A few years ago, the DMK Group, together with agricultural businesses and partners from academia and the field, launched a multi-year project to investigate precisely this question. The aim was to test measures for reducing greenhouse gas emissions under real-world conditions and to systematically analyse their effects. The starting point for the project – which was completed in 2025 and parts of which have been implemented in the cooperative’s operations – was the realisation that a significant proportion of emissions along the value chain arise in agricultural production, making this a key area for further development.
A project from practice, for practice
The focus was not on finding quick fixes, but on gaining robust insights from real-world experience. Several farms implemented measures across the entire production chain and documented their development over an extended period. The aim was not merely to examine individual measures, but above all to understand how they interact.
Learning on the farm: complexity rather than isolated solutions
Practical experience clearly shows that change rarely results from individual interventions, but rather from the interplay of many factors. Farmer Jörg Stottmeister sums it up: “There is no single measure that changes everything. The key is to look at the processes across the entire farm and understand the interrelationships.”
Florian Stümmler also describes the process as one of continuous development:
“We take a close look at what works on the farm and what needs adjusting – and develop step by step.”
Over the years, various approaches have been trialled – from adjustments to crop production and changes to feeding practices to optimisations in farm management and energy use. This has been complemented by technical solutions that enable more precise control of processes and improve the data foundation.
Data as the basis for decisions
A key aspect of the project was translating these approaches into operational practice. Henry Hashagen, Agri Business Manager and Project Leader, describes it as follows: “The crucial question for us was not just which measures are theoretically possible, but how they can actually be implemented on the farm. This is exactely where the farmers’ experience and the systematic analysis of the data help us.”
It is precisely this data transparency that has proved to be a key factor. “By analysing data, we gain a better understanding of our operations,” says Stottmeister, describing his experience. This makes it clear that further development is closely linked to the ability to make processes transparent and to make well-informed decisions on this basis.
Scientific context and a systemic perspective
Scientific support also helps to place practical experiences within a broader context. Environmental scientist Franz-Theo Gottwald describes the starting point as follows: “The dairy industry is part of a system that has developed over many decades.” Changes therefore affect not only individual processes, but entire structures. The developments are correspondingly long-term: “These are developments that take time and happen step by step,” says Gottwald.
From practice to strategic context
Against this backdrop, the strategic links of the project results also plays an important role. Dr Philipp Inderhees, Global Head of Corporate Strategy, Sustainability & Innovation, puts it this way: “The experiences gained from the farms help us to better understand how different approaches develop in practice and which framework conditions are crucial for their implementation. This understanding forms an important basis for the future direction along the value chain.”
This makes it clear that insights from practical experience do not stand in isolation but are incorporated into overarching considerations.
Exchange and Feasibility
At the same time, practical experience shows that changes cannot be implemented without effort. Investment, additional planning and the development of knowledge are often necessary requirements. This makes exchange between the different pilot farms with their individual site conditions sites all the more important. “Sharing experiences helps us to better contextualise measures and learn from one another,” says Stottmeister.
A review of recent years paints a nuanced picture. Changes in certain key performance indicators have been observed in individual farms; at the same time, it is clear how heavily the results depend on individual circumstances. Location, farm structure, weather conditions and management significantly influence the impact of measures.
Conclusion: Developing step by step
This multi-year project demonstrates that the further development of agricultural production systems is a complex and long-term process. Progress stems from a combination of various measures, practical trials and continuous reflection on one’s own farm operations.
The most important insight remains clear: there are no simple solutions – but there are approaches that can be developed step by step through systematic learning, exchange and thorough analysis.
