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Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior
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Modeling microbial growth and dynamics.

Daniel S Esser1, Johan H J Leveau2, Katrin M Meyer3

  • 1Department of Ecosystem Modelling, University of Göttingen, Büsgenweg 4, 37077, Göttingen, Germany. desser@uni-goettingen.de.

Applied Microbiology and Biotechnology
|August 24, 2015
PubMed
Summary
This summary is machine-generated.

This mini-review explores diverse microbial growth modeling techniques used in applied microbiology, including food safety and wastewater treatment. It highlights the benefits of combining different models and cross-disciplinary approaches for enhanced understanding and experimental design.

Keywords:
BacteriaFood safetyModelPredictive microbiologyWastewater

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Area of Science:

  • Applied Microbiology
  • Mathematical Modeling

Background:

  • Microbial growth modeling is crucial for applied microbiology fields like food safety and wastewater treatment.
  • Numerous modeling techniques exist, ranging from mathematical to agent-based approaches.

Purpose of the Study:

  • To review basic concepts and applications of various microbial growth models.
  • To highlight recent developments, particularly models incorporating spatial relationships.
  • To encourage cross-disciplinary exchange and hybrid modeling approaches.

Main Methods:

  • Summarized basic concepts of diverse modeling techniques.
  • Reviewed applications in food safety and wastewater treatment.
  • Examined recent developments in spatial relationship models.

Main Results:

  • Identified conceptual similarities across different application fields.
  • Demonstrated the utility of models in optimizing experimental design.
  • Showcased the potential of pattern-oriented modeling for parameterization.

Conclusions:

  • Combined use of diverse modeling techniques in hybrid models is encouraged.
  • Cross-disciplinary exchange can enhance microbial growth modeling.
  • Future models will likely leverage a broader, more complex toolbox.