Please use this identifier to cite or link to this item: http://hdl.handle.net/11189/2291
Title: Emulsion stability and steady shear characteristics of concentrated oil-in-water emulsion stabilized by gelatinized Bambara groundnut flour
Authors: Adeyi, Oladayo 
Ikhu-Omoregbe, D 
Jideani, Victoria A 
Issue Date: 2013
Source: Adeyi, O., Ikhu-Omoregbe, D. & Jideani, V. 2014. Emulsion Stability and Steady Shear Characteristics of Concentrated Oil-in-Water Emulsion Stabilized by Gelatinized Bambara Groundnut Flour. Asian Journal of Chemistry, 26(16): 4995-5002.
Abstract: Effect of sunflower oil and bambara groundnut flour concentrations on the stability and steady shear flow behaviour of concentrated sunflower oil-in-water (o/w) emulsion stabilized by gelatinized bambara groundnut flour dispersions was studied. Emulsion stability was studied using Turbiscan MA 2000 by observing changes in the average D-backscattering flux (%) at 20 °C. The steady shear flow behaviours were also modeled by two rheological equations. Both bambara groundnut flour and sunflower oil concentration affected the emulsion stability and rheological behaviour. Increase in oil phase fraction and bambara groundnut flour concentration improved emulsion creaming and led to increase in the emulsion viscosity. Kinetics of destabilization showed that increase in sunflower oil and bambara groundnut flour concentration has profound effect on emulsion destabilization. For the steady shear flow models, both of the rheological models tested were found to predict the rheological behaviour of the emulsions. Herschel-Bulkley (H-B) predicted an increase in consistency index, yield stress and decrease in flow behaviour index with increase in the oil and bambara groundnut flour concentrations while Casson model revealed that all emulsions studied possessed yield stress and plastic viscosity which increased as sunflower oil and bambara groundnut flour concentration increased. However, high value of coefficient of determination (R2) coupled with low root mean square error and standard error made Casson model a better predictor.
Description: 2nd International Conference and Exhibition on Food Processing and Technology
URI: http://hdl.handle.net/11189/2291
http://dx.doi.org/10.14233/ajchem.2014.16287
Appears in Collections:Eng - Conference Papers

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