Predictive statistical modelling of cadmium content in durum wheat grain based on soil parameters

Abstract

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.

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