OPTICAL PROPERTIES OF DENSE ALGAL CULTURES OUTDOORS AND THEIR APPLICATION TO REMOTE ESTIMATION OF BIOMASS AND PIGMENT CONCENTRATION IN SPIRULINA PLATENSIS (CYANOBACTERIA)1
Abstract
ABSTRACT Reflectance and vertical attenuation coefficient spectra from 400 to 1100 nm were investigated in detail on dense algal cultures of Spirulina in order to create algorithms for remote estimation of pigment and biomass concentration. Reflectance and the vertical attenuation coefficients were compared with biomass and pigment concentration in outdoor algal cultures. For assessing biomass concentration, the sum of reflectance above the base line from 670 to 950 nm was used. This allows the estimation of biomass with an error of less than 0.06 g·L−1 For chlorophyll a and phycocyanin estimation, vertical attenuation coefficients at the wavelengths 440 nm (or 676 nm) and 624 nm, respectively, were employed. The developed algorithms were tested by using independent data sets in the range of chlorophyll a from 0.2 to 20mg·L−1 and biomass from 0.15 to 1.1 g·L−1. An error of pigment estimation of less than 0.80 mg·L−1 was achieved. The potential use of the algorithms in algal biotechnology is further discussed.
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A large body of measured optical properties is available for several species.
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Cites
Chemistry and biochemistry of plant pigments
Goodwin, T. W. (1976) · Medical Entomology and Zoology · Cited by 3,081 · see citing works
Remote Assessment of Ocean Color for Interpretation of Satellite Visible Imagery
Gordon, H. R., & Morel, A. (1983) · Lecture notes on coastal and estuarine studies · doi:10.1029/ln004 · Cited by 1,143 · see citing works
Gitelson, A. A. (1992) · International Journal of Remote Sensing · doi:10.1080/01431169208904125 · Cited by 637 · see citing works
Self-citationIntroduction to the Physics and Techniques of Remote Sensing
Elachi, C., & van Zyl, J. (2021) · Wiley eBooks · doi:10.1002/9781119523048 · Cited by 577 · see citing works
Detection of optical water quality parameters for eutrophic waters by high resolution remote sensing
Dekker, A. G. (1993) · Digital Academic REpository of VU University Amsterdam (Vrije Universiteit Amsterdam) · Cited by 366 · see citing works
Quantitative remote sensing methods for real-time monitoring of inland waters quality
Gitelson, A. A., Garbuzov, G. P., Szilágyi, F., et al. (1993) · International Journal of Remote Sensing · doi:10.1080/01431169308953956 · Cited by 281 · see citing works
Self-citationProduction of spirulina biomass: Effects of environmental factors and population density
Vonshak, A., Abeliovich, A., Boussiba, S., Arad, S. M., & RICHMOND, A. E. (1982) · Biomass · doi:10.1016/0144-4565(82)90028-2 · Cited by 237 · see citing works
Self-citationRundquist, D. C., Han, L., Schalles, J. F., et al. (1996) · Photogrammetric Engineering & Remote Sensing · Cited by 156 · see citing works
Remote Sensing of Coastal Wetlands
Hardisky, M. A., Gross, M. F., & Klemas, V. (1986) · BioScience · doi:10.2307/1310341 · Cited by 119 · see citing works
The effect of spectral bandwidth and positioning on the spectral signature analysis of inland waters
Decker, A. G., Malthus, T., Wijnen, M. M., et al. (1992) · Remote Sensing of Environment · doi:10.1016/0034-4257(92)90079-y · Cited by 79 · see citing works
Gitelson, A. A., Mayo, M., Yacobi, Y. Z., et al. (1994) · Journal of Plankton Research · doi:10.1093/plankt/16.8.993 · Cited by 60 · see citing works
Self-citationHIGH‐RESOLUTION AIRBORNE REMOTE SENSING OF BLOOM‐FORMING PHYTOPLANKTON1
Millie, D. F., Baker, M. C., Tucker, C. S., et al. (1992) · Journal of Phycology · doi:10.1111/j.0022-3646.1992.00281.x · Cited by 51 · see citing works
QUIBELL, G. (1992) · International Journal of Remote Sensing · doi:10.1080/01431169208904067 · Cited by 44 · see citing works
Improving quantitative remote sensing for monitoring of inland water quality
Gitelson, A. A., Szilágyi, F., & Mittenzwey, K. ‐. (1993) · Water Research · doi:10.1016/0043-1354(93)90010-f · Cited by 38 · see citing works
Self-citationPicocyanobacteria and Bacteria in Lake Kinneret
Malinsky‐Rushanksy, N., & Berman, T. (1991) · Internationale Revue der gesamten Hydrobiologie und Hydrographie · doi:10.1002/iroh.19910760408 · Cited by 35 · see citing works
Rundquist, D. C., Schalles, J. F., & Peake, J. S. (1995) · Geocarto International · doi:10.1080/10106049509354508 · Cited by 34 · see citing works
Chlorophyll-a estimation in New Jersey's coastal waters using Thematic Mapper data
Bagheri, S., & Dios, R. (1990) · International Journal of Remote Sensing · doi:10.1080/01431169008955020 · Cited by 28 · see citing works
Algorithms for remote sensing of phytoplankton pigments in inland waters
Gitelson, A. A. (1993) · Advances in Space Research · doi:10.1016/0273-1177(93)90545-m · Cited by 25 · see citing works
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Lim, H. R., Khoo, K. S., Chia, W. Y., Chew, K. W., Ho, S.-H., & Show, P. L. (2022) · Biotechnology Advances · doi:10.1016/j.biotechadv.2022.107931 · Cited by 155 · see citing works
Danesi, E. D. G., Rangel-Yagui, C. O., Sato, S., & Carvalho, J. C. M. D. (2011) · Brazilian Journal of Microbiology · doi:10.1590/s1517-83822011000100046 · Cited by 67 · see citing works
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- Authors
- Gitelson, A. A., Laorawat, S., Keydan, G. P., & Vonshak, A.
- Affiliations
- Ben-Gurion University of the Negev (IL)
- Venue
- Journal of Phycology
- Publisher
- Wiley
- Published
- 1995-10
- Volume
- 31
- Issue
- 5
- Pages
- 828-834
- ISSN
- 0022-3646 (ISSN-L)
- 1529-8817
- OpenAlex
- W2047115360
- Cited by
- 46
- References
- 18
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 1 · 2022: 4 · 2021: 1 · 2017: 2 · 2015: 1 · 2014: 5 · 2013: 2 · 2012: 5
- FWCI
- 1.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Phycology (publishedVersion)
- Topics
- Physical Sciences › Earth and Planetary Sciences › Oceanography › Marine and coastal ecosystems
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Algal biology and biofuel production
- Physical Sciences › Environmental Science › Environmental Chemistry › Aquatic Ecosystems and Phytoplankton Dynamics
- Keywords
- Spirulina platensis, optical properties, spectral reflectance, vertical attenuation coefficient, chlorophyll a, phycocyanin, biomass estimation, pigment content, remote sensing algorithms, cyanobacteria
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