Centre des Sciences du Goût et de l'Alimentation, CNRS, INRA, Univ. Bourgogne Franche-Comté, F-21000 Dijon, France.
Campden BRI, Chipping Campden, United Kingdom.
Food Res Int. 2017 Sep;99(Pt 1):426-434. doi: 10.1016/j.foodres.2017.05.035. Epub 2017 May 30.
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.
让未经训练的消费者在同一时间段内进行感官时间主导性(TDS)和动态喜好度评估的想法最近被提出(Thomas、van der Stelt、Prokop、Lawlor 和 Schlich,2016)。在本研究中,采用了一种数据采集协议的变体,旨在在单次感官评估过程中,在同一屏幕上同时记录 TDS 和喜好度,以便在多次产品摄入期间进行。这种方法称为同时喜好度的时间驱动因素(S-TDL),用于描述国际实验中高达奶酪的样本。为了测试这个想法,来自六个欧洲国家的消费者(n=667)在一次感官评估过程中评估了四种不同成熟度和脂肪含量的高达奶酪。十种感官属性和九点愉悦度量表同时呈现在电脑屏幕上。在进行 TDS 的同时,消费者可以根据需要随时重新评估他们的喜好度评分。这种新型感官数据通过给定属性被感知为主导时的个体平均喜好度评分进行编码(主导时的喜好度;LWD)。尽管在国家之间观察到偏好存在显著差异,但对于融化、油腻和柔软质地的主导时间更长存在全球偏好。奶酪风味属性是最好的正 TDL,而苦味是强烈的负 TDL。对 667 名消费者的聚类分析确定了三个具有不同最受欢迎和最不受欢迎样本的显著喜好度聚类。对于按聚类进行的 TDL 计算,观察到了显著的特定 TDL。这些结果表明,在进行 TDL 分析之前,对整体喜好度进行细分非常重要,以确定哪些属性应该具有更长的主导时间,从而满足特定的消费者目标。