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A multivariate approach to the analysis of phytoplankton pigments
Stockholm University, Faculty of Science, Department of Analytical Chemistry.
2001 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Photosynthetic pigments are routinely determined in investigations of marine and freshwater environments, chlorophyll is used as an estimator of phytoplankton biomass. Photosynthetic pigments are also widely used to characterise phytoplankton taxonomic composition. To estimate biomass from the chlorophyll a concentration, in vitro absorption and fluorimetric spectroscopic methods are used. However, these methods are known to be prone to interference from chlorophyll degradation products. If a taxonomical characterisation is required, i.e. identification of the phytoplankton classes present in a sample, these methods are inadequate.

The objective of this thesis has been to develop qualitative and quantitative multivariate spectroscopic methods for the analysis of phytoplankton pigments. To evaluate the data in these studies, three chemometric methods have been used; principal component analysis (PCA), partial least squares regression (PLS) and parallel factor analysis (PARAFAC).

A multivariate regression model, based on the absorption spectra of standards, was developed for the determination of the six key analytes (the chlorophylls and their degradation products), the chlorophylls were accurately determined in the presence of degradation products (Paper I). This method is validated, with real samples and samples harvested from laboratory cultures. The prediction results obtained with the proposed method were in good agreement with HPLC analysis, and for the cultures the results were consistent with prior knowledge about the pigment composition (Paper II). Absorption spectra and multivariate models were used for qualitative analysis of phytoplankton cultures and samples. Nine species representing six phytoplankton classes are analysed and the results demonstrated the possibility to assess the gross phytoplankton composition (Paper III). From samples collected in the Baltic Sea during one year, it was shown that a PCA model of the spectra yielded similar results as a PCA model of microscopy counts, which outlines the possibility to monitor and screen samples (Paper IV). Fluorescence excitation emission matrices were registered for a set of laboratory prepared standards, these were decomposed with a PARAFAC model and the obtained results were used for regression analysis. The second-order advantage was exploited which suspends the requirement of measuring all interfering constituents (Paper V). Excitation emission matrices are also measured in vivo for cultures and samples. From decomposition of the data it was found that four components attributed to the variation in the data. Two components were similar to chlorophyll and carotenoids and two components to phycobilines (manuscript). 

In conclusion, the use of full spectrum techniques enhances the information acquired for phytoplankton samples, and chemometric methods have shown to be a valuable tool to extract this information.

Place, publisher, year, edition, pages
Stockholm: Department of Analytical Chemistry, Stockholm University , 2001. , 55 p.
Keyword [sv]
Växtplankton
National Category
Analytical Chemistry
Research subject
Analytical Chemistry
Identifiers
URN: urn:nbn:se:su:diva-143639ISBN: 91-7265-276-4 (print)OAI: oai:DiVA.org:su-143639DiVA: diva2:1103642
Public defence
2001-05-22, 13:00
Opponent
Note

Härtill 5 uppsatser

Available from: 2017-05-30 Created: 2017-05-30 Last updated: 2017-09-28Bibliographically approved

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