Doctor of Philosophy / Genetics Interdepartmental Program / Jesse A. Poland / A central question in modern biology is to understand the genotype-to-phenotype (G2P) link, that is, how the genetics of an organism results in specific characteristics. However, prediction of phenotypes from genotypes is a difficult problem due to the complex nature of genomes, the environment, and their interactions. While the recent advancements in genome sequencing technologies have provided almost unlimited access to high-density genetic markers, large-scale rapid and accurate phenotyping of complex plant traits remains a major bottleneck. Here, we demonstrate field-based complex trait assessment approaches using a commercially available light-weight Unmanned Aerial Systems (UAS). By deploying novel data acquisition and processing pipelines, we quantified lodging, ground cover, and crop growth rate of 1745 advanced spring wheat lines at multiple time-points over the course of three field seasons at three field sites in South Asia. High correlations of digital measures to visual estimates and superior broad-sense heritability demonstrate these approaches are amenable for reproducible assessment of complex plant traits in large breeding nurseries. Using these validated high-throughput measurements, we applied genome-wide association and prediction models to assess the underlying genetic architecture and genetic control. Our results suggest a diffuse genetic architecture for lodging and ground cover in wheat, but heritable genetic variation for prediction and selection in breeding programs. The logistic regression-derived parameters of dynamic plant height exhibited strong physiological linkages with several developmental and agronomic traits, suggesting the potential targets of selection and the associated tradeoffs. Taken together, our highly reproducible approaches provide a proof-of-concept application of UAS-based phenomics that is scalable to tens-of-thousands of plots in breeding and genetic studies as will be needed to understand the G2P and increase the rate of gain for complex traits in crop breeding.

It is a well-recognized fact that unmanned aerial vehicles are an essential element in today’s network-centric integrated battlefield environment. Compared to solo UAV missions, multiple unmanned aerial vehicles deployed in co-operative mode, offer many advantages that has motivated UAV researchers all over the world to evolve concept of operations that aims in achieving a paradigm shift from traditional ”dull” missions to perform ”dirty” and ”dangerous” missions. In future success of a mission will depend on interaction among UAV groups with no interaction with any ground entity. To reach this capability level, it is necessary for researchers, to first understand the various levels of autonomy and the crucial role that information and communication plays in making these autonomy levels possible. The thesis is in four parts: (i) Development of an organized framework to realize the goal of achieving fully autonomous systems. (ii) Design of UAV grouping algorithm and coordination tactics for ground attack missions. (iii) Cooperative network management in GPS denied environments. (iv) UAV group tactical path and goal re-plan in GPS denied wide area urban environments. This research thesis represents many first steps taken in the study of autonomous UAV systems and in particular group autonomy. An organized framework for autonomous mission control level by defining various sublevels, classifying the existing solutions and highlighting the various research opportunities available at each level is discussed. Significant contribution to group autonomy research, by providing first of its kind solution for UAV grouping based on Dubins’ path, establishing GPS protected wireless network capable of operating in GPS denied environment and demonstration of group tactical path and goal re-plan in a layered persistent ISR mission is presented. Algorithms discussed in this thesis are generic in nature and can be applied to higher autonomous mission control levels, involving strategic decisions among UAVs, satellites and ground forces in a network centric environment.