Related Experiment Video
Updated: Aug 6, 2025
08:19
Modified Most Probable Number Assay to Quantify Salmonella in Raw and Ready-to-Cook Chicken Products
Published on: January 31, 2025
458
Combined Quantification and Deep Serotyping for Salmonella Risk Profiling in Broiler Flocks
Tomi Obe1, Amy T Siceloff1, Megan G Crowe1
1Poultry Diagnostic and Research Center, Department of Population Health, College of Veterinary Medicine, University of Georgia, Athens, Georgia, USA.
Applied and Environmental Microbiology
|March 15, 2023
Summary
Salmonella contamination in poultry remains a concern despite product safety improvements. This study introduces a novel surveillance method combining Salmonella quantity and serotype identification for better pre-harvest risk assessment and control in broiler flocks.
Area of Science:
- Food Safety
- Veterinary Microbiology
- Public Health
Background:
- Human salmonellosis cases from poultry remain high, despite reduced contamination on final products.
- Effective pathogen mitigation requires targeting resilient serovars and reducing pre-processing contamination.
- Molecular methods offer rapid detection and quantification of Salmonella for improved surveillance.
Purpose of the Study:
- To develop and evaluate a high-resolution Salmonella surveillance approach for broiler farms.
- To combine Salmonella quantification and deep serotyping for pre-harvest risk assessment.
- To inform on-farm management and processing strategies for enhanced poultry safety.
Main Methods:
- Collected 160 boot sock samples from 20 broiler farms across four integrators.
- Utilized deep serotyping and CRISPR-SeroSeq for Salmonella serovar identification and quantification.
- Generated flock-specific risk scores based on Key Performance Indicator (KPI) serovars, abundance, and quantity.
Main Results:
- Salmonella detected in 85% of houses, with an average quantity of 3.6 log10 CFU/sample.
- Eleven serovars identified, including USDA-FSIS KPIs (Enteritidis, Infantis, Typhimurium).
- Eight multidrug-resistant isolates identified, seven of which were serovar Infantis.
Conclusions:
- A framework combining Salmonella quantity and deep serotyping provides a high-resolution surveillance approach.
- This method can inform on-farm management practices and minimize cross-contamination risks.
- The framework is adaptable for Salmonella surveillance in other food animal production systems.
