Location: Plant Physiology and Genetics ResearchTitle: Comparing nadir and multi-angle view sensor technologies for measuring in-field plant height of upland cotton
|ANDRADE-SANCHEZ, PEDRO - University Of Arizona|
|PAULI, DUKE - University Of Arizona|
Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/15/2019
Publication Date: 3/23/2019
Citation: Thompson, A.L., Thorp, K.R., Conley, M.M., French, A.N., Andrade-Sanchez, P., Pauli, D. 2019. Comparing nadir and multi-angle view sensor technologies for measuring in-field plant height of upland cotton. Remote Sensing of Environment. 11:700-719. https://doi.org/10.3390/rs11060700.
Interpretive Summary: Plant height is an important phenotype for cotton management and an indicator of plant health. This study shows that simple and relatively inexpensive industrial ultrasonic transducers are an effective and efficient means of measuring cotton plant height over time. Three-dimensional point clouds generated by photogrammetry from UAS-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.
Technical 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.