Exploring amazonian fats and oils blends by computational predictions of solid fat content

Abstract

The Amazon region has richness of oleaginous plants that have attracted attention due to its unique properties. Integrating local communities in an economic chain of valorization of fats/oils can enhance the social dimension of local oleaginous industry sustainability. Given the large diversity of raw materials and the possibility to mix them in different proportions, an experimental effort must be done to evaluate the physical properties of such feedstocks. In this context, the development of computational tools able to estimate physical properties based on rigorous thermodynamic models can orient the experimental efforts thorough the mixtures of fats and oils most promising. The evaluation of the melting curves of nine Amazonian oils and fats is done by using thermodynamic modeling of the solid-liquid equilibrium and optimization tools. The binary blends of different raw materials were also evaluated. An average absolute error of 4.5 °C was observed for the melting point and an absolute error of 3.8% was observed for the Solid Fat Content predictions over different temperatures and blends composition.