Dynamic changes in volatile profiles of fu brick tea during storage and a predictive model for aging year

This study investigated the dynamic evolution of volatile organic compounds (VOCs) in Jingyang Fu brick tea during storage. Using GC-IMS and HS-SPME-GC-MS, we characterized the VOC profiles, identifying 291 volatiles, among which 36 key compounds (including α-ionone, trans-β-ionone, and methyl salicylate) were pinpointed as responsible for the distinctive fungal-floral aroma that intensified with storage time. Sensory evaluation revealed a progressive shift from fresh to mellow fungal and aged characteristics. Key fungal-floral compounds exhibited synchronous variations with processing-derived metallic elements. Based on the identified VOCs, we developed the first predictive model for determining storage year using machine learning (PLSR and SVM). The model achieved a classification accuracy of 0.889 and high regression precision (R² > 0.87). This work provides fundamental insights into the aroma evolution of Fu brick tea during aging and offers a robust tool for quality control.