Evaluation of the Nietvoorbi j Wine Score Card and Experimental Wine Panelists Utilizing Pattern Recognition Techniques

Abstract

Principal component analysis (PCA) was applied to four cultivar wines, submitted repetitively amongst more than 450 experimental wines, to a sensory evaluation panel of 18 members who used a scoring system comprising overall wine quality and 11 wine descriptors. Inconsistent judges could be eliminated by the evaluation of scatter diagrams. After eliminating 11 judges, the scores of the remaining 7 were used to evaluate the score card in terms of weights placed on individual descriptors in a multiple regression equation, which related the 11 parameters to overall quality scores. Deviations from actual score card weights are discussed in terms of previous PCA analyses, and it is argued that both cultivar and the composition of a mixed data set with respect to these factors, could affect the relative importance of certain parameters. Fitting a similar equation to a large data set consisting of about 480 wines, comprising 23 different cultivars, confirmed the need for further investigations concerning relative score card weights, as well as a critical evaluation of score card parameters for evaluating widely diverging experimental wines.