Duan Yue, Gao Xing, Shi Bolin, Yu Mingguang, Raza Junaid, Sun Huijuan, Wang Ying, Song Huanlu, Xu Yongquan
Laboratory of Molecular Sensory Science, School of Food and Health, Beijing Technology and Business University (BTBU), Beijing 100048, China.
Food and Agriculture Standardization Institute, China National Institute of Standardization, Beijing 102200, China.
Food Chem. 2025 Oct 15;489:144931. doi: 10.1016/j.foodchem.2025.144931. Epub 2025 May 27.
Understanding aroma compounds' changes during Shuixian roasting is vital for scientific guidance. This study used gas chromatography-ion mobility spectrometry (GC-IMS) and two-dimensional gas chromatography-olfactory-mass spectrometry (GC × GC-O-MS) to identify 100 and 183 compounds, respectively. The random forest algorithm combined with relative odor activity value (rOAV) was used to identify eight key differential compounds: 3-methylbutanal, (E)-2-octenal, 5-methylfurfural, 2-ethyl-5-methylpyrazine, 1-furfuryl pyrrole, 1-(1H-pyrrol-2-yl)-ethanone, 1-octen-3-ol, and (Z)-4-heptenal. The metabolic pathways of these compounds were analyzed, mainly involving the Maillard reaction and lipid oxidation. This study not only provides theoretical support for the targeted processing and quality control of Shuixian but also introduces a novel methodological framework by integrating advanced analytical techniques with machine learning, offering new insights into the dynamic changes of volatile compounds during tea roasting.
了解水仙茶烘焙过程中香气化合物的变化对于科学指导至关重要。本研究采用气相色谱-离子迁移谱（GC-IMS）和二维气相色谱-嗅觉-质谱联用仪（GC×GC-O-MS）分别鉴定出100种和183种化合物。利用随机森林算法结合相对气味活度值（rOAV）鉴定出8种关键差异化合物：3-甲基丁醛、（E）-2-辛烯醛、5-甲基糠醛、2-乙基-5-甲基吡嗪、1-糠基吡咯、1-（1H-吡咯-2-基）-乙酮、1-辛烯-3-醇和（Z）-4-庚烯醛。分析了这些化合物的代谢途径，主要涉及美拉德反应和脂质氧化。本研究不仅为水仙茶的靶向加工和质量控制提供了理论支持，还通过将先进分析技术与机器学习相结合引入了一种新颖的方法框架，为茶叶烘焙过程中挥发性化合物的动态变化提供了新的见解。
