Prediction Models for Non-Destructive Identification of Compacted Soil Layers Based on Electrical Conductivity and Moisture Content

Crop root development, and in turn crop growth, is strongly influenced by soil strength and the mechanical impedance of compacted layers, which restrict root elongation and exploration. Because the depth and thickness of compacted layers vary across a field, their identification is essential for site-specific tillage and sustainable root-zone management. A sensing approach that can support future real-time identification of compacted layers after soil-specific calibration, which would enable variable-depth tillage, reducing mechanical impedance and improving energy-use efficiency while maintaining crop yields. This study aimed to develop and evaluate prediction models that can support future real-time identification of compacted soil layers using soil electrical conductivity (EC) and moisture content as non-destructive indicators. A sandy clay soil (48.6% sand, 29.3% clay, 22.1% silt) was tested in a soil-bin laboratory under controlled conditions at three moisture levels (13, 18, and 22% db.) and six depth layers (C1–C6, 0–30 cm) identified from the penetration-resistance profile to measure penetration resistance, shear resistance, and EC. Penetration and shear resistance increased toward the most resistant depth layer and decreased with increasing moisture content, whereas EC generally increased with both depth layer and moisture content. Linear regression models relating penetration resistance (R2=0.893) and shear resistance (R2=0.782) to EC and moisture content were developed and evaluated. Field validation in a paddy field of similar texture showed that predicted penetration resistance differed from measured values by 3–6% across the three compaction treatments evaluated. Root length density and root volume decreased with increasing machine-induced compaction, confirming the agronomic relevance of the modeled patterns and supporting the suitability of the proposed indicators. Together, these results demonstrate that EC and moisture content can potentially be used as non-destructive proxies for compacted-layer identification and provide a calibration basis for future on-the-go sensing systems to support site-specific, variable-depth tillage in agricultural fields.