DYNAMIC MECHANICAL SPECTRA OF SELECTED TURKISH HONEYS: CONSTRUCTION OF PREDICTIVE MODELS FOR COMPLEX VISCOSITY USING TWO DIFFERENT NONLINEAR MODELING TECHNIQUES

Abstract

Dynamic oscillatory shear rheological characteristics of honey samples from different floral sources were evaluated using frequency sweep test and stress sweep test at three different temperatures (10, 15, and 20 degrees C). All honey samples showed liquid-like behavior because the loss modulus was significantly greater than the elastic modulus. Pine honey showed the highest complex viscosity (86.33 Pa s at 10 degrees C), while the lowest complex viscosity was observed in citrus honey (22.15 Pa s) at the same temperature. Temperature dependency of complex viscosity of honey samples was modeled by Arrhenius model and activation energy values of honeys ranged from 83.13 to 97.46 kJ/mol. An efficient predictive model for complex viscosity values of honeys was constructed using adaptive neuro fuzzy inference system that showed satisfactory prediction performance with high coefficient of determination (0.995) and low root mean square error (0.04) in the validation period compared to artificial neural networks.