Abstract
Accurate measurement of the biomass and size distribution of picoplankton cells (0.2 to 2.0 microns) is paramount in characterizing their contribution to the oceanic food web and global biogeochemical cycling. Image-analyzed fluorescence microscopy, usually based on video camera technology, allows detailed measurements of individual cells to be taken. The application of an imaging system employing a cooled, slow-scan charge-coupled device (CCD) camera to automated counting and sizing of individual picoplankton cells from natural marine samples is described. A slow-scan CCD-based camera was compared to a video camera and was superior for detecting and sizing very small, dim particles such as fluorochrome-stained bacteria. Several edge detection methods for accurately measuring picoplankton cells were evaluated. Standard fluorescent microspheres and a Sargasso Sea surface water picoplankton population were used in the evaluation. Global thresholding was inappropriate for these samples. Methods used previously in image analysis of nanoplankton cells (2 to 20 microns) also did not work well with the smaller picoplankton cells. A method combining an edge detector and an adaptive edge strength operator worked best for rapidly generating accurate cell sizes. A complete sample analysis of more than 1,000 cells averages about 50 min and yields size, shape, and fluorescence data for each cell. With this system, the entire size range of picoplankton can be counted and measured.
Full text
PDF
Images in this article
Selected References
These references are in PubMed. This may not be the complete list of references from this article.
- Bjørnsen P. K. Automatic determination of bacterioplankton biomass by image analysis. Appl Environ Microbiol. 1986 Jun;51(6):1199–1204. doi: 10.1128/aem.51.6.1199-1204.1986. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Hiraoka Y., Sedat J. W., Agard D. A. The use of a charge-coupled device for quantitative optical microscopy of biological structures. Science. 1987 Oct 2;238(4823):36–41. doi: 10.1126/science.3116667. [DOI] [PubMed] [Google Scholar]
- Hobbie J. E., Daley R. J., Jasper S. Use of nuclepore filters for counting bacteria by fluorescence microscopy. Appl Environ Microbiol. 1977 May;33(5):1225–1228. doi: 10.1128/aem.33.5.1225-1228.1977. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Marr D., Hildreth E. Theory of edge detection. Proc R Soc Lond B Biol Sci. 1980 Feb 29;207(1167):187–217. doi: 10.1098/rspb.1980.0020. [DOI] [PubMed] [Google Scholar]
- Robertson B. R., Button D. K. Characterizing aquatic bacteria according to population, cell size, and apparent DNA content by flow cytometry. Cytometry. 1989 Jan;10(1):70–76. doi: 10.1002/cyto.990100112. [DOI] [PubMed] [Google Scholar]
- Sieracki M. E., Johnson P. W., Sieburth J. M. Detection, enumeration, and sizing of planktonic bacteria by image-analyzed epifluorescence microscopy. Appl Environ Microbiol. 1985 Apr;49(4):799–810. doi: 10.1128/aem.49.4.799-810.1985. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sieracki M. E., Reichenbach S. E., Webb K. L. Evaluation of automated threshold selection methods for accurately sizing microscopic fluorescent cells by image analysis. Appl Environ Microbiol. 1989 Nov;55(11):2762–2772. doi: 10.1128/aem.55.11.2762-2772.1989. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sieracki M. E., Viles C. L., Webb K. L. Algorithm to estimate cell biovolume using image analyzed microscopy. Cytometry. 1989 Sep;10(5):551–557. doi: 10.1002/cyto.990100510. [DOI] [PubMed] [Google Scholar]
- Young I. T. Sampling density and quantitative microscopy. Anal Quant Cytol Histol. 1988 Aug;10(4):269–275. [PubMed] [Google Scholar]