Discovery of the Potential Marker Compounds for Stored White Tea by Metabolomics Approach

Importance of the Topic

White tea is valued for its mild flavor and documented health benefits, including antioxidant and anticancer properties. Extended storage can enhance its protective effects and market value, but also introduces challenges in quality control and authentication. Identifying chemical markers that reflect storage-induced changes is essential to prevent adulteration, ensure product consistency and inform consumers.

Objectives and Overview of the Study

This study employed a non-targeted metabolomics strategy to characterize how non-volatile components in white tea evolve during long-term storage. The primary goals were to profile metabolite changes over time, discover novel compounds associated with aging and evaluate their potential as markers for storage duration in two tea subclasses (BMD and BHYZ).

Methodology and Instrumentation

Sample Preparation and Data Acquisition

• Tea samples were extracted using a standardized protocol to ensure reproducible metabolite recovery.
• An optimized UHPLC gradient separated thousands of compounds over a 35-minute run.
• Data were acquired on an Agilent 1290 Infinity II UHPLC coupled to an Agilent 6540/6545 QTOF mass spectrometer with positive ESI.

Data Processing

• Molecular feature extraction yielded 2584 compound features across all samples.
• Alignment and statistical analysis were performed in Agilent Mass Profiler Professional (MPP).
• Non-supervised PCA and supervised PLS-DA models assessed data quality and storage-related differences.

Main Results and Discussion

Data Quality and Multivariate Analysis

• Pooled quality control samples clustered tightly in PCA, confirming analytical reproducibility.
• Both PCA and PLS-DA models revealed clear separation of tea samples according to storage time.

Identification of Differential Metabolites

• 125 metabolites showing significant abundance changes were annotated by accurate MS/MS spectra and authentic standards.
• Heat maps and extracted ion chromatograms highlighted progressive alterations over storage.

Discovery of Novel EPSFs

• Seven 8-C N-ethyl-2-pyrrolidinone substituted flavan-3-ols (EPSFs) were newly detected in aged samples.
• Their levels increased markedly with storage duration in both BMD and BHYZ teas.
• Strong negative correlations were observed between EPSFs and precursor compounds (theanine and flavan-3-ols), suggesting in situ formation during aging.

Benefits and Practical Applications of the Method

The non-targeted metabolomics workflow provides a comprehensive chemical fingerprint of white tea aging. Identification of EPSFs as storage-dependent markers supports:

• Authentication of long-stored white tea products.
• Quality control protocols to detect adulteration or mislabeling.
• Insight into biochemical transformations that influence flavor and health properties.

Future Trends and Opportunities

Further research may focus on targeted quantification of EPSFs and their precursors in diverse tea varieties, elucidation of the underlying reaction mechanisms, and assessment of the biological activities of newly discovered compounds. Integration with sensory analysis and consumer studies could link chemical markers to perceptual quality and market preferences.

Conclusion

This study demonstrates that non-targeted UHPLC-QTOF metabolomics effectively monitors chemical changes in white tea during extended storage. The discovery of novel EPSFs and their correlation with storage duration offers promising markers for authentication and quality assessment of aged tea products.

Instrumentation Used

• Agilent 1290 Infinity II UHPLC with built-in degasser, temperature-controlled autosampler and C18 column (Zorbax Eclipse Plus, 150 × 3.0 mm, 1.8 µm).
• Agilent 6540/6545 QTOF mass spectrometer with Dual JetStream ESI (positive ion mode).

Reference

1. Mao, Y. et al. Cancer Prev. Res. 2010, 3, 1132–1140.
2. Ning, Z. et al. Eur. Food Res. Technol. 2016, 242, 2093–2104.
3. Dai, W. et al. J. Agric. Food Chem. 2018, 66(27), 7209–7218.