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Title: Two-dimensional prediction of spatial variation in topsoil compaction of a sandy loam field-based on measured horizontal force of compaction sensor, cutting depth and moisture content
Authors: Mouazen, Abdul Mounem ×
Dumont, K
Maertens, Koen
Ramon, Herman #
Issue Date: Nov-2003
Publisher: Elsevier science bv
Series Title: Soil & tillage research vol:74 issue:1 pages:91-102
Abstract: The development of a topsoil compaction map, based on real-time measurement of the draught (D) of a compaction sensor provides a quick view of positions of extremely compacted zones. The measured D of a subsoiler, used as a compaction sensor was utilised to draw the two-dimensional spatial variation in soil compaction of a sandy loam field (Arenic Cambisol). On the basis of a previously developed formula, dry bulk density (rho(d)) indicating soil compaction was estimated as a function of the measured horizontal force, cutting depth (d) and moisture content (w). This formula was the output of a numerical-statistical hybrid modelling scheme, which aimed to estimate the variation in sensor D as a function of w, d and rho(d). The ARCVIEW 3.1 GIS software was used to draw the field maps of measurement and model-based rho(d), d, w. The measurement and model-based rho(d) ranged from 1343 to 1750 and from 1271 to 1523 kg m(-3), respectively. The model-based rho(d) was underestimated by a mean error of 14%. A comparison of measurement and model-based rho(d) maps indicates a similar tendency of spatial variation in soil compaction, particularly positions of extremely compacted zones. This allows providing the farmer with a compaction map, which illustrates the extreme zones of soil compaction. A correction factor of 14% in rho(d) is incorporated into the developed numerical-statistical model, which improved the magnitude of the model-based predicted soil compaction. Furthermore, the real-time measurement of w with better control of d might be helpful to improve the magnitude Of rho(d) predicted and spatial distribution of soil compaction. (C) 2003 Elsevier B.V. All rights reserved.
URI: 
ISSN: 0167-1987
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Division of Mechatronics, Biostatistics and Sensors (MeBioS)
× corresponding author
# (joint) last author

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