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Fundamental, physics-based modeling of complex food processes is still in the developmental stages. This lack of development can be attributed to complexities in both the material and transport processes. Society has a critical need for automating food processes (both in industry and at home) while improving quality and making food safe. Product, process, and equipment designs in food manufacturing require a more detailed understanding of food processes that is possible only through physics-based modeling. The objectives of this paper are (1) to develop a general multicomponent and multiphase modeling framework that can be used for different thermal food processes and can be implemented in commercially available software (for wider use) and (2) to apply the model to the simulation of deep-fat frying and hamburger cooking processes and validate the results. Treating food material as a porous medium, heat and mass transfer inside such material during its thermal processing is described using equations for mass and energy conservation that include binary diffusion, capillary and convective modes of transport, and physicochemical changes in the solid matrix that include phase changes such as melting of fat and water and evaporation/condensation of water. Evaporation/condensation is considered to be distributed throughout the domain and is described by a novel nonequilibrium formulation whose parameters have been discussed in detail. Two complex food processes, deep-fat frying and contact heating of a hamburger patty, representing a large group of common food thermal processes with similar physics have been implemented using the modeling framework. The predictions are validated with experimental results from the literature. As the food (a porous hygroscopic material) is heated from the surface, a zone of evaporation moves from the surface to the interior. Mass transfer due to the pressure gradient (from evaporation) is significant. As temperature rises, the properties of the solid matrix change and the phases of frozen water and fat become transportable, thus affecting the transport processes significantly. Because the modeling framework is general and formulated in a manner that makes it implementable in commercial software, it can be very useful in computer-aided food manufacturing. Beyond its immediate applicability in food processing, such a comprehensive model can be useful in medicine (for thermal therapies such as laser surgery), soil remediation, nuclear waste treatment, and other fields where heat and mass transfer takes place in porous media with significant evaporation and other phase changes.

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in Wiley Online Library (wileyonlinelibrary.com).Accurate modeling of water transport in food materials requires knowledge of how transport properties depend on the material structure. Water transport in a cellular tissue depends on its pathway (intracellular versus extracellular), which in turn depends on temperature. Using a combination of permeability measurement, pore-size distribution analysis and bioimpedance analysis, it is shown that water in a cellular tissue (e.g., potatoes) is mostly intracellular at lower temperatures at which cell membranes are intact. During drying at high-temperatures, cell membranes in potatoes are damaged, and the moisture transport pathway is primarily extracellular (through intercellular spaces and the lacunae created by the killed cells), with a much lower resistance to water transport. The difference in moisture diffusivity in potatoes for the two pathways has been estimated to be three orders of magnitude. Therefore, transport properties measured or predicted at low temperatures cannot be used for high temperatures because they correspond to different moisture migration pathways.

Alternatives to first-order model of death kinetics of microorganisms have been proposed as improvements in the calculation of lethality for a thermal process. Although such models can potentially improve predictions for many situations, this article tries to answer the question of whether the added complexities of these models are a worthwhile investment once we include the effect of uncertainties in various microbiological and process parameters. Monte Carlo technique is used to include variability in kinetic parameters in lethality calculation for a number of heating processes, for both first-order and Weibull kinetics models. It is shown that uncertainties represented by coefficient of variation in kinetic parameters lead to a wide range of final log-reduction prediction. With the same percent variability in kinetic parameters, uncertainty in the final log reduction for Weibull kinetics was smaller or equal to that for first-order kinetics. Due to the large effect of variability in the input parameters on the final log reduction, the effort to move toward more accurate kinetic models needs to be weighed against inclusion of variability.