Monitoring of Biopolymer Production Process Using Soft Sensors Based on Off-Gas Composition Analysis and Capacitance Measurement
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F21%3A43923547" target="_blank" >RIV/60461373:22340/21:43923547 - isvavai.cz</a>
Výsledek na webu
<a href="https://www.mdpi.com/2311-5637/7/4/318" target="_blank" >https://www.mdpi.com/2311-5637/7/4/318</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/fermentation7040318" target="_blank" >10.3390/fermentation7040318</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Monitoring of Biopolymer Production Process Using Soft Sensors Based on Off-Gas Composition Analysis and Capacitance Measurement
Popis výsledku v původním jazyce
This paper focuses on the design of soft sensors for on-line monitoring of the biotechnological process of biopolymer production, in which biopolymers are accumulated in bacteria as an intracellular energy storage material. The proposed soft sensors for on-line estimation of the biopolymer concentration represent an interesting alternative to the traditional off-line analytical techniques of limited applicability for real-time process control. Due to the complexity of biochemical reactions, which make it difficult to create reasonably complex first-principle mathematical models, a data-driven approach to the design of soft sensors has been chosen in the presented study. Thus, regression methods were used in this design, including multivariate statistical methods (PLS, PCR). This approach enabled the creation of soft sensors using historical process data from fed-batch cultivations of the Pseudomonas putida KT2442 strain used for the production of medium-chain-length polyhydroxyalkanoates (mcl-PHAs). Specifically, data from on-line measurements of off-gas composition analysis and culture medium capacitance were used as input to the soft sensors. The resulting soft sensors allow not only on-line estimation of the biopolymer concentration, but also the concentration of the cell biomass of the production bacterial culture. For most of these soft sensors, the estimation error did not exceed 5% of the measurement range. In addition, soft sensors based on capacitance measurement were able to accurately detect the end of the production phase. This study thus offers an innovative and practically relevant contribution to the field of monitoring of bioprocesses used for the production of medium-chain-length biopolymers.
Název v anglickém jazyce
Monitoring of Biopolymer Production Process Using Soft Sensors Based on Off-Gas Composition Analysis and Capacitance Measurement
Popis výsledku anglicky
This paper focuses on the design of soft sensors for on-line monitoring of the biotechnological process of biopolymer production, in which biopolymers are accumulated in bacteria as an intracellular energy storage material. The proposed soft sensors for on-line estimation of the biopolymer concentration represent an interesting alternative to the traditional off-line analytical techniques of limited applicability for real-time process control. Due to the complexity of biochemical reactions, which make it difficult to create reasonably complex first-principle mathematical models, a data-driven approach to the design of soft sensors has been chosen in the presented study. Thus, regression methods were used in this design, including multivariate statistical methods (PLS, PCR). This approach enabled the creation of soft sensors using historical process data from fed-batch cultivations of the Pseudomonas putida KT2442 strain used for the production of medium-chain-length polyhydroxyalkanoates (mcl-PHAs). Specifically, data from on-line measurements of off-gas composition analysis and culture medium capacitance were used as input to the soft sensors. The resulting soft sensors allow not only on-line estimation of the biopolymer concentration, but also the concentration of the cell biomass of the production bacterial culture. For most of these soft sensors, the estimation error did not exceed 5% of the measurement range. In addition, soft sensors based on capacitance measurement were able to accurately detect the end of the production phase. This study thus offers an innovative and practically relevant contribution to the field of monitoring of bioprocesses used for the production of medium-chain-length biopolymers.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
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 periodika
Fermentation
ISSN
2311-5637
e-ISSN
—
Svazek periodika
7
Číslo periodika v rámci svazku
4
Stát vydavatele periodika
CH - Švýcarská konfederace
Počet stran výsledku
13
Strana od-do
—
Kód UT WoS článku
000737163700001
EID výsledku v databázi Scopus
—