Magnetic resonance imaging and mathematical modeling of ohmic heating process

Ohmic heating is a thermal process in which heat is internally generated by the passage of alternating electrical current through a body such as a food system that serves as an electrical resistor. Ohmic heating technology has shown significant promise in a number of food processes, especially in the pasteurization and sterilization of liquid-particulate food mixtures. However, lack of the understanding of the process and the absence of a non-invasive temperature monitoring method hindered its applications in food processing. No successful application of ohmic heating for multiphase foods has been filed with the Food and Drug Administration. The primary objective of this research was to develop a rapid temperature mapping technique using Magnetic Resonance Imaging (MRI) and apply it, together with mathematical modeling, to the ohmic heating of liquid-particulate food mixtures in order to gain an insight into the heating characteristics of this complex process. The Proton Resonance Frequency shift method was incorporated into MRI phase imaging via a Fast Low Angle SHot (FLASH) sequence to conduct temperature mapping during ohmic heating without interrupting the electrical heating power. A spatial resolution of 0.94 mm and a temporal resolution of 0.64 sec for the temperature mapping were achieved. Viscous brine and whey protein gel/potato particles were used as model liquid-particulate mixtures to be ohmically heated and monitored using MRI temperature mapping. The most important factor affecting ohmic heating---electrical conductivity of the materials---and their temperature dependence were experimentally studied. Heat convection effect at the liquid-particulate interface was investigated. A model system predicting the time-temperature profile was proposed and experimentally verified via MRI temperature mapping. The modeling procedures proposed in this research successfully predicted the temperature profile during static ohmic heating processes, especially the locations of the "cold" spot and the "hot" spot which are of importance in the process design and control. The use of electricity-to-heat conversion efficiency improved the accuracy of the model prediction. Application of the MRI temperature mapping provided a detailed verification of the model predictions. The modeling procedures can be used to simulate different heating conditions for product formulation, process design, and process control.