A Direct Comparison of Remote Sensing Approaches for High-Throughput Phenotyping in Plant Breeding.
A Direct Comparison of Remote Sensing Approaches for High-Throughput Phenotyping in Plant Breeding.
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DOI：
10.3389/fpls.2016.01131
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发表时间：
2016
影响因子：
5.6
通讯作者：
Chapman SC
中科院分区：
文献类型：
--
作者：
Tattaris M;Reynolds MP;Chapman SC
植物冠层的遥感(RS)可以实现对植物生理特征的非侵入性、高通量监测。这项研究比较了使用低空飞行的无人机(无人机)的三种遥感方法，以及近距离遥感和基于卫星的图像。考虑了冠层温度(CT)和植被指数(NDVI)这两个生理性状，以确定大规模作物遗传改良的最可行途径。无人机平台实现了地块级别的分辨率，同时通过在30-100米高度测量的高分辨率热像和多光谱图像，在一次任务中测量了数百个地块。卫星从770公里的高度测量多光谱图像。将这些信息与在距地块0.5-1米处使用红外温度计和NDVI传感器进行的近端测量进行了比较。为了进行稳健的比较，在灌溉和干旱条件下，在不同的温度条件下，在不适应的遗传资源上，在水分亏缺的情况下，对优良品种的CT和NDVI进行了评估。气载数据与成熟期产量/生物量的相关性一般高于同等的近邻相关。由于像素密度的限制，NDVI只能从较大面积(8.5×2.4米)的高分辨率卫星图像中提取。结果支持使用基于无人机的RS技术进行高通量表型分析，以提高精度和效率。
Remote sensing (RS) of plant canopies permits non-intrusive, high-throughput monitoring of plant physiological characteristics. This study compared three RS approaches using a low flying UAV (unmanned aerial vehicle), with that of proximal sensing, and satellite-based imagery. Two physiological traits were considered, canopy temperature (CT) and a vegetation index (NDVI), to determine the most viable approaches for large scale crop genetic improvement. The UAV-based platform achieves plot-level resolution while measuring several hundred plots in one mission via high-resolution thermal and multispectral imagery measured at altitudes of 30–100 m. The satellite measures multispectral imagery from an altitude of 770 km. Information was compared with proximal measurements using IR thermometers and an NDVI sensor at a distance of 0.5–1 m above plots. For robust comparisons, CT and NDVI were assessed on panels of elite cultivars under irrigated and drought conditions, in different thermal regimes, and on un-adapted genetic resources under water deficit. Correlations between airborne data and yield/biomass at maturity were generally higher than equivalent proximal correlations. NDVI was derived from high-resolution satellite imagery for only larger sized plots (8.5 × 2.4 m) due to restricted pixel density. Results support use of UAV-based RS techniques for high-throughput phenotyping for both precision and efficiency.