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Old 03-03-2011, 02:06 AM
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Default Metabolic characterization of Palatinate German white wines according to sensory attributes, varieties, and vintages using NMR spectroscopy and multivariate data analyses

Metabolic characterization of Palatinate German white wines according to sensory attributes, varieties, and vintages using NMR spectroscopy and multivariate data analyses


Abstract 1H NMR (nuclear magnetic resonance spectroscopy) has been used for metabolomic analysis of â??Rieslingâ?? and â??Mueller-Thurgauâ?? white wines from the German Palatinate region. Diverse two-dimensional NMR techniques have been applied for the identification of metabolites, including phenolics. It is shown that sensory analysis correlates with NMR-based metabolic profiles of wine. 1H NMR data in combination with multivariate data analysis methods, like principal component analysis (PCA), partial least squares projections to latent structures (PLS), and bidirectional orthogonal projections to latent structures (O2PLS) analysis, were employed in an attempt to identify the metabolites responsible for the taste of wine, using a non-targeted approach. The high quality wines were characterized by elevated levels of compounds like proline, 2,3-butanediol, malate, quercetin, and catechin. Characterization of wine based on type and vintage was also done using orthogonal projections to latent structures (OPLS) analysis. â??Rieslingâ?? wines were characterized by higher levels of catechin, caftarate, valine, proline, malate, and citrate whereas compounds like quercetin, resveratrol, gallate, leucine, threonine, succinate, and lactate, were found discriminating for â??Mueller-Thurgauâ??. The wines from 2006 vintage were dominated by leucine, phenylalanine, citrate, malate, and phenolics, while valine, proline, alanine, and succinate were predominantly present in the 2007 vintage. Based on these results, it can be postulated the NMR-based metabolomics offers an easy and comprehensive analysis of wine and in combination with multivariate data analyses can be used to investigate the source of the wines and to predict certain sensory aspects of wine.
  • Content Type Journal Article
  • Pages 1-12
  • DOI 10.1007/s10858-011-9487-3
  • Authors
    • Kashif Ali, Division of Pharmacognosy, Section Metabolomics, Institute of Biology, Leiden University, 2333 CC Leiden, The Netherlands
    • Federica Maltese, Division of Pharmacognosy, Section Metabolomics, Institute of Biology, Leiden University, 2333 CC Leiden, The Netherlands
    • Reinhard Toepfer, Julius Kuehn Institute (JKI), Federal Research Centre for Cultivated Plants, Institute for Grapevine Breeding Geilweilerhof, 76833 Siebeldingen, Germany
    • Young Hae Choi, Division of Pharmacognosy, Section Metabolomics, Institute of Biology, Leiden University, 2333 CC Leiden, The Netherlands
    • Robert Verpoorte, Division of Pharmacognosy, Section Metabolomics, Institute of Biology, Leiden University, 2333 CC Leiden, The Netherlands

Source: Journal of Biomolecular NMR
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