New publication in Environmental Research [10.07.24]
Daniel Einsiedel, Sara-Lena Welk and Christian Krupitzer from the Department of Food Informatics are Co-Authors of the publication "Investigating the correlation of analytical data on pesticide residues in fruits and vegetables with local climatic condition" in Environmental Research (Impact Factor: 7.7).
The publication "Investigating the correlation of analytical data on pesticide residues in fruits and vegetables with local climatic condition" by Daniel Einsiedel (Department of Foodinformatics (150L), and Computational Science Hub (CSH), University of Hohenheim, Stuttgart, Germany) with the co-authors, Sara-Lena Welk (Department of Foodinformatics (150L), University of Hohenheim, Stuttgart, Germany), Nevena Zujko (Tentamus, An d. Industriebahn 5, Berlin, 13088, Berlin, Germany), Yvonne Pfeifer (SGS Germany GmbH, Heidenkampsweg 99, Hamburg, 20097, Hansestadt Hamburg, Germany), Christian Krupitzer (Department of Foodinformatics (150L), and Computational Science Hub (CSH), University of Hohenheim, Stuttgart, Germany) was published in Environmental Research, Elsevier (Impact Factor: 7.7).
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
