An artificial intelligence tool for bioprocess monitoring: application to continuous production of gluconic acid by immobilized Aspergillus niger

Abstract

Experimental data on continuous fermentation of sucrose and glucose solution at low pH to gluconic acid by Asprgillus niger immobilized on cellulose fabric show complex dynamic behaviour including a decline in yield. The data have been analyzed using an artificial intelligence based symbolic regression technique to provide a mathematical model for predicting values of conversion 5, 10 and 15 h ahead values of conversion. These predictions can be used during continuous operations to monitor the bioprocess and adjust the residence time of fermentation to get complete and more efficient conversion of sucrose or glucose to gluconic acid.