According to the team, the new technology automates a tedious process that plays a key role in advancing our understanding of the world’s oceans and climate, today and in the prehistoric past.
Named ‘Forabot’, the new technology uses robotics and artificial intelligence to physically manipulate the remains of organisms called foraminifera, or forams, so that they can be isolated, imaged and identified.
“The beauty of this technology is that it is made using relatively inexpensive off-the-shelf components, and we are making both the designs and the artificial intelligence software open source,” said Edgar Lobaton, co-author of a paper on the work and an associate professor of electrical and computer engineering at North Carolina State University.
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“Our goal is to make this tool widely accessible, so that it can be used by as many researchers as possible to advance our understanding of oceans, biodiversity and climate.”
Forams are protists, neither plant nor animal, and have been prevalent in our oceans for more than 100 million years. When they die, they leave behind their tiny shells, most less than a millimetre wide. These shells give scientists insights into the characteristics of the oceans as they existed when the forams were alive.
For example, different types of foram species thrive in different kinds of ocean environments, and chemical measurements can tell scientists about everything from the ocean’s chemistry to its temperature when the shell was being formed. However, identifying foram shells and fossils is time consuming.
Lobaton explained that Forabot can identify six different types of foram with an accuracy rate of 79 per cent, and can process 27 forams per hour.
“This is a proof-of-concept prototype, so we’ll be expanding the number of foram species it is able to identify. And we’re optimistic we’ll also be able to improve the number of forams it can process per hour,” he said.
To use Forabot, users first have to wash and sieve a sample of hundreds of forams, leaving a pile of what looks like sand. The sample of forams is then placed into a container called the isolation tower.
A needle at the bottom of the isolation tower then projects up through the sample, lifting a single foram up where it is removed from the tower via suction. The suction pulls the foram to a separate container called the imaging tower, which is equipped with an automated, high-resolution camera that captures multiple images of the foram.
After the images are taken, the foram is lifted again by a needle until it can be picked up via suction and deposited in the relevant container in a sorting station.
Tom Marchitto, co-author of the paper and a professor of geological sciences at the University of Colorado, Boulder, said: “Once Forabot has been optimised, it will be a valuable piece of research equipment, allowing student ‘foram pickers’ to better spend their time learning more advanced skills.
“By using community-sourced taxonomic knowledge to train the robot, we can also improve uniformity of foram identification across research groups.”
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