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Predictive model for growth of Clostridium perfringens during cooling of cooked uncured meat and poultry

机译:未煮熟的肉类和家禽冷却过程中产气荚膜梭状芽孢杆菌生长的预测模型

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摘要

Comparison of Clostridium perfringens spore germination and outgrowth in cooked uncured products during cooling for different meat species is presented. Cooked, uncured product was inoculated with C. perfringens spores and vacuum packaged. For the isothermal experiments, all samples were incubated in a water bath stabilized at selected temperatures between 10 and 51℃and sampled periodically. For dynamic experiments, the samples were cooled from 54.4 to 27 ℃ and subsequently from 27 to 4 ℃ for different time periods, designated as x and y hours, respectively. The growth models used were based on a model developed by Baranyi and Roberts (1994. A dynamic approach to predicting bacterial growth in food. Int. J. Food Micro. 23, 277—294), which incorporates a constant, referred to as the physiological state constant, qo. The value of this constant captures the cells' history before the cooling begins. To estimate specific growth rates, data from isothermal experiments were used, from which a secondary model was developed, based on a form of Ratkowsky's 4-parameter equation. The estimated growth kinetics associated with pork and chicken were similar, but growth appeared to be slightly greater in beef; for beef, the maximum specific growth rates estimated from the Ratkowsky curve was about 2.7 log_(10) cfu/h, while for the other two species, chicken and pork, the estimate was about 2.2 log_(10) cfu/h. Physiological state constants were estimated by minimizing the mean square error of predictions of the logio of the relative increase versus the corresponding observed quantities for the dynamic experiments: for beef the estimate was 0.007, while those for pork and chicken the estimates were about 0.014 and 0.011, respectively. For a hypothetical 1.5 h cooling from 54 ℃° to 27° and 5 h to 48℃, corresponding to USDA-FSIS cooling compliance guidelines, the predicted growth (log_(10) of the relative increase) for each species was: 1.29 for beef; 1.07 for chicken and 0.95 log_(10) for pork. However, it was noticed that for pork in particular, the model using the derived q_0 had a tendency to over-predict relative growth when the observed amount of relative growth was small, and under-predict the relative growth when the observed amount of relative growth was large. To provide more fail-safe estimate, rather than using the derived value of qo, a value of 0.04 is recommended for pork.
机译:介绍了不同肉类在冷却过程中未发酵产品中产气荚膜梭状芽孢杆菌孢子萌发和生长的比较。用产气荚膜梭菌孢子接种煮熟的未固化产品,并真空包装。对于等温实验,将所有样品在稳定在10至51℃的选定温度下的水浴中孵育,并定期采样。为了进行动态实验,将样品从54.4冷却到27℃,然后从27冷却到4℃,持续不同的时间,分别指定为x和y小时。使用的生长模型基于Baranyi和Roberts(1994.预测食物中细菌生长的动态方法。Int。J. Food Micro。23,277-294)开发的模型,该模型包含一个常数,称为生理状态常数,qo。该常数的值捕获冷却开始之前的细胞历史。为了估算特定的增长率,使用了等温实验的数据,并根据Ratkowsky的4参数方程式建立了二次模型。估计与猪肉和鸡肉有关的生长动力学相似,但牛肉的生长似乎略有增加。对于牛肉,根据Ratkowsky曲线估计的最大比生长速率约为2.7 log_(10)cfu / h,而对于其他两种鸡肉和猪肉,估计约为2.2 log_(10)cfu / h。通过将相对增加的对数对数的预测与动态实验中相应观察到的数量的预测的均方误差最小化来估算生理状态常数:牛肉的估算值为0.007,而猪肉和鸡肉的估算值约为0.014和0.011 , 分别。对于假设的从54℃°降温到27°1.5 h降温以及从5 hr降到48℃的降温(对应于USDA-FSIS降温遵从性指南),每种物种的预测增长(相对增长的log_(10))为:牛肉1.29 ;鸡肉为1.07,猪肉为0.95 log_(10)。但是,特别是对于猪肉,使用观察到的相对生长量时,使用导出的q_0的模型倾向于过度预测相对生长,而当观察到相对生长量时,模型则低估了相对生长。很大。为了提供更多的故障安全估计,而不是使用qo的派生值,建议猪肉使用0.04的值。

著录项

  • 来源
    《Food microbiology》 |2011年第4期|p.791-795|共5页
  • 作者单位

    Microbial Food Safety Research Unit, Eastern Regional Research Center, Agricultural Research Service, U.S. Department of Agriculture, 600 E. Mermaid Lane,Wyndmoor, PA 19038, USA;

    U.S. Department of Agriculture, Food Safety Inspection Service, 14th and Independence S.W., Washington, DC 20250, USA;

    Microbial Food Safety Research Unit, Eastern Regional Research Center, Agricultural Research Service, U.S. Department of Agriculture, 600 E. Mermaid Lane,Wyndmoor, PA 19038, USA;

    Department of Food Science and Technology, University of Nebraska, Lincoln, NE 68583, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    C. perfringens; Predictive modeling; Growth kinetics;

    机译:产气荚膜梭菌;预测模型;生长动力学;

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