A dataset of sensory perception of chocolates, guacamoles, ice teas and crisps collected with consumers using six temporal methods

Michel Visalli; Sylvie Cordelle; Benjamin Mahieu; Catherine Pedron; Betty Hoffarth; Manon Praudel; Marine Coutière; Pascal Schlich

doi:10.1016/j.dib.2022.108708

A dataset of sensory perception of chocolates, guacamoles, ice teas and crisps collected with consumers using six temporal methods

Data Brief. 2022 Oct 28:45:108708. doi: 10.1016/j.dib.2022.108708. eCollection 2022 Dec.

Authors

Michel Visalli^{1

2}, Sylvie Cordelle^{1

2}, Benjamin Mahieu^{1

2

3}, Catherine Pedron^{1

2}, Betty Hoffarth^{1

2}, Manon Praudel^{1

2}, Marine Coutière^{1

2}, Pascal Schlich^{1

2}

Affiliations

¹ Centre des Sciences du Goût et de l'Alimentation, AgroSup Dijon, CNRS, INRAE, Université Bourgogne Franche-Comté, F-21000 Dijon, France.
² INRAE, PROBE research infrastructure, ChemoSens facility, F-21000 Dijon, France.
³ StatSC, ONIRIS, INRAE, Nantes, France.

Abstract

This article describes a dataset providing temporal sensory perception data of four dark chocolates, four guacamoles, four crisps and four ice teas collected from 436 consumers divided in six groups. Each group of consumers has tested all products using only one sensory evaluation method among: Temporal Dominance of Sensations (TDS, n=70), Temporal Check-All-That-Apply (TCATA, n=73), Attack-Evolution-Finish (AEF) dominance (n=74), AEF applicability (n=75), Free-Comment Attack-Evolution-Finish (FC-AEF) dominance (n=72) and FC-AEF applicability (n=72). Each consumer evaluated all the products: guacamoles and ice tea were evaluated in the lab in one session; chocolates and crisps were evaluated at home in two separate sessions. Within each product category, one sample has been replicated. The consumers started with product descriptions, then they gave a hedonic score, and after having tasted all the products related to a same category, they answered questions about product complexity and difficulty of the task. Consumer information included in the dataset is sex, age and frequency of consumption of each product category. This dataset is unique as it addresses several temporal methods applied on four product categories with different textures and levels of complexity. Thus, it could be very useful for the sensometric community to compare the different methods and their parameters: dominance vs. applicability, periods vs. continuous time, simultaneous vs. retrospective measures, list of terms vs. Free-Comment.

Keywords: AEF; Free-comment; Sensometric; TCATA; TDS.