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ARS Home » Northeast Area » Wyndmoor, Pennsylvania » Eastern Regional Research Center » Residue Chemistry and Predictive Microbiology Research » Research » Publications at this Location » Publication #366864

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

Location: Residue Chemistry and Predictive Microbiology Research

Title: A predictive growth model for Clostridium botulinum during cooling of cooked uncured ground beef

Author
item Juneja, Vijay
item PUROHIT, ANUJ - University Of Georgia
item GOLDEN, MAX - University Of Wisconsin
item GLASS, KATHLEEN - University Of Wisconsin
item MISHRA, ABHINAV - University Of Georgia
item THIPPARADDI, HARSHAVARDHAN - University Of Georgia
item DEVKUMAR, GOVINDARAJ - University Of Georgia
item MOHR, TIM - Food Safety Inspection Service (FSIS)
item MINOCHA, UDIT - Food Safety Inspection Service (FSIS)
item SILVERMAN, MERYL - Food Safety Inspection Service (FSIS)
item SCHAFFNER, DONALD - Rutgers University

Submitted to: Food Microbiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/5/2020
Publication Date: N/A
Citation: N/A

Interpretive Summary: The disease, botulism, caused by the Clostridium botulinum neurotoxin is a serious public health concern. We investigated the growth of this pathogen in ground beef and used a mathematical model to estimate growth in beef. A validated dynamic model was developed to estimate the growth at temperatures relevant to food processing operations. The model will assist food industry and regulatory agencies to evaluate risk of C. botulinum growth in beef during processing, distribution and storage.

Technical Abstract: A dynamic model to predict the germination and outgrowth of Clostridium botulinum spores in cooked ground beef was developed. Raw ground beef was inoculated with a ten-strain C. botulinum spore cocktail to achieve approximately 2 log spores/g. The inoculated ground beef was vacuum packaged, cooked to 71C to heat shock the spores, cooled to below 10C, and incubated isothermally at temperatures from 10 - 46C. C. botulinum growth was quantified and fitted into the primary Baranyi Model. Secondary models were fitted to maximum specific growth rate and lag phase duration using Modified Ratkowsky equation (R2 0.96) and hyperbolic function (R2 0.94), respectively. Similar experiments were also performed under non-isothermal (cooling) conditions. Acceptable zone prediction (APZ) analysis was conducted on growth data collected over 3 linear cooling regimes from the current study. The model performance (prediction errors) for all 22 validation data points collected in the current work were within the APZ limits (-1.0 to +0.5 log CFU/g). Additionally, two other growth data sets of C. botulinum reported in the literature were also subjected to the APZ analysis. In these validations, 20/22 and 9/14 predictions fell within the APZ limits. The model developed in this work can be employed to predict C. botulinum spore germination and growth in cooked uncured beef under non-isothermal conditions. The beef industry processors and food service organizations can utilize this predictive microbial model for cooling deviations and temperature abused situations and in developing customized process schedules for cooked, uncured beef products.