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Measurement, Modeling and Automation in Advanced Food Processing pp 153–193Cite as

How to Decide on Modeling Details: Risk and Benefit Assessment

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Part of the book series: Advances in Biochemical Engineering/Biotechnology ((ABE,volume 161))

Abstract

Mathematical models based on thermodynamic, kinetic, heat, and mass transfer analysis are central to this chapter. Microbial growth, death, enzyme inactivation models, and the modeling of material properties, including those pertinent to conduction and convection heating, mass transfer, such as diffusion and convective mass transfer, and thermodynamic properties, such as specific heat, enthalpy, and Gibbs free energy of formation and specific chemical exergy are also needed in this task. The origins, simplifying assumptions, and uses of model equations are discussed in this chapter, together with their benefits. The simplified forms of these models are sometimes referred to as “laws,” such as “the first law of thermodynamics” or “Fick’s second law.” Starting to modeling a study with such “laws” without considering the conditions under which they are valid runs the risk of ending up with erronous conclusions. On the other hand, models started with fundamental concepts and simplified with appropriate considerations may offer explanations for the phenomena which may not be obtained just with measurements or unprocessed experimental data. The discussion presented here is strengthened with case studies and references to the literature.

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Authors and Affiliations

  1. Food Engineering Department, Yeditepe University, 34755, Kayisdagi, Istanbul, Turkey

    Mustafa Özilgen

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  1. Mustafa Özilgen
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Correspondence to Mustafa Özilgen .

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  1. Institute of Food Science and Biotechnology, University of Hohenheim, Stuttgart, Baden-Württemberg, Germany

    Bernd Hitzmann

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Özilgen, M. (2017). How to Decide on Modeling Details: Risk and Benefit Assessment. In: Hitzmann, B. (eds) Measurement, Modeling and Automation in Advanced Food Processing. Advances in Biochemical Engineering/Biotechnology, vol 161. Springer, Cham. https://doi.org/10.1007/10_2017_9

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