Growth Kinetics and Predictive Growth Model of Aeromonas hydrophila in a Squid-based System

Introduction: Predictive modeling provides a fast and relatively cost-effect way to obtain reliable first estimates of microbial growth and survival. Predictive model was estimated Aeromonas hydrophila growth and to determine the shelf life of squid.

Purpose: This study investigated the growth characteristics of A. hydrophila on fresh squid and subsequently developed a predictive growth model of A. hydrophila on fresh squids as a function of storage temperature (5, 10, 20, 30, and 40 °C) using a response surface model (RSM). The model can be used as a reference in controlling A. hydrophila growth without the need for detection of the organism and may be of use for controlling growth.

Methods: Culture (1.0 x 10² cfu/g) as a cocktail of A. hydrophila (KCTC2358, KCTC12847, and KCCM11533) was inoculated on 5-10 spots on the surface of the squid. The squids were then stored at 5, 10, 20, 30, or 40 °C under aerobic conditions. The lag time and growth rate fitted to the modified Gompertz equation using a nonlinear regression model and the relationship of the lag time and growth rate to the growth curves was modeled using an RSM polynomial equation. The assessment of the RSM for describing the growth A. hydrophila of was evaluated using mean square error (MSE), bias (B_f) and accuracy factors (A_f).

Results: The A. hydrophila can grow on squid under refrigerated conditions, although the growth of the organism decreased at low temperatures. The primary models that we developed to obtain the specific growth rates (SGR) and lag time (LT) fit well (r ² = 0.973-0.999) with the Gompertz equation. Secondary polynomial models were obtained by non-linear regression analyses and calculated as: SGR model = 0.05152 + 0.00337*T + 0.00039*T²; and LT model = 50.51030 - 2.56290*T + 0.03446*T². The appropriateness of the secondary polynomial model was verified by the mean square error (MSE; 0.006 for the SGR model and 0.256 for the LT model), bias factor (B_f; 0.999 for the SGR model and 1.007 for the LT model), accuracy factor (A_f; 1.025 for the SGR model and 1.026 for the LT model), and coefficient of determination (r²; 0.991 for the SGR model and 0.993 for the LT model).

Significance: Our models may be of application fresh squid for manufacture of safe products by controlling A. hydrophila growth without the need for detection of the organism.