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研究水果和蔬菜中农药残留的分析数据与当地气候条件的相关性。

Investigating the correlation of analytical data on pesticide residues in fruits and vegetables with local climatic condition.

机构信息

Food Informatics, University of Hohenheim, Fruwirthstraße 21, Stuttgart, 70599, BW, Germany; Computational Science Hub, University of Hohenheim, Schloss, Stuttgart, 70599, BW, Germany.

Food Informatics, University of Hohenheim, Fruwirthstraße 21, Stuttgart, 70599, BW, Germany.

出版信息

Environ Res. 2024 Jul 1;252(Pt 1):118743. doi: 10.1016/j.envres.2024.118743. Epub 2024 Mar 26.

Abstract

The use of pesticides is increasing steadily, and even though pesticides are essential for food security, they are known for having adverse effects on human health, and the environment. Further, as pesticides are often a reaction to pests, which are influenced by environmental conditions, the environment might influence the use of pesticides-when assuming, that the use is optimized, and adjusted to those conditions. Therefore, it would be helpful to know how environmental conditions influence the pesticide residue levels of fruits and vegetables. In this work, we investigated the correlation between residue levels of ten different pesticides and the weather parameters air temperature, maximum and minimum temperature, wind speed, precipitation, and sun hours using the Pearson correlation coefficient, linear, and polynomial regression. Also, the pesticide residue levels were analyzed regarding outliers. No correlation between the measured residue levels and the weather parameters could be found for most pesticides. However, for Acetamiprid and Fluopyram, a slight correlation between the pesticide residue levels, the air, minimum-, and maximum temperature could be found. The polynomial regression model was better suited to describe the relationship between pesticide residue levels and weather parameters than the linear regression model, but R was not higher than 0.069 for any model.

摘要

农药的使用量正在稳步增加,尽管农药对于食品安全至关重要,但它们对人类健康和环境也有不良影响。此外,由于农药通常是针对受环境条件影响的害虫而使用的,因此环境可能会影响农药的使用——假设使用已优化并根据这些条件进行了调整。因此,了解环境条件如何影响水果和蔬菜中的农药残留水平将很有帮助。在这项工作中,我们使用 Pearson 相关系数、线性和多项式回归研究了十种不同农药的残留水平与空气温度、最高和最低温度、风速、降水和日照时间等气象参数之间的相关性。此外,还针对异常值分析了农药残留水平。对于大多数农药,未发现测量的残留水平与气象参数之间存在相关性。然而,对于乙虫脒和氟吡菌胺,发现农药残留水平与空气、最低和最高温度之间存在轻微相关性。与线性回归模型相比,多项式回归模型更适合描述农药残留水平与气象参数之间的关系,但任何模型的 R 都不高于 0.069。

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