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Modeling Food Process, Quality and Safety: Frameworks and Challenges

Chapter
Part of the Food Engineering Series book series (FSES)

Abstract

Physics-based models provide increased understanding and predictive capabilities that can increase efficiency in food product, process, and equipment design; they also improve quality and safety. However, certain key food-specific developments are needed to enable widespread use of simulation technology in the food sector. First and foremost is the need to develop concise modeling frameworks (formulating various food-processing situations in mathematical models) for various classes of processes, as opposed to a custom model for each process, as mostly exists today. Deformable porous media with multiphase transport can provide such a framework, as will be discussed through examples of various processes that have been modeled by many researchers. The next critical piece is to have easy access to the properties that needed to be model. State-of-property prediction, starting from simple correlations and proceeding to multiscale modeling and thermodynamics-based and molecular dynamics, as is being pursued by researchers around the world, will be shared. Prediction beyond process to quality and safety is the third topic, where various approaches to modeling quality in a diffusion-reaction modeling framework will be presented. For safety, a practical approach that groups various food products, and thus provides an avenue to simulate safety for a large number of situations, will be shared. Finally, efforts to integrate modeling components into a novel, user-friendly software for increased use of modeling will be described.

Keywords

Capillary Pressure Food Process Microwave Heating Food Material Solid Skeleton 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This project was partially supported by National Research Initiative Grant 2008-35503-18657 from the U.S. Department of Agriculture Cooperative State Research, Education, and Extension Service Competitive Grants program.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Cornell UniversityIthacaUSA

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