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ARS Home » Northeast Area » Wyndmoor, Pennsylvania » Eastern Regional Research Center » Microbial and Chemical Food Safety » Research » Publications at this Location » Publication #381849

Research Project: Data Acquisition, Development of Predictive Models for Food Safety and their Associated Use in International Pathogen Modeling and Microbial Databases

Location: Microbial and Chemical Food Safety

Title: Predictive model for growth of Clostridium perfringens during cooling of cooked pork supplemented with sodium chloride and sodium pyrophosphate

item Juneja, Vijay
item Osoria, Marangeli
item PUROHIT, ANUJ - Applied Measurement Sciences
item GOLDEN, CHASE - University Of Georgia
item MISHRA, ABHINAV - University Of Georgia
item TANEJA, NEETU - National Institute Of Technical Teachers Training & Research
item SALAZAR, JOELLE - Food And Drug Administration(FDA)
item THIPPAREDDI, HARSHAVARDHAN - University Of Georgia
item DEV KUMAR, GOVINDARAJ - University Of Georgia

Submitted to: Meat Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/11/2021
Publication Date: 5/14/2021
Citation: Juneja, V.K., Osoria, M., Purohit, A.S., Golden, C.E., Mishra, A., Taneja, N.K., Salazar, J.K., Thippareddi, H., Dev Kumar, G. 2021. Predictive model for growth of Clostridium perfringens during cooling of cooked pork supplemented with sodium chloride and sodium pyrophosphate. Meat Science.

Interpretive Summary: Clostridium perfringens continues to be a pathogen of concern to the food industry. Illnesses caused by this bacterium have been traditionally associated with inadequate rate and extent of cooling in retail food service establishments. Thus, there was a need to determine the cooling time and temperature for cooked meat products to remain pathogen-free and provide vital data for conducting risk assessment on cooked meat. We developed a model that can be used to predict the growth of C. perfringens at temperatures applicable to the cooling of cooked products. The predictive model will be useful to the retail food service operations and regulatory agencies to aid with the disposition of products subject to cooling deviations and therefore, ensure the safety of the cooked foods.

Technical Abstract: A dynamic model was developed to predict growth of Clostridium perfringens in cooked ground pork supplemented with salt (0-3% wt/wt) and sodium pyrophosphate (0-0.3% wt/wt) under varying temperatures. C. perfringens (NCTC 8238, NCTC 8239, and NCTC 10240) spores were heat shocked, cooled, and inoculated into ground pork. Isothermal bacterial growth was quantified with variable salt and phosphate concentrations at temperatures ranging from 15 - 51C. The primary Baranyi model was fitted to all C. perfringens growth profiles and gave a satisfactory fit (R2 more than 0.85). A quadratic polynomial secondary model was developed to predict the maximum specific growth rate as a function of temperature, salt, and phosphate concentrations (R2= 0.93). A dynamic model was developed and validated using growth data retrieved from 7 published studies. Thirty three out of 44 predictions were within the acceptable prediction zone (-0.5 less than or equal to prediction error less than or equal to1.0). The developed predictive model will be used in minimizing the risk of C. perfringens in pork products supplemented with additives during cooling.