Data science and big data are increasingly finding their way into agriculture to create economic and ecological production conditions adapted to the market. Digital networking is therefore playing an increasingly important role.
According to the German Farmers’ Association, “Agriculture 4.0” has arrived in every fifth farm.
This means the use of Industry 4.0 applications such as
Computer science and electronics have shaped everyday agricultural life for many years.
Remote-controlled helicopters and multicopters for civil purposes are used in agricultural practice. Wildlife rescue (fawn identification) with infrared detection, soil, fertilizer, crop protection monitoring, and crop protection application are possible fields of application with enormous amounts of data.
Dealing with soil, water, and air can be improved with agricultural-specific weather data. A close-knit network of weather stations and phenological observations are therefore of great informational value.
The irrigation of plants without damaging the water table and salinizing the soil is essential for the farmer. In digitized agriculture, this task is carried out by automatic irrigation computers.
Precision farming means that agricultural processes should be designed as precisely and optimally as possible. In this way, water, diesel, pesticides, and fertilizers can be saved in a targeted manner.
Optimizing the intelligent control of these processes, on the other hand, is the task of intelligent farming.
Modern production processes in agriculture generate large and varied amounts of data. Sensor data from agricultural machines, satellite, aerial images, weather and climate data, yields, cultivation methods, and soil properties result in a detailed picture of the relevant production processes.
The intelligent use and analysis of this amount of data through modern data science methods have the potential to expand knowledge about these processes significantly and, at the same time, to optimize operations in a variety of ways.
The European Commission already warned in 2011: “Many of today’s food-producing systems endanger the capacity of the earth to generate enough food in the future.” So there is an urgent need for action: “Resource conservation” is the buzzword among agricultural scientists.
Even considering the constantly growing world population, agriculture is confronted with the problem of high demand. So more efficient methods need to be developed to meet future needs.
Big data enables the simulation of scenarios in very complex systems. The analysis of this massive amount of data can reveal new connections and explain complex phenomena. In this way, research on arable land, the so-called “on-farm research,” is virtually possible.
Nevertheless, data alone does not create knowledge. Klaus-Herbert Rolf, Head of Marketing and Sales at 365FarmNet, thinks: “We have to move from Big Data to Smart Data.” Smart data means valuable, high-quality, and secure data.
Through the sustainable use of resources and needs-based treatment in agriculture and animal husbandry, the digitization of agriculture promises positive effects for the environment.
According to the Bavarian State Institute for Agriculture, digital farmers get by with ten percent fewer herbicides and 20 percent less fuel than farmers who do without sensors and self-driving systems.
Digitization, Agriculture 4.0, and Big Data continue to lead to a significant reduction in costs and an increase in the efficiency of agricultural production. This makes agriculture more competitive and can better withstand competitive pressure on the world market.
High quality and a favorable price/performance ratio of the food consequently lead to a greater acceptance of the agricultural sector within society.
However, the digitization of agriculture requires the necessary framework conditions. The German Farmers’ Association sees the biggest problem in the often poor internet connections. This is why the federal and state governments are calling for nationwide internet coverage.
In addition to the future-proof expansion of the digital infrastructure, interfaces and products from different manufacturers must also be standardized.
But digital progress in agriculture also has a downside. Experts assume that 42 percent of employees in Germany have a job that could be digitized or automated in around 20 years.
For agricultural companies, the question arises as to whether digitization impacts farm structures or the farmer’s workplace.
Agriculture 4.0 in connection with data science offers great potential for companies and society and allows us to achieve economic, social, and ecological progress.
Digitization is progress for agriculture if it preserves the entrepreneurial autonomy of farmers and strengthens and expands the role of agriculture at the heart of society.
However, so that knowledge is not lost and the goals of digital agriculture can be achieved, monopolized access to the data must be prevented.
To achieve this, researchers from the Leibniz Institutes are calling for public networking. Adequate nutrition can only be guaranteed if the knowledge gained is accessible to all parties.
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