Evidence map›Paper›PMID 42787968›Full record

ArticleFood chemistry: X2026

Multi-omics and machine learning reveal the mechanisms underlying cultivar-driven flavor differentiation in fermented ciba chili.

Tianyang Wang, Yiling Xiong, Changbo Gao, Zhaohui Huang, Zihao Liu, Defu Xu, Huachang Wu, Ju Guan, Liang Zhang, Bo Zu and 1 more

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In one paragraph

Article in Food chemistry: X, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Tianyang WangCollege of Life Sciences and Agriculture & Forestry, Southwest University of Science and Technology, Mianyang 621000, China.
Yiling XiongCuisine Science Key Laboratory of Sichuan Province, Sichuan Tourism University, Chengdu 610100, China.
Changbo GaoCollege of Life Sciences and Agriculture & Forestry, Southwest University of Science and Technology, Mianyang 621000, China.
Zhaohui HuangCollege of Life Sciences and Agriculture & Forestry, Southwest University of Science and Technology, Mianyang 621000, China.
Zihao LiuCollege of Life Sciences and Agriculture & Forestry, Southwest University of Science and Technology, Mianyang 621000, China.
Defu XuCollege of Life Sciences and Agriculture & Forestry, Southwest University of Science and Technology, Mianyang 621000, China.
Huachang WuCuisine Science Key Laboratory of Sichuan Province, Sichuan Tourism University, Chengdu 610100, China.
Ju GuanCuisine Science Key Laboratory of Sichuan Province, Sichuan Tourism University, Chengdu 610100, China.
Liang ZhangCollege of Life Sciences and Agriculture & Forestry, Southwest University of Science and Technology, Mianyang 621000, China.
Bo ZuCollege of Life Sciences and Agriculture & Forestry, Southwest University of Science and Technology, Mianyang 621000, China.
Xiaoming ChenCollege of Life Sciences and Agriculture & Forestry, Southwest University of Science and Technology, Mianyang 621000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

Indexed as

Chili varietiesCiba chiliFlavoromicsMachine learningMetabolic pathwayMetabolomics

Identifiers

PMID42787968
PMCPMC13602777

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