|GOLDEN, CHASE - University Of Georgia|
|MISHRA, ABHINAV - University Of Georgia|
|HARRISON, MARK - University Of Georgia|
|MOHR, TIM - Food Safety Inspection Service (FSIS)|
|SILVERMAN, MERYL - Food Safety Inspection Service (FSIS)|
Submitted to: International Journal of Food Microbiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/24/2018
Publication Date: 1/12/2019
Citation: Juneja, V.K., Golden, C.E., Mishra, A., Harrison, M.A., Mohr, T., Silverman, M. 2019. Predictive model for growth of bacillus cereus during cooling of cooked rice. International Journal of Food Microbiology. 290:49-58. https://doi.org/10.1016/j.ijfoodmicro.2018.09.023.
Interpretive Summary: A foodborne bacterium, Bacillus cereus, can cause food poisoning due to consumption of contaminated rice. We investigated the growth of this pathogen in cooked rice and compared four different mathematical growth models that can be used to estimate the growth in cooked rice. A dynamic model that can be used to estimate the growth under different time/temperature conditions was developed. The model will assist regulatory agencies and the food industry to evaluate risk of B. cereus growth in cooked rice during cooling, as well as during distribution and storage.
Technical Abstract: Bacillus cereus is frequently implicated in foodborne outbreaks associated with the consumption of cooked rice. The main contributing factors leading to outbreaks is rice cooked in large quantities and subsequently, inadequately chilled or stored at room temperatures for a prolonged period of time prior to consumption. Bacillus cereus growth in cooked rice inoculated with approximately 2 log CFU/g of heat-shocked (80C/10 min) spores at several isothermal conditions (between 10 to 49C) was quantified. B. cereus populations were determined by plating on mannitol egg yolk polymyxin agar and incubating at 30C for 24 h. Data were fitted into primary growth models, namely Baranyi, Huang, modified Gompertz, and logistic models. Growth rates generated by each primary model were fitted with the modified Ratkowsky square-root model with respect to temperature. All four primary models were well fitted by the modified Ratkowsky model (R2 values from 0.90-0.99). Based on the goodness of fit secondary model statistics (R2, SSE, RMSE), the Baranyi model performed the best and was chosen for tertiary modeling. Acceptable prediction zone (APZ) analysis was performed for validation of the Baranyi model predictions during single rate exponential and biphasic linear cooling temperature profiles. For single rate cooling, 23 of the 24 predictions fell within the APZ (-1.0 to 0.5 log CFU/g). For biphasic linear cooling, 26 of the 28 predictions fell within the APZ. The developed dynamic model can be used to predict potential B. cereus growth from spores in cooked rice during chilling and thus, support the disposition of product subject to cooling deviations.