Green analytical assay for the quality assessment of tea by using pocket-sized NIR spectrometer. (30th May 2021) - Wang, Yujie; Li, Menghui; Li, Luqing; Ning, Jingming; Zhang, Zhengzhu
Highlights: Pocket-sized NIRS was used to evaluate tea quality qualitatively and quantitatively. Accurate tea type discrimination and component prediction models were obtained. Novel IVSO can improve the accuracies of catechin, caffeine, and theanine models. It provided a green and low-cost method for the in-situ assessment of tea quality. Abstract: Rapid and low-cost testing tools provide new methods for the evaluation of tea quality. In this study, a micro near-infrared (NIR) spectrometer was used for the qualitative and quantitative evaluation of tea. A total of 360 tea samples consisting of black, green, yellow, and oolong tea were collected from different countries. Chemometrics including linear partial least squares (PLS) regression, PLS discriminant analysis, and nonlinear radial basis function–support vector machine (RBF–SVM) were used. The RBF–SVM model achieved optimal discriminant performance for tea types with a correct classification rate of 98.33%. Wavelength selection of iteratively variable subset optimization (IVSO) exhibited considerable advantages in improving the predictive performance of catechin, caffeine, and theanine models. The IVSO–PLS regression models achieved satisfactory results for catechins and caffeine prediction, with Rp over 0.9, and RPD over 2.5. Thus, the study provided a portable and low-cost method for in-situ assessing tea quality.