Abstract
Abstract. A predictive model of metal concentrations in crops was developed to optimize soil liming and sludge application strategies at a dedicated sewage sludge disposal site. Predictions of metal concentrations in plant tissue were derived from measured values of soil metal concentration, humus content and soil pH. The plant and soil data used to parameterize the model were collected on site using quadrat sampling of mature crop and underlying topsoil. The uptake model was used to map predicted metal concentrations in wheat grain and forage maize based upon a database of soil characteristics (metal content, % humus and pH) measured as part of a routine geochemical survey of the site. The effect of a management strategy to modify uptake of Cd by wheat by changing soil pH was investigated. The effect of soil dust adhering to maize plants at harvest was also simulated to investigate the importance of this pathway for Cd transfer to animal feed such as silage.The model gave satisfactory predictions for uptake of Cd and Zn but less useful simulations for Pb, Cu and Ni. The results for Cd uptake showed a greater dependence on soil pH in the case of wheat in comparison to maize. It is suggested that, for the study site, liming to pH 7.0 will reduce Cd concentrations in wheat grain to within EC legal standards. However the Cd content of maize may still exceed these guidelines, with a relatively minor contribution from contamination with soil dust.
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