Oil Extraction from Butter Fruit (Dacryodes Edulis) Seeds and its Optimization via Response Surface and Artificial Neural Networ

Abstract

In this study, oil was extracted from butter fruit (Dacrydes edulis). To model and optimize the process conditions of oil extraction, Response Surface Methodology (RSM) and Artificial Neural Network (ANN) were used. Physicochemical analysis of the oil was carried out in order to determine the suitable of oil for industrial applications. Dacryodes edulis seeds were collected from Ikot Abasi Village in Eket Local Government of Akwa Ibom State, Nigeria. The seed was washed with clean water to remove dirt, and open with a sharp stainless knife to remove the seed from the pulp. The seeds were cut into small pieces and sundried for 5 days and were grinded into powder. Oil extraction from the powder seed was carried out using Sohxlet extraction method. The experiment was designed using Box-Behnken Design approach on three levels, three factors which generated 17 experimental runs. Independent factors considered were extraction time (X1), solvent volume (X2) and sample weight (X3). The accuracy of the regression model obtained from the optimization software was determined using the co-efficient of determination (R2). Results showed the highest oil yield of 17.878% (w/w) was obtained at solvent volume of 200 ml, sample weight of 50 g and extraction time of 55 min, respectively. However, response surface methodology predicted an oil yield of 17.826% (w/w), while the artificial neural network predicted 17.875% (w/w) at the same variables condition. The predicted values were validated in triplicate, and an average of 17.46% (w/w) and 17.72% (w/w) were obtained for RSM and ANN, respectively. The predicted values obtained were well within the range predicted. The coefficient of determination, which determines the model accuracy, was obtained to be 0.8454 for RSM and 0.8712 for ANN. Physicochemical analysis of the oil showed the oil is highly unsaturated with high saponification value and high iodine value. The study concluded that Dacryodes edulis seeds are found to be rich in oil and the oil can be applicable in industries as raw materials for products formation.

Keywords

• Dacryodes edulis seeds
• response surface
• artificial neural network
• optimization
• extraction