首页> 外文会议>Conference on Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping;Society of Photo-Optical Instrumentation Engineers >Small plot identification from video streams for high-throughput phenotyping of large breeding populations with unmanned aerial systems
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Small plot identification from video streams for high-throughput phenotyping of large breeding populations with unmanned aerial systems

机译:视频流中的小样区识别,用于无人空中系统的大型繁殖种群的高通量表型分析

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In breeding and genetics programs, thousands of small plots in the size of a few square meters each having a uniquegenetic entry, are used to evaluate huge numbers of candidates and large mapping populations. Low-altitude remotesensing with unmanned aerial systems (UAS) can generate high geospatial resolution measurements of plants and enablehigh temporal resolution measurements through multiple crop growth stages. However, to identify individual plot fromaerial images robustly and automatically becomes a key challenge in high throughput phenotyping (HTP) using UAS. Inthis case study, we captured super high-resolution video clips of wheat canopies by a UAS at low altitude. We proposedan image processing pipeline for identifying individual plot from video frames. Preliminary results indicate the methodscan highly accelerate the process of linking genotypes to individual plot images and can be fully automated. Thisresearch provides a proof-of-concept and has broad implications of novel phenomics application of UAS that is scalableto tens-of-thousands of plots in crop breeding and genetic studies.
机译:在育种和遗传学计划中,成千上万个面积为几平方米的小块土地每个都有一个独特的 基因输入,用于评估大量候选对象和大量作图群体。低空遥控器 使用无人机系统(UAS)进行传感可以生成植物的高地理空间分辨率测量值,并可以实现 通过多个作物生长阶段进行高时间分辨率测量。但是,要从 强大且自动的航拍图像成为使用UAS进行高通量表型(HTP)的关键挑战。在 在本案例研究中,我们通过低空无人机拍摄了小麦冠层的超高分辨率视频片段。我们提议 图像处理管道,用于从视频帧中识别单个情节。初步结果表明了方法 可以大大加快将基因型链接到单个图谱图像的过程,并且可以完全自动化。这 研究提供了概念证明,并且对可扩展的UAS的新型表态学应用产生了广泛的启示 作物育种和遗传研究的成千上万个地块。

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