ArticleFoods (Basel, Switzerland)2026
Green Solvent-Based Dispersive Liquid-Liquid Microextraction Method Coupled with High-Performance Liquid Chromatography for the Determination of Triazole Fungicides in Cereal Samples.
Article in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Triazole fungicides (TFs) are widely used in cereal production due to their potent fungicidal activity and broad-spectrum efficacy. Nonetheless, residues of TFs in food products may pose risks to food safety and human health. Therefore, the development of efficient and environmentally friendly sample preparation methods is paramount for the reliable determination of TFs. Herein, a novel green solvent-based dispersive liquid-liquid microextraction method coupled with high-performance liquid chromatography (DLLME-HPLC) was developed for the determination of TFs in cereal samples. The prepared magnetic deep eutectic solvents (MDESs), composed of nonanoic acid and ferric hydroxide, served as green, magnetically responsive extraction solvents, enabling rapid magnetic separation without centrifugation. Four bio-based solvents (BBSs) were investigated as green dispersive solvents to facilitate the dispersion of MDESs and replace conventional toxic organic dispersants, thereby further enhancing the environmental sustainability of the extraction procedure. Owing to the combined effects of hydrophobic interactions, hydrogen-bonding networks, and magnetic responsiveness, the proposed method achieved efficient extraction and rapid phase separation while minimizing solvent consumption and operational complexity. The greenness of the method was evaluated using multiple green analytical chemistry metrics, confirming its low environmental impact, reduced waste generation, and improved operational safety compared with conventional DLLME procedures. Under optimized conditions, the method was successfully applied to determine TFs in rice, wheat, corn, buckwheat, and oat samples, achieving recoveries ranging from 75.0% to 101.9% and relative standard deviations of 1.6-4.8%. The developed DLLME method provides a rapid, sensitive, and environmentally friendly strategy for cereal pesticide residue analysis and expands the application of MDESs and BBSs in green sample preparation.
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