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.

中文翻译：

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基于从近端土壤传感数据生成的高分辨率土壤 pH、质地和 SOM 地图的精确石灰管理指南

土壤酸化是由自然遗传过程和人为影响引起的，但可以通过定期施用石灰来抵消。尽管存在用于可变速率石灰 (VRL) 的传感器和涂抹器，但没有使用这些工具或帮助在实践中实施 VRL 的既定策略。因此，本研究旨在为基于近端土壤传感的特定地点的石灰化提供指导。首先，使用移动传感器生成石灰相关指标（pH、土壤质地和土壤有机质含量）的高分辨率土壤图。土壤酸度由两个离子选择性锑电极预测（RMSEpH：0.37）；土壤质地是通过表观电阻率测量值和自然土壤中的伽马辐射（RMSEclay：0.046 kg kg-1）相结合来预测的；土壤有机质 (SOM) 状态通过红色 (660 nm) 和近红外 (NIR, 970 nm) 光学反射测量 (RMSESOM: 6.4 g kg-1) 的组合进行预测。其次，为了解决田间土壤的高变异性（pH 值变化 2.9 个单位，粘土含量变化 0.44 kg kg-1，SOM 变化 5.5 g kg-1），一种成熟的经验石灰推荐算法，代表最佳管理实践调整了德国的石灰用量，并确定了石灰需求 (LR)。生成的工作流程应用于德国东北部 25.6 公顷的试验场，并将变量 LR 与传统的统一 LR 进行比较。比较表明，在均匀施石灰方法下，63% 的田地将被约 12 吨石灰过度施肥，