A new system developed by Florida researchers could greatly improve the monitoring of harmful algal blooms (HABs) such as red tide in the coastal Gulf of Mexico.
A Phys.org report tells us that the AUTOHOLO is an autonomous, submersible 3D holographic microscope and imaging system for studying marine particles and plankton in their natural environment.
This system has the potential to overcome many of the limitations associated with current methods for monitoring HABs.
Improving Red Tide Detection
Karenia brevis blooms can cause red tides that are damaging to marine life and public health. Toxins produced by the organism can kill fish, cause respiratory irritation in humans, and harm sea turtles, dolphins, manatees, and birds.
Between late 2017 and early 2019, Mote Marine Laboratory notes that red tide blooms in Florida resulted in the demise of nearly 600 sea turtles, over 200 manatees, and 204 dolphins.
Additionally, the proliferation of this algal bloom caused a significant decline in the quality of life for the communities situated along the western coast of Florida.
Detecting red tide blooms at all stages of development and cell concentrations is critical for improving prediction and developing potential mitigation strategies to protect public health and vital resources.
Current methods for monitoring red tide, such as microscopic identification and enumeration, standard flow cytometry, and others, have limitations, such as size resolution and concentration range constraints, limited capacity for profiling due to space and time constraints, and processing small volumes of samples.
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While these methods are operational, there are delays in data reporting, and maintenance and personnel costs can be high.
What Is AUTOHOLO?
The AUTOHOLO was created by researchers from Florida Atlantic University's College of Engineering and Computer Science and the Harbor Branch Oceanographic Institute to be used in situ to study marine particles and plankton in their natural environment.
Their research, published in the journal Harmful Algae, is the first to use holography to characterize red tide in the field, breaking new ground in HAB monitoring.
How the System Works
Researchers conducted field studies in the Gulf of Mexico during a red tide bloom in the winter of 2020-2021. They collected surface and subsurface water samples and analyzed them using holographic imaging and flow cytometry in the lab.
They created a training dataset using holographic images of red tide cells and used it to train a customized convolutional neural network for automated classification. The researchers used a custom-built towing system to help record data over large areas during the bloom.
They showed 90 percent accuracy in their results across various datasets with different levels of red tide concentrations. The combination of the towing system and AUTOHOLO facilitated the rapid characterization of red tide distributions over large areas during bloom events.
The AUTOHOLO can monitor early bloom phases of red tide, which other methods, such as remote sensing, may not be able to do. It can detect cells at very low concentrations (less than five cells/mL) and capture particles at extremely low concentrations (about five particles/mL).
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