Simple improvement of consumer fit in external preference mapping

N.M. Faber, J. Mojet, A.A.M. Poelman

    Research output: Contribution to journalArticleAcademicpeer-review

    30 Citations (Scopus)

    Abstract

    In the common implementation of external preference mapping consumer preferences are fitted as polynomial functions of the first two principal components (PCs) of the sensory data. A major weakness of the method is the relatively small number of consumers that can be significantly fitted. Several researchers have proposed to improve the consumer fit by including higher-numbered PCs in the analysis. We have explored the possibility of including higher-numbered PCs while restricting the model choice to the simplest polynomial function, i.e. the (linear) vector model. In addition, we have developed a heuristic decision rule for determining the number of PCs to keep in the fit. A practical example is discussed where the consumer fit improved from 51øtwo PCs, polynomial) to 80øfive PCs, vector).
    Original languageEnglish
    Pages (from-to)455-461
    JournalFood Quality and Preference
    Volume14
    Issue number5-6
    DOIs
    Publication statusPublished - 2003

    Keywords

    • sensory profile
    • attributes
    • cheeses

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