Mechanistic Fermentation Models for Process Design, Monitoring, and Control

Mechanistic Fermentation Models for Process Design, Monitoring, and Control Mechanistic models require a significant investment of time and resources, but their application to multiple stages of fermentation process development and operation can make this investment highly valuable. This Opinion article discusses how an established fermentation model may be adapted for application to different stages of fermentation process development: planning, process design, monitoring, and control. Although a longer development time is required for such modeling methods in comparison to purely data-based model techniques, the wide range of applications makes them a highly valuable tool for fermentation research and development. In addition, in a research environment, where collaboration is important, developing mechanistic models provides a platform for knowledge sharing and consolidation of existing process understanding. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Trends in Biotechnology Elsevier

Mechanistic Fermentation Models for Process Design, Monitoring, and Control

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Publisher
Elsevier Current Trends
Copyright
Copyright © 2017 Elsevier Ltd
ISSN
0167-7799
D.O.I.
10.1016/j.tibtech.2017.07.002
Publisher site
See Article on Publisher Site

Abstract

Mechanistic models require a significant investment of time and resources, but their application to multiple stages of fermentation process development and operation can make this investment highly valuable. This Opinion article discusses how an established fermentation model may be adapted for application to different stages of fermentation process development: planning, process design, monitoring, and control. Although a longer development time is required for such modeling methods in comparison to purely data-based model techniques, the wide range of applications makes them a highly valuable tool for fermentation research and development. In addition, in a research environment, where collaboration is important, developing mechanistic models provides a platform for knowledge sharing and consolidation of existing process understanding.

Journal

Trends in BiotechnologyElsevier

Published: Oct 1, 2017

References

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