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Time lag model for batch bioreactor simulation accounting the effect of micro-organism mortality

In the present work, a generalization of the classical model of Monod accounting the influence of both delayed and instant mortalities on the dynamics of the micro-organism population is proposed. The model was analysed and compared with respect to its quality and applicability for simulation of the...

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Autores principales: Zahariev, Andrey, Kiskinov, Hristo, Angelov, Angel, Zlatev, Stoyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4434070/
https://www.ncbi.nlm.nih.gov/pubmed/26019633
http://dx.doi.org/10.1080/13102818.2014.993111
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author Zahariev, Andrey
Kiskinov, Hristo
Angelov, Angel
Zlatev, Stoyan
author_facet Zahariev, Andrey
Kiskinov, Hristo
Angelov, Angel
Zlatev, Stoyan
author_sort Zahariev, Andrey
collection PubMed
description In the present work, a generalization of the classical model of Monod accounting the influence of both delayed and instant mortalities on the dynamics of the micro-organism population is proposed. The model was analysed and compared with respect to its quality and applicability for simulation of the cultivation process of micro-organisms. Existence of a unique global positive solution of the Cauchy problem for the proposed model is proved and explicit relations between the decay parameters and the nutrition substrate concentration are obtained. These mathematical results allow us to calculate the nutrient substrate concentration which guarantees that the biomass concentration is maximal for every specific type of taxonomic groups of micro-organisms (bacteria, yeasts).
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spelling pubmed-44340702015-05-25 Time lag model for batch bioreactor simulation accounting the effect of micro-organism mortality Zahariev, Andrey Kiskinov, Hristo Angelov, Angel Zlatev, Stoyan Biotechnol Biotechnol Equip Article; Bioinformatics In the present work, a generalization of the classical model of Monod accounting the influence of both delayed and instant mortalities on the dynamics of the micro-organism population is proposed. The model was analysed and compared with respect to its quality and applicability for simulation of the cultivation process of micro-organisms. Existence of a unique global positive solution of the Cauchy problem for the proposed model is proved and explicit relations between the decay parameters and the nutrition substrate concentration are obtained. These mathematical results allow us to calculate the nutrient substrate concentration which guarantees that the biomass concentration is maximal for every specific type of taxonomic groups of micro-organisms (bacteria, yeasts). Taylor & Francis 2015-01-02 2015-01-07 /pmc/articles/PMC4434070/ /pubmed/26019633 http://dx.doi.org/10.1080/13102818.2014.993111 Text en © 2015 The Author(s). Published by Taylor & Francis. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Article; Bioinformatics
Zahariev, Andrey
Kiskinov, Hristo
Angelov, Angel
Zlatev, Stoyan
Time lag model for batch bioreactor simulation accounting the effect of micro-organism mortality
title Time lag model for batch bioreactor simulation accounting the effect of micro-organism mortality
title_full Time lag model for batch bioreactor simulation accounting the effect of micro-organism mortality
title_fullStr Time lag model for batch bioreactor simulation accounting the effect of micro-organism mortality
title_full_unstemmed Time lag model for batch bioreactor simulation accounting the effect of micro-organism mortality
title_short Time lag model for batch bioreactor simulation accounting the effect of micro-organism mortality
title_sort time lag model for batch bioreactor simulation accounting the effect of micro-organism mortality
topic Article; Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4434070/
https://www.ncbi.nlm.nih.gov/pubmed/26019633
http://dx.doi.org/10.1080/13102818.2014.993111
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