The use of vegetable oil as feedstock for biodiesel production is controversial as a result of the challenges of a food-fuel crisis associated with the use of edible oils for biodiesel production and use of arable land for energy feedstock generation. This work, therefore, focused on the extraction of oil from non-edible seed such as sandbox seed using a solvent extraction method, evaluation of optimal conditions for oil extraction from sandbox, and testing the fuel properties of extracted sandbox oil. A Box-Behnken design of response surface methodology (RSM) with 17 experimental runs was used to investigate the optimum conditions for the extraction, and the selected variables were effective seed/ solvent ratio (0.04, 0.06, 0.08 g/ml), extraction temperature (65, 60, 75ºC), and extraction time (3, 5, 7 h). Selected fuel properties (specific gravity, viscosity, cloud point, pour point, density, and refractive index) of the extracted oil were determined according to American Society for Testing Materials (ASTM) standards.The optimum oil yield (63.4%) was obtained at the seed/solvent ratio, extraction temperature, and extraction time of 0.05 g/ml, 68.13ºC, and 5 h, respectively The viscosity at 30ºC, specific gravity, density, cloud point, pour point, and refractive index of the extracted oil were 4.55 mm 2 /s, 0.91, 910 kg/m 3 , 5.9 ºC, -1.0ºC, and 1.4683, respectively. Thus the result from this research work has established the optimal conditions for solvent extraction of oil from sandbox seed. The fuel properties of the sandbox oil show that it is potentially suitable to produce biodiesel that can be used to power internal combustion engines. ARTICLE HISTORY

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Biodiesel has been seen as an alternative to diesel (fossil) fuel as a result of its favourable properties, energy security reasons and environmental benefits. In this research, transesterification of sandbox seed oil with ethanol to form biodiesel has been modelled using artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) techniques. Temperature (oC), time (min.), catalyst concentration (w/w) and catalyst type (g) were used as input variables while biodiesel yield was used as output variable for modelling the efficiency of biodiesel production from sandbox seed oil. The results showed that ANN model gave R2 of 0.925, RSME of 2.99255, MAE of 0.62196, SEP of 0.03689 and AD of 0.03194 while ANFIS model gave R2 of 0.961, RSME of 1.97379, MAE of 0.0001, SEP of 0.02433 and AD of 0.000005136. The results prove that ANFIS model is more reliable in predicting biodiesel yield from sandbox seed oil than ANN model.