E-nose and colorimetric sensor array combining homologous data fusion strategy discriminating the roasting degree of large-leaf yellow tea.

Different degrees of roasting result in differences in the quality and flavor of large-leaf yellow tea. The current sensory evaluation and chemical detection methods cannot meet the requirement of online differentiation of LYT roasting degree, so an accurate and comprehensive assessment method needs to be developed urgently. First, the two aroma sensing technologies were compared. Two variable screening methods and three recognition algorithms were employed to build discriminant models. The results showed that the discrimination rate of the colorimetric sensor array (CSA) in the prediction set reached 91.89 %, outperforming that of the E-nose. Subsequently, three fusion strategies were applied to improve the discrimination accuracy. The discrimination rate of the middle fusion strategy resulted in an optimal resolution of 94.59 %. The results obtained from the homologous fusion were able to evaluate the roasting degree comprehensively and accurately, which provides a new method and idea for tea aroma quality.

Rapid and comprehensive grade evaluation of Keemun black tea using efficient multidimensional data fusion.

To develop a comprehensive evaluation method for Keemun black tea, we used micro-near-infrared spectroscopy, computer vision, and colorimetric sensor array to collect data. We used support vector machine, least-squares support vector machine (LS-SVM), extreme learning machine, and partial least squares discriminant analysis algorithms to qualitatively discriminate between different grades of tea. Our results indicated that the LS-SVM model with mid-level data fusion attained an accuracy of 98.57% in the testing set. To quantitatively determine flavour substances in black tea, we used support vector regression. The correlation coefficient for the predicted sets of gallic acid, caffeine, epigallocatechin, catechin, epigallocatechin gallate, epicatechin, gallocatechin gallate and total catechins were 0.84089, 0.94249, 0.94050, 0.83820, 0.81111, 0.82670, 0.93230, and 0.93608, respectively. Furthermore, all compounds exhibited residual predictive deviation values exceeding 2. Hence, combining spectral, shape, colour, and aroma data with mid-level data can provide a rapid and comprehensive assessment of Keemun black tea quality.