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A predictive model for arsenic accumulation in rice grains based on bioavailable arsenic and soil characteristics
Yao, Bao-Min; Chen, Peng; Zhang, Hong-Mei; Sun, Guo-Xin
2021-06-15
Source PublicationJOURNAL OF HAZARDOUS MATERIALS
ISSN0304-3894
Volume412Pages:-
AbstractArsenic (As) is a well-known human carcinogen, and rice consumption is the main way Chinese people are exposed to As. In this study, 14 kinds of paddy soils were collected from the main rice-producing areas in China. The results showed that rice roots and leaves accumulated more As than stems and grains in the following sequence: Asroot Asleaf > Asstem > Asgrain. The accumulation of As by rice grains mainly depends on the total As and bioavailable As (0.43 mol/L HNO3 extractable As), which explained 32.2% and 22.2% of the variation in the grain As, respectively. In addition, soil pH, organic matter (OM) and clay contents were the major factors affecting grain As, explaining 13.1%, 7.9% and 5.3% of the variation, respectively. An effective prediction model was established via multiple linear regression as Asgrain = 0.024 BAs - 0.225 pH + 0.013 OM + 0.648 EC - 0.320 TN - 0.088 TP - 0.002 AS + 2.157 (R2 = 0.68, P < 0.01). Through the verification of the samples from both pot experiments and paddy fields, the model successfully provided accurate predictions for rice grain As.
Department城市与区域生态国家重点实验室
KeywordRice Bioavailable arsenic (As) Transfer factor Prediction models
WOS Research AreaEngineering, Environmental ; Environmental Sciences
Document Type期刊论文
Identifierhttps://ir.rcees.ac.cn/handle/311016/45396
Collection城市与区域生态国家重点实验室
Affiliation1.Chinese Acad Sci, Res Ctr Ecoenvironm Sci, State Key Lab Urban & Reg Ecol, Beijing 100085, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Jiaxing Acad Agr Sci, Xiuzhou Dist 314016, Jiaxing, Peoples R China
Recommended Citation
GB/T 7714
Yao, Bao-Min,Chen, Peng,Zhang, Hong-Mei,et al. A predictive model for arsenic accumulation in rice grains based on bioavailable arsenic and soil characteristics[J]. JOURNAL OF HAZARDOUS MATERIALS,2021,412:-.
APA Yao, Bao-Min,Chen, Peng,Zhang, Hong-Mei,&Sun, Guo-Xin.(2021).A predictive model for arsenic accumulation in rice grains based on bioavailable arsenic and soil characteristics.JOURNAL OF HAZARDOUS MATERIALS,412,-.
MLA Yao, Bao-Min,et al."A predictive model for arsenic accumulation in rice grains based on bioavailable arsenic and soil characteristics".JOURNAL OF HAZARDOUS MATERIALS 412(2021):-.
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