A fluorometric method for the discrimination of harmful algal bloom species developed by wavelet analysis

Abstract

An in vivo 3D fluorescence discrimination technique for ten harmful algal bloom (HAB) species that belong to eight genera of four divisions was developed by wavelet analysis. Daubechies-7 (db7) was employed as the mother wavelet. The fifth scale domains were selected as the discriminant characteristic spectra (DCS). Based on the DCS, The phytoplankton species at different growth stages were classified correctly at both the division and the genus level by Bayesian discriminant analysis (BDA). Based on the reference spectra of the DCS, the discrimination method of the phytoplankton species was established by the nonnegative least squares (NNLS) method. The correct discrimination ratios (CDRs) for samples of the single species were 96.1% with 0% blank noise and 93.3% with 10% noise at the genus level, while the CDRs were both 100% with 0% or 10% blank noise at the division level. When blank noise was up to 20%, the CDRs were down to 85.2% at the genus level and 98.0% at the division level. For the mixture samples, the CDRs of the dominant species were 98.3% and 96.3%, respectively, at the division level and at the genus level. As dominant species, Prorocentrum minimum ( Pm), Gymnodinium simplex ( Gs), Scrippsiella trochoidea ( Sc), Skeletonema costatuma ( Sk), Chaetoceros ( Cu and De), Phaeocystis globosa ( Cg) and Chlorella pynnoidosa ( Ch) can be correctly discriminated at both the division level and the genus level.