Abstract:
D- Gluconic acid is a simple dehydrogenation product of D- glucose which is widely used in the food, pharmaceutical, and chemical industries. Its market is now over 60,000 tonnes per annum and is still growing. Production of gluconic acid using several routes such as chemical, electrochemical, enzyme bioreactor, free and immobilized cells of either Gluconobacter oxydans, penicillium chrysogenum or Aspergillus niger have been extensively reviewed.
In the present work, we report on the bioconversion of glucose to gluconic acid under submerged conditions using mycelia of A. niger which has potential for better yield of acid. The aim of this work has been to optimize submerged fermentation process parameters. Experimental results showing the effects of variations in initial pH, CaCO3% composition in media, initial glucose level and fermentation period on yield of gluconic acid and biomass production under submerged phenomena have been obtained. It has been concluded that all the investigated parameters significantly affect the production process and their optimal values were explored.
Experimental results obtained by process parameter optimization on batch process of fermentation of glucose to gluconic acid by Aspergillus niger show complex dynamic behaviour including a decline in yield. The data have been analyzed using an artificial intelligence based statistical analysis method to provide a regression model for predicting values of conversion, yield and biomass production. 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 glucose to gluconic acid..
