RESUMEN
Speciation of Cd in soil solutions strongly determines the fate of this toxic metal in the environment. Generally, in soil solutions, Cd predominantly binds to the dissolved organic matter (DOM). The determination of the quantity and reactivity of DOM that actually complexes Cd in soil solutions is challenging for operational purposes. Therefore, this study tested whether Cd2+ concentration in soil solutions could effectively be predicted by considering complexation with a single mean organic ligand assumed to be a fraction of DOM of unspecified nature or assumed to be purely fulvic acids (FA) with reactivity as described in WHAM VII. The reactivity of the unspecified ligand and the concentration of FA were modelled and fitted to experimental data from 76 agricultural soils with low Cd contents. The optimal reactivity and FA concentration that minimized the relative error (RE) of predictions of the concentration of Cd2+ in soil solutions were either considered constant across soils or modelled from soil properties by multiple linear regressions (MLR) or random forests (RF), giving 6 models, the predictive value of which was assessed by 10-folds cross-validation. When the reactivity of the mean ligand and the optimal FA concentration were considered constant across soils, the models were biased and 66.9% of predictions had relative errors below a factor of 2. By contrast, if the reactivity of the mean ligand or the optimal FA concentration were allowed to vary with soil characteristics, these performances increased to 95.5%, soil pH being the main predictor and RF being slightly more efficient than MLR. With more than 95% of the relative errors of prediction below a factor of 2, the models developed in this work could be valuable for assessing Cd speciation in the solution of soils having a low Cd content.
RESUMEN
Regulatory limits on cadmium (Cd) content in food products are tending to become stricter, especially in cereals, which are a major contributor to dietary intake of Cd by humans. This is of particular importance for durum wheat, which accumulates more Cd than bread wheat. The contamination of durum wheat grain by Cd depends not only on the genotype but also to a large extent on soil Cd availability. Assessing the phytoavailability of Cd for durum wheat is thus crucial, and appropriate methods are required. For this purpose, we propose a statistical model to predict Cd accumulation in durum wheat grain based on soil geochemical properties related to Cd availability in French agricultural soils with low Cd contents and neutral to alkaline pH (soils commonly used to grow durum wheat). The best model is based on the concentration of total Cd in the soil solution, the pH of a soil CaCl2 extract, the cation exchange capacity (CEC), and the content of manganese oxides (Tamm's extraction) in the soil. The model variables suggest a major influence of cadmium buffering power of the soil and of Cd speciation in solution. The model successfully explains 88% of Cd variability in grains with, generally, below 0.02 mg Cd kg-1 prediction error in wheat grain. Monte Carlo cross-validation indicated that model accuracy will suffice for the European Community project to reduce the regulatory limit from 0.2 to 0.15 mg Cd kg-1 grain, but not for the intermediate step at 0.175 mg Cd kg-1. The model will help farmers assess the risk that the Cd content of their durum wheat grain will exceed regulatory limits, and help food safety authorities test different regulatory thresholds to find a trade-off between food safety and the negative impact a too strict regulation could have on farmers.
