Analysis of sensory assessors in texture profiling of potatoes by multivariate modelling

The aim of the present study was to analyse the reliability and performance of the sensory assessors in texture profiling by a univariate (ANOVA) and a multivariate procedure using discriminant partial least squares regressio n (DPLSR). Assessor x product modelling is relevant in the data analysis of sensory data, since potato tubers are slightly heterogeneous, even when gr own under controlled conditions and sorted with respect to size and density . Thus, different assessors may in fact get "different" products. Also the assessor level differences were removed by the modelling. Signal to noise p lots for all attributes showed reflection, mealiness and firmness to be the most reliable attributes, and springiness and chewiness to be the least re liable attributes. Signal to noise plots for each attribute illustrated som e assessors to be good in evaluation of some attributes and less good in ot hers. The assessors were questioned about psychological states after each s ession in order to study if individual differences influenced the assessors ' performance. Some assessors reporting that they felt concentrated, were i n fact found to be less reliable than others who felt stressed. (C) 2000 Pu blished by Elsevier Science Ltd. All rights reserved.