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The aim of predictive microbiology is the provision of tools and methods for predicting the growth, survival, and death of microorganisms in different food matrices under a range of environmental conditions. The parametrized mathematical models need to be calibrated using dedicated experimental data. In order to efficiently plan experiments, model-based experimental design is used. In this chapter, we explain model-based experimental design and provide step-by-step instructions for finding the optimal design using the well-known Baranyi-Roberts growth model as an example. We provide the Python software eDPM for Ordinary Differential Equation (ODE)-based models, such that the reader can apply model-based experimental design in their research context.

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Experimental Design for Predictive Models in Microbiology Depending on Environmental Variables

  • 章节

  • 发表日期：

    2025年

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  • Polina Gaindrik,
  • Jonas Pleyer,
  • Daniel Heger,
  • Christian Fleck

摘要

The aim of predictive microbiology is the provision of tools and methods for predicting the growth, survival, and death of microorganisms in different food matrices under a range of environmental conditions. The parametrized mathematical models need to be calibrated using dedicated experimental data. In order to efficiently plan experiments, model-based experimental design is used. In this chapter, we explain model-based experimental design and provide step-by-step instructions for finding the optimal design using the well-known Baranyi-Roberts growth model as an example. We provide the Python software eDPM for Ordinary Differential Equation (ODE)-based models, such that the reader can apply model-based experimental design in their research context.