Experimental Study and Neural Network Modeling of Enzymatic Hydrolysis of Microalgal Biomass for Bioethanol Production

Some key factors such as high growth rate, low demand for arable land and fresh water and high carbohydrate content causes microalgae to introduce a new sourceof bioethanol.In this study,mixed microalgae culture was cultivated in the plate photo-reactors. Afterwards, nitrogen starvation strategy was used to accumulate storage carbohydrates. After harvesting of microalgae, enzymatic hydrolysis was applied to extract the sugars in biomass. The concentrations of extracted reducing sugar using hydrolysis process were investigated at four different substrate concentrations and three different temperatures over time. The process simulation by neural networks was performed using MATLAB software program. The networkinput consisted of substrate concentration, temperature, hydrolysis time and the networkoutput consisted of reducing sugar concentration. Artificial neural network with one hidden layer of 8 neurons in conditions (70-15-15) has minimum Mean Square Error (MSE).