Decoding the Flavor Structure of Jiang-Flavor Low-Alcohol Base Baijiu: A Machine Learning-Driven Approach to Reveal the Flavor Evolution Patterns and Key Quality Control Nodes.

Jiaxing Geng, Yongguang Huang

Abstract read

In one paragraph

Article in Foods (Basel, Switzerland), 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

2 authors.

Jiaxing GengCollege of Liquor and Food Engineering, Guizhou University, Guiyang 550025, China.

Yongguang HuangKey Laboratory of Fermentation Engineering and Biological Pharmacy of Guizhou Province, College of Liquor and Food Engineering, Guizhou University, Guiyang 550025, China.

Funding

Guizhou Fund Project ZK[2024] Key Project No. 016Guizhou Science and Technology Achievement Project No. [2023] 477Guizhou Science and Technology Achievement Project LH [2025] Key Project No. 008National Natural Science Foundation No. 32360571Program of National Natural Science Foundation Grant No. 324727319Qiankehe Zhongyindi [2026]006Research on the Brewing Technology of Muhuang Characteristic Style Jiang-flavor Baijiu Qiankehechengguo [2023] 477

6 · The paper itself

Abstract

Low-alcohol base baijiu, a by-product of Jiang-flavor baijiu production, contains abundant flavor compounds, yet its flavor structure remains insufficiently understood, limiting its high-value utilization. This study integrated flavoromics with interpretable machine learning to characterize the flavor structure of Jiang-flavor low-alcohol base baijiu and identify its key driving factors. During distillation, ethanol decreased from 38.67% to 6.50% (

Indexed as

classification modelflavor markerslow-alcohol base baijiuSHAP analysisvolatile flavor compounds

Identifiers

PMID42279680

DOI10.3390/foods15111891

PMCPMC13257113

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.