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System identification of the fermentation system of Thermoanaerobacter sp. X514

Authors: Jing Yang 0006; Xiaofang Ling; Lishan Yao; Hua-Liang Wei; Visakan Kadirkamanathan;

System identification of the fermentation system of Thermoanaerobacter sp. X514

Abstract

Bioethanol production by means of anaerobic thermophilic microorganisms with pentose or hexose as the substrate are of paramount importance in sustainable fuel innovation. Manipulation of microorganisms and the associated experiment conditions by means of various ad-hoc technology is obviously the most straightforward way with the aim of maximizing bioethanol yield. However, methodology by means of mathematical modeling and analysis is often neglected among these routines. In this paper, typical input-output models are applied in the metabolic system analysis of Thermoanaerobacter sp. X514 under sole glucose substrate, sole xylose substrate and mixed glucose and xylose substrates conditions. Orthogonal Least Squares (OLS) approach is used for model parameter estimation. Model selection is proposed in order to testify the generality of the suggested model. System identification results illustrate that various forms of Nonlinear AutoRegressive with eXogenous input models (NARX) are applicable in delineating the system where different substrates (glucose or xylose) are utilized during the experiments. The proposed model structure infers that the yields of various products in X514 are mainly driven by the history information of the substrate consumption change. Moreover, the interaction between the main fermentation products of X514 is indirectly connected through the proposed models.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
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