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Open Access research with a European policy impact...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the European Policies Research Centre (EPRC).

EPRC is a leading institute in Europe for comparative research on public policy, with a particular focus on regional development policies. Spanning 30 European countries, EPRC research programmes have a strong emphasis on applied research and knowledge exchange, including the provision of policy advice to EU institutions and national and sub-national government authorities throughout Europe.

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Cell identification and sizing using digital image analysis for estimation of cell biomass in High Rate Algal Ponds

Gray, A.J. and Young, D. and Martin, N.J. and Glasbey, C.A. (2002) Cell identification and sizing using digital image analysis for estimation of cell biomass in High Rate Algal Ponds. Journal of Applied Phycology, 14 (3). pp. 193-204. ISSN 0921-8971

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Abstract

Current environmental concerns make estimation of microbial biomass apriority for monitoring purposes and to advance scientific understanding. Thispaper considers problems associated with algal cell imaging and measurement forcell biomass estimation in samples from high rate algal ponds. In a complexsystem, the only way of measuring microbial activity is to measure theindividual cells and estimate biovolumes. Accurate biomass determinationsdemanddirect microscopic counting and measurement of the sizes of individualmicrobialcells taken from known volumes of water. The system used for routinemeasurementat the laboratory where the images were generated, based on standard microscopeequipment, is only suitable for treatment of well dispersed specimens.Differential interference contrast (DIC) microscopy, on the other hand, offersthe best solution for optical enhancement of cell contrast, and produces animage with well defined edges, yet presents a great challenge to routine cellidentification by digital image analysis, owing to the bas-relief type imageproduced. The paper outlines several image analysis methods developedspecifically for this purpose, and presents illustrative results.