Winter Wheat
Winter wheat research focuses on optimizing yield and managing threats to production, such as disease and weeds. Current studies employ machine learning, particularly convolutional neural networks (CNNs) and transformers, to analyze multispectral imagery, 3D point clouds, and other data sources for tasks like yield prediction, disease detection (e.g., Fusarium head blight), and weed identification (e.g., blackgrass). These advancements in automated phenotyping and precision agriculture aim to improve efficiency, reduce resource use, and enhance food security.
Papers
November 7, 2024
July 31, 2024
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February 16, 2024
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November 27, 2023
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December 13, 2022
June 30, 2022