Determination of lipophilic metabolites for species discrimination and quality assessment of nine leafy vegetables

Abstract

The lipophilic compounds in nine vegetables consumed in Korea were characterized for diversity in phytochemical content. We also analyzed the relationships among these compounds in terms of their contents. The profiles of 18 lipophilic compounds in the leaves were subjected to data-mining processes, including principal component analysis (PCA), Pearson’s correlation analysis, hierarchical clustering analysis (HCA), and partial least squares discriminant analysis (PLS-DA). These species could be distinguished by means of the PCA results. HCA of these phytochemicals resulted in clusters derived from closely related biochemical pathways. PLS-DA showed significant separation among extracts from the following four families: Amaranthaceae, Asteraceae, Brassicaceae, and Malvaceae. The major metabolites that facilitated differentiation in the PLS-DA model were campesterol, β-sitosterol, β-amyrin, stigmasterol, cholesterol, octacosanol (c28), α-amyrin, and hexacosanol (c26). Chard contained high levels of triacontanol (c30), which was positively correlated with the c28 content (r = 0.746, p < 0.0001). Stigmasterol, α-amyrin, and β-amyrin contents were higher in Asteraceae species including chicon, lettuce, and oak than other plant families. These results demonstrate the utility of metabolic profiling, combined with multivariate analysis, for discrimination of vegetable species as well as evaluation of food quality.