chinese cabbage. It had been reported that with the increase of soil pH, MS biochar significantly reduced soil Cd bioavailability by 54% and accumulation in shoots of two cultivars of Chinese cabbage (AJ and ZH) by 35% and 41%, respectively (Khan et al. 2016). For Chinese flowering cabbage, Wu et al. (2018) reported that foliar application of Si alone or combined with Se could evidently decrease Cd concentrations in shoots under two Cd treatments. Li et al. (2007a) compared the effects of calcium (Ca), potassium (Na), zinc (Zn) fertilizers, and rice straw on the inhibition of Cd uptake by Chinese cabbage under the soils contaminated by Cd as high as 1.353 mg kg 1 and 3.135 mg kg 1, and the best results were obtained in the treatment with rice straw.

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A lot of regulating methods were carried out to reduce Cd accumulation in Pakchoi (Table 1.3). Wang et al. (2009), Pan et al. (2017), Fan et al. (2017), Chen et al. (2012) Hu et al. (2018), and Wang et al. (2012) reported that some fertilizers such as NO3 /NH4+ ratio (7:3), nitrate N, combination of high rate of P and mid-low rate of N and K, Ca-Mn phosphate fertilizer + peat fertilizer, Zn alone or together with Se and Mo fertilizers, and foliar application of 2 mmol/L FeSO4 + 1.8 mmol/L citric acid +0.2 mmol/L Na2EDTA + 0.2% urea were effective in reducing Cd accumulation in Pakcho. A lot of organic amendments, such as peanut shell, biochar, chicken manure, humic acid, biochar complex conditioner (biochar, peat, and lime), iron-modified biochar, charcoalat, and bio-nanomaterials, can also effectively reduce Cd accumulation in Pakcho (Wang et al. 2019; Li et al. 2015; Lin et al. 2019; Luo et al. 2018; Chen et al. 2019). For water spinach, Du et al. (2015) tested the effects of some NPK fertilizers on Cd accumulation of the species, and indicated specific combinations of NPK fertilizers that can restrict Cd accumulation in shoot of water spinach. Li et al. (2017) compared the effects of adding lime and biochar into soil on Pb and Cd accumulation in water spinach, and the results showed that the lime and biochar application decreased availability of Pb and Cd in soil and their accumulations in water spinach under both dry farming conditions and water submersion cultivation conditions. Wang (2006) investigated the effects of peat, wood chip, ZnSO4, MgSO4, calcium carbonate (CaCO3), and K2SO4 amendments in different Cd-contaminated soils (containing Cd as high as 0.623 mg kg 1 and 1.102 mg kg 1) on Cd accumulation of two water spinach cultivars (T308, a high-Cd cultivar and QLQ, a low-Cd cultivar). The results showed that all the six amendments inhibited shoot Cd accumulations of the two tested cultivars, under the Cd exposure of 0.623 mg kg 1, especially for QLQ, in which shoot Cd concentration could satiate State Food Security Standards for Cd in edible parts. While under the Cd exposure of 1.102 mg kg 1, only wood chip and ZnSO4 decreased shoots Cd concentration for the two cultivars. For other vegetables, Li et al. (2007b) indicated that rice straw as soil amendment had the best effect on restricting the Cd accumulation of Chinese flowering cabbage. Cd concentration in Chinese kale decreased by 77.6% after 1800 kg hm 2 Si fertilization (Hu et al. 2011). Zhang et al. (2016a, b) reported that peanut husk biochar could decrease uptake of Cd in lettuce by 8.4~38.4%, but some biomass losses were observed. Ding et al. (2008), (Zou et al. 2018) and Zhu et al. (2015) reported that the applications of 5 mmol kg 1 SO4 , Ca-Mn phosphate, and mixture of limestone and sepiolite (2:1) in soils can reduce Cd concentration in spinach, Amaranshus mangostanus, amaranth, and water spinach, respectively.

Amendment with charcoalat 5, 10, 25, and 50 g kg 1 Compound fertilizers, controlled-release nitrogen fertilizers, organic fertilizers Bio-nanomaterials 0%, 1%, 2%, 4%, 8%

Amendments type and dose in soil Different NO3 /NH4+ ratio10:0, 7:3, 5:5, 3:7, 0: 10 Common nitrogen (N) supply forms (ammonium, nitrate, ammonium/nitrate and urea) Biochar, chicken manure, humic acid, and sepiolite. Single applications, split applications (ammonium, urea, nitrate) N(0.10, 0.15, 0.30 g kg 1), P (0.10, 0.30 g kg 1), K (0.15 g kg 1) Five amendments (lime, chicken manure, peat, lime+chicken manure, lime+peat) Ferrous sulfate, citric acid, disodium ethylenediamine tetraacetic acid (Na2EDTA) and urea mixed fertilizers Two fungi strains (Cephalosporium chrysogenum) and Cephalosporium sp.) 2.68 mg kg 5.0 mg kg 5.0, 10.0 mg kg

Pot experiment Sterilized and nonsterilized soil Pot experiment Pot experiment Pot experiment

Pot experiment foliar application

Pot experiment

4.56 mg kg

1

1

1

1

0, 0.5, 1.0 mg kg 1 0.6, 1.02 mg kg 1 0.51 mg kg 1

Pot experiment

Pot experiment

Pot experiment

1

0, 1, 3 and 5 mg kg 1 0.3, 1.5 and 3 mg kg 1 10 mg kg 1

Soil Cd treatment 1.0 mg L

Pot experiment

Culture condition Hydroponic

Table 1.3 Effects of soil amendment applications on Cd control in Pakchoi

90 days

40 days

50 days

42 days

20 days

45 days

48 days

56 days

45 days

70 days

Duration 20 days

1

1

8% Bio-nanomaterials

Organic fertilizers

Charcoalat 50 g kg

2 mmol/L FeSO4 + 1.8 mmol/L citric acid +0.2 mmol/L Na2EDTA + 0.2% urea Cephalosporium sp. 20 mL nonsterilized soil

High rate of P combined with mid-low rate of N and K Lime+chicken manure, lime+peat

Nitrate or urea split applications

Sepioliteat 1.5 mg kg

Nitrate N

Treatment with the best effect NO3 /NH4+ ratio 7:3

(continued)

Luo et al. (2018) Wang et al. (2016a, b) Chen et al. (2019)

Lan et al. (2016)

Reference Wang et al. (2009) Pan et al. (2017) Li et al. (2015) Fan et al. (2017) Chen et al. (2012) Dai et al. (2015) Wang et al. (2018)

1 Cadmium Contamination in Agricultural Soils and Crops 17

1

Calcium magnesium phosphate fertilizer, sepiolite, lime and organic amendments Separately soil-applied selenium (Se), zinc (Zn) and molybdenum (Mo) fertilizer or their combination Melatonin (100 μmol L 1)

Biochar complex conditioner (biochar, peat, lime) 0, 80, 160, 240 g/pot Iron modified biochar 0, 0.1%, 0.3%, 0.5%, 1%

Amendments type and dose in soil Peanut shell biochar 0, 5, 10, 20, 40 g kg

Table 1.3 (continued)

1.26 mg kg 0.8 mg kg

20 μmol L

Field experiments

Hydroponic, foliar application

1

1

1

14.31 mg kg

Soil Cd treatment 0, 2.5, 5.0 mg kg 1 3.57 mg kg 1

Field experiments

Pot experiment

Pot experiment

Culture condition Pot experiment

1

7 days

87 days

45 days

42 days

_

Duration 90 days

Significantly decreased Cd accumulation of roots and shoots

Calcium magnesium phosphate fertilizer + peat combination Application of Zn alone or together with Se and Mo fertilizers

Biochar complex conditioner 240 g/ pot Iron-modified biochar 0.5%

Treatment with the best effect Peanut shell biochar 40 g kg 1 soil

Liu et al. (2018a, b)

Reference Wang et al. (2019) Jin et al. (2016) Lin et al. (2019) Hu et al. (2018) Wang et al. (2012)

18 Y. Huang et al.

1 Cadmium Contamination in Agricultural Soils and Crops

1.3.2

19

Cereal Crops

Liming at a rate of 7.5 t hm 2 decreased rice grain Cd concentration by 70–80% in both seasons and grain yield was not negatively influenced (Chen et al. 2018). Peng et al. (2019) reported that Cd concentration in various parts of rice decreased under Si-treated soil, and rice yield was increased with the treatments, indicating that Si application can not only effectively improve rice growth but can also reduce Cd accumulation in rice. Gu et al. (2019) reported that the biochar application at rates of 1.5%, 3%, and 6% decreased Cd migration from soil to plants and lowed rice grains Cd concentrations by 20.2%, 21.5% and 25.8%, respectively, comparing with that of control. Biochar application in Cd-contaminated soil could also evidently decrease Cd pollution in rice. Within the consideration of the cost, the corresponding amount of Si should be applied in terms of the pollution degree of Cd in order to reach the limit standard of the pollutants in foods. Cong et al. (2019) reported that the Cd uptake by maize grain under cow manure + straw treatment decreased by as high as 80.0%. Chen et al. (2019) found out that biomass of maize treated with lime + sepiolite was the highest among six compounded passivating agents and Cd content of maize shoots was the lowest under both intercropping and monoculturing systems. Shan and Sun (2019) reported that straw and pig manure can decrease Cd concentration of wheat, and positive correlation between the Cd concentration in wheat and exchangeable Cd content in soil was determined. Se application at a rate of 5.0 mg kg 1 decreased Cd mass fraction in grains, glumes, and stems as well as the translocation of Cd from roots to stems in winter wheat (Qin et al. 2019).

1.3.3

Fruit And Root (Tuber) Crops

Ding et al. (2012) reported that soil amendments of corn straw and red mud plus rape straw in combination with zinc fertilization could decrease Cd concentration in edible parts of cowpea by 27% on average. Liu et al. (2011a, b) reported that organo (C8H20O4Si, 2.5 mmol L 1) and inorgano (Na4SiO4, 2.5 mmol L 1) silicon (Si) treatments could reduce fruit Cd concentrations in two varieties (Shinongchaotianjiao and Yanjiao425) of hot pepper (Capsicum annuum L.) by 19.1%, 23.3% and 13.4%, 26.1% respectively, when exposed to the soil containing Cd as high as10 mg kg 1. Li et al. (2019) displayed that spraying a suitable concentration of sodium selenite solution improved growth of pepper and decreased Cd accumulation in its fruits. Tie et al. (2014) reported that selenium (Se) with a content in the soil lower than 1.5 mg kg 1 had an antagonistic action on the effect of Cd and reduced the Cd absorption in radish. Wheat straw, composted pig manure, and exogenous melatonin could also decrease Cd availability and subsequently lower the uptake by leaves and roots of radish (Shan et al. 2016; Huang et al. 2017a, b). Compared with control, Cd

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concentrations in edible parts of radish decreased by 31.4% under 100 μmol L 1 melatonin treatment (Huang et al. 2017a, b). Wang et al. (2016a, b) reported that under liquid organic fertilizer application as basal fertilizer, absorption of Pb and Cd in different organs of potato tubers decreased by 34.7% and 52.1%, respectively, as compared to the control. Liu et al. (2018a, b) studied the effects of five amendments, including nano-hydroxyapatite (n-HA) and its combination with lime, zeolite, bone mill, and fly ash on Cd uptake in potato, and different decrements of Cd in potato tubers were observed with the highest reduction of 39.1% under nano-hydroxyapatite combined amendments. An investigation showed that humic acid, as an optimal conditioner of Cd-contaminated soil, could promote production of sweet potato cultivar “Zhezi No.3” and inhibit the Cd absorption and accumulation in its edible parts. Generally, various fertilizers, elements, and materials as soil amendments could decrease Cd bio-availability and subsequently restrict Cd uptake in various crops. If the methods could be properly combined with the application of Cd-PSCs, which will be discussed in the next chapter as well as other chapters of this book, the Cd pollution risks in edible agricultural products would be greatly decreased.

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Chapter 2

Intraspecific Variations in Cadmium Accumulation Capacity of Crops and Application of Pollution-Safe Cultivar Hui Yu, Zhongyi Yang, Huixia Duan, Mengyuan Huang, Jin Zhao, and Chuntao He

Contents 2.1 Traditional Methods to Deal with Soil Heavy Metal Contamination in View of Food Safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.1 Remediation of Cd Contaminated Soil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.2 Traditional Agronomic Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Different Cd Accumulations Among Cultivars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1 Leafy Vegetables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.2 Cereal Crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.3 Other Crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Proposal of Pollution-Safe Cultivar (PSC) to Control Cd Pollution in Crops . . . . . . . . . . . . 2.3.1 PSCs Screening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2 PSCs Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Vegetables, especially leafy vegetables, are inclined to absorb and accumulate heavy metals than any other kinds of crops in the study of Liu et al. (2005a). To deal with the Cd contamination in agricultural soil around the world, numerous solutions are proposed to achieve the safe productions of crops. These solutions aim at minimizing the Cd bioavailability and further reducing the Cd uptake in plants through soil Cd removal or immobilization. Nevertheless, the uptake and accumulation of Cd varied greatly not only among plant species but also among cultivars, and Cd pollution-safe cultivars (Cd-PSCs) strategy is thus proposed based on the cultivardependent pollutant Cd accumulation.

H. Yu School of Life and Health Sciences, Hunan University of Science and Technology, Xiangtan, Hunan, China Z. Yang · H. Duan · M. Huang · J. Zhao School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China C. He (*) School of Agriculture, Sun Yat-sen University, Shenzhen, Guangdong, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2022 Z. Yang et al. (eds.), Theories and Methods for Minimizing Cadmium Pollution in Crops, https://doi.org/10.1007/978-981-16-7751-9_2

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H. Yu et al.

Traditional Methods to Deal with Soil Heavy Metal Contamination in View of Food Safety Remediation of Cd Contaminated Soil

Cd-contaminated soil remediation is the summary of divergent strategies to make safe use of agricultural soil by Cd removal or fixation, mainly including physical-, chemical- and biological-remediation methods. The soil replacement, electrokinetic remediation technique and soil leaching are ubiquitous physical and chemical soil remediation solutions while the phytoremediation is an assisted solution for the formers. 1. Soil replacement Soil replacement, also named as excavation and dredging, has been applied in the last century with a long application history. Soil replacement remediation usually involves contaminated soil deemed to be unrecoverable, and polluted soil is transported to a landfill set aside while clean soil is used to fill in the original area. Lanphear et al. (2003) reported a case in which the soil replacement remediation was to remove the contaminated soil and replace it by clean soil with the thickness at least 40–60 cm. Generally, the contaminated soil is excavated in the original site and transported to the disposal site for the subsequent purification. Further, the production potential of the agricultural soil remediated by soil replacement was explored. Seven vegetable species, namely root vegetables such as radish, carrot (Daucus carota), potato, leafy vegetables such as lettuce and leek, and fruit vegetables including french bean (Phaseolus vulgaris) and tomato (Solanum tuberosum), were cultivated in the originally contaminated soils and the clean replaced soils from 2003 to 2005 (Douay et al. 2008). Ubiquitous reductions of Cd about 40–60% were observed in the vegetables cultivated in the remediated soils, although Cd concentrations of about 17% of cultivated vegetables were still over the European legislative limits (french bean, tomato FI > FIII, which were consistent with the trends of Cd proportions in the three subcellular fractions. Cd-FII concentrations of leaves in T308 were 2.05 mg kg 1 and 2.61 mg kg 1 under low Cd and high Cd treatments, respectively, which were much higher than those in QLQ (0.70 mg kg 1 and 1.28 mg kg 1). Meantime, the proportions of Cd-FII in leaves of T308 were 1.32- and 1.05-fold higher than those of QLQ under low Cd and high Cd treatments, respectively. The Cd-FII concentrations and proportions of stems in T308 were all higher than those in QLQ under different Cd treatments. Whether in leaves or stems, most of Cd was combined with the cytoplasm under Cd stress, especially in the high-Cd cultivar. The higher concentration and proportion of Cd-FII in T308 than QLQ under Cd stress showed that the compartment capacity of Cd in cytoplasm (mainly in vacuole) is one of the main factors determining the ability of Cd accumulation. The synthesis of a series of compounds, such as organic acids, amino acids and thiol compounds in plants can be induced by Cd (Hall 2002; Pal and Rai 2010), and is considered to be one of the important detoxification mechanisms of plants. These compounds have high affinity with Cd and thus can reduce activity and toxicity of Cd in cells. Phytochelatins (PCs), as thiol compounds, play important roles in complexing free Cd ions by forming Cd-PC complexes (Kotrba et al. 1999; Masahiro 2005). The Cd-PC complexes can be transported into vacuole and is included in the Cd-FII. The much higher shoot Cd-FII in both concentration and proportion in T308 than QLQ under Cd treatments could be considered as the result of the exuberant Cd-PC synthesis in T308 responding to Cd stress, which is also consistent with the results reported by Li and Zhu (2004). With the increment of Cd exposed concentration, Cd-FI concentration in leaves of T308 increased greatly and was significantly higher than that of QLQ under high Cd treatment ( p < 0.05). However, the Cd-FI proportion was much higher in QLQ than in T308 under low Cd treatment, while the cultivar differences became much small under high Cd treatment, indicating that the cell wall of QLQ effectively fixed Cd only under low Cd stress, and the ability might be smaller than that of T308 which resulted in the similar proportion of Cd-FI between the two cultivars under high Cd treatment. In the stem, the proportions of Cd-FI in QLQ (low Cd treatment, 49.6% and high Cd treatment, 38.7%) were much higher than those in T308, although those in concentration had no significant difference between the two cultivars, implying a higher Cd capacity in stem cell walls of QLQ. Under Cd stress, the proportion of stem Cd-FI in QLQ was similar to or even higher than in T308 (Fig. 6.2). These results suggested that the cell wall of QLQ stem played a more important role in protecting protoplasts from Cd toxicity in the stem when compared with T308. Overall, the concentrations and proportions of Cd-FIII were basically at a low level wherever Cd is exposed or not in both QLQ and T308. Although the concentrations of Cd-FIII in leaves displayed significant differences between QLQ and T308 under CK and Cd treatments ( p < 0.05), their levels were much lower than those in stems where the Cd-III had no significant differences between cultivars and the proportions under low Cd and high Cd treatments were similar in both cultivars.

