Characterization of wines from grape varieties through multivariate statistical analysis of (1)H NMR spectroscopic data

(1)H NMR spectroscopic analysis coupled with multivariate statistical data was used to characterize wines vinified from four grape varieties: Muscat Bailey A (Vitis labrusca), Campbell Early (V. labrusca B.), Kyoho (V. labrusca L.) and Meoru (Vitis coignetiae). Pattern recognition methods, such as principal component analysis (PCA) and orthogonal projection to latent structure discriminant analysis (OPLS-DA), showed clear differentiation between wines made from these grape varieties. Metabolites responsible for the differentiation were identified as 2,3-butanediol, glycerol, malate, citrate, tartrate, succinate, lactate, proline, alanine, choline and trigonelline. The PCA score plot of quantitative analysis of targeted profiling data also showed clear separation between the wines. The highest levels of glycerol, 2,3-butanediol, succinate and alcohol were found in Kyoho wines, suggesting higher sugar content in the Kyoho grape berry compared to other grape varieties. Higher contents of citrate and trigonelline in Muscat Bailey A wines, alanine in Campbell Early wines and proline, malate and choline in Meoru wines demonstrated that the metabolites of the wines vary with the grape variety. This study provides insight into the relationship between grape variety and its wine through global and targeted analysis of (1)H NMR spectral data.