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).
- sensory profile
Faber, N. M., Mojet, J., & Poelman, A. A. M. (2003). Simple improvement of consumer fit in external preference mapping. Food Quality and Preference, 14(5-6), 455-461. https://doi.org/10.1016/S0950-3293(03)00011-9