An Exploratory Application of Pivot-CATA and Pivot-RATA in Reference-Based Sensory Evaluation of Sunscreen Cosmetics

Abstract

Semi-trained panelists evaluated sunscreen cosmetics using the Pivot-CATA (combining Pivot profile with Check-all-that-apply) and Pivot-RATA (combining Pivot profile with Rate-all-that-apply) methods, comparing results with Descriptive Analysis (DA). The findings indicated that, on a scale of 1–5 with two evaluation batches, Pivot-RATA generated a more similar product space distribution to DA (the highest RV value). Although Pivot-RATA showed lower product differentiation capability than DA, it was higher than Pivot-CATA. Under both Pivot-CATA and Pivot-RATA methods, the semi-trained panelists evaluated in reproducible ways and produced reliable results. Pivot-RATA can be a potential option for batch-evaluating products and integrating data analysis to construct a product sensory map.