A robust soft sensor to monitor 1,3-propanediol fermentation process by Clostridium butyricum based on artificial neural network.

Biotechnology and Bioengineering
Ai-Hui ZhangBai-Shan Fang

Abstract

With the aggravation of environmental pollution and energy crisis, the sustainable microbial fermentation process of converting glycerol to 1,3-propanediol (1,3-PDO) has become an attractive alternative. However, the difficulty in the online measurement of glycerol and 1,3-PDO creates a barrier to the fermentation process and then leads to the residual glycerol and therefore, its wastage. Thus, in the present study, the four-input artificial neural network (ANN) model was developed successfully to predict the concentration of glycerol, 1,3-PDO, and biomass with high accuracy. Moreover, an ANN model combined with a kinetic model was also successfully developed to simulate the fed-batch fermentation process accurately. Hence, a soft sensor from the ANN model based on NaOH-related parameters has been successfully developed which cannot only be applied in software to solve the difficulty of glycerol and 1,3-PDO online measurement during the industrialization process, but also offer insight and reference for similar fermentation processes.

References

Aug 12, 2009·Biotechnology Advances·R K SaxenaJasmine Isar
Nov 9, 2010·Biotechnology Journal·Hongjuan LiuDehua Liu
Oct 6, 2011·Applied Microbiology and Biotechnology·Erik WilkensKlaus-Dieter Vorlop
Feb 22, 2014·BMC Microbiology·Daria Szymanowska-Powałowska, Wojciech Białas
Jul 23, 2019·Biotechnology and Bioengineering·Deepti SusannaViraraghavan Ramamurthy

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Citations

Jul 3, 2021·Life·Anurag S RathorePriyanka Priyanka

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