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  • Monitoring the baking quali...
    Song, Feihu; Xiang, Hao; Li, Zhenfeng; Li, Jing; Li, Luqing; Fang Song, Chun

    Food research international, March 2023, 2023-03-00, 20230301, Letnik: 165
    Journal Article

    Display omitted •The quality of tea was evaluated by internal quality components and volatiles composition under different roasting conditions.•The electronic nose combined with GC–MS were used to analyze and identify aromas and odors changes during Tieguanyin baking.•Sensory evaluation and electronic nose technology were used to assess baking quality.•The baking process was monitored to find a better baking conditions and quality. Roasting is extremely important for Tieguanyin oolong tea production because it strongly affects its chemical composition and sensory quality. In addition, there were significant differences in the preference for roasted tea among different people. However, the effect of roasting degree on the aroma characteristics and flavor quality of Tieguanyin tea is still unclear. To further study this, an electronic nose combined with gas chromatography–mass spectrometry (GC–MS) was used to monitor the baking process of Tieguanyin. The physicochemical indexes, sensory quality, and odor characteristics of the tea leaves subjected to different roasting conditions were measured. The increase in the roasting degree caused a decrease in the amount of taste substances such as tea polyphenols, catechins, and amino acids and a sharp increase in the phenol to ammonia ratio. Sensory evaluation results showed that moderate roasting could help improve the quality of the tea leaves. The results obtained using the electronic nose and GC–MS showed that there were substantial differences in the volatile substances, and 103 flavor compounds were highly correlated with the aroma characteristics of roasted tea with different roasting degrees. In addition, the electronic nose combined with various classification models could better distinguish tea leaves with different roasting degrees. Among them, the accuracy of the RF training set and prediction set reached>98.44%. The results of this study will aid in comprehensively monitoring the effects of the baking process on the flavor, chemical composition, and aroma of Tieguanyin as well as in distinguishing Tieguanyin tea leaves with different qualities.