Estimating microbial growth parameters from non-isothermal data: a case study with Clostridium perfringens

Area of Science:

• Microbiology
• Food Science
• Mathematical Modeling

Background:

• Traditional microbial growth parameter calculation relies on isothermal data.
• Non-isothermal (dynamic) data offers an alternative for deriving growth parameters.
• This requires numerical solutions of rate models incorporating temperature profiles.

Purpose of the Study:

• To demonstrate a methodology for deriving microbial growth parameters from non-isothermal data.
• To validate the method using simulated and experimental microbial growth data.
• To explore the potential for in situ growth modeling under dynamic temperature conditions.

Main Methods:

• Numerical solution of a rate model with temperature-dependent coefficients.
• Application to simulated non-isothermal microbial growth data with added noise.
• Validation using known growth parameters and experimental data of *C. perfringens* in ground beef.

Main Results:

• Successful retrieval of known generation parameters from simulated dynamic growth curves.
• Application to experimental *C. perfringens* data demonstrated prediction under different temperature histories.
• The method's practicality is currently limited by data scatter and collection frequency.

Conclusions:

• Deriving microbial growth parameters from dynamic temperature data is feasible.
• Further improvements in data quality and collection frequency are needed for practical application.
• The method holds promise for in situ microbial growth prediction during food processing, transport, and storage.