Vadasz Peter, Vadasz Alisa S
College of Engineering and Natural Sciences, Northern Arizona University, P.O. Box 15600, Flagstaff, AZ 86011-5600, USA.
Int J Food Microbiol. 2005 Jul 25;102(3):257-75. doi: 10.1016/j.ijfoodmicro.2004.12.018.
The variety of models that are currently being used in "Predictive Microbiology" or "Microbial Ecology" aiming at reproducing the growth curve of microorganisms motivates this study. It is widely agreed that no model can reproduce generically and consistently the "LAG Phase" of microorganism growth. To promote the objective of "predictive modeling", we present here a model that was derived from first biological and physical principles, which is shown to reproduce qualitatively as well as quantitatively all typical features captured experimentally in microorganism growth. In particular, this paper focuses on capturing and controlling of the "LAG Phase" a typical phase in microorganisms growth, at the initial growth stages, as well as the inflection point on the "ln curve" of the cell concentration, i.e. a Logarithmic Inflection Point referred here as "LIP". The proposed model also captures the Logistic Growth curve as a special case. Comparison of the solutions obtained from the proposed model with experimental data confirms its quantitative validity, as well as its ability to recover a wide range of qualitative features captured in experiments.
当前在“预测微生物学”或“微生物生态学”中用于重现微生物生长曲线的各种模型激发了本研究。人们普遍认为，没有一个模型能够通用且一致地重现微生物生长的“延迟期”。为推动“预测建模”目标，我们在此提出一个基于生物学和物理学第一原理推导出来的模型，该模型被证明能够定性和定量地重现微生物生长实验中捕捉到的所有典型特征。特别是，本文着重于捕捉和控制微生物生长初始阶段的典型阶段“延迟期”以及细胞浓度“ln曲线”上的拐点，即此处称为“对数拐点”（LIP）的点。所提出的模型还将逻辑斯蒂生长曲线作为一种特殊情况包含在内。将所提出模型得到的解与实验数据进行比较，证实了其定量有效性以及恢复实验中捕捉到的广泛定性特征的能力。
