Guizhou Green Tea Metabolomics Analysis: Volatile Metabolites Based on HS-GC-IMS and UPLC-Q-TOF-MSMS and Quality Evaluation.

This study identifies metabolite profiles associated with aroma variations among three Guizhou green teas (Meitan Cuiya, Meitan Maofeng, and Duyun Maojian) using integrated HS-GC-IMS and UPLC-Q-TOF-MSMS analysis. We identified 57 volatile organic compounds and 159 phenolic compounds, with 22 compounds exhibiting relative odor activity values (rOAVs) ≥ 1. A partial least squares regression (PLSR) model was developed to establish quantitative relationships between metabolite concentrations and electronic tongue sensory parameters, demonstrating predictive capability (R 2 Y = 0.89, Q 2 = 0.82). Variable importance in projection (VIP) analysis identified heptanal, butanol, and pentanol as major contributors to sensory variance. Significant correlations were observed between specific metabolites and sensory attributes (e.g., heptanal-green perception: r = 0.82, p = 0.003). Unique metabolite combinations were identified for each tea variety: 2-furanmethanol acetate for Meitan Cuiya, propanol for Meitan Maofeng, and myrcene-D/M for Duyun Maojian. The OPLS-DA model (R 2 Y = 99.3%, Q 2 = 98.2%) provides a classification tool for tea differentiation. Absolute quantification was achieved for 22 key aroma compounds and 15 major phenolics with complete method validation. These findings identify metabolite profiles associated with aroma variations among Guizhou green teas and provide candidate markers for quality assessment.