These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
Pubmed for Handhelds
PUBMED FOR HANDHELDS
Search MEDLINE/PubMed
Title: Measuring temporal liking simultaneously to Temporal Dominance of Sensations in several intakes. An application to Gouda cheeses in 6 Europeans countries. Author: Thomas A, Chambault M, Dreyfuss L, Gilbert CC, Hegyi A, Henneberg S, Knippertz A, Kostyra E, Kremer S, Silva AP, Schlich P. Journal: Food Res Int; 2017 Sep; 99(Pt 1):426-434. PubMed ID: 28784502. Abstract: The idea of having untrained consumers performing Temporal Dominance of Sensations (TDS) and dynamic liking in the same session was recently introduced (Thomas, van der Stelt, Prokop, Lawlor, & Schlich, 2016). In the present study, a variation of the data acquisition protocol was done, aiming to record TDS and liking simultaneously on the same screen in a single session during multiple product intakes. This method, called Simultaneous Temporal Drivers of Liking (S-TDL), was used to describe samples of Gouda cheese in an international experiment. To test this idea, consumers from six European countries (n=667) assessed 4 Gouda cheeses with different ages and fat contents during one sensory evaluation session. Ten sensory attributes and a 9-point hedonic scale were presented simultaneously on the computer screen. While performing TDS, consumers could reassess their liking score as often as they wanted. This new type of sensory data was coded by individual average liking scores while a given attribute was perceived as dominant (Liking While Dominant; LWD). Although significant differences in preference were observed among countries, there were global preferences for a longer dominance of melting, fatty and tender textures. The cheese flavour attribute was the best positive TDL, whereas bitter was a strong negative TDL. A cluster analysis of the 667 consumers identified three significant liking clusters, each with different most and least preferred samples. For the TDL computation by cluster, significant specific TDL were observed. These results showed the importance of overall liking segmentation before TDL analysis to determine which attributes should have a longer dominance duration in order to please specific consumer targets.[Abstract] [Full Text] [Related] [New Search]