Dynamic Model of Heat Inactivation Kinetics for Bacterial Adaptation

Abstract

The Weibullian-log logistic (WeLL) inactivation model was modified to account for heat adaptation by introducing a logistic adaptation factor, which rendered its "rate parameter" a function of both temperature and heating rate. The resulting model is consistent with the observation that adaptation is primarily noticeable in slow heat processes in which the cells are exposed to sublethal temperatures for a sufficiently long time. Dynamic survival patterns generated with the proposed model were in general agreement with those of Escherichia coli and Listeria monocytogenes as reported in the literature. Although the modified model's rate equation has a cumbersome appearance, especially for thermal processes having a variable heating rate, it can be solved numerically with commercial mathematical software. The dynamic model has five survival/adaptation parameters whose determination will require a large experimental database. However, with assumed or estimated parameter values, the model can simulate survival patterns of adapting pathogens in cooked foods that can be used in risk assessment and the establishment of safe preparation conditions.Combined with heat transfer data or models, microbial survival kinetics, especially of bacteria or spores, is extensively used to determine the safety of industrial heat preservation processes like canning, extant or planned. The same is true for milder heat processes such as milk and fruit pasteurization. However, survival models are also a valuable tool to assess the safety of prepared foods, especially those made of raw meats, poultry, and eggs, where surviving pathogens can be a public health issue.The heat resistance of a bacterium, or any other microorganism, is almost always determined from a set of its isothermal survival curves, recorded at several lethal temperatures. The kinetic models, which define the heat resistance parameters, may vary, but the calculation procedure itself is usually the same. First, the experimental isothermal survival data are fitted with what is known as the "primary model." Once fitted, the temperature dependence of this primary model's coefficients is described by what is known as the "secondary model." When combined with a temperature profile expression, T(t), and incorporated into the inactivation rate equation, the result is a "tertiary model," which enables its user to predict the organism's survival curve under any static or dynamic (i.e., nonisothermal) conditions.The traditional log-linear ("first-order kinetic") model is the best-known primary survival model, and it is still widely used in sterility calculations in the food, pharmaceutical, and other industries. Traditionally, it has been assumed that the D value calculated with this model has a log-linear temperature dependence or, alternatively, that the temperature effect on the exponential rate constant, k,

Towards a maximal cell survival in convective thermal drying processes

“…Firstly, in the model it is reasonable to take into account the changing rates of moisture content and temperature. This has been suggested as a future direction even in the area of modeling the microbial inactivation during a heat treatment, where both the temperature and water activity are usually treated as constant (Corradini & Peleg, 2009;Valdramidis, Bernaerts, Van Impe, & Geeraerd, 2005;Valdramidis, Geeraerd, & Van Impe, 2007). Modeling studies of spray drying processes may follow the pattern observed for the fluidized bed drying, where models were firstly developed to describe the drying kinetics of microorganisms, and later combined with the inactivation kinetics.…”

Prediction of targeted Salmonella enterica serovar typhimurium inactivation in fresh cut cantaloupe (Cucumis melo L.) using electron beam irradiation

“…The experimental data (Fig. 6) shows that the survival curve is non-linear; therefore different models could be used to predict its inactivation kinetics for S. typhimurium in fresh cantaloupe by ionizing radiation (Corradini and Peleg, 2009). …”

Inactivation kinetics of Salmonella spp. under thermal and emerging treatments: A review

“…(6) can also be solved using general-purpose software as described by Peleg, Normand, and Corradini (2005). Stasiewicz et al (2008) and Corradini and Peleg (2009) have proposed variants to the Weibull inactivation model in order to account for cell adaptation during exposure to sublethal temperatures. The modifications to the model permitted to adequately estimate the inactivation of several microorganisms, among them Salmonella, when exposed to low heating rates.…”