Determination of the filamentous cyanobacteria Planktothrix rubescens in environmental water samples using an image processing system |
| |
Authors: | Bernhard Ernst Stephan Neser Evelyn OBrien Stefan J Hoeger Daniel R Dietrich |
| |
Institution: | aEnvironmental Toxicology, University of Konstanz, P.O. Box X 918, D-78457 Konstanz, Germany;bDepartment of Mathematics and Natural Sciences, University of Applied Sciences Darmstadt, Schöfferstrasse 3, 64295 Darmstadt, Germany |
| |
Abstract: | Cyanobacteria occur in surface waters worldwide. Many of these produce peptides and/or alkaloids, which can present a risk for animal and human health. Effective risk assessment and management requires continuous and precise observation and quantification of cyanobacterial cell densities. In this respect, quantification of filamentous Planktothrix species is problematic. The aim of this study was to develop an automated system to count filamentous Planktothrix rubescens using image processing. Furthermore, this study aimed to assess optimum sample volumes and filament density for measurement precision and to validate image processing measurement of P. rubescens for an effective risk assessment.Three environmental samples and one cultured sample of P. rubescens were collected by filtration onto nitrocellulose filters. Filament lengths were determined using fluorescence microscopy combined with an image processor. Cell density could be calculated from the resulting images. Cyanobacteria could easily be discriminated from algae via their fluorescence properties. The results were found to be independent of the mode of image acquisition. The precision of total filament length determination was dependent on the total filament length on the filter, i.e. analyses of highest precision could be expected for filters containing 2000–20,000 μm filaments per mm2. When using suitable filtration volumes, the detection limits of the described method are sufficient for an effective risk assessment. To summarise, this procedure is a fast, easy and accurate method to determine cell densities of filamentous P. rubescens in water samples without costly and tedious manual handling. |
| |
Keywords: | Cyanobacteria Filament Image processing Planktothrix Cell quantification Risk assessment |
本文献已被 ScienceDirect 等数据库收录! |
|