Evidence map›Paper›PMID 40293051›Full record

ArticleSensors (Basel, Switzerland)2025

Development and In-Field Validation of an Autonomous Soil Mechanical Resistance Sensor.

Valentijn De Cauwer, Simon Cool, Axel Willekens, Sébastien Temmerman, David Nuyttens, Tommy D' Hose, Jan Pieters, Sam Leroux

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Valentijn De CauwerTechnology and Food Science Unit, Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), 9820 Merelbeke-Melle, Belgium.ORCID 0009-0000-3548-543X
Simon CoolTechnology and Food Science Unit, Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), 9820 Merelbeke-Melle, Belgium.
Axel WillekensTechnology and Food Science Unit, Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), 9820 Merelbeke-Melle, Belgium.ORCID 0000-0002-3893-5632
Sébastien TemmermanTechnology and Food Science Unit, Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), 9820 Merelbeke-Melle, Belgium.
David NuyttensTechnology and Food Science Unit, Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), 9820 Merelbeke-Melle, Belgium.ORCID 0000-0002-4531-0526
Tommy D' HosePlant Science Unit, Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), 9820 Merelbeke-Melle, Belgium.
Jan PietersDepartment of Plants and Crops, Ghent University, 9000 Ghent, Belgium.ORCID 0000-0003-4034-9269
Sam LerouxDepartment of Information Technology, Ghent University, 9000 Ghent, Belgium.ORCID 0000-0003-3792-5026

Funding

Horizon Europe 101129644
6 · The paper itself

Abstract

Soil compaction is a widespread problem, leading to soil degradation, yield losses, and adverse environmental impacts. Nowadays, various measurement methods exist to assess and map soil compaction, with vertical cone penetration resistance measurements being one of the most commonly used. This method is easy, rapid, inexpensive, and generally accepted. However, manual penetration resistance measurements are time-consuming, labor-intensive, and often less accurate due to inconsistent penetration speed. To address these limitations, an automated penetrometer was developed and integrated on an autonomous robot platform, paving the way for high-resolution compaction mapping as a starting point for precision subsoiling to remediate soil compaction. The performance of this setup was validated in controlled and field conditions against a hand-held penetrometer. Therefore, experiments were conducted in soil-filled cylinders and on plots of a long-term field experiment, including measurements across spraying tracks. The automated penetrometer demonstrated high correlations with the hand-held device under controlled conditions, though the correlation was somewhat lower in the field due to the soil's heterogeneity. Deviations between the two measurement devices were likely caused by the inconsistent insertion speed of the hand-held penetrometer, particularly in soils with high penetration resistance. Both penetrometers successfully identified the plow pan at a depth of 30-40 cm but were unable to clearly show the effect of the long-term presence of spraying tracks.

Indexed as

automated penetrometerautonomous robotmechanical resistanceprecision agriculturesoil compactionsoil penetration resistancespraying tracksvalidation

Identifiers

PMID40293051
PMCPMC11946251

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.