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.