TIME-INDEPENDENT RHEOLOGICAL BEHAVIOUR OF PEANUT BUTTER: MODELLING AND ARTIFICIAL NEURAL NETWORK APPLICATION

In this study, the rheological behaviour of semisolid peanut butter samples with a fat ratio of 42.7 % were examined in a temperature interval of 10-50 degrees C via rotational rheometer at different shear rates. Peanut butter samples display non-Newtonian yield-pseudoplastic behaviour. Seven model equalities were used for representing the time-independent rheological behaviour of peanut butter and the representation ability of the models were determined by way of determination coefficient (r(2)), mean absolute percentage error (MA%E), chi-square (chi(2)) and root mean square error (RMSE) statistical parameters. It was observed that the O'foli model was the most successful among the models applied to experimental data. Temperature dependency of viscosity at shear rates of 0.1, 0.4 and 0.75 s(-1) was determined via Arrhenius equality and activation energies varied between the interval of 46818.63-51952.52 J/mol. Three-layer model suggested for estimating viscosity using artificial neural network method was observed to be quite successful.