开耳:一个超负担得起的,高通量,精确的玉米耳朵表型系统
Shaoqi Fan1,2, Guoji Li1,2, Revocatus Bahitwa1,3
1State Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, Center for Crop Functional Genomics and Molecular Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.
Plant methods
|February 8, 2026
概括
OpenEar是一个新的,负担得起的系统,用于高通量玉米耳的表型化. 这个DIY成像平台和深度学习管道准确地提取关键特征,帮助作物遗传分析和育种.
科学领域:
- 农业科学 农业科学
- 计算机科学 计算机科学
- 遗传学 是一个遗传学.
背景情况:
- 在单一植物水平上进行高通量作物表型化对于遗传分析和育种至关重要,但仍然是一个重要的瓶.
- 现有的准确和负担得起的玉米耳表型化工具是有限的,阻碍了该领域的进步.
研究的目的:
- 开发OpenEar,一个开源的,低成本的玉米耳的表型系统.
- 创建基于深度学习的管道,用于从玉米耳中端到端提取表型数据.
主要方法:
- 开发了一个DIY玉米耳朵成像平台,使用3D打印的零件和随时可用的电子设备进行360°表面扫描.
- 使用卷积神经网络 (CNN) 模型用于耳朵识别和YOLOv11模型用于耳朵细分和表面投影图像生成.
- 使用开发的管道提取了十个关键的耳朵和内核特征.
主要成果:
- 在多个特征上,OpenEar与手动测量有很高的一致性,包括耳朵长度 (R2=0.972),耳朵体积 (R2=0.976) 和内核数量 (R2=0.98).
- 该系统在各种耳朵和内核特征上实现了可靠的性能,R2值在0.515到0.98.9之间.
- 作为社区资源,公开发布手动注释的耳朵图像和视频.
结论:
- OpenEar提供了一种经过验证,低成本和可访问的解决方案,用于高通量玉米耳的表型化.
- 基于DIY的方法有可能显著推进作物遗传分析和育种应用.
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