David Gouache

Applying remote sensing expertise to crop improvement: progress and challenges to scale up high throughput field phenotyping from research to industry

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.

Interest of a Multiparental and Outcrossing Wheat Population for Fine Mapping

The use of multiparental populations for QTL discovery has been recently highlighted by different theoretical and experimental developments. Here, we explored the interest of French populations using heterogeneous genetic stocks of cultivated wheat, maintained in situ over 12 sites since 1984 with an outcrossing mating system. We studied one of these populations (Le Moulon, 48.4°N, 21°E), derived from 12 cycles of random crosses between 60 founders, selected to maximize genetic diversity. Outcrossing was allowed by the integration of a nuclear male sterility allele (ms1b, Probus donor) in the population. We analyzed 1,000 Single Seed Descent lines (SSD) derived from the 12th generation of cultivation. This population was genotyped using the 9 K i-select SNPs (Single Nucleotide Polymorphisms) array, covering the whole genome. Polymorphism and quality checks resulted in the selection of around 6,500 SNPs. First, the evolution of genetic diversity was explored through the comparison of SSD lines and the inferred initial population. The low population structure and the strong decay in linkage disequilibrium between SSD lines and the inferred initial population confirmed the efficiency of the 12 cycles of the random outcrossing in producing a highly diverse and recombined population. Two years of observations of population earliness under different environments were used to show the complementarity of association genetics, which allowed the detection of already known Vrn major genes, and evolutionary approach, which, lead to the discovery of two new minor effect QTLs.