Natural deep eutectic solvents as a sustainable alternative for multi-class pesticide extraction in food safety analysis

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Authors: Laura Carbonell-Rozas, Ivan Aloisi, Antonia Garrido Frenich, Hans Mol, Laura Righetti
Cited by: 6
References: 19

Abstract

Pesticide residue analysis in food is frequently carried out worldwide, often requiring a large volume of organic solvents. To improve sustainability, new generation solvents such as natural deep eutectic solvents (NADES) have recently emerged as a promising alternative to conventional solvents. This study demonstrates the applicability of NADES as green extraction solvents for pesticides in food samples prior to analysis by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). The present research goes beyond previous studies by covering an extended set of pesticide residues. For that, five hydrophilic and hydrophobic NADES were evaluated as extraction solvents in a solid-liquid extraction (SLE). Initially, eleven representative pesticides covering a broad range of chemical classes and physicochemical properties were selected, while food matrices were chosen to cover different commodity groups according to SANTE/11312/2021v2, including orange, wheat, and spinach. NADES were tailored in order to cover a wide range of physicochemical properties such as polarity, pH, and viscosity. Thymol: menthol (molar ratio, 1:1) was found to be the most effective, and key extraction parameters were optimized. The greenness and transferability of the NADES-based SLE were evaluated using the AGREEprep and BAGI metrics. Finally, the method was successfully validated for the extraction of a wide range of pesticides commonly analyzed in food safety assessments.

Fields of Study & Subjects

Analytical chemistry methods development Ionic liquids properties and applications Pesticide Residue Analysis and Safety

Publication details

Journal / source
npj Science of Food
Publisher
Springer Science and Business Media LLC
Volume
10
Issue
1
Pages
67–67
Publication date
20 January 2026
Language
EN