ArticleFood chemistry: X2025
Predicting the low-level and extremely low-threshold compounds in Baijiu: uniform manifold approximation and projection.
Article in Food chemistry: X, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- 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.Foods (Basel, Switzerland) · 2026Article
- Machine Learning and SHAP Feature Analysis: Classification Model for Aroma Components in Green Plum Wine.Foods (Basel, Switzerland) · 2026Article
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the flavor analysis of Baijiu, the identification of compounds exhibiting high flavor dilution factors but displaying minimal or undetectable response signals in analytical measurements, remains a significant challenge in current research. To clearly elucidate the correlation between the structure of odorants and their odors in Baijiu, a "compound-aroma" database consisting of 646 compounds and their known associated odors (70 aroma descriptors) has been compiled. Each individual compound was coded with 1024-bit molecular fingerprints and analyzed by K-means and uniform manifold approximation and projection (UMAP). Moreover, by calculating the presence or the absence of odor molecular substructures, associations for both odor notes and chemical groups of the aroma compounds in Baijiu were revealed, and an indicative model diagram was constructed. Finally, a strong roasted odor of Baijiu, which presented at the retention index of 1324-1334 with no distinct response signal, has been successfully identified as 2,5-dimethylpyrazine or 2,6-dimethylpyrazine by using the aforementioned model.
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