Giannakourou Maria C, Stoforos Nikolaos G
Department of Food Technology, Technological Educational Institute of Athens, Athens 12210, Greece.
Department of Food Science and Human Nutrition, Agricultural University of Athens, Athens 11855, Greece.
Foods. 2017 Jan 12;6(1):7. doi: 10.3390/foods6010007.
Traditionally, for the determination of the kinetic parameters of thermal inactivation of a heat labile substance, an appropriate index is selected and its change is measured over time at a series of constant temperatures. The rate of this change is described through an appropriate primary model and a secondary model is applied to assess the impact of temperature. By this approach, the confidence intervals of the estimates of the rate constants are not taken into account. Consequently, the calculated variability of the secondary model parameters can be significantly lower than the actual variability. The aim of this study was to demonstrate the influence of the variability of the primary model parameters in establishing the confidence intervals of the secondary model parameters. Using a Monte Carlo technique and assuming normally distributed values (parameter associated with a primary inactivation model), the error propagating on the and -values (secondary model parameters) was assessed. When confidence intervals were broad, the secondary model's parameter variability was appreciably high and could not be adequately estimated through the traditional deterministic approach that does not take into account the variation on the values. In such cases, the proposed methodology was essential for realistic estimations.
传统上,为了确定热不稳定物质热失活的动力学参数,需选择一个合适的指标,并在一系列恒定温度下随时间测量其变化。这种变化的速率通过适当的一级模型来描述,然后应用二级模型来评估温度的影响。通过这种方法,未考虑速率常数估计值的置信区间。因此,计算出的二级模型参数变异性可能显著低于实际变异性。本研究的目的是证明一级模型参数变异性在建立二级模型参数置信区间中的影响。使用蒙特卡罗技术并假设值呈正态分布(与一级失活模型相关的参数),评估了在和值(二级模型参数)上传播的误差。当置信区间较宽时,二级模型的参数变异性相当高,并且无法通过不考虑值变化的传统确定性方法进行充分估计。在这种情况下,所提出的方法对于实际估计至关重要。