Abstract
AbstractA proton nuclear magnetic resonance (NMR)-based metabolomic study was used to characterize 2009, 2010, 2011, and 2012 vintages of Cabernet Sauvignon wines from Ningxia, which were vinified using the same fermentation technique. The pattern recognition methods of principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal PLS-DA (OPLS-DA) clearly distinguished between the different vintages of wine driven by the following metabolites: valine, 2,3-butanediol, ethyl acetate, proline, succinic acid, lactic acid, acetic acid, glycerol, gallic acid, and choline. The PLS-DA loading plots also differentiated among the metabolites of different vintages. In the 2009 vintage wines, we found the highest levels of gallic acid, valine, proline, and 2,3-butanediol. The 2011 vintage wines contained the highest levels of lactic acid, and the highest levels of ethyl acetate, succinic acid, glycerol, and choline were observed in the 2012 vintage wines. We selected eight metabolites from the1H NMR spectra that were quantified according to their peak areas, and the concentrations were in agreement with the results of PLS-DA and OPLS-DA analyses.
Highlights
Wine obtains several metabolites from grape berries during fermentation
The principal component analysis (PCA) score plot shows a clear differentiation among the Cabernet Sauvignon wines of different vintages
The partial least squares discriminant analysis (PLS-DA) and orthogonal PLS-DA (OPLS-DA) models were used to compare the different vintages of wine
Summary
Wine obtains several metabolites from grape berries during fermentation. Many factors, including the soil, climate, viticultural practices (soil tillage and covering), winemaking process, and vintage, contribute to the metabolite composition and content of wines [1,2,3,4,5]. The common parameters used to evaluate the quality of wine are the total soluble solids, alcohol concentration, total acids, and total phenols. These basic parameters are significant, and the classical analytical methods can detect many other important compounds [1,6,7,8,9]. These parameters reflect only the health of the wine and cannot fully explain the quality of the wine. For wine quality assessment, powerful advanced analysis methods are necessary to determine the metabolites in wines [6,10]
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