Modeling microbial kinetics as a function of temperature: Evaluation of dynamic experiments to identify the growth/inactivation interface

On optimum dynamic temperature profiles for thermal inactivation kinetics determination

Determination of inactivation kinetics, associated with thermal processing of foods and obtained from dynamic temperature experiments, requires carefully designed experiments, the primary element being the selection of the appropriate temperature profile along with a carefully planned sampling schedule. In the present work, a number of different dynamic temperature profiles were investigated in terms of their ability to generate accurate kinetic parameters with low confidence intervals (CIs). Although alternative models have been also tested, our work was concentrated on thermal inactivation kinetics that could be described by the classical D-z values. A pair of D and z values was assumed, and for each temperature profile tested, concentration data at different processing times were generated through the appropriate models. Next, an error (up to ±2.5% or ±5%) was introduced on these theoretical values to generate pseudo-experimental data, and the back-calculation of the assumed kinetic parameters by non-linear regression was performed. The accuracy and the 95% CIs of the estimated kinetic parameters were evaluated; joint confidence regions were also constructed to investigate parameters correlation. The effect of temperature profile pattern, level of error, number of experimental points, and reference temperature was assessed. A stepwise increasing and a single triangle-pattern temperature profile were the best profiles among those tested. As a general observation, based on different kinetic models investigated, temperature profiles and sampling intervals that result in concentration versus time diagrams having shapes as suggested by the primary model used when isothermally applied are not considered appropriate for parameter estimation.

One-Step Analysis for Listeria monocytogenes Growth in Ready-to-Eat Braised Beef at Dynamic and Static Conditions

This study aimed to estimate the growth parameters of Listeria monocytogenes growth in ready-to-eat (RTE) braised beef by one-step dynamic and static kinetic analysis. The Baranyi model and cardinal parameters model were integrated into a dynamic and static model to estimate the kinetic parameters under one dynamic condition (-20 to 40.0°C) and eight static conditions (4, 8, 15, 20, 30, 35, 37, and 40°C). Based on the dynamic and static methods, the respective dynamic and static results for estimated growth boundaries of L. monocytogenes in RTE braised beef were from -2.5 and -2.7°C to 40.5 and 40.7°C with optimal specific growth rates of 1.078 and 0.913 per h at temperatures of 35.7 and 35.0°C. Temperature effects on the specific growth rate and lag period were developed and used to simulate the change of the physiological state of inocula during the bacterial growth. Subsequently, three additional dynamic temperature profiles were implemented for external validation. The root mean square error of the model developed by dynamic regression (0.19 log CFU/g) is slightly better than that of the model developed by static regression (0.23 log CFU/g). Comparing the validation results, one-step dynamic analysis might be a preferable method for prediction, especially when the growth approaches the stationary phase. Generally, both one-step dynamic and static analyses could be used to accurately predict L. monocytogenes growth in RTE braised beef under fluctuating temperatures.