A Gompertz Model Approach to Microbial Inactivation Kinetics by High-Pressure Processing (HPP): Model Selection and...

Area of Science:

• Food Science and Technology
• Microbiology
• Mathematical Modeling

Background:

• High-pressure processing (HPP) is an effective non-thermal method for microbial inactivation in food.
• Accurate kinetic modeling is crucial for optimizing HPP parameters and ensuring food safety.
• Existing models often simplify or neglect dynamic effects like come-up time (CUT).

Purpose of the Study:

• To validate a recently proposed Gompertz model (GMPZ) for describing microbial inactivation kinetics under HPP.
• To evaluate different functions for pressure-dependent lag time (λ) and maximum inactivation rate (μmax).
• To assess the model's predictive capability for Listeria innocua inactivation in milk.

Main Methods:

• Experimental determination of Listeria innocua inactivation in milk at various HPP conditions (300-600 MPa, t hold ≤10 min).
• Application and statistical evaluation of GMPZ incorporating initial load (N0) and limit (Nlim).
• Comparison of exponential, logistic-exponential, and inverse functions for λ and μmax parameters.

Main Results:

• All GMPZ models adequately fitted the experimental data (R² ≥ 0.95).
• Models using a logistic-exponential function for μmax showed superior performance (R² ≥ 0.97).
• The model predicted a theoretical inactivation initiation pressure (Pλ) of ~597 MPa, aligning with experimental observations.

Conclusions:

• The GMPZ approach, particularly with a logistic-exponential function, is a robust tool for modeling HPP microbial inactivation kinetics.
• The model accurately predicts inactivation thresholds and provides insights into pressure effects on microbial survival.
• Further validation across diverse microorganisms and food matrices is recommended for broader application.