Abstract
Panax vietnamensis, indigenous to Vietnam and southern China, is classified into three subspecies: Panax vietnamensis Ha et Grushv. (PVV), Panax vietnamensis var. fuscidiscus (PVF), and Panax vietnamensis var. langbianensis (PVL). A method to distinguish these varieties in their intact form is absent, which poses a possible risk of misclassification. Here, we aimed to devise a plant metabolite-based discrimination algorithm for the three varieties, without causing significant damage to individual plants. A multivariate analysis on mass spectral data of PVV, PVF, and PVL revealed that a peak at m/z 426, which was subsequently identified as an indole alkaloid glycoside, was exclusive to PVF and therefore clearly distinguished PVF from PVV and PVL. Additionally, global metabolic profiling was conducted to elucidate the discrimination markers between PVV and PVL, and lysophospholipids and hydroxy fatty acids were selected as potential discrimination markers. The performance of these markers was validated by cross-validation using machine learning algorithm.