Cover Image

Stochastic modeling of the C. Acetobutylicum and solvent productions in fermentation

Recent decade has seen great progress in the use of stochastic models in biological process. Researchers are now realising that stochastic models have important roles to play in biological process especially in the analysis of population dynamics. This progress encourages many researchers to develop...

Full description

Saved in:
Bibliographic Details
Main Author: Mohd. Aziz, Mohd. Khairul Bazli
Format: Thesis
Language:English
Published: 2010
Subjects:
QA Mathematics
Online Access:http://eprints.utm.my/id/eprint/12331/6/MohdKhairulBazliMFS2010.pdf
http://eprints.utm.my/id/eprint/12331/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.12331
record_format eprints
spelling my.utm.123312017-09-13T03:31:49Z http://eprints.utm.my/id/eprint/12331/ Stochastic modeling of the C. Acetobutylicum and solvent productions in fermentation Mohd. Aziz, Mohd. Khairul Bazli QA Mathematics Recent decade has seen great progress in the use of stochastic models in biological process. Researchers are now realising that stochastic models have important roles to play in biological process especially in the analysis of population dynamics. This progress encourages many researchers to develop new methods and techniques to improve the stochastic model. In recent study, logistic equations have been used to model the cell growth of C.acetobutylicum while the Luedeking-Piret equation incorporating the logistic equation used to model the formation of solvent. However, it was found that the Luedeking-Piret equation is not adequate for modeling the production of acetone and butanol. In this study, stochastic power law logistic model has been considered to model the cell growth of C.acetobutylicum and the solvent production in five different yeast cultures. In order to solve the SDEs, simulated maximum likelihood estimation method and Euler-Maruyama approximation method have been used. Finally, the stochastic models and deterministic models are compared by using their root mean square errors of the growth model and solvent productions model. The stochastic models have smaller value of root mean square errors, thus showed that the stochastic power law logistic models are better models than their deterministic counterparts to describe the growth of C.acetobutylicum and solvent productions in fermentation. 2010 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/id/eprint/12331/6/MohdKhairulBazliMFS2010.pdf Mohd. Aziz, Mohd. Khairul Bazli (2010) Stochastic modeling of the C. Acetobutylicum and solvent productions in fermentation. Masters thesis, Universiti Teknologi Malaysia, Faculty of Science.
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
Mohd. Aziz, Mohd. Khairul Bazli
Stochastic modeling of the C. Acetobutylicum and solvent productions in fermentation
description Recent decade has seen great progress in the use of stochastic models in biological process. Researchers are now realising that stochastic models have important roles to play in biological process especially in the analysis of population dynamics. This progress encourages many researchers to develop new methods and techniques to improve the stochastic model. In recent study, logistic equations have been used to model the cell growth of C.acetobutylicum while the Luedeking-Piret equation incorporating the logistic equation used to model the formation of solvent. However, it was found that the Luedeking-Piret equation is not adequate for modeling the production of acetone and butanol. In this study, stochastic power law logistic model has been considered to model the cell growth of C.acetobutylicum and the solvent production in five different yeast cultures. In order to solve the SDEs, simulated maximum likelihood estimation method and Euler-Maruyama approximation method have been used. Finally, the stochastic models and deterministic models are compared by using their root mean square errors of the growth model and solvent productions model. The stochastic models have smaller value of root mean square errors, thus showed that the stochastic power law logistic models are better models than their deterministic counterparts to describe the growth of C.acetobutylicum and solvent productions in fermentation.
format Thesis
author Mohd. Aziz, Mohd. Khairul Bazli
author_facet Mohd. Aziz, Mohd. Khairul Bazli
author_sort Mohd. Aziz, Mohd. Khairul Bazli
title Stochastic modeling of the C. Acetobutylicum and solvent productions in fermentation
title_short Stochastic modeling of the C. Acetobutylicum and solvent productions in fermentation
title_full Stochastic modeling of the C. Acetobutylicum and solvent productions in fermentation
title_fullStr Stochastic modeling of the C. Acetobutylicum and solvent productions in fermentation
title_full_unstemmed Stochastic modeling of the C. Acetobutylicum and solvent productions in fermentation
title_sort stochastic modeling of the c. acetobutylicum and solvent productions in fermentation
publishDate 2010
url http://eprints.utm.my/id/eprint/12331/6/MohdKhairulBazliMFS2010.pdf
http://eprints.utm.my/id/eprint/12331/
_version_ 1643645925971722240
score 13.211869

Similar Items