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An agricultural drone is an unmanned aerial vehicle used in agriculture operations, mostly in yield optimization and in monitoring crop growth and crop production. Agricultural drones provide information on crop growth stages, crop health, and soil variations.
Using many sources of information — weather data, GIS spatial mapping, soil sensor data, satellite/drone pictures, etc. — e-extension platforms can provide real-time recommendations to farmers. For example, the machine-learning-enabled mobile app Plantix , Krisikart India diagnoses crops' diseases, pests, and nutrient deficiencies based on ...
An agricultural robot is a robot deployed for agricultural purposes. The main area of application of robots in agriculture today is at the harvesting stage. Emerging applications of robots or drones in agriculture include weed control, [1] [2] [3] cloud seeding, [4] planting seeds, harvesting, environmental monitoring and soil analysis.
And while that concept isn't exactly new, the method of doing so certainly is: Microsoft is using drones to autonomously identify ideal locations for mosquito traps, as well as placing and ...
Satellite crop monitoring technology allows to perform online crop monitoring on different fields, located in different areas, regions, even countries and on different continents. The technology's advantage is a high automation level of sown area condition and its interpretation in an interactive map which can be read by different groups of users.
Precision agriculture reduces the pressure of agriculture on the environment by increasing the efficiency of machinery and putting it into use. For example, the use of remote management devices such as GPS reduces fuel consumption for agriculture, while variable rate application of nutrients or pesticides can potentially reduce the use of these ...
Speeding up laboratory testing; one example of this was Skysports and their use of drones for COVID test delivery in Scotland. [97] Surveillance. [98] While other uses are being researched, such as their use for larval source management (LSM) to control vectors of diseases like malaria. [99]
The plant disease triangle represents the factors necessary for disease to occur. Plant disease forecasting is a management system used to predict the occurrence or change in severity of plant diseases. At the field scale, these systems are used by growers to make economic decisions about disease treatments for control.