Submitted to: Innovative Food Science and Emerging Technologies
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/1/2002
Publication Date: 4/1/2003
Citation: Juneja, V.K., Marks, H.M. 2003. Mathematical description of non-linear survival curves of listeria monocytogenes as determined in a beef gravy model system at 57.5 to 65c. Innovative Food Science and Emerging Technologies. 4:307-317. Interpretive Summary: Listeria monocytogenes is a pathogen of major concern for the food industry because of its association with several outbreaks of foodborne illness. One of the common and effective means of controlling this bacterium is the application of adequate heat treatment. When bacterial populations are heated they usually die at a constant rate, but there are exceptions. Consequently, the food industry and regulatory agencies need a tool to choose the best mild heat treatment to apply for the production of safe food. We have developed a mathematical model that can be used to predict the destruction of the deadly pathogen. This information will be of immediate use to consumers and to the food industry and regulatory agencies to aid in the development of guidelines to ensure safety of the food supply.
Technical Abstract: This paper presents a nonlinear model for predicting the inactivation of Listeria monocytogenes, suspended in beef broth after heat treatment. A five-strain cocktail of L. monocytogenes was used in developing inactivation data at 57.5C, 60C, 62.5C and 65C, where maximum observed lethalities were more than 7 log10 for the latter three temperatures. For all four temperatures, the survival curves, i.e., the common logarithms (base 10) of the numbers of surviving cells versus times, were distinctly convex. Four functions, based on different assumptions underlying the shape of the survival curves, were compared. The assumptions involve the asymptotic behavior of the survival curves. Mechanistic considerations were used in deriving some of the functions considered. The function selected for further modeling was the logistic function, where the natural logarithm of time is the independent variable. Using this function, a model for predicting the amount of inactivation for temperatures between 57.5C and 65C was determined. The model presented in this paper is different from models that have been presented in the predictive microbiology literature, in that the parameters that describe the model are assumed to be random variables. Thus, a full description of the model includes standard deviations of parameters, which were estimated using a mixed- effects analysis. Other research has indicated a logistic function adequately describes survival curves of L. monocytogenes. The use of this function entails that there are not non-zero asymptotic D-values. In conclusion, there is a substantial body of evidence suggesting that nonlinear models are needed for characterizing survival curves of L. monocytogenes.