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Fig. 6.1 Cd concentrations in the three subcellular fractions of water spinach leaves and stems under three Cd exposures. Note: ns, * and ** indicate that the differences between QLQ and T308 are not significant, significant at the p < 0.05 and p < 0.01 level, respectively. FI, cell walls and cell wall debris fractions; FII, soluble fraction (including the vacuole); FIII, organelle fraction (excluding the vacuole)

Cd concentration (mg kg–1, FW)

QLQ Cd concentration (mg kg–1, FW) Cd concentration (mg kg–1, FW)

Leaf FI Cd concentration (mg kg–1, FW) Cd concentration (mg kg–1, FW)

2.0

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Fig. 6.2 Percentages of Cd concentrations in three subcellular fractions of leaves and stems under three Cd treatments

It is considered that there are some mechanisms to prevent Cd entering into organelles, and thus a stable level of Cd-III can be maintained. A further pot experiment was conducted by Xin et al. (2013), who investigated the Cd proportions in the different tissues of QLQ and T308 in detail. The tendency of the Cd proportions in the different fractions of QLQ and T308 leaves (Fig. 6.3) were different from those under water cultivation. Most of Cd was observed in FI in both young and old leaves in pot experiment. These observations suggested that immobilization of Cd in cell walls is the preliminary strategy to maintain normal physiological activities of leaves. Similar dominant Cd distribution in cell walls was exhibited in the leaves of lettuce, i.e. 64% Cd distributed in the cell wall fraction (Inmaculada et al. 2002). Unlike the decline of Cd-FI percentages in old leaves of QLQ under T1 and T2 treatments, the percentages of Cd-FI in T308 remained fairly constant (51–57%) among all treatments. These results proved that T308 could accumulate more Cd in the cell wall of old leaves than QLQ, particularly under high Cd exposure. It is noteworthy that under T2 treatment, percentages of Cd-FII in young leaves of T308 were all higher than those of QLQ (Fig. 6.3), and the Cd-FII in young leaves of QLQ under CK and T2 were not detected. Higher Cd-FII percentages were observed in QLQ than T308 in old leaves, which implied that QLQ might have stronger ability to transport Cd from young leaves to the old leaves than T308 did. Meanwhile, percentages of Cd-FIII in young leaves of T308 were all lower than those of QLQ under different treatments, indicating that T308 had a trend of avoiding the accumulation of high Cd in organelles for protecting them. Therefore, the Cd detoxification mechanisms in leaves were obviously different between T308 and QLQ. In stems, percentages of Cd in the three fractions showed little difference between the two cultivars (Fig. 6.4). The percentages of Cd-FI in the two cultivars were elevated and the percentages of Cd-FII and Cd-FIII decreased with the increase in

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Fig. 6.3 Percentages of Cd concentrations in three subcellular fractions of young and old leaves under different Cd treatments

Fig. 6.4 Percentages of Cd concentrations in three subcellular fractions of stems under different Cd treatments

soil Cd stress, suggesting the importance of Cd sequestrating in cell walls under high Cd stress (Liu et al. 2018). The proportions of Cd-FII were higher in T308 than QLQ under Cd stresses, and Cd-FIII performed oppositely, indicating a similar Cd detoxification way in the stem of T308 as that in leaves.

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6.1.2

Cd Subcellular Distribution in QLQ and T308 Roots

Root FI

QLQ

40

T308 

30 20 ns

10 0

ns CK

1 5 Cd treatments (mg/L)

50

Root FII QLQ

T308

40

ns

30 20



10 0

ns CK

1 Cd treatments (mg/L)

5

Cd concentration (mg kg–1, FW)

50

Cd concentration (mg kg–1, FW)

Cd concentration (mg kg–1, FW)

Cd mobility could be represented by the subcellular distribution of Cd in the cells of plants, which has been verified in different crops (Wang et al. 2009; Yang et al. 2019; Zhang et al. 2015). In the water cultivation experiment for water spinach, the concentration and proportion of Cd-FI in roots of QLQ were much higher than those in T308 under high Cd treatment (Fig. 6.5), indicating that Cd retention ability in roots of QLQ was higher than that in T308 under high Cd stress. Similar results were also observed in Chinese kale (Brassica alboglabra L. H. Bailey) (Guo et al. 2018) and leafy lettuce (Lactuca sativa Linn. var. ramosa Hort.) (data unpublished). The results indicated that the cell wall of the low-Cd cultivars generally exhibits stronger ability to block Cd in roots and further decrease root-to-shoot translocation of Cd, which may be one of the main mechanisms for lower Cd accumulation in shoots of the low-Cd cultivars. For FII in roots, the significant difference in Cd concentrations between the two cultivars was observed only under low Cd treatment, where Cd concentration in QLQ was higher than in T308 (Fig. 6.5). Under high Cd stress, however, the Cd-FII proportions in roots of T308 were much higher than in QLQ (Fig. 6.6), suggesting that the Cd in roots of T308 should have stronger immigration ability than that of QLQ. Wan et al. (2003) indicated that the crops with higher Cd accumulation in the soluble part of root cells tended to exhibit higher Cd concentration in shoots, which was also demonstrated from the subcellular distribution traits of Cd-FII in roots of QLQ and T308 of water spinach. The higher Cd concentration in shoots accompanying the higher proportion of Cd-FII in root cells observed in the high-Cd cultivar indicated that the higher Cd level in cytoplasm of roots is one of the main factors determining the ability of shoot Cd accumulation in water spinach. The Cd-induced change of Cd-FIII proportion in roots of T308 was irregular and stayed at a relatively low level (only 8.3–12.8%) under different Cd treatments. This may be beneficial to protect root organelles from Cd toxicity. The elevation of concentration as well as proportion in the Cd-FIII of QLQ roots under high Cd treatment might be one of the reasons that the QLQ activated more molecular responses in the pathways involving Cd detoxification (Huang et al. 2016).

10

Root FIII QLQ

8

T308



6 4 ns 2 0

ns CK

1 5 Cd treatments (mg/L)

Fig. 6.5 Cd concentrations in the three subcellular fractions of root under three Cd levels. Note: ns, * and ** indicate that the differences between QLQ and T308 are not significant, significant at the p < 0.05 and p < 0.01 level, respectively

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Fig. 6.6 Percentages of Cd concentrations in three subcellular fractions of roots under three Cd treatments

Fig. 6.7 Percentages of Cd concentrations in three subcellular fractions of roots under three Cd treatments

Under soil cultivation, QLQ retained higher percentages of Cd-FI in lateral and main roots than those in T308, especially in the main roots (Fig. 6.7). For Cd-FII in roots, higher Cd-FII percentages both in lateral and main roots of T308 than those of QLQ were observed under Cd treatment. These results implied that the Cd retention ability of cell walls was higher in the low-Cd cultivar, while Cd mobility in the root cells was higher in the high-Cd cultivar.

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The proportions of Cd-FIII in roots were different from those in leaves and stems under Cd stress, i.e. the higher proportion in organelles in roots of T308 than that of QLQ. This might be attributed to that the higher Cd accumulation in roots of QLQ activated some mechanisms to avoid the damages by Cd toxicity to the organelles. However, there is no similar phenomenon in Chinese kale (Guo et al. 2018) and leafy lettuce (data unpublished) which also accumulated higher Cd in roots of low-Cd cultivars than high-Cd cultivars did, and further investigation is needed to explain the phenomenon. The different Cd subcellular distribution patterns in water spinach between Wang et al. (2009) and Xin et al. (2013) might be probably ascribed to the following conditions. (a) The exposure durations of 30 days in the study of Xin had provided enough responsive time to the cell wall thicken, which was a ubiquitous strategy of numerous plants to alleviate heavy metal stress (Krzesłowska et al. 2009, 2016; Song et al. 2013). Hence, the enhanced cell wall could achieve the higher Cd restoration in the cell wall rather than other subcellular components. What’s more, short exposure duration might be insufficient to fulfill the cell wall thicken, which has restricted the restoration capacity of cell wall in the study of Wang et al. (2009). (b) Higher effective Cd concentrations adopted in the study of Wang have brought the acute saturation of cation binding sites in cell wall during the short exposure duration, which would further facilitate the Cd influx and accumulation via the symplastic pathway.

6.2

Relationship Between Cd Chemical Forms and the Cultivar-Dependent Cd Accumulation of Water Spinach

The activity, toxicity, migration ability and difficulty of separation from substrates of metals are closely related to their chemical forms (Xu et al. 1991). Different chemical forms of compounds can be extracted by different extractions (Yang and He 1995). For example, 80% ethanol is mainly used to extract heavy metals bound to alcohol-soluble proteins and amino acid. The water-soluble organic acid salts and free heavy metal ions can be extracted by deionized water (ddH2O). Meanwhile, the certain concentrations of NaCl can extract heavy metals combined with protein or pectin extracts. Whereas, metal-phosphate that are difficult to dissolve in water and metal-oxalate complexes are extracted by HAc and HCl, respectively. Sequential chemical extraction method has been conducted for the Cd associated with different chemical forms. The Cd extraction solutions in the specific order for different chemical forms were listed in Table 6.1. The chemical forms of Cd are related to Cd mobility in plants, which is associated with Cd translocation and toxicity in plants (Wei et al. 2007; Fu et al. 2011). The ethanol- and water-soluble Cd display the strongest mobility activity, followed by Cd extracted by NaCl, and the mobility of Cd-phosphate and Cd-oxalate complexes

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Table 6.1 The solutions for extracting different Cd chemical forms Extractions ① 80% ethanol (FE) ② Distilled water (FW) ③ 1 mol/L NaCl (FNaCl) ④ 2% HAc (FHAc) ⑤ 0.6 mol/L HCl (FHCl) ⑥ Residue (FR)

Chemical forms Mainly including nitrate-, chloride-, and aminophenol Cd, etc. Water-soluble organic acids and Cd(H2PO4)2, etc. Pectate- and protein-integrated Cd, etc. Insoluble Cd-phosphate complexes, including diphosphate, orthophosphate, etc. Cd-oxalate complexes, etc. Insoluble heavy metals

is low (Wang et al. 2008; Zhang et al. 2009). The difference of Cd accumulation abilities in shoots might be involved with the proportions of high-mobility chemical forms of Cd, including water-soluble organic acid, protein and pectin binding forms in roots, which participated in Cd translocation from roots to shoots (Zhao et al. 2015; Zhou et al. 2017). Whereas, low-mobility chemical forms of Cd make contributions to Cd retention in plant root cells, rather than translocation from roots to shoots. Therefore, the various chemical forms of Cd in plants reflect the different abilities of Cd mobility, which lead to the difference of Cd accumulation abilities (Xue et al. 2014).

6.2.1

Difference of Cd Chemical Forms Between in QLQ and T308 Shoots

The chemical forms of Cd have been conducted in different plants to reveal Cd tolerance mechanisms in plants (Fu et al. 2011; Pan et al. 2019; Wang et al. 2015; Wu et al. 2005). There were obvious differences in chemical forms of Cd between the shoot of QLQ and T308 (Tables 6.2 and 6.3) under the same Cd treatment, and the different Cd treatments also exerted obvious effects on the chemical forms of Cd between QLQ and T308 shoots. Whatever the Cd treatment levels, the greatest amounts and proportions of Cd in leaves were obtained in the extraction of 80% ethanol for both T308 and QLQ, with higher levels in the former than the latter. Under LCd treatment, the difference of Cd concentration extracted by 80% ethanol between the cultivars was 2.53-fold, while it decreased to 1.57-fold under HCd treatment. However, the differences in proportion under HCd treatment were greater than that under LCd treatment. Similar trends were observed in the Cd extracted by the 80% ethanol in stems, but the cultivar difference degree was lowered obviously, the Cd proportions in stems were lower than those in leaves and the difference between the two cultivars was opposite to that in leaves under HCd treatment. Furthermore, the concentration as well as proportion of water-extracted Cd in leaves of T308 were higher than those in QLQ and the concentration differences

Proportion

Concentration

Proportion

Item Concentration

Cultivar QLQ T308 QLQ T308 QLQ T308 QLQ T308 1

FW 0.11  0.01b 0.38  0.02a 8.21 11.05 0.22  0.03b 0.52  0.10a 8.60 14.08

FNaCl 0.05  0.01a 0.01  0.00b 3.80 0.29 0.19  0.04a 0.05  0.01b 7.54 1.27

FHAc 0.05  0.02b 0.09  0.02a 3.56 2.51 0.15  0.03a 0.12  0.02a 5.70 3.37

FHCl 0.04  0.00b 0.16  0.03a 3.29 4.6 0.23  0.04a 0.23  0.05a 8.81 6.24

FR ND ND 0 0 ND ND 0 0

and 5.0 mg L 1; Different letters within the same column indicate the significant differences at

FE 1.09  0.10b 2.76  0.08a 81.13 81.55 1.80  0.41b 2.83  0.35a 69.34 75.04

Notes: LCd and HCd represent Cd treatments of 1.0 mg L p < 0.05 level; ND means not detected

HCd

Treatment LCd

Table 6.2 Cd concentration (mg kg 1, FM) and proportion (%) of different chemical forms in leaves of water spinach under different Cd treatments

116 H. Fu et al.

Proportion

Concentration

Proportion

Concentration

Cultivar QLQ T308 QLQ T308 QLQ T308 QLQ T308 1

FW 0.13  0.01b 0.29  0.06a 5.74 10.81 0.19  0.02b 0.33  0.06a 5.66 7.12

FNaCl 0.72  0.09a 0.92  0.14a 31.86 29.77 0.94  0.13b 1.47  0.16a 27.95 36.19

FHAc 0.31  0.00a 0.24  0.05b 16.64 7.59 0.38  0.08a 0.29  0.05a 9.39 6.70

FHCl 0.05  0.01a 0.04  0.01a 2.40 1.37 0.13  0.02a 0.12  0.02a 3.75 3.04

FR ND ND 0 0 ND ND 0 0

and 5.0 mg L 1; Different letters within the same column indicate the significant differences at

