title: Prediction models for transfer of arsenic from soil to corn grain (Zea mays L.).
abstract: In this study, the transfer of arsenic (As) from soil to corn grain was investigated in 18 soils collected from throughout China. The soils were treated with three concentrations of As and the transfer characteristics were investigated in the corn grain cultivar Zhengdan 958 in a greenhouse experiment. Through stepwise multiple-linear regression analysis, prediction models were developed combining the As bioconcentration factor (BCF) of Zhengdan 958 and soil pH, organic matter (OM) content, and cation exchange capacity (CEC). The possibility of applying the Zhengdan 958 model to other cultivars was tested through a cross-cultivar extrapolation approach. The results showed that the As concentration in corn grain was positively correlated with soil pH. When the prediction model was applied to non-model cultivars, the ratio ranges between the predicted and measured BCF values were within a twofold interval between predicted and measured values. The ratios were close to a 1:1 relationship between predicted and measured values. It was also found that the prediction model (Log [BCF]=0.064 pH-2.297) could effectively reduce the measured BCF variability for all non-model corn cultivars. The novel model is firstly developed for As concentration in crop grain from soil, which will be very useful for understanding the As risk in soil environment.
authors.affiliation: Institute of Agricultural Resources and Regional Planning, Key Laboratory of Plant Nutrition and Fertilizer, Ministry of Agriculture, Chinese Academy of Agricultural Sciences, Beijing, 100081, People's Republic of China.|Guizhou Key Laboratory of Mountain Environment, Guizhou Normal University, Guiyang, 550001, People's Republic of China.
authors.forename: Hua
authors.initials: H
authors.lastname: Yang
authors.affiliation: Institute of Agricultural Resources and Regional Planning, Key Laboratory of Plant Nutrition and Fertilizer, Ministry of Agriculture, Chinese Academy of Agricultural Sciences, Beijing, 100081, People's Republic of China. lizhaojun@caas.cn.
authors.forename: Zhaojun
authors.initials: Z
authors.lastname: Li
authors.affiliation: Guizhou Key Laboratory of Mountain Environment, Guizhou Normal University, Guiyang, 550001, People's Republic of China.
authors.forename: Jian
authors.initials: J
authors.lastname: Long
authors.affiliation: Institute of Agricultural Resources and Regional Planning, Key Laboratory of Plant Nutrition and Fertilizer, Ministry of Agriculture, Chinese Academy of Agricultural Sciences, Beijing, 100081, People's Republic of China.
authors.forename: Yongchao
authors.initials: Y
authors.lastname: Liang
authors.affiliation: Scion, Christchurch, 29-237, New Zealand.
authors.forename: Jianming
authors.initials: J
authors.lastname: Xue
authors.affiliation: Scion, Christchurch, 29-237, New Zealand.
authors.forename: Murray
authors.initials: M
authors.lastname: Davis
authors.affiliation: College of Natural Resources and Environment, Northwest A&F University, Yangling, 712100, People's Republic of China.
authors.forename: Wenxiang
authors.initials: W
authors.lastname: He
mesh_terms: D001151:Arsenic / Q000032:analysis*; D002681:China; D002523:Edible Grain / Q000737:chemistry; D016014:Linear Models; D008962:Models, Theoretical; D012044:Regression Analysis; D012987:Soil / Q000737:chemistry; D012989:Soil Pollutants / Q000032:analysis*; D003313:Zea mays / Q000737:chemistry*
chemical_list: D012987:Soil; D012989:Soil Pollutants; D001151:Arsenic
keywords: Arsenic; BCF; Corn grain; Cross-species extrapolation; Prediction model; Soils