Integration of lipidomics and metabolomics approaches for the discrimination of harvest time of green tea in spring season by using UPLC-Triple-TOF/MS coupled with chemometrics - Cui, Hui-Na; Gu, Hui-Wen; Li, Zhi-Quan; Sun, Weiqing; Ding, Baomiao; Li, Zhenshun; Chen, Ying; Long, Wanjun; Yin, Xiao-Li; Fu, Haiyan (Frontiers in Sustainable Food Systems, 2023)
A multifaceted strategy that integrates lipidomics and metabolomics, based on UPLC-Triple-TOF/MS coupled with chemometrics, was developed to discriminate early spring green tea (ET) and late spring green tea (LT). Twenty-six lipids and forty-five metabolites were identified as characteristic components. As for characteristic lipids, most of glycerophospholipids and acylglycerolipids have higher contents in ET. By contrast, glycoglycerolipids, sphingolipids and hydroxypheophytin a were shown higher levels in LT samples. Most of the differential metabolites identified were more abundant in ET samples. LT samples have much higher catechin, procyanidin B2, and 3',8-dimethoxyapigenin 7-glucoside contents. Based on the integration of differential lipids and metabolites, the reconstructed orthogonal partial least squares discriminant analysis (OPLS-DA) model displayed 100% correct classification rates for harvest time discrimination of green tea samples. These results demonstrated that the integration of lipidomics and metabolomics approaches is a promising method for the discrimination of tea quality.