Multiphase transport models of food processes require surface heat and mass transfer coefficients as boundary conditions that are traditionally assumed. A conjugate heat and mass transfer model is solved for simple microwave heating of food as a porous medium (from which vapor blows out) with air flow over it, such that there is no need to provide the boundary conditions at the food-air interface. Surface fluxes due to diffusion and flow (blowing) are computed for both vapor and heat from which transfer coefficients are obtained. As evaporation increases with heating, vapor flux due to pressure-driven flow increases but remains small compared with diffusive flux. Vapor accumulation at the interface increases the diffusive flux, leading to an 8% increase in mass transfer coefficient. Heat transfer at the interface occurs through both conduction and flow, and the heat transfer coefficient shows a slight decrease (10%) as blowing increases with heating. The rate of heating has minimal effect on the transfer coefficients. (C) 2011 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

A multiphase model based on unsaturated flow in a hygroscopic porous medium, which accounts for the important physical phenomena that take place during thermal treatment of meat, is developed. Frozen meat is considered as a porous solid comprising of water, fat and protein with gas trapped in its pores. As it is heated, water and fat melt, and, are gradually released from the solid protein matrix to the pore space. With further rise in temperature, liquid water evaporates. Since four fluid components (liquid water phase, liquid fat phase, water vapor and air) are present in the pore space, a mass balance equation is written for each component. Local thermal equilibrium assumption leads to one energy balance equation for the whole system. The model is validated for double-sided contact heating of hamburger patties by comparing temperature and moisture profiles with experimental studies. Dominant modes of transport are identified. (c) 2012 Elsevier Ltd. All rights reserved.

Computer-aided engineering tools can help speed up food product, process and equipment design by making it easier to check "what if" scenarios, much as such tools have improved productivity in other industries. In particular, food safety is a critical area where such predictive tools can have great impact. A realistic, integrated and comprehensive software has been developed that can simulate a food process and its safety by combining a fundamental, physics-based model of the process with the kinetics of microbiological and chemical changes during processing to provide needed information at any time and at any location in the food during processing. Compositions for a large number of foods are integrated into the software, and therefore, composition-based prediction of thermophysical properties, needed for the model, can be obtained. Microbiological and chemical kinetic databases that are also built-in can cover many practical situations, based on the grouping of foods. An intuitive graphical user interface has been built with those in the food sector in mind.

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. (C) 2010 American Institute of Chemical Engineers AIChE J, 57: 2574-2588, 2011

The objective of this study was to use an existing database of food products and their associated processes, link it with a list of the foodborne pathogenic microorganisms associated with those products and finally identify growth and inactivation kinetic parameters associated with those pathogens. The database was to be used as a part of the development of comprehensive software which could predict food safety and quality for any food product. The main issues in building such a predictive system included selection of predictive models, associations of different food types with pathogens (as determined from outbreak histories), and variability in data from different experiments. More than 1000 data sets from published literature were analyzed and grouped according to microorganisms and food types. Final grouping of data consisted of the 8 most prevalent pathogens for 14 different food groups, covering all of the foods (>7000) listed in the USDA Natl. Nutrient Database. Data for each group were analyzed in terms of 1st‐order inactivation, 1st‐order growth, and sigmoidal growth models, and their kinetic response for growth and inactivation as a function of temperature were reported. Means and 95% confidence intervals were calculated for prediction equations. The primary advantage in obtaining group‐specific kinetic data is the ability to extend microbiological growth and death simulation to a large array of product and process possibilities, while still being reasonably accurate. Such simulation capability could provide vital ‘‘what if’’ scenarios for industry, Extension, and academia in food safety.

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.

The objective of this study was to use an existing database of food products and their associated processes, link it with a list of the foodborne pathogenic microorganisms associated with those products and finally identify growth and inactivation kinetic parameters associated with those pathogens. The database was to be used as a part of the development of comprehensive software which could predict food safety and quality for any food product. The main issues in building such a predictive system included selection of predictive models, associations of different food types with pathogens (as determined from outbreak histories), and variability in data from different experiments. More than 1000 data sets from published literature were analyzed and grouped according to microorganisms and food types. Final grouping of data consisted of the 8 most prevalent pathogens for 14 different food groups, covering all of the foods (>7000) listed in the USDA Natl. Nutrient Database. Data for each group were analyzed in terms of 1st-order inactivation, 1st-order growth, and sigmoidal growth models, and their kinetic response for growth and inactivation as a function of temperature were reported. Means and 95% confidence intervals were calculated for prediction equations. The primary advantage in obtaining group-specific kinetic data is the ability to extend microbiological growth and death simulation to a large array of product and process possibilities, while still being reasonably accurate. Such simulation capability could provide vital "what if" scenarios for industry, Extension, and academia in food safety.

This article is part of a collection entitled “Models for Safety, Quality, and Competitiveness of the Food Processing Sector,” published in Comprehensive Reviews in Food Science and Food Safety. It has been peer‐reviewed and was written as a follow‐up of a pre‐IFT workshop, partially funded by the USDA NRI grant 2005‐35503‐16208.

The multiphase porous media model, developed in the companion paper, has been applied to frying of a restructured potato slice to obtain temperature, pressure, moisture, oil content, acrylamide content and evaporation rate profiles, providing valuable insight into the frying process. The model is validated by comparing temperature, moisture content and crust thickness profiles from literature experimental results. A novel non-equilibrium formulation, different from the existing food literature, is able to describe well the evaporation process. Post-frying cooling is included through appropriate changes in boundary conditions. It is seen that the oil pickup mostly takes place during post-frying cooling and is due to capillary suction created by the negative pressures from condensation of water–vapour. Acrylamide is formed primarily in the crust region where temperature exceeds 100°C. Sensitivity analyses of the process to surface mass transfer coefficient, evaporation rate constant and oil diffusivity show that they all have significant effects on the process. Development of this mechanistic model that is also more easily implementable than previous models should make computer-aided design and optimization of frying processes closer to reality.