Abstract
An analytical technique allowing a distinction between cyanobacteria and other microscopic life forms that exploits autofluorescence in the deep ultraviolet has been developed. The proposed approach is based on the amplitude of relative fluorescence peaks of natural pigments or metabolites in unicellular microorganisms commonly present in the waters. The experimental results showed a clear distinction between cyanobacteria and other planktonic species. This approach has been applied to an aquaponics system receiving input water from the Drennec lake, in France, correctly detecting the presence of cyanobacteria.
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He X, Liu YL, Conklin A, Westrick J, Weavers LK, Dionysiou DD, Lenhart JJ, Mouser PJ, Szlag D, Walker HW (2016) Toxic cyanobacteria and drinking water: impacts, detection, and treatment. Harmful Algae 54:174–193
Gandola E, Antonioli M, Traficante A, Franceschini S, Scardi M, Congestri R (2016) ACQUA: automated cyanobacterial quantification algorithm for toxic filamentous genera using spline curves, pattern recognition and machine learning. J Microbiol Methods 124:48–56
Bourgeois W, Burgess JE, Stuetz RM (2001) On-line monitoring of wastewater quality: a review. J Chem Technol Biotechnol 76:337–348
Persichetti G, Testa G, Bernini R (2013) High sensitivity UV fluorescence spectroscopy based on an optofluidic jet waveguide. Opt Express 21:24219–24230
Lakowicz JR (2006) Principles of fluorescence spectroscopy. Springer, Baltimore
Billinton N, Knight AW (2001) Seeing the wood through the trees: a review of techniques for distinguishing green fluorescent protein from endogenous autofluorescence. Anal Biochem 291:175–197
Zhang D, Muller JP, Lavender S, Walton D, Dartnell LR (2012) Fluorescent analysis of photosynthetic microbes and polycyclic aromatic hydrocarbons linked to optical remote sensing. Int Arch Photogramm Remote Sens Spat Inf Sci ISPRS Arch 39:555–559. https://doi.org/10.5194/isprsarchives-xxxix-b8-555-2012
Persichetti G, Viaggiu E, Testa G, Congestri R, Bernini R (2019) Spectral discrimination of planktonic cyanobacteria and microalgae based on deep UV fluorescence. Sens Actuators B: Chem 284:228–235
Acknowledgements
This research has been partially supported by the ERA-NET Cofund WaterWorks2015 project SMARTECOPONICS, “On-Site Microbial Sensing For Minimising Environmental Risks From Aquaponics To Human Health”.
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Persichetti, G. et al. (2020). UV Autofluorescence Spectroscopy for Cyanobacteria Monitoring and Discrimination in Source Water. In: Di Francia, G., et al. Sensors and Microsystems. AISEM 2019. Lecture Notes in Electrical Engineering, vol 629. Springer, Cham. https://doi.org/10.1007/978-3-030-37558-4_37
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DOI: https://doi.org/10.1007/978-3-030-37558-4_37
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