ArticleFoods (Basel, Switzerland)2023
Widely Targeted Metabolomics Was Used to Reveal the Differences between Non-Volatile Compounds in Different Wines and Their Associations with Sensory Properties.
Article in Foods (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
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- Metabolomics and sensomics reveal non-volatile flavor dynamics in summer-autumn steamed green tea flakes processing.NPJ science of food · 2025Article
- Analysis of Volatile Organic Compounds in Wines fromFoods (Basel, Switzerland) · 2025Article
- Elucidating the Molecular Mechanisms of Physiological Fruit Abscission inPlants (Basel, Switzerland) · 2025Article
- Effects of Different Shaping Methods and Loading on Fruit Quality and Volatile Compounds in 'Beibinghong' Grapes.Foods (Basel, Switzerland) · 2025Article
- Transcriptomic and metabolomic analyses reveal the positive effect of moderate concentration of sodium chloride treatment on the production of β-carotene, torulene, and torularhodin in oleaginous red yeastFood chemistry. Molecular sciences · 2024Article
- Phenolic metabolites changes during baijiu fermentation through non-targeted metabonomic.Food chemistry: X · 2024Article
- The Metabolic and Antioxidant Activity Profiles of Aged Greek Grape Marc Spirits.Foods (Basel, Switzerland) · 2024Article
- Widely Targeted Metabolomic Analysis Revealed the Diversity in Milk from Goats, Sheep, Cows, and Buffaloes and Its Association with Flavor Profiles.Foods (Basel, Switzerland) · 2024Article
- Study on the Effect of Different Concentrations of SOFoods (Basel, Switzerland) · 2024Article
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Authors and funding
6 authors.
Funding
Abstract
In this study, metabolites from six varieties of wines, including 'Haasan' (A1), 'Zuoshaner' (A2), 'Beibinghong' (A3), 'Shuanghong' (A4), 'Zijingganlu' (A5), and 'Cabernet Sauvignon' (A6), were identified and quantified using widely targeted metabolomics analysis techniques. Based on the test results, 1172 metabolites were detected and classified into 18 categories. These include 62 amino acids, 178 alkaloids, 189 flavonoids, 106 phenols, 148 terpenoids, etc. Comparing the differential metabolites between the comparison groups of each variety, differences between varieties based on P-values and VIP values were shown. Among these differential metabolites, Trimethoprim and Crotonoside were screened out as core differential metabolites. Multiple comparisons also screened the biomarkers for each species. We used widely targeted metabolomics to reveal the differences between non-volatile compounds in different wines and their associations with sensory properties. We also used the simultaneous weighted gene co-expression network analysis (WGCNA) to correlate metabolites with sensory traits, including color difference values and taste characteristics. Two of the six key modules were screened by WGCNA for relevance to sensory traits (brown module and turquoise module). This study provides a high-throughput method for linking compounds to various sensory characteristics of food, opening up new avenues for explaining differences in different varieties of wine.
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