title: Discrimination of cherry wines based on their sensory properties and aromatic fingerprinting using HS-SPME-GC-MS and multivariate analysis.
abstract: Volatiles of cherry wines were extracted by headspace solid phase microextraction (HS-SPME) and analyzed by gas chromatography mass spectrometry (GC-MS), multivariate statistical techniques (such as principal component analysis (PCA) and cluster analysis (CA) and correlation analysis) to differentiate sensory attributes of 3 groups of the wines through characterization of volatiles of cherry wine. Seventy-five volatiles were identified in 9 samples, including 29 esters, 22 alcohols, 8 acids, 3 ketones, 5 aldehydes, and 8 miscellaneous compounds. The PCA results showed that the cherry wines were mainly differentiated by 8 sensory attributes. The samples W2, W4, and W7 were grouped around sweet aromatic and the samples W1, W5, and W9 were highly associated with the sweet, esters, green, bitter, and fermented. Nevertheless, the samples W3, W6, and W8 were located close to the sour, alcoholic, and fruity. The final result of correlation analysis was in conformity with the conclusion of PCA. The CA results showed that the group of W2, W4, and W7, and the group of W1, W5, and W9 had less difference than the group of W3, W6, and W8. The reason should be that esterification reactions and fermentation process during the ageing period was more extended. The results of analyzing revealed that HS-SPME-GC-MS coupled with chemometrics could give an appropriate way of characterizing and classifying the cherry wines.
  
  
  CONCLUSIONS
  Attributes that represent and discriminate among cherry wines might be made use of a better comprehending of the wines and for being utilized in future work. In addition, several chemometrics were used to classify the type of wines and try to install the relationship between volatiles and sensory property. Especially, PCA clearly revealed that the most contributing compounds for sensory attributes of cherry wines, CA was a more applicable way to distinguish types of cherry wines. Therefore, a feasible method that would be helpful to promote the quality of the wines by improving the winemaking process and analyzing aromatic characteristics of wines.
authors.affiliation: School of Perfume and Aroma Technology, Shanghai Inst. of Technology, Shanghai, China.
authors.forename: Zuobing
authors.initials: Z
authors.lastname: Xiao
authors.forename: Shengjiang
authors.initials: S
authors.lastname: Liu
authors.forename: Yongbo
authors.initials: Y
authors.lastname: Gu
authors.forename: Na
authors.initials: N
authors.lastname: Xu
authors.forename: Yi
authors.initials: Y
authors.lastname: Shang
authors.forename: Jiancai
authors.initials: J
authors.lastname: Zhu
mesh_terms: D000438:Alcohols / Q000032:analysis; D000447:Aldehydes / Q000032:analysis; D001557:Benzenesulfonates; D016000:Cluster Analysis; D004952:Esters / Q000032:analysis; D005285:Fermentation; D005421:Flavoring Agents / Q000032:analysis; D008401:Gas Chromatography-Mass Spectrometry / Q000379:methods; D006801:Humans; D007659:Ketones / Q000032:analysis; D015999:Multivariate Analysis; D009812:Odorants / Q000032:analysis*; D025341:Principal Component Analysis; D027861:Prunus / Q000737:chemistry*; D052617:Solid Phase Microextraction / Q000379:methods; D013649:Taste; D055549:Volatile Organic Compounds / Q000032:analysis*; D014920:Wine / Q000032:analysis*
chemical_list: D000438:Alcohols; D000447:Aldehydes; D001557:Benzenesulfonates; D004952:Esters; D005421:Flavoring Agents; D007659:Ketones; D055549:Volatile Organic Compounds; C056082:4-sulfophenylmethallyl ether
keywords: HS-SPME-GC-MS; cherry wines; multivariate analysis; sensory properties; volatiles