U.S. Department of Agriculture, Agricultural Research Service, Eastern Regional Research Center, 600 East Mermaid Lane, Wyndmoor, PA 19038, United States.
Department of Food Science and Technology, University of Georgia, Athens, GA 30602, United States.
Food Res Int. 2021 Nov;149:110695. doi: 10.1016/j.foodres.2021.110695. Epub 2021 Sep 3.
Cooking temperature of poultry meat is typically inadequate to inactivate the heat resistant spores of Clostridium botulinum. The purpose of this study is to develop a predictive model for C. botulinum during cooling of cooked ground chicken. Cooked chicken was inoculated with a cocktail of five strains of proteolytic C. botulinum type A and five strains of proteolytic C. botulinum type B to yield a final spore concentration of approximately 2 log CFU/g. The growth of C. botulinum was determined at constant temperatures from 10 to 46 °C. Dynamic temperature experiments were performed with continued cooling from 54.4 to 4.4 °C or 7.2 °C in mono- or bi-phasic cooling profiles, respectively. The Baranyi primary model was used to fit growth data and the modified Ratkowsky secondary model was used to fit growth rates with respect to temperature. The primary models fitted the growth data well (R values ranging from 0.811 to 0.988). The R and root mean square error (RMSE) of the modified Ratkowsky secondary model were 0.95 and 0.06, respectively. Out of 11 prediction error values calculated in this study, ten were within the limit of acceptable prediction zone (-1.0 to 0.5), indicating a good fit of the model. The predictive model will assist institutional food service operations in determining the safety of cooked ground chicken subjected to different cooling periods.
家禽肉的烹饪温度通常不足以使耐热孢子的肉毒梭菌失活。本研究的目的是开发一个预测模型，用于研究烹饪后的鸡肉在冷却过程中肉毒梭菌的生长情况。将烹饪过的鸡肉接种了由五种蛋白酶型 A 的肉毒梭菌和五种蛋白酶型 B 的肉毒梭菌组成的混合物，以获得约 2 个对数 CFU/g 的最终孢子浓度。在 10 至 46°C 的恒定温度下测定肉毒梭菌的生长情况。分别采用单相或双相冷却曲线，在 54.4 至 4.4°C 或 7.2°C 时进行动态温度实验，持续冷却。使用巴尼一级模型拟合生长数据，使用修正的拉特科夫斯基二级模型拟合生长速率与温度的关系。主要模型很好地拟合了生长数据（R 值范围从 0.811 到 0.988）。修正的拉特科夫斯基二级模型的 R 和均方根误差（RMSE）分别为 0.95 和 0.06。在本研究中计算的 11 个预测误差值中，有 10 个在可接受的预测范围（-1.0 到 0.5）内，表明模型拟合良好。该预测模型将有助于机构食品服务运营，确定不同冷却时间下烹饪鸡肉的安全性。
