Salmonella has been studied and researched for more than a hundred years and yet it remains a problem for human and animal health. The goal of this dissertation was to apply the systems thinking approach to Salmonella contamination and develop a System Dynamics (SD) simulation model for Salmonella contamination in the chill tank of a poultry processing plant. But first the appropriate carcass rinse sampling method that would not impact on the resulting Salmonella contamination status of the broiler carcass was studied. Kappa agreement analysis was used to evaluate three sampling methods. The adjacent rinse method was found to be the best method. In the absence of actual data, literature data was used to develop a literature-based SD simulation model of Salmonella contamination of broiler carcasses in the chill tank. The literature-based SD model is the first application of system dynamics simulation modeling in the poultry-processing field. The model was able to show and simulate the dynamic and non-linear interrelationships between parameters, namely pH, chlorine (Cl) level, water flow and turbidity. Actual data collection was done using a specially designed apparatus that recorded the time, temperature, pH, chlorine, water flow and turbidity in the chill tank as carcass rinse samples were collected. Linear regression analysis was used to identify the statistically significant models for relationships between the parameters in the chill tank. Finally, the data was analyzed using logistic regression to determine the association between the parameters in the chill tank and the occurrence of Salmonellaa in carcasses exiting the chill tank. These results were used to develop a data-based SD model. The data-based model was then validated using the validity tests proposed by various authors for SD simulation models and found to be a valid model. The developed model offers a fresh perspective to the problem of Salmonella contamination- to view it as a system of factors that are interrelated and have a feedback mechanism, rather than the traditional concept of linear causation. The developed model is a powerful cost efficient tool for testing interventions for reducing Salmonella contamination in the poultry processing plant.

Campylobacter is a foodborne pathogen commonly found in live poultry and raw poultry products. Identifying areas of contamination or modes of transmission during commercial processing can lead to strategies to reduce the level of Campylobacter on finished products. Monitoring levels of airborne Campylobacter may be useful for identifying the presence or relative concentration of the pathogen in a processing plant environment. In this study, air sampling was used to detect and quantify Campylobacter in a commercial chicken processing plant by location within the plant and collection time during the day. Air was sampled from evisceration and post-chill areas in a poultry processing plant on four days and at 4 hour intervals onto Campy-Cefex agar plates or gelatin filters that were subsequently transferred to Campy-Cefex agar plates. Additionally, pre-evisceration and post-chill carcass rinses were analyzed quantitatively for Campylobacter. The mean level of airborne Campylobacter was 5 CFU/1000L of air sampled (10% samples positive) in comparison with 413 CFU/mL from carcass rinses (70% samples positive). Higher concentrations were found in carcass rinse samples from pre-evisceration. Airborne Campylobacter was detected from the evisceration area more frequently than from the post-chill carcass area of the plant (P < 0.05). This study shows that airborne Campylobacter can be quantified with a selective agar and with gelatin filter collection. Further research is needed to prove the utility of airborne detection of Campylobacter for estimating the relative contamination level of live poultry flocks and the processing plant environment and the potential for cross-contamination. / Master of Science in Life Sciences