Analysis of Soil Variability Measured With a Soil Strength Sensor

Hanquet, Bernard; Sirjacobs, Damien; Destain, Marie‐France; Frankinet, Marc; Verbrugge, Jean-Claude

doi:10.1023/b:prag.0000032763.54104.b4

Cited by 30 publications

(8 citation statements)

References 10 publications

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“…The DF demanded by shanks have been used to map the soil compaction spatial variability in different agricultural systems, as proposed by Bergeijk et al (2001) and experimentally presented by Herzog et al (2004), Cepik et al (2005) and Conte et al (2007). The DF correlates with the physical attributes of soils, such as mechanical resistance to penetration (Hanquet et al, 2004;Conte et al, 2008).…”

Section: Resultsmentioning

confidence: 98%

Soil disturbance index as an indicator of seed drill efficiency in no-tillage agrosystems

Conte

Levien

Debiasi

et al. 2011

Soil and Tillage Research

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Section: Resultsmentioning

confidence: 98%

Soil disturbance index as an indicator of seed drill efficiency in no-tillage agrosystems

Conte

Levien

Debiasi

et al. 2011

Soil and Tillage Research

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“…existence of old meadow), and stress history (i.e. over-consolidated zones due to repeated passages of machines) (Hanquet et al, 2004). As a consequence, interpolation of the cartographic results to estimate the precompression stress or the compaction risk at the parcel level cannot be performed as it would lead to random errors.…”

Section: Discussionmentioning

confidence: 99%

Toward a tool aimed to quantify soil compaction risks at a regional scale: Application to Wallonia (Belgium)

D’Or¹,

Destain

2014

Soil and Tillage Research

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The spatial analysis of the soil compaction risk has been developed at the regional level and applied to Wallonia (Belgium). The methodology is based on the estimation of the probability of exceeding the preconsolidation stress due to the application of loads on the soil. Preconsolidation stresses (Pc) are computed from the pedotransfer functions of Horn and Fleige (2003) at pF 1.8 and 2.5 and classified into 6 categories ranging from very low Pc (< 30 kPa) to extremely high Pc (> 150 kPa). The computation requires the knowledge of pedological (texture, organic content), mechanical (bulk density, cohesion, internal friction angle), and hydraulic variables (water content available, non-available water content, air capacity, saturated hydraulic conductivity). These variables are obtained from databases like HYPRES or AARDEWERK or from pedotransfer functions. The computation of Pc takes into account the spatial structure of the data: in some cases, data are abundant (e.g. texture data) and spatial variability is taken into account through geostatistical methods. In other cases, the data is sparse but uncertainty information can be extracted from the knowledge of the statistical distribution. Maps of the most probable Pc class are produced. Uncertainty is computed as the classification error probability. Implementation of these methods in Wallonia showed that Pc values higher than 120 kPa are reached either on 64 % of the territory at pF 2.5 or on 55 % at pF 1.8. A higher uncertainty was found at pF 2.5 than at pF 1.8. Uncertainty was also found higher for clay and clayed loess than for other textural classes present in Wallonia. The risk of compaction is defined as the probability that Pc is exceeded by the stress created by a load applied to the soil at a depth of 40 cm, the loads being similar to those induced by agricultural or forestry tires. It appeared that subsoil compaction risks exist mainly in loamy forest soils with small coarse fragments supporting loads similar to that existing on logging machines. In the zones where the uncertainty is low, the developed tool could be used as a basis for providing policy measures in order to promote soil-friendly farming and forest practices.

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“…Form a fatigue analysis viewpoint, it is essential to account for the effects of the variability in tillage forces on the resulted stress on tillage machines. The current state of knowledge suggests that there are only experimental works available to estimate the spatial variability in tillage forces [15,16,17]. These methods do not provide a tool for estimating the life time of tillage tools due to fatigue as it cannot account for all affecting parameters.…”

Section: -Introductionmentioning

confidence: 99%

Theoretical analysis of the spatial variability in tillage forces for fatigue analysis of tillage machines

Al-kheer

Eid

Aoues

et al. 2011

Journal of Terramechanics

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This paper presents a new theoretical model to describe the spatial variability in tillage forces for the purpose of fatigue analysis of tillage machines. The proposed model took into account both the variability in tillage system parameters (soil engineering properties, tool design parameters and operational conditions) and the cyclic effects of mechanical behaviour of the soil during failure ahead of tillage tools on the spatial variability in tillage forces. The stress-based fatigue life approach was used to determine the life time of tillage machines, based on the fact that the applied stress on tillage machines is primarily within the elastic range of the material. Stress cycles with their mean values and amplitudes were determined by the rainflow algorithm. The damage friction caused by each cycle of stress was computed according to the Soderberg criterion and the total damage was calculated by the Miner's law.

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Analysis of Soil Variability Measured With a Soil Strength Sensor

Cited by 30 publications

References 10 publications

Soil disturbance index as an indicator of seed drill efficiency in no-tillage agrosystems

Soil disturbance index as an indicator of seed drill efficiency in no-tillage agrosystems

Toward a tool aimed to quantify soil compaction risks at a regional scale: Application to Wallonia (Belgium)

Theoretical analysis of the spatial variability in tillage forces for fatigue analysis of tillage machines

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