The depletion of fossil fuels and growing environmental concerns necessitate the development of renewable biofuels. Blighia sapida seed oil, an inedible and underutilized resource, presents a viable option for biodiesel production. This study optimized its transesterification process using advanced modelling to improve yield and fuel quality. A two-step esterification–transesterification approach was used, with process variables, methanol-to-oil molar ratio (6:1–12:1), catalyst concentration (0.5–1.5 wt%), reaction temperature (50°C–70 °C), and time (30–90 min), optimized via Response Surface Methodology (RSM) and Adaptive Neuro-Fuzzy Inference System integrated with Particle Swarm Optimization (ANFIS–PSO). Model performance was evaluated using R 2 , RMSE, and MAE. ANFIS–PSO outperformed RSM with R 2 = 0.9997, RMSE = 0.0925, and MAE = 0.0721, compared to RSM’s R 2 = 0.9896, RMSE = 0.6384, and MAE = 0.4162. Optimal ANFIS–PSO conditions, methanol-to-oil ratio of 9.8:1, catalyst concentration of 1.2 wt%, temperature of 62 °C, and reaction time of 78 min, yielded 96.21% biodiesel. The biodiesel met international standards: kinematic viscosity (3.38 mm 2 /s), flash point (167 °C), density (0.8765 g/cm 3 ), acid value (1.178 mg KOH/g), and cetane number (58.06). These findings validate B. sapida as a promising biodiesel feedstock and position ANFIS–PSO as a superior modelling tool for scalable biofuel production from non-edible sources.
Ogunkunle et al. (2026) studied this question.