Taxonomic Classification of Phytoplankton with Multivariate Optical Computing, Part III: Demonstration

Author:

Pearl Megan R.1,Swanstrom Joseph A.1,Bruckman Laura S.1,Richardson Tammi L.2,Shaw Timothy J.1,Sosik Heidi M.3,Myrick Michael L.1

Affiliation:

1. Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC 29208 USA

2. Department of Biological Sciences, University of South Carolina, Columbia, SC 29208 USA

3. Department of Biology, Woods Hole Oceanographic Institution, Woods Hole, MA 02543 USA

Abstract

We describe the automatic analysis of fluorescence tracks of phytoplankton recorded with a fluorescence imaging photometer. The optical components and construction of the photometer were described in Part I and Part II of this series in this issue. An algorithm first isolates tracks corresponding to a single phytoplankter transit in the nominal focal plane of a flow cell. Then, the fluorescence streaks in the track that correspond to individual optical elements on the filter wheel are identified. The fluorescence intensity of each streak is integrated and used to calculate ratios. This approach was tested using 853 fluorescence measurements of the coccolithophore Emiliania huxleyi and the diatom Thalassiosira pseudonana. Average intensity ratios for the two classes closely follow those predicted in Part I of this series, with a distribution of ratios in each class that is consistent with the signal-to-noise ratio calculations in Part II for single cells. No overlap of the two class ratios was observed, yielding perfect classification.

Publisher

SAGE Publications

Subject

Spectroscopy,Instrumentation

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