Optimising Multispectral Active Fluorescence to Distinguish the Photosynthetic Variability of Cyanobacteria and Algae
This study assesses the ability of a new active fluorometer, the LabSTAF, to diagnostically assess the physiology of freshwater cyanobacteria in a reservoir exhibiting annual blooms. Specifically, we analyse the correlation of relative cyanobacteria abundance with photosynthetic parameters derived f...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/1/461 |
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| author | Emilie Courtecuisse Elias Marchetti Kevin Oxborough Peter D. Hunter Evangelos Spyrakos Gavin H. Tilstone Stefan G. H. Simis |
| author_facet | Emilie Courtecuisse Elias Marchetti Kevin Oxborough Peter D. Hunter Evangelos Spyrakos Gavin H. Tilstone Stefan G. H. Simis |
| author_sort | Emilie Courtecuisse |
| collection | DOAJ |
| description | This study assesses the ability of a new active fluorometer, the LabSTAF, to diagnostically assess the physiology of freshwater cyanobacteria in a reservoir exhibiting annual blooms. Specifically, we analyse the correlation of relative cyanobacteria abundance with photosynthetic parameters derived from fluorescence light curves (FLCs) obtained using several combinations of excitation wavebands, photosystem II (PSII) excitation spectra and the emission ratio of 730 over 685 nm (F<sub>o</sub>(730/685)) using excitation protocols with varying degrees of sensitivity to cyanobacteria and algae. FLCs using blue excitation (B) and green–orange–red (GOR) excitation wavebands capture physiology parameters of algae and cyanobacteria, respectively. The green–orange (GO) protocol, expected to have the best diagnostic properties for cyanobacteria, did not guarantee PSII saturation. PSII excitation spectra showed distinct response from cyanobacteria and algae, depending on spectral optimisation of the light dose. F<sub>o</sub>(730/685), obtained using a combination of GOR excitation wavebands, F<sub>o</sub>(GOR, 730/685), showed a significant correlation with the relative abundance of cyanobacteria (linear regression, <i>p</i>-value < 0.01, adjusted R<sup>2</sup> = 0.42). We recommend using, in parallel, F<sub>o</sub>(GOR, 730/685), PSII excitation spectra (appropriately optimised for cyanobacteria versus algae), and physiological parameters derived from the FLCs obtained with GOR and B protocols to assess the physiology of cyanobacteria and to ultimately predict their growth. Higher intensity LEDs (G and O) should be considered to reach PSII saturation to further increase diagnostic sensitivity to the cyanobacteria component of the community. |
| first_indexed | 2024-03-09T09:40:50Z |
| format | Article |
| id | doaj.art-8b596195a2594f0185f32dc2b119f477 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T09:40:50Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-8b596195a2594f0185f32dc2b119f4772023-12-02T00:57:15ZengMDPI AGSensors1424-82202023-01-0123146110.3390/s23010461Optimising Multispectral Active Fluorescence to Distinguish the Photosynthetic Variability of Cyanobacteria and AlgaeEmilie Courtecuisse0Elias Marchetti1Kevin Oxborough2Peter D. Hunter3Evangelos Spyrakos4Gavin H. Tilstone5Stefan G. H. Simis6Plymouth Marine Laboratory, Prospect Place, Plymouth PL1 3DH, UKSchool of Biological and Marine Sciences, University of Plymouth, Plymouth PL4 8AA, UKChelsea Technologies Ltd., 55 Central Avenue West Molesey, Surrey KT8 2QZ, UKFaculty of Natural Sciences, University of Stirling, Stirling FK9 4LA, UKFaculty of Natural Sciences, University of Stirling, Stirling FK9 4LA, UKPlymouth Marine Laboratory, Prospect Place, Plymouth PL1 3DH, UKPlymouth Marine Laboratory, Prospect Place, Plymouth PL1 3DH, UKThis study assesses the ability of a new active fluorometer, the LabSTAF, to diagnostically assess the physiology of freshwater cyanobacteria in a reservoir exhibiting annual blooms. Specifically, we analyse the correlation of relative cyanobacteria abundance with photosynthetic parameters derived from fluorescence light curves (FLCs) obtained using several combinations of excitation wavebands, photosystem II (PSII) excitation spectra and the emission ratio of 730 over 685 nm (F<sub>o</sub>(730/685)) using excitation protocols with varying degrees of sensitivity to cyanobacteria and algae. FLCs using blue excitation (B) and green–orange–red (GOR) excitation wavebands capture physiology parameters of algae and cyanobacteria, respectively. The green–orange (GO) protocol, expected to have the best diagnostic properties for cyanobacteria, did not guarantee PSII saturation. PSII excitation spectra showed distinct response from cyanobacteria and algae, depending on spectral optimisation of the light dose. F<sub>o</sub>(730/685), obtained using a combination of GOR excitation wavebands, F<sub>o</sub>(GOR, 730/685), showed a significant correlation with the relative abundance of cyanobacteria (linear regression, <i>p</i>-value < 0.01, adjusted R<sup>2</sup> = 0.42). We recommend using, in parallel, F<sub>o</sub>(GOR, 730/685), PSII excitation spectra (appropriately optimised for cyanobacteria versus algae), and physiological parameters derived from the FLCs obtained with GOR and B protocols to assess the physiology of cyanobacteria and to ultimately predict their growth. Higher intensity LEDs (G and O) should be considered to reach PSII saturation to further increase diagnostic sensitivity to the cyanobacteria component of the community.https://www.mdpi.com/1424-8220/23/1/461active fluorescencemultispectralphytoplanktoncyanobacteriaalgaepopulation dynamics |
| spellingShingle | Emilie Courtecuisse Elias Marchetti Kevin Oxborough Peter D. Hunter Evangelos Spyrakos Gavin H. Tilstone Stefan G. H. Simis Optimising Multispectral Active Fluorescence to Distinguish the Photosynthetic Variability of Cyanobacteria and Algae Sensors active fluorescence multispectral phytoplankton cyanobacteria algae population dynamics |
| title | Optimising Multispectral Active Fluorescence to Distinguish the Photosynthetic Variability of Cyanobacteria and Algae |
| title_full | Optimising Multispectral Active Fluorescence to Distinguish the Photosynthetic Variability of Cyanobacteria and Algae |
| title_fullStr | Optimising Multispectral Active Fluorescence to Distinguish the Photosynthetic Variability of Cyanobacteria and Algae |
| title_full_unstemmed | Optimising Multispectral Active Fluorescence to Distinguish the Photosynthetic Variability of Cyanobacteria and Algae |
| title_short | Optimising Multispectral Active Fluorescence to Distinguish the Photosynthetic Variability of Cyanobacteria and Algae |
| title_sort | optimising multispectral active fluorescence to distinguish the photosynthetic variability of cyanobacteria and algae |
| topic | active fluorescence multispectral phytoplankton cyanobacteria algae population dynamics |
| url | https://www.mdpi.com/1424-8220/23/1/461 |
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