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首页> 外文期刊>Food microbiology >Prediction of time to growth of Listeria monocytogenes using Monte Carlo simulation or regression analysis, influenced by sublethal heat and recovery conditions
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Prediction of time to growth of Listeria monocytogenes using Monte Carlo simulation or regression analysis, influenced by sublethal heat and recovery conditions

机译：受亚致死热量和恢复条件的影响，使用蒙特卡罗模拟或回归分析预测单核细胞增生李斯特菌的生长时间

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摘要

Stochastic models, including the variability in extent and probability of microbial growth, are useful for estimating the risk of foodbome illness (i.e. Nauta, 2000). Risk assessment typically has to embrace all sources of variability. In this paper, a stochastic approach to evaluate growth of heat damaged Listeria monocytogenes cells influenced by different stresses (pH and presence of eugenol) was performed, using an individual-based approach of growth through OD measurements. Both the lag phase duration and the "work to be done" (h_0 parameter) were derived from the growth curves obtained. From results obtained histograms of the lag phase were generated and distributions were fitted. Histograms showed a shift to longer lag phases and an increase in variability with high stress levels. Using the distributions fitted, predictions of time to unacceptable growth (10~2 cfu/g) of L monocytogenes were established by Monte Carlo simulation and they were compared with results from statistical methods. It was evidenced that both methods (Monte Carlo and regression analysis) gave a good indication of the probability of a certain level of growth other than the average. Tornado plots were obtained to establish a sensitivity analysis of the influence of the conditions tested (heat, pH, eugenol) applied to the microorganism and their combinations.
机译：随机模型，包括微生物生长的程度和可能性的变异性，可用于估计食源性疾病的风险（即Nauta，2000年）。风险评估通常必须涵盖所有可变性来源。在本文中，通过基于OD值的基于个体的生长方法，进行了一种随机方法来评估受不同压力（pH和丁香酚的存在）影响的热损伤单核细胞增生李斯特菌细胞的生长。滞后阶段的持续时间和“要完成的工作”（h_0参数）均从获得的生长曲线得出。根据获得的结果，生成了滞后阶段的直方图，并拟合了分布。直方图显示向较长的滞后阶段转移，并且在高应力水平下变异性增加。使用拟合的分布，通过蒙特卡洛模拟建立了单核细胞增生李斯特氏菌不可接受的生长时间（10〜2 cfu / g）的预测，并将其与统计方法的结果进行了比较。事实证明，这两种方法（蒙特卡罗和回归分析）都很好地表明了除平均水平以外某种程度的增长可能性。获得了龙卷风图，以建立对微生物及其组合所测条件（热，pH，丁子香酚）的影响的敏感性分析。

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  • 来源
    《Food microbiology》 |2010年第4期|p.468-475|共8页
  • 作者

    Marina Munoz; Leymaya Guevara; Alfredo Palop; Pablo S. Fernandez;

  • 作者单位

    Dpto. Ing. Alimentos y del Equipamiento Agricola, Escuela Tecnica Superior de Ingenieria Agronomica, Universidad Politecnica de Cartagena, Paseo Alfonso XIII 48, 30203 Cartagena, Spain;

    Dpto. Ing. Alimentos y del Equipamiento Agricola, Escuela Tecnica Superior de Ingenieria Agronomica, Universidad Politecnica de Cartagena, Paseo Alfonso XIII 48, 30203 Cartagena, Spain;

    Dpto. Ing. Alimentos y del Equipamiento Agricola, Escuela Tecnica Superior de Ingenieria Agronomica, Universidad Politecnica de Cartagena, Paseo Alfonso XIII 48, 30203 Cartagena, Spain Instituto de Biotecnologia Vegetal, Universidad Politecnica de Cartagena, 30203 Cartagena, Spain;

    Dpto. Ing. Alimentos y del Equipamiento Agricola, Escuela Tecnica Superior de Ingenieria Agronomica, Universidad Politecnica de Cartagena, Paseo Alfonso XIII 48, 30203 Cartagena, Spain Instituto de Biotecnologia Vegetal, Universidad Politecnica de Cartagena, 30203 Cartagena, Spain;

  • 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

    listeria monocytogenes; predictive modelling; monte carlo simulation; lag phase distributions; individual lag phase;

    机译：李斯特菌;预测建模;蒙特卡洛模拟滞后相位分布个人滞后阶段;

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