Validation of a tertiary model for predicting variation of Salmonella typhimurium DT104 (ATCC 700408) growth from a low initial density on ground chicken breast meat with a competitive microflora.

Growth of a multiple antibiotic-resistant strain (ATCC 700408) of Salmonella Typhimurium definitive phage type 104 (DT104) from a low initial density (10(0.6) most probable number [MPN] or CFU/g) on ground chicken breast meat with a competitive microflora was investigated and modeled as a function of time and temperature (10 to 40 degrees C). MPN and viable counts (CFU) on a selective medium with four antibiotics enumerated the pathogen. Data from five replicate challenge studies per temperature were combined and fit to a primary model to determine maximum specific growth rate (micro), maximum population density (Nmax), and the 95% prediction interval (PI). Nonlinear regression was used to obtain secondary models as a function of temperature for micro, Nmax, and PI, which ranged from 0.04 to 0.4 h(-1), 1.6 to 9.4 log MPN or CFU/g, and 1.4 to 2.4 log MPN or CFU/g, respectively. Secondary models were combined with the primary model to create a tertiary model for predicting variation (95% PI) of pathogen growth among batches of ground chicken breast meat with a competitive microflora. The criterion for acceptable model performance was that 90% of observed MPN or CFU data had to be in the 95% PI predicted by the tertiary model. For data (n=344) used in model development, 93% of observed MPN and CFU data were in the 95% PI predicted by the tertiary model, whereas for data (n=236) not used in model development but collected using the same methods, 94% of observed MPN and CFU data were in the 95% PI predicted by the tertiary model. Thus, the tertiary model was successfully verified against dependent data and validated against independent data for predicting variation of Salmonella Typhimurium DT104 growth among batches of ground chicken breast meat with a competitive microflora and from a low initial density.