FE 0.98  0.06b 1.56  0.20a 43.35 50.46 1.78  0.25a 1.90  0.32a 53.24 46.66

Notes: LCd and HCd represent Cd treatments of 1.0 mg L p < 0.05 level; ND means not detected

HCd

Cd level LCd

Table 6.3 Cd concentration (mg kg 1, FM) and proportion (%) of different chemical forms in stems of water spinach under different Cd treatments

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reached to 3.45- and 2.36-folds under LCd and HCd treatments, respectively. Although the levels in both concentration and proportion of water-extracted Cd were much lower than Cd extracted by 80% ethanol, their cultivar difference displayed similar patterns that the levels were mostly higher in T308 than QLQ in both leaves and stems, indicating that the mobility of Cd is much higher in the highCd cultivar than in the low-Cd cultivar (Mwamba et al. 2016; Zhao et al. 2015). Under both LCd and HCd treatments, the Cd extracted by 80% ethanol and by water were dominant chemical forms in leaves (nearby or exceeding 90% of the total Cd) and stems (exceeding 50% of the total Cd) of the two water spinach cultivars, which was different from the results in leaves of Brassica napu, shoots of barley and pakchoi (Brassica chinensis L.) (Mwamba et al. 2016; Wu et al. 2005; Xue et al. 2014) as well as in shoots of leafy lettuce (data unpublished), whose main chemical form is 1 M NaCl extracted Cd. It is suggested that there were rather different biochemical behaviors of the Cd that enters the cells of different plants, which would lead to the differences in Cd immigration and detoxification. As for the Cd extracted by 1 M NaCl, the concentration and proportion in leaves of the two cultivars under Cd stress were relatively low, and those in QLQ leaves were much higher than in T308 leaves. In stems, however, the concentrations and concentrations of the 1 M NaCl extracted Cd were much higher than in leaves, only lower than the Cd extracted by 80% ethanol, and the difference in concentration displayed oppositely, with a higher level in T308 than in QLQ under both treatments. The 1 M NaCl extracted Cd is considered to chelate Cd with pectate, proteins or peptides, and compartment them in vacuole (Marentes and Rauser 2010, Shang et al. 2014, Sun et al. 2004, Yoshimura 2011). It is an important way of Cd detoxification in many crops such as rice, barley and various vegetables as mentioned above. It is supposed that the 1 M NaCl extracted Cd in stem would play more important role in Cd detoxification rather than in leaves, especially in T308. The manifestations of the Cd extracted by 2% HAc and 0.6 M HCl were similar to those of extracted by 1 M NaCl, presenting much higher levels of both concentration and proportion in stems than in leaves and always higher levels in QLQ stems than in T308 stems. The results implied that the two chemical forms played little roles in Cd detoxification in leaves, but non-ignorable roles in stems of water spinach. Cd extracted by 2% HAc extracted and 0.6 M HCl have be considered as the Cd retained by phosphates and oxalates and also as an indicator of Cd immigration and detoxification abilities in some plants such as pokeweed (Phytolacca Americana L.) (Fu et al. 2011) and Kandelia obovata (Weng et al. 2012). In shoots of water spinach, however, the mechanism of Cd detoxification can be not fully elucidated only by determining Cd chemical forms. It might be also associated with on the Cd-induced changes in root Cd uptake, root-to-shoot translocation, oxidation resistance, and so on (Ahsan et al. 2012; Clemens 2006; DalCorso et al. 2010; RodríguezSerrano et al. 2009). As for the stems, the mechanisms relating to 1 M NaCl, 2% HAc and 0.6 M HCl extracted Cd might play certain roles in Cd detoxification because the total proportion of the chemical forms in the stem reaches 38.73–50.9%. Considering the features of the Cd chemical forms in both leaves and stems, shoots

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of low-Cd cultivar seemed to be more tolerant to Cd toxicity than the high-Cd cultivar.

6.2.2

Difference of Cd Chemical Forms Between QLQ and T308 Roots of Water Spinach

Chemical forms of Cd in roots decide not only the Cd detoxification ability but also the Cd root-to-shoot translocation ability (Zhou et al. 2017). Similar with the results in shoots, concentrations and proportions of the Cd with higher activity, including 80% ethanol extracted, water extracted and 1 M NaCl extracted Cd were the dominant chemical forms in roots of both water spinach cultivars (Table 6.4), with the proportions as high as 90% in most cases. However, large parts of these Cd seemed to be combined with pectate, proteins or peptides (i.e. the Cd extracted by 1 M NaCl) and the proportions were mostly higher than 60% in the roots of both cultivars, and were much higher than those in their shoots. It has been reported that the enhanced synthesis of small molecular compounds, such as PCs, not only promotes Cd tolerance of plants, but also contributes to root-to-shoot translocation of Cd (Gong et al. 2003). On the one hand, the Cd-PC complex would be transported into vacuole under the participation of HAMs, which could decrease cell toxicity of Cd (Khoudi et al. 2012; Salt and Wagner 1993). On the other hand, the plants with higher concentration of Cd coordination with PCs (small molecular proteins) in roots tend to accumulate more Cd in shoots (Guo and Marschner 1995), because they can be transported to shoots more easily than Cd combined with macromolecular substances (Wu et al. 2005). In the two tested cultivars of water spinach, it could be said that the way to enhance Cd combination with small molecular compounds in roots is an important response induced by Cd stress. Between the low-Cd and high-Cd cultivars of water spinach, however, the differences in the response were not much regular under different Cd stresses, indicating that the roles of the biochemical way on Cd detoxification or translocation in water spinach might be mainly altered by growth conditions instead of cultivars. The concentrations and proportions of 2% HAc and 0.6 M HCl extracted Cd in QLQ roots were mostly higher than those in T308 under both LCd and HCd treatments, which were consistent with the results in their stems. It is suggested that the mechanism to combine more Cd with phosphates and oxalates, which were primarily blocked in cell walls or sequestered in the vacuole (Zhang et al. 2015), would be one of the ways to reduce Cd immigration ability in roots of QLQ rather than T308. These results are consistent with the features of the Cd subcellular distribution mentioned earlier, in which the higher concentrations and proportions of Cd-FI and Cd-FII in QLQ than in T308 were observed. It is thus suggested that the Cd chemical forms profiles in the low-Cd and high-Cd cultivars can partly explain the biochemical mechanisms of the cultivar-dependent Cd accumulation in water spinach.

Proportion

Concentration

Proportion

Concentration

Cultivar QLQ T308 QLQ T308 QLQ T308 QLQ T308 1

FW 1.64  0.32a 1.94  0.18a 4.90 4.97 3.52  0.16a 3.06  0.46a 4.46 6.04

FNaCl 11.93  0.79b 26.32  5.77a 35.75 67.46 48.50  5.59a 31.78  5.22b 61.44 62.64

FHAc 2.64  0.32a 2.68  0.45a 7.92 6.86 6.59  0.08a 3.70  0.83b 8.35 7.30

FHCl 0.42  0.06a 0.35  0.03a 1.27 0.90 1.92  0.29a 0.70  0.15b 2.43 1.38

FR ND ND 0 0 ND ND 0 0

and 5.0 mg L 1; Different letters within the same column indicate the significant differences at

FE 16.74  0.34a 7.73  0.60b 50.16 19.82 18.41  2.31a 11.49  1.89b 23.32 22.64

Notes: LCd and HCd represent Cd treatments of 1.0 mg L p < 0.05 level; ND means not detected

HCd

Cd level LCd

Table 6.4 Cd Concentration (mg kg 1, FM) of different chemical forms in roots of water spinach exposed to different levels of Cd

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Chapter 7

Breeding of New Cultivar of Water Spinach with Low Shoot Cd and Pb Accumulations Junliang Xin, Yangxiu Mu, Baifei Huang, Chuang Shen, Huiling Fu, Zhongyi Yang, and Yingying Huang

Contents 7.1 Genetic Models for Cd-PSC Breeding of Water Spinach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.1 Methods of Genetic Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.2 Genetic Model of Shoot Biomass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.3 Genetic Model of Shoot Cd Concentration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Breeding of a Low Cd/Pb Accumulation and High Yield Water Spinach Cultivar . . . . . 7.3 Comparisons of Nutrients in Shoots Between the New Cd/Pb-PSC and Its Parents of Water Spinach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.1 Organic Substances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.2 Metal Elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

126 126 128 132 136 139 139 140 145

In the earlier chapters, the Cd-PSC strategy has been described, and the feasibility to minimize Cd pollution in crops is also convincing. Generally, the yield of Cd-PSCs (Cd-pollution safe cultivars) is also low, such as QLQ. If we only select Cd-PSCs from the currently using crop cultivars, the utilization of the strategy would be greatly limited. Therefore, creations of new Cd-PSCs integrated with other excellent traits using specific breeding methods are proposed (Grant et al. 2008; Zhou 2016; Huang et al. 2017).

J. Xin · B. Huang · C. Shen · H. Fu · Y. Huang (*) School of Chemical and Environmental Engineering, Hunan Institute of Technology, Hengyang, Hunan, China e-mail: [email protected] Y. Mu Ningxia Center of Agricultural Organic Synthesis, Agricultural Resource and Environment Institute of Ningxia Academy of Agriculture and Forestry Science, Yinchuan, Ningxia, China Z. Yang School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China © Springer Nature Singapore Pte Ltd. 2022 Z. Yang et al. (eds.), Theories and Methods for Minimizing Cadmium Pollution in Crops, https://doi.org/10.1007/978-981-16-7751-9_7

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Genetic Models for Cd-PSC Breeding of Water Spinach

Although shoot Cd concentration in the low-Cd cultivar (QLQ) of water spinach is much lower than the high-Cd cultivar (T308), its biomass is lower, which is unfavorable to scale up production. A breeding procedure was conducted to create a new cultivar with low shoot Cd concentration and high yield. Other agronomic features involving food quality of the new cultivar were also investigated.

7.1.1

Methods of Genetic Analysis

It is considered that shoot biomass and Cd concentration of water spinach belong to quantitative traits, which are controlled by a few major genes and several polygenes. In order to analyze mixed-inheritance models, joint segregation analysis (JSA) has been successfully applied to the genetic study of major gene plus polygene mixed quantitative variation in plants (Zhang and Gai 2000). Furthermore, the parameter in the JSA model is estimated using the expectation and iterated maximization (EIM) (Zhang et al. 2003). The selection of the best-fitting genetic model is mainly based on the Akaike’s information criterion (AIC) (Hao et al. 2008). Plant cultivation, data collection and statistical analysis: Previously, we obtained a high-Cd and high-yield cultivar of water spinach (male, P1), a low-Cd and low-yield cultivar (female, P2), and their hybrid (F1) (Xin et al. 2010), and then we produced the first backcross generations, B1 (the cross F1
P1) and B2 (the cross F1
P2), and F2 generation (self-crossing of F1) through traditional breeding methods. In order to estimate the shoot biomass and Cd concentration heritabilities and genetic effects, all the generations, P1, P2, F1, F2, B1, and B2, were grown in pots (one plant per pot) filled with soil containing 0.597 mg Cd kg1 in a greenhouse with natural daylight. Fifty plants in each of P1, P2, and F1 generation and 100 plants in each of F2, B1, and B2 generation were used to construct genetic models. All the shoots were harvested in the 30th day after germination, and biomass and Cd concentration were determined. Joint segregation analysis: For a mixed inheritance model and the JSA, trait variation in each segregating generation is assumed to the result of major gene (s) modified by polygenes and the environment. Phenotypic value ( p) is the sum of population mean (m), major gene effect (g), polygene effect (c), and environment effect (e), where g is different for different major gene, and c and e are normally distributed values. Therefore, the phenotypic variation (σ 2p) can be considered as consisting of major genic variation (σ 2mg), polygenic variation (σ 2pg) and environmental variation (σ 2e). Thus, the heritability of major gene(s) (h2mg) and polygene (h2pg) can be defined as h2mg ¼ σ 2mg/σ 2p and h2pg ¼ σ 2pg/σ 2p, respectively. Genetic models: There are five selected types (A-E) of genetic models to explain the genetic control for shoot biomass and Cd concentration in water spinach (Table 7.1). Because of the gene action, including additive, dominance, additive-dominance, or additive-dominance-epistasis, the model types are

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Table 7.1 Genetic models and their parameters in the joint segregation analysis of the six generations P1, F1, P2, B1, B2, and F2 (Gai et al. 2003) Model code A-1 A-2 A-3 A-4

B-2

Model implication One additive-dominance major gene One additive major gene One complete dominance major gene One negative complete dominance major gene Two additive-dominance-epistasis major genes Two additive-dominance major genes

B-3

Two additive major genes

B-4

Two equal additive major genes

B-5 B-6

Two complete dominance major genes Two equal dominance major genes

C C-1 D

Additive-dominance-epistasis polygene Additive-dominance polygene Mixed one additive-dominance major gene and additive-dominance-epistasis polygene Mixed one additive-dominance major gene and additive-dominance polygene Mixed one additive major gene and additivedominance polygene Mixed one complete dominance major gene and additive-dominance polygene Mixed one negative complete dominance major gene and additive-dominance polygene Mixed one negative complete dominance major gene and additive-dominance polygene Mixed two additive-dominance-epistasis major genes and additive-dominance-epistasis polygene Mixed two additive-dominance-epistasis major genes and additive-dominance polygene Mixed two additive-dominance major genes and additive-dominance polygene Mixed two additive major genes and additive-dominance polygene Mixed two equal additive major genes and additive-dominance polygene

B-1

D-1 D-2 D-3 D-4

D-4

E

E-1

E-2 E-3 E-4

First-order parameter m, d, h m, d, (h ¼ 0) m, d (¼ h) m, d (¼ h)

Second-order parameter σ2 σ2 σ2 σ2 σ2

m, da, db, ha, hb, i, jab, jba, l m, da, db, ha, hb, (i ¼ jab ¼ jba ¼ l ¼ 0) m, da, db, (ha ¼ hb ¼ 0) m, d (¼ da ¼ db, ha ¼ hb ¼ 0) m, da ¼ ha, db ¼ hb m, d (¼ da ¼ db ¼ ha ¼ hb) m1~m6 m, [d], [h] m1~m6, d, h

σ42,σ52,σ62,σ2 σ42,σ52,σ62,σ2 σ42,σ52,σ62,σ2

m, d, h, [d], [h]

σ42,σ52,σ62,σ2

m, d, (h ¼ 0), [d], [h]

σ42,σ52,σ62,σ2

m, d ¼ h, [d], [h]

σ42,σ52,σ62,σ2

m, d ¼ h, [d], [h]

σ42,σ52,σ62,σ2

m, d ¼ h, [d], [h]

σ42,σ52,σ62,σ2

m1~m6, da, db, ha, hb, i, jab, jba, l

σ42,σ52,σ62,σ2

m, da, db, ha, hb, i, jab, jba, l, [d], [h]

σ42,σ52,σ62,σ2

m, da, db, ha, hb, [d], [h] m, da, db, ha ¼ hb, ¼ 0, [d], [h] m, d (¼ da ¼ db, ha ¼ hb ¼ 0), [d], [h]

σ42,σ52,σ62,σ2

σ2 σ2 σ2 σ2 σ2

σ42,σ52,σ62,σ2 σ42,σ52,σ62,σ2 (continued)

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Table 7.1 (continued) Model code E-5

Model implication Mixed two complete dominance major genes and additive-dominance polygene

First-order parameter m, da ¼ ha, db ¼ hb, [d], [h]

Second-order parameter σ42,σ52,σ62,σ2

Notes: m population mean; d and h additive and dominance effects of major gene for models A and D; da, ha additive and dominance effects of the first major gene for models B and E; db, hb additive and dominance effects of the second major gene for models B and E; i, jab, jba, l additive
additive, additive
dominance, dominance
additive, dominance
dominance epistatic effects between the two major genes; m1~m6 population mean of P1, F1, P2, B1, B2, and F2; [d], [h] additive and dominance effects of the polygenes; σ2 population distribution variance of P1, F1 and P2; σ42,σ52,σ62 population distribution variance of B1, B2 and F2, respectively Table 7.2 Descriptive statistics of shoot biomass (g, FW) of water spinach in six generations Generation P1 P2 F1 F2 B1 B2

Sample size 50 50 50 100 100 100

Minimum 7.62 3.86 7.32 3.74 5.50 3.72

Maximum 19.12 8.93 14.57 15.01 16.14 11.75

Mean 12.74 5.89 9.85 7.34 9.79 7.56

Standard deviation 2.63 1.15 1.64 2.09 2.06 1.99

CV (%) 20.64 19.52 16.65 28.47 21.04 26.32

subdivided into 24 scenarios and estimation of component and genetic parameters were calculated according to the methods reported by Gai et al. (2003). Model selection: According to the AIC (Akaike 1977), the model with the minimum AIC value is considered as the optimal model. Here, AIC ¼ 2 L (Y|θ) + 2 k, where L (Y|θ) is the logarithm likelihood function, θ is a parameter in the logarithmic likelihood function, k is the number of independent parameters in a genetic model. Therefore, the minimum AIC value is first used to select the optimal model class. Then the goodness-of-fit test is used to examine whether a genetic model in the same genetic class is significantly different from others. If there is no significant difference, the model with the lowest AIC value will be considered as the best-fitting model. The methods of the goodness-of-fit test include uniformity test, Smirnov test, and Kolmogorov test (Gai et al. 2003).

