Studies on simultaneous saccharification and fermentation (SSF) of wheat bran flour, a grain milling residue as the substrate using coculture method were carried out with strains of starch digesting Aspergillus niger and nonstarch digesting and sugar fermenting Kluyveromyces marxianus in batch fermentation. Experiments based on central composite design (CCD) were conducted to maximize the glucose yield and to study the effects of substrate concentration, pH, temperature, and enzyme concentration on percentage conversion of wheat bran flour starch to glucose by treatment with fungal α-amylase and the above parameters were optimized using response surface methodology (RSM). The optimum values of substrate concentration, pH, temperature, and enzyme concentration were found to be 200 g/L, 5.5, 65°C and 7.5 IU, respectively, in the starch saccharification step. The effects of pH, temperature and substrate concentration on ethanol concentration, biomass and reducing sugar concentration were also investigated. The optimum temperature and pH were found to be 30°C and 5.5, respectively. The wheat bran flour solution equivalent to 6% (w/V) initial starch concentration gave the highest ethanol concentration of 23.1 g/L after 48 h of fermentation at optimum conditions of pH and temperature. The growth kinetics was modeled using Monod model and Logistic model and product formation kinetics using LeudekingPiret model. Simultaneous saccharificiation and fermentation of liquefied wheat bran starch to bioethanol was studied using coculture of amylolytic fungus A. niger and nonamylolytic sugar fermenting K. marxianus.

Ethanol production from agricultural products mainly corn, wheat, sweat potato and residue are gaining importance and requires an industrially viable novel technology namely simultaneous saccharification and fermentation process. This process has an advantage of carrying out saccharification using enzyme and fermentation using yeast in a single fermenter. The investment cost for industrial ethanol production using cheap agricultural residues can be well achieved using SSF process. The success of SSF process greatly depends upon the pretreatment methods using different enzymes to break the complex carbohydrates to simple sugars. Optimization of key process variables is essential to maximize the ethanol yield from suitable substrates. The key process variables affecting the SSF process are pH, temperature, fermentation time, enzyme concentration and substrate concentration. The medium components are to be screened for effective nitrogen, potassium and phosphorous sources to increase the ethanol yield.

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Ethanol is viable alternative fuel and it’s substitute to fossil fuel has gained importance with rise in fuel prices. The chapter elaborates about methods of production from different types of bio resources like molasses, starch and cellulose commercially. The chapter also details about different methods of pretreatment for cellulisic and starchy raw materials. This also includes hydrolysis using acid and enzymes. The modes of ethanol fermentation using bioreactors like batch fed batch and continuous operation will be discussed. The growth kinetics models like monad logistic model will be elaborated. The product formation growth associated models like Leudiking piret model and parameter estimation methods will be described. Optimization of process variables using response surface methodology and media optimization using PB design will be elaborated. The application of ANN in modeling will be described.