The occurrence and severity of harmful algal blooms are on the rise. This trend necessitates the development of a reliable and scalable approach for public safety and conservation agencies to swiftly detect and quantify the cells that form cyanobacterial colonies and filaments. The FlowCam is an established technology that facilitates the identification of taxa at the genus level and estimates the abundance of individual cells. It integrates digital imaging, flow cytometry, and microscopy to measure the dimensions, biovolume, and abundance of cells.
FlowCam is being used across the globe to estimate cell abundance of cyanobacteria, specifically colonial Microcystis. FlowCam Cyano utilizes advancements in technology, specifically a 633 nm laser, to detect the presence of phycocyanin and chlorophyll, thereby identifying cyanobacteria and other algae in water samples. The quantification of cells within colonies and filaments is achieved through a straightforward Excel-based formula, allowing monitoring agencies and researchers to efficiently count cells in large sample volumes. The FlowCam system provides precise measurements of cell abundance in large folded colonies as these colonies flatten within the specialized flow cell chamber.
Many customers are using to FlowCam to answer the question: How do you analyze algae populations?
Algae analysis is simplified using FlowCam's image analysis software VisualSpreadsheet. While manual identification may still be required for taxonomic purposes, algae identification and population analysis can be achieved with little effort using this system.
Step 1: Build Algae Libraries
As you analyze samples on FlowCam, you can build libraries for individual algae taxa. VisualSpreadsheet uses algae morphology and machine learning to detect and correctly classify samples into libraries.
Step 2: Classify Algae Using Libraries
By saving your custom filter sets as libraries, you can utilize the classification feature of VisualSpreadsheet, which facilitates the semi-automated identification of algae. Each time a new sample is processed through FlowCam, the imaged algal cells are compared to these libraries. Statistical pattern recognition algorithms are employed to determine the library that the algal cell most closely matches, thereby assigning it to the appropriate classification.
Learn more about VisualSpreadsheet or the FlowCam for phytoplankton and zooplankton analysis. Read articles, customer profiles, and peer-reviewed research about how FlowCam has been used for semi-automated algae analysis.
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