Mathematical Modeling Techniques in Food and Bioprocesses: An Overview

Authored by: Ashim K. Datta , Shyam S. Sablani

Handbook of Food and Bioprocess Modeling Techniques

Print publication date:  December  2006
Online publication date:  December  2006

Print ISBN: 9780824726713
eBook ISBN: 9781420015072
Adobe ISBN:

10.1201/9781420015072.ch1

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Abstract

A model is an analog of a physical reality, typically simpler and idealized. Models can be physical or mathematical and are created with the goal to gain insight into the reality in a more convenient way. A physical model can be a miniature, such as a benchtop version of an industrial scale piece of equipment. A mathematical model is a mathematical analog of the physical reality, describing the properties and features of a real system in terms of mathematical variables and operations. The phenomenal growth in the computing power and its associated user-friendliness have allowed models to be more realistic and have fueled rapid growth in the use of models in product, process, and equipment design and research. Many advantages of a model include (1) reduction of the number of experiments, thus reducing time and expenses; (2) providing great insight into the process (in case of a physics-based model) that may not even be possible with experimentation; (3) process optimization; (4) predictive capability, i.e., ways of performing “what if” scenarios; and (5) providing improved process automation and control capabilities.

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