Halder A, Datta A K, Geedipalli S S R
Biological and Environmental Engineering, Cornell Univ., Ithaca, NY 14853, USA.
J Food Sci. 2007 May;72(4):E155-67. doi: 10.1111/j.1750-3841.2007.00329.x.
Alternatives to first-order model of death kinetics of microorganisms have been proposed as improvements in the calculation of lethality for a thermal process. Although such models can potentially improve predictions for many situations, this article tries to answer the question of whether the added complexities of these models are a worthwhile investment once we include the effect of uncertainties in various microbiological and process parameters. Monte Carlo technique is used to include variability in kinetic parameters in lethality calculation for a number of heating processes, for both first-order and Weibull kinetics models. It is shown that uncertainties represented by coefficient of variation in kinetic parameters lead to a wide range of final log-reduction prediction. With the same percent variability in kinetic parameters, uncertainty in the final log reduction for Weibull kinetics was smaller or equal to that for first-order kinetics. Due to the large effect of variability in the input parameters on the final log reduction, the effort to move toward more accurate kinetic models needs to be weighed against inclusion of variability.
作为热过程致死率计算的改进方法,已经提出了微生物死亡动力学一阶模型的替代模型。尽管这些模型有可能改善许多情况下的预测,但本文试图回答这样一个问题:一旦我们考虑到各种微生物和工艺参数不确定性的影响,这些模型增加的复杂性是否是一项值得的投入。蒙特卡罗技术用于在多个加热过程的致死率计算中纳入动力学参数的变异性,包括一阶动力学模型和韦布尔动力学模型。结果表明,动力学参数变异系数所代表的不确定性导致最终对数减少预测的范围很广。在动力学参数具有相同百分比变异性的情况下,韦布尔动力学最终对数减少的不确定性小于或等于一阶动力学的不确定性。由于输入参数变异性对最终对数减少有很大影响,因此在采用更精确的动力学模型的努力与纳入变异性之间需要进行权衡。