Farming is becoming fashionable, in large part because of its growing profitability. And innovations are making their work much more efficient. For example, farmers can get plant id to identify any type of plant. And this is a small part of what modern technology offers.
According to the UN, by 2050 the world’s population is expected to reach 9.7 billion. And humanity will have no choice but to learn how to farm more efficiently to solve the global food problem. There is no way to deal with this by ignoring modern technology.
However, innovation in agriculture is already commonplace. Thanks to the industrial revolution, farmers have minimized the use of manual labor tools and are now adopting high-tech solutions to increase the efficiency of land cultivation. In addition to IoT sensors, artificial intelligence, and machine learning systems, big data and blockchain are being used. The number of mobile applications for the agricultural sector is growing. There are several examples of how such technologies can help crop production, not in some distant future, but today.
Increase Rice Yields with the Internet of Things
In Central Java, Indonesia, Atilze was able to increase rice yields by 30-50% and save up to 50% water through precision farming. This is the name of the approach in which modern technologies help manage soil productivity: global positioning, yield estimation, remote sensing, the Internet of Things, and others.
The Atilze company has installed smart agricultural sensors that measure soil moisture and acidity, as well as ambient air temperature and humidity. This data allows for better conditions for cultivating rice, which is actually grown in standing water. Farmers are now harvesting higher yields of the crop without increasing the area of the fields.
Control the production and supply of sauces with blockchain
Barilla is the world’s largest pasta manufacturer, owning 45 percent of the Italian and 35 percent of the U.S. markets. The company has joined forces with IBM to better control the production and delivery cycles of its pasta and pesto sauce. Pesto’s special QR codes allow the Italian manufacturer to track every detail. From growing, harvesting in the field, to transportation, storage, quality control, production, and delivery directly to customers. IBM provided Barilla with a blockchain platform that processes the scan results and stores them as a continuous chain of data. This helps retailers and end consumers get reliable information about the origin of a product and be assured of its high quality.
Identify weeds with artificial intelligence and machine learning
Bayer is known as a pharmaceutical company. Today, it is a major concern with many divisions, including manufacturers of crop protection products and pest control.
A subsidiary of Bayer Digital Farming has developed an app that uses machine learning and artificial intelligence technologies to identify weeds. Farmers upload a photo of a weed to the app on their smartphone, and it compares the image to a cloud-based database of nearly 100,000 images. Farmers understand exactly what kind of weed they’re dealing with and can choose the most effective tools to control it. This helps protect crops and increase yields.
Reduce water consumption with IoT sensors
WaterBit, a developer of IoT soil moisture sensors, helped San Jose farmers manage irrigation systems – artificial irrigation of land that lacks moisture. Another company, PrecisionKing, has provided them with a system to monitor water consumption based on actual irrigation needs. More than 3,000 sensors transmit data to the cloud via AT&T’s cellular carrier network and help farmers reduce excessive water use and maintain the right soil moisture based on the crop that grows on it.
Using big data for precision farming
InVivo is a leading French agricultural group with 220 divisions and sales of up to 6.4 billion euros a year. Its subsidiary SMAG, a leading developer of information systems for the agribusiness sector, supplies its software solutions to 80% of farms and 50% of French retailers.
SMAG has already developed a large number of mobile applications to facilitate farmers’ daily work. A few years ago it consolidated the data collected in the process on a single digital platform. It stores satellite imagery and photos from drones, weather data, and information collected by soil moisture sensors – what we call big data.
Based on this platform, a sophisticated agronomic algorithm, Data Crop, works to help make more accurate farming decisions. For example, tracking crop progress throughout the year and predicting crop yields. The success of the SMAG project can be seen by the fact that Data Crop is now used to manage 80% of all agricultural land in France used for wheat cultivation.
The fact that the agricultural sector will have powerful incentives for development is confirmed by experts from one of the world’s leading news portals, Business Insider Intelligence. They believe that in 2023, the number of agricultural IoT sensors alone will be more than 12 million units.