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ARS Home » Northeast Area » Wyndmoor, Pennsylvania » Eastern Regional Research Center » Microbial and Chemical Food Safety » Research » Publications at this Location » Publication #226933

Title: Mathematical modeling of growth of Salmonella in raw ground beef under isothermal conditions from 10 to 45 Degree C

item Juneja, Vijay
item Huang, Lihan

Submitted to: International Journal of Food Microbiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/26/2009
Publication Date: 5/1/2009
Citation: Juneja, V.K., Melendes, M., Huang, L., Subbiah, J., Thippareddi, H. 2009. Mathematical modeling of growth of Salmonella in raw ground beef under isothermal conditions from 10 to 45 Degree C. International Journal of Food Microbiology. 131:106-111.

Interpretive Summary: Salmonella is a foodborne pathogen very frequently associated with raw meats, including beef. Different growth rates are used to describe the behavior of the pathogen in meat. Their behavior are determined through experiments. This study investigated the growth kinetics of this microorganism in raw beef and compared four different mathematical growth models that can be used to estimate the growth in raw beef under different temperature conditions. The results showed that the performance of all models were similar. The findings will be used by food processors and regulatory agencies to assess the hazards in contaminated beef during storage and distribution.

Technical Abstract: The objective of this study was to develop primary and secondary models to describe the growth of Salmonella in raw ground beef. Primary and secondary models can be integrated into a dynamic model that can predict the microbial growth under varying environmental conditions. Growth data of Salmonella at nine different isothermal conditions – 10, 15, 20, 25, 28, 32, 35, 42, and 45 degree C were first fitted into primary models, namely the logistic, modified Gompertz, Baranyi, and Huang models. Performances of these models were evaluated by using various statistical criteria, namely mean square error (MSE), pseudo-R2, -2 log likelihood, Akaike’s and Bayesian’s information criteria. The modified Gompertz and Baranyi models fitted well to the growth data of Salmonella based on these criteria. The results of statistical analysis showed that there was no significant difference in the performances of the four primary models, suggesting that the models were equally suitable for describing isothermal bacterial growth. The specific growth rates derived from each model was fitted to the Ratkowski equation, relating the specific growth rate to growth temperatures. It was also observed that the lag phase duration was an inverse function of specific growth rates. These models, if validated, can be used to construct dynamic models to predict potential Salmonella growth in raw ground beef.