Food Analytical Methods

, Volume 12, Issue 4, pp 956–965 | Cite as

Wine Authenticity by Quantitative 1H NMR Versus Multitechnique Analysis: a Case Study

  • Louis Gougeon
  • Gregory da Costa
  • Tristan Richard
  • François GuyonEmail author


Food counterfeit is a major issue for food industries. In the case of wines, there can be multiple forgeries such as geographical, vintage, or varietal mislabeling. For the last 10 years, the use of quantitative 1H NMR (q-NMR) for food authentication has experienced an enormous increase. This study was based on a comparative evaluation of the results obtained for three sets of authentic high-valued wines and suspected wines. Two methodologies have been followed: (i) the usual wine analysis, based on the utilization of multiple techniques, which is the traditional way of analysis for wine authentication and (ii) q-NMR profiling, the alternative proposed method. For wine comparison, an original approach based on similarity score (S-score) by analogy to the Z-score calculation was developed. A limit of four S-scores outside the range − 2/2 has been, arbitrary, defined to reveal that wines are different using q-NMR analysis. Data treatments allowed the extraction of discriminating parameters, some of which were common to both approaches while others could be linked to the techniques’ capabilities showing the complementarity of the two approaches. This study demonstrated the potential of q-NMR in wine authentication by comparative analysis with authentic samples. The q-NMR alternative method has also the advantages of rapidity (around 20 min including sample preparation, analysis, and data treatment) and low volume (0.5 mL), which is a prerequisite for analyzing priceless wines.


Food authenticity Food quality control Wine Classical wine analysis 1H NMR q-NMR Chemometric 



Château Mouton Rothschild is warmly thanked for their authorization to publish these results. The authors thank the SCL’s team of Bordeaux-Pessac for performing usual analysis: Laetitia Gaillard for stable isotope analyses; Ludovic Pottier, François Auger, Claude Roux, and Nathalie Diet for ICP-AES; Carole Lagrèze and André Domec for HPCE; and Rodolphe Robin, Maryse Viateau, and Sebastien Raud for GC and standard wine analysis. Josep Valls-Fonayet (ISVV) is greatly acknowledged for his comments and advises.

Funding Information

This study is financially supported by the Conseil Régional d’Aquitaine, the Conseil Interprofessionnel du Vin de Bordeaux (CIVB), and FranceAgriMer program. The work was supported by the Bordeaux Metabolome Facility and MetaboHUB (ANR-11-INBS-0010 project).

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. Tristan Richard declares that he has no conflict of interest. François Guyon declares that he has no conflict of interest.

Ethical Approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed Consent

Not applicable.

Supplementary material

12161_2018_1425_MOESM1_ESM.docx (353 kb)
Fig. S1 (DOCX 353 kb)
12161_2018_1425_MOESM2_ESM.docx (3 kb)
Table S1 (DOCX 3.416 kb)


