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    Imaging Flow Cytometry and Microscopy Combine for Pollen Identification

    Article obtained from Photonics RSS Feed.

    Collaborating scientists from the Helmholtz Centre for Environmental Research (UFZ) and the German Centre for Integrative Biodiversity Research (iDiv) developed an image-based particle analysis system, reliant upon laser light and AI, to automate the process of pollen analysis. The method combines flow cytometry and deep learning to create a tool capable of correctly identifying species and quantifying pollen grains in a sample.

    Pollen analysis delivers important ecological and economical information, which is a useful component in many areas of research, including that which aims to study climate change and the loss of species by examining the relationship between plants and pollinators. Though microscopy remains the standard…

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    Oct, 08 2020 |

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