Adams M L, Zhao F J, McGrath S P, Nicholson F A, Chambers B J
Agriculture and Environment Division, Rothamsted Research, Harpenden, Hertfordshire AL5 2JQ, UK.
J Environ Qual. 2004 Mar-Apr;33(2):532-41. doi: 10.2134/jeq2004.5320.
The entry of Cd into the food chain is of concern as it can cause chronic health problems. To investigate the relationship between soil properties and the concentration of Cd in wheat (Triticum aestivum L.) and harley (Hordeum vulgare L.) grain, we analyzed 162 wheat and 215 barley grain samples collected from paired soil and crop surveys in Britain, and wheat and barley samples from two long-term sewage sludge experiments. Cadmium concentrations were much lower in barley grain than in wheat grain under comparable soil conditions. Multiple regression analysis showed that soil total Cd and pH were the significant factors influencing grain Cd concentrations. Significant cultivar differences in Cd uptake were observed for both wheat and barley. Wheat grain Cd concentrations could be predicted reasonably well from soil total Cd and pH using the following model: log(grain Cd) = a + b log(soil Cd) - c(soil pH), with 53% of the variance being accounted for. The coefficients obtained from the data sets of the paired soil and crop surveys and from long-term sewage sludge experiments were similar, suggesting similar controlling factors of Cd bioavailability in sludge-amended or unamended soils. For barley, the model was less satisfactory for predicting grain Cd concentration (22% of variance accounted for). The model can be used to predict the likelihood of wheat grain Cd exceeding the new European Union (EU) foodstuff regulations on the maximum permissible concentration of Cd under different soil conditions, particularly in relation to the existing Directive and the proposed new Directive on land applications of sewage sludge.
镉进入食物链令人担忧，因为它会导致慢性健康问题。为了研究土壤性质与小麦（Triticum aestivum L.）和大麦（Hordeum vulgare L.）籽粒中镉浓度之间的关系，我们分析了从英国配对的土壤和作物调查中采集的162个小麦籽粒样本和215个大麦籽粒样本，以及来自两项长期污水污泥实验的小麦和大麦样本。在可比的土壤条件下，大麦籽粒中的镉浓度远低于小麦籽粒中的镉浓度。多元回归分析表明，土壤总镉和pH值是影响籽粒镉浓度的重要因素。在小麦和大麦中均观察到镉吸收存在显著的品种差异。利用以下模型可以根据土壤总镉和pH值较好地预测小麦籽粒中的镉浓度：log(籽粒镉)=a + b log(土壤镉)-c(土壤pH值)，该模型解释了53%的方差。从配对的土壤和作物调查数据集以及长期污水污泥实验中获得的系数相似，这表明在施用或未施用污泥的土壤中，镉生物有效性的控制因素相似。对于大麦，该模型在预测籽粒镉浓度方面不太令人满意（解释了22%的方差）。该模型可用于预测在不同土壤条件下，特别是与现有指令以及关于污水污泥土地应用的拟议新指令相关的情况下，小麦籽粒镉含量超过欧盟关于镉最大允许浓度的新食品法规的可能性。
