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

A recently proposed Gompertz model (GMPZ) approach describing microbial inactivation kinetics by high-pressure processing (HPP) incorporated the initial microbial load (N₀ ) and lower microbial quantification limit (N_lim ), and simplified the dynamic effects of come-up time (CUT). The inactivation of Listeria innocua in milk by HPP treatments at 300, 400, 500, and 600 MPa and pressure holding times (t_hold ) ≤10 min was determined experimentally to validate this model approach. Models based on exponential, logistic-exponential, and inverse functions were evaluated to describe the effect of pressure on the lag time (λ) and maximum inactivation rate (μ_max ), whereas the asymptote difference (A) was fixed as A = log₁₀ (N₀ /N_lim ). Model performance was statistically evaluated and further validated with additional data obtained at 450 and 550 MPa. All GMPZ models adequately fitted L. innocua data according to the coefficient of determination (R²  ≥ 0.95) but those including a logistic-exponential function for μ_max (P) were superior (R²  ≥ 0.97). These GMPZ versions predicted that approximately 597 MPa is the theoretical pressure level (P_λ ) at which microbial inactivation begins during CUT, mathematically defined as λ (P = P_λ ) = t_CUT , and matching the value observed on the microbial survival curve at 600 MPa. As pressure increased, predictions tended to slightly underestimate the HPP lethality in the tail section of the survival curve. This may be overseen in practice since the observed microbial counts were below the predicted log₁₀ N values. Overall, the modeling approach is promising, justifying further validation work for other microorganisms and food systems.