Dynamic Chemical and Flavor Changes in Black Tea During Fermentation

Significance of the Topic

Black tea fermentation involves complex enzymatic and oxidative reactions that transform key polyphenols and other metabolites, directly impacting flavor attributes such as bitterness and astringency, as well as nutritional quality. Detailed knowledge of these dynamic chemical changes supports improved process control, product consistency and the design of teas with targeted sensory profiles.

Objectives and Overview of the Study

This study applied a nontargeted metabolomics approach to map the temporal variation of metabolites during a 14-hour black tea fermentation. Using UHPLC-Q-TOF/MS and chemometric tools, researchers aimed to identify major differential compounds and correlate their abundance changes with sensory bitterness and astringency.

Methodology and Instrumentation

The workflow comprised:

• Sample preparation: Fresh tea leaves withered, rolled and fermented at 30 °C/90 % RH for up to 14 hours with sampling at multiple time points.
• Extraction: 70:30 methanol–water, sonication, centrifugation and 0.22 μm filtration.
• Chromatography and MS: Agilent 1290 Infinity LC with ZORBAX Eclipse Plus C18 column; 30 min gradient elution; Agilent 6540 Q-TOF in positive ESI mode.
• Data processing: Molecular Feature Extraction, recursive alignment in MassHunter Profinder, and multivariate analysis in Mass Profiler Professional.
• Sensory scoring: Bitterness and astringency rated on a 1–10 scale by expert panel.

Main Results and Discussion

• Over 1 000 ion features detected; 62 compounds identified or tentatively assigned, including mono- and dimeric catechins, theaflavins, flavonol glycosides, amino acids, organic acids, alkaloids and nucleosides.
• PCA revealed a clear time-dependent shift in metabolome composition, with the first two components explaining >77 % of variance.
• Catechins (EGCG, ECG, EGC, EC) decreased by >90 % within 6–8 hours, correlating with reduced astringency and bitterness.
• Theaflavins and other dimeric oxidation products peaked early (2–4 h) and then declined, indicating further polymerization.
• Pearson correlation analysis linked EGCG, ECG, 3-galloyl procyanidin B1, myricetin-3-O-galactoside and theanine to sensory scores (R² > 0.8).

Benefits and Practical Applications

• Comprehensive metabolite profiles guide optimization of fermentation parameters for desired flavor outcomes.
• Identified chemical markers enable real-time monitoring and quality control.
• Data support the development of tea products with enhanced taste and health attributes.

Future Trends and Potential Applications

Future work may focus on targeted quantification of key markers, integration of rapid online MS sensors for process control, coupling metabolomics with genomics of tea oxidation enzymes, and machine learning models to predict sensory profiles from metabolite data.

Conclusion

This nontargeted metabolomics study provides a detailed view of the chemical evolution during black tea fermentation, linking metabolite dynamics to sensory quality. The identified markers and workflows offer valuable tools for improving tea manufacture and tailoring product characteristics.

Reference

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