Nontargeted metabolomics coupled with multivariate modelling techniques for discrimination of (Batal.) Ijinskaja leaves from different geographic altitudes.

Altitude-associated nutrition-compositional evaluation is critical for quality control and value determination of plants. Herein, an exploratory study was applied to investigate the differences in the metabolites of (CP) leaves from different altitudes (200-1000 m) using a UPLC-QTOF-MS-based metabolomics method, employed to create models for discrimination of CP leaves. On the one hand, 70 metabolites exhibiting significant distinctions within various components in different altitude environments were detected and identified, of which majority showed a close connection. High altitude environments with a decrease in temperature accompanied by enhanced UV-B radiation significantly influenced the profile of flavonoids and organic acids. On the other hand, the PLS-DA model ( = 0.994 and = 0.990) with the VIP variable selection method and -value were selected to characterize fifteen potential differential metabolites. Moreover, the DD-SIMCA model involving the above-mentioned differential compounds showed both good specificity and accuracy of 100%. These results provide guidance for the discrimination of CP leaves from different geographic altitudes, which may be extended to improve the growing conditions of CP leaves.