Yang Hua, Li Zhaojun, Lu Lu, Long Jian, Liang Yongchao
Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Key Laboratory of Plant Nutrition and Fertilizer, Ministry of Agriculture, Beijing, China ; Guizhou Key Laboratory of Mountain Environment, Guizhou Normal University, Guiyang, China.
PLoS One. 2013 Dec 6;8(12):e80855. doi: 10.1371/journal.pone.0080855. eCollection 2013.
Cadmium (Cd) is a highly toxic heavy metal for both plants and animals. The presence of Cd in agricultural soils is of great concern regarding its transfer in the soil-plant system. This study investigated the transfer of Cd (exogenous salts) from a wide range of Chinese soils to corn grain (Zhengdan 958). Through multiple stepwise regressions, prediction models were developed, with the combination of Cd bioconcentration factor (BCF) of Zhengdan 958 and soil pH, organic matter (OM) content, and cation exchange capacity (CEC). Moreover, these prediction models from Zhengdan 958 were applied to other non-model corn species through cross-species extrapolation approach. The results showed that the pH of the soil was the most important factor that controlled Cd uptake and lower pH was more favorable for Cd bioaccumulation in corn grain. There was no significant difference among three prediction models in the different Cd levels. When the prediction models were applied to other non-model corn species, the ratio ranges between the predicted BCF values and the measured BCF values were within an interval of 2 folds and close to the solid line of 1∶1 relationship. Furthermore, these prediction models also reduced the measured BCF intra-species variability for all non-model corn species. Therefore, the prediction models established in this study can be applied to other non-model corn species and be useful for predicting the Cd bioconcentration in corn grain and assessing the ecological risk of Cd in different soils.
镉(Cd)对动植物而言都是一种剧毒重金属。农业土壤中镉的存在,因其在土壤 - 植物系统中的迁移而备受关注。本研究调查了多种中国土壤中镉(外源盐)向玉米籽粒(郑单958)的迁移情况。通过多元逐步回归,结合郑单958的镉生物富集系数(BCF)与土壤pH值、有机质(OM)含量及阳离子交换容量(CEC),建立了预测模型。此外,通过跨物种外推法将郑单958的这些预测模型应用于其他非模式玉米品种。结果表明,土壤pH值是控制镉吸收的最重要因素,较低的pH值更有利于镉在玉米籽粒中的生物累积。在不同镉水平下,三种预测模型之间无显著差异。当将预测模型应用于其他非模式玉米品种时,预测的BCF值与实测的BCF值之比范围在2倍以内,且接近1∶1关系的实线。此外,这些预测模型还降低了所有非模式玉米品种实测BCF的种内变异性。因此,本研究建立的预测模型可应用于其他非模式玉米品种,有助于预测玉米籽粒中的镉生物富集情况,并评估不同土壤中镉的生态风险。