Monitoring the withering condition of leaves during black tea processing via the fusion of electronic eye (E-eye), colorimetric sensing array (CSA), and micro-near-infrared spectroscopy (NIRS)

Withering of leaves is an important step in the processing of black tea and determines the taste and aroma of the tea. Currently, the withering degree of the leaves is mainly determined via sensory evaluation by the tea maker, and this is time-consuming and laborious. In this study, near-infrared spectroscopy, electronic eye, and colorimetric sensing array technologies were combined to evaluate the extent of withering. A low-cost micro-spectrometer, a self-built machine vision system, and a homemade colorimetric array were used to capture relevant information regarding the withered tea leaf samples in situ. Additionally, low- and middle-level data fusion strategies were modeled and compared using a support vector machine (SVM). The SVM model, which combined the information obtained using the three technologies, performed substantially better than a single technology. Low-level fusion achieved acceptable discriminant performance, with an accuracy of 90.00% for both the SVM and principal component analysis-SVM models for the prediction set. The middle-level fusion strategy achieved better performance than the low-level fusion strategy, with an optimal discriminant accuracy of 97.50% for SVM model. Hence, this study demonstrated that in situ and low-cost quality assessment and intelligent control of the withering process of black tea leaves are possible.