State Key Laboratory for Quality and Safety of Agro-products; Key Laboratory of Information Traceability for Agricultural Products, Institute of Quality and Standard for Agro-products, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China.
College of Agriculture, Hainan University, Haikou, 570228, China.
Environ Sci Pollut Res Int. 2020 May;27(13):14953-14962. doi: 10.1007/s11356-020-07976-1. Epub 2020 Feb 15.
The consumption of rice contaminated with soil cadmium (Cd) threatens human health. It is essential to ensure the production of rice that meets food quality standards. Therefore, a large-scale field survey was conducted in Zhejiang province, southeastern China, to investigate the relationship between Cd accumulation in rice grains and Cd bioavailability in soil, and thus to establish a model to predict Cd contents in rice grains based on soil properties. For this purpose, a total of 156 paired rice and soil samples were collected. Pearson's correlation analysis revealed that Cd measurements obtained by diffusive gradient in thin films (DGT) had a higher correlation (r = 0.818, p < 0.001) with the Cd in rice grains as compared to the Cd measured by the DTPA, CaCl, EDTA, and HCl extraction methods, which indicated that the DGT technique was a reliable method for the assessment of Cd bioavailability in soils. In addition, among the four extraction methods, the DTPA-extractable Cd showed the highest correlation with the Cd contents in rice grains. Therefore, we developed two predictive models (model and model) to predict Cd levels in rice grains via Cubist multivariate mixed linear regression, using "soil DGT-measured Cd, pH, and oxide contents of Ca, Si, and Fe" or "soil DTPA-extractable Cd, pH, OM, and oxide contents of Ca and Fe" as explanatory variables, respectively. The overall model and model had R values of 0.95 and 0.93, respectively, and relative error values of 0.30 and 0.33, respectively. Simple correlation analysis showed direct and close relationships between the measured Cd in rice grains and the Cd concentrations predicted by the Cubist model and model, with R values of 0.979 and 0.922, respectively. Therefore, Cd levels in rice grains could be predicted very well based on the two prediction models, and thus, the two models derived in this study are effective in identifying soils in which the Cd in rice grains will exceed food safety standards, thereby helping to ensure safe rice production.
食用受土壤镉（Cd）污染的大米会威胁到人类健康。确保生产符合食品质量标准的大米至关重要。因此，在中国东南部的浙江省进行了大规模的田间调查，以研究稻米中镉积累与土壤中镉生物有效性之间的关系，并建立基于土壤特性预测稻米中镉含量的模型。为此，共采集了 156 对水稻和土壤样品。Pearson 相关分析表明，与 DTPA、CaCl2、EDTA 和 HCl 提取方法相比，扩散梯度薄膜（DGT）测量的 Cd 与稻米中 Cd 的相关性更高（r=0.818，p<0.001），这表明 DGT 技术是一种可靠的评估土壤中 Cd 生物有效性的方法。此外，在这四种提取方法中，DTPA 可提取的 Cd 与稻米中 Cd 含量的相关性最高。因此，我们通过 Cubist 多元混合线性回归，使用“土壤 DGT 测量的 Cd、pH 值以及 Ca、Si 和 Fe 的氧化物含量”或“土壤 DTPA 可提取的 Cd、pH 值、OM 和 Ca 和 Fe 的氧化物含量”作为解释变量，分别建立了两个预测模型（模型和模型）来预测稻米中 Cd 含量。总体模型和模型的 R 值分别为 0.95 和 0.93，相对误差值分别为 0.30 和 0.33。简单相关分析表明，稻米中实测 Cd 与 Cubist 模型和模型预测的 Cd 浓度之间存在直接且密切的关系，R 值分别为 0.979 和 0.922。因此，基于这两个预测模型，可以很好地预测稻米中 Cd 的含量，因此，本研究中得出的这两个模型可以有效地识别稻米中 Cd 含量超过食品安全标准的土壤，从而有助于确保安全的稻米生产。
