Estimation of hedonic responses from descriptive skin sensory data by Chi-square minimization
2006
Almeida, I.F. | Gaio, A.R. | Bahia, M.F.
Six topical formulations were evaluated by a trained panel according to a descriptive analysis methodology and by a group of consumers who rated the products on a hedonic scale. We present a new approach that describes the categorical appreciation of appearance, texture and skinfeel of the formulations by the consumers as a function of related sensory attributes assessed by the trained panel. For each hedonic attribute, a latent random variable depending on the sensory attributes is constructed and made discrete (in a nonlinear fashion) according to the distribution of consumer-hedonic scores in such a way as to minimize a corresponding chi-square criterion. Standard partial least squares (PLS) regression, bootstrapping and cross-validation techniques describing the overall liking of the hedonic attributes as a function of associated sensory attributes were also applied. Results from both methods were compared, and it was concluded that chi-square minimization can work as a complementary method to the PLS regression.
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