中文关键词复垦土壤玉米硒富集特征重金属拮抗效应 英文关键词reclaimed soilmaizeseleniumenrichment characteristicsheavy metalsantagonistic effect

作者	单位	E-mail
尹炳	安徽理工大学地球与环境学院, 淮南 232001	1741514351@qq.com
汪建飞	安徽理工大学地球与环境学院, 淮南 232001 安徽科技学院资源与环境学院, 滁州 233100
师胜	安徽科技学院资源与环境学院, 滁州 233100
卜中原	安徽理工大学地球与环境学院, 淮南 232001
霍天满	安徽科技学院资源与环境学院, 滁州 233100
张世文	安徽理工大学地球与环境学院, 淮南 232001	mamin1190@126.com

中文摘要 针对矿业废弃地复垦土壤硒与重金属"双高"现象，为充分开发其富硒土地资源，确保作物安全，本文基于"点对点"采集的土壤和玉米样品，利用反距离权重（inverse distance weighted，IDW）、多元线性回归（multiple linear regression，MLR）、偏最小二乘回归（partial least squares regression，PLSR）和随机森林回归（random forest regression，RFR）等方法，开展了西南某硫磺矿复垦区玉米硒元素吸收预测的同时，分析硒（Se）对重金属（Hg、As、Cd和Cr）的拮抗效应.结果表明研究区土壤中硒资源丰富，土壤Se平均含量达到0.83mg·kg^-1，是中国土壤Se平均含量的2.87倍，玉米籽粒硒含量处于0.02~0.16mg·kg^-1之间.由相关性分析和模型预测可知，研究区玉米籽粒硒含量主要影响因素为土壤硒、pH值、有机质和重金属As等，多元线性回归（MLR）对其预测最为有效，决定系数R²为0.52.通过比较研究区土壤硒不同含量梯度下玉米对重金属（Hg、As、Cd和Cr）富集特性，表明了土壤Se对重金属Hg、As、Cd和Cr存在一定的拮抗作用.本研究结果可为今后同类矿业废弃地复垦土地发展特色富硒农业提供依据. 英文摘要 To fully exploit selenium-rich land resources and ensure crop safety, the phenomenon of "double high" of Se and heavy metals in reclaimed soil of mining wasteland was studied. Soil and maize samples collected from "point-to-point" were weighted by the inverse distance weighted (IDW) method; multiple linear regression (MLR), partial least squares regression (PLSR), random forest regression (RFR), and other methods were used to predict selenium uptake by maize in a sulfur mine reclamation area in southwest China. Meanwhile, the antagonistic effects of selenium (Se) on heavy metals (Hg, As, Cd, and Cr) were analyzed. The results showed that the soil in the study area was rich in selenium resources. The average Se content in the soil reached 0.83 mg·kg^-1, which was 2.87 times that of the average Se content in Chinese soil. The Se content in maize grains ranged from 0.02 mg·kg^-1 to 0.16 mg·kg^-1. According to correlation analysis and model prediction, the main influencing factors of selenium content in maize grains in the study area were soil selenium, pH value, organic matter, and heavy metal As. Multivariate linear regression (MLR) was the most effective method for predicting selenium content in maize grains, and the determinant coefficient R² was 0.52. By comparing the enrichment characteristics of maize to heavy metals (Hg, As, Cd, and Cr) under different concentration gradients of Se in the soil of the study area, the results showed that Se had antagonistic effects on Hg, As, Cd, and Cr. The results can provide a basis for the development of selenium-rich agriculture in similar mining wasteland reclamation in the future.

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