An award is made to Iowa State University to develop and deploy PhenoNet - an integrated robotic network for field-based studies of genotype crossed with environment (GxE) interactions. The core component of PhenoNet is a set of PhenoBots; lightweight robots that are able to autonomously navigate between crop rows using GPS and local range sensors while employing advanced sensing technologies to phenotype crop plants. The PhenoBots can measure indicators such as stalk size, plant height, leaf angle and tassel/inflorescence properties over time. The robots will be optimized for maize research and can be easily adapted for other row crops. The network (PhenoNet) is a universal platform which enables comprehensive field-based research on genotype and environment interactions. The broader impacts of this project are threefold. First, PhenoNet will have an important impact on society as understanding genome X environment interactions will help address the need for sufficient food, feed, and fiber for the planet's growing population, which is vital in an ever-changing environment. PhenoNet will bring "big data" more deeply into agriculture by cementing connections between plant scientists and engineers in their efforts to reach this goal. Second, this project is synergistic with the NSF-NRT project, "Predictive Phenomics of Plants", recently awarded to Iowa State University. The research and engineering outlined in this Major Research Instrumentation project will provide an outstanding opportunity for students from engineering disciplines, computer science, statistics, and agronomy to collaborate and engage in state-of-the-art interdisciplinary research. This project will also advance the training of current engineers and plant scientists who are experienced with networking, robotics and agronomy. Third, this project will reach out to underrepresented groups by targeting minority-serving institutions for student recruitment and will work with the Society of Women Engineers and other similar groups in seeking women participants to help meet the NSF-NRT award's efforts to broaden participation.
The PhenoBots are an important and essential advancement in the fields of agriculture and technology because they more efficiently characterize tall plants over time to their maturity. Previous technology and platforms are either incapable of, or are greatly hindered by various constraints. The design improvements of the Phenobots enable the robots to be more robust, stable, lightweight, integrated and economical. This creates a pathway for transformative research as it enables in situ, non-invasive monitoring of the traits of tall crops, like maize, over time. PhenoNet will consist of a network of four PhenoBots, which will be deployed by plant scientists in Iowa, Kansas, Minnesota, Nebraska, and Wisconsin. The data generated from high throughput phenotyping will address whether it is possible to predict the phenotype of a given genotype in a specified environment.
