Observational analysis revealed effective soil assessment through digital technologies in agriculture, indicating innovative practices may improve crop management.
In the conditions of intensively developing digital technologies, agriculture is also an active environment for their application. The article demonstrates some of the capabilities of the intelligent Scanfield-5S system and the integrated DSC - "Digital Soil Cube" for assessing the condition of the soil. The DSC method uses non-contact measurement of electrical conductivity (ECa) up to 0.4m depth in the soil. The study was usually conducted after harvest and before agricultural operations for the next crop. All collected ECa data are georeferenced. An adaptive soil sampling scheme was applied, which is specific for a given field. The number of sampling sites was determined after applying a graph-analytical method. A high confidence probability (over 80%) was obtained from the ECa data, which is a confirmation of the suitability of the method. Analyses were performed for bulk density (BD), relative humidity (dW), clay content (Clay), organic matter (OM) and activated carbon (C_(act.)) in the soil. The presented results characterize the soil as homogeneous with relatively good biological indicators (OM and C_(act.)). The adaptive soil sampling scheme and the obtained regression models for the soil parameters are specific to the studied field. The regression models for the observed parameters are linear and are presented through spatial resolution maps. The Scanfield-5S system provides solutions such as variable rate maps (VRA), soil carbon prediction, and overall soil health assessment. The digital soil model created using the DSC method is specific to the field under study, but has the potential for universality.
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Bratoev et al. (2025) studied this question.
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