Food Science and Technology Department

 

Department of Food Science and Technology: Faculty Publications

Document Type

Article

Date of this Version

2012

Citation

Published in Journal of Food Engineering 112: 1-2 (2012), pp. 100-111; doi: 10.1016/j.jfoodeng.2012.03.013

Comments

Copyright © 2012 Elsevier Ltd. Used by permission.

Abstract

Microwave ovens are used extensively for heating a variety of not-ready-to-eat food products. Non-uniform heating of foods in microwave ovens is a major concern in assuring microbiological safety of such products. The non-uniform heating of foods is attributed by complex interaction of microwaves with foods. To understand this complex interaction, a comprehensive model was developed to solve coupled electromagnetic and heat transfer equations using finite-difference time-domain based commercial software. The simulation parameters, cell size, heating time step, and number of iterations for steady state electromagnetic field were optimized. The model was validated by 30 s heating profile of a cylindrical model food (1% gellan gel) in a 700 W microwave oven. The model was validated qualitatively by comparing the simulated temperature profiles on three planes in the gel and compared them to the corresponding thermal images. Quantitative validation was performed by comparing simulated temperature of the gel at 12 locations with experimental temperature acquired at those points using fiber optic sensors. Simulated spatial temperature profiles agreed well with the thermal image profiles. The root mean square error values ranged from 0.53 to 4.52 °C, with an average value of 2.02 °C. This study laid a framework for selecting the required model parameters which are critical for better temperature prediction. The developed model can be effectively used to identify hot and cold spots in food products, thereby helping in microwaveable food product development to achieve better cooking performance in terms of heating uniformity, food quality and safety. The model can also be used to identify the best product, package and cavity parameters to achieve better heating uniformity and electromagnetic distribution inside the cavity.

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