A neural network application in the design of emulsion-based products

A. Dubbelboer, E. Zondervan, J. Meuldijk, H. Hoogland, P.M.M. Bongers

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Abstract

In the design of emulsion-based products, consumer appreciation is the key aspect. While the most commonly applied product/process design strategies lack the incorporation of consumer desires, this contribution describes a design approach where consumer appreciation is the main objective. The first step of the design is to translate the consumer needs into quantifiable product attributes, e.g. creaminess and firmness for a mayonnaise. A tasting panel is employed to rate these attributes. A Neural Network (NN) is then applied to correlate these attributes with a characteristic product viscosity. The uncertainty of both the measurements and the panel ratings is included in the training and validation of the neural network. According to the Akaike information criterion NN is inferior to partial least squares regression but NN scores better on the validation test; RMSE = 10%.
Original languageEnglish
Title of host publicationProceedings of the 22nd European Symposium on Computer Aided Process Engineering (ESCAPE 22), 17-20 June 2012, London, UK
Place of PublicationLondon
PublisherElsevier
Pages692-696
DOIs
Publication statusPublished - 2012
Event22nd European Symposium on Computer Aided Process Engineering (ESCAPE 22) - University College, London, United Kingdom
Duration: 17 Jun 201220 Jun 2012
Conference number: 22

Conference

Conference22nd European Symposium on Computer Aided Process Engineering (ESCAPE 22)
Abbreviated titleESCAPE
Country/TerritoryUnited Kingdom
CityLondon
Period17/06/1220/06/12

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