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United States Department of Agriculture

Agricultural Research Service

Research Project: NON-THERMAL AND ADVANCED THERMAL FOOD PROCESSING INTERVENTION TECHNOLOGIES Title: An integrated model for predictive microbiology and simultaneous determination of lag phase duration and exponential growth rate

Author
item Huang, Lihan

Submitted to: International Conference on Predictive Modeling in Foods
Publication Type: Proceedings
Publication Acceptance Date: September 7, 2009
Publication Date: N/A

Technical Abstract: A new mechanistic growth model was developed to describe microbial growth under isothermal conditions. The development of the mathematical model was based on the fundamental phenomenon of microbial growth, which is normally a three-stage process that includes lag, exponential, and stationary phases. A differential logistic growth model was adopted to describe the competitive nature of microbial growth in the exponential and stationary phases. Incorporated with a transitional function to define the lag phase, an integrated differential logistic growth model was developed and solved analytically. The new model was capable of describing a complete three-phase growth curve or a partial growth curve that contains only lag and exponential phases. The new integrated model was validated using Listeria monocytogenes in tryptic soy broth and beef frankfurters and Escherichia coli O157:H7 in mechanically tenderized beef. The inoculated samples were incubated at various temperature conditions and enumerated to obtain isothermal growth curves. A nonlinear regression procedure in SAS was employed to analyze each growth curve to simultaneously determine the lag phase duration and exponential growth rate. Both bias factor (Bf) and accuracy factor (Af) were used to evaluate the performance of the new model. Results indicated that both Bf and Af values were very close to 1.0, suggesting that the new model was very suitable for describing isothermal microbial growth. Modified Ratkowsky models were used to analyze lag phase durations and exponential growth rates and develop secondary models. The maximum and minimum temperatures obtained from the resulting secondary models matched closely with the biological nature of L. monocytogenes and E. coli O157:H7.

Last Modified: 10/31/2014
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