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DOI: 10.3791/66112-v
Here, we present a simple method for direct observation and automated measurement of stomatal responses to bacterial invasion in Arabidopsis thaliana. This method leverages a portable stomatal imaging device, together with an image analysis pipeline designed for leaf images captured by the device.
Plant stomata plays a central role in the adaptation to stress conditions, so we need to measure stoma aperture to understand how plants respond to biotic and antibiotic stresses. However, stomatal aperture measurement is time-consuming and cumbersome. To measure stomatal aperture, we feel the epidermis and observe stomata under microscope.
Then we manually measure stomatal aperture, which takes a long time even though we're experienced researchers. We challenged these barriers and developed a tool and a technique that can automatically measure stomatal aperture in intact Arabidopsis leaves. So we strongly believe that stomata imaging device and deep learning algorithm that we developed will facilitate functional analysis of stomata responses to various biotic and abiotic stresses because these technical advances significantly reduce time and human labor required for stomatal aperture measurement.
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