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Artificial Intelligence and Agriculture: Prospects for the Future

Artificial Intelligence and Agriculture: Prospects for the Future

It is no secret that agriculture is a major occupation in many countries of the world. The agriculture industry is estimated by the World Bank to be worth $5 trillion. By 2025, it must feed around 9 billion people. However, the amount of newly cultivated land will only increase by 4%. This trend towards organic products is forcing agricultural enterprises to look for alternatives to the use of chemicals in weed control. In many countries, there is a shortage of labor.

Additionally, human toil makes production too expensive. In such circumstances, agriculture is looking for ways to optimize the use of the land, what to grow, and of what people graze on it. On the one hand, the agro-industry is one of the most conservative in terms of innovation in all countries. And, on the other hand, agriculture has been using all sorts of technologies for a long time, probably except for deep antiquity.

How Can Artificial Intelligence Help?

AI in agriculture is a real chance to achieve sustainable development. Artificial intelligence plays an important role in transforming food systems. It also addresses food and nutrition insecurity. In the agricultural sector, AI can help to optimize or even completely relieve humans from activities such as planting and harvesting. Thereby increasing productivity and improving working conditions (in the form of reducing time and labor intensity) and ensuring more efficient use of natural resources. Including streamlining knowledge management and planning.

In particular, with the rapid development of electronic agricultural technology, AI is finding increasing use in important areas such as agricultural robotics, soil and crop monitoring, and predictive analytics. Given climate change, population growth, and the depletion of natural resources, progress in these areas can contribute significantly to the conservation of soil and water resources. Both of which are key to food security in a sustainable manner.

Artificial Intelligence and Weed Control

Work continues improving systems for pest control around the world. A new spraying device for orchards is testing in the USA. The system mounts on a tractor and ultrasonic sensors determine the size and distance to the tree. The data analytics create a jet of spray with the right power and quantity of active ingredients. The experiment shows that in this way up to 27% of herbicides can be saved.

German companies Bayer and Bosh are also working on the Smart Spraying technology. The system will be able to identify the weed from the crop, determine its species and inject the required amount of herbicide based on the data entered in the software.

EcoRobotix is working on a device that will be able to roam across a field, find and treat weeds on its own. The company estimates that the use of the device will reduce the amount of herbicide applied by a factor of 20.

Using AI to Identify Diseases in Plants

Modern technology makes it easy to diagnose a plant disease, select a treatment and calculate the estimated damage. The number of applications to such services allows farmers to expand their libraries and increase the number of diseases that can be identified. By simply providing a picture of the affected plant, the disease can be identified and treatment suggested in seconds.

One of the services for diagnosing plant diseases is the Plantix app from Peat. The app allows you to diagnose more than 60 diseases. The service contains a large library of images that are conveniently sorted. With a gradual increase in the number of images uploaded, the algorithms for diagnosing diseases are also improving.

The Scouting application on the Xarvio digital platform is useful. By processing photographic images, the application is able to identify diseases, damage, and plant development disorders. The service is capable of identifying weeds and providing data on the nitrogen availability of the plant. There is a function to send a notification when a dangerous disease or pest is detected in the vicinity of the plants.

Thus, there are great prospects for the future, namely to identify plant diseases as quickly as possible and to treat them. Soon, we will be able to use technology that not only identifies diseases in plants but also regulates their treatment according to the stage of the disease.

Fields and Drones

AI improves yield forecasting with real-time sensor data and visual analytics from drones. The amount of data  smart sensors and drones can collect is astronomical. This real-time video provides agricultural experts with entirely new sets of information that have never been available before. Data from moisture, fertilizer, and soil nutrient sensors can now analyze the growth dynamics of each crop over time. Machine learning is the ideal technology for combining powerful data sets and providing recommendations to optimize yields. Drones are a reliable platform for collecting important data for farmers. AI, ground sensors, infrared imagery, and real-time video analytics all provide farmers with new insights. These can then improve crop health and yields.

The UN, international agencies, and large agricultural enterprises are now using information from drones to improve pest control. In the future, using infrared camera data from drones with sensors in fields will monitor plant health levels. Agro-producers who use artificial intelligence will be able to predict and detect pest infestations even before they happen.

Machines Instead of People

In some regions today, there is a shortage of workers in the agribusiness sector. This factor makes intelligent tractors, agro-bots, and robotics based on artificial intelligence and machine learning popular. Thus it is a viable option for many agricultural businesses that have difficulty finding workers. Large agricultural enterprises and agro holdings that cannot find enough workers are turning to robotics to cultivate hundreds of hectares of land.

Programming self-propelling robotics, for example, to distribute fertilizer to each row of crops helps reduce operating costs and further increases field yields. The complexity of agricultural robots is increasing rapidly every day. So, we can see that soon, robotic technology could be invaluable and even replace humans.

Conclusion

To sum it up, it can be said that even in agriculture, the future lies in AI. It is artificial intelligence technology that is helping to redefine the process of optimizing the production cycle and making entrepreneurial activity more efficient.

Technology is penetrating all areas of industry, including agriculture. It is reducing costs for businesses and making everyday work easier for employees. All while providing new tools to analyze and make informed decisions based on detailed data about the production process. This is no longer a distant future, but a reality for businesses. Especially those that are striving for sustainable and harmonious development. Now, not only economically, but also environmentally and socially.

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