IDENTIFYING PHYTOPLANKTON IN SEAWATER BASED ON DISCRETE EXCITATION-EMISSION FLUORESCENCE SPECTRA (original) (raw)

Fluorescence Excitation Spectroscopy for Phytoplankton Species Classification Using an All-Pairs Method: Characterization of a System with Unexpectedly Low Rank

Applied spectroscopy, 2017

An all-pairs method is used to analyze phytoplankton fluorescence excitation spectra. An initial set of nine phytoplankton species is analyzed in pairwise fashion to select two optical filter sets, and then the two filter sets are used to explore variations among a total of 31 species in a single-cell fluorescence imaging photometer. Results are presented in terms of pair analyses; we report that 411 of the 465 possible pairings of the larger group of 31 species can be distinguished using the initial nine-species-based selection of optical filters. A bootstrap analysis based on the larger data set shows that the distribution of possible pair separation results based on a randomly selected nine-species initial calibration set is strongly peaked in the 410-415 pair separation range, consistent with our experimental result. Further, the result for filter selection using all 31 species is also 411 pair separations; The set of phytoplankton fluorescence excitation spectra is intuitively ...

Delayed fluorescence excitation spectroscopy: A rapid method for qualitative and quantitative assessment of natural population of phytoplankton

Water Research, 1998

ÐNatural phytoplankton samples were analyzed by a spectrometer which is designed to measure delayed¯uorescence (DF) excitation spectra in the range from 400 to 728 nm. It was possible to detect taxonomical changes in the algal assemblage of Lake Kinneret, Israel using DF spectra as analytical signature. The ratio of spectrally integrated excitation delayed¯uorescence to chlorophyll a concentration (DF/chlorophyll) in samples collected from Lake Kinneret, Israel,¯uctuated throughout the investigation period, which covered the annual bloom of the dino¯agellate Peridinium gatunense. The DF/chl ratio increased with the initiation of Peridinium population build up, reached the highest value when the algal bloom reached its peak and declined with the decrease of algal density. DF intensity was positively correlated with the primary productivity at the depth of maximal productivity, indicating that DF intensity may be used as a rapid probe of this variable.

A Rapid Technique for Classifying Phytoplankton Fluorescence Spectra Based on Self-Organizing Maps

Applied Spectroscopy, 2009

Fluorescence spectroscopy has been demonstrated to be a powerful tool for characterizing phytoplankton communities in marine environments. Using different fluorescence spectra techniques, it is now possible to discriminate the major phytoplankton groups. However, most of the current techniques are based on fluorescence excitation measurements, which require stimulation at different wavelengths and thus considerable time to obtain the complete spectral profile. This requirement may be an important constraint for several mobile oceanographic platforms, such as vertical profilers or autonomous underwater vehicles, which require rapid-acquisition instruments. This paper presents a novel technique for classifying fluorescence spectra based on self-organizing maps (SOMs), one of the most popular artificial neural network (ANN) methods. The method is able to achieve phytoplankton discrimination using only fluorescence emission spectra (single wavelength excitation), thus reducing the acquisition time. The discrimination capabilities of SOM using excitation and emission spectra are compared. The analysis shows that the SOM has a good performance using excitation spectra, whereas data preprocessing is required in order to obtain similar discrimination capabilities using emission spectra. The final results obtained using emission spectra indicate that the discrimination is properly achieved even between algal groups, such as diatoms and dinoflagellates, which cannot be discriminated with previous methods. We finally point out that although techniques based on excitation spectra can achieve a better taxonomic accuracy, there are some applications that require faster acquisition processes. Acquiring emission spectra is almost instantaneous, and techniques such as SOM can achieve good classification performance using appropriately preprocessed data.

Improved estimates of phytoplankton community composition based on in situ spectral fluorescence: use of ordination and field-derived norm spectra for the bbe FluoroProbe

Canadian Journal of Fisheries and Aquatic Sciences, 2016

The use of spectral fluorometers for assessing phytoplankton concentrations and taxonomic composition in aquatic environments is increasingly common. However, the accuracy of such assessments suffers because the necessary norm spectra (spectral fingerprints) are derived using selected taxa and laboratory conditions that may not adequately represent the taxa and environmental conditions in the study area. Ordination analysis of raw fluorescence data has been proposed as a better means of interpreting spectral fluorescence data. We applied nonmetric multidimensional scaling and cluster analysis to raw in situ fluorescence data from Sturgeon Bay, a small, mesotrophic embayment of Georgian Bay (Lake Huron) to obtain system-specific norm spectra for the bbe FluoroProbe. The revised spectra gave improved estimates of phytoplankton taxonomy (root mean square error of 10% versus 14%) and of dissolved organic carbon and chlorophyll a concentrations. While promising, this method should be fur...

