Dens E J, Vereecken K M, Van Impe J F
Department of Food and Microbial Technology, Katholieke Universiteit Leuven, Kardinaal Mercierlaan 92, Leuven, B-3001, Belgium.
J Theor Biol. 1999 Dec 7;201(3):159-70. doi: 10.1006/jtbi.1999.1021.
An important factor which has not been included in many models in the field of predictive microbiology is the influence of a background of microflora in a food product. It is however generally known that the growth of a microorganism as a pure culture can be substantially different from its growth in a mixed culture, due to microbial interactions. Because of the importance of these interactions and the lack of suitable modeling techniques in the field of predictive microbiology to describe them, the potential of models in other research fields-namely ecology-to deal with interactions is explored in previous work of the authors. However, a model structure for microbial growth in food products cannot simply be copied from those elaborated in ecology. The structure of a predictive growth model is indeed typical, primarily due to the explicit modeling of a lag phase. The current paper proposes a prototype model structure for growth of mixed microbial populations in homogeneous food products. The model is able to describe a lag phase and reduces to a classical predictive growth model in the special case of single-species growth.
预测微生物学领域的许多模型中未包含的一个重要因素是食品中微生物群落背景的影响。然而，众所周知，由于微生物间的相互作用，纯培养微生物的生长情况可能与混合培养时有很大不同。鉴于这些相互作用的重要性以及预测微生物学领域缺乏合适的建模技术来描述它们，作者之前的工作探索了其他研究领域（即生态学）中处理相互作用的模型的潜力。然而，食品中微生物生长的模型结构不能简单地照搬生态学中构建的模型结构。预测生长模型的结构确实具有典型性，主要是因为对滞后期进行了明确建模。本文提出了一个用于均质食品中混合微生物群体生长的原型模型结构。该模型能够描述滞后期，并且在单物种生长的特殊情况下可简化为经典的预测生长模型。
