Bioethanol is known as a viable alternative fuel to solve both energy and environmental crises. This study used response surface methodology based on the Box-Behnken experimental design to obtain the optimum conditions for and quality of bioethanol production. Enzymatic hydrolysis optimization was performed with selected hydrolysis parameters, including substrate loading, stroke speed, α-amylase concentration and amyloglucosidase concentration. From the experiment, the resulting optimum conditions are 23.88% (w/v) substrate loading, 109.43 U/g α-amylase concentration, 65.44 U/mL amyloglucosidase concentration and 74.87 rpm stroke speed, which yielded 196.23 g/L reducing sugar. The fermentation process was also carried out, with a production value of 0.45 g ethanol/g reducing sugar, which is equivalent to 88.61% of ethanol yield after fermentation by using Saccharomyces cerevisiae (S. cerevisiae). The physical and chemical properties of the produced ethanol are within the specifications of the ASTM D4806 standard. The good quality of ethanol produced from this study indicates that Manihot glaziovii (M. glaziovii) has great potential as bioethanol feedstock.

Optimizing the process parameters of biodiesel production is the key to maximizing biodiesel yields. In this study, artificial neural network models integrated with ant colony optimization were developed to optimize the parameters of the two-step Cerbera manghas biodiesel production process: (1) esterification and (2) transesterification. The parameters of esterification and transesterification processes were optimized to minimize the acid value and maximize the C. manghas biodiesel yield, respectively. There was excellent agreement between the average experimental values and those predicted by the artificial neural network models, indicating their reliability. These models will be useful to predict the optimum process parameters, reducing the trial and error of conventional experimentation. The kinetic study was conducted to understand the mechanism of the transesterification process and, lastly, the model could measure the physicochemical properties of the C. manghas biodiesel.

The limitation of fossil fuel sources and negative environmental impact persuade scientists around the world to find a solution. One possible solution is by using renewable fuel to replace fossil fuel with an inexpensive, fast, and effective production process. The objective of this study is to investigate the biodiesel production from crude Reutealis trisperma oil using the conventional and the ultrasonic bath stirrer method through the esterification and transesterification process. The result shows that the most effective reaction time with an optimum condition for the esterification and transesterification of Reutealis trisperma oil is at 2 h 30 min by using the ultrasonic bath stirrer method. The optimum conditions at a temperature of 55 °C for the esterification and at 60 °C for transesterification with 2% (v/v) of sulphuric acid with catalyst concentration of 0.5 wt.% were a methanol-to-oil ratio of 60%, and agitation speed of 1000 rpm. This optimum condition gives the highest yield of 95.29% for the Reutealis trisperma biodiesel. The results showed that the ultrasonic bath stirrer method had more effect on the reaction time needed than using the conventional method and reduced half of the conventional method reaction time. Finally, the properties of Reutealis trisperma biodiesel fulfilled the ASTM D6751 and EN 14214 biodiesel standards with density, 892 kg/m³; pour point, −2 °C; cloud point, −1 °C; flash point, 206.5 °C; calorific value, 40.098 MJ/kg; and acid value, 0.26 mg KOH/g.