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Sensory test A-Not A rating signal detection: Panel's sensory learning and stability of decision criteria. | LitMetric

Sensory test A-Not A rating signal detection: Panel's sensory learning and stability of decision criteria.

Food Res Int

Department of Food Science and Biotechnology, College of Engineering, Ewha Womans University, Seoul 03760, South Korea. Electronic address:

Published: May 2023

AI Article Synopsis

Article Abstract

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'),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); Modified-1, 0.25 RPP with reference categorization (FP); Modified-2, 0.5 RPP with reference categorization (FP). 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' 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.

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http://dx.doi.org/10.1016/j.foodres.2023.112592DOI Listing

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