Pollen goes with the flow
During the spring, the presence of pollen on the surface of lakes changes the surface color observed by satellites and is an important indication of the ecological cycles of a region. For instance paleopalynologic evidence of forest pollen across North America is the best way to analyze the effects of past climate changes on the forest cover, and developing a network of pollen detectors across the lakes of Canada will allow us to map the effects of current climate change on tree species. Pollen presence is also an important issue for public health, and a network of such sensors could be used as an indicator for such issues.
The current project proposes an innovative approach by designing an imaging flow cytometer specifically for the analysis of pollen in freshwater lakes. By designing and testing the instrument at the right wavelengths and with state-of-the-art microflow systems, we will gather pollen data in a much more efficient process than the current methods.
Flow cytometry is a method for characterizing individual living particles within the flow of a liquid as they pass within the focus point of a laser beam. The scattering pattern and the fluorescence, or the color spectrum of the light that is re-emitted by the pollen grain can deliver information on the morphology and characteristics of the grain.
Confocal imagery combines microscopes whose focal points are adjusted at different heights within the flow, which allows the 3D analysis of individual pollen grains, allowing a reliable identification of the species using a properly trained image-recognition neural network.
Combining these two approaches, we will deliver an automatic system, gathering samples of lake water and analyzing the species and number of pollen grains.
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