AUTHOR=Cui Hui-Na , Gu Hui-Wen , Li Zhi-Quan , Sun Weiqing , Ding Baomiao , Li Zhenshun , Chen Ying , Long Wanjun , Yin Xiao-Li , Fu Haiyan 

TITLE=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

JOURNAL=Frontiers in Sustainable Food Systems

VOLUME=Volume 7 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/sustainable-food-systems/articles/10.3389/fsufs.2023.1119314

DOI=10.3389/fsufs.2023.1119314

ISSN=2571-581X

ABSTRACT=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.