ArticleNPJ science of food2023
Metabolomics integrated with machine learning to discriminate the geographic origin of Rougui Wuyi rock tea.
Article in NPJ science of food, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Metabolomic signatures and machine learning-based geographical origin discrimination of fresh tea leaves from Enshi Prefecture.Food chemistry: X · 2026Article
- Long-Tea-CLIP: An Expert-Level Multimodal AI Framework for Fine-Grained Green Tea Grading Across Five Sensory Dimensions.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Geographical Origin Traceability of Tea (Foods (Basel, Switzerland) · 2026Review
- Machine Learning and SHAP Feature Analysis: Classification Model for Aroma Components in Green Plum Wine.Foods (Basel, Switzerland) · 2026Article
- Deep learning enable precision authentication of seasonal and processing signatures in tieguanyin tea.NPJ science of food · 2026Article
- Seasonal and processing differences in nonvolatile compounds and volatile aroma of teas from Zhaoyuan, China: insight into "spring green, summer black, autumn dark" quality pattern.Food chemistry: X · 2026Article
- Comparison of Flavor Characteristics and Metabolite Basis of Oolong Tea from Six Different Tea Plant Cultivars Under High- and Low-Altitude Conditions.Plants (Basel, Switzerland) · 2025Article
- Advances in predicting human olfactory perception: from data acquisition to computational models.RSC advances · 2025Review
- Discrimination of Dried Ginger and Its Different Processed Products: Untargeted Metabolomics, Network Pharmacology, and Machine Learning.ACS omega · 2025Article
- Machine learning based on metabolomics to discriminate Wuyi rock tea production areas and "rock flavor" substances.Food chemistry: X · 2025Article
- Characterization of key astringent compounds and optimization of the fixation process of early tea in Chuanyu region.NPJ science of food · 2025Article
- The Impact of Harvest Season on Oolong Tea Aroma Profile and Quality.Plants (Basel, Switzerland) · 2025Article
- Exploring the taste code of light-withered tea: the mechanism of nonvolatile metabolite changes in LED light-withered oolong tea (Food chemistry: X · 2025Article
- Characterization and feature selection of volatile metabolites in Yangxian pigmented rice varieties through GC-MS and machine learning algorithms.Frontiers in nutrition · 2025Article
- Volatilomics and Macro-Composition Analyses of Primary Wuyi Rock Teas of Rougui and Shuixian Cultivars from Different Production Areas.Plants (Basel, Switzerland) · 2024Article
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Authors and funding
17 authors.
Funding
Abstract
The geographic origin of agri-food products contributes greatly to their quality and market value. Here, we developed a robust method combining metabolomics and machine learning (ML) to authenticate the geographic origin of Wuyi rock tea, a premium oolong tea. The volatiles of 333 tea samples (174 from the core region and 159 from the non-core region) were profiled using gas chromatography time-of-flight mass spectrometry and a series of ML algorithms were tested. Wuyi rock tea from the two regions featured distinct aroma profiles. Multilayer Perceptron achieved the best performance with an average accuracy of 92.7% on the training data using 176 volatile features. The model was benchmarked with two independent test sets, showing over 90% accuracy. Gradient Boosting algorithm yielded the best accuracy (89.6%) when using only 30 volatile features. The proposed methodology holds great promise for its broader applications in identifying the geographic origins of other valuable agri-food products.
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Registered trials
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