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Seed Funding

The Center for Digital Agriculture is a catalyst for collaborative research projects across engineering and agricultural disciplines. Leveraging the strong tradition of team building for large long-term interdisciplinary research and education projects at the University of Illinois, CDA offered a competitive seed-funding program for new collaborative projects spanning two or more of the Center’s initial themes: Automation, Data, Animals and Crops, and People.

Current Awards

A Scalable Early Warning System: Electronic Detection of Corn Rootworm Beetles with a Microcontroller-based Sensor Network — George Gollin; Nicholas Seiter

Affordable and Scalable Non-Intrusive Measurements of Bovine Methanogenesis — George Gollin; Josh McCann

Autonomous Robotic Platform for Digital Agriculture: Cover Crop Interrow Planting — Dokyoung Lee; Girish Chowdhary

Crop Protection Decision Support using Long-Endurance UAV for Closing the Mission Feedback Loop — Marco Caccamo; Kaustubh Bhalerao; Or Dantsker

CropEYEs: A Low-Cost Camera IoT Network to Intelligently Track Crop Productivity — Chongya Jiang; Alexander Schwing

Engineering SWEET Family Transporters in Crops using Transfer Learning Approaches — Diwakar Shukla; Li-Qing Chen

Integration of Novel Wireless In-Field Sensors and Machine Learning for Smart Precision Agriculture — Yi Lu; Jian Peng; Wendy H. Yang; Li-Qing Chen

Optimization of Nutrient Management using Convolutional Neural Networks and Transfer Learning — Nicolas Martin; Naira Hovakimyan

Solving Dairy Cattle Genetic Improvement Challenges using Deep Learning — Sandra Rodriguez Zas; Eliu Huerta Escudero

Toward the Augmentation of Ruminal Fermentation: Developing a Computational-Experimental Framework to Predict Microbiome Dynamics and Function — Josh McCann; Ting Lu; Sara Tondini

Towards an Efficient and Programmable Computer Vision System for High Throughput Livestock Monitoring — Narendra Ahuja; Matthew Caesar; Ryan Dilger; Angela Green-Miller

Using Computational Methods and a Survey Experiment to Examine the Content and Impact of Social Media Discourse about an Emerging Food Technology — Leona Yi-Fan Su; Margaret Yee Man Ng; Yi-Cheng Wang

Past Awards

Addressing Effects of Soil and Water Pollution on Health in Rural Communities and Farmer Families — Liudmila Sergeevna Mainzer; Aiman Soliman; Kenton McHenry; Maxwell Burnette; Zeynep Madak-Erdogan; Rebecca Smith

Advancing Deep Learning for Vision Based Agricultural Phenotyping and Monitoring — Alexander Schwing; Girish Chowdhary; Brian Diers; Nicolas Martin; Nathan Kleczweski; D.K. Lee; Adam Davis

Algorithms and Methods for Simplifying Autonomy for Field Robots — Katherine Driggs-Campbell; Sasa Misailovic; Sayan Mitra; Girish Chowdhary

Data Carpentry for Agriculture: Computer Science Basics for Illinois Farmers, Agronomists, and CCAs — Lindsay Clark; Dena Strong; Carolyn Butts-Wilmsmeyer; Neal Davis

Deriving Tillage Practices and Irrigation Area/Methods from National Agriculture Imagery Database using Deep Learning and Supercomputing — Adam Stewart; Jian Peng; Kaiyu Guan

Estimating Yield and Water-Quality Response Functions using On-Farm Precision Experimentation, Spatially-Intense Soil Sampling, and Hyperspectral Imagery — David Bullock; Praveen Kumar; Andrew Margenot; Nicolas Martin; Laura Gentry

Event-Based Decision Making for Distributed Food and Agriculture Systems — Luis Rodriguez; Richard Sowers; Jay Solomon

Expanding the Utility of a Multi-Locus and Multi-Trait GWAS Model — Alexander Lipka; Lindsay Clark; Aurelie Lozano; Naoki Abe

Intelligent Development of Illinois Soils: ACES-Beckman-Center for Digital Agriculture (ABC) Collaborative Research in Soil Health Diagnostics — Tony Grift; Michelle Wander; Carmen Ugarte; Martin Bohn; Iwona Dobrucka

Machine Learning to Detect Fertilizer Adulteration in Developing Countries — Hope Michelson; Andrew Margenot; Ranjitha Kumar

Towards an Operational Methodology to Map Crop Photosynthetic Capacity from Airborne Remote Sensing — Kaiyu Guan; Elizabeth Ainsworth; Sheng Wang

Using Computer Vision to Relieve the Crop Phenotyping Bottleneck — Andrew Leakey; Narendra Ahuja; John M. Hart

Virtual Farming Networks for Smallholders through Digital Communities of Trust — Adam Davis; Lav Varshney