Rong Yanna, Riaz Tahreem, Lin Hao, Wang Zhen, Chen Quansheng, Ouyang Qin
School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China.
National Research and Development Center for Matcha Processing Technology, Jiangsu Xinpin Tea Co., Ltd, Changzhou 213254, PR China.
Spectrochim Acta A Mol Biomol Spectrosc. 2024 Jan 5;304:123385. doi: 10.1016/j.saa.2023.123385. Epub 2023 Sep 9.
The drying process is a critical stage in developing the aroma quality of tencha. In our research, visible near infrared (Vis-NIR) and colorimetric sensor array (Vis-NIR-CSA) were used for evaluating the aroma quality of tencha drying process. Vis-NIR recorded the spectral signal of CSA after the reaction in samples. Subsequently, the aroma quality was predicted by a combination of different data fusion strategies and classification and regression tree (CART) in tencha drying process. The high-level fusion strategy showed the best performance, with calibration and prediction set accuracy of 94.68% and 93.48%, respectively. The results indicated that Vis-NIR-CSA combined with high-level data fusion could be applied satisfactorily in the aroma quality evaluation of tencha. Moreover, pentanal was identified to be highly correlated with aroma quality during tencha drying process, which verified the sensor identification results. This study contributed to controlling good manufacturing practices and designing optimal tencha processing systems.
干燥过程是抹茶香气品质形成的关键阶段。在我们的研究中，可见近红外（Vis-NIR）和比色传感器阵列（Vis-NIR-CSA）被用于评估抹茶干燥过程中的香气品质。Vis-NIR记录了样品反应后CSA的光谱信号。随后，通过不同数据融合策略与分类回归树（CART）相结合的方法对抹茶干燥过程中的香气品质进行预测。高级融合策略表现最佳，校准集和预测集的准确率分别为94.68%和93.48%。结果表明，Vis-NIR-CSA结合高级数据融合可令人满意地应用于抹茶香气品质评估。此外，已确定戊醛与抹茶干燥过程中的香气品质高度相关，这验证了传感器识别结果。本研究有助于控制良好生产规范并设计优化的抹茶加工系统。
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