Like many other industries, agriculture is becoming increasingly digitalised. What is behind Agriculture 4.0?
Prof. Dr. Peter Breunig: From the farmers' point of view, Agriculture 4.0 means an easing of the burden of their work because their machines work more precisely. This makes it easier for them to make better decisions. However, networking is not only taking place within farms, but increasingly along the entire value chain. Today, for example, agricultural machinery dealers can remotely monitor their customers' machines and make suggestions on how to use them most efficiently and maintain them optimally.
And what's behind this from a technical perspective?
Prof. Dr. Patrick Noack: There are many buzzwords for digitalisation in agriculture: precision farming, smart farming, digital farming and Agriculture 4.0. In terms of content, they describe almost the same thing: methods that partially or fully automate processes and decisions based on data and information. It starts with automatic steering in tractors and continues with tractor functions being controlled by the implement (TIM). Implements include seed drills, sprayers or fertiliser spreaders. Conversely, the tractor can also control the implements via a control unit and thus, for example, control the spread rates and switch functions on or off.
Networking plays a key role here – both the networking of tractor and implement and the networking of vehicles with server-based data sources and services.
How has digitalisation already changed agriculture today? What more can digitalisation of agriculture bring in the future?
Prof. Dr. Patrick Noack: The most widespread are automatic steering systems, which can drive with high accuracy using satellite positioning. The automatic switching on and off of pesticide sprayers, fertiliser spreaders and seed drills has also quickly gained acceptance. These methods are independent of fruit type, soil and weather and are relatively easy to use. In livestock farming, more and more milking robots have been used in recent years.
In plant production, site-specific cultivation is certainly the next step. Innovative companies are already using it. It is based on adapting tillage, sowing, fertilisation and pesticides to differences in soil and plant development. This brings with it new requirements.
In the area of crop protection, there are promising approaches to using image processing and artificial intelligence to detect weeds and thus significantly reduce the use of pesticides. Such processes may become more important against the backdrop of increasing social and political pressure to significantly reduce the use of pesticides.
Robotics will also increasingly find its way into agriculture over the next few years. Although it is still unclear whether conventional tractors will drive autonomously across the field or whether lots of small robots will take over the work of one large tractor.
Can we run through this with an example?
Prof. Dr. Patrick Noack: Fertilisation with nitrogen is extremely important in plant production, as it determines the yield and quality of the harvested products to a large extent. Too little nitrogen fertilisation reduces yield and quality. On the other hand, supplying too much nitrogen reduces the gain and leads to nitrate entering the groundwater.
Nitrogen sensors measure the nitrogen content of the plants in real time, so that fertilisation can be adapted immediately. This means less nitrogen is needed for fertilisation and it can be optimally distributed in the field.
In a second step, the yield capacity of the soil can be very accurately estimated from soil measurement data (geoelectrics), satellite images and yield measurements. With this additional data, it is possible to calculate not only the current supply levels but also the expected total demand until harvest. Many digital methods are involved here too.
As a third step, an NIR sensor can be used in organic nitrogen fertilisation with slurry to measure the nutrient content of the slurry in real time. This method can also significantly reduce over- and under-fertilisation.
Digital methods and Agriculture 4.0 not only serve to optimise farm management, but can also help to protect resources at the same time.
AI or artificial intelligence is currently one of the world's major technical issues of the future. Will AI also find its way into agriculture and what will it look like?
Prof. Dr. Peter Breunig: Farmers may have to get used to the fact that AI makes better decisions than they do. This already applies to specific areas such as weed detection or the identification of plant diseases. It should be noted that it is not only the algorithms that are getting better, but also that more and more data is available to train AI systems. This means that AI in agriculture will increasingly produce better results and will relieve farmers of more and more decisions.
What agricultural areas does this concern?
Prof. Dr. Patrick Noack: In crop and livestock production, AI methods can significantly increase efficiency. Many factors have an impact on success. In livestock farming, there is interaction between genetics, feeding and husbandry conditions. In plant cultivation, yield and quality are affected by genetics, varying soil characteristics and climatic factors. It is impossible to describe the many input and output variables with classical mathematical models – AI is much better suited for this. Currently, the scientific implementation fails because the data basis is too small.
Sensors, data analysis, robotics – all this costs money. What companies is digitalisation intended for?
Prof. Dr. Patrick Noack: The digital methods and tools are manifold. Of course, not all tools are suitable for all businesses. In principle, the same applies as for other investments: if there is a return on investment, the purchase of systems or the use of services is worthwhile.
Prof. Dr. Peter Breunig: In the past, certain machines and technologies often only paid off for farms over a certain size, but with many digital solutions things are different: an app to identify disease in your stocks is worthwhile both for the small farmer in India and for the large company in Russia.
A glimpse into the future: what will a fully digitalised farm look like 10, 20, even 50 years from now?
Prof. Dr. Peter Breunig: Digitalisation is driving change in agriculture, but not for everything. Considering the progress made in biotechnology (genome editing) and alternative proteins (lab-grown meat), it is very difficult to make concrete predictions. However, one thing is very likely: due to the exponential development of many new technologies, the pace of change in agriculture will accelerate.
Prof. Dr. Patrick Noack: In principle, it is conceivable that food and feed could be produced without human intervention. The question then is whether farmers, society and consumers want this. It would always be cost-efficient and environmentally friendly if the systems worked reliably.
