Weighted PLS-discriminant analysis with application to conventional sensory profiling

Within the framework of sensory conventional profiling, we propose a general strategy of weight assignment to the various statistical units (products × assessors). This means that for each product, an assessor who does not agree with the other assessors on the evaluation of the product under consideration will be down-weighted thus limiting their impact on the outcome of the analysis. The weights are derived from similarity measures between assessors which reflect the extent to which the assessors agree on the position of each product in the perceptual space. The weights are used to compute the usual statistical parameters such as means and variance–covariance matrices. They are also used to compute the PLS-discriminant components which reflect directions of discrimination among the products. The usefulness of the strategy of weight assignment is demonstrated on the basis of a case study where it is shown that it improves the stability of the representation of the products to small perturbations.

► We propose a weighting strategy in sensory profiling.
► We use the weights in a PLS-discriminant analysis.
► We prove it can lead to better performance.