Optimization of lipid production for algal biodiesel in nitrogen stressed cells of Dunaliella salina using FTIR analysis
Abstract
Background: Large improvements in productivity are required to make massive scale biodiesel production from microalgae an economic reality. Although the maximum neutral lipid content of microalgae has received much attention as a target for optimization, there are other factors that are equally important. These are (1) the rates of accumulation of both biomass and lipids and (2) the maximum densities of algal cells that can be sustained in continuous cultivation. The combined effect of these factors for lipid production has not been thoroughly examined in Dunaliella species. Hence this study examines the rates of growth and lipid accumulation in Dunaliella salina using Fourier transform infrared spectroscopy (FTIR) under several combinations of temperatures and cell densities. Results: The FTIR signal at 2926 cm−1 (rather than 1740 cm−1) is better for measuring lipids and the PCA of the full spectrum showed a clear separation between the nitrogen replete and nitrogen depleted cells. As expected, cells subjected to nitrogen starvation (N‐depleted) showed very little growth compared to the N‐replete cells. N‐depleted cells achieved a final lipid content that was 78% more than the N‐replete samples at 26 °C, while the differential for 16 °C was 28%. However, the slower growth rates caused by the stress of nitrogen starvation meant that the total lipid production over the starvation period was lower for many samples. Indeed, the only stress condition that gave significantly higher total lipid production was the highest cell density studied at 26 °C. Conclusion: For optimization of lipid productivity for biodiesel, the trade‐off between lipid content, growth rate and cell density needs to be considered. © 2013 Society of Chemical Industry
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These off-line studies reveal the potential versatility of on-line/in-line MIR monitoring.
“These off-line studies reveal the potential versatility of on-line/in-line MIR monitoring [56].”
From Microalgal process-monitoring based on high-selectivity spectroscopy tools: status and future perspectives (2018) · cites this paper as [56]
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- Authors
- Liu, J., Mukherjee, J., Hawkes, J. J., & Wilkinson, S. J.
- Affiliations
- University of Sheffield (GB)
- University of Hong Kong (HK)
- University of Manchester (GB)
- Corresponding author
- Wilkinson, Stephen J.
- Venue
- Journal of Chemical Technology & Biotechnology
- Publisher
- Wiley
- Published
- 2013-02-25
- Volume
- 88
- Issue
- 10
- Pages
- 1807-1814
- ISSN
- 0142-0356 (ISSN-L)
- 0268-2575
- 1097-4660
- OpenAlex
- W1572390516
- Cited by
- 77
- References
- 20
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 8 · 2023: 3 · 2022: 8 · 2021: 5 · 2020: 3 · 2019: 4 · 2018: 6 · 2017: 6 · 2016: 7 · 2015: 11 · 2014: 6 · 2013: 1
- FWCI
- 3.03
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Chemical Technology & Biotechnology (publishedVersion)
- Funders
- China Scholarship Council
- Topics
- 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
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biochemistry › Lipid metabolism and biosynthesis
- Keywords
- Dunaliella salina, microalgae biodiesel, lipid accumulation, nitrogen starvation, nitrogen deficiency, growth rate, cell density, temperature effects, microalgae cultivation
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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