State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, 163 Xianlin Ave., Nanjing, China.
Technical Innovation Center of Ecological Monitoring & Restoration Project on Land (Arable), Geological Survey of Jiangsu, 100 Zhujiang Rd., Nanjing, China.
J Hazard Mater. 2020 Dec 5;400:123135. doi: 10.1016/j.jhazmat.2020.123135. Epub 2020 Jun 11.
An accurate model to predict Cd accumulation in crops based on soil properties would facilitate evaluations of soil quality and the potential risk posed by metals. However, given the heterogeneity of soil, such models are difficult to establish on large regional scales. This study for the first time examined the applicability of a multi-surface speciation model (MSM) in predicting Cd accumulation in wheat at a regional field scale, based on 140 soil-wheat paired samples collected from a 205-km field. The MSM resulted in a better correlation between Cd accumulation in wheat grain (R = 0.75) and roots (R = 0.74) than obtained with chemical extraction methods (total Cd in soil, 0.01 M CaCl, and 0.43 M HNO). In addition, while the performance of the MSM was comparable to that of a traditional multiple regression model, a parameter-fitting process was not required. The predictive ability of the MSM was further used to assess and predict the soil Cd risk and to develop a soil Cd sensitivity map to better localize areas of greatest sensitivity to Cd contamination. The results showed that the MSM can serve as a useful tool for regional soil risk assessments and thus in the development of soil protection measures.
基于土壤特性建立准确的作物镉积累预测模型，有助于评估土壤质量和金属的潜在风险。然而，由于土壤的异质性，这种模型很难在大区域尺度上建立。本研究首次在 205 公里长的田间采集了 140 对土壤-小麦样本，基于多表面形态模型（MSM），在区域田间尺度上检验了其预测小麦镉积累的适用性。与化学提取方法（土壤中总镉、0.01 M CaCl 和 0.43 M HNO）相比，MSM 使小麦籽粒（R = 0.75）和根系（R = 0.74）中镉积累的相关性更好。此外，虽然 MSM 的性能与传统的多元回归模型相当，但不需要进行参数拟合过程。进一步利用 MSM 的预测能力来评估和预测土壤镉风险，并开发土壤镉敏感性图，以便更好地定位对镉污染最敏感的区域。结果表明，MSM 可以作为区域土壤风险评估的有用工具，从而有助于制定土壤保护措施。
