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A brief introduction to multivariate methods in grape and wine analysis

Authors Cozzolino D, Cynkar WU, Shah N, Dambergs RG, Smith PA

Published 18 March 2009 Volume 2009:1 Pages 123—130


Review by Single anonymous peer review

Peer reviewer comments 4

D Cozzolino1, W U Cynkar1, N Shah1, R G Dambergs2, P A Smith1

1The Australian Wine Research Institute, Urrbrae, Glen Osmond, SA, Australia; 2The Australian Wine Research Institute, Tasmanian Institute of Agricultural Research, University of Tasmania, Hobart, Tasmania, Australia

Abstract: Real-world systems are usually multivariate and hence usually cannot be adequately described by one selected variable without the risk of serious misrepresentation. Analyzing the effect of one variable at a time by analysis of variance techniques can give useful descriptive information, but this will not give specific information about relationships among variables and other important relationships in the entire matrix. Multivariate data analysis was developed in the late 1960s, and used by a number of research groups in analytical and physical organic chemistry due to the introduction of instrumentation giving multivariate responses for each sample analyzed. Development of such methods was also made possible by the availability of computers. Multivariate data analysis involves the use of mathematical and statistical techniques to extract information from complex data sets. The objective of this paper is to briefly describe and illustrate some multivariate data analysis methods used for grape and wine analysis.

Keywords: multivariate analysis, data mining, wine, grape


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