In sensory analysis a panel of assessors scores 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. This paper shows the advantages of either interval/fuzzy coding and fuzzy PLS path modeling in the context of sensory analysis. Specifically, as many path models as assessors are considered and compared in terms of fuzzy path coefficients so as to detect eventual differences between assessors. Furthermore, an ad hoc interval coding is used to collapse the tables over the assessors into a two-way table partitioned by the ttributes. A fuzzy PLS path modeling provides two sets of synthesized assessments: the overall latent scores for each product and the partial latent scores for the different blocks of attributes.
ROMANO, R., ESPOSITO VINZI, V. and PALUMBO, F. (2007). Fuzzy PLS Path Modeling for Crisp and Interval Data: A New Tool for Handling Sensory Data.