Agricultural production has drastically increased in recent years, and studies predict that aggregate agricultural consumption will increase by 69% from 2010 to 2050. This increase will be mostly stimulated by population growth from 7 billion to 9 billion by 2050.
In order to keep up with increasing demand, agriculture will have to revolutionise the way it produces food and become much more productive. Furthermore, production should be kept sustainable and help to prevent environmental damage. Moreover, other obstacles such as climate change make it harder to grow crops, due to an increasing number of unexpected weather events all over the world. So to satisfy world demand for food, close collaboration between governments, technology and industry has to be reinforced.
Until now, the main obstacle in farming has been the large area of farmed land and low efficiency in crop monitoring. This problem is exacerbated by increasingly unpredictable weather conditions, which increase farming risk and field maintenance costs. Until recently, the most advanced form of monitoring used satellite imagery. The main limitation was that images had to be ordered in advance, could be taken only once a day and were not very precise. In addition, the services were extremely expensive and gave no guarantee of quality, which could easily drop on a cloudy day.
Today, drone technology offers a large variety of crop monitoring possibilities at a lower cost. Furthermore, drones can be integrated at every stage of the crop lifecycle, from soil analysis and seed planting to choosing the right moment for harvesting.
The first stage of any agricultural cycle is to analyse the soil. Drones are able to produce precise 3D maps allowing early soil analysis, which can be used to plan seed planting patterns. Various start-ups have been able to create drone planting systems that not only achieve an uptake rate of 75%, but also decrease planting costs by 85%.23 These systems shoot pods with seeds and plant nutrients into the soil, giving the plant all the nutrients necessary to stay alive. Furthermore, the analysis provides data for irrigation and nitrogen level management. Drones with hyperspectral, multispectral or thermal sensors are able to tell exactly which parts of a field lack water or need improvements. Additionally, once the crop is growing, they allow the calculation of the vegetation index, show the heat signature and allow crop planting.
Once the later stage of a crop life cycle is reached, the farmer’s main objective turns to keeping the plants alive and healthy, which requires constant field monitoring. Drone monitoring possibilities are constantly being enhanced, providing the opportunity to reduce risk in the industry.
One of the latest developments helps to assess a plant’s health and spot bacteria or fungal infections on trees. Scanning a crop using visible light (VIS) and near-infrared (NIR) light shows which plants reflect different amounts of green light and NIR light. This information can produce multi-spectral images that spot changes in plants and indicate their health. A fast reaction is usually crucial, because it can save a whole orchard from dying. In addition, as soon as a sickness is spotted, a more precise remedy can be applied and monitored. These two possibilities increase a plant’s chance to overcome disease. Furthermore, in the case of crop failure, the farmer will be able to document losses for insurance claims much faster.
Crop spraying is another area of drone applications in agriculture. Drones can scan the ground, and maintain the right distance from the crops to spray the correct amount of liquid, modulating spraying in real time for even coverage. This will increase the efficiency of spraying, reducing the amount of excess chemicals penetrating into groundwater. Experts estimate that aerial spraying can be done as much as five times faster than with traditional machinery such as tractors.
Drones will allow farming to become a highly data-driven industry, which eventually will lead to an increase in productivity and yields. Due to their ease of use and low cost, drones can be used for producing time series animations showing the precise development of a crop. Such analysis could reveal production inefficiencies and lead to better crop management. With those possibilities in mind, it can be assumed that this technology will transform agriculture into a high-tech industry for the first time, with decisions being based on real gathering and processing of data. Thus, agriculture’s prime concern is not the drone’s speed or flexibility, but the type and quality of data it can obtain. So the industry will primarily push for more sophisticated sensors and cameras. Another objective will be to obtain drones that will require a minimal level of training and be highly automated.