7.1.2

Genetic Model of Shoot Biomass

Shoot biomass of P1 was significantly higher than that of F1, and that of P2 was the lowest (Table 7.2). The coefficient of variations (CV) of shoot biomass in the six generations were ranked as F2 > B2 > B1 > P1 > P2 > F1, which indicated that the variations among individuals in the three segregation generations (F2, B1, and B2) were higher than those in P1, F1, and P2 in terms of shoot biomass. The Kolmogorov-Smirnov test showed that the shoot biomasses of six generations were all normal distribution (Fig. 7.1).

7 Breeding of New Cultivar of Water Spinach with Low Shoot Cd and Pb. . . P1

14

12

12

8

Shoot biomass (g, FW)

8.9 F2

28

F1

14

24

12

20

10

Frequency

8 6

16 12

15.0

13.9

12.8

11.6

10.5

9.4

8.2

7.1

3.7

14.6

13.5

12.5

11.5

10.4

0

9.4

0 8.4

4

7.3

2

6.0

8

4

4.9

Shoot biomass (g, FW)

Shoot biomass (g, FW)

B2

18

B1

25

15 Frequency

20 15 10

12 9

Shoot biomass (g, FW)

Shoot biomass (g, FW)

Fig. 7.1 Normal distribution of shoot biomass of water spinach in six generations

11.8

10.9

9.3

10.1

8.5

7.7

6.1

5.3

4.5

16.1

15.1

14.0

12.9

11.9

10.8

9.8

8.7

0 7.6

0 6.6

3

5.5

5

3.7

6

6.9

Frequency

8.2

Shoot biomass (g, FW)

16

Frequency

7.5

3.9

19.1

17.5

15.9

14.2

12.6

0

10.9

2

0 9.3

4

2

6.8

6

4

6.0

6

10

5.3

8

4.6

Frequency

10

P2

16

14

7.6

Frequency

16

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Table 7.3 Maximum log-likelihood values (MLV) and AIC values under various genetic models for shoot biomass of water spinach Model A-1 A-2 A-3 A-4 B-1 B-2 B-3 B-4

MLV 968.40 969.56 1023.37 1010.79 950.50 966.37 967.55 971.59

AIC 1944.80 1945.13 2052.74 2027.58 1921.00 1944.74 1943.10 1949.17

Model B-5 B-6 C C-1 D D-1 D-2 D-3

MLV 1012.96 1012.96 947.53 983.97 946.59 959.48 959.47 962.07

AIC 2033.92 2031.92 1915.06 1981.95 1917.19 1936.95 1934.94 1940.13

Model D-4 E E-1 E-2 E-3 E-4 E-5 E-6

MLV 960.35 943.40 949.10 966.89 959.05 983.99 984.00 –

AIC 1936.70 1922.80 1928.20 1955.78 1936.10 1983.99 1985.99 –

Note: Lower AIC values are underlined

Maximum log-likelihood values (MLV) and AIC values of 24 genetic models are presented in Table 7.3. Models B-1, C, D, and E with lower AIC values were selected for goodness-of-fit tests. The results showed that two statistics in each of Model C, D, and E reach the significant level, and seven statistics in Model B-1 reach the significant level (Table 7.4). Therefore, only Model C, D, and E are suitable as a candidate genetic model. Furthermore, the likelihood ratio test for the three models showed χ2C-D ¼ 1.88 (P ¼ 0.390628), χ2C-E ¼ 8.26 (P ¼ 0.408494), and χ2D-E ¼ 6.38 (P ¼ 0.381995), indicating that there was no significant difference among them (P > 0.05). Because Model C has the lowest AIC value, it is chosen as the best genetic model for shoot biomass of water spinach. The first- and second-order component parameters in the Model C are presented in Table 7.5, and the estimates of genetic parameters in each segregating population are shown in Table 7.6. The values of additive [d] and dominant effects [h] were 3.425 and 7.583, respectively, indicating that the dominant effect was in the same direction as the additive effect, and was larger than the latter. The values of additive
additive [i], additive
dominance and dominance
dominance epistatic effects [l] were 5.332, 2.386, and 1.718, respectively. It demonstrated that the interaction among genes also had a great effect on shoot biomass. The heritability of polygene was relatively low (15.23%, 9.24%, and 17.74%) in the segregation generations (B1, B2, and F2), suggesting that environment has a greater effect on shoot biomass compared with polygene. In classical genetics, crop yield is considered as a complex trait controlled by polygene with low heritability (Li et al. 1995). The plant architecture is closely related to the traits such as plant height, leaf length, leaf width, number of leaves and branches, and diameter of stem, which determine the shoot biomass. Therefore, good genes need to be gathered continuously via the methods of hybridization and recurrent selection in order to improve the shoot biomass. The breeding method of individual selection, that is, to select the individual with the largest biomass, can be better than others, such as methods of mixed-individual selection and single seed descent.

Generation P1 F1 P2 B1 B2 F2 P1 F1 P2 B1 B2 F2 P1 F1 P2 B1 B2 F2 P1 F1 P2 B1 B2 F2

Statistic U12 0.265(0.6065) 0.611(0.4344) 0.541(0.4622) 0.125(0.7236) 1.054(0.3047) 15.120** 0.000(0.9899) 0.065(0.7991) 0.007(0.9346) 0.087(0.7676) 0.017(0.8971) 0.520(0.4710) 0.000(0.9930) 0.070(0.7919) 0.007(0.9319) 0.121(0.7283) 0.017(0.8971) 0.560(0.4541) 0.000(0.9995) 0.080(0.7777) 0.009(0.9264) 0.102(0.7495) 0.016(0.8993) 0.159(0.6904) U22 2.010(0.1562) 0.518(0.4718) 2.160(0.1416) 0.061(0.8046) 0.884(0.3472) 15.950** 0.433(0.5105) 0.247(0.6195) 1.068(0.3014) 0.156(0.6927) 0.024(0.8775) 1.006(0.3159) 0.498(0.4805) 0.212(0.6454) 1.011(0.3148) 0.316(0.5743) 0.024(0.8775) 1.034(0.3092) 0.636(0.4251) 0.151(0.6975) 0.900(0.3427) 0.484(0.4865) 0.025(0.8745) 0.316(0.5742)

U32 13.517** 0.022(0.8817) 9.188** 5.566* 0.046(0.8297) 0.838(0.3601) 7.189** 1.001(0.3171) 14.562** 0.190(0.6627) 1.249(0.2638) 1.487(0.2226) 8.155** 0.671(0.4127) 13.615** 0.813(0.3673) 1.249(0.2637) 1.366(0.2425) 10.193** 0.213(0.6446) 11.817** 2.392(0.1220) 1.258(0.2619) 0.497(0.4810)

2

0.2896(>0.05) 0.0755(>0.05) 0.2962(>0.05) 0.1868(>0.05) 0.1551(>0.05) 1.7899** 0.1495(>0.05) 0.0615(>0.05) 0.3728(>0.05) 0.0490(>0.05) 0.0846(>0.05) 0.1966(>0.05) 0.1666(>0.05) 0.0565(>0.05) 0.3461(>0.05) 0.0720(>0.05) 0.0846(>0.05) 0.1844(>0.05) 0.2023(>0.05) 0.0508(>0.05) 0.2967(>0.05) 0.0907(>0.05) 0.0847(>0.05) 0.0892(>0.05)

nW

Dn 0.1416(>0.05) 0.0914(>0.05) 0.1743(>0.05) 0.0822(>0.05) 0.0864(>0.05) 0.2318** 0.1172(>0.05) 0.0936(>0.05) 0.1710(>0.05) 0.0660(>0.05) 0.0815(>0.05) 0.0943(>0.05) 0.1214(>0.05) 0.0955(>0.05) 0.1669(>0.05) 0.0710(>0.05) 0.0815(>0.05) 0.0942(>0.05) 0.1294(>0.05) 0.0992(>0.05) 0.1588(>0.05) 0.0627(>0.05) 0.0815(>0.05) 0.0707(>0.05)

Notes: U12, U22, U32 χ2 statistics with 1 degree of freedom; nW2 Smirnov’s statistics; Dn Kolmogorov’s statistics; The probability value is in parentheses; * and ** represent the 0.05 and 0.01 significance level, respectively

E

D

C

Model B-1

Table 7.4 Goodness-of-fit tests for genetic models of shoot biomass of water spinach

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Table 7.5 Estimates of component parameters in genetic model C of shoot biomass of water spinach First-order parameter μ1 μ2 μ3 μ4 μ5 μ6

Estimate 12.739 9.847 5.888 9.793 7.561 7.344

Second-order parameter σ2 σ 42 σ 52 σ 62

Estimate 3.567 4.208 3.930 4.336

Notes: μ1, μ2, μ3, μ4, μ5, and μ6 are the distribution means in P1, F1, P2, B1, B2, and F2, respectively; σ 2 is the mean of phenotypic variances of P1, P2, and F1 and can be regarded as the environmental variance since there is no genetic variation in each of the three populations; σ 42, σ 52, and σ 62 are the phenotypic variances in B1, B2, and F2, respectively, which consist of polygenic variance and environmental variance

Table 7.6 Estimates of genetic parameters of shoot biomass of water spinach First-order parameter [d] [h] [i] [l]

Estimate 3.425 7.583 5.332 2.386 1.718

Second-order parameter σ 2p σ 2pg σ 2e h2pg (%)

Estimate B1 4.208 0.641 3.567 15.23

B2 3.930 0.363 3.567 9.24

F2 4.336 0.769 3.567 17.74

Notes: [d] additive effect of polygene; [h] dominant effect of polygene; [i] and [l] are additive
additive, additive
dominance and dominance
dominance epistatic effects for the polygene, respectively. σ 2p phenotypic variance; σ 2pg polygenic variance; σ 2e environmental variance; h2pg polygene heritability; σ 2p ¼ σ 2pg + σ 2e; h2pg ¼ σ 2pg/σ 2p

7.1.3

Genetic Model of Shoot Cd Concentration

P1 had the highest shoot Cd concentration, followed by F1 and P2, and the mean value of shoot Cd concentration in F1 was between the values of P1 and P2, but was higher than the average value of P1 and P2 (6.358 mg kg1 DW) (Table 7.7). The coefficient of variance in each of segregation generations of F2, B1, and B2, was higher than that in P1, P2, and F1. In addition, the Kolmogorov-Smirnov test showed that shoot Cd concentration in each of the six generations was at normal distribution (Fig. 7.2). Table 7.8 shows the maximum log-likelihood values and AIC values of 24 genetic models of shoot Cd concentration. Model D-1, D-2, and E-3 with lower AIC values were selected as candidate models. The results of goodness-of-fit test showed that 4 statistics in Model D-1 and D-2 and 8 ones in Model E-3 were significant (Table 7.9). Therefore, Model D-1 and D-2 were more suitable as genetic model of shoot Cd concentration than Model E-3. Furthermore, the likelihood ratio test for

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Table 7.7 Descriptive statistics of shoot Cd concentration (mg kg1, DW) of water spinach in six generations Generation P1 P2 F1 F2 B1 B2

Sample size 50 50 50 100 100 100

Minimum 7.062 3.471 5.035 4.248 5.757 3.375

Maximum 10.345 4.844 7.703 11.086 10.661 8.033

Mean 8.464 4.251 6.500 6.782 7.413 5.670

Standard deviation 0.871 0.290 0.560 1.335 1.003 0.960

CV (%) 10.29 6.82 8.61 19.68 13.53 16.93

the two models showed χ2 ¼ 0.000612 (P ¼ 0.980263), indicating that there was no significant difference between them (P > 0.05). Model D-2 was chosen as the best genetic model for shoot Cd concentration due to its lower AIC value than Model D-1. The first- and second-order component parameters in the Model D-2 are presented in Table 7.10, and the estimates of genetic parameters in each segregating population are shown in Table 7.11. These results showed that the sum of additive effects of major gene and polygene was greater than the dominant effect of polygene, implying that shoot Cd concentration was dominated by additive effect. The positive dominant effect of polygene suggested that the trait of shoot Cd concentration was positive partial dominance. Shoot Cd concentration of F1 generation was between those of P1 and P2 generations, and was close to that of P1 generation with higher shoot Cd concentration, and it is thus considered that no negative heterosis in shoot Cd concentration existed in water spinach. However, negative heterosis in kernel Cd concentration of sunflower is quite obvious and has been used to breed low Cd hybrid (Li et al. 1995). Therefore, shoot of water spinach may be different from sunflower kernel in terms of the genetic characteristics of Cd concentration. The heritability of major gene in the segregation generations B1, B2, and F2 ranged from 50.27 to 59.78%, and that of polygene was relatively low, only 2.68%, 8.69% and 24.07% for B1, B2, and F2, respectively. This indicates that variation of shoot Cd concentration in water spinach is greatly controlled by major gene and polygene, and determined by major gene. Comparatively, Cd concentration in durum wheat is controlled by a single low Cd gene with a high heritability (Clarke et al. 1997), and it is thus easier to breed low Cd cultivars of durum wheat than that of water spinach. In segregation generations, the heritability of major gene plus polygene ranged from 58.96% to 78.78% (Table 7.11), indicating that genetic effect was stronger than environmental effect. The average shoot Cd concentration of F1 generation was 6.5 mg kg1, which was between the averages of P1 (8.5 mg kg1) and P2 (4.3 mg kg1), demonstrating that there was no negative heterosis in shoot Cd concentration of water spinach. In this study, shoot Cd concentration was more influenced by genetic effects than by environmental effects.

