Soil organic matter (SOM) plays a key role in arable farming when it comes to sustainable land management, soil fertility, and resilience to climate extremes. Soils rich in SOM store more water, have better aeration, provide a habitat for soil organisms, and ensure stable nutrient availability. They also improve load-bearing capacity and soil structure—factors that significantly influence both crop yield and workability. In the face of increasing droughts, heavy rainfall events, and growing economic pressure, it is becoming clear: targeted SOM buildup is not only ecologically important but also economically essential.
SOM Accumulation: More than an Environmental Goal
SOM largely consists of organically bound carbon. Every additional percentage point of SOM in the topsoil can increase the soil’s water retention capacity by up to 20%. On light soils in particular, this can make the difference between securing a harvest or facing crop failure. In addition, SOM improves aggregate stability, supports biological activity, protects against erosion, and buffers nutrients—benefiting both soil health and plant growth. SOM levels can be increased through various farming practices. Diverse crop rotations including legumes and cover crops, undersown crops with long growing periods, and perennial species like clover-grass or alfalfa are especially effective. Depending on site conditions and management, annual carbon inputs of 0.2 to 0.8 tons per hectare are possible. Flower strips also contribute to SOM formation and promote biodiversity. However, the actual impact always depends on soil type, climate, rainfall distribution, and specific management practices.
Sound Advisory Work Needs Reliable Data
But how can SOM levels be reliably assessed? And how can advisors provide effective support without placing an excessive burden on the farming operation?
Two main tools are currently in use: humus balances and soil sampling.
- Humus balances are calculation models that estimate changes in SOM based on crop rotation, yields, fertilization, and cultivation practices. They are easy to apply, rely on available farm data, and provide a quick overview—indicating whether a system is SOM building, stable, or degrading. Models like VDLUFA or STAND are commonly used in practice. However, their accuracy is limited: especially over short time spans (under five years), they correlate poorly with measured values from soil samples. As such, they are most useful for awareness-raising, planning, and discussion—but not as a substitute for empirical data or as a basis for incentive mechanisms such as carbon payments.
- Soil sampling remains the gold standard for determining soil organic carbon (SOC) levels, which are a key component of SOM. However, the sampling effort and associated costs should not be underestimated. SOM levels can vary significantly within a single field due to factors like micro-aggregation, root development, and microclimatic differences. Traditional methods (3–6 mixed samples per field) often fail to capture this variability. Stratified grid sampling or more than 30 individual samples per field can significantly improve data quality—but require more time and financial resources. Nevertheless, regular, methodical soil sampling remains the most reliable method for tracking actual changes in SOM over time.
Combining Approaches
Modern strategies combine soil sampling with modeling to better reflect site-specific conditions. While basic humus balances primarily illustrate trends, more advanced models such as RothC—incorporating soil type, management history, and weather data—can provide more accurate projections. However, they require detailed inputs and technical expertise.
Satellite-based and other remote sensing technologies are also increasingly being explored to support large-scale soil monitoring. While these tools cannot yet determine SOM levels or short-term changes in SOC with sufficient accuracy at field level, they offer real potential for cost-efficient monitoring in the future. By identifying spatial variability, monitoring vegetation dynamics, and highlighting areas of interest, they can help target sampling efforts and guide advisory strategies. Crucially, remote sensing techniques must be calibrated with on-the-ground data—particularly soil samples—to produce reliable results. The integration of remote sensing, modeling, and structured soil sampling holds strong promise as a cost-effective approach to improving spatial resolution and decision-making in SOM management.
Targeted SOM buildup is not only ecologically important but also economically essential – Felix Baumann, Bioland.
Conclusion
In practical terms, humus balances are a helpful entry point for advisory work, strategic planning, and evaluating management options. They highlight potential improvements and can be easily integrated into digital farm tools. However, those seeking reliable insights into actual SOM levels will continue to rely on systematic, repeated soil measurements. A combination of both approaches—practical estimation tools and empirical monitoring—provides a robust foundation for soil- onscious, future-ready farming.
About the Author:
Bioland Beratung GmbH is a German consulting firm specializing in providing advice to farmers and businesses involved in organic agriculture. In OrganicClimateNET, it works as a National Coordinator.
Article by Felix Baumann
