Çoklu-omik ve makine öğrenimi, fermente ciba biberinde çeşit kaynaklı lezzet farklılaşmasının altında yatan mekanizmaları ortaya koyuyor

Özet (abstract)

Ciba chili quality is strongly influenced by raw material characteristics, but the cultivar-driven mechanisms underlying quality differentiation remain unclear. Ciba chili made from Inner Yellow New Generation (ICP), Lantern (LCP), and Devil's (DCP) peppers was comprehensively investigated using physicochemical analysis, GC-IMS, UHPLC-MS/MS untargeted metabolomics, 16S rRNA sequencing, and machine learning. Cultivar specificity profoundly shaped fermentation results. Volatile profiling revealed late-stage acid and ester enrichment in LCP, higher aldehyde retention alongside earlier ester formation in ICP, and an enrichment of alcohols, ketones, furans, and pyrazines in DCP. Furthermore, untargeted metabolomics showed that LCP, ICP, and DCP were enriched in organic oxygen-containing compounds, organic acids and organoheterocyclic compounds, and lipids and benzenoids, respectively. A random forest model utilizing these metabolites showed superior classification performance, and SHAP analysis further identified 20 core discriminatory metabolites contributing to cultivar classification. KEGG analysis traced flavor differentiation to phenylpropanoid metabolism, lipid oxidation, purine cofactor metabolism, and l -glutamine-mediated nitrogen metabolism. Cultivar-dependent bacterial succession was observed: DCP was dominated by Lactiplantibacillus , LCP by Weissella , and ICP showed delayed, less coordinated Weissella dominance. Crucially, correlation analysis revealed bacteria metabolite networks: LCP exhibited strong negative associations, ICP showed a balanced network linking acidification, nitrogen metabolism, and flavor precursors, while DCP displayed pronounced coupling associated with complex aromas and pungency. This study establishes an integrated multi-omics and machine learning framework to elucidate how chili cultivar drives quality differentiation, providing theoretical support for cultivar selection and flavor oriented industrial fermentation.

Yazarların özeti; kaynağından alınmıştır. Food Chemistry X, 2026 · DOI ↗