Application of unmanned aerial systems for high-throughput phenotyping in wheat

We have developed and applied small unmanned aerial systems for image-based high-throughput phenotyping of wheat.  Over 100,000 plot level measurements of normalized difference vegetation index (NDVI) and plot-height have been taken on breeding nurseries over the current growing season.  An efficient pipeline for image processing is being implimented, along with novel algorithms for efficient extraction of plot level data.  Following characterization of simple vegetation indexes, this information is being incorporated to predict yield in breeding lines using multivariate models encompassing high-throughput phenotypes and genomic information.  Taken together, the merging of genomic prediction with novel high-throughput phenotyping has the power to greatly accelerate the breeding program through accurate predictions of early generation material.