title: Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars.
abstract: OBJECTIVE
  Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although 1H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors.
  
  
  RESULTS
  We applied 1H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses.
  
  
  CONCLUSIONS
  Differences in grape-derived metabolites associated with genetic differences alone are a major source of 1H NMR-based discrimination of wines and 1H NMR has the capacity to discriminate between very closely related cultivars.
  
  
  CONCLUSIONS
  The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by 1H NMR-PCA/PLS and indicates that 1H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach.
authors.affiliation: College of Food Science and Engineering, Yangzhou University, Yangzhou, Jiangsu, China.
authors.forename: Boran
authors.initials: B
authors.lastname: Hu
authors.affiliation: College of Food Science and Engineering, Yangzhou University, Yangzhou, Jiangsu, China.
authors.forename: Yaqing
authors.initials: Y
authors.lastname: Yue
authors.affiliation: College of Tourism and Gastronomy, Yangzhou University, Yangzhou, Jiangsu, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: Zhu
authors.affiliation: College of Tourism and Gastronomy, Yangzhou University, Yangzhou, Jiangsu, China.
authors.forename: Wen
authors.initials: W
authors.lastname: Wen
authors.affiliation: Testing Center of Yangzhou University, Yangzhou, Jiangsu, China.
authors.forename: Fengmin
authors.initials: F
authors.lastname: Zhang
authors.affiliation: Northern Melbourne Institute of TAFE, Epping, Victoria, Australia.
authors.forename: Jim W
authors.initials: JW
authors.lastname: Hardie
mesh_terms: D016000:Cluster Analysis; D005838:Genotype; D055442:Metabolome; D015999:Multivariate Analysis; D010802:Phylogeny; D025341:Principal Component Analysis; D066244:Proton Magnetic Resonance Spectroscopy / Q000379:methods*; D027843:Vitis / Q000737:chemistry / Q000145:classification / Q000235:genetics*; D014920:Wine / Q000032:analysis* / Q000145:classification