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Front. Plant Sci. | doi: 10.3389/fpls.2017.02002

High-throughput phenotyping of plant height: comparing Unmanned Aerial Vehicles and ground LiDAR estimates

 Simon Madec1*,  Fred Baret1, Benoît De Solan2, Samuel Thomas2, Dan Dutartre3, Stéphane Jezequel2,  Matthieu Hemmerlé3, Gallian Colombeau1 and Alexis Comar3
  • 1UMR EMMAH, INRA Centre Provence-Alpes-Côte d'Azur, France
  • 2Arvalis - Institut du Végétal, France
  • 3hi-phen, 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 phénomobile 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 Vehicle, Dense point cloud, lidar, phenotyping, Broad-sense heritability

Received: 22 Aug 2017; Accepted: 09 Nov 2017.

Edited by:

Yann Guédon, Centre de coopération internationale en recherche agronomique pour le développement (CIRAD), France

Reviewed by:

Barbara George-Jaeggli, The University of Queensland, Australia
Andreas Bolten, University of Cologne, Germany  

Copyright: © 2017 Madec, Baret, De Solan, Thomas, Dutartre, Jezequel, Hemmerlé, Colombeau and Comar. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: PhD. Simon Madec, INRA Centre Provence-Alpes-Côte d'Azur, UMR EMMAH, Avignon, France,