1. Modeling the Survival and Growth of Salmonella on Chicken Skin Stored at 4 to 12  C Thomas P. Oscar, Ph.D. U.S. Department of Agriculture Agricultural Research Service Princess Anne, MD

2. Introduction Salmonella & poultry Salmonella & poultry 1 - 2 cases per 100,000 1 - 2 cases per 100,000 Initial contamination Initial contamination < 30 CFU per chicken carcass < 30 CFU per chicken carcass Illness dose Illness dose 10 5 to 10 7 CFU 10 5 to 10 7 CFU Int. J. Food Microbiol. 2004. 93:231-247.

3. Introduction Risk Assessment Risk Assessment Hazard Identification Hazard Identification Hazard Characterization Hazard Characterization Exposure Assessment Exposure Assessment Risk Characterization Risk Characterization Packaging Contamination Cold Storage Temp. Abuse Meal Prep. Temp. Abuse Cooking Under-cooking Consumption Exposure Meal Prep. Cross-contamination Risk Pathway

4. Introduction Predictive microbiology Predictive microbiology Support risk assessments Support risk assessments Data gaps Data gaps Low initial dose Low initial dose Microbial competition Microbial competition Low temperatures Low temperatures

5. Introduction Another data gap Another data gap Variation among serotypes Variation among serotypes Autoclaved chicken meat at 25  C J. Food Safety. 2000. 20:225-236.

6. Objective Develop a predictive model Develop a predictive model Survival & growth Survival & growth Salmonella Typhimurium & Kentucky Salmonella Typhimurium & Kentucky Low initial dose (0.9 log) Low initial dose (0.9 log) Chicken thigh skin (2.14 cm 2 ) Chicken thigh skin (2.14 cm 2 ) with microbial competition with microbial competition Low temperature (4 to 12  C) Low temperature (4 to 12  C)

7. Materials & Methods Experimental design Experimental design Model development (Salmonella serotype Typhimurium DT104) Model development (Salmonella serotype Typhimurium DT104) 5 x 5 full factorial 5 x 5 full factorial Temperature (4, 6, 8, 10, 12  C) Temperature (4, 6, 8, 10, 12  C) Time (0, 1, 3, 6, 10 days) Time (0, 1, 3, 6, 10 days) 4 replicates 4 replicates

8. Materials & Methods Experimental design Experimental design Model validation (Salmonella serotype Typhimurium DT104) Model validation (Salmonella serotype Typhimurium DT104) 4 x 5 full factorial 4 x 5 full factorial Temperature (5, 7, 9, 11  C) Temperature (5, 7, 9, 11  C) Time (0, 1, 3, 6, 10 days) Time (0, 1, 3, 6, 10 days) 2 replicates 2 replicates

9. Materials & Methods Experimental design Experimental design Model validation (Salmonella serotype Kentucky) Model validation (Salmonella serotype Kentucky) 4 x 5 full factorial 4 x 5 full factorial Temperature (5, 7, 9, 11  C) Temperature (5, 7, 9, 11  C) Time (0, 1, 3, 6, 10 days) Time (0, 1, 3, 6, 10 days) 2 replicates 2 replicates

10. Materials & Methods Salmonella enumeration Salmonella enumeration Combined MPN & CFU method Combined MPN & CFU method  MPN  CFU J. Food Prot. 2006. 69:2048-2057.

11. Materials & Methods Plating media Plating media Salmonella serotype Typhimurium DT104 Salmonella serotype Typhimurium DT104 XLH-CATS XLH-CATS Salmonella serotype Kentucky Salmonella serotype Kentucky XLH-NATS XLH-NATS J. Food Prot. 2006. 69:2048-2057.

12. Materials & Methods General Regression Neural Network Model General Regression Neural Network Model Tt ……-0.714.13 N(x)D(x) ŷ Input Layer Pattern Layer Summation Layer Output (Δ) Temp. time Distance Function Predicted Value IEEE Trans. Neural. Netw. 1991. 2:568-576

13. Materials & Methods Model performance Model performance Residual Residual Observed - predicted Observed - predicted Acceptable prediction zone (APZ) Acceptable prediction zone (APZ) -1 log (fail-safe) to 0.5 log (fail-dangerous) -1 log (fail-safe) to 0.5 log (fail-dangerous) Acceptable performance Acceptable performance  70% of residuals in APZ  70% of residuals in APZ Prediction bias & accuracy J. Food Sci. 2005. 70:M129-M137.

14. Results Salmonella serotype Typhimurium DT104 Salmonella serotype Typhimurium DT104 Model development (n = 163) Model development (n = 163)

15. Results Salmonella serotype Typhimurium DT104 Salmonella serotype Typhimurium DT104 Model validation for interpolation (n = 77) Model validation for interpolation (n = 77)

16. Discussion Salmonella serotype Typhimurium DT104 Salmonella serotype Typhimurium DT104 Growth on sterile chicken breast meat at 10  C Growth on sterile chicken breast meat at 10  C Oscar (unpublished)

17. Results Salmonella serotype Kentucky Salmonella serotype Kentucky Model validation for extrapolation (n = 70) Model validation for extrapolation (n = 70)

18. Discussion Variation among serotypes Variation among serotypes Kentucky grows slower on chicken skin at 35  C Kentucky grows slower on chicken skin at 35  C J. Food Prot. 2009. 72:2078-2087.

19. Results & Discussion Model Performance (Development) Model Performance (Development)

20. Results & Discussion Model Performance (Interpolation) Model Performance (Interpolation)

21. Results & Discussion Model Performance (Extrapolation) Model Performance (Extrapolation)

22. Results & Discussion

23. Conclusions Model was validated Model was validated Microbial competition suppresses growth Microbial competition suppresses growth MPD = 1 log vs 8 log @ 10  C MPD = 1 log vs 8 log @ 10  C Kentucky grows slower Kentucky grows slower Compatible with @Risk Compatible with @Risk