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Detecting phycocyanin pigments with dynamic imaging particle analysis

The 9th annual National Monitoring Conference is being held this week in Cincinnati, Ohio at the Duke Energy Center. We're an exhibitor at this show and our own Brandon Rieff will be there manning the booth and chatting with fellow water-quality monitoring professionals. He'll also be doing a poster session where he will present an overview of a phycocyanin-detecting dynamic imaging particle analysis technology currently in development and review its effectiveness using cyanobacteria cultures and surface water samples from a public water supply.

Cyanobacteria imaged with FlowCam

Numerous technologies make use of fluorescence measurements to detect and estimate cyanobacteria biovolume in water samples. While useful, results from these instruments can be significantly skewed by turbidity and the presence of other fluorescing pigments and particles.

Fluid Imaging Technologies is exploring ways the FlowCAM particle analyzer can detect the phycocyanin pigment in cyanobacteria with the use of an appropriate laser and optical filters. A test model can distinguish cyanobacteria from other organisms, relying on pigment detection in addition to image-based morphological analysis.


A laser centered on 630nm was selected to match the natural excitation wavelength of the phycocyanin accessory pigment. To isolate the emission from phycocyanin, two discrete detection filters were chosen for the PMT (photomultipler tubes). One with an emission of 655nm and one with a 700nm wavelength emission. Both were chosen based on peer reviewed literature. The instrument is triggered to take a picture when algae containing phycocyanin are detected.

1.) Detect & Capture: The laser in the test instrument is directed through a beam shaping filter to create a laser “trip” line. When the algae cross the laser line, and if it contains phycocyanin, the detection filters have picked up the fluorescence and tell the camera to take an image.

2.) Tag & Sort: The images taken from the triggering event are uniquely tagged with the fluorescence data from each detection filter. Whether the algae triggered the system on Channel 1 (655) or Channel 2 (700) or both, this information will be available in the post-processing software.

3.) Using the Data: Using both the data from the fluorescence detection and standard image parameters, along with the software’s pattern recognition capabilities it is possible to separate images into like types and provide community composition estimates. The software will also provide concentrations, counts, biovolume estimates and size distribution information among other data.


The FlowCAM for cyanobacteria would support multiple applications including;

  • academic research
  • reservoir monitoring
  • municipal water
  • laboratory research

We would like to thank the scientists at the University of Toronto for their ideas, guidance and assistance in the development and testing of this new technology.



Watch this short video to see how the FlowCAM works.



Topics: News and Events, FlowCam Technology, Aquatic Research