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Predicting As, Cd and Pb uptake by rice and vegetables using field data from China
Authors:Hongzhen Zhang  Yongming Luo  Jing Song  Haibo Zhang  Jiaqi Xia and Qiguo Zhao
Institution:1. Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China; Chinese Academy for Environmental Planning of Ministry of Environmental Protection, Beijing 100012, China
2. Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
3. Nanjing Institute of Environmental Science, Ministry of Environmental Protection, Nanjing 210042, China
Abstract:Plant uptake factor (PUF), single-variable regression of natural log-transformed concentrations in rice grain/vegetables versus natural log-transformed concentrations in soil and multiple-variable regression with soil concentrations and pH, was derived, validated and compared based on the paired crop and soil data collected from studies regarding As, Cd and Pb contaminated croplands in China. Results showed that the median value of PUF did not present deterministic prediction. But after natural logarithm transformation, the PUF followed Gaussian distribution which could be useful in risk assessment. The single-variable regression models were significant for As, Cd and Pb uptake both by rice and vegetables; however, the standard errors of all the regressions were comparatively large. Soil pH as a variable was generally significant but it only contributed positively to model fit for Cd uptake. After model comparison and selection, the upper 95% prediction limits of the multiple regression model for Cd uptake by rice was recommended to calculate screening value of Cd for paddy soil based on the limit for Cd concentration in rice grain.
Keywords:trace elements  regression model  rice  vegetable  plant uptake factor  croplands
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