An emerging system which combines rapid imaging with artificial intelligence could help scientists build a comprehensive picture of present and historic environmental change – by swiftly and accurately analysing pollen.
An emerging system which combines rapid imaging with artificial intelligence could help scientists build a comprehensive picture of present and historic environmental change – by swiftly and accurately analysing pollen.
Pollen grains from different plant species are unique and identifiable based on their shape. Analysing which pollen grains are captured in samples such as sediment cores from lakes helps scientists understand which plants were thriving at any given point in history, potentially dating back thousands to millions of years.
Up to now, scientists have manually counted pollen types in sediments or from air samples using a light microscope – a specialised and time-consuming task.
Now, scientists at the University of Exeter and Swansea University are combining cutting-edge technologies including imaging flow cytometry and artificial intelligence to build a system capable of identifying and categorising pollen at much faster rates. Their progress is published today in a research paper in New Phytologist. As well as building a fuller picture of past flora, the team hope the technology could one day be applied to more accurate pollen readings in today’s environment, which may help provide hayfever sufferers to mitigate symptoms.
Read more at University of Exeter
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