Drones, the new scouts for diseases, pests on the farm

Veronica Mugo and Yvonne Mukami set up a drone in a farm in Meru. Drones, which are delivering a whole new perspective of crop disease and pest early warning system to farmers, has brought new hope to many in Ntugi, Naare, Kibirichia and Timau. PHOTO | LEOPOLD OBI | NMG

What you need to know:

  • Late blight is a highly contagious disease as it quickly spreads from one farm to another. The cutting edge technology offered by the drone has put farmers ahead, enabling them contain pests and diseases thanks to early detection and control.
  • According to experts, drone’s precision at detecting pests and diseases is over 10 times accurate compared to the human eye.
  • The drone, which is delivering a whole new perspective of crop disease and pest early warning system to farmers, has brought new hope to many.
  • Green means the crop has no stress, yellow the crop has scanty stress while red indicates that the crop has too much stress.

On a windy day high up in the hilly Kibirichia village, Meru County, Susan Naftali observes an eagle-sized unmanned aerial vehicle (drone) hovering low above his field.

The drone, which is delivering a whole new perspective of crop disease and pest early warning system to farmers, has brought new hope to many in Ntugi, Naare, Kibirichia and Timau.

Susan, a mother of three, who grows potatoes and wheat, each on an acre, said before the arrival of the technology in 2017, she only managed four bags of potatoes.

Like many farmers in Kibirichia, her farm was attacked by late blight, which severely affected her, but she had no recourse due to lack of any means to detect the diseases early enough.

Late blight is a highly contagious disease as it quickly spreads from one farm to another. The cutting edge technology offered by the drone has put farmers ahead, enabling them contain pests and diseases thanks to early detection and control.

“After the drone flew over my wheat and potato farm, I was informed that the former had been attacked by thrips while the later late blight disease,” Susan said, adding she was advised on which pesticide to use.

According to experts, drone’s precision at detecting pests and diseases is over 10 times accurate compared to the human eye.

The drones are capable of collecting very high resolution images with very numerous details, thus, they are useful in mapping and surveying farms.

The use of drone in disease surveillance in the area is a pilot project initiated by Netherlands Development Agency (SNV) in partnership with Jomo Kenyatta University of Agriculture Technology (JKUAT) and Third Eye Company, a tech solution provider.

The drones are mounted with a near-infrared sensor (NIR) capable of detecting pest and diseases, 10 days before it becomes visible to an agronomist or an extension worker.

The gadgets ability to diagnose stress levels in plants at early stages, according to experts, helps in minimising insecticide use.

“It is easier to plan with data gathered from drones whether there will be any changes in production,” says Prof Bancy Mati, director and founder Water Research and Resource Centre at JKUAT, which is offering technical scientific research part of the project. Yvonne Mukami, an extension officer at Third Eye Company, says the sensor can take up to 20 samples in one day.

“In a day, we can make about eight to 15 visits to farmers,” she says.

Mukami explained that drone sensors use infra-red spectrum of light and other configuration called Normalised Difference Vegetation Index (NDVI) to give the intensity of stress in the crop.

“NDVI has four main colours; blue, green, red and yellow, which are used to outline the degree of crop stresses,” she notes.

Green means the crop has no stress, yellow the crop has scanty stress while red indicates that the crop has too much stress.

Blue appears where there is no vegetation or where the vegetation is very small or where there are buildings. “Captured images are processed through image composite editor that helps to stitch them together to form a single map,” explains Mukami. After being edited, the images are viewed and analysed. “The images are then finally broken down to a format that the farmer can easily understand,” says Mukami.

Dr James Messo, the chairman of soil, water and environmental engineering department at JKUAT, says one way of increasing a farm’s productivity to enhance food security is through early detection of diseases and good use of water.

Messo explains that drone technology’s ability to reveal whether individual plants are water-stressed, nutritionally deficient or under attack by insects or viruses helps in enhancing crop management advisory.

“Using near-infrared, farmers are able to predict pest and disease attacks, identify plant stresses like water and humidity 10-14 days ahead of time,” says Messo.

He said the 10-day warning could prevent large-scale crop losses. Dr Messo says that there is early indication that the project is working. “With this project, we are able to reduce the impact of pests and this means we can help farmers move out of poverty,” says Messo.

Dr Abraham Mehari, deputy project manager, SNV smart-water for agriculture programme, says the drone technology aims to entice youth into agricultural extension services.