ArticleFood chemistry: X2025
Machine learning based on metabolomics to discriminate Wuyi rock tea production areas and "rock flavor" substances.
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 3 papers.
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Who cites it
3 citing papers in PubMed.
- High-Accuracy Prediction of Chunmee Tea Grade via DeepSpectra Model and Near-Infrared Spectroscopy.Foods (Basel, Switzerland) · 2026Article
- Optimization of ultrasound-assisted extraction of Sargassum polycystum for antitumor activity: Multi-objective optimization and mechanistic insights.Ultrasonics sonochemistry · 2026Article
- Editorial: Applications of metabolomics in the formation of food flavor.Frontiers in nutrition · 2026Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The "rock flavor" quality of Wuyi Rock Tea varies across production areas, but scientific classification criteria for production areas and a comprehensive understanding of the chemical basis of "rock flavor" remain limited. This study integrated metabolomics and machine learning to systematicallyanalyze the volatile metabolite profiles of 137 Wuyi Rock Teasamples (Zhengyan, Banyan, and Waishan productions) and established a high-precision random forest model (99 % accuracy) for production area discrimination. Feature importance analysis identified Zhengyan production markers as hotrienol, dihydroactinidiolide, benzyl alcohol, and trans-nerolidol.Banyan production markers as hotrienol, benzyl alcohol, trans-nerolidol, and heptanal,and Waishan production markers as methyl decanoate, (
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