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10 8

Shoot Cd concentration (mg kg-1, DW)

4.8

4.6

Shoot Cd concentration (mg kg-1, DW)

F1

14

4.5

3.5

10.3

9.9

8.9

9.4

0

8.5

0 8.0

4

7.5

2

4.3

8

4.1

4

3.9

6

3.7

Frequency

12

7.1

Frequency

P2

16

F2

25

12

20 Frequency

Frequency

10 8 6

15 10

4 5

11.1

9.0

9.7

8.4

7.7

6.3

B2

24 20

Frequency

20 Frequency

7.0

Shoot Cd concentration (mg kg-1, DW)

B1

25

5.6

4.2

7.7

7.3

6.9

6.6

6.2

5.8

5.4

5.0

Shoot Cd concentration (mg kg-1, DW)

4.9

0

0

10.4

2

15 10

16 12 8

5

Shoot Cd concentration (mg kg-1, DW)

Shoot Cd concentration (mg kg-1, DW)

Fig. 7.2 Normal distribution of shoot Cd concentration of water spinach in six generations

8.0

7.6

7.1

6.6

6.2

5.7

5.2

4.8

4.3

3.8

0 3.4

10.7

9.7

9.2

8.7

8.2

7.7

7.2

6.7

6.2

5.8

0

10.2

4

7 Breeding of New Cultivar of Water Spinach with Low Shoot Cd and Pb. . .

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Table 7.8 Maximum log-likelihood values (MLV) and AIC values under various genetic models for shoot Cd concentration of water spinach Model A-1 A-2 A-3 A-4 B-1 B-2 B-3 B-4

MLV 610.40 610.51 709.15 732.60 582.22 591.48 594.26 594.72

AIC 1228.79 1227.02 1424.30 1471.20 1184.44 1194.97 1196.51 1195.44

Model B-5 B-6 C C-1 D D-1 D-2 D-3

MLV 680.31 680.31 589.12 595.30 582.92 580.09 580.09 589.30

AIC 1368.63 1366.63 1198.24 1204.59 1189.84 1178.19 1176.19 1194.60

Model D-4 E E-1 E-2 E-3 E-4 E-5 E-6

MLV 583.63 579.36 580.24 588.74 580.46 592.16 595.28 –

AIC 1183.26 1194.73 1190.48 1199.49 1178.93 1200.31 1208.55 –

Note: Lower AIC values are underlined Table 7.9 Tests of goodness-of-fit for genetic models of shoot Cd concentration of water spinach Statistic U22 U32 Model Generation U12 D-1 P1 0.238(0.6258) 0.354(0.5517) 18.228**

D-2

E-3

F1

0.020(0.8864) 0.114(0.7362) 0.631(0.4270)

P2 B1

0.000(0.9921) 1.715(0.1903) 27.842** 1.704(0.1918) 1.832(0.1759) 0.128(0.7205)

B2

0.088(0.7665) 0.067(0.7955) 0.013(0.9096)

F2

0.629(0.4277) 0.881(0.3479) 0.466(0.4948)

P1

0.238(0.6258) 0.354(0.5517) 18.228**

F1

0.020(0.8864) 0.114(0.7362) 0.631(0.4270)

P2 B1

0.000(0.9922) 1.715(0.1903) 27.842** 1.704(0.1918) 1.832(0.1759) 0.128(0.7205)

B2

0.088(0.7666) 0.067(0.7956) 0.013(0.9098)

F2

0.629(0.4278) 0.881(0.3481) 0.466(0.4948)

P1

0.018(0.8939) 1.523(0.2171) 19.538**

F1

0.194(0.6597) 0.078(0.7801) 0.346(0.5561)

P2 B1 B2

0.121(0.7281) 2.666(0.1025) 26.878** 7.827** 8.270** 0.446(0.5043) 0.032(0.8573) 0.085(0.7708) 0.220(0.6391)

F2

0.182(0.6696) 0.115(0.7345) 0.088(0.7672)

nW

2

0.4063 (>0.05) 0.0444 (>0.05) 0.8809** 0.3037 (>0.05) 0.0557 (>0.05) 0.1211 (>0.05) 0.4063 (>0.05) 0.0444 (>0.05) 0.8809** 0.3037 (>0.05) 0.0557 (>0.05) 0.1211 (>0.05) 0.4108 (>0.05) 0.0555 (>0.05) 0.8551** 0.8389** 0.0644 (>0.05) 0.0581 (>0.05)

Dn 0.1758 (>0.05) 0.0711 (>0.05) 0.2288* 0.1062 (>0.05) 0.0710 (>0.05) 0.0883 (>0.05) 0.1758 (>0.05) 0.0711 (>0.05) 0.2288* 0.1062 (>0.05) 0.0710 (>0.05) 0.0883 (>0.05) 0.1642 (>0.05) 0.0769 (>0.05) 0.237** 0.1418* 0.0810 (>0.05) 0.0532 (>0.05)

Notes: The probability value is in parentheses; * and ** represent the 0.05 and 0.01 significance level, respectively

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Table 7.10 Estimates of component parameters in genetic model D-2 of shoot Cd concentration of water spinach First-order parameter μ1 μ2 μ3 μ41 μ42

Estimate 8.481 6.521 4.255 8.275 6.726

First-order parameter μ51 μ52 μ61 μ62 μ63

Estimate 6.319 4.971 8.723 6.289 6.288

Second-order parameter σ2 σ 42 σ 52 σ 62

Estimate 0.378 0.405 0.458 0.807

Notes: μ1, μ2, and μ3 are the distribution means in P1, F1, and P2, respectively; μ41 and μ42 are the distribution means of two major genes in B1; μ51 and μ52 are the distribution means of two major genes in B2; μ61, μ62, and μ63 are the distribution means of three major genes in F2; σ 2 is the mean of phenotypic variances of P1, P2, and F1 and can be regarded as the environmental variance since there is no genetic variation in each of the three populations; σ 42, σ 52, and σ 62 are the variances of component distributions in B1, B2, and F2, respectively, which consist of polygenic variance and environmental variance

Table 7.11 Estimates of genetic parameters of shoot Cd concentration of water spinach First-order parameter m d [d] [h]

Estimate 6.539 1.294 0.733 0.324

Second-order parameter σ 2p σ 2mg σ 2pg σ 2e h2mg (%) h2pg (%)

Estimate B1 1.007 0.602 0.027 0.378 59.78 2.68

B2 0.921 0.463 0.080 0.378 50.27 8.69

F2 1.782 0.975 0.429 0.378 54.71 24.07

Notes: m population mean of six generations; d additive effect of major gene; [d] additive effect of polygene; [h] dominant effect of polygene; σ 2p phenotypic variance; σ 2mg major-gene variance; σ 2pg polygenic variance; σ 2e environmental variance; h2mg major-gene heritability; h2pg polygene heritability; σ 2p ¼ σ 2mg + σ 2pg + σ 2e; h2mg ¼ σ 2mg/σ 2p; h2pg ¼ σ 2pg/σ 2p

7.2

Breeding of a Low Cd/Pb Accumulation and High Yield Water Spinach Cultivar

Although the biomass and concentrations of Cd and Pb in shoots of hybrid F1 (QLQ
T308) were closer to those of T308 rather than QLQ (Xin et al. 2010), it has been proved that shoot biomass and Cd concentration are controlled by polygene and one major gene + polygene, respectively. Therefore, it is possible to breed a new cultivar of water spinach with high yield and low concentrations of Cd and Pb by selecting purposefully individuals from offspring population reproduced by selfcrossing of the F1 generation. Previously, we selected 4 individuals from F2 population, whose shoot Cd concentrations were lower than the mean of QLQ and their shoot biomasses were higher than the mid-parent value of QLQ and T308 (Xin et al. 2012). After the self-crossing of the F2 generation, 11 out of 40 individuals of F3

7 Breeding of New Cultivar of Water Spinach with Low Shoot Cd and Pb. . .

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population were selected because their shoot biomass was higher than 95% of T308. Finally, only 1 individual was used to produce F4 generation due to its lower shoot Cd concentration than QLQ (Xin et al. 2012). Twenty F4 seeds (one per pot) were grown in contaminated soil with 0.46 mg Cd kg1 and 109.7 mg Pb kg1 and QLQ and T308 were used as controls. The results showed that there was no significant difference in shoot biomass between T308 and F4 population (Table 7.12). In addition, shoot Cd concentration of F4 population was lower than the Codex maximum limit (ML) for Cd, and is not significantly different from that of QLQ. As for shoot Pb concentration, the mean of F4 population is between those of QLQ and T308 with significant differences each other (Table 7.12). Notably, shoot Pb concentration of F4 individuals varied greatly, and those of some individuals were higher than the Codex ML for Pb, indicating that low Cd F4 individuals do not necessarily have low shoot Pb concentration (Fig. 7.3). Among 20 F4 individuals, No. 6 and 17 have lower shoot Cd and Pb concentrations and Table 7.12 Descriptive statistics of shoot biomass and concentrations of Cd and Pb in T308, QLQ, and F4 population Trait Shoot biomass (g, FW)

Shoot Cd concentration (mg kg1, FW)

Shoot Pb concentration (mg kg1, FW)

Statistic Sample size Minimum Maximum Mean Sample size Minimum Maximum Mean Sample size Minimum Maximum Mean

T308 3 22.6 27.3 25.2a 3 0.302 0.332 0.313a 3 0.361 0.405 0.384a

QLQ 3 13.7 16.2 15.1b 3 0.174 0.196 0.184b 3 0.233 0.270 0.254c

F4 20 19.8 38.2 29.2a 20 0.152 0.198 0.178b 20 0.245 0.408 0.318b

Note: Different small letters within the same row indicate significant difference at p < 0.05 level

Fig. 7.3 Shoot Cd and Pb concentrations and shoot biomass of F4 individuals

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Table 7.13 Descriptive statistics of shoot biomass and concentrations of Cd and Pb in T308, QLQ, and the new PSC Trait Shoot biomass (g, FW)

Shoot Cd concentration (mg kg1, FW) Shoot Pb concentration (mg kg1, FW)

Statistic Sample size Minimum Maximum Mean Sample size Minimum Maximum Mean Sample size Minimum Maximum Mean

CK T308 8 17.15 27.61 22.67 a 8 0.056 0.114 0.094 a 8 0.053 0.165 0.111 b

QLQ 8 11.68 17.96 15.84 b 8 0.038 0.068 0.054 b 8 0.042 0.161 0.125 b

new PSC 54 14.05 29.09 21.09 a 54 0.030 0.086 0.049 b 54 0.052 0.236 0.156 a

Cd/Pb co-exposure T308 QLQ 8 8 23.08 15.36 33.68 19.21 27.66 a 17.33 c 8 8 0.416 0.251 0.659 0.342 0.504 a 0.283 b 8 8 0.260 0.216 0.389 0.317 0.333 a 0.259 b

new PSC 54 11.66 33.22 23.68 b 54 0.217 0.383 0.397 b 54 0.172 0.383 0.250 b

Note: Different small letters within the same row indicate significant difference at p < 0.05 level

higher shoot biomass than others. Therefore, the two individuals can be used to breed for high yield and low Cd/Pb cultivar of water spinach. All F4 individuals show low shoot Cd accumulation, demonstrating that the trait of shoot Cd accumulation can be stably inherited. Additionally, most F4 individuals (16 out of 20) yielded a higher shoot biomass than the average value of T308, suggesting that the genes related to high yield have been successfully transmitted and integrated to offspring from their parents through breeding procedures. A new Cd/Pb-PSC water spinach cultivar was obtained by self-crossing of F4 individuals whose Cd and Pb concentrations have no significant difference with QLQ and biomass was higher than T308. The shoot biomass of the new Cd/Pb-PSC was between those of T308 and QLQ, and was significantly higher than that of QLQ both under control Cd/Pb co-exposures (Table 7.13). In addition, shoot Cd and Pb concentrations of the new Cd/Pb-PSC cultivar were lower than those of T308 under Cd/Pb co-exposures and had no significant difference with QLQ. These results indicated that we have successfully bred a new water spinach cultivar with low shoot Cd/Pb concentrations and high production. Compared with the development of durum wheat cultivar with low grain Cd concentration and high quality, the breeding for water spinach is really a time-saving process although the grain Cd concentration is proved to be controlled by a single gene. In Canada, 13 years were spent to develop the durum wheat cultivar “Strongfield,” which has high grain yield, protein concentration, grain yellow pigment concentration, and low grain Cd concentration (Clarke et al. 2006). Therefore, breeding of low Cd leafy vegetable is undoubtedly a shortcut to reduce heavy metal intake in human diet.

7 Breeding of New Cultivar of Water Spinach with Low Shoot Cd and Pb. . .

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139

Comparisons of Nutrients in Shoots Between the New Cd/Pb-PSC and Its Parents of Water Spinach

It has been reported that nutrient uptake in plants, especially for mineral elements, could be affected by heavy metals (Zhang et al. 2002; Liu et al. 2003). Unlike conventional breeding programs, which was usually aimed to increase crop yield or nutritional quality, Cd-PSCs breeding targeted to reduce Cd accumulation in edible parts of crops. Therefore, it is concerned that Cd-PSCs breeding might lower the nutritional qualities of crops accompanied by the decrease of Cd concentration. During the breeding of a low Cd durum wheat cultivar (“Strongfield”), the breeders also tried to improve the agronomic performance, disease resistance, and processing quality, and finally got a new cultivar with high yield, high grain protein, and low grain Cd concentration (Clarke et al. 2005). To verify whether the breeding process would not cut down the nutritional qualities of the new Cd-PSC cultivar, the shoot organic substances (chlorophyll, vitamin C, soluble protein, soluble sugar) and minerals elements (Ca, Mg, K, Zn and Cu) concentrations of the newly bred PSC of water spinach (offspring from the No. 17 individual of the F4) was compared to its parents (Huang et al. 2018).

7.3.1

Organic Substances

It has been reported that organic substances contents, including chlorophyll, vitamin C, soluble sugar, and soluble protein, would be significantly affected by heavy metals such as Cd and Pb (Table 7.14). Qiu et al. (2006) observed that soluble sugar content in Kandelia candel was increased under low Cd stress but decreased under high Cd stress. Monteiro et al. (2009) displayed that chlorophyll content was decreased by Cd treatment in lettuce (Lactuca sativa). According to Hassan et al. (2016), chlorophyll and carotenoid contents were significantly decreased by Cd treatment in potato (Solanum tuberosum). In Astragalus membranaceus, chlorophyll content in leaves and soluble protein and soluble sugar in roots were also have been reported to be decreased by Cd stress (Sainao et al. 2018). Similar decrements of sucrose content caused by Pb treatment have also been reported in edible parts of lettuce, spinach (Spinacia oleracea), radish (Raphanus sativus), carrot (Daucus carota), red beet (Beta vulgaris), and onion (Allium cepa) (Gaweda 2007). Mani et al. (2012) suggested that both Cd treatment alone and Cd/Pb co-exposure treatments could decrease soluble sugar and vitamin C content in spinach, radish, coriander (Coriandrum sativum), and fenugreek (Trigonella foenumgraecum). To verify the effects of the Cd-PSC breeding on the organic substance contents, chlorophyll, vitamin C soluble sugar and soluble protein, in edible parts of the newly bred water spinach cultivar with low shoot Cd/Pb concentration and high yield and

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Table 7.14 Several studies on the effects of heavy metals on organic substances contents Treatment Cd

Plant Kandelia candel

Cd

Lettuce

Cd

Potato

Cd

Astragalus membranaceus

Pb

Lettuce, spinach, radish, carrot, red beet, and onion Spinach, radish, coriander, and fenugreek Spinach, radish, coriander, and fenugreek

Cd

Cd + Pb

Conclusions Soluble sugar content was increased under low Cd stress but decreased under high Cd stress Chlorophyll content was decreased.

Chlorophyll content, carotenoid content, plant macronutrient (N, P, K, Ca, Mg) and micronutrient (Zn, Cu, Fe, Mn) uptake in potato root and shoots were decreased Chlorophyll content of the leaves and soluble protein content, and soluble sugar content of roots were decreased Sucrose content in edible plant parts was decreased while starch content was increased Soluble sugar content and vitamin C content were decreased

Ref. Qiu et al. (2006) Monteiro et al. (2009) Hassan et al. (2016) Sainao et al. (2018) Gaweda (2007) Mani et al. (2012)

Soluble sugar content and vitamin C content were decreased

its parents (QLQ and T308) were compared under control and Cd/Pb co-exposure. As shown in Fig. 7.4, shoot soluble sugar and protein did not shown significant differences among different cultivars under all of the treatment. Both shoot chlorophyll and vitamin C contents of the new bred cultivar had no significant difference with at least one of its parents (T308). It can be concluded that the PSC breeding did not decrease the organic substance contents of the newly bred water spinach Cd-PSC.

