Spectral Characterization of Eight Marine Phytoplankton Phyla and Assessing a Pigment-Based Taxonomic Discriminant Analysis for the in Situ Classification of Phytoplankton Blooms.

Autor: Zieger SE; Optical Sensors Group, Institute of Analytical Chemistry and Food Chemistry , Graz University of Technology , Graz , Austria., Seoane S; Plant biology and Ecology Department, Faculty of Science and Technology , University of the Basque Country (UPV/EHU) , Leioa 48940 , Spain., Laza-Martínez A; Plant biology and Ecology Department, Faculty of Science and Technology , University of the Basque Country (UPV/EHU) , Leioa 48940 , Spain., Knaus A; Optical Sensors Group, Institute of Analytical Chemistry and Food Chemistry , Graz University of Technology , Graz , Austria., Mistlberger G; Optical Sensors Group, Institute of Analytical Chemistry and Food Chemistry , Graz University of Technology , Graz , Austria., Klimant I; Optical Sensors Group, Institute of Analytical Chemistry and Food Chemistry , Graz University of Technology , Graz , Austria.
Jazyk: angličtina
Zdroj: Environmental science & technology [Environ Sci Technol] 2018 Dec 18; Vol. 52 (24), pp. 14266-14274. Date of Electronic Publication: 2018 Nov 30.
DOI: 10.1021/acs.est.8b04528
Abstrakt: Early stage identification of harmful algal blooms (HABs) has gained significance for marine monitoring systems over the years. Various approaches for in situ classification have been developed. Among them, pigment-based taxonomic classification is one promising technique for in situ characterization of bloom compositions, although it is yet underutilized in marine monitoring programs. To demonstrate the applicability and importance of this powerful approach for monitoring programs, we combined an ultra low-cost and miniaturized multichannel fluorometer with Fisher's linear discriminant analysis (LDA). This enables the real-time characterization of algal blooms at order level based on their spectral properties. The classification capability of the algorithm was examined with a leave-one-out cross validation of 53 different unialgal cultures conducted in terms of standard statistical measures and independent figures of merit. The separation capability of the linear discriminant analysis was further successfully examined in mixed algal suspensions. Besides this, the impact of the growing status on the classification capability was assessed. Further, we provide a comprehensive study of spectral features of eight different phytoplankton phyla including an extensive study of fluorescence excitation spectra and marker pigments analyzed via HPLC. The analyzed phytoplankton species belong to the phyla of Cyanobacteria, Dinophyta (Dinoflagellates), Bacillariophyta (Diatoms), Haptophyta, Chlorophyta, Ochrophyta, Cryptophyta, and Euglenophyta.
Databáze: MEDLINE