European Commission outlines data and interoperability measures for agricultural AI
An agrifood webinar report proposes easier comparison of AI tools and stronger shared data foundations to address adoption barriers.
Following the machines, people and ideas shaping agriculture. Selected developments, clear context and a link to the original source.
Robotics. Intelligence. Agriculture.
137 stories matching “Data”.
An agrifood webinar report proposes easier comparison of AI tools and stronger shared data foundations to address adoption barriers.
An October organizer update confirms the July 2027 conference and explains review timing following its extended abstract deadline.
NbS4Tea introduced drone operations at Uganda’s Rwebitaba Tea Research Centre as part of a wider programme on resilient tea production and irrigation.
A new research paper sets out WildDrone’s drone, ecology and computer-vision programme, including wildlife monitoring at Kenya’s Ol Pejeta Conservancy.
FAO’s Central and Western Region locust commissions launched a programme combining classroom, simulator and field instruction for national surveillance and response teams.
A Ghana–Belgium partnership is developing locally grounded maize-yield estimation while addressing the field-data mismatches that can undermine satellite models.
An Earth-observation demonstrator for RICOWAS is being designed around geolocated farm records and the realities of a West African adaptation programme.
Philippine field research links aerial measurements with plant physiology across 318 rice accessions, offering a faster way to compare breeding material.
A five-day Côte d’Ivoire workshop linked flight operations, image analysis and shared breeding services for participants from seven West and Central African countries.
A Jendouba pilot compares daily 10-metre evapotranspiration data with a coarser product, exposing both operational benefits and validation gaps.
Semear Digital is testing irrigation decisions based on crop water stress, with vineyard results in São Paulo and expansion into pineapple production.
KALRO and CGIAR partners are combining historical trials and machine learning to develop maize nutrient recommendations adapted to local conditions.