Abundant oil palm empty fruit bunches (OPEFB) generated from the palm oil mill industry create huge problems for the environment and the palm oil mill itself. Despite the importance of determining the amount of oil left in the OPEFB, little research of that nature has been reported. This study describes the oil content and physicochemical characteristics of OPEFB fibers, detection of oil attachment on the fiber’s surface using sudan red dye, contact angle values, and also the quality of the residual oil. The OPEFB fibers, which are normally used as mulch for the palm oil mill, have been found to be a rich source of lignocellulosic materials, especially cellulose, which constitutes 33.70 to 35.10% for a press-shredded fiber. Residual oil (3 to 7% on dry basis) extracted from the OPEFB exhibits good quality parameters such as deterioration of bleachability index (DOBI), free fatty acid (FFA), and peroxide value (PV). The DOBI values were still in the acceptable range, which is from 1.94 to 2.43, while the PV results are within the range of about 1.84 to 2.80 meq/kg. The major fatty acids of the residual fiber oil were palmitic and oleic acids, at 39.77% to 39.89% and 39.55% to 42.60%, respectively. There were no significant changes in the macronutrients and quality of the OPEFB residual oil. Therefore, the residual oil from the OPEFB should be recovered and reused as a raw material for industrial applications, boosting the oil extraction rate (OER) in the palm oil industry.
Food waste with high carbohydrate content is considered as a suitable substrate for fermentation of methane gas. In this study, co-digestion of poultry manure (PM) and food waste (FW) was used. Response surface methodology (RSM) and artificial neural network (ANN) were applied to optimize parameters of co-digestion of PM and FW at different ratios, initial pH values and temperatures. A comparative analysis was done using RSM and ANN in a predictive model of the experimental data obtained in accordance with the central composite design. The combined effects of the independent variables (ratio, pH and temperature) as the most significant parameters of methane fermentation of PM and FW were investigated. Optimization using RSM and ANN showed a good fit between the experimental and the predicted data as elucidated by the coefficient of determination with R 2 values of 0.991 and 0.998, respectively. Quadratic RSM predicted the maximum methane yield to be 537 mL CH 4 /g VS at the optimal conditions; ratio 80:20 (PM : FW); temperature 35 °C; and initial pH 7.11. The maximum predicted methane yield by the ANN model was 535.82 mL CH 4 /g VS at the following conditions; ratio of poultry manure to food waste 80:20; temperature 35 °C; and pH 7.00. The verification experiments successfully produced 538 mL CH 4 /g VS within 14 days of incubation. These experiments indicated that the developed model was successfully used to predict the fermentable methane production.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.