Combination of two analytical techniques improves wine classification by Vineyard, Region, and vintage

Alexandra A. Crook, Diana Zamora-Olivares, Fatema Bhinderwala, Jade Woods, Michelle Winkler, Sebastian Rivera, Cassandra E. Shannon, Holden R. Wagner, Deborah L. Zhuang, Jessica E. Lynch, Nathan R. Berryhill, Ron C. Runnebaum, Eric V. Anslyn, Robert Powers

Research output: Contribution to journalArticlepeer-review

Abstract

Three important wine parameters: vineyard, region, and vintage year, were evaluated using fifteen Vitis vinifera L. ‘Pinot noir’ wines derived from the same scion clone (Pinot noir 667). These wines were produced from two vintage years (2015 and 2016) and eight different regions along the Pacific Coast of the United States. We successfully improved the classification of the selected Pinot noir wines by combining an untargeted 1D 1H NMR analysis with a targeted peptide based differential sensing array. NMR spectroscopy was used to evaluate the chemical fingerprint of the wines, whereas the peptide-based sensing array is known to mimic the senses of taste, smell, and palate texture by characterizing the phenolic profile. Multivariate and univariate statistical analyses of the combined NMR and differential sensing array dataset classified the genetically identical Pinot noir wines on the basis of distinctive metabolic signatures associated with the region of growth, vineyard, and vintage year.

Original languageEnglish (US)
Article number129531
JournalFood Chemistry
Volume354
DOIs
StatePublished - Aug 30 2021

Keywords

  • Chemometrics
  • Differential sensing
  • Metabolomics
  • NMR
  • Pinot noir
  • Wine

ASJC Scopus subject areas

  • Analytical Chemistry
  • Food Science

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