Back to results

University of South Carolina

System Design, Construction, Implementation, and Validation For Rapid Single-Cell Classification Using Imaging Multivariate Optical Computing

Abstract

dc:description.abstract

<p>Phytoplankton biomass is highly variable over space and time. The development of sensors for the in situ discrimination of phytoplankton size and community composition is necessary to better understand the oceanic carbon cycle. Our research focuses on developing instrumentation to classify single-cell phytoplankton cells in situ. Excitation spectra are collected using a single-cell optical trapping instrument built in house. Linear discriminant analysis (LDA) has been used to classify individual phytoplankton cells based on the fluorescence excitation spectra for individual cells in the wavelength range 350-650 nm. Interference filters called multivariate optical elements (MOEs), are fabricated based on the linear discriminant analysis results of the single-cell spectra. The transmission spectrum of each MOE mimics the performance of one linear discriminant function required for classification of a phytoplankton species. Target cells are excited with a light source filtered through a spinning series of MOEs that is incorporated into an imaging multivariate optical computing (IMOC) system. IMOC uses fluorescence excitation spectral information combined with optical discriminant analysis to identify different phytoplankton taxa. The fluorescence response of the target cells produces a classifying ''bar code' in a camera image. A set of MOEs has been fabricated that successfully classifies the three different phytoplankton species, six different phytoplankton species, and a set that indicates nitrogen status of phytoplankton species. The optical system used for experimental confirmation of the modeling will be illustrated and the classification of the phytoplankton cells will be shown.</p>

Degree

thesis:*
Name thesis:degree_name
Ph.D.
Level thesis:degree_level
Campus Access Dissertation
Discipline thesis:degree_discipline
Chemistry and Biochemistry
Year
2011

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Hill, Laura Sabra
Contributors dc:contributor
  • Michael L Myrick

Subjects

dc:subject × 2

Rights

dc:rights
Statement dc:rights
  • © 2011, Laura Sabra Hill

Identifiers

dc:identifier.*
Repository record dc:identifier
https://scholarcommons.sc.edu/etd/687
OAI identifier oai:identifier
oai:scholarcommons.sc.edu:etd-1688

Chain of custody

source
Harvested from
University of South Carolina
Base URL
scholarcommons.sc.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Hill, Laura Sabra. System Design, Construction, Implementation, and Validation For Rapid Single-Cell Classification Using Imaging Multivariate Optical Computing. Campus Access Dissertation thesis, 2011. https://scholarcommons.sc.edu/etd/687