Widely Targeted Metabolomics Was Used to Reveal the Differences between Non-Volatile Compounds in Different Wines and Their Associations with Sensory Properties

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 targete...

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Bibliographic Details
Published in:Foods 2023-01, Vol.12 (2), p.290
Main Authors: Cao, Weiyu, Shu, Nan, Wen, Jinli, Yang, Yiming, Wang, Yanli, Lu, Wenpeng
Format: Article
Language:English
Subjects:
Amino acids
Biomarkers
Cell cycle
color difference analysis
Consumers
Fermentation
Flavonoids
Food
Food science
Gene expression
Metabolism
Metabolites
Metabolomics
Modules
Network analysis
non-volatile metabolites
Phenols
Quality standards
sensory evaluation
Sensory properties
Terpenes
Trimethoprim
Volatile compounds
weighted gene co-expression network analysis
Wines
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Summary: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.
ISSN:2304-8158
2304-8158
DOI:10.3390/foods12020290