Digital Counts of Maize Plants by Unmanned Aerial Vehicles (UAVs)
Digital Counts of Maize Plants by Unmanned Aerial Vehicles (UAVs)
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DOI：
10.3390/rs9060544
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发表时间：
2017-06-01
期刊：
影响因子：
5
通讯作者：
Schmidhalter, Urs
中科院分区：
文献类型：
--
作者：
Gnaedinger, Friederike;Schmidhalter, Urs
精确的表型分析，特别是图像分析的使用，使研究人员能够获得有关植物特性和植物健康的信息。利用无人机（UAV）进行航空图像检测为精准农业和精确表型分析提供了新的机会。精准农业创造了对植物密度空间数据的迫切需求。植株数量不仅反映了最终田间出苗情况，而且还允许对最终产量参数进行更精确的评估。这项工作的目的是推进无人机的使用和图像分析作为一种可能的高通量表型分析技术。在这项研究中，四个不同的玉米品种种植在不同的播种系统（行和等距）和不同的氮肥水平（施加在50，150和250公斤N/公顷）的地块。实验田包括96块地块，在50米的高度飞越，配备有1000万像素相机的直升机每5秒拍摄一张照片。在BBCH 13-15（它是鉴定植物的物候发育阶段的尺度，在此为3- 5叶发育阶段）之间记录图像，此时嫩叶的颜色不同于老叶。密切的相关性R-2 = 0.89被发现之间的原位和基于图像的计数植物适应去相关拉伸对比度增强程序，增强图像中的色差。平均而言，视觉和数字计数植物之间的误差为
Precision phenotyping, especially the use of image analysis, allows researchers to gain information on plant properties and plant health. Aerial image detection with unmanned aerial vehicles (UAVs) provides new opportunities in precision farming and precision phenotyping. Precision farming has created a critical need for spatial data on plant density. The plant number reflects not only the final field emergence but also allows a more precise assessment of the final yield parameters. The aim of this work is to advance UAV use and image analysis as a possible high-throughput phenotyping technique. In this study, four different maize cultivars were planted in plots with different seeding systems (in rows and equidistantly spaced) and different nitrogen fertilization levels (applied at 50, 150 and 250 kg N/ha). The experimental field, encompassing 96 plots, was overflown at a 50-m height with an octocopter equipped with a 10-megapixel camera taking a picture every 5 s. Images were recorded between BBCH 13-15 (it is a scale to identify the phenological development stage of a plant which is here the 3- to 5-leaves development stage) when the color of young leaves differs from older leaves. Close correlations up to R-2 = 0.89 were found between in situ and image-based counted plants adapting a decorrelation stretch contrast enhancement procedure, which enhanced color differences in the images. On average, the error between visually and digitally counted plants was