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United States Department of Agriculture

Agricultural Research Service

Research Project: EPIDEMIOLOGY, ECOLOGY, AND MOLECULAR GENETICS OF ANTIMICROBIAL RESISTANCE IN PATHOGENIC AND COMMENSAL BACTERIA FROM FOOD ANIMALS

Location: Bacterial Epidemiology and Antimicrobial Resistance

Title: Use of stochastic modeling to predict prevalence of Salmonella positive broilers entering the processing plant

Authors
item Cosby, Douglas
item Bailey, Joseph
item Hofacre, Charles - UNIVERSITY OF GEORGIA
item Cole, Dana - GA DEPT OF HUMAN RESOURCE
item Finklin, Marilynn - UNIVERSITY OF GEORGIA
item Turner, Bradley - UNIVERSITY OF GEORGIA

Submitted to: Southern Poultry Science Society Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: December 8, 2006
Publication Date: January 22, 2007
Citation: Cosby, D.E., Bailey, J.S., Hofacre, C.L., Cole, D., Finklin, M., Turner, B.J. 2007. Use of stochastic modeling to predict prevalence of Salmonella positive broilers entering the processing plant. Southern Poultry Science Society Meeting Abstracts. P167. 55.

Technical Abstract: In the U.S. salmonellae are responsible for approximately 15% (approximately 40,000 cases) of all food borne illnesses per year and improperly handled or undercooked poultry and eggs are often identified as a source of salmonellosis in humans. Since chickens are a major carrier for salmonellae, determining the prevalence of contaminated chickens entering a plant has become a priority in order to assess the cross contamination that may affect poultry products exiting the plant. Samples were collected from six houses on individual farms and from a single local integrator followed through the processing plant. On-farm (boot socks, drag swabs, litter composites, cloacal swabs, ceca and carcass rinses) and in-plant (ceca and carcass rinses) samples were evaluated to determine the relationships between Salmonella prevalence on the farm to that found in the processing plant. Prevalence data was analyzed using Spearman correlation coefficients and regression to determine relationship between on-farm and plant data. Using the data collected, a stochastic model (Crystal Ball 7®) was developed to predict the prevalence distribution of Salmonella spp., contaminated birds entering the plant. Boot socks showed the strongest correlation with plant carcass rinses (r=0.7882), and cloacal swabs were most predictive of plant ceca contamination (r=0.8111), although neither was significant at P< 0.05. More research in the area of on-farm contamination and in plant contamination is needed to accurately model the true end point contamination of poultry products to reduce and/or prevent food borne illnesses related to poultry and poultry products.

Last Modified: 9/22/2014
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