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Analysis of 181 Pesticides with Multi-residue Method by LC–MS/MS and GC–MS/MS in Flowers, Leaves and Tree Trunks and the Results of Catalan Production from 2014 to 2021

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Abstract

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.

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Data Availability

The data may be available upon request to all laboratories in compliance with the relevant data protection laws.

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Authors and Affiliations

  1. Laboratori Agroalimentari, Generalitat de Catalunya, Departament d’Acció Climàtica, Alimentació i Agenda Rural, Cabrils, Barcelona, Spain

    Laia Sanchez Costa, Judit Pujol Boira, Miriam Aragó Iglesias, Pilar Rodríguez Martínez & Mireia Medina Sala

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  1. Laia Sanchez Costa
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  2. Judit Pujol Boira
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  3. Miriam Aragó Iglesias
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  4. Pilar Rodríguez Martínez
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  5. Mireia Medina Sala
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Laia Sanchez Costa, Judit Pujol Boira, Miriam Aragó Iglesias, Pilar Rodríguez Martínez and Mireia Medina Sala. The first draft of the manuscript was written by Laia Sanchez Costa and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Laia Sanchez Costa.

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The authors declare no competing interests.

Affiliated Institution

This research was performed in the Laboratori Agroalimentari (Agrifood Laboratory) of the Generalitat de Catalunya with the support of its Departament d’Acció Climàtica, Alimentació i Agenda Rural (Department of Climate Action, Food and Rural Agenda).

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Costa, L.S., Boira, J.P., Iglesias, M.A. et al. Analysis of 181 Pesticides with Multi-residue Method by LC–MS/MS and GC–MS/MS in Flowers, Leaves and Tree Trunks and the Results of Catalan Production from 2014 to 2021. Food Anal. Methods 16, 239–251 (2023). https://doi.org/10.1007/s12161-022-02407-y

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