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共存重金属对土壤向小麦籽粒中镉迁移转化的可变影响。

Changeable effects of coexisting heavy metals on transfer of cadmium from soils to wheat grains.

机构信息

Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education), School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, China.

Key Laboratory of Heavy-metal Pollution Monitoring and Remediation of Henan Province, Jiyuan 459000, China.

出版信息

J Hazard Mater. 2022 Feb 5;423(Pt B):127182. doi: 10.1016/j.jhazmat.2021.127182. Epub 2021 Sep 12.

DOI:10.1016/j.jhazmat.2021.127182
PMID:34537640
Abstract

Cadmium (Cd) and other heavy metals usually coexist in soils. Effects of coexisting heavy metals on the accumulation and transfer of Cd in field soils by wheat remain poorly understood. Here we revealed changeable effects of coexisting Pb, Zn and Cu on the Cd transfer from soils to wheat grains. Soil burdens of Cd were found to exhibit positive correlations (r = 0.459-0.946) with those of coexisting Pb, Zn and Cu (particularly Pb). Effects of three coexisting metals on to the uptake of Cd by wheat varied in the directions and/or extents with types of metals and transfer processes of Cd. Coexisting Zn inhibited the uptake of Cd by wheat grains to higher extent than Pb and Cu. Soil Zn, along with soil Cd, soil pH and soil Ca, was used to construct the predictive model of grain Cd (R = 0.868). External verifications of the model on 572 datasets of large representation performed well. The predictive accuracy was about 54%, 73% and 89% for a factor of 1, 2 and 5 above and below the ideal fit, respectively. This finding has practical interest in risk assessments and remediation measures of Cd-contaminated soil sites in regional scales.

摘要

镉(Cd)和其他重金属通常共存于土壤中。然而,共存重金属对田间土壤中小麦吸收和转运 Cd 的影响仍知之甚少。本研究揭示了共存 Pb、Zn 和 Cu 对土壤中 Cd 向小麦籽粒转移的可变影响。研究发现,土壤 Cd 负荷与共存 Pb、Zn 和 Cu(尤其是 Pb)的负荷呈正相关(r = 0.459-0.946)。三种共存金属对小麦吸收 Cd 的影响在方向和/或程度上因金属类型和 Cd 的转移过程而异。共存 Zn 比 Pb 和 Cu 更能抑制小麦籽粒对 Cd 的吸收。土壤 Zn 与土壤 Cd、土壤 pH 值和土壤 Ca 一起,被用于构建籽粒 Cd 的预测模型(R = 0.868)。对具有代表性的 572 组数据集进行的外部验证表明,该模型的预测精度在理想拟合上下 1、2 和 5 倍的因子范围内分别约为 54%、73%和 89%。这一发现对于区域尺度上 Cd 污染土壤场地的风险评估和修复措施具有实际意义。

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