Hyperspectral imaging technology coupled with human sensory information to evaluate the fermentation degree of black tea

文献类型： 外文期刊

第一作者： An, Ting

作者： An, Ting;Zhao, Chunjiang;Li, Guanglin;An, Ting;Huang, Wenqian;Tian, Xi;Fan, Shuxiang;Duan, Dandan;Zhao, Chunjiang;An, Ting;Dong, Chunwang;Zhao, Chunjiang

作者机构：

关键词： Hyperspectral imaging; Data fusion; pH sensors; TPP sensors; Black tea fermentation

期刊名称：SENSORS AND ACTUATORS B-CHEMICAL （ 影响因子：9.221； 五年影响因子：7.676 ）

ISSN：

年卷期： 2022 年 366 卷

页码：

收录情况： SCI

摘要： Hitherto, the intelligent evaluation of black tea fermentation is still an unsolved problem because it is difficult to obtain the complicated changes information of tea composition, color, texture and aroma in the fermentation process at the same time. In this research, hyperspectral imaging technology was used to collect sensory information including taste (sample spectra), vision (sample color image) and olfactory (pH, porphyrin and metalloporphyrin (TPP) sensing array spectra) of fermentation leaves. Subsequently, different data fusion strategies combined with support vector machine algorithm (SVM) were used to establish the fermentation degree discrimination model. The performance of the established models using data fusion strategy were better than that of the model using each single information. The middle-level-PCA strategy achieved a satisfactory performance, with the variable compression rate of 99% and the accuracy of 95% for the prediction set. Remarkably, for the most important moderate fermentation class, the precision and recall of the model were 100% both in calibration and prediction set. These results demonstrated that our proposed strategy could accurately evaluate the fermentation degree of black tea.

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