By 2050, the world's population will have reached 10 billion. However, soils will be increasingly barren, aquifers will be more polluted and the climate crisis will lead to much higher average temperatures. This is why it is essential to redesign agriculture. We need processes based on the circular economy and advanced technologies that are sustainable, efficient and even more productive. One solution can be precision farming, based on reimagining the way we understand crop production and maintenance and implementing connected and automated devices that improve yields and minimise waste.
Agriculture is responsible for 10% of greenhouse gas emissions. It is essential to design technologies that allow us to optimise crops in order to curb the climate crisis. At the same time, the world's population continues to grow and age, and natural resources, such as fresh water, are becoming increasingly limited. These solutions must therefore contribute to designing a more efficient, sustainable and environmentally friendly agriculture. One of the most attractive proposals in this respect is precision agriculture, also known by its English name: 'precision farming'.smart farming'. For many, these systems will represent the third great revolution in agriculture, after the introduction of artificial fertilisers and the development of genetic modification methods at the beginning and end of the last century, respectively.
In reality, precision agriculture is a compendium of many different technologies. On the one hand, measurement and analysis techniques are used to assess soil quality, detect moisture, evaluate crop maturity and other parameters. Thanks to all this data, productivity can be optimised, the use of natural resources and the impact on the environment can be reduced. It also takes advantage of the latest advances in connectivity and communications to improve response times, speed up decision-making and monitor crop yields in near real-time. Finally, precision farming also encompasses the renewal of agricultural machinery and the implementation of new systems, including autonomous vehicles, which are safer, more efficient and more accurate, as we will see below.
There are different alternatives for monitoring crop quality. On a small scale, drones, small remotely controlled unmanned aerial vehicles (UAVs), can be used. These devices can capture images, make measurements and take data that provide information on crop water stress, potential plant nutritional deficiencies, the occurrence of pests, diseases and other threats, as well as the progress and development of plantations. Thanks to the information provided by drones, farmers can better adjust the amounts of fertilisers, pesticides and herbicides, and target these actions only to the areas of the crop that really need them. This technology allows us to have real-time crop data, as well as making tremendous savings in economic terms, and increases the sustainability of the process: reducing the quantities of fertilisers, for example, minimises the eutrophication of the environment, the proliferation of micro-organisms and other invasive species, and the pollution of rivers, lakes and aquifers.
Artificial satellites make it possible to scale up many of these operations to much larger areas. According to Javier Ventura-Traveset, an expert at the Rafael del Pino Foundation and director of the scientific office of the European Space Agency's Galileo navigation system, space is the perfect investment. Although the figures for investment in space technologies often come as a surprise, the fact is that the benefits far outweigh the infrastructure costs. Like drones, satellites can provide information on parameters such as humidity, crop maturity and even the appearance of pests. But satellites also allow us to observe, measure and study the Earth's atmosphere, and make observations directly related to the climate crisis and extreme weather events such as tornadoes, droughts and even incipient fires.
Thanks to technologies developed by the European Union, such as the Galileo, Copernicus and Etnos systems, data from these satellites are available openly and in near real-time. This speeds up decision-making and allows early detection of problems and mishaps. Some satellites, for example, incorporate systems known as reflectometers, which are based on technologies such as radar, making it possible to obtain information from the emission of signals and the detection of reflected radiation. These devices can measure soil moisture, the salinity of water bodies and the amount of nutrients in the soil, and allow for more effective resource management. Satellite systems also provide valuable information for long-term climate studies and statistics. Thus, for example, the efficiency of crops can be evaluated, their environmental impact assessed, and even activities that do not comply with regulations and protocols established by the authorities can be identified. Finally, satellites enable modern navigation systems and the operation of intelligent vehicles.
In addition to drones, precision agriculture also encompasses the development of intelligent ground vehicles, from small robots to tractors and other types of agricultural machinery. These operate by exploiting information detected by satellites, which they use to guide and position themselves, as well as to make decisions on crop treatment. Often these devices also incorporate their own sensors and detectors, which they use both to cross-check information received from other sources and to recalibrate these measurements and improve existing models.
Finally, connectivity between devices and IT developments such as artificial intelligence will also play a key role in the implementation of precision farming. Thanks to systems such as smartphones, 5G networks and the internet of things, precision farming enables the creation of collaborative solutions that ensure sustainable plantations, quick responses in case of emergency and the optimisation of resources. Different devices can not only connect with each other, but also share information through centralised IT systems and cloud services, so that data on one type of crop collected by one farmer in Europe can save another farmer's plantation in South America. Analysis of data generated by supercomputers and machine learning algorithms will enable agriculture to adapt to increasingly complex and extreme conditions, marked by soil erosion, nutrient scarcity, growing pollution of aquifers and rampant urbanisation, which will force a rethink of distribution and logistics models. It is estimated that, by 2050, we will need to produce between 60 and 70% more food. However, the area available for cultivation will be practically the same (it is unsustainable to continue deforesting the planet) and will have to be more efficient and environmentally friendly. The implementation of precision farming is not only an opportunity, but also an opportunity to meet sustainable development goals.
