Design, development, and field evaluation of a dual-mode robotic-human system for in situ soil compaction assessment in agricultural fields

• Developed a high-throughput robotic penetrometer for reliable in-field compaction mapping. • Enables precision management, including variable-rate tillage depth to protect plant growth. • Benchmarked against the FieldScout SC900, showing significant depth-mean agreement (R 2 ≈0.97; RMSE≈103 kPa (15 PSI)). • Fills a key measurement gap by quantifying compaction in highly tilled, heterogeneous fields. • End-to-end pipeline enables site-specific remediation i.e. Controlled traffic farming lanes and subsoiling. Soil compaction is a major constraint in mechanized agriculture. Its accurate measurement is essential for understanding machinery impacts, optimizing crop growth, and guiding soil management practices. However, its strong spatial and depth-wise variability makes it difficult to characterize with traditional hand-held penetrometers alone. This study aimed to develop and evaluate a robotic penetrometer system for field-scale compaction mapping in sandy-loam potato–forage rotations on Prince Edward Island (PEI), Canada, over two consecutive growing seasons (2024 and 2025) at six depths. In 2024, we collected co-located penetration-resistance profiles with a FieldScout SC900 and the robotic penetrometer in electrical-conductivity (EC) zones derived from SWAT Box maps in two potato fields. In 2025, after calibration, the robot was deployed on a regular grid in two alfalfa fields that had grown potatoes in the previous year. In total, depth-wise mean profiles from the two instruments showed excellent agreement (R 2 ≈0.97), while point-wise paired measurements exhibited moderate but positive correlation (R 2 ≈0.60), reflecting micro-scale heterogeneity and differences in insertion mechanics. Spatial results revealed low to moderate compaction with localized hotspots in the 2024 potato fields, but extensive, vertically coherent high-resistance zones in the 2025 alfalfa fields, indicating persistent subsoil compaction following intensive potato traffic and limited subsequent tillage. The study demonstrates that a calibrated robotic penetrometer can reproduce conventional measurements while providing higher spatial resolution, deeper and more consistent penetration, and seamless integration with geospatial analysis. These capabilities support controlled-traffic farming, targeted subsoiling, and data-driven decision support for managing soil structure in traffic-sensitive cropping systems.

Authors

Institutions

Publication Details

Journal
Computers and Electronics in Agriculture
Published
2026-04-16
DOI
https://doi.org/10.1016/j.compag.2026.111767
Primary Topic
Soil Mechanics and Vehicle Dynamics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Design, development, and field evaluation of a dual-mode robotic-human system for in situ soil compaction assessment in agricultural fields

Raheleh Malekian, Hassan Afzaal, Ryan Barrett, Charanpreet Singh et al.
Computers and Electronics in Agriculture
Soil Mechanics and Vehicle Dynamics
article

Design, development, and field evaluation of a dual-mode robotic-human system for in situ soil compaction assessment in agricultural fields

Raheleh Malekian, Hassan Afzaal, Ryan Barrett, Charanpreet Singh, Aitazaz A. Farooque, Yuvraj Singh Gill, Andrew Fraser, Gurjit S. Randhawa
article en

Abstract

• Developed a high-throughput robotic penetrometer for reliable in-field compaction mapping. • Enables precision management, including variable-rate tillage depth to protect plant growth. • Benchmarked against the FieldScout SC900, showing significant depth-mean agreement (R 2 ≈0.97; RMSE≈103 kPa (15 PSI)). • Fills a key measurement gap by quantifying compaction in highly tilled, heterogeneous fields. • End-to-end pipeline enables site-specific remediation i.e. Controlled traffic farming lanes and subsoiling. Soil compaction is a major constraint in mechanized agriculture. Its accurate measurement is essential for understanding machinery impacts, optimizing crop growth, and guiding soil management practices. However, its strong spatial and depth-wise variability makes it difficult to characterize with traditional hand-held penetrometers alone. This study aimed to develop and evaluate a robotic penetrometer system for field-scale compaction mapping in sandy-loam potato–forage rotations on Prince Edward Island (PEI), Canada, over two consecutive growing seasons (2024 and 2025) at six depths. In 2024, we collected co-located penetration-resistance profiles with a FieldScout SC900 and the robotic penetrometer in electrical-conductivity (EC) zones derived from SWAT Box maps in two potato fields. In 2025, after calibration, the robot was deployed on a regular grid in two alfalfa fields that had grown potatoes in the previous year. In total, depth-wise mean profiles from the two instruments showed excellent agreement (R 2 ≈0.97), while point-wise paired measurements exhibited moderate but positive correlation (R 2 ≈0.60), reflecting micro-scale heterogeneity and differences in insertion mechanics. Spatial results revealed low to moderate compaction with localized hotspots in the 2024 potato fields, but extensive, vertically coherent high-resistance zones in the 2025 alfalfa fields, indicating persistent subsoil compaction following intensive potato traffic and limited subsequent tillage. The study demonstrates that a calibrated robotic penetrometer can reproduce conventional measurements while providing higher spatial resolution, deeper and more consistent penetration, and seamless integration with geospatial analysis. These capabilities support controlled-traffic farming, targeted subsoiling, and data-driven decision support for managing soil structure in traffic-sensitive cropping systems.

Computers and Electronics in AgricultureVol. 248
University of Prince Edward Island (CA), University of Guelph (CA)
Natural Sciences and Engineering Research Council of Canada
Zero hunger
Openalex Percentile: Top 8%
Soil Mechanics and Vehicle Dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.