Comparison of RATA, CATA, sorting and Napping® as rapid alternatives to sensory profiling in a food industry environment

Abstract

Today, there is a need to accelerate new product development to deliver faster innovations which are expected by consumers. This requires identifying rapid descriptive methodologies requiring less training than conventional sensory profiling (SP) still providing good quality data allowing to identify food sensory drivers of consumer liking. A set of nine samples covering a large sensory space has been designed systematically combining at three different ratio three commercial almond, rice, and oat-based milks. Ten expert panellists familiar with sensory profiling and naïve with the plant-based milk category performed sorting, Napping®, CATA, RATA tasks and then SP. Overall liking of each sample was rated by 80 plant-based milk consumers. Among the four alternative methodologies, RATA provided both an overall product configuration and description the closest to SP (RV = 0.93) and allowed to identify the sensory drivers of plant-based milk acceptance similarly to SP. CATA is relevant to build a product landscape and to highlight product clusters with major sensory differences whereas Sorting and Napping® are alternatives to CATA, as product mappings were close, when no previous glossary or knowledge exits on product attributes.