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

Abstract

The production season is one of the judgment standards of the green tea quality and spring tea is generally considered of higher quality. Moreover, early spring tea is usually more precious and sells for a higher price. Therefore, 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.