Linking sensory perceptions anc physical properties of orange drinks

McCulloch, Josie, Isaev, Svetlin, Bachour, Khaled , Jreissat, Mohannad, Wagner, Christian and Makatsoris, Charalampos (2017) Linking sensory perceptions anc physical properties of orange drinks. 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC) . pp. 1511-1516.

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Linking sensory perceptions anc physical properties of orange drinks
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Item Type:Article
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This paper investigates if sensory perceptions of orange drinks (e.g., acidity, thickness, wateriness) can be linked to physical measurements (e.g., pH, particle size, density). Using this information, manufactured drinks can be tailored according to consumer’ desires by, for example, the consumer providing a sensory description of their preferred drink. Sensory perceptions of different juices are collected in a survey and used to determine 1) if consumers can distinguish between different drinks using the provided sensory descriptors, and 2) if the perceptions match to physical measurements of the drinks. Results show that most of the given sensory descriptors are useful in describing differences in orange drinks. Additionally, the perceived wateriness and thickness of the drinks can be predicted from measurements. However, the perceived acidity could not be reliably predicted. The results show that personally tailored orange beverages can be manufactured according to some of the consumer’s desires and there is scope for future developments tailored to a wider range of drink attributes.

Keywords:Atmospheric measurements, Particle measurements, Fuzzy sets, Temperature measurement, Density measurement, Vocabulary, Size measurement, beverage industry, beverages, customer profiles, food additives, statistical analysis, drink attributes, sensory perceptions, physical properties, orange drinks, physical measurements, manufactured drinks, consumer desires, sensory description, preferred drink, provided sensory descriptors, given sensory descriptors, personally tailored orange beverages
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
Divisions:College of Science > School of Computer Science
ID Code:34886
Deposited On:02 May 2019 10:17

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