Search

Liming is an effective measure to increase the soil pH and to counterbalance soil acidification. Therefore, the liming recommendations (LRs) for agricultural practice consider two aspects: changing the initial pH to the desired pH and compensating for all pH decreases taking place within the liming interval. The separation of these aspects is essential to optimize LRs and to minimize lime losses to the environment. Therefore, we developed a pedotransfer function (PTF) to calculate the lime demand to change the initial pH to the desired pH and compared the results with the LRs for agricultural practice. Applying this PTF to a set of 126 soil samples that were analyzed for base neutralization capacity could explain approximately 78% of the variability in the pH changes after the addition of different amounts of Ca(OH)2. Consequently, the lime demand to change the initial pH to the desired pH increased by approximately one-sixth compared to the lime demand proposed by the liming recommendation scheme, which is commonly used in Germany. From the numerical difference between the lime demand according to the LRs and the PTF, we calculated the annual acidification rates based on the soil texture, organic matter content and initial pH. Decoupling the abovementioned two aspects of LRs might be helpful to optimize the LRs by adapting to different regions, diverse management strategies and a changing climate.

There is currently a significant focus on oil organic carbon, as interest in mitigating climate change by increasing soil carbon stocks is leading to efforts to include this within carbon farming and the trade of CO2 certificates. In addition, soil organic carbon controls many other soil functions, such as soil productivity. However, results from long-term field experiments suggest that an ever-increasing carbon content in soil, at some point, will no longer increase productivity, but will cause environmental risks, especially from excess nitrogen. In Germany, the most widely recognized soil organic matter (SOM) balance method, VDLUFA (Association of German Agricultural Investigation and Research Institutions), addresses soil management only, without a relation to the soil carbon stock. To close this gap, a methodology is developed based on results from European long-term field experiments that allows for an assessment of agricultural management both in terms of the carbon input to soil and the amount of carbon stored in soil. Due to the transformation of carbon stock into carbon flux, it is possible to apply the classification scheme of the VDLUFA balance to the carbon content of topsoils. This provides information to qualify further decisions about fostering carbon accumulation. This was demonstrated on experimental results from Bad Lauchstädt, as well as on data from the German Agricultural Soil Inventory (BZE-LW) for arable soils on a regional scale.

For more than 40 years, farmers in Germany have used the fertilization recommendation schema provided by the Association of German Agricultural Investigation and Research Institutions (VDLUFA) to quantify the required lime (CaO) demand of arable mineral soils. To be applicable as guidelines in practice, the results of 30 years of fertilization experiments that studied the correlation between crop yields and the actual soil pH, the soil texture, and the soil organic matter (SOM) content were finally condensed into a look-up table system. However, because the original experimental data are no longer accessible, the purpose of this study is to reconstruct the interaction between the three soil parameters and their appropriate lime demands. Therefore, the class-based, stepwise approach of the look-up table system is transferred into a continuous, stepless approach using mathematical models. Under the precondition to preserve the pH-, texture- and SOM-dependent CaO amounts recommended in the look-up system (n = 317) to the greatest extent possible, the algorithm was successful; more than 99% of their variability could be explained by the models. This adaptation helps to meet the accuracy of present-day requirements of precision farming.