Development of a Novel Growth Model Based on the Central Limit Theorem for the Determination of Beef Spoilage

Currently, no published studies are available that compare central limit theorem model with traditionally used growth models in predictive food microbiology to describe bacterial growth behaviors of Pseudomonas spp. in beefs. The major objectives of the present study were to develop a novel growth model based on the central limit theorem and compare the prediction capability of the model with those of various growth models (modified Gompertz, logistic, Baranyi and Huang models) commonly used in predictive food microbiology. Material and Methods: Bacterial growth data for Pseudomonas spp. were collected from previously published studies on beefs stored at isothermal storage temperatures (0, 4, 7, 10, 15 and 20 °C). Temperature dependent kinetic parameters (maximum specific growth rate ‘μmax’ and lag phase duration ‘λ’) collected from various primary models were described as functions of storage temperatures using Ratkowsky model. Fitting capability of the novel growth model based on the central limit theorem was compared with other growth models using mean square error and coefficient of determination. Results and Conclusion: The novel growth model developed in this study provided mean square errors less than 0.104 and coefficients of determination greater than 0.962. No significant differences (p>0.05) were seen between the statistical indices of this developed model and traditionally used growth models. Results have shown that the novel growth model based on the central limit theorem can be used to describe the growth behaviors of microorganisms as alternative to traditionally used growth models of modified Gompertz, logistic, Baranyi and Huang models in predictive food microbiology. Furthermore, this novel model can be used for the prediction of shelf-life of beefs as a function of temperature since spoilage of beefs is directly linked to the load of Pseudomonas spp.