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Measurement, Modeling and Automation in Advanced Food Processing

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Attention for Chapter 9: How to Decide on Modeling Details: Risk and Benefit Assessment
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Chapter title
How to Decide on Modeling Details: Risk and Benefit Assessment
Chapter number 9
Book title
Measurement, Modeling and Automation in Advanced Food Processing
Published in
Advances in biochemical engineering biotechnology, January 2017
DOI 10.1007/10_2017_9
Pubmed ID
Book ISBNs
978-3-31-960109-0, 978-3-31-960111-3
Authors

Mustafa Özilgen, Özilgen, Mustafa

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.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 29%
Other 1 14%
Unknown 4 57%
Readers by discipline Count As %
Engineering 2 29%
Unknown 5 71%