Following the machines, people and ideas shaping agriculture. Selected developments, clear context and a link to the original source.
Robotics. Intelligence. Agriculture.
463 stories matching “AI”.
A GRDC-supported national project is building multi-season evidence on where variable-rate fertilizer application improves nutrient efficiency and farm returns.
IRRI and Vietnamese partners report cooperative-led adoption of equipment that places seed and fertilizer at different depths to reduce input waste.
A Spanish pilot brings aquifer monitoring into agricultural water discussions through the European CLEPSYDRA project and its decision-support work.
CIMMYT and Grupo Trimex report early results from Mexican wheat fields combining tailored fertilization, conservation practices and improved irrigation management.
Lincoln University reports lower estimated nitrate losses from a combined management strategy, alongside an eight-percent profit reduction in the trial.
An ICRISAT update describes work under Mission Mausam to connect weather expertise, agronomic data and AI workflows for farmer decision support.
The OdinsAEye consortium will connect tractor-mounted cameras, weed recognition and farm software, backed by DKK 8.3 million from Innovation Fund Denmark.
Autonomous Agri Solutions says it has acquired hardware, parts and technical assets for the Danish-developed ROBOTTI platform, with machine sales and customer support among its priorities.
The Danish manufacturer’s new FD60 scales its seed-position-based weeding approach to a wider platform. Orders are open, while the company schedules first deliveries for January 2027.
A Cornell-led collaboration will develop robotic orchard operations while examining affordability and adoption, supported by a new USDA Specialty Crop Research Initiative award.
Southern Illinois University researchers are building a mobile imaging and AI workflow for soybean disease monitoring after aerial cameras missed important views beneath leaves.
USDA’s Digital Agricultural Systems Hub combines crop imagery, machine-learning resources and deployable cameras to help move agricultural computer vision from research into practical field tools.
