Aim: The study employed the Response surface methodology (RSM) model to optimize ethanol production from Calabash (Crescentia cujete) pulp juice using Saccharomyces cerevisiae.
Study Design: The Calabash pulp was squeezed with muslin cloth, and vacuum filtered to clear solution before use. The clear juice was tested for reducing sugars using the Dinitrosalicylic acid (DNS) method. Twenty three (23) runs, including 3 controls, of the fermentation was conducted at varying temperatures, pH, and volumes of inoculum.The process parameters (input variables): volumes of inoculum, temperature,and pH were subjected to response surface model, using the Central Composite Design (CCD).
Place and Duration of Study: This study was carried out in the Environmental Microbiology Laboratory, University of Port Harcourt for six months.
Methodology: Fermentation was done in conical flasks covered with cotton wool and foil in a stationary incubator for four days (96 hours). Active stock culture of Saccharomyces cerevisiae was used, with inoculum developed using Marcfaland’s method. Samples were collected every 24 hours, centrifuged, filtered and analyzed for measurement of the output variables: Reducing sugar, cell density and ethanol concentration.
Results: The concentration of reducing sugars from Calabash pulp was 3.2 mg/ml. Results obtained also revealed that the fermentation can take place on a wide range of temperature 25-40°C. The optimal pH range for performance of S. cerevisiae for the fermentation process was pH 5.0-6.5. The optimum volume of inoculum was 5.5%v/v (ie 5.5 ml in 94.5ml juice). The optimized process using the RSM model gave 6.19% v/v bioethanol.
Control: The bioethanol yield from Calabash substrate is reasonable considering the concentration of reducing sugars obtained from the juice and the duration of the fermentation.
Soy whey based medium for optimized phytase activity in Saccharomyces cerevisiae MTCC 5421 and α-D-galactosidase and antibacterial activities in Lactobacillus plantarum MTCC 5422 by response surface methodology