Monitoring the dynamic change of catechins in black tea drying by using near-infrared spectroscopy and chemometrics

Drying is an important process in black tea processing, at the same time, catechin is an important factor in determining the sensory quality of black tea. However, there is a lack of effective real-time detection methods for the detection of catechins in black tea drying process. Therefore, we analyzed the trends of catechins in black tea drying process under different drying conditions and further explored the quantitative prediction model of eight individual catechins in black tea drying process by Least squares support vector machine (LS-SVM) based on near-infrared spectroscopy (NIRS) and chemometrics methods. The results showed that the prediction accuracy of the eight monomeric catechins prediction models established based on the extraction of competitive adaptive reweighted sampling (CARS) and successive projections algorithm (SPA) feature spectra achieved the best results, and the correlation coefficient values of the prediction sets (Rp) were all greater than 0.98, and the relative percentage deviation (RPD) values were all greater than 5. The gallocatechin gallate (GCG) with the highest prediction accuracy was 0.9977 and the RPD value was 14.8. This study shows that the method based on near-infrared spectroscopy and chemometrics has strong predictive power for catechins in black tea drying process, which is a guideline for controlling the sensory quality of black tea drying.