How to Differentiate Bordeaux Red Wines to Prevent Wine Fraud

Certain French geographical indications are granted the prized French certification appellation d'origine contrôlée (AOC; "controlled designation of origin") for a range of food and drink, including wines.

For a wine produced in Bordeaux to acquire AOC labeling, it has to satisfy Bordeaux's strict regional wine rules. These dictate where and how the grapes are grown, e.g., no irrigation, which grape varieties may be grown, e.g., no chardonnay grapes, and the level of alcohol a wine may contain (a maximum of 14%). Wines that do not meet these specifications have to be sold as "table wine."

Within Bordeaux, the exact area where the grapes are grown is more important than the varietal of grape used. For instance, wines from grapes grown on one side of the River Gironde are distinguished from those grown on the other side.

Cabernet Sauvignon tends to dominate Bordeaux wines sourced from the left bank, whereas grape-growing villages found on the right bank have historically made wines dominated with Merlot. For wine producers in Bordeaux, the ability to distinguish wines from different regions is highly sought after.

In the classification of wines from different grape varieties, geographical origins, or vintages¹ metabolomic nuclear magnetic resonance (NMR) analysis has proved to be effective, which raised the question of whether NMR was able to distinguish between wines from different areas within the Bordeaux region.

Bordeaux wine

Bordeaux accounts for 46% of the total value of exports of French Protected Designation of Origin (PDO) wines and is a leading wine-producing area. There are almost sixty PDO areas in Bordeaux that are categorized into five main subdivisions: Libournais, Médoc, Entre-deux-Mers, Graves and Blaye-Bourg.

The cultivation of red grapes is dedicated to three-quarters of Bordeaux vineyards, with Merlot being the main cultivar. Cabernet Franc and Cabernet Sauvignon are also widely utilized. Minor red grape types like Petit Verdot, Malbec, or Carmenere may be added to some blends.

The value Bordeaux places on its wines is demonstrated in the cumbersome classification system. This came about from a request from Napoleon III to identify the best Bordeaux wines for the 1855 International Exposition in Paris.

The categorization of wines by price and quality still stands today, but a number of additional regionally driven classification systems have since been developed.

Wine classification

In combination with advanced statistical and mathematical methods, quantitative analytical data have been widely utilized in the classification of wine².

Metabolomic data have been gathered by utilizing a variety of gas and liquid chromatography techniques coupled with a spectroscopic detective and quantification methods like Raman spectroscopy, mass spectroscopy, or nuclear magnetic resonance spectroscopy (NMR)³.

Quantitative ¹H NMR spectrometry especially has proven to be a useful tool for establishing the provenance of a wine⁴ including geographic origin⁵. NMR has been utilized effectively to confirm the authenticity of wines^6,7. Most recently, the method has been investigated for the characterization and discrimination of Bordeaux red wines⁸.

NMR characterization of Bordeaux red wines

Samples of 224 red wines from the main French DPO regions (Languedoc-Roussillon, Burgundy, Bordeaux, Côtes du Rhône, Beaujolais, and Loire Valley) and of different vintages (2004–2017) were assessed using quantitative NMR with a Bruker 600 MHz spectrometer.

TMPS was utilized in order to align all ¹H NMR spectra, and an exponential weighting was applied prior to Fournier transformation using Bruker Topspin^® software⁸.

Next, multivariate statistical analysis was utilized to examine if NMR fingerprinting could be employed to identify Bordeaux wines from the other French PDO wines and distinguish between wines from six different Bordeaux appellations (Libournais, Blaye and Bourg, Entre-deux-Mers, Bordeaux generic, Graves, and Médoc).

The effects of wine evolution during bottle aging and vintage on the NMR spectra of Bordeaux red wines were assessed. In the wine samples, 40 compounds were established. Bordeaux wines were correctly distinguished from the other French wines and classified with 95% accuracy⁸.

Compared with other French wines, the metabolite profile was highly specific for Bordeaux red wines, including higher levels of phenethyl alcohol, proline, and succinic and gallic acids.

The discrimination of wines from the two major Bordeaux sub-regions, Médoc and Libournais, was also permitted by NMR spectrometric analyses coupled to multivariate methods.

The differences seen between wines from these two Bordeaux regions came about from grape variety composition in addition to viticultural practices and soil type. Médoc wines contained less ethanol and more lactic acid than Libournais wines.

Differences were also seen between duration of bottle aging and wines of different vintages. Syringic acid, caffeic acid and succinic acid had a bigger presence in older wines, whereas catechin, epicatechin, and tyrosine were associated with young wines.

A clear evolution during bottle aging was seen that allowed the discrimination between wines at a given point in time, plus the differences between vintages. This research demonstrates that NMR metabolomics permits a high degree of differentiation between wines according to the vintage, the vineyard from which they originated, and the duration of bottle aging.

References

1. Anastasiadi M, Zira A, Magiatis P, et al. ¹H NMR-based metabonomics for the classification of Greek wines according to variety, region, and vintage. Comparison with HPLC data. Journal of Agricultural and Food Chemistry 2009;57(23):11067–11074.
2. Geana EI, Popescu R, Costinel D, et al. Classification of red wines using suitable markers coupled with multivariate statistic analysis. Food Chemistry 2016;192:1015–1024.
3. Médina B, Salagoïty MH, Guyon F, et al. Using new analytical approaches to verify the origin of wine. In P. Brereton (Ed.). Analytical approaches for verifying the origin of food (pp. 149–188). Woodhead Publishing 2013.
4. Amargianitaki M & Spyros A. NMR-based metabolomics in wine quality control and authentication. Chemical and Biological Technologies in Agriculture 2017;4(1):9.
5. Godelmann R, Fang F, Humpfer E, et al. 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. Journal of Agricultural and Food Chemistry 2013;61(23):5610–5619.
6. Gougeon L, Da Costa G, Le Mao I, et al. Wine analysis and authenticity using ¹H-NMR metabolomics data: Application to Chinese wines. Food Analytical Methods 2018;11(12):3425–3434.
7. Gougeon L, Da Costa G, Richard T, & Guyon F. Wine authenticity by quantitative ¹H NMR versus multitechnique analysis: A case study. Food Analytical Methods 2019. https://doi.org/10.1007/s12161-12018-01425-z.
8. Gougeon L, et al. Food Chemistry 2019;301:125257. https://doi.org/10.1016/j.foodchem.2019.125257

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