Exploration of chemical markers using a metabolomics strategy and machine learning to study the different origins of Ixeris denticulata (Houtt.) Stebb

Abstract

As a generally edible plant, Ixeris denticulata (Houtt.) Stebb is widely distributed in China. Its medicinal value has attracted much attention in recent years. However, the chemical markers that cause quality and taste differences in I. denticulata from different regions are currently unclear. In this study, samples from 8 different origins were collected and analysed by UPLC-Q-TOF/MS. A metabolomics data processing strategy and machine learning method were established to explore the reasons for the difference in quality and taste of different origins from the perspective of chemical composition. With the established strategy, 10 characteristic chemical markers were identified that could be used to distinguish the origins of I. denticulata. The strategy proposed in this study could provide a certain basis for quality control and reasonable consumption of I. denticulata and additional food and medicinal homologous species.

Keywords: 4-Dicaffeoylquinic acid (PubChemCID: 9798666); Chemical markers; Chicoric acid (PubChemCID: 5281764); Chlorogenic acid (PubChemCID: 1794427); Citric acid (PubChemCID: 311); Esculin hydrate (PubChemCID: 16211025); Gallocatechin (PubChemCID: 65084); Ixerin Z (PubChemCID: 10740895); Ixeris denticulata (Houtt.) Stebb; Kaempferol (PubChemCID: 5280863); Kaempferol-3-O-glucuronide (PubChemCID: 5318759); Metabolomics; Neochlorogenic acid (PubChemCID: 5280633); Support Vector Machine; UPLC-Q-TOF/MS.