This study was conducted to determine the prevalence and antimicrobial resistance of Salmonella isolates recovered from processed poultry. Four hundred eighty pre- and postchill whole broiler chicken carcasses were collected from a poultry processing plant between July 2004 and June 2005. Water samples also were collected at the entrance and exit of the chiller. After preenrichment, carcass and water samples were analyzed for the presence of Salmonella using the automated BAX system followed by traditional culture methods. The proportions of pre- and postchill carcasses that were positive for Salmonella were 88.4 and 84.1%, respectively. Ninety-two percent of water samples collected at the entrance of the chiller were positive for Salmonella, but all exit samples were negative. There was no significant difference in the prevalence of Salmonella between pre- and postchill carcasses (P > 0.05). Salmonella isolates recovered were serotyped and tested for susceptibility to antimicrobials. Thirteen serotypes were identified; the most common were Salmonella Kentucky (59.5%) and Salmonella Typhimurium (17.8%). Three hundred thirty-nine (79.8%) of the isolates were resistant to at least one antimicrobial, and 53.4% were resistant to three or more antimicrobials. Resistance was most often observed to tetracycline (73.4% of isolates), ampicillin (52.9%), amoxicillin-clavulanic acid (52%), ceftiofur (51.7%), streptomycin (35.2%), and sulfisoxazole (21.8%). These results indicate the high prevalence of Salmonella contamination in whole broiler carcasses, and a large number of these Salmonella isolates were resistant to commonly used antimicrobials.

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.

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