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Copyright of Journal of Food Science (John Wiley & Sons, Inc.) is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

BACKGROUND The present study cross-culturally investigated the drivers of liking for traditional and ethnic chicken marinades using descriptive analysis and consumer taste tests incorporating the check-all-that-apply (CATA) method. Seventy-three Koreans and 86 US consumers participated. The tested sauces comprised three tomato-based sauces, a teriyaki-based sauce and a Korean spicy seasoning-based sauce. Chicken breasts were marinated with each of the five barbecue sauces, grilled and served for evaluation. Descriptive analysis and consumer taste tests were conducted. Consumers rated the acceptance on a hedonic scale and checked the reasons for (dis)liking by the CATA method for each sauce. A general linear model, multiple factor analysis and chi-square analysis were conducted using the data. RESULTS The results showed that the preference orders of the samples between Koreans and US consumers were strikingly similar to each other. However, the reasons for (dis)liking the samples differed cross-culturally. The drivers of liking of two sauces sharing relatively similar sensory profiles but differing significantly in hedonic ratings were effectively delineated by reasons of (dis)liking CATA results. CONCLUSION Reasons for (dis)liking CATA proved to be a powerful supporting method to understand the internal drivers of liking which can be overlooked by generic descriptive analysis. © 2014 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

This article reviews a beneficial effect of technology transfer from Electrical Engineering to Food Sensory Science. Specifically, it reviews the recent adoption in Food Sensory Science of the receiver operating characteristic (ROC) curve, a tool that is incorporated in the theory of signal detection. Its use allows the information processing that takes place in the brain during sensory difference testing to be studied and understood. The review deals with how Signal Detection Theory, also called Thurstonian modeling, led to the adoption of a more sophisticated way of analyzing the data from sensory difference tests, by introducing the signal-to-noise ratio, d′, as a fundamental measure of perceived small sensory differences. Generally, the method of computation of d′ is a simple matter for some of the better known difference tests like the triangle, duo-trio and 2-AFC. However, there are occasions when these tests are not appropriate and other tests like the same-different and the A Not-A test are more suitable. Yet, for these, it is necessary to understand how the brain processes information during the test before d′ can be computed. It is for this task that the ROC curve has a particular use. [ABSTRACT FROM AUTHOR]

Consumers rated a set of toothpastes and a set of orange-flavored beverages on a 9-point hedonic scale, using two experimental protocols: Rank-Rating where stimuli could continually be reassessed and a more traditional approach where they could not. A 21-point hedonic scale was also used in the Rank-Rating condition. The hedonic data were analyzed in the usual way using ANOVA with multiple comparisons and also by ranking the data and using an R-index analysis. Regarding the numbers of significant differences recorded, the two analyses were comparable, with a very slight and nonsignificant advantage for the ANOVA analysis. Unlike with intensity scaling, the difference between Rank-Rating and “traditional” scaling was slight but not for all products. The same was true for scale length effects. Differences among the products suggested effects due to the number of attributes that varied. PRACTICAL APPLICATIONS The key finding in this study is the use of Rank-Rating where stimuli could continually be re-assessed for the assessment of hedonic response of consumers in the various products. Rank-Rating may possibly give a better discrimination than more traditional scaling, depending on the number of attributes which varied. The results of the study also recommend the use of R-index analyses of ranked hedonic data in the analyses rather than ANOVA with multiple comparisons. [ABSTRACT FROM AUTHOR]

Abstract: Two experiments were performed in which untrained judges were required to perform a descriptive analysis, using a serial monadic protocol and an attribute-by-attribute protocol. They reached ‘criterion’ performance more rapidly using the attribute-by-attribute protocol, indicating that they were using a relative scaling strategy. Criterion performance required judges to rate all attributes according to the rank order of their physical strengths. Later, they reached criterion performance with the serial monadic protocol, indicating that during experimentation, they had learned to establish sufficient intensity exemplars for an absolute scaling strategy. [Copyright &y& Elsevier]

Abstract: For sensory difference tests, one way, but not the only way, of dealing with the problem of overdispersion is to use a beta-binomial analysis. Commonly, binomial statistical analyses are used for these methods and they assume that the sensitivity of the judges is uniform. However, judge sensitivity varies and this adds a problematical extra variance to the distribution. This is termed overdispersion and renders simple binomial analysis prone to Type I error. The distribution of sensitivity of the judges is described by a beta-distribution. The analysis, combining beta and binomial distributions, gives an index, gamma. This ranges from zero, for no overdispersion, to unity, for total overdispersion. A compact beta-distribution clustered around the mean of the binomial distribution, would add little extra variance and elicit minimum distortion of the binomial distribution, yielding a zero or near zero gamma value. A more scattered or even bimodal beta-distribution would have a substantial effect and yield a significant gamma value. One question that has been posed is whether some test methods are more prone to overdispersion than others. Yet, a consideration of the reasons for overdispersion would suggest that significant gamma values were more a result of obtaining a heterogenous sample of sensitive and insensitive judges by chance. To confirm this, ‘less sensitive’ and ‘more sensitive’ samples of judges performed 2-AFC and 3-AFC tests with resulting zero gamma values, indicating no overdispersion. However, when the less and more sensitive groups were combined, significant gamma values were obtained, indicating the presence of overdispersion. However, in a further experiment using 2-AFC tests, when the ‘less sensitive’ group had its sensitivity increased by a ‘warm-up’ procedure, combination with the ‘more sensitive’ group did not result in overdispersion. [Copyright &y& Elsevier]