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  2. Agricultural drone - Wikipedia

    en.wikipedia.org/wiki/Agricultural_drone

    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.

  3. Satellite crop monitoring - Wikipedia

    en.wikipedia.org/wiki/Satellite_crop_monitoring

    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.

  4. Data mining in agriculture - Wikipedia

    en.wikipedia.org/wiki/Data_mining_in_agriculture

    In agriculture, data mining is the use of data science techniques to analyze large volumes of agricultural data. Recent advancements in technology, such as sensors, drones, and satellite imagery, have enabled the collection of large amounts of data on soil health, weather patterns, crop growth, and pest activity.

  5. Precision agriculture - Wikipedia

    en.wikipedia.org/wiki/Precision_agriculture

    Point indicators allow them to track a crop's status, i.e., to see whether diseases are developing, if the crop is suffering from water stress, nitrogen stress, or lodging, whether it has been damaged by ice, and so on. This information may come from weather stations and other sensors (soil electrical resistivity, detection with the naked eye ...

  6. Digital agriculture - Wikipedia

    en.wikipedia.org/wiki/Digital_agriculture

    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 ...

  7. Normalized difference vegetation index - Wikipedia

    en.wikipedia.org/wiki/Normalized_difference...

    Today, this often involves agricultural drones, which are paired with NDVI to compare data and recognize crop health issues. One example of this is agriculture drones from PrecisionHawk and Sentera, which allow agriculturalists to capture and process NDVI data within one day, a change from the traditional NDVI uses and their long lag times. [19]

  8. Delivery drone - Wikipedia

    en.wikipedia.org/wiki/Delivery_drone

    Drones capture valuable information, which includes soil characteristics, location of drainage tiles, crop nutrient stress levels, crop emergence or stand count, weed species and infestation level, and detection of insects and diseases. [57] The benefits of drones in agriculture for increasing crop yields, cutting costs, and enhancing ...

  9. Disease management (agriculture) - Wikipedia

    en.wikipedia.org/wiki/Disease_management...

    In agriculture, disease management is the practice of minimizing disease in crops to increase quantity or quality of harvest yield. Organisms that cause infectious disease in crops include fungi , oomycetes , bacteria , viruses , viroids , virus-like organisms, phytoplasmas , protozoa , nematodes and parasitic plants .