Predicting Temperature-Dependent Viscosity of Amazonian Vegetable Oils and Their Mixtures from Fatty Acid Composition

Abstract

Several studies on predicting the viscosity of oils and their mixes are found in the literature. However, data on Amazonian oils are relatively scarce. This study aimed to measure the viscosity and the influence of temperature and of the fatty acid composition of three Amazonian vegetable oils (buriti, pataua, and Brazil nut), as well as their mixtures. Models were applied from the literature and a new equation was presented to predict viscosity. Among the models assessed to estimate the viscosity of the oils and their mixtures as a function of temperature, the Andrade, modified Andrade, and Arrhenius models had the best fits. The models by Grunberg-Nissan and Kendall and Monroe can be used to predict the viscosity of mixtures from their compositions. The equation presented to predict viscosity was shown to be appropriate with R² values above 0.998 and error below 1.0723.

Keywords:

• Viscosity
• Vegetable oil
• Buriti
• Pataua
• Models

FUNDING

The authors acknowledge CAPES and CNPq for granting scholarships and PROPES/UFPA for financial support of this research.

Additional information

Funding

The authors acknowledge CAPES and CNPq for granting scholarships and PROPES/UFPA for financial support of this research.