| Abstrakt: |
The aim of this article is to provide a unified analytical methodology that allows the determination of 181 pesticides in flowers, leaves and tree trunks, in compliance with the current legislation in Europe. Most of these commodities are not included in the regulation and do not have established a maximum residue limit as many of them are not edible. Moreover, the analysis of pesticides of these commodities is very important to evaluate the exposure of phytosanitary products on plants throughout their life. The present study was performed over 7 years, allowing the creation of a database of Catalan agricultural production capable of providing a global perspective on the use of phytosanitary products in crops before harvest and to evaluate their sustainable use. During this study, 590 samples were analysed, of which 77% reported positive results, with an average of two positive pesticides per sample. To determine these different pesticides, a multi-residue analysis method was developed, where the different matrix group products were divided into different subgroups, according to their composition, in order to be able to quantify them more efficiently. The pesticides were extracted using a modified QuEChERS protocol. On the one hand, for trunks, a generic clean-up process was introduced, which allows the elimination of the principal interferences; additionally, for leaves, this clean-up process also contains active carbon that allows the elimination of chlorophylls, which reduces the matrix effect. On the other hand, a freezing step was introduced in addition to a clean-up process for fats, which allows the elimination of waxes present in flowers. Finally, the resultant extracts were analysed by liquid and gas chromatography coupled to a triple quadrupole mass spectrometer. This methodology was validated in accordance with the standards described in the SANTE/11312/2021 guidelines, achieving a good level of sensitivity and selectivity at the limits of quantification. In addition, excellent accuracy was also achieved with recoveries between 70 and 120% and good precision with relative standard deviation below 20%, as well as excellent linearity. [ABSTRACT FROM AUTHOR] |
Full text from SpringerLink