Field Endophenotyping Hub (FEED)
Leads: Robert Shepherd, Meagan Lang
Senior Personnel: Taryn Bauerle, Girish Chowdhary, Abe Stroock, Hakim Weatherspoon
The Field Endophenotyping Hub (FEED) serves as the innovation engine for hardware and computing in CROPPS. FEED provides a forum for the development of the technologies — based on robotics, material science, micro- and nanotechnology, and computer science — required to achieve the CROPPS vision for human-plant dialogues at scale, across genetic diversity, and in field environments. The Hub emphasizes the pursuit of engineering science and foundational design principles to provide robust, generalizable solutions to the challenge of defining intimate interactions with living plants systems in agricultural contexts. In collaboration with the Living Labs and the Plant Bioengineering Hub (PBH), FEED will develop sensors that capture and interpret organismal parameters to allow deep exploration of biological questions about responses to environment and to engineered solutions in collaborations. The team will detect these messages – e.g., optical, chemical, or acoustic – sent by programmed plants from below and above ground, process them through multi-scale models, and emit response signals to alter plant behavior in response to stress. Computation-based technologies will focus on ways to capture, deliver, translate, and interpret these messages from plants and to anticipate and respond to their needs. The rich data gathered from this work will be used to develop predictive models that can be tested experimentally with the Living Labs. The Hub will work with SEED to engage discussions with stakeholders and various publics to understand use-case scenarios, questions, and concerns; these discussions will feedback into the FEED vision and research plans.
In our work, we pursue the following objectives:
- Engineering intimate interactions with plant systems for field endophenotyping: field-ready micro- and nanotechnologies that provide quantitative, in-situ measurements and actuation of biological, chemical, and optical parameters across plant systems.
- Hybrid robotics for intimate, high throughput interactions with above- and belowground components of plant systems: agile and robust robots capable of engaging in multiplexed measurement and actuation with shoots, roots, and the rhizosphere.
- Integrative modeling and computational capabilities: models and computational technologies necessary to realize genotype to phenotype prediction and real-time communication between plants and models running on edge compute embedded in the plant environment.