COMPARATIVE EVALUATION OF DESIGN OF EXPERIMENTS TECHNIQUES FOR YELLOW OLEANDER BIODIESEL PRODUCTION

Jeremiah MASIME; Betty MBATIA; Erich OGUR; Geoffrey OTIENO

doi:10.24193/subbchem.2026.3.06

Authors

Jeremiah MASIME Department of Chemistry and Material Science, Technical University of Kenya, Nairobi, Kenya. *Corresponding author: masimejo@gmail.com
Betty MBATIA School of Pharmacy and Health Sciences, United States International University-Africa, Nairobi, Kenya
Erich OGUR Department of Mechanical and Mechatronic Engineering, Technical University of Kenya, Nairobi, Kenya
Geoffrey OTIENO Department of Chemical Science and Technology, Technical University of Kenya, Nairobi, Kenya

DOI:

https://doi.org/10.24193/subbchem.2026.3.06

Keywords:

Yellow oleander biodiesel, Eggshell-derived CaO, Design of Experiments

Abstract

This study optimized biodiesel production from yellow oleander (Thevetia peruviana) oil using eggshell-derived CaO nanocatalysts through an integrated Design of Experiments (DoE) approach. A full factorial design (FFD), Taguchi analysis, and response surface methodology based on the Box–Behnken design (RSM-BBD) were sequentially applied to optimize the transesterification process. The RSM-BBD model demonstrated excellent predictive accuracy (R² = 0.994; adjusted R² = 0.982) and predicted a maximum biodiesel yield of 96.8%. ANOVA identified reaction time as the most significant factor (39.94%), followed by the temperature–catalyst interaction (19.38%). Signal-to-noise (S/N) ratio analysis indicated that shorter reaction times enhanced process robustness. The integrated optimization strategy reduced experimental runs by approximately 60% compared to conventional one-factor-at-a-time approaches (from approximately 75 full factorial runs to 30 BBD runs) while maintaining high precision. Optimum conditions were validated at 60°C, 75 minutes, and 1.0 wt.% catalyst loading, confirming yellow oleander oil as a promising sustainable biodiesel feedstock.

References

1. J. Wang and W. Azam, “Natural resource scarcity, fossil fuel energy consumption, and total greenhouse gas emissions in top emitting countries,” Geoscience Frontiers, vol. 15, no. 2, p. 101757, 2024, doi: https://doi.org/10.1016/j.gsf.2023.101757.

2. “Oil 2020 - Analysis and forecast to 2025”.

3. L. S. Paraschiv and S. Paraschiv, “Contribution of renewable energy (hydro, wind, solar and biomass) to decarbonization and transformation of the electricity generation sector for sustainable development,” Energy Reports, vol. 9, pp. 535–544, Sep. 2023, doi: https://doi.org/10.1016/j.egyr.2023.07.024.

4. B. Ma and A. Wang, “Exploring the role of renewable energy in green job creation and sustainable economic development: An empirical approach,” Energy Strategy Reviews, vol. 58, p. 101642, Mar. 2025, doi: https://doi.org/10.1016/j.esr.2025.101642.

5. W. N. A. Wan Osman, M. H. Rosli, W. N. A. Mazli, and S. Samsuri, “Comparative review of biodiesel production and purification,” Carbon Capture Science & Technology, vol. 13, p. 100264, Dec. 2024, doi: https://doi.org/10.1016/j.ccst.2024.100264.

6. E. M. Aro, “From first generation biofuels to advanced solar biofuels,” Ambio, vol. 45, no. 1, pp. 24–31, 2016, doi: https://doi.org/10.1007/s13280-015-0730-0.

7. S. Brahma, B. Nath, B. Basumatary, B. Das, P. Saikia, K. Patir, S. Basumatary “Biodiesel production from mixed oils: A sustainable approach towards industrial biofuel production,” Chemical Engineering Journal Advances, vol. 10, p. 100284, May 2022, doi: https://doi.org/10.1016/j.ceja.2022.100284.

8. S. Bhattacharyya, “Transesterification of Yellow Oleander seed oil, its utilization as biodiesel and performance evaluation,” Heliyon, vol. 8, no. 4, p. e09250, Apr. 2022, doi: https://doi.org/10.1016/j.heliyon.2022.e09250.

