Kakagianni Myrsini, Aguirre Juan S, Lianou Alexandra, Koutsoumanis Konstantinos P
Laboratory of Food Microbiology and Hygiene, Department of Food Science and Technology, School of Agriculture, Faculty of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece.
Laboratorio de Microbiología y Probioticos, INTA, Universidad de Chile, Avenida El Líbano 5524, Macul, Santiago, Chile.
Food Microbiol. 2017 Oct;67:76-84. doi: 10.1016/j.fm.2017.04.009. Epub 2017 Apr 22.
The lag times (λ) of Geobacillus stearothermophilus single spores were studied at different storage temperatures ranging from 45 to 59 °C using the Bioscreen C method. A significant variability of λ was observed among individual spores at all temperatures tested. The storage temperature affected both the position and the spread of the λ distributions. The minimum mean value of λ (i.e. 10.87 h) was observed at 55 °C, while moving away from this temperature resulted in an increase for both the mean and standard deviation of λ. A Cardinal Model with Inflection (CMI) was fitted to the reverse mean λ, and the estimated values for the cardinal parameters T, T, T and the optimum mean λ of G. stearothermophilus were found to be 38.1, 64.2, 53.6 °C and 10.3 h, respectively. To interpret the observations, a probabilistic growth model for G. stearothermophilus individual spores, taking into account λ variability, was developed. The model describes the growth of a population, initially consisting of N spores, over time as the sum of cells in each of the N imminent subpopulations originating from a single spore. Growth simulations for different initial contamination levels showed that for low N the number of cells in the population at any time is highly variable. An increase in N to levels exceeding 100 spores results in a significant decrease of the above variability and a shorter λ of the population. Considering that the number of G. stearothermophilus surviving spores in the final product is usually very low, the data provided in this work can be used to evaluate the probability distribution of the time-to-spoilage and enable decision-making based on the "acceptable level of risk".
使用Bioscreen C方法研究了嗜热栖热放线菌单个孢子在45至59°C不同储存温度下的延迟期（λ）。在所有测试温度下，各个孢子之间的λ存在显著差异。储存温度影响了λ分布的位置和离散程度。在55°C时观察到λ的最小平均值（即10.87小时），而偏离该温度会导致λ的平均值和标准差均增加。将带拐点的基数模型（CMI）拟合到反向平均λ，发现嗜热栖热放线菌的基数参数T、T、T的估计值以及最佳平均λ分别为38.1、64.2、53.6°C和10.3小时。为了解释这些观察结果，开发了一个考虑λ变异性的嗜热栖热放线菌单个孢子的概率生长模型。该模型描述了最初由N个孢子组成的群体随时间的生长情况，即来自单个孢子的N个即将出现的亚群体中每个亚群体的细胞总和。不同初始污染水平的生长模拟表明，对于低N值，群体中任何时候的细胞数量变化很大。将N增加到超过100个孢子的水平会导致上述变异性显著降低，并且群体的λ缩短。考虑到最终产品中存活的嗜热栖热放线菌孢子数量通常非常低，这项工作中提供的数据可用于评估变质时间的概率分布，并基于“可接受的风险水平”进行决策。
