AS-based images were also found to be an effective way to measure plant height. The LiDAR sensors explored in this study were found to be less effective and efficient overall but may have more intrinsic value for more complex traits such as leaf and branching angle. Supplementary Materials: The following are available online at http://www.mdpi.com/2072-4292/11/6/700/s1, Figure S1: Growth curves 2016, Figure S2: Growth curves 2017, Table S1: Plant height means and standard deviations, Table S2: Repeatability and standard error. Author Contributions: A.T., K.T., D.P., and P.A.-S. conceived of the project and its components. A.T., M.C., and D.M.E. performed data collections along with acknowled
Open resource ↗pdf-raw-page:17 lines:1-49Unverified paper record
Comparing Nadir and Multi-Angle View Sensor Technologies for Measuring in-Field Plant Height of Upland Cotton
Remote Sensing · 23 Mar 2019 · 10.3390/rs11060700
Abstract
Plant height is a morphological characteristic of plant growth that is a useful indicator of plant stress resulting from water and nutrient deficit. While height is a relatively simple trait, it can be difficult to measure accurately, especially in crops with complex canopy architectures like cotton. This paper describes the deployment of four nadir view ultrasonic transducers (UTs), two light detection and ranging (LiDAR) systems, and an unmanned aerial system (UAS) with a digital color camera to characterize plant height in an upland cotton breeding trial. The comparison of the UTs with manual measurements demonstrated that the Honeywell and Pepperl+Fuchs sensors provided more precise estimates of plant height than the MaxSonar and db3 Pulsar sensors. Performance of the multi-angle view LiDAR and UAS technologies demonstrated that the UAS derived 3-D point clouds had stronger correlations (0.980) with the UTs than the proximal LiDAR sensors. As manual measurements require increased time and labor in large breeding trials and are prone to human error reducing repeatability, UT and UAS technologies are an efficient and effective means of characterizing cotton plant height.
Plant phenotyping relevance
綿花の草丈という植物形質を対象に、複数のセンサーとUASを比較・検証しており、取得手法の技術性能評価が研究の中心である。
abstractThis paper describes the deployment of four nadir view ultrasonic transducers (UTs), two light detection and ranging (LiDAR) systems, and an unmanned aerial system (UAS) with a digital color camera to characterize plant height in an upland cotton breeding trial.
abstractThe comparison of the UTs with manual measurements demonstrated that the Honeywell and Pepperl+Fuchs sensors provided more precise estimates of plant height than the MaxSonar and db3 Pulsar sensors.
abstractPerformance of the multi-angle view LiDAR and UAS technologies demonstrated that the UAS derived 3-D point clouds had stronger correlations (0.980) with the UTs than the proximal LiDAR sensors.
Code and data availability
The paper's supplementary materials, hosted publicly on MDPI, contain paper-specific plant-phenotyping results: growth curves for 2016 and 2017, plant height means and standard deviations, and repeatability estimates with standard errors. No author analysis code, raw sensor data, or UAS imagery is stated to be publicly
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