Soil acidifcation is caused by natural paedogenetic processes and anthropogenic impact but can be counteracted by regular lime application. Although sensors and applicators for variable-rate liming (VRL) exist, there are no established strategies for using these tools or helping to implement VRL in practice. Therefore, this study aimed to provide guidelines for site-specifc liming based on proximal soil sensing. First, high-resolution soil maps of the liming-relevant indicators (pH, soil texture and soil organic matter content) were generated using on-the-go sensors. The soil acidity was predicted by two ion-selective antimony electrodes (RMSEpH: 0.37); the soil texture was predicted by a combination of apparent electrical resistivity measurements and natural soil-borne gamma emissions (RMSEclay: 0.046 kg kg−1); and the soil organic matter (SOM) status was predicted by a combination of red (660 nm) and near-infrared (NIR, 970 nm) optical refection measurements (RMSESOM: 6.4 g kg−1). Second, to address the high within-feld soil variability (pH varied by 2.9 units, clay content by 0.44 kg kg−1 and SOM by 5.5 g kg−1), a well-established empirical lime recommendation algorithm that represents the best management practices for liming in Germany was adapted, and the lime requirements (LRs) were determined. The generated workfow was applied to a 25.6 ha test feld in north-eastern Germany, and the variable LR was compared to the conventional uniform LR. The comparison showed that under the uniform liming approach, 63% of the feld would be over-fertilized by approximately 12 t of lime, 6% would receive approximately 6 t too little lime and 31% would still be adequately limed.
Guidelines for precise lime management based on high‑resolution soil pH, texture and SOM maps generated from proximal soil sensing data
Bönecke, E.; Meyer, S.; Vogel, S.; Schröter, I.; Gebbers, R.; Kling, C.; Kramer, E.; Lück, K.; Nagel, A.; Philipp, G.; Gerlach, F.; Palme, S.; Scheibe, D.; Zieger, K.; Rühlmann, J. (2020). Guidelines for precise lime management based on high‑resolution soil pH, texture and SOM maps generated from proximal soil sensing data. Precision Agric 22, 493–523 (2021). https://doi.org/10.1007/s11119-020-09766-8