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Characterizing and estimating pesticide degradation in food crops

机译:粮食作物的特征和估算农药降解

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Background. Dissipation half-lives are an important driver for fate behavior of pesticides in food crops, but also among most uncertain parameters in exposure models. Hence, a proper estimation of half-lives in crops is required, but still not available. Aims. We aimed at providing a consistent framework for estimating pesticide half-lives in food crops for use in modeling approaches applied in human exposure assessments. Methods. We first build a database of 4518 measured pesticide dissipation half-lives, of which 41% have been measured in the last 5 years, mostly in Asia. Second, we determine the influence of temperature using a subset of 1011 data points with reported temperatures. Third, we calculate recommended geomean values of half-lives at 20°C and standard deviations on their log for 330 pesticides and 44 crops, using multiple imputations for missing temperatures. We finally propose a regression-based model to predict half-lives for other pesticides as a function of temperature, substance class, chemical properties and crop type. Results. Temperature is the major determinant of the variability of measured half-lives for a given pesticide. When temperature was also reported, the regression model is able to explain 69% of the variability as a function of crop, temperature and substance. Considering all data available, the model still explains 46% of the variability. Interestingly, the range of recommended geomean half-lives is relatively narrow, with the 2.5th and 97th percentiles across pesticides ranging from 0.9 to 21 days. Results of the predictive model show that when temperature is known, 56% of half-life variability can be explained by temperature, crop type, substance class, Kow and Koc. When substance class and crop are not considered in the model, the R2 is reduced from 0.56 to 0.30 with molecular weight becoming significant. Conclusions. Our research has important implications for human exposure assessment, especially since food crop consumption is the predominant exposure pathway of the general public towards pesticides.
机译:背景。耗散半衰期是粮食作物的农药的命运行为的重要驱动力,而且在曝光模式最不确定的参数之一。因此,半衰期的作物适当的估计是必需的,但仍然无法使用。目标。我们的目的是为在粮食作物估计农药半衰期建模使用人体暴露评估办法应用提供一个统一的框架。方法。我们首先建立4518测量农药消散半衰期,其中41%的人在过去5年中被测量,主要在亚洲的一个数据库。其次,我们确定的温度使用的1011个数据点的子集报道温度的影响。第三,我们计算推荐自己的日志330种农药和作物44在20℃的半衰期和标准偏差的几何平均值,使用多重归因于缺少温度。最后,我们提出了基于回归的模型来预测半衰期为其他农药作为温度的函数,物质类,化学性质和作物类型。结果。测量温度的半衰期为给定的农药变异的主要决定因素。当还报温度,回归模型能够解释变异的69%,作物,温度和物质的功能。考虑到所有可用数据,模型还解释了变异的46%。有趣的是,推荐的几何平均值的半衰期的范围比较窄,并在保持杀虫剂范围从0.9到21天的第2.5和第97百分位数。的预测模型表明,当温度是已知的,半衰期可变性的56%,可通过温度,作物类型,类物质,和水分配系数的Koc解释结果。当物质类别和作物没有在模型中考虑时,R 2选自0.56减小到0.30,分子量变得显著。结论。我们的研究对人类暴露评估的重要意义,尤其是粮食作物消费对农药广大市民的主要照射途径。

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