Oscar T P
U.S. Department of Agriculture, Agricultural Research Service, Center for Food Science and Technology, University of Maryland Eastern Shore, Princess Anne, Maryland 21853, USA.
J Food Prot. 2005 Dec;68(12):2606-13. doi: 10.4315/0362-028x-68.12.2606.
Models are used in the food industry to predict pathogen growth and to help assess food safety. However, criteria are needed to determine whether models provide acceptable predictions. In the current study, primary, secondary, and tertiary models for growth of Salmonella Typhimurium (10(4.8) CFU/g) on sterile chicken were developed and validated. Kinetic data obtained at 10 to 40 degrees C were fit to a primary model to determine initial density (N0), lag time (lambda), maximum specific growth rate (micromax), and maximum population density (Nmax). Secondary models for N0, lambda, micromax, and Nmax as a function of temperature were developed and combined with the primary model to create a tertiary model that predicted pathogen density (N) at times and temperatures used and not used in model development. Performance of models was evaluated using the acceptable prediction zone method in which experimental error associated with growth parameter determinations was used to set criteria for acceptable model performance. Models were evaluated against dependent and independent (validation) data. Models with 70% prediction or relative errors (RE) in an acceptable prediction zone from -0.3 to 0.15 for micromax, -0.6 to 0.3 for lambda, and -0.8 to 0.4 for N, N0, and Nmax were classified as acceptable. All secondary models had acceptable goodness of fit and were validated against independent (interpolation) data. Percent RE in the acceptable prediction zone for the tertiary model was 90.7 for dependent data and 97.5 for independent (interpolation) data. Although the tertiary model was validated for interpolation, an unacceptable %RE of 2.5 was obtained for independent (extrapolation) data obtained with a lower N0 (10(0.8) CFU/g). The tertiary model provided overly fail-dangerous predictions of N from a lower N0. Because Salmonella concentrations on chicken are closer to 10(0.8) than 10(4.8) CFU/g, the tertiary model should not be used to help assess chicken safety.
模型被用于食品工业中预测病原体的生长,并协助评估食品安全。然而,需要有标准来确定模型是否能提供可接受的预测。在当前的研究中,开发并验证了鼠伤寒沙门氏菌(10⁴·⁸CFU/g)在无菌鸡肉上生长的一级、二级和三级模型。在10至40摄氏度下获得的动力学数据被拟合到一个一级模型中,以确定初始密度(N₀)、延迟期(λ)、最大比生长速率(μₘₐₓ)和最大种群密度(Nₘₐₓ)。开发了作为温度函数的N₀、λ、μₘₐₓ和Nₘₐₓ的二级模型,并将其与一级模型相结合,创建了一个三级模型,该模型可预测在模型开发中使用和未使用的时间和温度下的病原体密度(N)。使用可接受预测区方法评估模型的性能,其中与生长参数测定相关的实验误差被用于设定可接受模型性能的标准。根据相关和独立(验证)数据对模型进行评估。对于μₘₐₓ,在-0.3至0.15的可接受预测区内预测或相对误差(RE)为70%的模型、对于λ在-0.6至0.3的模型以及对于N、N₀和Nₘₐₓ在-0.8至0.4的模型被归类为可接受。所有二级模型都具有可接受的拟合优度,并根据独立(插值)数据进行了验证。对于三级模型,相关数据在可接受预测区内的RE百分比为90.7%,独立(插值)数据为97.5%。尽管三级模型针对插值进行了验证,但对于用较低N₀(10⁰·⁸CFU/g)获得的独立(外推)数据,得到了2.5%的不可接受的RE。三级模型对较低N₀的N提供了过度失效危险的预测。由于鸡肉上沙门氏菌的浓度更接近10⁰·⁸CFU/g而不是10⁴·⁸CFU/g,因此不应使用三级模型来协助评估鸡肉的安全性。