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Identifying temporal drivers of liking and satiation based on temporal sensory descriptions and consumer ratings
Affiliation:1. Department of Food Technology, Ho Chi Minh City University of Technology (HCMUT), Ho Chi Minh City, Viet Nam;2. Vietnam National University Ho Chi Minh City, Ho Chi Minh City, Viet Nam;3. Nofima AS, Osloveien 1, P.O. Box 210, N-1431 Ås, Norway;1. Department of Agricultural Economics, Statistics and Business Management, Universidad Politécnica de Madrid, Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas, Ciudad Universitaria s/n, 28040 Madrid, Spain;2. Instituto de Investigación en Ciencias de la Alimentación (CIAL), (CSIC-UAM), C/ Nicolás de Cabrera, 9, 28049 Madrid, Spain;3. Visiting Scholar at Universidad Politécnica de Madrid, Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell''Università, 16, 35020 Legnaro, Italy;1. Carr Consulting, 1215 Washington Ave., Suite 208, Wilmette, IL 60091, USA;2. Charles Sturt University, Wagga Wagga, NSW, Australia;1. LUNAM University, ONIRIS, Sensometrics and Chemometrics Laboratory, Nantes, France;2. INRA, Nantes, France;3. CTIFL, Centre de Saint Rémy de Provence, France;4. CTIFL, Centre de Balandran, France;1. Department of Biological Sciences, Brock University, St. Catharines, Ontario L2S 3A1, Canada;2. Department of Psychology, Brock University, St. Catharines, Ontario L2S 3A1, Canada;3. Cool Climate Oenology and Viticulture Institute, Brock University, St. Catharines, Ontario L2S 3A1, Canada;4. Compusense Inc., Guelph, Ontario N1H 1C5, Canada;5. Charles Sturt University, Locked Bag 588, Wagga Wagga, NSW 2678, Australia;6. University of the Sunshine Coast, Sippy Downs, Queensland 4556, Australia;1. Nofima AS, Osloveien 1, P.O. Box 210, N-1431 Ås, Norway;2. The Norwegian University of Life Sciences, Department of Chemistry, Biotechnology and Food Science (IKBM), Ås, Norway;3. University of Copenhagen, Department of Food Science, Denmark
Abstract:Capturing temporal sensory changes has been the focus in recent research to better understand how consumers perceive food products. This information can be linked to consumer expectations (e.g., liking, satiety) to study the sensory drivers throughout the eating experience, namely temporal drivers. This study explores the use of penalty-lift analyses for each time point in the temporal sensory description to identify the temporal drivers of liking/satiety for different groups of consumers with different patterns in their expectations of satiety.Eight yoghurt samples formulated based on an experimental design, with identical composition, varying in textural properties, were used in the study. Temporal Check-All-That-Apply (TCATA) was used to describe dynamic sensory profiles. Consumers (n = 101) tasted each yoghurt and rated their liking and expected satiety.Cluster analysis of variables around latent variables (CLV) method was applied to cluster consumers based on their expectations of satiety, detecting two relevant clusters.Penalty-lift analysis was used for each time point. Also, the false discovery rate (FDR) was applied to correct p-values for multiple tests responding to sequential time points. Differences were found related to how particle size attributes and flavour intensities drove liking for each cluster at different time points. For cluster 1, while Gritty was positive driver from the middle to the end, Sandy was negative driver in the middle; and Vanilla was positive driver of liking throughout the mastication. For cluster 2, only Sweet was pointed as positive driver at the beginning, and Dry as negative driver in some time points at the middle of the mastication.With regards to expected satiety, main difference was that Gritty (or Sandy) was considered as positive (or negative) driver for cluster 1, but not for cluster 2; significant over the entire time period.These findings demonstrate that the temporal driver approach appears as a suitable method to unveil the drivers of liking/satiety during the eating process in groups of consumers with different eating behaviours and preferences.
Keywords:Liking  Satiety  Penalty-lift analysis  Temporal driver  Yoghurt
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