Modeling the rheological behavior of thermosonic extracted guava, pomelo, and soursop juice concentrates at different concentration and temperature using a new combination model

This study has modeled the rheological behavior of thermosonic extracted pink‐fleshed guava, pink‐fleshed pomelo, and soursop juice concentrates at different concentrations and temperatures. The effects of concentration on consistency coefficient (K) and flow behavior index (n) of the fruit juice concentrates was modeled using a master curve which utilized the concentration‐temperature shifting to allow a general prediction of rheological behaviors covering a wide concentration. For modeling the effects of temperature on K and n, the integration of two functions from the Arrhenius and logistic sigmoidal growth equations has provided a new model which gave better description of the properties. It also alleviated the problems of negative region when using the Arrhenius model alone. The fitted regression using this new model has improved coefficient of determination, R (2) values above 0.9792 as compared to using the Arrhenius and logistic sigmoidal models alone, which presented minimum R (2) of 0.6243 and 0.9440, respectively. PRACTICAL APPLICATIONS: In general, juice concentrate is a better form of food for transportation, preservation, and ingredient. Models are necessary to predict the effects of processing factors such as concentration and temperature on the rheological behavior of juice concentrates. The modeling approach allows prediction of behaviors and determination of processing parameters. The master curve model introduced in this study simplifies and generalized rheological behavior of juice concentrates over a wide range of concentration when temperature factor is insignificant. The proposed new mathematical model from the combination of the Arrhenius and logistic sigmoidal growth models has improved and extended description of rheological properties of fruit juice concentrates. It also solved problems of negative values of consistency coefficient and flow behavior index prediction using existing model, the Arrhenius equation. These rheological data modeling provide good information for the juice processing and equipment manufacturing needs.