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Journal ArticleDOI

Modeling of bacterial growth; formulation and evaluation of a structured model.

TLDR
The general formal approach to structured modeling is developed in matrix notation and a simple two‐compartmental model, i.e., a structured model describing the activity of the biomass with two variables, is described.
Abstract
Models which consider changes in the composition of biomass in response to environmental changes are called Structured models. They provide a more comprehensive description of microbial behavior than unstructured models. Compared with the unstructured modeling efforts, very little has so far been done on the theory and practice of structured model building. In most of the works reported so far, no experimental data were provided, and hence no means of testing the proposed models were offered. Others only reported macroscopic response data and not the cellular composition. In an attempt to fill some of the gaps in this field, in this work, first the general formal approach to structured modeling is developed in matrix notation. Then, a simple two-compartmental model, i.e., a structured model describing the activity of the biomass with two variables, is described. The cell is divided into two fractions, one of which relates to the RNA fraction. The proposed model was then critically evaluated with experimental data, including the RNA data, obtained from fed-batch and continuous-culture experiments. The importance of using cellular structure data for model verification, i.e., RNA data in this case, is shown. Shortcomings and capabilities of the developed model are discussed.

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Book

Bioreaction Engineering Principles

TL;DR: Bioreactor Modelling: Morph Structured Models for Population Balances Based on Cell Number and Mass Transfer and Cellular Growth Reactions.
Journal ArticleDOI

Modelling of microbial kinetics

TL;DR: This review of bacterial and fungal models is preceded by a discussion of a general framework for the study of microbial kinetics and the use of a two-dimensional discretization of the kinetic model wherein both the individual cell and the cell mass is structured is shown to be helpful in dealing with comlex fermentation systems.
Journal ArticleDOI

Structured modeling of the anaerobic digestion of biomass particulates.

TL;DR: The model agrees well with two existing experimental studies of anaerobic digestion of biomass particulates and Hypothetical computer simulations are presented to illustrate possible instabilities of theAnaerobic process under various operating scenarios.
Journal ArticleDOI

A simple and reliable method for the determination of cellular RNA content

TL;DR: A rapid, simple and reliable method for the determination of the cellular RNA content is described and results from applying the method to monitor transient experiments in a chemostat with Lactococcus cremoris are presented.
Journal ArticleDOI

Theory and applications of unstructured growth models: Kinetic and energetic aspects

TL;DR: It is concluded that the art of unstructured model building has already reached its maturity and that now much effort should be channelled into the development and verification of structured models.
References
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Journal ArticleDOI

Fermentation of Glucose, Lactose, Galactose, Mannitol, and Xylose by Bifidobacteria

TL;DR: It was shown that bifidobacteria convert mannitol to fructose-6-phosphate by an inducible polyol dehydrogenase and fructokinase and the phosphoroclastic enzyme could not be demonstrated in cell-free extracts.
Journal ArticleDOI

A model of cell growth dynamics

TL;DR: It is argued that confirmation of a cell model based on single cell growth curves is of little value—that more sensitive tests can be obtained by studying simulated populations of the model cells by exploiting the close similarity in dynamic behavior to that of actual cell populations.
Journal ArticleDOI

Dynamics of microbial propagation: Models considering inhibitors and variable cell composition

TL;DR: The structured models account for the dependence of growth on the past, history of the cells; thus they predict all growth phases observed in batch cultures, whereas the unstructured models do not predict a lag phase.
Book ChapterDOI

Mathematical Models for Fermentation Processes

TL;DR: It is discussed that models serve to correlate data and so provide a concise way of thinking about a system or process and can be used to guide one's reasoning in the design of experiments to isolate important parameters and elucidate the nature of the system and process.
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