UAV Technology

The revolutionary capabilities of the latest UAV technology used by SOYL have numerous benefits for farm management and efficiency.

The SOYL UAV’s primary task is to take images of crops which can be used for:

> Crop health monitoring

> Identification of weed patches

> Yield estimates

> Plant counting.

The eight rotor platform offers precision performance, controlled by GPS systems. It can fly autonomously using a pre-prepared flight plan and taking the most efficient route to cover the field. The onboard cameras record multispectral images of crops which can be used to identify crop performance issues before they become apparent to the naked eye.

Before the UAV takes to the air a consultation is held with the grower to identify requirements and ensure that the UAV collects the correct data. Fields are carefully surveyed to make sure they are safe to fly, then with plans confirmed, the flight takes place.

SOYL's UAV takes images using two camera systems. The first is a standard camera which takes traditional aerial images of the field. The second is a multi-spectral unit with 6 individual lenses, each of which captures images in a specific area of the spectrum. These different wavelengths of light are associated with specific traits or different plant species and can highlight potential problems that can’t be seen by the human eye. Near infra-red frequencies are closely associated with a healthy crop, so identifying areas with a lower response in this area allows early action to be taken. The system also lends itself to weed mapping applications; by matching the reflected wavelengths of a known weed, a search can be conducted across the field, spotting any areas in need of attention.

The multi-spectral camera can also be used to look at various crop indices, such as the chlorophyll index, which has a very close relationship to the nitrogen value of the plant and red edge NDVI, which uses a narrower spectrum of light, can be used to quantify growth stages.

The results are impressive. SOYLsight can show the exact location of patches of black-grass, for example, providing information that can then be used to create a variable rate treatment zone.

Following the flight and image capture the data is interpreted and analysed to form the basis for recommendations to the grower.

The example map below demonstrates how mean NDVI per plot is recorded.

UAV map example for web2

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