When is simple good enough: A comparison of the Gompertz, Baranyi, and three-phase linear models for fitting bacterial growth curves
When is simple good enough: A comparison of the Gompertz, Baranyi, and three-phase linear models for fitting bacterial growth curves
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DOI：
10.1006/fmic.1997.0125
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发表时间：
1997-08-01
影响因子：
5.3
通讯作者：
Damert, WC
中科院分区：
文献类型：
--
作者：
Buchanan, RL;Whiting, RC;Damert, WC
使用曲线拟合软件的主要数学模型正在极大地改变定量食品微生物学。两个最广泛使用的初级增长模型是Baranyi和Gompertz模型。一个三相线性模型的开发，以确定如何以及生长曲线可以使用一个更简单的模型来描述。该模型将细菌生长曲线分为三个阶段：滞后期和稳定期，其中比生长率为零（mu=0），以及指数期，其中细菌种群的对数随时间线性增加（mu=常数）。该模型有四个参数：N-0（初始种群密度的Log（10））、NMAX（最终种群密度的Log（10））、hac（滞后期结束的时间）和tMax（指数期结束的时间）。使用大肠杆菌0157：H7的既定生长数据，将线性模型与Baranyi和Gompertz模型进行比较。三种模型预测的生长曲线吻合较好。线性模型比其他模型更“鲁棒”，特别是当实验数据很少时。基本的线性模型的生理假设进行了讨论，特别强调确保该模型是一致的细菌的行为，无论是作为个体细胞和群体。提出细菌在滞后期结束时的过渡行为可以基于生物学变异性来解释。(C)出版社：Academic Press Limited。
The use of primary mathematical models with curve fitting software is dramatically changing quantitative food microbiology. The two most widely used primary growth models are the Baranyi and Gompertz models. A three-phase linear model was developed to determine how well growth curves could be described using a simpler model. The model divides bacterial growth curves into three phases: the lag and stationary phases where the specific growth rate is zero (mu=0), and the exponential phase where the logarithm of the bacterial population increases linearly with time (mu=constant). The model has four parameters: N-0 (Log(10) of initial population density), NMAX (Log(10) of final population density), hac (time when lag phase ends), and tMax (time when exponential phase ends). A comparison of the linear model was made against the Baranyi and Gompertz models, using established growth data for Escherichia coli 0157:H7. The growth curves predicted by the three models showed good agreement. The linear model was more 'robust' than the others, especially when experimental data were minimal. The physiological assumptions underlying the linear model are discussed, with particular emphasis on assuring that the model is consistent with bacterial behavior both as individual cells and as populations. it is proposed that the transitional behavior of bacteria at the end of the lag phase can be explained on the basis of biological variability. (C) 1997 Academic Press Limited.