Phytoplankton identification by combined methods of morphological processing and fluorescence imaging

2015 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS) Proceedings, 2015

The identification of phytoplankton is currently an important issue to prevent the aquatic environment. The growth of one or several phytoplankton species can lead to hyper eutrophication and causes lethal consequences on other organisms. In this paper, the selective recognition of invading species is investigated by automatic recognition algorithms of optical and fluorescence imaging. Firstly, morphological characteristics of algae of microscopic imaging are treated. The image processing lead to the identification the genus of aquatic organisms and compared to a morphologic data base. Secondly, fluorescence images allow an automatic recognition based on multispectral data that identify locally the ratio of different photosynthetic pigments and gives a unique finger print of algae. It is shown that the combination of both methods are useful in the recognition of aquatic organisms.

Discrimination of marine algal taxonomic groups using delayed fluorescence spectroscopy

Environmental and Experimental Botany, 2011

We present a method for in situ monitoring of phytoplankton composition changes in a marine environment. The method is based on delayed fluorescence excitation spectra analyzed with CHEMTAX software, which is generally used for determination of phytoplankton communities with HPLC pigment data. Delayed fluorescence (DF) is a photosynthetic parameter that can only be measured in living cells. Algal DF excitation spectra are group-specific, based on their composition of photosynthetic pigments.

Analysis of Phytoplankton Pigments by Excitation Spectra of Fluorescence

2000

The advantages and problems of the application of actively excited fluorescence in natural phyto- plankton analysis are discussed. The focus is made to a correct prediction of pigment concentrations by fluorescence data. The results of high resolution mapping of chlorophylls and phycobilins in the Gotland Basin (Baltic Sea) during Cyanobacterial blooms in 1997 and 1998 are presented. Dynami- cal spatial

The use of spectral fluorescence methods to detect changes in the phytoplankton community

Eutrophication in Planktonic Ecosystems: Food Web Dynamics and Elemental Cycling, 1998

In vivo fluorescence methods are efficient tools for studying the seasonal and spatial dynamics of phytoplankton. Traditionally the measurements are made using single excitation-emission wavelength combination. During a cruise in the Gulf of Riga (Baltic Sea) we supplemented this technique by measuring the spectral fluorescence signal (SFS) and fixed wavelength fluorescence intensities at the excitation maxima of main accessory pigments. These methods allowed the rapid collection of quantitative fluorescence data and chemotaxonomic diagnostics of the phytoplankton community. The chlorophyll a-specific fluorescence intensities (R) and the spectral fluorescence fingerprints were analysed together with concentrations of chlorophyll a in different algal size-groups, phytoplankton biomass and taxonomic position. The lower level of R in the southern gulf was related to the higher proportion of cyanobacteria relative to total biomass and the lower abundance of small algae. The phycoerythrin fluorescence signal was obviously due to the large cyanobacteria. The basin-wide shift in the shape of chlorophyll a excitation spectra was caused by the variable proportions of differently pigmented cyanobacteria, diatoms and cryptomonads.

Statistical approach for the retrieval of phytoplankton community structures from in situ fluorescence measurements

Optics express, 2016

Knowledge of phytoplankton community structures is important to the understanding of various marine biogeochemical processes and ecosystem. Fluorescence excitation spectra (F(λ)) provide great potential for studying phytoplankton communities because their spectral variability depends on changes in the pigment compositions related to distinct phytoplankton groups. Commercial spectrofluorometers have been developed to analyze phytoplankton communities by measuring the field F(λ), but estimations using the default methods are not always accurate because of their strong dependence on norm spectra, which are obtained by culturing pure algae of a given group and are assumed to be constant. In this study, we proposed a novel approach for estimating the chlorophyll a (Chl a) fractions of brown algae, cyanobacteria, green algae and cryptophytes based on a data set collected in the East China Sea (ECS) and the Tsushima Strait (TS), with concurrent measurements of in vivo F(λ) and phytoplankto...