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Evaluation and optimization of two stage sequential in situ transesterification process for fatty acid methyl ester quantification from microalgae

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  • Kumar, Vikram
  • Muthuraj, Muthusivaramapandian
  • Palabhanvi, Basavaraj
  • Ghoshal, Aloke Kumar
  • Das, Debasish

Abstract

This study demonstrates a direct transesterification (DT) method for reliable quantification of microalgal lipid. Primary screening of various transesterification methods and the types of biomass (wet, oven dried and lyophilized) were performed with heterotrophically grown Chlorella sp. FC2 IITG which revealed two stage DT with lyophilized biomass using NaOH in first stage and H2SO4 in second stage as the best combination with fatty acid methyl ester (FAME) yield of 39.17% (w/w, dry cell weight). Further optimization of transesterification parameters for selected method using response surface methodology, predicted the optimum values for catalyst to biomass ratio 0.67 (w/w) and 2.07 (v/w), methanol to biomass ratio 49.51 (v/w) and 61.07 (v/w) and reaction time 19.33 (min) and 10 (min) for first and second stages respectively. The optimum conditions showed 462.6% and 445.4% increment in FAME yield when compared with Bligh and Dyer method for Chlorella sp. FC2 IITG and Chlorella sorokiniana FC6 IITG respectively with highest transesterification efficiency of 98.96%. Improved transesterification efficiency of two stage DT was attributed to efficient destabilization of cell wall as confirmed by scanning electron microscopic imaging. FAME produced via DT of Chlorella sp. FC2 IITG satisfied most of the biodiesel properties as per ASTM D6751 and hence, could be an alternative to petro-diesel.

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  • Kumar, Vikram & Muthuraj, Muthusivaramapandian & Palabhanvi, Basavaraj & Ghoshal, Aloke Kumar & Das, Debasish, 2014. "Evaluation and optimization of two stage sequential in situ transesterification process for fatty acid methyl ester quantification from microalgae," Renewable Energy, Elsevier, vol. 68(C), pages 560-569.
    • Handle: RePEc:eee:renene:v:68:y:2014:i:c:p:560-569
    DOI: 10.1016/j.renene.2014.02.037
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    2. Arridina Susan Silitonga & Teuku Meurah Indra Mahlia & Abd Halim Shamsuddin & Hwai Chyuan Ong & Jassinnee Milano & Fitranto Kusumo & Abdi Hanra Sebayang & Surya Dharma & Husin Ibrahim & Hazlina Husin , 2019. "Optimization of Cerbera manghas Biodiesel Production Using Artificial Neural Networks Integrated with Ant Colony Optimization," Energies, MDPI, vol. 12(20), pages 1-21, October.
    3. Amit & Divakar Dahiya & Uttam K. Ghosh & Poonam S. Nigam & Amit K. Jaiswal, 2021. "Food Industries Wastewater Recycling for Biodiesel Production through Microalgal Remediation," Sustainability, MDPI, vol. 13(15), pages 1-17, July.
    4. Goswami, Lalit & Tejas Namboodiri, M.M. & Vinoth Kumar, R. & Pakshirajan, Kannan & Pugazhenthi, G., 2017. "Biodiesel production potential of oleaginous Rhodococcus opacus grown on biomass gasification wastewater," Renewable Energy, Elsevier, vol. 105(C), pages 400-406.
    5. Naira, Venkateswara R. & Das, Debasish & Maiti, Soumen K., 2020. "A novel bubble-driven internal mixer for improving productivities of algal biomass and biodiesel in a bubble-column photobioreactor under natural sunlight," Renewable Energy, Elsevier, vol. 157(C), pages 605-615.

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