Linear Regression Models to Estimate Soil Liquid Limit and Plasticity Index From Basic Soil Properties

Seybold, Cathy A.; Elrashidi, M. A.; Engel, R. J.

doi:10.1097/ss.0b013e318159a5e1

Cited by 40 publications

(71 citation statements)

References 10 publications

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“…In lieu of measuring LL, Seybold et al [29] derived linear regression equations for LL using percentage total clay, percentage organic carbon, water content at −1,500 kPa soil water potential, cation exchange capacity, percentage linear extensibility, and bulk density as regression factors. The factors used to provide the "best fit" regression model depended upon taxonomic soil order.…”

Section: Plant Available Watermentioning

confidence: 99%

LLWR Techniques for Quantifying Potential Soil Compaction Consequences of Crop Residue Removal

Benjamin

Karlen

2014

Bioenerg. Res.

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Harvesting crop residues for bioenergy or bioproduct production may decrease soil organic matter (SOM) content, resulting in the degradation of soil physical properties and ultimately soil productivity. Using the least limiting water range (LLWR) to evaluate improvement or degradation of soil physical properties in response to SOM changes has generally been hampered by the extensive amount of data needed to parameterize limiting factor models for crop production. Our objective was to evaluate five pedotransfer functions to determine their effectiveness in predicting soil water holding capacity in response to different SOM levels. Similarly, two other pedotransfer functions were evaluated to determine the effects of SOM on cone index values. Predictions of field capacity and wilting point water content as well as the cone index-water content-bulk density relationship of soil strength using the pedotransfer functions were compared with field data from two tillage experiments near Akron, CO that had a range of SOM concentrations. Equations previously developed by da Silva and Kay gave the best estimates of LLWR for the pedotransfer functions we evaluated. These equations were then used to illustrate LLWR changes in response to different soil and crop management practices on a Duroc loam near Sidney, NE. The results showed that tillage and, possibly, soil erosion decreased the LLWR as tillage intensity increased. Therefore, we recommend that crop residue removal rates be limited to rates that maintain or increase SOM content to ensure soil physical conditions are not degraded.

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Section: Plant Available Watermentioning

confidence: 99%

LLWR Techniques for Quantifying Potential Soil Compaction Consequences of Crop Residue Removal

Benjamin

Karlen

2014

Bioenerg. Res.

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“…Plastic limit (LL-PL) refers to the plasticity index (PI) in terms of moisture content. Plasticity, on the other hand, is the ability of the soil to be exposed to a deformation which cannot be reversed without cracking or breaking at a constant volume [11].…”

Section: Introductionmentioning

confidence: 99%

“…However, identification of LL and PI is not a part of routine soil study definition analysis, and is expensive and time consuming. These are conducted only once, and such data are not generally useful [11]. Traditionally, manually manipulating the liquid limit and plastic limit data for the soil (attempts to improve) can cause significant failures [23].…”

Section: Introductionmentioning

confidence: 99%

“…Atterberg limits define the condition of the soil with respect to the relationships between the grain content of the soil and the water and the changing water content [10]. Seybold et al [11], defined the limits of consistency as the limit moisture content which is the degree of resistance against deformation in the classification of water content of the soil, and emphasized the importance of the role they play in the classification of swelling potential and cohesion of the soil along with factors used to describe the soil such as shear strength, bearing capacity, and compressibility [11]. Moreover, Atterberg limits are the lower and upper limits, namely, liquid (W L = LL) and plastic limit (W P = PL) values, which define the plasticity of fine-grained soils, and bear great importance in the assessment of some engineering properties of the soils.…”

Section: Introductionmentioning

confidence: 99%

“…An even further reduction of the water content will no longer lead to a reduction in the volume and the soil will exhibit a brittle behavior; the water content of this condition is called water retention or shrinkage limit (W R = R L ) [9]. Briefly, liquid limit is the water content at which liquid changes its phase from liquid to plastic; plastic limit is the water content at which soil changes its phase from plastic to semi-solid; and shrinkage limit is the water content at which soil changes its phase from semi-solid to solid [9] [11].…”

Section: Introductionmentioning

confidence: 99%

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Determination of the Plasticity Index of Soils with Fine-Grained Soils Using Methylene Blue Test

Otçu¹,

Uzundurukan²,

Kaplan³

2017

GEP

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The amount of fine material available in the soil is significant in Atterberg limits and methylene blue tests. In the context of Atterberg limits, increased amount of clay minerals contained in the soil increases liquid and plastic limit values; however, increasing sand content reduces the moisture content reducing the water retention capacity of the soil which in return reduces the plasticity index (PI) value. In the case of methylene blue test, which is used to specify the quality of the amount of fine material, existence of clay in the medium increases the pollution level of the sand and the amount of methylene solution (V 1 ) used. In this study, soil classes were determined and pollution rates were identified with Atterberg limits, pycnometer, sieve analysis, hydrometer analysis and methylene blue tests conducted on 11 different natural soil samples collected from different regions. From the data obtained, first the relationship between PI and methylene blue (MB) was examined and was evaluated according to the results of the "single regression" method. Furthermore, the other coefficient of uniformity (C u ), coefficient of graduation (C c ), unit weight of soils (γ s ) parameters obtained from experimental studies were also subjected to "multiple regression analysis" in order to reveal their impact on the MB and this impact was confirmed taking both statistical analyses into account.

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Prediction of Soil Plasticity Index with the Use of Regression Analysis and Artificial Neural Networks: A Specific Case for Bakırköy District

Arama

Yücel

Akin

et al. 2020

Advances in Intelligent Systems and Computing

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Linear Regression Models to Estimate Soil Liquid Limit and Plasticity Index From Basic Soil Properties

Cited by 40 publications

References 10 publications

LLWR Techniques for Quantifying Potential Soil Compaction Consequences of Crop Residue Removal

LLWR Techniques for Quantifying Potential Soil Compaction Consequences of Crop Residue Removal

Determination of the Plasticity Index of Soils with Fine-Grained Soils Using Methylene Blue Test

Prediction of Soil Plasticity Index with the Use of Regression Analysis and Artificial Neural Networks: A Specific Case for Bakırköy District

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