Cited by 41Biofuel production and bioconversionAlgal biology and biofuel productionMicrobial Metabolic Engineering and Bioproduction

A Seagrass-Based Biorefinery for Generation of Single-Cell Oils for Biofuel and Oleochemical Production.

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Masri, Mahmoud A., Younes, Samer, Haack, Martina, Qoura, Farah, Mehlmer, Norbert, Brück, Thomas·2018·Energy Technology

Abstract

Abstract 78 million tons of residual seagrass deposits accumulate annually on shorelines worldwide. These represent an untapped feedstock for fermentative single‐cell oil production, targeted at biofuel and oleochemical generation, without affecting the sensitive marine environment or compromising food security. Seven beach‐cast samples of seagrass (related to Z. marina, Z. noltii, S. filiforme, P. australis, P. oceanic, and T. testudinum) were collected from marine ecosystems around the world. A combination of 18S rRNA phylogenetic, structural, and comprehensive biomass analyses of seagrass leaves were applied. The carbohydrate content ranged from 73 to 81 % (w/dwbiomass). Single‐step enzymatic hydrolysis was developed to efficiently release the monomeric sugars contained in seagrasses biomass without any pretreatment. P. oceanica hydrolysate allowed for higher lipid yields (6.8 g L−1) compared to the synthetic minimal medium (5.1 g L−1) in shake flasks, and was subsequently utilized as the sole fermentation medium for oleaginous yeast T. oleaginosus at a technical scale using a fed‐batch bioreactor, which provided 24.5 g L−1 lipids (0.35 g L−1 h−1). Moreover, the sugar/lipid conversion ratio was 0.41 (w/w). Cumulative data indicates that by exploiting only half of the global beach‐cast seagrass, approximately 4 million tons of microbial oils could be generated.

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  • Estimations of up to 40 million tons of dry seagrass biomass, which can be used for biofuel production, are given.

    “Estimations of up to 40 million tons of dry seagrass biomass, which can be used for biofuel production, are given.”

    From The potential of biofuels from first to fourth generation (2023) · cites this paper as [61]

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Research works printed but not linked: 14

  1. G. V. Subhash,S .V .Mohan, Fuel 2014, 116,5 09 -515.
  2. M. Rakicka,Z .L azar, T. Dulermo, P. Fickers,J .M.N icaud, Bio- technol. Biofuels 2015, 8,1 ;
  3. R.W ang, J. Wang, R. Xu, Z. Fang, A. Liu, BioResources 2014, 9,7 027 -7040.
  4. G .D eF alco,S .S imeone,M .B aroli, J. Coastal Res. 2008, 24,69-75.
  5. B. H. Daru, K. Yessoufou in DNAB arcodingi nM arine Perspectives, Springer, Switzerland, 2016,pp. 313 -330.
  6. Y. A. Tsigie,C .-Y.W ang, N. S. Kasim,Q .-D.D iem, L.-H. Huynh, Q.-P.H o, C.-T.T ruong, Y. -H. Ju, BioMed Res.I nt. 2012, 2012, 378384;
  7. L. Yong-Hong, L. Bo,Z .Z ong-Bao,B .F eng-Wu, Chin. J. Biotechnol. 2006, 22,6 50 -656.
  8. Energy Technol. 2018, 6, 1026-1038 2018 The .ublished -VCH . ,W einheim
  9. Z. Gong, H. Shen, X.Y ang, Q. Wang, H. Xie,Z .K.Z hao, Biotech- nol. Biofuels 2014, 7,158.
  10. Y. Zha, B. Muilwijk,L .C oulier, P. J. Punt, J. Bioprocess.B iotech. 2012, 2,1 12 -122.
  11. S. Asif,L .F .C huah, J. J. Klemes ˇ,M .A hmad, M. M. Akbar, K. T. Lee,A.F atima, J. Cleaner Prod. 2017, 161,1360 -1373.
  12. B. Díez, C. Pedrós-Alió,R .M assana, Appl. Environ. Microbiol. 2001, 67,2932 -2941.
  13. C. Kurtzman, C. Robnett, J. Clin. Microbiol. 1997, 35,1 216 -1223.
  14. J. Folch, M. Lees,G .S .S tanley, J. Biol. Chem. 1957, 226,4 97 -509.

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Authors
Masri, M. A., Younes, S., Haack, M., Qoura, F., Mehlmer, N., & Brück, T.
Affiliations
Technical University of Munich (DE)
Corresponding author
Brück, Thomas
Venue
Energy Technology
Publisher
Wiley
Published
2017-12-11
Volume
6
Issue
6
Pages
1026-1038
ISSN
  • 2194-4288 (ISSN-L)
  • 2194-4296
OpenAlex
W2757757252
Cited by
41
References
64
Citations by year
2026: 2 · 2025: 3 · 2024: 7 · 2023: 5 · 2022: 3 · 2021: 17 · 2020: 3 · 2019: 1
FWCI
0.49
Type
journal article
Language
en
Open access
Locations
Energy Technology (publishedVersion, cc-by-nc-nd)
Funders
  • German Federal Ministry of Education and Research (031A261, 03SF0446A)
  • Bavarian State Ministry for Environment and Consumer Protection (TLKO1U-69045)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Biofuel production and bioconversion
  • Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Algal biology and biofuel production
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
Keywords
seagrass, biorefinery, single cell oil, microbial lipids, oleaginous yeast, enzymatic hydrolysis, carbohydrate content, Zostera marina, Zostera noltii, Posidonia oceanica, Thalassia testudinum, biofuels, oleochemicals, 18S rRNA phylogeny

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