The temperature of chilled foods is a very important variable for microbial safety in a production and distribution chain. To predict the number of organisms as a function of temperature and time, it is essential to model the lag time, specific growth rate, and asymptote (growth yield) as a function of temperature. The objective of this research was to determine the suitability and usefulness of different models, either available from the literature or newly developed. The models were compared by using an F test, by which the lack of fit of the models was compared with the measuring error. From the results, a hyperbolic model was selected for the description of the lag time as a function of temperature. Modified forms of the Ratkowsky model were selected as the most suitable model for both the growth rate and the asymptote as a function of temperature. The selected models could be used to predict experimentally determined numbers of organisms as a function of temperature and time. Predictive modeling is a promising field in food microbi-ology. Models are used to describe the behavior of microor-ganisms at different physical and chemical conditions, such as temperature, pH, and water activity. They can be used to predict microbial safety or shelf life of products, to find critical points in the process, and to optimize production and distribution chains. A major factor determining the specific growth rate of microorganisms in chilled foods is tempera-ture. Various models have been proposed to describe this relationship. Spencer and Baines (16) proposed a linear dependency of the rate of microbial spoilage of fish on temperature. This relationship was shown to be valid only at temperatures below 6°C (8). Therefore, Olley and Rat-kowsky (8) proposed an Arrhenius (2)-type equation. This equation could predict results up to 15°C. However during cooling, freezing, heating, or thawing, regions in the product can have a temperature far above 15°C, and therefore a wider growth-temperature range is important. Schoolfield et al. (13) proposed a nonlinear Arrhenius type of model on a biological basis, describing the specific growth rate as a function of temperature over the whole biokinetic tempera-ture range. Further empirical models were proposed by Ratkowsky et al. (10, 11), i.e., the square root model, describing the specific growth rate up to 15°C, and the expanded square root model, describing the growth rate over the whole biokinetic temperature range. A model which is only seldom used is the model of Hinshelwood (7), although it is a simple model with a biological basis. Adair et al. (1) modeled the growth rate and the inverse of the lag time using the Ratkowsky and Schoolfield models and concluded that the Schoolfield model gives the best predictions. The literature provides us with a number of models. However, a systematic approach to determine the most suitable model is lacking. The objective of this research was to determine the suitability and usefulness of the different models by systematic and statistical analysis of a large amount of experimental data.
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