WOS: 000306407200001International audienceFor food scientists and industrials, descriptive profiling is an essential tool that involves the evaluation of both the qualitative and quantitative sensory characteristics of a product by a panel. Recently, in response to industrial demands to develop faster and more cost-effective methods of descriptive analysis, several methods have been offered as alternatives to conventional profiling. These methods can be classified in three families: (i) verbal-based methods (flash profile and check-all-that-apply), (ii) similarity-based methods (free sorting task and projective mapping aka Napping (R)) and (iii) reference-based methods (polarised sensory positioning and pivot profile). We successively present these three classes of methods in terms of origin, principles, statistical analysis, applications to food products, variations of the methods and the Pros and Cons

The other-race effect was examined in a series of experiments and simulations that looked at the relationships among observer ratings of typicality, familiarity, attractiveness, memorability, and the performance variables of d' and criterion. Experiment 1 replicated the other-race effect with our Caucasian and Japanese stimuli for both Caucasian and Asian observers. In Experiment 2, we collected ratings from Caucasian observers on the faces used in the recognition task. A Varimax-rotated principal components analysis on the rating and performance data for the Caucasian faces replicated Vokey and Read's (1992) finding that typicality is composed of two orthogonal components, dissociable via their independent relationships to: (1) attractiveness and familiarity ratings and (2) memorability ratings. For Japanese faces, however, we found that typicality was related only to memorability. Where performance measures were concerned, two additional principal components dominated by criterion and by d' emerged for Caucasian faces. For the Japanese faces, however, the performance measures of d' and criterion merged into a single component that represented a second component of typicality, one orthogonal to the memorability-dominated component. A measure of face representation quality extracted from an autoassociative neural network trained with a majority of Caucasian faces and a minority of Japanese faces was incorporated into the principal components analysis. For both Caucasian and Japanese faces, the neural network measure related both to memorability ratings and to human accuracy measures. Combined, the human data and simulation results indicate that the memorability component oftypicality may be related to small, local, distinctive features, whereas the attractiveness/familiarity component may be more related to the global, shape-based properties of the face.For many years, it has been suspectedthat faces of one's own race are recognized more accurately than faces of other races (Feingold, 1914). Indeed, there is abundant empirical evidence for this other-race phenomenon, as two recent metaanalyses of the face recognition literature attest (Bothwell, Brigham, & Malpass, 1989;Shapiro & Penrod, 1986). In addition to the empirical support for this phenomenon, the other-race effect is widely known outside of the laboratory. Deffenbacher and Loftus (1982), Thanks are due June Chance and AI Goldstein for providing the Caucasian and Japanese faces used in the present experiments and simulations and to James C. Bartlett for helpful comments throughout the entire course of the project. We would like to thank also James I. Chumbley, John W. Shepherd, and John R. Vokey for very helpful comments on a previous version of the manuscript. We are grateful also to Barbara Edwards and to Ray Zhu for assistance in testing subjects. Requests for reprints should be sent to A. J. O'Toole, School of Human Development, GR4.1, University of Texas at Dallas, Richardson, TX 75083-0688 (e-mail: otoole@utdallas.edu). -Accepted by previous editor...

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