Interval-valued sensory evaluation for customized beverage product formulation and continuous manufacturing

Isaev, Svetlin, Jreissat, Mohannad, Makatsoris, Charalampos, Bachour, Khaled, McCulloch, Josie and Wagner, Christian (2017) Interval-valued sensory evaluation for customized beverage product formulation and continuous manufacturing. In: 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017), 9-12 July 2017, Naples, Italy.

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Abstract

Understanding of consumer preferences and perceptions is a vital challenge for the food and beverage industry. Food and beverage product development is a very complex process that deals with highly uncertain factors, including consumer perceptions and manufacturing complexity. Sensory evaluation is widely used in the food industry for product design and defining market segments. Here, we develop a two-step approach to minimize uncertainty in the food and beverage product development, including consumers as co-creators. First, we develop interval-valued questionnaires to capture sensory perceptions of consumers for the corresponding sensory attributes. The data captured is modelled with fuzzy sets in order to then facilitate the design of new consumer-tailored products. Then, we demonstrate the real-world manufacture of a personalized beverage product with a continuous food formulation system. Finally, we highlight consumers` perceptions for the corresponding sensory attributes and their fuzzy set generated agreement models to capture product acceptance for the formulated and commercial orange juice drinks, and consequently to establish that continuous beverage formulator is capable of making similar commercial products for individuals.

Item Type: Conference or Workshop Item (Paper)
RIS ID: https://nottingham-repository.worktribe.com/output/871908
Additional Information: Published in: 2017 IEEE International Conference on Fuzzy Systems. (FUZZ-IEEE), doi: 10.1109/FUZZ-IEEE.2017.8015695
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Depositing User: Eprints, Support
Date Deposited: 26 Apr 2017 07:27
Last Modified: 04 May 2020 18:54
URI: https://eprints.nottingham.ac.uk/id/eprint/42283

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