The Neglected Dimension in Pesticide Residues: Emerging Green and Enantioselective Strategies for the Analysis and Removal of Chiral Pesticides

Chirality remains the most neglected axis of pesticide residue science. Many active ingredients are sold as racemates although their enantiomers differ in potency, persistence, transport, and toxicology; as a result, total concentration is a poor surrogate for risk. This review synthesizes green and enantioselective strategies spanning the full analytical–remediation continuum. We survey solvent-minimized sample preparation approaches (SPME/TF-SPME, FPSE, µSPE, DLLME with DES/NADES), MS-compatible chiral separations (immobilized polysaccharide CSPs in LC and SFC, cyclodextrin-based selectors in GC, CE/CEC), and HRMS-enabled confirmation and suspect screening. Complex matrices (e.g., fermented beverages such as wine and high-sugar products) are critically discussed, together with practical matrix-tolerant workflows and the complementary role of chiral GC for hydrophobic residues. We then examine emerging enantioselective materials—MIPs, MOFs/COFs, and cyclodextrin-based sorbents—for extraction and preconcentration and evaluate stereoselective removal via adsorption, biodegradation, and chiral photocatalysis. Finally, we propose toxicity-weighted enantiomeric fraction (EF) metrics for decision-making, outline EF-aware green treatment strategies, and identify metrological and regulatory priorities (CRMs, ring trial protocols, FAIR data). Our thesis is simple: to reduce hazards efficiently and sustainably, laboratories and practitioners must measure—and manage—pesticide residues in the chiral dimension.

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Publication Details

Journal
Separations
Published
2025-12-23
DOI
https://doi.org/10.3390/separations13010004
Primary Topic
Analytical Chemistry and Chromatography
Type
article
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article

The Neglected Dimension in Pesticide Residues: Emerging Green and Enantioselective Strategies for the Analysis and Removal of Chiral Pesticides

Haixiang Gao, Ziyan Gong, Binbin Liu
Separations
Analytical Chemistry and Chromatography
article

The Neglected Dimension in Pesticide Residues: Emerging Green and Enantioselective Strategies for the Analysis and Removal of Chiral Pesticides

Haixiang Gao, Ziyan Gong, Binbin Liu
article en

Abstract

Chirality remains the most neglected axis of pesticide residue science. Many active ingredients are sold as racemates although their enantiomers differ in potency, persistence, transport, and toxicology; as a result, total concentration is a poor surrogate for risk. This review synthesizes green and enantioselective strategies spanning the full analytical–remediation continuum. We survey solvent-minimized sample preparation approaches (SPME/TF-SPME, FPSE, µSPE, DLLME with DES/NADES), MS-compatible chiral separations (immobilized polysaccharide CSPs in LC and SFC, cyclodextrin-based selectors in GC, CE/CEC), and HRMS-enabled confirmation and suspect screening. Complex matrices (e.g., fermented beverages such as wine and high-sugar products) are critically discussed, together with practical matrix-tolerant workflows and the complementary role of chiral GC for hydrophobic residues. We then examine emerging enantioselective materials—MIPs, MOFs/COFs, and cyclodextrin-based sorbents—for extraction and preconcentration and evaluate stereoselective removal via adsorption, biodegradation, and chiral photocatalysis. Finally, we propose toxicity-weighted enantiomeric fraction (EF) metrics for decision-making, outline EF-aware green treatment strategies, and identify metrological and regulatory priorities (CRMs, ring trial protocols, FAIR data). Our thesis is simple: to reduce hazards efficiently and sustainably, laboratories and practitioners must measure—and manage—pesticide residues in the chiral dimension.

SeparationsVol. 13(1)
China Agricultural University (CN)
Openalex Percentile: Top 40%
Analytical Chemistry and Chromatography
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The Neglected Dimension in Pesticide Residues: Emerging Green and Enantioselective Strategies for the Analysis and Removal of Chiral Pesticides — Haixiang Gao, Ziyan Gong, et al. · Separations (2025) | TGRS Research Map | TGRS