Modeling growth rates as a function of temperature: model performance evaluation with focus on the suboptimal...

Area of Science:

• Microbiology
• Mathematical Modeling
• Food Safety

Background:

• Microbial growth rate is crucial for predicting spoilage and ensuring food safety.
• Secondary models are used to describe microbial growth as a function of temperature.
• Existing models may not accurately represent growth in suboptimal temperature ranges.

Purpose of the Study:

• To evaluate the performance of secondary models for microbial growth rate at suboptimal temperatures.
• To compare the cardinal temperature model with inflection (CTMI), the square root model (SQRT), and an adapted version (aCTMI).
• To assess model accuracy for Escherichia coli K12 MG1655.

Main Methods:

• Fitting square root of maximum growth rate (μ(max)(T)) estimates using CTMI, SQRT, and aCTMI.
• Focusing on model performance in the suboptimal temperature region.
• Case study using Escherichia coli K12 MG1655.

Main Results:

• The aCTMI provided a more accurate description of the μ(max)(T)-relation compared to CTMI and SQRT, especially below 30 °C.
• The aCTMI yielded a more realistic minimum temperature (T(min)) estimate of approximately 6 °C.
• Improved data description with aCTMI suggests two phases in E. coli's suboptimal growth, possibly linked to cold shock response.

Conclusions:

• The adapted cardinal temperature model with inflection (aCTMI) offers superior performance for describing microbial growth at suboptimal temperatures.
• Commonly used secondary models may have structural limitations in accurately representing temperature effects on microbial growth.
• Findings highlight the importance of model selection for accurate microbial growth prediction in food safety applications.