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In East Africa, researchers from the university of Nairobi have been using drones to gather crop information for farming operations.

“Crop statistics are important for planning, policy making and timely interventions to address food security,” said Elijah Cheruiyot, a research associate in remote sensing at the International Potato Centre in Kenya.

Drone-based remote sensing technology is a game changer in the gathering of agricultural statistics data. It is relatively cheaper; boasts high quality sensors and allows collection of accurate statistics on a large scale with minimal effects from clouds or rain, which in some cases blurs images taken by satellites.

“The drone maps everything on the ground, after which the data is processed by specialised software and scientists can then zero in on their area of interest,” said Mr Cheruiyot.

 The drones can gather data on all food crops in a particular area and point out diseases and water-stressed areas, making them an important tool in irrigation scheduling. The drones have been known to detect diseases in a field two weeks before the symptoms become obvious to the human eye.

Using sweet potato as the pilot crop, scientists are advocating the use of unmanned aerial vehicles to collect accurate and timely agricultural data.

“This is a great technology and we should develop it further,” said Arnold Bett from the University of Nairobi.

The University of Nairobi is offering opportunities for training in and teaching this technology, specifically developing electronics that aid scientific research. The College of Agriculture and Veterinary Science also does research on agriculture.

 Mr Bett said the continuous monitoring of plants using drones can help to increase crop yields because a data log of the plants’ health within one planting season can be useful for the next planting season.

Drone technology can help identify the right pesticides to use on plants. The images captured by the drone can also map areas of a farm where there are diseases or lack of soil nutrients.

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  • Optimise processes by identifying irrigation weakness