Development and validation of primary, secondary, and tertiary models for growth of Salmonella Typhimurium on sterile chicken.
Models are used in the food industry to predict pathogen growth and to help assess food safety. However, criteria are needed to determine whether models provide acceptable predictions. In the current study, primary, secondary, and tertiary models for growth of Salmonella Typhimurium (10(4.8) CFU/g) on sterile chicken were developed and validated. Kinetic data obtained at 10 to 40 degrees C were fit to a primary model to determine initial density (N0), lag time (lambda), maximum specific growth rate (micromax), and maximum population density (Nmax). Secondary models for N0, lambda, micromax, and Nmax as a function of temperature were developed and combined with the primary model to create a tertiary model that predicted pathogen density (N) at times and temperatures used and not used in model development. Performance of models was evaluated using the acceptable prediction zone method in which experimental error associated with growth parameter determinations was used to set criteria for acceptable model performance. Models were evaluated against dependent and independent (validation) data. Models with 70% prediction or relative errors (RE) in an acceptable prediction zone from -0.3 to 0.15 for micromax, -0.6 to 0.3 for lambda, and -0.8 to 0.4 for N, N0, and Nmax were classified as acceptable. All secondary models had acceptable goodness of fit and were validated against independent (interpolation) data. Percent RE in the acceptable prediction zone for the tertiary model was 90.7 for dependent data and 97.5 for independent (interpolation) data. Although the tertiary model was validated for interpolation, an unacceptable %RE of 2.5 was obtained for independent (extrapolation) data obtained with a lower N0 (10(0.8) CFU/g). The tertiary model provided overly fail-dangerous predictions of N from a lower N0. Because Salmonella concentrations on chicken are closer to 10(0.8) than 10(4.8) CFU/g, the tertiary model should not be used to help assess chicken safety.
Oscar
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U.S. Department of Agriculture, Agricultural Research Service, Center for Food Science and Technology, University of Maryland Eastern Shore, Princess Anne, Maryland 21853, USA. toscar@umes.edu
D000818:Animals; D002645:Chickens / Q000382:microbiology*; D015169:Colony Count, Microbial; D003198:Computer Simulation; D003257:Consumer Product Safety; D005516:Food Microbiology; D006801:Humans; D008954:Models, Biological; D011237:Predictive Value of Tests; D012486:Salmonella typhimurium / Q000254:growth & development*; D012680:Sensitivity and Specificity; D013696:Temperature; D013997:Time Factors