E-monitoring of in vitro culture parameters for prediction of maximal biomass yields

An e-monitoring system was established and modeled by object-oriented methodology for prediction of the maximal biomass yields based on in vitro culture parameters. The system calculates the maximal biomass yields through neuro-fuzzy or adaptive neuro-fuzzy inference system (ANFIS) methodology. The...

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Bibliographic Details
Published in:Biomass conversion and biorefinery 2022-12, Vol.12 (12), p.5677-5685
Main Authors: Petković, Biljana, Petkovic, Dalibor, Kuzman, Boris, Jovanovic, Drazen
Format: Article
Language:English
Subjects:
Adaptive systems
Artificial neural networks
Biomass
Biotechnology
Energy
Fuzzy logic
Mathematical models
Model accuracy
Monitoring
Original Article
Parameters
Renewable and Green Energy
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Summary:An e-monitoring system was established and modeled by object-oriented methodology for prediction of the maximal biomass yields based on in vitro culture parameters. The system calculates the maximal biomass yields through neuro-fuzzy or adaptive neuro-fuzzy inference system (ANFIS) methodology. The final biomass fresh weight was considered as a function of culture parameters. ANFIS models were created for the prediction of the maximal biomass yields. According to the prediction accuracy of the models, the inputs’ influence was determined on the biomass fresh weight. It was determined that the pH of growth medium has the highest impact on the biomass fresh weight (RMSE = 0.8302) while the medium culture vessel has the smallest influence on the biomass fresh weight (RMSE = 0.9556). The designed e-monitoring system could have the potential for practical applications.
ISSN:2190-6815
2190-6823
DOI:10.1007/s13399-020-00986-6