The application of multivariate analysis techniques-- such as factor analysis, cluster analysis, discrimination analysis, and multidimensional scaling-- to data reduction and classification problems in sensory analysis has been the subject of theoretical and practical interest for a number of years (Woskow, 1964; Schiffman, 1974; Godwin et al., 1978; Clapperton and Piggott, 1979; Ennis et al., 1982). These techniques are very valuable from the viewpoint of visualizing the structure of complex multivariate data sets and have yielded clues with regard to physiochemical-perceptual relationships for foods, they have a limited range in helping us to understand how chemosensory, visual, or auditory stimulants are perceived because, with the possible exception of multidimensional scaling, they are based on limited perceptual models, or none at all.
This article appears as:
Ennis, D. M. (1988). Multivariate sensory analysis. Food Technology, 42, 118, 120-122.
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Multivariate sensory analysis
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