Investigating the impact of geographical origin and harvesting season on the quality of Hypericum perforatum L. using LC-MS, GC-MS, and ICP-MS technologies in conjunction with random forest model

In this study, liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS), and inductively coupled plasma mass spectrometry (ICP-MS) were applied to analyze secondary metabolites and elemental content in Hypericum perforatum L. (HPL). Following this, random forest (RF) model was established to highlight the differences among HPL originating from various sources. SHapley Additive exPlanations (SHAP) values were utilized to elucidate the contribution of each variable. Ultimately, the levels of these differential metabolites and elements were analyzed to evaluate their impact on quality. The established RF models exhibit excellent classification accuracy and can effectively identify HPL samples from different sources. From the perspective of secondary metabolite content, HPL harvested in July from Xinjiang demonstrated superior quality compared to samples collected in September, with both outperforming HPL harvested from southwestern China. In terms of elemental composition, all collected HPL samples complied with the heavy metal content standards as stipulated by the pharmacopoeia.