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Optimization of microwave-assisted solvent extraction of non-edible sandbox (Hura crepitans) seed oil: A potential biodiesel feedstock

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  • Ibrahim, Ayooluwa Paul
  • Omilakin, Ropo Oluwasesan
  • Betiku, Eriola

Abstract

In this study, modeling and optimization of the microwave-assisted solvent extraction (MASE) of sandbox seed oil (SSO) were investigated. D-optimal design with two numeric (extraction time (5–15 min), heating power (180–540 W)) and two categoric (solid/solvent ratio (1:10–1:40) and solvent type (ethyl acetate, n-hexane and acetone)) factors was used to model and optimize SSO yield. The model developed had coefficient of determination (R2) of 0.9821, indicating it can be used to adequately describe the MASE process with high accuracy. Optimum SSO yield of 72.20 ± 0.35 wt% could be obtained using extraction time of 5 min, microwave heating power of 180 W, solid/solvent ratio of 1:40 and ethyl acetate as solvent of extraction. Performance evaluation of the solvents in terms of oil yield showed that ethyl acetate was the most efficient (72.20 ± 0.35 wt%) followed by acetone (57.90 ± 1.27 wt%) and n-hexane (56.25 ± 1.77 wt%). Physicochemical properties of the SSO varied depending on the solvent of extraction. Fatty acids profile of the SSO showed that it had more unsaturated (79.7–84.5%) fractions than saturated (15.5–20.2%) fractions. Therefore, SSO could serve as feedstock for biodiesel and other oleochemical production.

Suggested Citation

  • Ibrahim, Ayooluwa Paul & Omilakin, Ropo Oluwasesan & Betiku, Eriola, 2019. "Optimization of microwave-assisted solvent extraction of non-edible sandbox (Hura crepitans) seed oil: A potential biodiesel feedstock," Renewable Energy, Elsevier, vol. 141(C), pages 349-358.
    • Handle: RePEc:eee:renene:v:141:y:2019:i:c:p:349-358
    DOI: 10.1016/j.renene.2019.04.010
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    References listed on IDEAS

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    1. Jack P. C. Kleijnen, 2015. "Response Surface Methodology," International Series in Operations Research & Management Science, in: Michael C Fu (ed.), Handbook of Simulation Optimization, edition 127, chapter 0, pages 81-104, Springer.
    2. Feng, Weiliang & Qian, Liang & Wang, Weiguo & Wang, Teilin & Deng, Zikui & Yang, Fang & Xiong, Jing & Wang, Cunwen, 2018. "Exploring the potential of lipids from black soldier fly: New paradigm for biodiesel production (II)—Extraction kinetics and thermodynamic," Renewable Energy, Elsevier, vol. 119(C), pages 12-18.
    3. Ogbu, I.M. & Ajiwe, V.I.E., 2016. "FTIR studies of thermal stability of the oils and methyl esters from Afzelia africana and Hura crepitans seeds," Renewable Energy, Elsevier, vol. 96(PA), pages 203-208.
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    Cited by:

    1. Thangarasu, Vinoth & M, Angkayarkan Vinayakaselvi & Ramanathan, Anand, 2021. "Artificial neural network approach for parametric investigation of biodiesel synthesis using biocatalyst and engine characteristics of diesel engine fuelled with Aegle Marmelos Correa biodiesel," Energy, Elsevier, vol. 230(C).
    2. Oraegbunam, Jennifer Chinazor & Oladipo, Babatunde & Falowo, Olayomi Abiodun & Betiku, Eriola, 2020. "Clean sandbox (Hura crepitans) oil methyl esters synthesis: A kinetic and thermodynamic study through pH monitoring approach," Renewable Energy, Elsevier, vol. 160(C), pages 526-537.

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