7.3.2

Metal Elements

As reviewed in Table 7.15, soil heavy metals can significantly affect the mineral elements uptake of the plants. Cd and Pb showed both synergistic and antagonistic effect on mineral elements uptake, which showed great variation among different species and changed with the concentrations of Cd and Pb in soils. It has been reported that Cd showed significant and positive correlations with Fe3+, Zn2+, Mn2+, and Cu2+ in 20 rice cultivars collected from different regions (Liu et al. 2003). Hassan et al. (2016) indicated that macronutrient (N, P, K, Ca, Mg) and micronutrient (Zn, Cu, Fe, Mn) uptakes in potato root and shoot were decreased by Cd treatment. Zhang et al. (2002) reported that the effects of Cd treatment on nutrient concentrations in wheat differed from different nutrients, genotypes, and organs,

7 Breeding of New Cultivar of Water Spinach with Low Shoot Cd and Pb. . .

2.5

B Treatment F = 7.65* Cultivar F= 13.60* Treatment × Cultivar F=1.34

2 1.5

a*

a

T308 QLQ new PSC

b

b

b

b

1 0.5 0

CK

Treatment

a ab b

Treatment F = 14.08* Cultivar F= 3.28 Treatment × Cultivar F=2.30 a a

40

a**

30 20 10

CK

Cd/Pb co-expusures

Treatment

D

30 Soluble protein concentrations (mg kg-1, FW)

50

0

Cd/Pb co-expusures

C Treatment F = 1.86 Cultivar F= 0.09 Treatment × Cultivar F=1.23

25 20 15 10 5 0

60 Vitamin C concentrations (mg kg-1, FW)

3

CK

Cd/Pb co-expusures

Treatment

Soluble sugar concentrations (mg kg-1, FW)

Chlorophyll concentrations (mg kg-1, FW)

A

141

Treatment F = 3.00 Cultivar F= 1.73 Treatment × Cultivar F=0.28

12 10 8 6 4 2 0

CK

Cd/Pb co-expusures

Treatment

Fig. 7.4 Shoot organic substances concentrations of QLQ, T308, and the new Cd/Pb-PSC under different treatments. Notes: (a) shoot chlorophyll concentrations; (b) vitamin C concentrations; (c) soluble protein concentrations; (d) soluble sugar concentrations; Different letters within the same soil indicate significant differences at p < 0.05 level between different cultivars; * and ** indicate significant difference at p < 0.05 and p < 0.01 level between different soil treatment. (Modified from Huang et al. 2018)

and P, K, and Mn contents in roots were increased by the Cd treatment. Yu et al. (2010) also found that Cd stimulated the absorption of Fe, Cu, and Zn in wheat roots, especially Fe. In 4 barley (Hordeum vulgare) genotypes, Cd reduced Ca and Mg concentrations in roots and shoots and increased Cu concentrations in roots compared to control (Huang et al. 2007). A synergistic effect between Cd and Fe and an antagonistic effect between Cd and Cu or Zn were observed in Lonicera japonica (Liu et al. 2011). The concentrations of P, K, Ca, Mg, Fe, and Zn were increased by Cd treatment in 25 welsh onion (Allium fistulosum) cultivars (Li et al. 2016). It has also been reported that mineral elements accumulation could be significantly affected by Pb treatment in 3 sunflower (Helianthus annuus) genotypes, and genotype-dependent difference was observed (Bao et al. 2013). Khan et al. (2016) indicated that Cd and Pb showed synergistic or antagonistic effects on Ca, Mg, Fe, and Mn uptake in potato, lettuce, and tomato.

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Table 7.15 Several studies on the effects of heavy metals on organic substances contents Treatment Cd

Plant Potato

/

Cd

20 rice cultivars collected from different regions Five wheat cultivars

Cd

Wheat

Cd

Four barley genotypes

Pb

Three sunflower genotypes

Cd/Pb

Potato, lettuce, tomato

Cd

Lonicera japonica

Cd

25 welsh onion cultivars

Conclusions Chlorophyll content, carotenoid content, plant macronutrient (N, P, K, Ca, Mg), and micronutrient (Zn, Cu, Fe, Mn) uptake in potato root and shoots were decreased Cooperative absorption between Cd2+ and Fe3+, Mn2+, Cu2+, Zn2+ were found in rice The effects of Cd treatment on nutrient concentrations in wheat varied among elements, genotypes, and parts. Cd treatment increased P, K, and Mn contents in roots Cd stimulated the absorption of Fe, Cu, and Zn in roots, especially Fe in roots Cd reduced Ca and Mg concentrations in roots and shoots, increased Cu concentrations in roots Pb treatment significantly affected mineral elements accumulation and showed genotypedependent difference Cd and Pb showed both synergistic and antagonistic effects on mineral nutrients uptake (Ca, Mg, Fe, Mn) A synergistic effect between Cd and Fe and an antagonistic effect between Cd and Cu or Zn were found Cd treatment increased the concentrations of inorganic nutrients (P, K, Ca, Mg, Fe, and Zn)

Ref. Hassan et al. (2016) Liu et al. (2003) Zhang et al. (2002) Yu et al. (2010) Huang et al. (2007) Bao et al. (2013) Khan et al. (2016) Liu et al. (2011) Li et al. (2016)

To verify the effects of the Cd-PSC breeding of water spinach on the mineral nutrients, shoot concentrations of five mineral elements (Ca, Mn, K, Zn, and Cu) of the new cultivar and its parents (QLQ and T308) were compared under control and Cd/Pb co-exposure. As shown in Fig. 7.5, shoot Mg, K, and Cu concentrations were not significantly affected by the treatments, cultivars, and interaction of treatment
cultivar. Shoot Ca and Zn were significantly affected by cultivar. For the five tested mineral elements, the new cultivar had no significant differences with at least one of its parents, suggesting that the Cd-PSC breeding of water spinach did not decrease the mineral nutrients contents of the new Cd-PSC. In summary, the breeding process targeted to get a new Cd-PSC of water spinach did not decreased the nutritional quality including mineral elements and organic nutritional components when compared to at least one of its parents (Table 7.16). These results suggest that the decrease of Cd and Pb would not decline nutritional components in the offspring from the Cd-PSCs breeding process, and the Cd-PSC breeding for vegetables would be feasible if appropriate breeding method was employed.

7 Breeding of New Cultivar of Water Spinach with Low Shoot Cd and Pb. . .

Shoot Ca concentrations (mg kg-1, FW)

1.8 a

1.6

B

Treatment F = 0.04 Cultivar F = 0.20 ** a Treatment × Cultivar F = 1.34

1.4

T308 QLQ new PSC

b

1.2

b

b

b

1 0.8 0.6 0.4 0.2

Shoot Mg concentrations (mg kg-1, FW)

A

250

Treatment F = 0.41 Cultivar F = 2.73 Treatment × Cultivar F = 0.38

200

150

100

50

0

0 CK

CK

Cd/Pb co-exposures

Cd/Pb co-exposures

Treatment Treatment F = 0.85 Cultivar F = 2.02 Treatment × Cultivar F = 0.99

20

Shoot Zn concentration (mg kg-1, FW)

7

Shoot K concentration (g kg-1, FW)

Treatment

D

C 6 5 4 3 2 1 0

Cd/Pb co-exposures

1.8 1.6

16 14

a

a

ab a

b

a

12 10 8 6 4 2 CK

Cd/Pb co-exposures

Treatment

Treatment

E

18

Treatment F = 2.16 Cultivar F = 7.11** Treatment × Cultivar F = 0.68

0 CK

Shoot Cu concentration (mg kg-1, FW)

143

Treatment F = 0.01 Cultivar F = 2.71 Treatment × Cultivar F = 0.87

1.4 1.2 1 0.8 0.6 0.4 0.2 0 CK

Cd/Pb co-exposures

Treatment

Fig. 7.5 Shoot mineral elements concentrations of QLQ, T308, and the new Cd/Pb-PSC under different treatments. Notes: (a) Shoot Ca concentrations; (b) Mg concentrations; (c) K concentrations; (d) Zn concentrations; (e) Cu concentrations; Different letters within the same soil indicate significant difference at p < 0.05 level between different cultivars; * and ** indicate significant difference at p < 0.05 and p < 0.01 level between different soil treatment (modified from Huang et al. 2018)

0.304

0.174 0.193 0.514 0.049 0.372 0.036

0.665 0.128

0.073

0.929 0.648 0.203 0.397 0.982* 0.902

0.592 0.500

0.970*

0.251 0.021 0.429 0.213 0.063 0.171

B B I I B I

B

I D

E

0.969* 0.095 0.151 0.041 0.848 0.721

0.276

0.549 0.842 0.589 0.944 0.790 0.664 0.571

0.101 0.532

QLQ

0.434 0.344

Pb T308

0.960* 0.963* 0.162 0.188 0.818 0.082

0.124

new PSC 0.271 0.348

B D B B B D

I

I U

E

0.070 0.397 0.211 0.333 0.971* 0.466

0.944

0.537 0.190

0.063 0.126 0.482 0.563 0.816 0.603

0.896

0.985* 0.893

Cd/Pb treatment Cd T308 QLQ

0.992** 0.930 0.159 0.756 0.974* 0.571

0.181

0.339 0.961*

new PSC

I D B D D B

B

B I

E

0.678 0.730 0.403 0.299 0.747 0.821

0.636

0.150 0.862

Pb T308

0.545 0.553 0.975* 0.949 0.776 0.643

0.732

0.376 0.066

QLQ

0.661 0.835 0.372 0.390 0.753 0.077

0.256

new PSC 0.806 0.390

I D I I U I

B

I I

E

Notes: * significant at p < 0.05 level; ** significant at p < 0.01 level; E evaluation for the changes in the new bred genotype based on the relationships between concentrations of the components related to nutritional quality and Cd or Pb each other (comparing between the new bred genotype and its parents): I improved; D dropped; B balanced; U unchanged

Chlorophyll Soluble protein Soluble sugar Vitamin C Ca Mg K Zn Cu

new PSC 0.982* 0.790

QLQ

CK Cd T308

Table 7.16 Correlation coefficients between Cd or Pb concentration and the traits related to nutritional quality in the shoot of water spinach

144 J. Xin et al.

7 Breeding of New Cultivar of Water Spinach with Low Shoot Cd and Pb. . .

145

Acknowledgments This work was supported by National Natural Science Foundation of China (Grant Nos. 20877104, 21277178, 21777195, and 41977147).

References Akaike H (1977) On entropy maximum principles. Applications of statistics. North-Holland Publishing Company, Amsterdam, Netherlands Bao SG, Liu HX, Na Q et al (2013) Effects of absorption and accumulation of mineral elements in sunflower seedlings under lead stress. J Soil Water Conserv 27(1):107–110 Clarke J, Leisle D, Kopytko G (1997) Inheritance of cadmium concentration in five durum wheat crosses. Crop Sci 37:1722–1726 Clarke J, McCaig T, DePauw R et al (2005) Strongfield durum wheat. Can J Plant Sci 85(3): 651–654 Clarke J, McCaig T, DePauw R et al (2006) Registration of ‘Strongfield’ durum wheat. Crop Sci 46: 2306–2307 Gai J, Zhang Y, Wang J (2003) Genetic system of quantitative traits in plants. Science Press, Beijing Gaweda M (2007) Changes in the contents of some carbohydrates in vegetables cumulating lead. Pol J Environ Stud 16(1):57–62 Grant CA, Clarke JM, Duguid S et al (2008) Selection and breeding of plant cultivars to minimize cadmium accumulation. Sci Total Environ 390:301–310 Hao JJ, Yu SX, Ma QX et al (2008) Inheritance of time of flowering in upland cotton under natural conditions. Plant Breed 127(4):383–390 Hassan W, Bano R, Bashir S et al (2016) Cadmium toxicity and soil biological index under potato (Solanum tuberosum L.) cultivation. Soil Research 54(4):460 Huang YZ, Wei K, Yang J et al (2007) Interaction of salinity and cadmium stresses on mineral nutrients, sodium, and cadmium accumulation in four barley genotypes. J Zhejiang Univ B 8(7): 476–485 Huang YY, He CT, Shen C et al (2017) Toxicity of cadmium and its health risks from leafy vegetable consumption. Food Funct 8(4):1373–1401 Huang YY, Mu YX, He CT et al (2018) Cadmium and lead accumulations and agronomic quality of a newly bred pollution-safe cultivar (PSC) of water spinach. Environ Sci Pollut Res Int 25(11): 1–11 Khan A, Khan S, Alam M et al (2016) Toxic metal interactions affect the bioaccumulation and dietary intake of macro- and micro-nutrients. Chemosphere 146:121–128 Li YM, Chaney RL, Schneither AA et al (1995) Combining ability and heterosis estimates for kernel cadmium level in sunflower. Crop Sci 35(4):1015–1019 Li X, Zhou Q, Sun X et al (2016) Effects of cadmium on uptake and translocation of nutrient elements in different welsh onion (Allium fistulosum L.) cultivars. Food Chem 194:101–110 Liu JG, Liang JS, Li KQ et al (2003) Correlations between cadmium and mineral nutrients in absorption and accumulation in various genotypes of rice under cadmium stress. Chemosphere 52(9):1467–1473 Liu Z, He X, Chen W (2011) Effects of cadmium hyperaccumulation on the concentrations of four trace elements in Lonicera japonica Thunb. Ecotoxicology 20(4):698–705 Mani D, Sharma B, Kumar C et al (2012) Cadmium and lead bioaccumulation during growth stages alters sugar and vitamin C content in dietary vegetables. Proc Nat Acad Sci India B Biol Sci 82(4):477–488 Monteiro MS, Santos C, Soares A et al (2009) Assessment of biomarkers of cadmium stress in lettuce. Ecotoxicol Environ Safety 72(3):811–818

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Qiu QG, Ling YC, Li WL (2006) Effect of cadmium stress on the contents of tannin, soluble sugar and proline in Kandelia candel (L.) Druce seedlings. Acta Ecol Sinica Sainao WQ, Zhang MD, Ma XJ et al (2018) Physiological effects of cadmium stress on Astragalus membranaceus seedlings and alleviative effects of attapulgite clay on cadmium stress. China J Chinese Materia Med 43(15):3115–3126 Xin J, Huang B, Yang Z et al (2010) Responses of different water spinach cultivars and their hybrid to Cd, Pb and Cd–Pb exposures. J Hazard Mater 175(1-3):468–476 Xin J, Huang B, Yang J et al (2012) Breeding for pollution-safe cultivar of water spinach to minimize cadmium accumulation and maximize yield. Fresenius Environ Bull 21(7):1833–1840 Yu KL, Zou J, Zou JH (2010) Effects of cadmium stress on antioxidant enzyme system and absorption of mineral elements in maize seedlings. J Agro-Environ Sci 29(6):1050–1056 Zhang YM, Gai JY (2000) Identification of mixed major genes and polygenes inheritance model of quantitative traits by using DH or RIL population. Acta Genet Sin 27:634–640 Zhang G, Fukami M, Sekimoto H (2002) Influence of cadmium on mineral concentrations and yield components in wheat genotypes differing in Cd tolerance at seedling stage. Field Crop Res 77(2-3):93–98 Zhang YM, Gai JY, Yang YH (2003) The EIM algorithm in the joint segregation analysis of quantitative traits. Genet Res 81:157–163 Zhou Q. (2016) Molecular Mechanisms in Cadmium Induced Genotype Differences of Two Important Vegetables Belonging to Genus Brassica [D]. Sun Yat-Sen University

Chapter 8

Differences of Cd-Induced Gene Expressions Between Low- and High-Cd Accumulating Cultivars of Water Spinach: A Case Using Suppression Subtractive Hybridization (SSH) Method Baifei Huang, Xiaojun Liu, Yingying Huang, Chuang Shen, Huiling Fu, Zhongyi Yang, and Junliang Xin

Contents 8.1 Functional Classification of Cd-Induced Genes in the Shoot of Water Spinach . . . . . . . . 8.2 Different Responsive Genes in Shoots of Low-Cd and High-Cd Cultivars of Water Spinach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 Different Responsive Genes in the Roots of Low-Cd and High-Cd Cultivars of Water Spinach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

148 163 167 172

Two Cd-PSCs of water spinach were selected in order to reduce Cd content entering into food chain. The mechanisms of the cultivar-dependent Cd accumulation are worth studying. Various methods, such as differential display reverse transcriptionpolymerase chain reaction (DDRT-PCR) approach (Wang et al. 2019), suppression subtractive hybridization (SSH) (Huang et al. 2009) and comparative transcriptome analysis (Zhou et al. 2016; Huang et al. 2016), were used to investigate mechanisms of differential gene expression in cultivars. In this chapter, genes differentially expressed between the two water spinach cultivars were investigated by using SSH method.

