Abstract
This chapter describes the multivariate data analytical methods used for sensory analysis and includes a general introduction to bilinear modelling (BLM), principal component analysis, naïve assessor reliability testing, generalised Procrustes analysis and partial least squares regression. Internal, external and hybrid (PLS) preference mapping is also discussed with respect to the mapping of subjective consumer type data to objective data such as sensory descriptive, instrumental and physicochemical data. BLM is also used to demonstrate how multivariate data analysis can be used for the correlation of a multimodal and complex data set incorporating gas chromatography/mass spectrometry, electronic nose data and descriptive sensory data in a presented case study.
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