Proper selection of rheological models is very important in flow characterization. These models are often used to evaluate parameters that help in the characterization of food samples. Rheological models also provide flow predictions for extreme conditions where the flow nature of the fluid cannot be determined, hence the need for appropriate selection of rheological models. The principal aim of this study is to suggest a rheological model that best characterize the rheological behavior of native cassava starch and to determine the effect of state variables like temperature and concentration on the accuracy of rheological models. Five rheological models (i.e. Herschel-Bulkley model, Robertson-Stiff model, Power-law model, Bingham plastic model and Prandtl-Eyring model) were selected for this study and these models were modified into statistical models by the inclusion of the error variance (ε). The least-square method was used in evaluating the various model parameters for each model. From this study, it was seen that the Herschel-Bulkley model and the Robertson-Stiff model most accurately described the rheological patterns in cassava starch production. The sensitivity analysis of the different rheological models also shows that the accuracy of the Herschel-Bulkley model, Robertson-Stiff model and Power-law model is not significantly affected by variations in temperature and concentration of the cassava starch. However, it was observed that the Bingham plastic model and Prandtl-Eyring model gave less accurate predictions at higher concentration and lower temperature respectively. A lot of the industrially accepted models such as the Bingham plastic model may not necessarily be the best model for characterization cassava starch production as shown in this study, hence rheological model optimization is recommended for further study.
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