  1. Amargianitaki M, Spyros A (2017) NMR-based metabolomics in wine quality control and authentication. Chem Biol Technol Agric 4:9CrossRefGoogle Scholar
  2. Anastasiadi M, Zira A, Magiatis P, Haroutounian SA, Skaltsounis AL, Mikros E (2009) 1H NMR-based metabonomics for the classification of Greek wines according to variety, region, and vintage. Comparison with HPLC data. J Agric Food Chem 57:11067–11074CrossRefGoogle Scholar
  3. Bharti SK, Roy R (2012) Quantitative 1H NMR spectroscopy. TrAC Trends Anal Chem 35:5–26CrossRefGoogle Scholar
  4. Caruso M, Galgano F, Morelli MAC, Viggiani L, Lencioni L, Giussani B, Favati F (2012) Chemical profile of white wines produced from ‘Greco Bianco’ grape variety in different Italian areas by nuclear magnetic resonance (NMR) and conventional physicochemical analyses. J Agric Food Chem 60:7–15CrossRefGoogle Scholar
  5. Cobas C, Seoane F, Dominguez 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
  6. Consonni R, Cagliani LR, Guantieri V, Simonato B (2011) Identification of metabolic content of selected Amarone wine. Food Chem 129:693–699CrossRefGoogle Scholar
  7. Fotakis C, Kokkotou K, Zoumpoulakis P, Zervou M (2013) NMR metabolite fingerprinting in grape derived products : an overview. Food Res Int 54:1184–1194CrossRefGoogle Scholar
  8. 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 61:5610–56169CrossRefGoogle Scholar
  9. Godelmann R, Kost C, Patz CD, Ristow R, Wachter H (2016) Quantitation of compounds in wine using 1H NMR spectroscopy: description of the method and collaborative study. J AOAC Int 99:1295–1304CrossRefGoogle Scholar
  10. Gougeon L, Da Costa G, Le Mao I, Ma W, Teissedre PL, Guyon F, Richard T (2018) Wine analysis and authenticity using 1H NMR metabolomics data: application to Chinese wines. Food Anal Methods 11:3425–3434CrossRefGoogle Scholar
  11. Huang Z, Ough CS (1989) Effect of vineyard locations, varieties, and rootstocks on the juice amino acid composition of several cultivars. Am J Enol Vitic 40:135–139Google Scholar
  12. Larive CK, Barding GA, Dinges MM (2014) NMR spectroscopy for metabolomics and metabolic profiling. Anal Chem 87:133–146CrossRefGoogle Scholar
  13. López-Rituerto E, Savorani F, Avenoza A, Busto JH, Peregrina JM, Enegelsen SB (2012) Investigation of la Rioja terroir for wine production using 1H NMR metabolomics. J Agric Food Chem 60:3452–3461CrossRefGoogle Scholar
  14. Mardones C, Hitschfeld A, Contreras A, Lepe K, Gutiérrez L, von Baer D (2005) Comparison of shikimic acid determination by capillary zone electrophoresis with direct and indirect detection with liquid chromatography for varietal differentiation of red wines. J Chrom A 1085:285–292CrossRefGoogle Scholar
  15. Medina B, Salagoity MH, Guyon F, Gaye J, Hubert P, Guillaume F (2013) Using new analytical approaches to verify the origin of wine. In “New Analytical Approaches for Verifying the Origin of Food” ED. P. Brereton, Woodhead publishing limited, 149–188Google Scholar
  16. OIV a Compendium of international methods of analysis: alcoholic strength by volume.-OIV-MA-AS312-01A at
  17. OIV b Compendium of international methods of analysis: dosage of sugars in wine by HPLC. OIV-MA-AS311–03 at
  18. OIV c Compendium of international methods of analysis: volatile Acidity. OIV-MA-AS313–02 at
  19. OIV d Compendium of international methods of analysis: analysis of volatile compounds in wines by gas chromatography. OIV-MA-AS315–27 at
  20. OIV e Compendium of international methods of analysis: determination of the principal organic acids of wines and sulphates by capillary electrophoresis. OIV-MA-AS-313-19 at
  21. OIV f Compendium of international methods of analysis: analysis of mineral elements in wines using ICP - AES (inductively coupled plasma / atomic emission spectrometry). OIV-MA-AS311–05 at
  22. OIV g Compendium of international methods of analysis : determination of the deuterium distribution in ethanol derived from fermentation of grape musts, concentrated grape musts, grape sugar (rectified concentrated grape musts) and wines by application of nuclear magnetic resonance (SNIF-NMR/ RMN-FINS). OIV-MA-AS311–05 at
  23. OIV h Compendium of international methods of analysis: determination by isotope ratio mass spectrometry 13C/12C of wine ethanol or that obtained through the fermentation of must, concentrated musts or grape sugar. OIV-MA-AS312–06 at
  24. OIV i Compendium of international methods of analysis: method for 18O/16O ratio determination of water in wines and must. OIV-MA-AS2–12 at
  25. OIV j Compendium of international methods of analysis: method for sulfur dioxyde. OIV-MA-AS323-04A at
  26. Pauli GF, Gödecke T, Jaki BU, Lankin DC (2012) Quantitative 1H NMR. Development and potential of an analytical method: an update. J Nat Prod 75, 834–851Google Scholar
  27. PereiraGE, GaudillereJ, van LeeuwenC, HilbertG, MaucourtM, DebordeC, MoingA, RolinD (2007) 1H NMR metabolic profiling of wines from three cultivars, three soil types and two contrasting vintages. J. Int Sci Vigne Vin41, 103–109Google Scholar
  28. Schlesier K, Fauhl-Hassek C, Forina M, Cotea V, Kocsi E, Schoula R, van Jaarsveld F, Wittkowski R (2009) Characterization and determination of the geographical origin of wines. Part I: overview. Eur Food Res Technol 230, 1–14Google Scholar
  29. Simmler C, Napolitano JG, McAlpine JB, Chen SN, Pauli GF (2014) Universal quantitative NMR analysis of complex natural samples. Curr Opin Biotechnol 25:51–59CrossRefGoogle Scholar
  30. Smeyers-Verbeke J, Jäger H, Lanteri S, Brereton P, Jamin E, Fauhl-Hassek C, Forina M, Römisch U (2009) Characterization and determination of the geographical origin of wines. Part II: descriptive and inductive univariate statistics. Eur Food Res Technol 230, 15–29Google Scholar
  31. Son HS, Kim KM, van den Berg F, Hwang GS, Park WM, Lee CH, Hong YS (2008) 1H nuclear magnetic resonance-based metabolomic characterization of wines by grape varieties and production areas. J Agric Food Chem 56:8007–8016CrossRefGoogle Scholar
  32. Son HS, Hwang GS, Ahn HJ, Park WM, Lee CH, Hong YS (2009a) Characterization of wines from grape varieties through multivariate statistical analysis of 1H NMR spectroscopic data. Food Res Int 42:1483–1491CrossRefGoogle Scholar
  33. Son HS, Hwang GS, Kim KM, Ahn HJ, Park WM, van den Berg F, Hong YS, Lee CH (2009b) Metabolomic studies on geographical grapes and their wines using 1H NMR analysis coupled with multivariate statistics. J Agric Food Chem 57:1481–1490CrossRefGoogle Scholar
  34. Suarez MA, Polo MC, Llugano C (1979) Etude de la composition de vins mousseux pendant la prise de mousse et au cours du vieillissement en bouteilles. I. Etude des acides aminés libres, du glycérol, des sucres et des acides organiques. Connaiss Vigne Vin 3:199–217Google Scholar
  35. Viggiani L, Castiglione Morelli MA (2008) Characterization of wines by nuclear magnetic resonance: a work study on wines from the Basilicata region in Italy. J Agric Food Chem 56:8273–8279CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Louis Gougeon
    • 1
  • Gregory da Costa
    • 1
  • Tristan Richard
    • 1
  • François Guyon
    • 2
    Email author
  1. 1.Univ. Bordeaux, ISVV, EA 4577, USC 1366 INRA, Unité de RechercheVillenave d’OrnonFrance
  2. 2.Service Commun des LaboratoiresPessacFrance

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