Use of face reading to measure oral processing behaviour and its relation to product perception

Aikaterini Katsikari, Mads Erling Pedersen,Ingunn Berget,Paula Varela

Food Quality and Preference(2024)

引用 0|浏览0
暂无评分
摘要
Food texture can influence sensory perception and eating behaviour; it can be managed to affect intake, by inducing higher expected satiety and satiation, and eventually reducing overeating. The objective of this work was to assess face reading as an automatic measure of oral processing behaviour of products with different texture modifications, aimed at reducing intake. Three oat breads with different textural properties were used as a case study. A trained panel used Temporal Dominance of Sensations to describe dynamic sensory profiles of the breads and were simultaneously video recorded; the videos were analysed by FaceReader (intake, chewing motions, chewing period). The parameters extracted through face reading showed significant differences among the breads in duration of chewing period and number of chewing motions, which can be interpreted together with the TDS results. A consumer test (n = 135) was conducted on the breads, where participants evaluated overall liking, expected satiation and satiety, and answered a Check-All-That-Apply question including sensory and non-sensory attributes. Results indicated that the samples were significantly different in terms of liking, expected satiation and satiety and that consumers described samples in CATA question in line with the panel. Results interpreted together allowed the identification of the dynamic textural properties responsible for enhancing satiety and satiation expectations. Methodological implications are discussed throughout the paper. The novelty of the study is to show that automatic measures of oral processing behaviour by face reading, can be linked to self-reported explicit measures of satiety, opening the door to larger studies, unfeasible using manual annotation.
更多
查看译文
关键词
Textural properties,Automatic measures,Oral processing,Satiety,Consumer acceptance,Dynamic profile
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要