Natural deep eutectic solvent-based headspace gas chromatography for determination of 14 residual solvents in tea polyphenol products

Abstract

A headspace gas chromatography (HS-GC) method using natural deep eutectic solvent (NADES) as a green matrix medium was reported for the simultaneous determination of 14 residual solvents in tea polyphenol products. Through systematically screening, a NADES, choline chloride-glycerol (1:2, mol/mol), was selected as the optimal matrix medium in tea polyphenol dissolution. After the headspace parameters, including equilibrium temperature and time were optimized. A HS-GC method was developed and demonstrated good linearity (R² = 0.9874–0.9995) over 0.005–1000 μg/g. Limits of detection (LODs) and quantification (LOQs) ranged from 0.01 to 0.25 μg/g and 0.03 to 0.83 μg/g, respectively. In spiked tea polyphenol samples, the recoveries from 82.4% to119.0% were obtained with relative standard deviations (RSDs) of 0.14%–4.91%. And the above HS-GC method was utilized to measure 41 commercial tea polyphenol products. The results confirmed that the detected residual solvents in all the samples were below the Permissible Daily Exposure (PDE) limits. Risk assessment based on the hazard quotient (HQ, calculated as the ratio of Daily Intake to PDE) yielded values of 50.8% for benzene and 1.47% for dichloromethane. These results suggest that benzene requires prioritized control as a critical point. And we also should pay attention to dichloromethane. This study provides a green and efficient approach for residual solvent analysis in tea polyphenol products and demonstrates the potential of NADESs as sustainable matrix media in food safety testing.

Supplementary files

Article information

Article type
Paper
Submitted
09 Mar 2026
Accepted
12 May 2026
First published
15 May 2026

Anal. Methods, 2026, Accepted Manuscript

Natural deep eutectic solvent-based headspace gas chromatography for determination of 14 residual solvents in tea polyphenol products

H. Xu, Z. Yao, X. Bao, Y. Cai, X. Zuo and C. Peng, Anal. Methods, 2026, Accepted Manuscript , DOI: 10.1039/D6AY00418K

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