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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 #358453

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 Bacillus cereus at temperatures applicable to cooling of cooked pasta

Author
item Juneja, Vijay
item GOLDEN, CHASE - University Of Georgia
item MISHRA, ABHINAV - University Of Georgia
item HARRISON, MARK - University Of Georgia
item MOHR, TIM - Food Safety Inspection Service (FSIS)

Submitted to: Journal of Food Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/18/2019
Publication Date: 3/16/2019
Citation: Juneja, V.K., Golden, C.E., Mishra, A., Harrison, M.A., Mohr, T. 2019. Predictive model for growth of Bacillus cereus at temperatures applicable to cooling of cooked pasta. Journal of Food Science. https://doi.org/10.1111/1750-3841.14448.
DOI: https://doi.org/10.1111/1750-3841.14448

Interpretive Summary: A predictive model was developed to predict the relative growth of Bacillus cereus from spores during cooling of cooked pasta. Cooked pasta was inoculated with a cocktail of four strains of heat-shocked (80C/10 min) B. cereus spores to obtain a final spore concentration of approximately 2 log CFU/g. Thereafter, growth was determined at isothermal temperatures starting at 10C and every three degrees up to 49C. Samples were removed periodically and plated on mannitol egg yolk polymyxin agar. The plates were incubated for 24 h at 30C. Baranyi, Huang, and modified Gompertz primary growth models were used to fit growth data. The modified Ratkowsky secondary model was used to fit growth rates determined by the primary growth models with respect to temperature. All three primary models fitted the growth data well. The modified Ratkowsky secondary model adequately fit growth rates generated by the three primary models (R2 values ranging from 0.96-0.98). After acceptable prediction zone (APZ) validation and goodness of fit statistical analyses, it was determined that the Baranyi primary growth model was best suited for these data. For both single-rate exponential cooling and biphasic linear cooling model validation, all Baranyi model predictions (n=24 and 28, respectively) fell within the APZ (-1.0 to 0.5 log CFU/g). The model will assist institutional food service settings to determine the safety of cooked pasta subjected to longer cooling times or stored at improper temperatures.

Technical Abstract: A predictive model was developed to predict the relative growth of Bacillus cereus from spores during cooling of cooked pasta. Cooked pasta was inoculated with a cocktail of four strains of heat-shocked (80C/10 min) B. cereus spores to obtain a final spore concentration of approximately 2 log CFU/g. Thereafter, growth was determined at isothermal temperatures starting at 10C and every three degrees up to 49C. Samples were removed periodically and plated on mannitol egg yolk polymyxin agar. The plates were incubated for 24 h at 30C. Baranyi, Huang, and modified Gompertz primary growth models were used to fit growth data. The modified Ratkowsky secondary model was used to fit growth rates determined by the primary growth models with respect to temperature. All three primary models fitted the growth data well. The modified Ratkowsky secondary model adequately fit growth rates generated by the three primary models (R2 values ranging from 0.96-0.98). After acceptable prediction zone (APZ) validation and goodness of fit statistical analyses, it was determined that the Baranyi primary growth model was best suited for these data. For both single-rate exponential cooling and biphasic linear cooling model validation, all Baranyi model predictions (n=24 and 28, respectively) fell within the APZ (-1.0 to 0.5 log CFU/g). The model will assist institutional food service settings to determine the safety of cooked pasta subjected to longer cooling times or stored at improper temperatures.