Gas Chromatography/Mass Spectrometry-Based Metabolic Profiling and Differentiation of Ginseng Roots According to Cultivation Age Using Variable Selection

Abstract

Ginseng roots are an important herbal resource worldwide, and the adulteration of ginseng with age is recognized as a serious problem. It is therefore crucial to develop objective criteria or standard protocols for differentiating ginseng root samples according to their cultivation age. The reported study used GC/MS combined with multivariate statistical analysis with variable selection to obtain metabolic profiling and an optimal partial least squares-discriminant analysis (PLS-DA) model for the differentiation of ginseng according to cultivation age. Relative levels of various metabolites, such as amino acids, alcohols, fatty acids, organic acids, and sugars, were measured for various ginseng cultivation ages. Increasing cultivation age resulted in the production of higher levels of panaxynol and panaxydol, which are active polyacetylene compounds in ginseng. In addition, optimized PLS-DA models for the prediction of ginseng age were obtained by selecting variables based on a variable importance in the projection cut-off value of 1.3. Proline, glucaric acid, mannose, gluconic acid, glucuronic acid, myoinositol, panaxydol, and panaxynol are suggested as key and relevant compounds with which to differentiate the age of ginseng samples. The findings of this study suggest that GC/MS-based metabolic profiling can be used to differentiate ginseng samples according to cultivation age.