TY - JOUR A1 - Bönecke, Eric A1 - Meyer, Swen A1 - Vogel, Sebastian A1 - Schröter, Ingmar A1 - Gebbers, Robin A1 - Kling, Charlotte A1 - Kramer, Eckart A1 - Lück, Katrin A1 - Nagel, Anne A1 - Philipp, Golo A1 - Gerlach, Felix A1 - Palme, Stefan A1 - Scheibe, Dirk A1 - Zieger, Karin A1 - Rühlmann, Jörg T1 - Guidelines for precise lime management based on high-resolution soil pH, texture and SOM maps generated from proximal soil sensing data JF - Precision Agriculture N2 - Soil acidification is caused by natural paedogenetic processes and anthropogenic impacts 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-specific 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 reflection measurements (RMSESOM: 6.4 g kg−1). Second, to address the high within-field 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 workflow was applied to a 25.6 ha test field 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 field 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. KW - Variable rate soil liming; Soil texture; Soil pH; Soil organic matter; Soil sensing; Site specific soil management Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:eb1-opus-4890 SN - 1385-2256 VL - 22 SP - 493 EP - 523 PB - Springer Nature ER - TY - CHAP A1 - Kling, Charlotte A1 - Schröter, Ingmar A1 - Vogel, Sebastian A1 - Bönecke, Eric A1 - Rühlmann, Jörg A1 - Gebbers, Robin A1 - Lück, Katrin A1 - Schubert, Torsten A1 - Gerlach, Felix A1 - Philipp, Golo A1 - Scheibe, Dirk A1 - Zieger, Karin A1 - Palme, Stefan A1 - Kramer, Eckart ED - Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF), T1 - Optimization of soil pH and crop yield based on a precision liming strategy guided by proximal soil sensing: Results of three on-farm field trails BT - Book of Abstracts T2 - Landscape 2021 Diversity for sustainable and resilient agriculture, Online conference, 20.-22.09.2021 N2 - Soil acidity is a key factor for soil fertility as it simultaneously influences several yield-relevant soil properties and thus the productivity of agricultural soils. Besides natural pedogenetic processes, on agricultural land, soil acidification is amplified by the removal of the harvested biomass as well as by the application of acidifying fertilizers. Therefore, regular lime application on agricultural fields is inevitable to sustain soil quality and productivity. In Germany, the standard method for defining the lime requirement of a soil is the VDLUFA framework of the German Advisory Board for Agricultural Analytics. The VDLUFA method uses look-up tables that define the lime requirement according to soil texture, soil pH (CaCl2) and soil organic matter (SOM) content (LVLF et al., 2008). To determine these lime-relevant parameters, fields should be subdivided into subunits of 3 to 5 ha. Within a subunit, one mixed sample from 15 to 20 samples should form a composite sample for further reference lab analysis. However, a uniform lime requirement determined for subunits of 3 to 5 ha is often in contrast to the real soil variability observed in the field (Kling et al., 2019). In order to reflect the within-field soil variability, a few studies have demonstrated the use of high-resolution proximal soil sensing (PSS) data as tools for variable rate (VR) lime application (Bönecke et al., 2020; Pätzold et al., 2020). However, there is a lack of studies that evaluate the feasibility and benefit of VR methods in on-farm field trails. Therefore, the aim of this study is to compare the performance of site-specific liming based on PSS to optimize soil pH and crop yield with that of commonly applied standard liming methods in Germany. To determine the effect and practicability of the VRA method, a multi-site-multi-year experiment was conducted between 2017 and 2020 on three sites in Brandenburg, Germany. The trial compared the effects on soil pH and crop yield of three lime management practices: variable-rate liming based on PSS data (VR-PS), uniform liming rate based on the VDLUFA standard method (UR), and no liming (ZR). Soil texture and soil pH were assessed with two mobile sensor platforms: the Geophilus system measuring apparent electrical resistivity (ERa) and Gamma-radiation and the Veris pH Manager (Veris Technologies Inc., Salina, KS, USA). Crop yields were obtained from revenue recordings of combine harvesters. Lime prescription maps were generated with an adapted and stepless VDLUFA algorithm, allowing a continuous CaO recommendation (Bönecke et al., 2020). Based on these maps, management zones were delineated to perform lime spreading with state-of-the-art technique. In this study, we outline the conceptual framework of the VR liming approach and present first results from the on-farm field trials to verify the VR approach for an optimized soil acidity management as well as consider whether the higher economic revenue can compensate for added costs for mapping services and spreading technologies. Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:eb1-opus-7741 SP - 292 ER - TY - JOUR A1 - Ruehlmann, Joerg A1 - Bönecke, Eric A1 - Gebbers, Robin A1 - Gerlach, Felix A1 - Kling, Charlotte A1 - Lück, Katrin A1 - Meyer, Swen A1 - Nagel, Anne A1 - Palme, Stefan A1 - Philipp, Golo A1 - Scheibe, Dirk A1 - Schröter, Ingmar A1 - Vogel, Sebastian A1 - Kramer, Eckart ED - Ciavatta, Claudio T1 - Predicting the Base Neutralization Capacity of Soils Based on Texture, Organic Carbon and Initial pH: An Opportunity to Adjust Common Liming Recommendation Approaches to Specific Management and Climate Conditions JF - Agronomy N2 -

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.

KW - - KW - acidification KW - organic carbon KW - lime KW - pedotransfer function KW - pH KW - soil KW - texture Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:eb1-opus-9435 SN - 2073-4395 VL - 13 IS - 11 PB - MDPI ER -