B. Huang · Y. Huang · C. Shen · H. Fu · J. Xin (*) School of Chemical and Environmental Engineering, Hunan Institute of Technology, Hengyang, Hunan, China e-mail: [email protected] X. Liu Quatech Consulting Co., Ltd., Guangzhou, Guangdong, China Z. Yang School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China © Springer Nature Singapore Pte Ltd. 2022 Z. Yang et al. (eds.), Theories and Methods for Minimizing Cadmium Pollution in Crops, https://doi.org/10.1007/978-981-16-7751-9_8

147

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Functional Classification of Cd-Induced Genes in the Shoot of Water Spinach

Based on suppression PCR, SSH is a good method to find genes differentially expressed in two groups. Some studies used SSH to find genes related to heavy metal tolerance and accumulation in plants. A type 2 metallothionein gene (MT2) was found differentially regulated in lead-treated Sesbania drummondii by the SSH method (Srivastava et al. 2007). Differentially expressed genes in the roots between two wheat near-isogenic lines after aluminium stress were compared through the SSH method (Guo et al. 2007). We conducted an SSH experiment using the high-Cd accumulation cultivar (T308) and the low Cd accumulation cultivar (QLQ) of water spinach with three Cd treatments shown in Table 8.1. After treated with different Cd concentrates, shoots of plants were sampled and the fresh shoots were used for SSH (Huang et al. 2009). Four SSH libraries were constructed, namely a QLQ 24S library, a T308 24S library, a QLQ GS library and a T308 GS library. In QLQ 24S library and T308 24S library, the cDNA prepared from the 24 h Cd-treated seedlings of cv.QLQ or cv.T308 was used as the “tester” and that from the control samples of cv.QLQ or cv.T308 was used as the “driver”. There were rather different responses to the Cd stresses between the two libraries and the results were reported in detail (Huang et al. 2009). In QLQ GS library and T308 GS library, the cDNA prepared from the gradient Cd-treated seedlings of cv. QLQ or cv.T308 was used as the “tester” and that from the control samples of cv.QLQ or cv. T308 was used as the “driver”. In QLQ 24S and T308 24S library, 220 non-repeat sequences (150 from the QLQ 24S library and 70 from the T308 24S library) were obtained. By comparison with the databases of BLASTN and BLASTX, 164 non-repeat sequences (112 from the QLQ 24S library and 52 from the T308 24S library) were homologous with the published sequences in the databases (Table 8.2), and 56 non-repeat sequences (38 from the QLQ 24S library and 18 from the T308 24S library) had no significant similarity with published sequences. Among the 164 known sequences, 136 (93 from the QLQ 24S library and 43 from the T308 24S library) of them could be assigned to functional proteins or genes, but 28 sequences (19 from the QLQ 24S library and 9 from the T308 24S library) were classified into gene or protein without any known function. cDNA fragments representing the same gene were counted as a single gene, and a total of 102 different Cd-induced genes (68 from the QLQ 24S library and 34 from the T308 24S library) with putative function was obtained. In QLQ GS and T308 GS library, Table 8.1 Treatment of water spinach with Cd (mg kg
1) Cultivar and treatment Gradient Cd treatment (G) Twenty-four hours Cd treatment (24) Without Cd treatment (Control)

1–7 d 1 0

8–10 d 2 0

11–13 d 3 0

14–16 d 4 0

17–19 d 5 0

20–21 d 6 6

0

0

0

0

0

0

8 Differences of Cd-Induced Gene Expressions Between Low- and High-Cd. . .

149

Table 8.2 Cd-induced genes in four libraries of shoot SSH Clone Name Q168

Base pairs 279

Q31

495

Q58

339

Q18

307

*Q133

249

*Q200, Q201

332

Q77, Q105, Q393

424

Q312

411

Q391

503

Q356

320

Q345

277

Q390

388

Q222

355

Q339

371

Q21

293

Q68

497

*Q254, Q185

520

Nearest homolog Ipomoea nil In35 mRNA for hypothetical protein, complete cds Lycopersicon esculentum clone 133171F, mRNA sequence Lycopersicon esculentum clone 135057F, mRNA sequence Oryza rufipogon (W1943) cDNA clone: ORW1943C104F01, full insert sequence plant synaptotagmin [Populus trichocarpa] PREDICTED: hypothetical protein [Vitis vinifera] Solanum lycopersicum cDNA, clone: FC18AB11, HTC in fruit Solanum lycopersicum cDNA, clone: LEFL1004AF11, HTC in leaf Solanum lycopersicum cDNA, clone: LEFL1004DE06, HTC in leaf Solanum lycopersicum cDNA, clone: LEFL1012CG05, HTC in leaf Solanum lycopersicum cDNA, clone: LEFL1012DC08, HTC in leaf Solanum lycopersicum cDNA, clone: LEFL1023BC11, HTC in leaf Solanum lycopersicum cDNA, clone: LEFL1073DB11, HTC in leaf Solanum lycopersicum cDNA, clone: LEFL1096AH08, HTC in leaf Solanum lycopersicum Tomato chromosome 2, C02SLe0089P21, complete sequence Solanum tuberosum Drm3-like protein mRNA, complete cds SOUL heme-binding family protein [Arabidopsis thaliana]

FUN. CAT.a 0

Score Acc. 3eAB267830.1 120 2e81 2e22 1e42

BT014071.1

0

BT013331.1

0

CT841984.1

0

5e35 2e20 4e57 5e38

XP_002312964.1

0

XP_002271692.1

0

AK246646.1

0

AK319467.1

0

1e59

AK320084.1

0

5e49

AK320730.1

0

9e20

AK320745.1

0

1e25

AK319506.1

0

2e23

AK324212.1

0

5e50

AK325408.1

0

9e146

AC215459.1

0

7e68 2e46

DQ191667.1

0

NP_173153.1

0 (continued)

150

B. Huang et al.

Table 8.2 (continued) SSH Clone Name Q344

Base pairs 343

Q56

289

Q14

507

Q191

552

*Q209

276

*Q116

183

Q205

269

*Q198

271

Q137

416

Q218

345

Q179

222

Q73

497

Nearest homolog Vitis vinifera, whole genome shotgun sequence, contig VV78X057517.7, clone ENTAV 115 Vitis vinifera, whole genome shotgun sequence, contig VV78X266006.21, clone ENTAV 115 Arabidopsis thaliana bis(50 -adenosyl)-triphosphatase, putative (AT5G58240) mRNA, complete cds Arabidopsis thaliana TMS membrane family protein/ tumour differentially expressed (TDE) family protein (AT1G16180) mRNA, complete cds ATHDH (HISTIDINOL DEHYDROGENASE); histidinol dehydrogenase [Arabidopsis thaliana] ATPH1 (ARABIDOPSIS THALIANA PLECKSTRIN HOMOLOGUE 1); phosphoinositide binding [Arabidopsis thaliana] Capsicum chinense acyl-ACP thioesterase (FatA) mRNA, complete cds CNX2 (COFACTOR OF NITRATE REDUCTASE AND XANTHINE DEHYDROGENASE 2); catalytic [Arabidopsis thaliana] Gossypium hirsutum beta-Dglucosidase mRNA, complete cds Lycopersicon esculentum arginase 1 (ARG1) mRNA, complete cds Nicotiana tabacum obtusifoliol14-demethylase (NtCYP51-2) mRNA, complete cds Nicotiana tabacum phosphoribosylaminoimidazole carboxylase (purEK) mRNA, partial cds

Score Acc. 3eAM438874.1 20

FUN. CAT.a 0

8e20

AM461090.1

0

8e67

NM_203228.2

1

3e61

NM_101485.2

1

2e13

NP_851260.1

1

8e10

NP_565687.1

1

3e32

AF318288.1

1

1e26

NP_850177.2

1

7e68

AY335818.1

1

4e83

AY656837.1

1

3e49

AY065641.1

1

4e128

AY429422.1

1

(continued)

8 Differences of Cd-Induced Gene Expressions Between Low- and High-Cd. . .

151

Table 8.2 (continued) SSH Clone Name Q385

Base pairs 449

Q135

490

Q208

418

Q316

533

Q165, Q352, Q365, Q371

346

Q273

311

Q20

188

Q375

227

Q333

236

Q27, Q176

308

Q120, Q206, Q413 307

Q3, Q114, Q175, Q188, Q271, Q304, Q323 Q122

276

502

Q217

443

Nearest homolog PREDICTED: Vitis vinifera hypothetical protein LOC100254959 (LOC100254959), mRNA. carbohydrate metabolism PREDICTED: Vitis vinifera similar to hydrolase, alpha/beta fold family protein (LOC100265524), mRNA Solenostemon scutellarioides CBS domain-containing protein mRNA, complete cds Zea mays haloacid dehalogenase-like hydrolase domain-containing protein 1A (LOC100280513), mRNA Brassica rapa mRNA for putative delta subunit of ATP synthase, partial cds Capsicum annuum mRNA for chloroplast ferredoxin-NADP+ oxidoreductase precursor (fnr gene) Lycopersicon esculentum 33 kDa precursor protein of oxygen-evolving complex (PsbO) mRNA, partial cds N.tabacum mRNA for chloroplast Rieske FeS precursor protein 1 Prunus persica clone Mdh1 NAD-dependent malate dehydrogenase (mdh1) mRNA, complete cds S.tuberosum cycl gene encoding cytochrome c1 Zea mays clone 1695472 ferredoxin-1 mRNA, complete cds Zea mays clone 1695472 ferredoxin-1 mRNA, complete cds Nicotiana tabacum mRNA for histone H3, complete cds Nicotiana tabacum mRNA for histone H3, complete cds

FUN. Score Acc. CAT.a 2eXM_002276836.1 1 132

6e51

XM_002265985.1 1

3e41

EF076754.1

1e76

NM_001153433.1 1

8e41

D78493.1

2

5e76

AJ250378.1

2

1e46

DQ539439.1

2

2e40

X66009.1

2

8e20

AF367442.1

2

2e91 5e43

X62124.1

2

EU958479.1

2

1e44

EU958479.1

2

3e136 4e71

AB015760.1

3

AB015760.1

3

1

(continued)

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Table 8.2 (continued) SSH Clone Name Q158, Q162

Base pairs 567

Q377

453

Q57

446

Q322

822

Q406

470

*Q379

293

Q359

294

Q187

321

Q170

466

Q308

633

Q147

428

Q409

675

Q128

472

Q28, Q74

497

Q157

248

Nearest homolog Populus trichocarpa precursor of protein cell division protease ftsh-like protein, mRNA Camellia sinensis zinc finger protein mRNA, complete cds L.esculentum mRNA for homeobox protein Nicotiana tabacum poly(A)binding protein (PABP) mRNA, complete cds Populus trichocarpa AP2 domain-containing transcription factor (RAP2), mRNA Zinc finger (C3HC4-type RING finger) family protein [Arabidopsis thaliana]. Arabidopsis thaliana 60S ribosomal protein L10A (RPL10aA) (AT1G08360) mRNA, complete cds Arabidopsis thaliana putative hydroxyproline-rich glycoprotein (At3g22440) mRNA, complete cds Nicotiana tabacum (clone: L24-2) chloroplast ribosomal protein L24 mRNA, complete cds Solanum tuberosum 60s acidic ribosomal protein-like protein mRNA, complete cds Solanum tuberosum clone 081G01 ribosome-associated protein p40-like mRNA, complete cds Solanum tuberosum clone 154B05 ripening regulated protein DDTFR10-like mRNA, complete cds Solanum tuberosum EF-1-alpha mRNA for Elongation factor 1-alpha, complete cds Solanum tuberosum ribosomal protein S27-like protein mRNA, complete cds Ipomoea batatas aspartic protease mRNA, complete cds

FUN. Score Acc. CAT.a 2eXM_002301891.1 3 159 1e46 3e72 0

DQ869863.1

4

X94947.1

4

AF190655.1

4

3e80

XM_002310679.1 4

6e18

NP_001078548.1

4

1e74

NM_100709.4

5

5e56

AY096625.1

5

6e82

M87839.1

5

1e74

DQ191633.1

5

1e121

DQ207864.1

5

1e162

DQ235167.1

5

3e156

AB061263.1

5

2e87

DQ191664.1

5

3e113

DQ903691.1

6 (continued)

8 Differences of Cd-Induced Gene Expressions Between Low- and High-Cd. . .

153

Table 8.2 (continued) SSH Clone Name Q123

Base pairs 547

Q324, Q400

326

Q194

235

Q90

948

Q155

382

Q319

485

*Q367

453

Q130, Q207, Q389 361 Q24

167

Q63

290

Q260

291

*Q224

492

Q239, Q403

367

Q64

159

Q418

470

Nearest homolog Ipomoea batatas cathepsin B-like cysteine proteinase (CathB) mRNA, complete cds Lycopersicon esculentum leucine aminopeptidase preprotein (LapN) mRNA, complete cds Nicotiana tabacum B38 mRNA for DnaJ homolog, complete cds Nicotiana tabacum Ntubc1 mRNA for ubiquitinconjugating enzyme (E2), complete cds Populus tomentosa cultivar Hebeinica cysteine proteinase inhibitor (HBMYCPI) mRNA, complete cds Populus trichocarpa f-box family protein (FBL2), mRNA predicted protein [Populus trichocarpa] serine-type endopeptidase inhibitor activity Sweet potato sporamin B mRNA, complete cds Tamarix androssowii ubiquitinconjugating enzyme family protein mRNA, complete cds Momordica charantia auxin influx carrier-like protein 2 (AIC2) mRNA, complete cds Nicotiana tabacum mRNA for sucrose transporter (sut1x gene), cultivar Samsun Protease inhibitor/seed storage/ lipid transfer protein (LTP) family protein [Arabidopsis thaliana] Pyrus communis Py-PIP2-1 mRNA for plasma membrane intrinsic protein 2-1, complete cds Pyrus communis Py-PIP2-1 mRNA for plasma membrane intrinsic protein 2-1, complete cds S.tuberosum pPOM36I mRNA for 36kDA porinI

FUN. CAT.a 6

Score Acc. 0 AF101239.1

3e58

AF510743.1

6

2e51 4e106

AB032545.1

6

AB026055.1

6

5e29

DQ020096.1

6

1e104 1e11

XM_002321300.1 6 XP_002314645.1

6

7e29 3e41

M16883.1

6

AY587772.1

6

3e25

AF522029.1

7

3e32

FM164640.1

7

5e14

NP_188456.1

7

3e65

AB058678.1

7

1e27

AB058678.1

7

2e81

X80388.1

7 (continued)

154

B. Huang et al.

Table 8.2 (continued) SSH Clone Name *Q417

Base pairs 349

Q12

664

Q150, Q369

288

Q101

317

Q117

378

Q121

384

Q13, Q302

319

Q132, Q203, Q330 366 Q159

338

Q169

351

Q17

208

Q171

337

Q182

332

Q204

456

Q225

340

Q252

348

Q266

380

Q307

495

Q328

400

Q45

703

Nearest homolog Glycoside hydrolase family 28 protein/polygalacturonase (pectinase) family protein [Arabidopsis thaliana]. Arabidopsis thaliana protein kinase family protein (AT1G64630) mRNA, complete cds Nicotiana benthamiana ADP-ribosylation factor 1 (ARF1) mRNA, complete cds Calystegia sepium lectin mRNA, complete cds Calystegia sepium lectin mRNA, complete cds Calystegia sepium lectin mRNA, complete cds Calystegia sepium lectin mRNA, complete cds Calystegia sepium lectin mRNA, complete cds Calystegia sepium lectin mRNA, complete cds Calystegia sepium lectin mRNA, complete cds Calystegia sepium lectin mRNA, complete cds Calystegia sepium lectin mRNA, complete cds Calystegia sepium lectin mRNA, complete cds Calystegia sepium lectin mRNA, complete cds Calystegia sepium lectin mRNA, complete cds Calystegia sepium lectin mRNA, complete cds Calystegia sepium lectin mRNA, complete cds Calystegia sepium lectin mRNA, complete cds Calystegia sepium lectin mRNA, complete cds Calystegia sepium lectin mRNA, complete cds

