Following the machines, people and ideas shaping agriculture. Selected developments, clear context and a link to the original source.
Robotics. Intelligence. Agriculture.
38 stories matching “NSF”.
The JaetRobi project combines camera-based plant recognition with a precisely positioned blue laser, targeting young weeds close to vegetable crops while researchers address speed and reliability.
A June 2020 competition announcement paired agricultural researchers and experienced growers in Yunnan, testing how sensing, greenhouse automation and cultivation knowledge could contribute to strawberry quality and productivity.
Zambia’s Industrial Development Corporation reported its participation in the April 2025 AgriTech Expo, while Italy’s trade agency organised a machinery pavilion, illustrating the event’s role in agricultural investment and technical exchange.
Bosch and eight agricultural partners received a silver Agritechnica Innovation Award in 2019 for NEVONEX, a platform intended to run connected digital services directly on agricultural machinery.
Greenhouse in Transition brings universities and industry together to rethink growing systems and their connections with nearby farms, homes and industrial sites.
Penn describes inexpensive soil and leaf sensors, field communications and a startup working to reveal crop stress before visible damage becomes widespread.
Aga Khan University and Simon Fraser University are examining how LiteWeed can fit East African farming conditions and community priorities.
Croplands and SwarmFarm combine autonomous spot spraying with optional automated refilling and six-wheel drive in their Series 2 platform.
A Nairobi agreement creates a collaboration framework for agroecology, climate resilience and evidence-based rural development in Africa.
The November engineering conference will examine autonomous machines, sensors, interoperability and powertrains alongside practical machinery design.
Arkansas graduates won two competitions in Indianapolis, including a strawberry processing prototype combining vision, motion control and safety systems.
A study reports 84% crop-classification accuracy using an open-source satellite model, while highlighting limitations in ground data and mixed-crop evaluation.
