Assessing the transfer of Cd and As from co-contaminated soil to peanut (Arachis hypogaea L.): prediction models and soil thresholds.

In China, the co-contamination of soil with cadmium (Cd) and arsenic (As) is one of the most severe forms of combined pollution. Modeling the transfer of Cd and As from co-contaminated soil to crops has not been thoroughly studied. In this study, five soils with significant differences in physicochemical properties were selected to simulate the compound pollution conditions by exogenously adding Cd and As, and the bioaccumulation and translocation behaviors of these two elements were thoroughly investigated. The study used machine learning methods and stepwise linear regression to establish prediction models for the accumulation of Cd and As in peanut plants. The safety thresholds of Cd and As in soil based on food quality standards were then derived. The results demonstrated that peanuts exhibited significantly higher Cd accumulation capacity compared to As, with bioconcentration factors (BCFs) ranging from 0.77 to 36.55 for Cd and 0.006 to 0.449 for As. Cd was mainly translocated to peanut shoots and concentrated aboveground, while As was mainly accumulated in roots. Compared to single Cd contamination, the presence of As increased Cd concentrations in roots, shoots, shells, and kernels by up to 87.5 %, 71.3 %, 120.2 %, and 48.9 %, respectively. Conversely, the presence of Cd reduced As content in roots, shells, and kernels by up to 38.3 %, 45.5 %, and 38.1 %. Using the XGBoost and stepwise linear regression models, key factors influencing the accumulation of Cd and As in plants were identified. Additionally, corresponding regression prediction equations were developed, which explained over 0.66 of the variance in metal accumulation in peanut parts. Our derived soil safety thresholds suggest that contaminant concentrations should be more tightly controlled to reduce health risks in case of mixed contamination. This study provides new insights into soil contamination management and contributes to developing more effective contamination control strategies for co-contaminated soils.