Prediction of the thermophysical properties of papaya seed oil influencing solvent selection based on the new group contribution model

Abstract

As one of the sustainable food sources, papaya seed oil (PSO) has extraordinary health benefits with unsaturated fatty acids being the main components. In general, the PSO extraction can be accomplished by predetermining the thermophysical properties of the PSO, appropriate use of solvent, and operating conditions. However, the thermophysical properties data of the PSO in the literature are quite scarce, while their quantitative measurements are expensive and time-consuming. For this reason, the group contribution models (GCMs) that have been developed over the last few decades can be essential tools for the estimation of the thermophysical properties of PSO. Moreover, this study also proposes a new GCM to predict PSO thermophysical properties based on its fatty acids composition and validate the accuracy using the experimental data available in the literature. The results showed that the new model has excellent accuracy in estimating the thermophysical properties of PSO at 298.15 K and normal boiling point (Tb). The average absolute relative deviation (AARD) for enthalpy of vaporization values at both temperatures were 2.09% and 2.04%, respectively. Meanwhile, the AARD values for molar volume at both temperatures were 0.48% and 0.86%, respectively. Accordingly, the estimated values of the Hansen’s solubility parameters and partition coefficients were very close to the experimental data with a distance (D) of 0.21 and AARD of 0.030%. Therefore, this model can be employed to quickly predict the important PSO properties and other its unknown properties based on its molecular structure for its extraction purpose.