Hexaploid bread wheat (Triticum aestivum L. em. Thell) is one of the world's most important crop plants and displays a very low level of intraspecific polymorphism. We report the development of highly polymorphic microsatellite markers using procedures optimized for the large wheat genome. The isolation of microsatellite-containing clones from hypomethylated regions of the wheat genome increased the proportion of useful markers almost twofold. The majority (80%) of primer sets developed are genome-specific and detect only a single locus in one of the three genomes of bread wheat (A, B, or D). Only 20% of the markers detect more than one locus. A total of 279 loci amplified by 230 primer sets were placed onto a genetic framework map composed of RFLPs previously mapped in the reference population of the International Triticeae Mapping Initiative (ITMI) Opata 85 × W7984. Sixty-five microsatellites were mapped at a LOD >2.5, and 214 microsatellites were assigned to the most likely intervals. Ninety-three loci were mapped to the A genome, 115 to the B genome, and 71 to the D genome. The markers are randomly distributed along the linkage map, with clustering in several centromeric regions.

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The dynamics of the Green Leaf Area Index (GLAI) is of great interest for numerous applications such as yield prediction and plant breeding. We present a high-throughput model-assisted method for characterizing GLAI dynamics in maize ( Zea mays subsp. mays ) using multispectral imagery acquired from an Unmanned Aerial Vehicle (UAV). Two trials were conducted with a high diversity panel of 400 lines under well-watered and water-deficient treatments in 2016 and 2017. For each UAV flight, we first derived GLAI estimates from empirical relationships between the multispectral reflectance and ground level measurements of GLAI achieved over a small sample of microplots. We then fitted a simple but physiologically sound GLAI dynamics model over the GLAI values estimated previously. Results show that GLAI dynamics was estimated accurately throughout the cycle (R 2 > 0.9). Two parameters of the model, biggest leaf area and leaf longevity, were also estimated successfully. We showed that GLAI dynamics and the parameters of the fitted model are highly heritable (0.65 ≤ H 2 ≤ 0.98), responsive to environmental conditions, and linked to yield and drought tolerance. This method, combining growth modeling, UAV imagery and simple non-destructive field measurements, provides new high-throughput tools for understanding the adaptation of GLAI dynamics and its interaction with the environment. GLAI dynamics is also a promising trait for crop breeding, and paves the way for future genetic studies.