Computational studies on physico-chemical properties in the quality analysis of corn and peanut oil

Abstract

Oils are commonly used in cooking as a frying medium which has been constantly subjected to different levels of heating. In this work, we have considered the most commonly used oils namely peanut oil and corn oil. Quality analyses of corn and peanut oils were made by relating macroscopic properties (ultrasonic velocity, viscosity, and density) to microscopic parameters (intermolecular free length, adiabatic compressibility etc.,) by subjecting them to six cycles of heating (190 ˚C). Variation in the mentioned property indexes, the degree of degradation and reusability for the next heating cycle that could be used in the food industry and processing were monitored. Using Newton-Laplace and Wood’s equation, the adiabatic compressibility, acoustic impedance, and intermolecular free length of the oil were estimated from the experimental data. Ultrasonic velocity was observed linearly as related to viscosity with the dependency factor (R2 = 0.932). With the aid of experiential data, the physical thermodynamic parameters, particularly particle size, packing factor, chemical potential, and L-J potential were computed. A high correlation factor was observed by fitting ultrasonic velocity, viscosity, and density to Parthasarathy and Bakshi, and Rodenbush equations. In the study, ultrasonic velocity, a macroscopic parameter, could be decoded to determine the microscopic variations in oil subjected to different temperatures in an industrial application.