Wine Analysis and Authenticity Using 1H-NMR Metabolomics Data: Application to Chinese Wines
- 383 Downloads
A NMR-based metabolomics method was developed to semiautomatically quantify the main components of wine. The method was applied to discriminate wines from two regions of China, Shanxi and Ningxia, which were produced by 6 wineries and for 6 vintages. Two different cultivars, Cabernet Sauvignon and Beihong, were used for winemaking. The method allowed the quantification of 33 metabolites including sugars, amino acids, organic acids, alcohols, and phenolic compounds. Depending on the compounds, the LOD values were in the range of 0.6 to 116 mg/L. The results showed that NMR-based metabolomics combined with multivariate statistical analysis allowed wine separation as a function of terroir and cultivar. Nevertheless, wine differentiation as a function of wineries and ageing would need to be examined more carefully.
KeywordsWine composition Wine analysis qNMR Authenticity Traceability NMR-based metabolomics
The work was supported by the Bordeaux Metabolome Facility and MetaboHUB (ANR-11-INBS-0010 project).
This study was funded by the Conseil Régional d’Aquitaine, Conseil Interprofessionnel du Vin de Bordeaux (CIVB) and FranceAgriMer program (grant number 2014–0785).
Compliance with Ethical Standards
Conflict of Interest
Louis Gougeon declares that he has no conflict of interest. Gregory Da Costa declares that he has no conflict of interest. Inès Le Mao declares that she has no conflict of interest. Wen Ma declares that she has no conflict of interest. Pierre-Louis Teissedre declares that he has no conflict of interest. François Guyon declares that he has no conflict of interest. Tristan Richard declares that he has no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
- Cobas C, Seoane F, Domínguez S, Sykora S, Davies AN (2011) A new approach to improving automated analysis of proton NMR spectra through global spectral deconvolution (GSD). Spectrosc Eur 23:26–30Google Scholar
- Godelmann R, Fang F, Humpfer E, Schütz B, Bansbach M, Schäfer H, Spraul M (2013) Targeted and nontargeted wine analysis by 1H NMR spectroscopy combined with multivariate statistical analysis. Differentiation of important parameters: grape variety, geographical origin, year of vintage. J Agric Food Chem 61:5610–5619CrossRefGoogle Scholar
- Guyon F, Gaillard L, Salagoïty M-H, Médina B (2011) Intrinsic ratios of glucose, fructose, glycerol and ethanol 13C/12C isotopic ratio determined by HPLC-co-IRMS: toward determining constants for wine authentication. Anal Bioanal Chem 401:1551–1558. https://doi.org/10.1007/s00216-011-5012-5 CrossRefPubMedGoogle Scholar
- Hu B, Yue Y, Zhu Y, Wen W, Zhang F, Hardie JW (2015) Proton nuclear magnetic resonance-spectroscopic discrimination of wines reflects genetic homology of several different grape (V. vinifera L.) cultivars. PLoS One 10:e0142840. https://doi.org/10.1371/journal.pone.0142840 CrossRefPubMedPubMedCentralGoogle Scholar