欧亚国际

    本文探讨了利用LiDAR与无人机法进行高通量植物表型性状研究-植物高度估算的方法。我们使用良好浇水以及水分胁迫条件下的小麦基因型进行了实验。利用phénomobiles 无人驾驶移动表型车，多次在生长期进行LiDAR测量。配有高分辨率RGB相机的UAV进行了多次飞行，用来追溯数字表明模型（移动的结构信息）。两种技术均可提供3D密度点云，可估算植物高度。植物高度首先界定为z值，99.5%的密度点云情况参见全文。该方法与手工测量植物高度 (RMSE = 3.5 cm) 方法有良好的一致性，在每个微区消除了差异。结果显示，LiDAR和来自移动结构信息的植物高度值非常一致。但是，观测到移动技术获得结构有轻微低估，与LiDAR相比，无人机摄影空间分辨率较差，移动时结构穿透力有限。植物高度的动力学显示其携带了植物胁迫时间以及程度的相关信息。另外，发现植物高度达到较高的时期是可遗传的（(H2 > 0.88) ，也是开花时间很好指示参数。文章较后探讨了将植物高度作为全部地上生物量和产量的指示参数。

    注：该植物表型成像车为法国Hiphen公司自主研制，专有软件分析系统，是当今上自动化程度较高、较先进的表型成像系统。

    Fred Baret1,Benoît de Solan2 , Samuel Thomas2 , Dan Dutartre3 , Stéphane Jezequel2 , <a href="http://loop.frontiersin.org/people/408350/overview" h"="">Matthieu Hemmerlé3 , Gallian Colombeau1  and Alexis Comar3 

    1 INRA, UMR EMMAH, Avignon, France, 2 ARVALIS – Institut du végétal, Avignon, France, 3 HIPHEN, Avignon, France 

    The capacity of LiDAR and Unmanned Aerial Vehicles  (UAVs) to provide plant height estimates as a high-throughput plant phenotyping trait was explored. An experiment over wheat genotypes conducted under well watered and water stress modalities was conducted. Frequent LiDAR measurements were performed along the growth cycle using a phénomobiles unmanned ground vehicle. UAV equipped with a high resolution RGB camera was flying the experiment several times to retrieve the digital surface model from structure from motion techniques. Both techniques provide a 3D dense point cloud from which the plant height can be estimated. Plant height first defined as the z-value for which 99.5% of the points of the dense cloud are below.This provides good consistency with manual measurements of plant height (RMSE = 3.5 cm) while minimizing the variability along each microplot. Results show that LiDAR and structure from motion plant height values are always consistent. However, a slight under- estimation is observed for structure from motion techniques, in relation with the coarser spatial resolution of UAV imagery and the limited penetration capacity of structure from motion as compared to LiDAR. Very high heritability values (H2  > 0.90) were found for both techniques when lodging was not present. The dynamics of plant height shows that it carries pertinent information regarding the period and magnitude of the plant stress. Further, the date when the maximum plant height is reached was found to be very heritable (H2  > 0.88) and a good proxy of the flowering stage. Finally, the capacity of plant height as a proxy for total above ground biomass and yield is discussed. 

    Keywords: plant  height,  high  throughput, unmanned  aerial  vehicles,  dense  point  cloud, LiDAR, phenotyping, broad-sense heritability.