Software sensors for Monitoring of Biopolymer Production
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F21%3A43923546" target="_blank" >RIV/60461373:22340/21:43923546 - isvavai.cz</a>
Výsledek na webu
<a href="https://ieeexplore.ieee.org/document/9447540" target="_blank" >https://ieeexplore.ieee.org/document/9447540</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/PC52310.2021.9447540" target="_blank" >10.1109/PC52310.2021.9447540</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Software sensors for Monitoring of Biopolymer Production
Popis výsledku v původním jazyce
The topic of this paper is the design of software sensors for online monitoring of the biotechnological process of biopolymer production, in which biopolymers are accumulated in bacteria as an intracellular energy storage material. The proposed software sensors enabling on-line estimation of the biopolymer concentration represent in the case of these complicated bioprocesses an interesting alternative to the traditional off-line analytical techniques, which have only limited applicability for the real-time control of these bioprocesses. Due to the complexity of biochemical reactions, which make it difficult to create reasonably complex and therefore practically applicable first-principle mathematical models, a data-driven approach to the design of software sensors has been chosen in the presented study. Thus, regression methods were used in the design of the proposed software sensors, including multivariate statistical methods (PLS, PCR), which enabled the creation of software sensors using historical process data. The so obtained software sensors enable not only on-line estimation of the biopolymer concentration, but also the concentration of the cell biomass of the production bacterial culture. The model process for this study was fed-batch cultivation of the Pseudomonas putida KT2442 strain used for the production of medium-chain-length polyhydroxyalkanoates (mcl-PHAs).
Název v anglickém jazyce
Software sensors for Monitoring of Biopolymer Production
Popis výsledku anglicky
The topic of this paper is the design of software sensors for online monitoring of the biotechnological process of biopolymer production, in which biopolymers are accumulated in bacteria as an intracellular energy storage material. The proposed software sensors enabling on-line estimation of the biopolymer concentration represent in the case of these complicated bioprocesses an interesting alternative to the traditional off-line analytical techniques, which have only limited applicability for the real-time control of these bioprocesses. Due to the complexity of biochemical reactions, which make it difficult to create reasonably complex and therefore practically applicable first-principle mathematical models, a data-driven approach to the design of software sensors has been chosen in the presented study. Thus, regression methods were used in the design of the proposed software sensors, including multivariate statistical methods (PLS, PCR), which enabled the creation of software sensors using historical process data. The so obtained software sensors enable not only on-line estimation of the biopolymer concentration, but also the concentration of the cell biomass of the production bacterial culture. The model process for this study was fed-batch cultivation of the Pseudomonas putida KT2442 strain used for the production of medium-chain-length polyhydroxyalkanoates (mcl-PHAs).
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
20205 - Automation and control systems
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2021
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Proceedings of the 2021 23rd International Conference on Process Control (PC)
ISBN
978-1-66540-330-6
ISSN
—
e-ISSN
—
Počet stran výsledku
5
Strana od-do
308-312
Název nakladatele
Czechoslovakia Section IEEE
Místo vydání
Praha
Místo konání akce
Štrbské Pleso
Datum konání akce
1. 6. 2021
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
000723653400052