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Research Article

Comparison of Multivariate Regression Methods for the Analysis of Phenolics in Wine Made from Two Vitis vinifera Cultivars

Christopher W. Beaver, James F. Harbertson
Am J Enol Vitic.  2016  67: 56-64  ; DOI: 10.5344/ajev.2015.15063
Christopher W. Beaver
1Viticulture and Enology Program, School of Food Science, Washington State University, Wine Science Center, 2710 Crimson Way, Richland, WA 99354-1671
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James F. Harbertson
2Associate Professor of Enology, Viticulture and Enology Program, School of Food Science, Washington State University, Wine Science Center, 2710 Crimson Way, Richland, WA 99354-1671
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  • For correspondence: jfharbertson@wsu.edu
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Abstract

The quantification of key phenolic classes during different stages of red wine production has important industrial applications. Decisions of this nature require greater speed and economy than current bench or instrumental methodologies offer. Efforts to create rapid analysis have used models created from multivariate regression of easily obtained spectra (ultraviolet (UV)/visible or near infrared) and referenced phenolic measurements. For this experiment, reference measures of phenolics and UV/visible spectra were gathered from 100 samples each of Cabernet Sauvignon and Syrah red wine throughout fermentation to create a model that could rapidly predict several phenolic classes in red wine must. The reference method, UV/visible spectra sample dilution, and multivariate regression method were all varied to determine which combination gave the greatest predictive power. Ridge regression unanimously outperformed the other regression methods tested when calibrated with the modified assay at pH 7 and UV/visible sample dilution at 10-fold for only the Cabernet Sauvignon samples. Correlation coefficients obtained for anthocyanins, small and large polymeric pigments, tannins, and total iron reactive phenolics were 0.83, 0.78, 0.76, 0.92, and 0.90, respectively. When the same multivariate regression evaluation was performed for Syrah, none of the methods tested gave accurate predictions, suggesting some cultivar specificity.

  • tannins
  • ridge regression
  • mathematical model
  • phenolics
  • wine
  • Cabernet Sauvignon
  • ©2016 by the American Society for Enology and Viticulture
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You have accessRestricted access
Comparison of Multivariate Regression Methods for the Analysis of Phenolics in Wine Made from Two Vitis vinifera Cultivars
Christopher W. Beaver, James F. Harbertson
Am J Enol Vitic.  2016  67: 56-64  ; DOI: 10.5344/ajev.2015.15063
Christopher W. Beaver
1Viticulture and Enology Program, School of Food Science, Washington State University, Wine Science Center, 2710 Crimson Way, Richland, WA 99354-1671
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
James F. Harbertson
2Associate Professor of Enology, Viticulture and Enology Program, School of Food Science, Washington State University, Wine Science Center, 2710 Crimson Way, Richland, WA 99354-1671
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: jfharbertson@wsu.edu

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Comparison of Multivariate Regression Methods for the Analysis of Phenolics in Wine Made from Two Vitis vinifera Cultivars
Christopher W. Beaver, James F. Harbertson
Am J Enol Vitic.  2016  67: 56-64  ; DOI: 10.5344/ajev.2015.15063
Christopher W. Beaver
1Viticulture and Enology Program, School of Food Science, Washington State University, Wine Science Center, 2710 Crimson Way, Richland, WA 99354-1671
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
James F. Harbertson
2Associate Professor of Enology, Viticulture and Enology Program, School of Food Science, Washington State University, Wine Science Center, 2710 Crimson Way, Richland, WA 99354-1671
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: jfharbertson@wsu.edu
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