Abstract: A non-targeted metabolomics method for identifying the quality of Gougunao tea, Lu Mountain Clouds-Mist tea, and Wuyuan green tea was established by ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS). The original data were screened by MassHunter Mass Profile, and 220 characteristic differential metabolites were obtained. The results of principal component analysis (PCA) and hierarchical cluster analysis (HCA) showed that there was a clear discrimination among the three teas. Partial least squares discriminant analysis (PLS-DA) was used to establish a prediction model for identifying the quality of tea with an accuracy of 100%. Meanwhile, of the 220 characteristic differential metabolites, 22 were identified, mainly including flavonoids, glycoside derivatives and organic acids. Through heatmap analysis, it was found that their contents were significantly different among tea samples. This study is meaningful for guiding tea quality identification, which can be widely used in food analysis and characterization.

Key words: famous Jiangxi teas; quality identification; ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry; non-targeted metabolomics; multivariate statistical analysis