4.7 Article

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

JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
Volume 61, Issue 23, Pages 5610-5619

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/jf400800d

Keywords

H-1 NMR spectroscopy; grape variety; geographical origin; year of vintage; German wine; multivariate statistical analysis

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The authenticity, the grape variety, the geographical origin, and the year of vintage of wines produced in Germany were investigated by H-1 NMR spectroscopy in combination with several steps of multivariate data analysis including principal component analysis (PCA), linear discrimination analysis (LDA), and multivariate analysis of variance (MANOVA) together with cross-validation (CV) embedded in a Monte Carlo resampling approach (MC) and others. A total of about 600 wines were selected and carefully collected from five wine-growing areas in the southern and southwestern parts of Germany. Simultaneous saturation of the resonances of water and ethanol by application of a low-power eight-frequency band irradiation using shaped pulses allowed for high receiver gain settings and hence optimized signal-to-noise ratios. Correct prediction of classification of the grape varieties of Pinot noir, Lemberger, Pinot blanc/Pinot gris, Muller-Thurgau, Riesling, and Gewurztraminer of 95% in the wine panel was achieved. The classification of the vintage of all analyzed wines resulted in correct predictions of 97 and 96%, respectively, for vintage 2008 (n = 318) and 2009 (n = 265). The geographic origin of all wines from the largest German wine-producing regions, Rheinpfalz, Rheinhessen, Mosel, Baden, and Wurttemberg, could be predicted 89% correctly on average. Each NMR spectrum could be regarded as the individual fingerprint of a wine sample, which includes information about variety, origin, vintage, physiological state, technological treatment, and others.

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