Submitted to: International Association for Food Protection
Publication Type: Abstract Only
Publication Acceptance Date: 12/1/2003
Publication Date: 8/8/2004
Citation: Oscar, T.P. 2004. Verification of a tertiary model for growth of salmonella. International Association for Food Protection. T50.
Technical Abstract: Incorporation of predictive models for pathogen growth into user-friendly computer software applications (tertiary modeling) is important for their routine use in the food industry to assess food safety. Kinetic data for high-density (4.8 log CFU/g) growth of Salmonella Typhimurium ATCC 14028 on sterile cooked ground chicken breast meat portions (1 g) incubated at 8 to 47 C were fit to a logistic with delay primary model to determine lag time (LT), maximum specific growth rate (SGR) and maximum population density (MPD). Secondary models for LT, SGR, and MPD were combined in a computer spreadsheet with the primary model to create a tertiary model that predicted changes in density of S. Typhimurium as a function of time and temperature. Ability of the tertiary model to reverse the modeling process and predict the data used to develop it (i.e., verification) was evaluated using a safe prediction zone method where the log cycle difference (Delta) between observed density and density predicted by the tertiary model was determined for 433 prediction cases obtained from 30 growth curves. The proportion of Delta (pDelta) in a safe prediction zone from a Delta of -0.5 (fail-safe) to 0.25 (fail-dangerous) log CFU per g was used as the index of model performance. Models with pDelta greater than 0.7 were found to provide unbiased and accurate predictions of Salmonella growth. An acceptable pDelta of 0.79 was obtained for the tertiary model predictions of the kinetic data used to develop it and thus, its predictions were successfully verified.