P0394
P3: Predictive Phenomics in Plants, A NSF Research Traineeship Program

Julie Dickerson , Iowa State University, Ames, VA
Carolyn J. Dill , Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA
Ted Heindel , Iowa State University, Ames, IA
Mary Losch , Center for Social and Behavioral Research, Cedar Falls, IA
Patrick S. Schnable , Iowa State University, Ames, IA
Understanding how particular genetic traits result in given plant characteristics under specific environmental conditions is a core goal of modern biology that will facilitate the efficient development of crops with commercially useful characteristics. Plant characteristics are influenced by genetics and a wide range of environmental factors, including, for example, rainfall, temperature and soil types. Developing methods to effectively integrate these diverse inputs that take advantage of existing biological, statistical, and engineering knowledge will be a key area in this research and training program that will bring together faculty from eight departments. Trainees will engage in cutting-edge research and development areas involving direct data collection and analysis from living plants, including sensor development, high throughput robotic technology, and biological feature extraction through image analysis. This traineeship will use the T-training model to provide students with training across a broad range of disciplines while developing a deep technical expertise in one area. This expertise, in combination with soft skills development, will enable the trainees to work across organizational and cultural boundaries as well as scientific disciplines. To develop understanding of how to share knowledge with diverse groups, the program will provide students with training beyond traditional coursework and research through activities that will develop advanced communication and entrepreneurship skills. Additionally, internship opportunities in industry, national labs, and other settings will equip trainees to choose among the diverse career paths available to scientists and engineers.