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

Volume 67, Number 6 (June 2013) Page 640-647

MEGAN R. PEARL, JOSEPH A. SWANSTROM, LAURA S. BRUCKMAN, TAMMI L. RICHARDSON, TIMOTHY J. SHAW, HEIDI M. SOSIK, and MICHAEL L. MYRICK*


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.



Index Headings: Phytoplankton; Fluorescence; Multivariate optical computing; Photometer; Classification.