Background: Saposhnikoviae radix (SR), a valuable Chinese medicinal plant with high medicinal and edible value, suffers from inconsistent quality caused by growth patterns, cultivation duration, and geographical origin. Methods: In this study, comprehensive volatile metabolite profiling using HS-GC-MS/MS combined with multivariate chemometrics was performed to characterize these quality-related differences. Results: In total, 7, 13, and 11 differential volatile compounds were identified for wild versus cultivated SR, cultivation duration, and geographical origin, respectively. By integrating the three comparisons, 11 recurrent differential compounds were selected for network pharmacology and molecular docking analyses. trans-3-Nonen-2-one, benzaldehyde, and Octanoic acid were predicted to interact with key targets, including TNF, IL1B, ALB, EGFR, and CASP3, which were mainly enriched in inflammation- and pain-related pathways, including the PI3K-Akt signaling pathway, apoptosis, and the HIF-1 signaling pathway. Molecular docking further supported favorable predicted interactions between the selected compounds and core targets. Conclusions: Overall, this study reveals volatile metabolite variation associated with major quality-related factors of SR and identifies candidate bioactive and quality-associated volatile compounds. The integration of volatile metabolite profiling, chemometrics, network pharmacology, and molecular docking provides a complementary strategy for the comprehensive quality evaluation of SR and offers a reliable reference for quality control research on other medicinal Apiaceae species.

Sojae Semen Praeparatum (SSP) is a traditional fermented soybean product with both dietary and medicinal uses in China. However, the dynamic metabolic changes and microbial community succession during SSP fermentation remain insufficiently characterized. In this study, untargeted metabolomics based on UHPLC-HRMS (Ultra-high-performance liquid chromatography-high-resolution mass spectrometry) was integrated with 16S rRNA gene and ITS amplicon sequencing to investigate metabolite remodeling, bacterial and fungal community succession, and their potential associations during SSP fermentation. Clear stage-dependent separation of metabolite profiles was observed, and 22,343 metabolic features were detected, of which 4281 were putatively annotated. Differential metabolites were mainly assigned to amino acids, dipeptides, lipids, carbohydrates, and isoflavones. Sucrose and other carbohydrates were progressively consumed during fermentation, while N-acetyl amino acids, short dipeptides, proline betaine and a range of lipid metabolites built up towards the later stages. The microbiota did not drift at random: amplicon sequencing resolved a clear successional sequence in both kingdoms. Bacteria converged on genera within the Enterobacteriaceae—mainly Enterobacter, Kosakonia and Citrobacter—whereas the fungi started out dominated by Rhizopus and ended in a co-dominant configuration of Aspergillus, Mucor and several minor taxa. When the two data sets were linked, the dominant taxa were associated with metabolites assigned to nitrogen, lipid and phenolic pathways. Procrustes analysis suggested a potential association between the fungal community and the metabolome, whereas the bacterial association was marginal; however, the difference in coupling strength between the two was not directly tested. These results provide preliminary evidence and a foundation for quality control and process optimization, but require validation across independent batches.