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本文引用的文献

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Response Surface Model for Predicting the Effects of Temperature pH, Sodium Chloride Content, Sodium Nitrite Concentration and Atmosphere on the Growth of Listeria monocytogenes.用于预测温度、pH值、氯化钠含量、亚硝酸钠浓度和气氛对单核细胞增生李斯特菌生长影响的响应面模型
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Stochastic modelling of bacterial lag phase.细菌延迟期的随机建模
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Comparison of maximum specific growth rates and lag times estimated from absorbance and viable count data by different mathematical models.通过不同数学模型根据吸光度和活菌计数数据估算的最大比生长速率和延滞期的比较。
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Estimation of temperature dependent growth rate and lag time of Listeria monocytogenes by optical density measurements.通过光密度测量评估温度依赖性单核细胞增生李斯特菌的生长速率和延迟期。
J Microbiol Methods. 1999 Oct;38(1-2):137-46. doi: 10.1016/s0167-7012(99)00089-5.
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Growth and inactivation models to be used in quantitative risk assessments.用于定量风险评估的生长和失活模型。
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Estimation of bacterial growth rates from turbidimetric and viable count data.根据比浊法和活菌计数数据估算细菌生长速率。
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根据活菌计数和光密度数据对单核细胞增生李斯特菌的延迟期进行建模。

Modeling the lag time of Listeria monocytogenes from viable count enumeration and optical density data.

作者信息

Baty F, Flandrois J P, Delignette-Muller M L

机构信息

CNRS UMR 5558, Laboratoire de Bactériologie, Faculté de Médecine Lyon-Sud, 69921 Oullins Cedex, France.

出版信息

Appl Environ Microbiol. 2002 Dec;68(12):5816-25. doi: 10.1128/AEM.68.12.5816-5825.2002.

DOI:10.1128/AEM.68.12.5816-5825.2002
PMID:12450800
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC134405/
Abstract

The following two factors significantly influence estimates of the maximum specific growth rate ( micro (max)) and the lag-phase duration (lambda): (i) the technique used to monitor bacterial growth and (ii) the model fitted to estimate parameters. In this study, nine strains of Listeria monocytogenes were monitored simultaneously by optical density (OD) analysis and by viable count enumeration (VCE) analysis. Four usual growth models were fitted to our data, and estimates of growth parameters were compared from one model to another and from one monitoring technique to another. Our results show that growth parameter estimates depended on the model used to fit data, whereas there were no systematic variations in the estimates of micro (max) and lambda when the estimates were based on OD data instead of VCE data. By studying the evolution of OD and VCE simultaneously, we found that while log OD/VCE remained constant for some of our experiments, a visible linear increase occurred during the lag phase for other experiments. We developed a global model that fits both OD and VCE data. This model enabled us to detect for some of our strains an increase in OD during the lag phase. If not taken into account, this phenomenon may lead to an underestimate of lambda.

摘要

以下两个因素会显著影响最大比生长速率(μ(max))和延滞期持续时间(λ)的估计值:(i)用于监测细菌生长的技术,以及(ii)用于估计参数的拟合模型。在本研究中,通过光密度(OD)分析和活菌计数枚举(VCE)分析同时监测了九株单核细胞增生李斯特菌。对我们的数据拟合了四种常用的生长模型,并比较了不同模型之间以及不同监测技术之间的生长参数估计值。我们的结果表明,生长参数估计值取决于用于拟合数据的模型,而当基于OD数据而非VCE数据进行估计时,μ(max)和λ的估计值没有系统性差异。通过同时研究OD和VCE的变化,我们发现,在我们的一些实验中,log OD/VCE保持恒定,而在其他实验中,延滞期出现了明显的线性增加。我们开发了一个能同时拟合OD和VCE数据的全局模型。该模型使我们能够检测到我们的一些菌株在延滞期OD的增加。如果不考虑这一现象,可能会导致对λ的低估。