Makanza Richard, Zaman-Allah Mainassara, Cairns Jill E, Magorokosho Cosmos, Tarekegne Amsal, Olsen Mike, Prasanna Boddupalli M
International Maize and Wheat Improvement Center (CIMMYT), P.O. Box MP163, Harare, Zimbabwe;
International Maize and Wheat Improvement Center (CIMMYT), P.O. Box 1041, Nairobi, Kenya;
Remote Sens (Basel). 2018 Feb 23;10(2):330. doi: 10.3390/rs10020330.
In the crop breeding process, the use of data collection methods that allow reliable assessment of crop adaptation traits, faster and cheaper than those currently in use, can significantly improve resource use efficiency by reducing selection cost and can contribute to increased genetic gain through improved selection efficiency. Current methods to estimate crop growth (ground canopy cover) and leaf senescence are essentially manual and/or by visual scoring, and are therefore often subjective, time consuming, and expensive. Aerial sensing technologies offer radically new perspectives for assessing these traits at low cost, faster, and in a more objective manner. We report the use of an unmanned aerial vehicle (UAV) equipped with an RGB camera for crop cover and canopy senescence assessment in maize field trials. Aerial-imaging-derived data showed a moderately high heritability for both traits with a significant genetic correlation with grain yield. In addition, in some cases, the correlation between the visual assessment (prone to subjectivity) of crop senescence and the senescence index, calculated from aerial imaging data, was significant. We concluded that the UAV-based aerial sensing platforms have great potential for monitoring the dynamics of crop canopy characteristics like crop vigor through ground canopy cover and canopy senescence in breeding trial plots. This is anticipated to assist in improving selection efficiency through higher accuracy and precision, as well as reduced time and cost of data collection.
在作物育种过程中，使用能够可靠评估作物适应性性状的数据收集方法，比目前使用的方法更快、更便宜，可通过降低选择成本显著提高资源利用效率，并可通过提高选择效率促进遗传增益增加。目前估计作物生长（地面冠层覆盖）和叶片衰老的方法基本上是人工的和/或通过视觉评分，因此往往主观、耗时且昂贵。航空传感技术为以低成本、更快且更客观的方式评估这些性状提供了全新的视角。我们报告了在玉米田间试验中使用配备RGB相机的无人机进行作物覆盖和冠层衰老评估的情况。航空成像获得的数据显示，这两个性状具有中等程度的高遗传力，且与籽粒产量存在显著的遗传相关性。此外，在某些情况下，作物衰老的视觉评估（容易出现主观性）与根据航空成像数据计算出的衰老指数之间的相关性显著。我们得出结论，基于无人机的航空传感平台在监测育种试验地块中作物冠层特征（如通过地面冠层覆盖和冠层衰老反映的作物活力）动态方面具有巨大潜力。预计这将有助于通过更高的准确性和精确性以及减少数据收集的时间和成本来提高选择效率。
