Calliera Maura, Balderacchi Matteo, Capri Ettore, Trevisan Marco
Università Cattolica del Sacro Cuore, Institute of Environmental and Agricultural Chemistry, Plant Chemistry Section, Via Emilia Parmense 84, 29100 Piacenza, Italy.
Pest Manag Sci. 2008 Oct;64(10):981-8. doi: 10.1002/ps.1608.
A 'step-by-step' method was used to develop a simplified procedure for calculating pesticide residue levels on fruit at harvest by considering the application of the compound and the relevant routes of loss. The model is applicable to cases where the most important exposure route is by direct spray to the canopy of the crop and where uptake into the plant by the roots can be disregarded. The exposure dose is calculated by considering the proportion of total crop cover represented by the fruits. The loss processes considered are photodegradation, uptake, volatilization and washoff. The outputs of the model were compared with measured residues of pesticides on pear. Analysis of the model fit demonstrates that the model predicted the measured data with a good level of accuracy for four of seven investigated pesticides. The predicted/observed quotients are close to 1, as is the modelling efficiency, and there are no great differences between the predicted and observed values. Taking into account the extreme simplicity of the model and the complexity of the environmental processes considered, these results encourage further research into the modelling of residue behaviour in food commodities. The objectives of this work were to produce a tool to predict pesticide residues in products of plant origin, to complement monitoring of pesticide levels and to be useful in evaluating the effect of government policies on food safety. All predicted values were below the maximum levels fixed for pesticide residues in pear, as amended in Council Directives 86/362/EEC and 90/642/EEC.
采用“逐步”方法，通过考虑化合物的施用情况和相关损失途径，制定了一种简化程序，用于计算收获时水果上的农药残留水平。该模型适用于最重要的暴露途径是直接喷洒到作物冠层且可忽略根系对农药吸收的情况。通过考虑果实占作物总覆盖面积的比例来计算暴露剂量。所考虑的损失过程包括光降解、吸收、挥发和冲洗。将该模型的输出结果与梨上农药的实测残留量进行了比较。模型拟合分析表明，对于七种被调查农药中的四种，该模型能够以较高的准确度预测实测数据。预测值与观测值的比值接近1，建模效率也是如此，预测值与观测值之间没有很大差异。考虑到该模型极其简单以及所考虑环境过程的复杂性，这些结果鼓励对食品商品中残留行为建模进行进一步研究。这项工作的目标是开发一种工具，用于预测植物源产品中的农药残留，以补充农药水平监测，并有助于评估政府食品安全政策的效果。所有预测值均低于经欧盟理事会第86/362/EEC号和90/642/EEC号指令修订的梨中农药残留最高限量。
