This roundtable discussion will focus on the development of a roadmap/white paper for integrating new materials and computational approaches into autonomously sampled sensors/imagers to advance high throughput plant phenotyping at multiple scales. The goal is a published manuscript that will guide an Engineering Research Center for Materials for Agriculture Resource Imaging Analytics at High Resolution (MARIAH).

The discussion is free and lunch will be provided in the meeting room for all discussion attendees. 

Full summary:

National Science Foundation Planning Grant: Engineering Research Center for Materials for Agriculture Resource Imaging Analytics at High Resolution (MARIAH) 

University of Arkansas, Arkansas State University, Arizona State University, Iowa State University, Oregon State University, Purdue University, University of Georgia, University of Nebraska-Lincoln 

‘Partnering to nourish a healthier world’ 

Rising global demand for food amidst increasing drought, extreme temperatures, and pest damage is straining precious land, water, and energy resources. The Engineering Research Center for Materials for Agricultural Resource Imaging Analytics at High Resolution (MARIAH) will engage experts in agriculture and other sciences, engineering, and management in developing innovative approaches to increase crop yields while reducing insecticide, herbicide, and fertilizer use. 

We are gathering academic, industry and regulatory partners in the natural, computational and social sciences, engineering, and business to catalyze bold new innovative strategies for data-driven crop variety selection and crop management. We envision (i) new materials to examine stress tolerance in individual plants; (ii) novel devices to image crop phenotypes and environment (e.g., detectors based on advanced semiconductors or quantum dots); (iii) advanced high throughput plant phenotyping systems and data analytics to mitigate effects of drought, extreme temperature and pest damage; and (iv) an inclusive culture for innovation and future workforce in data-driven sustainable agriculture. Progress in each area builds on advances in electronics, optics, bioinformatics, omics, and data science unique to partnering faculty and institutions. 

We anticipate integrating novel, high-resolution sensing/imaging platforms with autonomous collection and advanced data analytics at multiple scales. These new tools will spur innovations in data-driven selection of crop varieties and crop management strategies that increase crop resilience to stress, improve food and water quality, and decrease energy usage and nutrient pollution. Acclaimed methods for innovation, mentoring, and communications will attract participants from diverse backgrounds and disciplines and train next-generation leaders in data-driven sustainable agriculture. By identifying bold new approaches to increase crop yield and sustainably use land, water, and energy resources while preparing tomorrow’s workforce, we will advance the U.S. agriculture economy. Our goal is ‘partnering to nourish a healthier world.’ Come join us!  

Contacts: D. Keith Roper (, University of Arkansas 

Michael Costellano (, Iowa State University 

Jennifer Clarke (, University of Nebraska-Lincoln 

Changying (Charlie) Li (, University of Georgia 

Carol Reeves (, University of Arkansas 

Any opinions, findings, conclusions or recommendations presented are only those of the researchers and do not necessarily reflect the views of the National Science Foundation.