Decoding regional and temporal drivers on raw Anhua dark tea odorants for traceability

Area of Science:

• Food Chemistry
• Analytical Chemistry
• Sensory Science

Background:

• Anhua dark teas (RADTs) possess a complex aroma profile influenced by geographical origin and aging.
• Understanding these volatile organic compounds is crucial for quality control and authenticity verification.

Purpose of the Study:

• To comprehensively characterize the odorant profiles of RADTs from diverse regions and vintages.
• To elucidate the impact of regional origin and storage duration on tea aroma.
• To develop predictive models for classifying RADTs based on origin and age.

Main Methods:

• Gas chromatography-mass spectrometry (GC-MS) for odorant identification and quantification.
• Multivariate statistical analysis (e.g., Random Forest, OPLS-DA) for pattern recognition.
• Chemical marker identification for traceability.

Main Results:

• 122 odorants were identified, with 16 key aroma compounds identified, notably (E)-β-ionone.
• Regional origin significantly influenced initial aroma diversity.
• Storage led to the degradation of catechins and accumulation of methoxybenzenes, altering aroma notes.
• Random Forest model achieved 100% accuracy for regional classification and 0.35 years MSE for vintage prediction.
• 13 and 19 robust markers were identified for regional and temporal differentiation, respectively.

Conclusions:

• Aroma profiles of RADTs are distinctively shaped by their region of origin and storage history.
• Chemical markers and predictive models offer reliable tools for ensuring the traceability and authenticity of RADTs.
• This research provides a scientific basis for the quality assessment and authentication of Anhua dark teas.