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Proceedings Paper

Applying remote sensing expertise to crop improvement: progress and challenges to scale up high throughput field phenotyping from research to industry
Author(s): David Gouache; Katia Beauchêne; Agathe Mini; Antoine Fournier; Benoit de Solan; Fred Baret; Alexis Comar
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Paper Abstract

Digital and image analysis technologies in greenhouses have become commonplace in plant science research and started to move into the plant breeding industry. However, the core of plant breeding work takes place in fields. We will present successive technological developments that have allowed the migration and application of remote sensing approaches at large into the field of crop genetics and physiology research, with a number of projects that have taken place in France. These projects have allowed us to develop combined sensor plus vector systems, from tractor mounted and UAV (unmanned aerial vehicle) mounted spectroradiometry to autonomous vehicle mounted spectroradiometry, RGB (red-green-blue) imagery and Lidar. We have tested these systems for deciphering the genetics of complex plant improvement targets such as the robustness to nitrogen and water deficiency of wheat and maize. Our results from wheat experiments indicate that these systems can be used both to screen genetic diversity for nitrogen stress tolerance and to decipher the genetics behind this diversity. We will present our view on the next critical steps in terms of technology and data analysis that will be required to reach cost effective implementation in industrial plant breeding programs. If this can be achieved, these technologies will largely contribute to resolving the equation of increasing food supply in the resource limited world that lies ahead.

Paper Details

Date Published: 8 June 2016
PDF: 13 pages
Proc. SPIE 9866, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping, 986604 (8 June 2016); doi: 10.1117/12.2229389
Show Author Affiliations
David Gouache, ARVALIS - Institut du végétal (France)
Katia Beauchêne, ARVALIS - Institut du végétal (France)
Agathe Mini, ARVALIS - Institut du végétal (France)
Antoine Fournier, ARVALIS - Institut du végétal (France)
Benoit de Solan, ARVALIS - Institut du végétal (France)
Fred Baret, INRA UMR EMMAH (France)
Alexis Comar, ARVALIS - Institut du végétal (France)
Hi-Phen SAS (France)

Published in SPIE Proceedings Vol. 9866:
Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping
John Valasek; J. Alex Thomasson, Editor(s)

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