Fuzzy PLS path modeling: a new tool for handling sensory data

In sensory analysis a panel of assessors gives scores to blocks of sensory attributes for profiling products, thus yielding a three-way table crossing assessors, attributes and products. In this context, it is important to evaluate the panel performance as well as to synthesize the scores into a global assessment to investigate differences between products. Recently, a combined approach of fuzzy regression and PLS path modeling has been proposed for comparing different structural equation models. Fuzzy regression considers crisp/fuzzy variables and identifies a set of fuzzy parameters using optimization techniques. In this framework, the present work aims to show the advantages of either interval/fuzzy coding and fuzzy PLS path modeling in the context of sensory analysis.