9. I. B. Hvidsten, K. H. Liland, O. Tomic, and J. M. Marchetti, “Modeling of biodiesel production using optimization designs from literature: aiming to reduce the laboratory workload,” Fuel Processing Technology, vol. 275, p. 108265, Oct. 2025, doi: https://doi.org/10.1016/j.fuproc.2025.108265.

10. N. Ferreira, T. Viana, B. Henriques, D.S. Tavares, J. Jacinto, J. Colónia, J. Pinto, E. Pereira, “Application of response surface methodology and box–behnken design for the optimization of mercury removal by Ulva sp.,” Journal of Hazardous Materials, vol. 445, p. 130405, Mar. 2023, doi: https://doi.org/10.1016/j.jhazmat.2022.130405.

11. A. Jankovic, G. Chaudhary, and F. Goia, “Designing the design of experiments (DOE) – An investigation on the influence of different factorial designs on the characterization of complex systems,” Energy and Buildings, vol. 250, p. 111298, Nov. 2021, doi: https://doi.org/10.1016/j.enbuild.2021.111298.

12. J. O. Masime, B. N. Mbatia, E. O. Ogur, A. O. Aluoch, and G. Otieno, “Optimization of Yellow Oleander Oil Extraction Process using Response Surface Methodology (RSM), and Central Composite Design (CCD),” 2025.

13. B. Birhanu, D. Deshmukh, T. Hailelule, and K. Yeneneh, “RSM-optimized biodiesel production from Ethiopian Podocarpus falcatus seed oil using a CaO-CeO2 heterogeneous composite catalyst and oxidative stability assessment,” Sci Rep, vol. 16, no. 1, p. 3919, Dec. 2025, doi: https://doi.org/10.1038/s41598-025-34007-1.

14. R. D. Rhithuparna, J.V.L. Ruatpuia, S.P. Gouda, P. Kodgire, S. Basumatary, G. Halder, S.L. Rokhum, “Microwave-assisted biodiesel production using bio-waste catalyst and process optimization using response surface methodology and kinetic study,” Sci Rep, vol. 13, no. 1, p. 2570, Feb. 2023, doi: https://doi.org/10.1038/s41598-023-29883-4.

15. E. Betiku and S. O. Ajala, “Modeling and optimization of Thevetia peruviana (yellow oleander) oil biodiesel synthesis via Musa paradisiacal (plantain) peels as heterogeneous base catalyst: A case of artificial neural network vs. response surface methodology,” Industrial Crops and Products, vol. 53, no. April 2019, pp. 314–322, 2014, doi: https://doi.org/10.1016/j.indcrop.2013.12.046.

16. B. Ogaga Ighose, I. A. Adeleke, M. Damos, H. Adeola Junaid, K. Ernest Okpalaeke, and E. Betiku, “Optimization of biodiesel production from Thevetia peruviana seed oil by adaptive neuro-fuzzy inference system coupled with genetic algorithm and response surface methodology,” Energy Conversion and Management, vol. 132, pp. 231–240, 2017, doi: https://doi.org/10.1016/j.enconman.2016.11.030.

17. A.I. Osman, M. Nasr, M. Farghali, A.K. Rashwan, A. Abdelkader, A.H. Al-Muhtaseb, I. Ihara, D.W. Rooney, “Optimizing biodiesel production from waste with computational chemistry, machine learning and policy insights: a review,” Environ Chem Lett, vol. 22, no. 3, pp. 1005–1071, Jun. 2024, doi: https://doi.org/10.1007/s10311-024-01700-y.

18. C.J. Taylor, A. Pomberger, K.C. Felton, R. Grainger, M. Barecka, T.W. Chamberlain, R.A. Bourne, C.N. Johnson, A.A. Lapkin, “A Brief Introduction to Chemical Reaction Optimization,” Chem. Rev., vol. 123, no. 6, pp. 3089–3126, Mar. 2023, doi: https://doi.org/10.1021/acs.chemrev.2c00798.

19. R. C. Sanito, S.-J. You, and Y.-F. Wang, “Application of Taguchi method and structural equation modeling on the treatment of e-waste,” Environmental Technology & Innovation, vol. 27, p. 102725, Aug. 2022, doi: https://doi.org/10.1016/j.eti.2022.102725.