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High clearance phenotyping systems for season-long measurement of corn, sorghum and other row crops to complement unmanned aerial vehicle systems

机译:玉米,高粱和其他行作物的季节长度测量高清关表型系统,以补充无人驾驶飞行器系统

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The next generation of plant breeding progress requires accurately estimating plant growth and development parameters to be made over routine intervals within large field experiments. Hand measurements are laborious and time consuming and the most promising tools under development are sensors carried by ground vehicles or unmanned aerial vehicles, with each specific vehicle having unique limitations. Previously available ground vehicles have primarily been restricted to monitoring shorter crops or early growth in corn and sorghum, since plants taller than a meter could be damaged by a tractor or spray rig passing over them. Here we have designed two and already constructed one of these self-propelled ground vehicles with adjustable heights that can clear mature corn and sorghum without damage (over three meters of clearance), which will work for shorter row crops as well. In addition to regular RGB image capture, sensor suites are incorporated to estimate plant height, vegetation indices, canopy temperature and photosynthetically active solar radiation, all referenced using RTK GPS to individual plots. These ground vehicles will be useful to validate data collected from unmanned aerial vehicles and support hand measurements taken on plots.
机译:下一代植物育种进展需要准确地估算植物生长和开发参数,以在大型现场实验中通过常规间隔进行。手动测量是费力且耗时的,并且开发的最有前途的工具是由地面车辆或无人驾驶飞行器携带的传感器,每个特定车辆具有独特的速度。以前可获得的地面车辆主要被限制为监测玉米和高粱的较短作物或早期生长,因为拖拉机或喷雾器的植物可能损坏。在这里,我们设计了两个,并且已经建造了这些自行车的地面车辆中的一个,可调高度可清除成熟的玉米和高粱,而不会损坏(超过三米的间隙),这将适用于较短的行作物。除常规RGB图像捕获外,传感器套件还包含估算植物高度,植被指数,冠层温度和光合有源太阳辐射,所有这些都是使用RTK GP对各个图的引用。这些地面车辆可用于验证从无人驾驶飞行器收集的数据并支持在图上拍摄的手测量。

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