Score Acc. 4eNP_194081.1 35

FUN. CAT.a 9

4e41

NM_105138.4

10

2e98

DQ531849.1

10

1e87 1e109 8e111 2e90 1e109 1e100 6e106 2e50 2e98 1e95 1e26 6e99 2e104 4e108 1e134 3e97 0

U56820.1

11

U56820.1

11

U56820.1

11

U56820.1

11

U56820.1

11

U56820.1

11

U56820.1

11

U56820.1

11

U56820.1

11

U56820.1

11

U56820.1

11

U56820.1

11

U56820.1

11

U56820.1

11

U56820.1

11

U56820.1

11

U56820.1

11 (continued)

8 Differences of Cd-Induced Gene Expressions Between Low- and High-Cd. . .

155

Table 8.2 (continued) SSH Clone Name Q85

Base pairs 110

Q96

306

Q227

403

Q5, Q301

414

Q373

198

Q143

220

Q202

279

Q67

442

Q313

808

Q22, Q29

358

*Q34, Q263

500

*Q415

480

*Q192

612

Q329

520

Q370

270

Q407

369

*Q219

335

Q7, Q30, Q395

429

*Q156

180

*T14, T148

348

Nearest homolog Calystegia sepium lectin mRNA, complete cds Calystegia sepium lectin mRNA, complete cds Ipomoea batatas metallothionein-like protein (SPMT) mRNA, complete cds Ipomoea batatas metallothionein-like protein (SPMT) mRNA, complete cds Ipomoea batatas mRNA for ipomoelin, complete cds Ipomoea batatas mt2k mRNA for metallothionein-like type 2 protein, complete cds Ipomoea batatas proteinase inhibitor (SPLTI-b) mRNA, complete cds Nicotiana tabacum polyphenol oxidase gene, partial cds Nicotiana tabacum sretory peroxidase (PER) mRNA, complete cds Nicotiana tabacum wound inducive mRNA, complete cds Polyphenol oxidase [Populus trichocarpa] Polyphenol oxidase [Populus trichocarpa] Polyphenol oxidase [Populus trichocarpa] Populus EST from severe drought-stressed leaves Populus EST from severe drought-stressed leaves Populus EST from severe drought-stressed leaves Protease inhibitor, putative [Arabidopsis thaliana] Sweet potato mRNA for catalase (EC 1.11.1.6) Wound-responsive proteinrelated [Arabidopsis thaliana] Arabidopsis thaliana unknown protein

Score 9e26 1e80 3e155

Acc. U56820.1

FUN. CAT.a 11

U56820.1

11

AF242374.1

11

4e158

AF242374.1

11

1e35 6e59

D89823.1

11

AB193157.1

11

4e75

AF404833.1

11

3e21 0

DQ356947.1

11

AF149251.1

11

2e79 5e42 6e39 7e49 3e35 2e21 3e21 2e13 2e180 5e21 1e26

AB009885.1

11

XP_002331793.1

11

XP_002331793.1

11

XP_002331793.1

11

CU227612.1

11

CU227595.1

11

CU227595.1

11

NP_030435.1

11

X05549.1

11

NP_177671.1

11

NP_564055

0 (continued)

156

B. Huang et al.

Table 8.2 (continued) SSH Clone Name T183

Base pairs 789

T290, T313

330

*T364

706

T378

389

T265

350

T284

605

T253

362

T26

264

*T174

315

T244

304

T180, T298

404

*T143

186

*T151, T295

281

T120, T139, T142 317

T124

382

Nearest homolog Lycopersicon esculentum clone 113819F, mRNA sequence Populus trichocarpa predicted protein, mRNA PREDICTED: hypothetical protein [Vitis vinifera] PREDICTED: Vitis vinifera hypothetical protein LOC100248166 (LOC100248166), mRNA Solanum lycopersicum cDNA, clone: LEFL1090AD06, HTC in leaf Solanum lycopersicum cDNA, clone: LEFL1097CH09, HTC in leaf Sorghum bicolor hypothetical protein, mRNA Vitis vinifera, whole genome shotgun sequence, contig VV78X145709.7, clone ENTAV 115 Arabidopsis thaliana GAE6 (UDP-D-GLUCURONATE 4-EPIMERASE 6), catalytic Gossypium hirsutum trans-2enoyl-CoA reductase (ECR2) mRNA, complete cds Ipomoea batatas soluble acid invertase Ib2FRUCT3 (Ibbfruct3) mRNA, complete cds Long-chain-fatty-acid—CoA ligase family protein/long-chain acyl-CoA synthetase family protein (LACS8) [Arabidopsis thaliana] Long-chain-fatty-acid—CoA ligase family protein/long-chain acyl-CoA synthetase family protein (LACS8) [Arabidopsis thaliana] Lupinus luteus mRNA for putative metallophosphatase (ppd2 gene) Nicotiana glutinosa NGR2 mRNA for RNase NGR2, complete cds

FUN. CAT.a 0

Score Acc. 0 BT012803.1 4e31 4e16 1e46

XM_002330046.1 0

2e73

AK325009.1

0

5e59

AK325542.1

0

1e20 1e28

XM_002456021.1 0 AM480356.1

0

4e39

NP_189024

1

2e55

EU001743.1

1

2e167

AY037938.2

1

3e16

NP_178516.1

1

1e30

NP_178516.1

1

6e80

AJ421010.1

1

4e64

AB032256.1

1

XP_002277015.1

0

XM_002263937.1 0

(continued)

8 Differences of Cd-Induced Gene Expressions Between Low- and High-Cd. . .

157

Table 8.2 (continued) SSH Clone Name T300

Base pairs 240

T221, T311, T358, 333 T412 T175

332

T279, T287

188

T266

525

T16

219

T243

461

T105, T129, T133, 249 T192, T219, T222, T269, T275, T283, T302, T327, T344, T361, T366, T385, T391, T414 T211 605

T281

467

T179

364

T262

312

T272

241

Nearest homolog Nicotiana tabacum sterol-C5 (6)-desaturase homolog mRNA, complete cds Solanum lycopersicum ext mRNA for endo-xyloglucan transferase, complete cds Betula pendula mRNA for ribulose-1,5-bisphosphate carboxylase (rbcS gene) Betula pendula mRNA for ribulose-1,5-bisphosphate carboxylase (rbcS gene) Capsicum annuum mRNA for chloroplast ferredoxin-NADP+ oxidoreductase precursor (fnr gene) Ipomoea aquatica ribulose-1,5bisphosphate carboxylase/ oxygenase large subunit (rbcL) gene, partial cds; chloroplast gene for chloroplast product Ipomoea aquatica ribulose-1,5bisphosphate carboxylase/ oxygenase large subunit (rbcL) gene, partial cds; chloroplast gene for chloroplast product Ipomoea batatas rubisco activase (rca) mRNA, complete cds

Score Acc. 1eAF099969.1 42

Ipomoea batatas rubisco activase (rca) mRNA, complete cds Ipomoea batatas rubisco activase (rca) mRNA, complete cds Ipomoea nil CAB-like protein mRNA, complete cds Ipomoea nil mRNA for non-photosynthetic ferredoxin, complete cds Lycopersicon esculentum ascorbate free radical reductase (AFRR), complete cds

FUN. CAT.a 1

3e83

D16456.1

1

8e52

Y07779.1

2

5e33

Y07779.1

2

8e172

AJ250378.1

2

3e107

AY100958.1

2

0

AY100958.1

2

3e107

EU287993.1

2

6e108

EU287993.1

2

5e108

EU287993.1

2

3e90 1e63

AY547298.1

2

AB038037.1

2

L41345.1

2

2e71

(continued)

158

B. Huang et al.

Table 8.2 (continued) SSH Clone Name T146

Base pairs 316

T291, T307, T326, 342 T386

T212

378

T215, T371

269

T106, T110, T203, 307 T278, T301, T336, T392 T382 645

T132, T334

305

T108

294

T185

501

T188, T255

523

T317

440

T114, T125, T138, 228 T150, T163, T197, T214, T232, T274, T282, T304, T322, T328, T346, T357

Nearest homolog Musa acuminata chloroplast ribulose-1,5-bisphosphate carboxylase/oxygenase small subunit (rbcS-Ma5) gene, complete cds; nuclear gene for chloroplast product Musa acuminata chloroplast ribulose-1,5-bisphosphate carboxylase/oxygenase small subunit (rbcS-Ma5) gene, complete cds; nuclear gene for chloroplast product Oryza sativa Japonica Group mRNA for cytochrome C, complete cds Solanum tuberosum clone 154D06 fructose-bisphosphate aldolase-like mRNA, complete cds Zea mays clone 1695472 ferredoxin-1 mRNA, complete cds Zea mays clone 1695472 ferredoxin-1 mRNA, complete cds Pisum sativum mRNA for Ftshlike protease (ftsh11 gene) Japanese morning glory high mobility group protein mRNA sequence Solanum tuberosum clone 145H06 putative 60S ribosomal protein L7-like protein mRNA, complete cds Solanum tuberosum EF-1-alpha mRNA for Elongation factor 1-alpha, complete cds Arabidopsis thaliana CSN complex subunit 7ii (CSN7) mRNA, complete cds, alternatively spliced Lotus japonicus ubiquitin mRNA, complete cds

Score Acc. 8eDQ088101.1 28

FUN. CAT.a 2

1e45

DQ088101.1

2

1e52

D12634.1

2

3e63

DQ235169.1

2

5e43

EU958479.1

2

1e42

EU958479.1

2

5e68 2e111

AJ786652.1

3

L12169.1

4

6e100

DQ294270.1

5

0

AB061263.1

5

5e89

AF395066.1

6

2e76

DQ249171.1

6

(continued)

8 Differences of Cd-Induced Gene Expressions Between Low- and High-Cd. . .

159

Table 8.2 (continued) SSH Clone Name T17, T400

Base pairs 519

T126

758

T24, T166, T207, 400 T261, T370, T380, T393, T413 T156, T303 394

T218,T259

402

T324

443

T22, T149, T167, 198 T169, T194, T229, T236, T332 T173

457

T337

290

T102, T136, T160, 381 T162, T190, T224, T225, T238, T247, T254, T268, T286, T330, T345, T351 T242 635

QG6, QG65

321

QG95

407

QG67

99

QG21, QG26

398

FUN. CAT.a 6

Nearest homolog Nicotiana tabacum partial mRNA for putative beta7 proteasome subunit (β7 gene) Populus trichocarpa f-box family protein, mRNA Populus trichocarpa f-box family protein, mRNA

Score Acc. 8eAJ291743.1 118 5e48 3e47

XM_002320135.1 6

Capsicum chinense mRNA for putative multidrug resistanceassociated protein, complete cds Populus trichocarpa cationic amino acid transporter (PtrCAT9), mRNA Populus trichocarpa predicted protein, mRNA (protontransporting two-stor ATPase complex) Arabidopsis thaliana RhoGTPase-activating proteinrelated (AT4G35750) mRNA, complete cds Nicotiana tabacum callusexpressing factor (CEF1) mRNA, complete cds Nicotiana tabacum wound inducive mRNA, complete cds Solanum tuberosum temperature-induced lipocalin (TIL) mRNA, complete cds

3e116

AB372261.1

3e53

XM_002302454.1 7

8e99

XM_002319212.1 7

8e24

NM_119741.2

10

4e26

AY286010.1

11

4e44 5e93

AB009885.1

11

DQ222995.1

11

Solanum tuberosum temperature-induced lipocalin (TIL) mRNA, complete cds Solanum lycopersicum cDNA, clone: LEFL1020AG12, HTC in leaf Solanum lycopersicum cDNA, clone: FC03DG05, HTC in fruit Oryza sativum mitochondrial ribulose bisphosphate carboxylase/oxygenase (rbcS) mRNA Musa cuminate chloroplast (dessert banana) ribulose-1,5bisphosphate carboxylase/ oxygenase small subunit (rbcSMa5) gene

2e77

DQ222995.1

11

1e69

AK247433.1

0

1e51 9e25

AK246209.1

0

L22155.1

2

1e45

DQ088101.1

2

XM_002320135.1 6

7

(continued)

160

B. Huang et al.

Table 8.2 (continued) SSH Clone Name QG13

Base pairs 584

QG19

363

QG75

205

QG68

522

*QG81

195

*QG33

184

QG93

388

QG71

307

QG31, QG53, QG83

266

*QG5

372

TG41

416

TG97

364

TG96

456

TG140

256

TG37

405

*TG55

268

*TG148

325

*TG51

231

*TG141

286

Nearest homolog Betula pendula mRNA for ribulose-1,5-bisphosphate carboxylase (rbcS gene) Fragaria x ananassa mRNA for histone H4 Nicotiana tabacum histone H3.3-like mRNA, Solanum tuberosum ribosomal protein S27-like protein mRNA Arabidopsis thaliana AGT (Alanine:glyoxylate aminotransferase) Arabidopsis thaliana 40S ribosomal protein S21 (RPS21B) N.tabacum mRNA for aquaporin 1 Oryza sativa anti-disease protein 1 (ADI1) mRNA Ipomoea batatas metallothionein-like protein (SPMT) mRNA Arabidopsis thaliana ATGSTU8 Glutathionetransferase (class tau) Lycopersicon esculentum clone 133449R Solanum lycopersicum cDNA, clone: FC11CH07, HTC in fruit Solanum lycopersicum genomic DNA, chromosome 8, clone: C08HBa0251H04, Solanum lycopersicum cDNA, clone: FC02AD07, HTC in fruit Solanum tuberosum mRNA for 4-alpha-glucanotransferase precursor (dpeP gene) Arabidopsis thaliana family II extracellular lipase 1 (EXL1) Arabidopsis thaliana family II extracellular lipase 1 (EXL1), Arabidopsis thaliana SPS2 (Solanesyl diphosphate synthase 2); dimethylallyltranstransferase Arabidopsis thaliana ATP binding/damaged DNA binding

Score Acc. 8eY07779.1 87

FUN. CAT.a 2

9e90 8e62 7e81 4e25

AB197150.1

3

EF051133. 1

3

DQ191664.1

5

NP_178969

5

3e10 9e21 3e44 3e100

NP_190957

5

Y08161.1

7

AY072818.1

11

AF242374.1

11

2e17

NP_187538

11

1e94 4e81 1e32

BT014247.1

0

AK246469.1

0

AP009287.1

0

6e65 2e111

AK246158.1

0

X68664.1

1

1e25 5e36 4e29

NP_565120

1

NP_565120

1

NP_173148

2

1e12

NP_180196

3 (continued)

8 Differences of Cd-Induced Gene Expressions Between Low- and High-Cd. . .

161

Table 8.2 (continued) SSH Clone Name TG63

Base pairs 616

TG128, TG109

383

TG136

580

*TG135

456

TG106

211

*TG52

332

TG142

625

Nearest homolog Convolvulus arvensis 26S ribosomal RNA gene Convolvulus arvensis 26S ribosomal RNA gene Solenostemon scutellarioides CBS domain-containing protein mRNA Arabidopsis thaliana serine carboxypeptidase S28 family protein Coffea canephora sugar transport protein (STP1) mRNA Arabidopsis thaliana protein binding/zinc ion binding Ipomoea batatas metallothionein-like protein (SPMT) mRNA

Score Acc. 0 AF479176.1

FUN. CAT.a 5

0

AF479176.1

5

3e80

EF076754.1

6

7e53

NP_850050

6

5e46 9e45 7e158

DQ842236.1

7

NP_564218

7

AF242374.1

11

Notes: QG the gradient Cd treatment library of cv. QLQ, TG, the gradient Cd treatment library of T308 *From BLASTX, the E-value