Taxonomic Classification of Phytoplankton with Multivariate Optical Computing, Part I: Design and Theoretical Performance of Multivariate Optical Elements

@article{Swanstrom2013TaxonomicCO,
  title={Taxonomic Classification of Phytoplankton with Multivariate Optical Computing, Part I: Design and Theoretical Performance of Multivariate Optical Elements},
  author={Joseph A. Swanstrom and L. Bruckman and Megan Pearl and M. Simcock and K. Donaldson and T. Richardson and T. Shaw and M. Myrick},
  journal={Applied Spectroscopy},
  year={2013},
  volume={67},
  pages={620 - 629}
}
Phytoplankton are single-celled, photosynthetic algae and cyanobacteria found in all aquatic environments. Differential pigmentation between phytoplankton taxa allows use of fluorescence excitation spectroscopy for discrimination and classification. For this work, we applied multivariate optical computing (MOC) to emulate linear discriminant vectors of phytoplankton fluorescence excitation spectra by using a simple filter-fluorometer arrangement. We grew nutrient-replete cultures of three… Expand
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Taxonomic Classification of Phytoplankton with Multivariate Optical Computing, Part III: Demonstration
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