A novel two-step rating-based ‘double-faced applicability’ test. Part 2: Introducing a novel measure of affect magnitude ( d ′ A ) for profiling consumers’ product usage experience based on Signal Detection Theory

Sensory test A-Not A rating signal detection: panel’s sensory learning and stability of decision criteria

Signal detection theory (SDT) sensory discrimination analysis using A-Not A with a two-step rating is an efficient approach to in-house sensory quality management in the food industry. For such sensory analysis using an internal panel, the panels' ability to use stable decision criteria and provide a consistent response distribution responding to "A" vs "Not A" is critical for guaranteeing the data quality. This study examined the effects of the familiarization procedure (FP) and reference presentation probability (RPP) in the SDT A-Not A rating protocol on the panels' sensory learning of samples and stability of decision criteria using SDT parameters, recognition d' (d'_Rec),criteria location (c), and discrimination d' indices. Three different protocols were compared using ice-tea samples with small differences: Control, 0.25 RPP with repeated reference tasting (FP_R); Modified-1, 0.25 RPP with reference categorization (FP_C); Modified-2, 0.5 RPP with reference categorization (FP_C). An independent sample design with three groups having equal sensitivity was used to identify the differences among the protocols. For each protocol, two sub-groups with similar decision criteria (response bias) were formed according to the results obtained from the pre-test and used for the main-test analysis. SDT analysis results indicated that the Modified-2 protocol with a higher RPP (0.5) induced the most efficient sensory learning of the reference. The protocol improved the subjects' recognition of the reference and test samples, better differentiating from the reference and stabilizing the decision criterion, resulting in higher discrimination performance (larger d'). The results showed that d'_Rec analysis, together with d' analysis using a sensory panel, is a useful tool for monitoring the panel performance and checking for the sensory data quality of the sensory difference tests. In the present paper, a detailed illustration of the A-Not A sensory test procedure and examples of how to apply the SDT indices for different business decision-making is also introduced using the design and results of the present experiment.

Two-step rating-based 'double-faced applicability' test for sensory analysis of spread products as an alternative to descriptive analysis with trained panel

Descriptive analysis with a trained sensory panel has thus far been the most well defined methodology to characterize various products. However, in practical terms, intensive training in descriptive analysis has been recognized as a serious defect. To overcome this limitation, various novel rapid sensory profiling methodologies have been suggested in the literature. Among these, attribute-based methodologies such as check-all-that-apply (CATA) questions showed results comparable to those of conventional sensory descriptive analysis. Kim, Hopkinson, van Hout, and Lee (2017a, 2017b) have proposed a novel attribute-based methodology termed the two-step rating-based 'double-faced applicability' test with a novel output measure of applicability magnitude (d'_A) for measuring consumers' product usage experience throughout various product usage stages. In this paper, the potential of the two-step rating-based 'double-faced applicability' test with d'_A was investigated as an alternative to conventional sensory descriptive analysis in terms of sensory characterization and product discrimination. Twelve commercial spread products were evaluated using both conventional sensory descriptive analysis with a trained sensory panel and two-step rating-based 'double-faced applicability' test with an untrained sensory panel. The results demonstrated that the 'double-faced applicability' test can be used to provide a direct measure of the applicability magnitude of sensory attributes of the samples tested in terms of d'_A for sensory characterization of individual samples and multiple sample comparisons. This suggests that when the appropriate list of attributes to be used in the questionnaire is already available, the two-step rating-based 'double-faced applicability' test with d'_A can be used as a more efficient alternative to conventional descriptive analysis, without requiring any intensive training process.