KNAW Repository

Functional analysis and classification of phytoplankton based on data from an automated flow cytometer

Malkassian, A. and Nerini, D. and Van Dijk, M.A. and Thyssen, M. and Mante, C. and Gregori, G. (2011) Functional analysis and classification of phytoplankton based on data from an automated flow cytometer. Cytometry Part A, 79A, 263-275. ISSN 1552-4922.

[img]PDF - Published Version
Restricted to KNAW only

1745Kb

Official URL: http://dx.doi.org/10.1002/cyto.a.21035

Abstract

Analytical flow cytometry (FCM) is well suited for the analysis of phytoplankton communities in fresh and sea waters. The measurement of light scatter and autofluorescence properties of particles by FCM provides optical fingerprints, which enables different phytoplankton groups to be separated. A submersible version of the CytoSense flow cytometer (the CytoSub) has been designed for in situ autonomous sampling and analysis, making it possible to monitor phytoplankton at a short temporal scale and obtain accurate information about its dynamics. For data analysis, a manual clustering is usually performed a posteriori: data are displayed on histograms and scatterplots, and group discrimination is made by drawing and combining regions (gating). The purpose of this study is to provide greater objectivity in the data analysis by applying a nonmanual and consistent method to automatically discriminate clusters of particles. In other words, we seek for partitioning methods based on the optical fingerprints of each particle. As the CytoSense is able to record the full pulse shape for each variable, it quickly generates a large and complex dataset to analyze. The shape, length, and area of each curve were chosen as descriptors for the analysis. To test the developed method, numerical experiments were performed on simulated curves. Then, the method was applied and validated on phytoplankton cultures data. Promising results have been obtained with a mixture of various species whose optical fingerprints overlapped considerably and could not be accurately separated using manual gating. © 2011 International Society for Advancement of Cytometry.

Item Type:Article
Institutes:Nederlands Instituut voor Ecologie (NIOO)
ID Code:8860
Deposited On:28 Jun 2011 02:00
Last Modified:24 Apr 2012 16:42

Repository Staff Only: item control page