Following the machines, people and ideas shaping agriculture. Selected developments, clear context and a link to the original source.
Robotics. Intelligence. Agriculture.
274 stories matching “ANT”.
The European Commission’s Joint Research Centre has introduced an approach using Sentinel-2 imagery to distinguish crop types in monitoring, with initial maize results included in its September 2026 MARS Bulletin.
Michigan State University has secured more than US$16.2 million from USDA NIFA for research-greenhouse renovations, with university matching funds bringing the new support to more than US$32.5 million.
University of Georgia researcher Hongwoo Lee is studying how deep learning could decode and design regulatory DNA, helping scientists alter when and where useful plant traits are expressed.
Cornell is testing genetically engineered tomato sentinel plants whose colour changes under nitrogen deprivation, examining whether a living sensor can provide useful nutrient information under variable field conditions for growers.
The University of Tennessee Institute of Agriculture appointed José Peiretti to a statewide Extension role focused on evaluating the practical performance and economics of precision technologies for row-crop growers locally.
Southern Illinois University brought drone mapping and agricultural AI demonstrations to its July field day, showing growers how aerial observations can support scouting and discussion of site-specific crop management practices.
A University of Georgia podcast introduces precision agriculture through drones, robotics and AI, connecting examples from horticultural research with discussion of efficiency, sustainability and skills needed in agricultural technology careers.
Kansas State University Extension describes how aerial imagery can speed stand counts and crop-health scouting, while stressing that farmers still need field checks to interpret what drone images show correctly.
The University of Bonn announced Stefano Mintchev’s appointment to advance interactive drones that use flexible structures, tactile sensing and control methods suited to close work in natural agricultural environments.
University of Florida, USDA and NASA researchers used hyperspectral imaging to identify early drought stress in lettuce, supporting development of non-destructive monitoring methods for greenhouses and other tightly controlled growing environments.
A University of Idaho-led research collaboration is developing harvest-integrated measurements and AI models to connect crop genetics with stalk strength, aiming to improve breeding for resistance to bending and breakage.
UC Merced researchers are developing materials that absorb ultraviolet light and emit visible wavelengths, exploring whether molecular design can improve greenhouse light management under the Central Valley’s demanding growing conditions.
