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Open Access | Just Accepted

An Emerging Strategy for Grading Chun Mee Green Tea by Combination of Metabolites, Sensory Properties, and Bioactivities

Libin Chena,bJia-Ping Kea,bGuoping Laia,bMingchun Wena,bPiaopiao Longa,bLiang Zhanga,b( )Zisheng Hana,b( )

a State Key Laboratory of Tea Plant Germplasm Innovation and Resource Utilization, Anhui Agricultural University, Hefei 230036, China

b International Joint Laboratory on Tea Chemistry and Health Effects of Ministry of Education, Anhui Agricultural University, Hefei 230036, China

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Abstract

Chun Mee green tea (CMGT), one of the major export teas from China, has a comprehensive classification (grading) system. However, the chemical constituents underlying grade differentiation, as well as their associations with astringency and bioactivity, remain unclear. In this study, we integrated quantitative descriptive analysis (QDA), tea-mucin complex analysis, in vitro bioactivity evaluations, and metabolomics, supported by Random Forest (RF) modeling and correlation analysis. QDA demonstrated that higher-grade samples exhibited superior overall sensory quality and stronger astringency. Tea-mucin complex analysis (turbidity, particle size, SEM) confirmed reduced aggregation in lower grades, consistent with weaker astringency. Quantitative analysis revealed a significant decrease in major flavor compounds (EGCG, caffeine, and amino acids) as the grade declined. Liquid chromatography-mass spectrometry (LC-MS)-based metabolomics further classified samples into high-grade (T1, T2, T3) and low-grade (T4, T5, T6, 1, 2) clusters, identifying 68 grade-differentiating markers. High-grade teas exhibited stronger antioxidant activity and inhibition effects on α-amylase and α-glucosidase. RF and correlation analysis revealed that catechins, phenolic acids, hydrolysable tannins, and acylated quercetin glycosides were critical for grading, with trans-p-coumaroylquinic acid and its derivatives contributing significantly to both astringency and antioxidant capacity. In addition, a grade estimation model based on four compounds (5-galloylquinic acid, EGCG, ECG, GCG) was constructed using elastic net and ridge regression, achieving high accuracy (R2 = 0.995, RMSE = 0.168). Commercial samples verification confirmed the model’s reliability for ranking CMGT grades from the same factory. These findings provide an objective approach for grade evaluation and may facilitate the refinement of CMGT grading standards.

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Food Science and Human Wellness

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Cite this article:
Chen L, Ke J-P, Lai G, et al. An Emerging Strategy for Grading Chun Mee Green Tea by Combination of Metabolites, Sensory Properties, and Bioactivities. Food Science and Human Wellness, 2026, https://doi.org/10.26599/FSHW.2026.9251014

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Received: 28 August 2025
Revised: 20 October 2025
Accepted: 14 November 2025
Available online: 17 March 2026

© 2026 Beijing Academy of Food Sciences. Publishing services by Tsinghua University Press.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).