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A deep learning-integrated micro-CT image analysis pipeline for quantifying rice lodging resistance-related traits
2021
Plant Communications
Lodging is a common problem in rice, reducing its yield and mechanical harvesting efficiency. Rice architecture is a key aspect of its domestication and a major factor that limits its high productivity. The ideal rice culm structure, including major_axis_culm, minor axis_culm, and wall thickness_culm, is critical for improving lodging resistance. However, the traditional method of measuring rice culms is destructive, time consuming, and labor intensive. In this study, we used a high-throughput
doi:10.1016/j.xplc.2021.100165
pmid:33898978
pmcid:PMC8060729
fatcat:46dbeyuy4faerd5bp3exx2pbo4