Cornell engineers and plant scientists have teamed up to develop a low-cost system that allows grape growers to predict their yields much earlier in the season and more accurately than costly traditional methods.
An app that would maximize profit and minimize food spoilage and loss across the agriculture supply chain was named the grand prize winner in the third annual Cornell Institute for Digital Agriculture Hackathon.
A new study describes a breakthrough method for imaging the physical and chemical interactions that sequester carbon in soil at near atomic scales, which may have implications for mitigating climate change.
A Cornell-led, multi-institution, interdisciplinary team seeks to use computer vision, automation and robotics to optimize per-tree apple production, which is currently a highly manual and imprecise process.
A Cornell-led project will use computer modeling and outreach to find optimal strategies to minimize COVID-19 cases and transmission among workers in food processing facilities, while maintaining the best possible production.
Aimee Schulz' research in the Buckler Lab for Maize Genetics and Diversity examines the plant’s competitive ability. With the help of a phenotyping robot, she is able to collect data of 6,000+ plants in under half an hour! Watch video
Jaron Porciello in the Department of Global Development is exploring barriers to the widespread adoption of digital agriculture tools through a grant from USAID and the Bill & Melinda Gates Foundation.