Discrimination and prediction of Qingzhuan tea storage year using quantitative chemical profile combined with multivariate analysis: Advantages of MRMHR based targeted quantification metabolomics

Abstract

The duration of storage significantly influences the quality and market value of Qingzhuan tea (QZT). Herein, a high-resolution multiple reaction monitoring (MRMHR) quantitative method for markers of QZT storage year was developed. Quantitative data alongside multivariate analysis were employed to discriminate and predict the storage year of QZT. Furthermore, the content of the main biochemical ingredients, catechins and alkaloids, and free amino acids (FAA) were assessed for this purpose. The results show that targeted marker–based models exhibited superior discrimination and prediction performance among four datasets. The R2Xcum, R2Ycum and Q2cum of orthogonal projection to latent structure–discriminant analysis discrimination model were close to 1. The correlation coefficient (R2) and the root mean square error of prediction of the QZT storage year prediction model were 0.9906 and 0.63, respectively. This study provides valuable insights into tea storage quality and highlights the potential application of targeted markers in food quality evaluation.