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Abstract
Bacillus cereus is a ubiquitous spore forming pathogen often isolated from raw and processed foods and can cause diarrheal and emetic illnesses in humans. Dynamic predictive models for growth of B. cereus in roast turkey, beef, and ham were developed and validated. Freshly prepared meat samples were inoculated with B. cereus spores, heat-treated and stored at various isothermal temperatures (10 - 55⁰C). B. cereus growth data was obtained at each temperature and was used to develop the primary model (Baranyi). The modified Ratkowsky model was used for secondary model, and the models showed high accuracy (R2 values: 0.9873 and 0.9435, respectively). Tertiary models for non-isothermal profiles were developed and validated using the Acceptable Prediction Zone Analysis (APZ) method. Over 80% (average) observations fell within the APZ limits (-1.0 < predictive errors < 0.5 log CFU/g). The developed models help food industry and regulatory agencies to predict B. cereus growth under extended storage and temperature abuse scenarios to ensure microbiological safety of cooked meat products.