Review of effective thermal conductivity models for foods

Abstract The literature associated with modelling and predicting the thermal conductivities of food products has been reviewed. The uncertainty involved in thermal conductivity prediction increases as the differences between the food components' thermal conductivities increase, which means that there is greater uncertainty involved with predicting the thermal conductivity of foods which are porous and/or frozen, than with unfrozen, non-porous foods. For unfrozen, non-porous foods, a number of simple effective thermal conductivity models that are functions only of the components' thermal conductivities and volume fractions may be used to provide predictions to within ±10%. For frozen and/or porous foods, the prediction procedure is more complicated, and usually requires the prediction of porosity and/or ice fraction, which introduces another source of error. The effective thermal conductivity model for these foods may require an extra parameter (in addition to the components' thermal conductivities and volume fractions) whose value must often be determined empirically. Recommendations for selecting models for different classes of foods are provided. There is scope for more research to be done in this area.

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