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

This study comprehensively characterized the 122 odorants of raw Anhua dark teas (RADTs) from seven core production regions between 2015 and 2024. Among them, 16 compounds with aroma character impact (ACI) ≥1% constituted the crucial aroma profile, with (E)-β-ionone contributing the most in RADTs. Multivariate analysis indicated that regional origin shaped initial aroma diversity, while storage drove subsequent transformation. Freshly processed samples in 2024 were enriched in floral, roasty, and sulfuric notes, whereas long-term storage promoted the degradation of galloylated catechins and the accumulation of methoxybenzenes, conferring stale and woody attributes. The Random Forest model achieved 100% accuracy in regional classification and a mean squared error of 0.35 years in vintage prediction, outperforming the orthogonal partial least squares discriminant analysis (OPLS-DA) model. Furthermore, 13 and 19 robust chemical markers were identified for regional and temporal differentiation, respectively, providing reliable evidence for the traceability and authenticity of RADT.