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FUZZY CLUSTERING MODELING AND EVALUATION OF SURFACE INTERACTIONS AND EMULSIONS OF SELECTED WHEAT PROTEIN COMBINED TO IOTA‐CARRAGEENAN AND GUM ARABIC SOLUTIONS
Author(s) -
ABUGHOUSH MAHMOUD,
SAMHOURI MURAD,
YASEEN EMAD,
HERALD THOMAS
Publication year - 2010
Publication title -
journal of food process engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.507
H-Index - 45
eISSN - 1745-4530
pISSN - 0145-8876
DOI - 10.1111/j.1745-4530.2008.00324.x
Subject(s) - surface tension , emulsion , gum arabic , chemistry , carrageenan , cluster analysis , arabic , biological system , chromatography , chemical engineering , thermodynamics , computer science , physics , food science , artificial intelligence , organic chemistry , linguistics , philosophy , biology , engineering
Gums and proteins are valuable ingredients with a wide spectrum of applications. Surface properties (surface tension, interfacial tension, emulsion activity index [EAI] and emulsion stability index [ESI]) of 4% deamidated wheat protein (DWP) in a combination with iota‐carrageenan (IC) (0.05, 0.1 and 0.5%) or gum arabic (GA) (0.5, 1 and 5%) were investigated. The results showed that the addition of IC to 4% DWP significantly increased the surface tension, interfacial tension, EAI and ESI, whereas the addition of GA to 4% DWP significantly increased the surface tension and decreased the interfacial tension and EAI (except at 5% of GA). In addition, a fuzzy‐based clustering model was used to predict the surface properties of the DWP. The fuzzy model achieved accuracies of (97%, 90%, 97% and 75%) for predicting (EAI, ESI, surface tension and interfacial tension), respectively. This approach can be applied to predict many other parameters and properties in the food industry.PRACTICAL APPLICATIONS The surface properties (surface tension, interfacial tension, emulsion activity index and emulsion stability index) of wheat protein (DWP) in combination with iota‐carrageenan or gum arabic were investigated. In addition, subtractive clustering‐based fuzzy models for predicting the surface properties of DWP was constructed. This modeling can be used as an indicator of usefulness of fuzzy clustering in such a system which directly can be used as a tool by the food processors to produce a high quality beverage product.