On Particle‐Size Distributions in Soils

Wu, Qixin; Borkovec, Michal; Sticher, H.

doi:10.2136/sssaj1993.03615995005700040001x

Cited by 130 publications

(66 citation statements)

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“…These results indicated that LDM underestimated clay content relative to SPM by an average of 45.1% but overestimated silt content by an average of 18.3% in the soils of the Loess Plateau, consistent with other findings for diverse soil textures (Loizeau et al, 1994;Konert and Vandenberghe, 1997;Eshel et al, 2004;Shein et al, 2006;Yang et al, 2009;Wang et al, 2013a). Beuselinck et al (1998), however, reported that LDM underestimated the clay fraction of silty soils but generally overestimated the clay fraction of milled quartz samples, and Wu et al (1993) and Muggler et al (1997) reported agreement between the two methods.…”

Section: Comparison Of Particle-size Distributions Between Laser-diffsupporting

confidence: 88%

“…For example, LDM underestimated clay fractions and overestimated silt fractions compared with SPM (Konert and Vandenberghe, 1997;Beuselinck et al, 1998;Eshel et al, 2004;Yang et al, 2009). A few study, however, reported good agreement between the two methods (Wu et al, 1993;Muggler et al, 1997;Cheetham et al, 2008). These differences in PSDs between the two methods were due to differences in methodology, mineralogy, refraction index values of the samples, and particle morphology (Zobeck, 2004).…”

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confidence: 99%

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Determination of Soil Texture by Laser Diffraction Method

Yang

Zhang

et al. 2015

Soil Science Society of America Journal

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The laser-diffraction method (LDM) can rapidly determine soil particlesize distributions (PsDs), but LDM-derived PsDs cannot be directly used to classify soil textures by referring to the standards of the classical sievepipette method (sPM). Our objectives were to explore calibration models for converting PsD data from LDM (volume, %) to sPM (mass, %), and to evaluate the precision of textural classification by using LDM data. we determined the PsDs using both methods for 235 soil samples of various textures collected from three typical land uses, on the Loess Plateau of China. The LDM generally underestimated clay fractions by an average of 45.1%, and overestimated silt fractions by an average of 18.3% compared with sPM. Differences in PsD data between the two methods, indicated by coefficient Cs, increased with increasing clay contents for the 235 samples (P < 0.05). Three calibration models could, however, convert the clay, silt, and sand contents from the volume percentage (LDM) to the mass percentage (sPM). After the conversion, the mean coefficient C between the two methods decreased from 7.9 to 4.1% for the validation samples (n = 78). The distributions of soil textures within the usDA textural triangle agreed well in 71 of the 78 samples, for measured and converted PsD data. The three types of land use did not affect the differences between measured and converted PsD data (P > 0.05). soil textures can thus be rapidly determined by converting PsD data from the faster volume-based LDM to data equivalent to the mass-based sPM, independent of land-use type.

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Section: Comparison Of Particle-size Distributions Between Laser-diffsupporting

confidence: 88%

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confidence: 99%

Determination of Soil Texture by Laser Diffraction Method

Yang

Zhang

et al. 2015

Soil Science Society of America Journal

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“…By the same token, Prosperini and Perugini (2008) partitioned the whole PSD of soil samples into two fractal scaling domains and obtained the fractal dimensions ranging from 0 to 3. Millán et al (2003) compared the fitness of piecewise fractal model with nonlinear and log-linear regressions by using the experimental data of the PSD for a clay soil and a loam soil (Wu et al 1993, Bird et al 2000. The linear regression to log-transformed data showed some lack of fit, as reflected by the low coefficient of determination (0.75), whereas the piecewise law with respect to high correlation (0.98) is regarded to be better.…”

Section: Piecewise Fractal Modelmentioning

confidence: 99%

Fractal analysis in particle dissolution: a review

Bao

Long

et al. 2014

Reviews in Chemical Engineering

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Abstract:Fractal is a geometric language to describe the objects, the systems, and the phenomenon spatially and temporally. This paper reviews the literature on fractal models developed to describe the dissolution of particles. Dissolution, the process by which a solid forms a homogeneous mixture with a solution, is the behavior of a population of particles rather than a single one in most of the cases. The fractal models developed for the particle population are reviewed on the basis of two key particle surface properties, namely, the surface fractal nature and the chemical reactivity of particle surfaces. In terms of the surface fractal nature, fractals have been used to describe the change in the superficial roughness of particles, surface area-particle size relation, and particle size distribution (PSD). In terms of the reactive fractal dimensions, the models that describe the dissolution process have been developed to obtain the empirical noninteger exponent, the reactive fractal dimension that can dictate the chemical reactivity of a solid surface. The comparison between the surface fractal dimension and the reactive fractal dimension provides the dissolution mechanisms in many aspects of surface morphology. Further research is necessary to modify the current models to coincide with the real industrial processes and production and to develop the specific models for a better understanding of many processes involving the dissolution of particles encountered in many areas, including pharmaceutical and chemical applications and hydrometallurgy.

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“…Primary minerals originate from weathering of a parent material, and generally present in the sandand silt-sized fractions, while secondary minerals such as clay minerals are the result of formation of new minerals (Wu et al 1993;Posadas et al 2001). Particle-size distributions of soils are often used to estimate other soil properties such as soil moisture characteristics and hydraulic conductivity (Bittelli et al 1999;Khodaverdiloo et al 2011), thus accurate estimation of soil properties strongly depends on the accuracy of particle size determination.…”

Section: Introductionmentioning

confidence: 99%

Soil particle size distribution and solid fractal dimension as influenced by pretreatments

Günal

Erşahin

et al. 2011

Tarım Bilimleri Dergisi

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Soil particle-size distributions can provide valuable information on the processes and products of soil formation. The purpose of this study was to assess the pretreatment effect on the particle size distribution and corresponding fractal dimension of particle size (D s ). Twenty nine soil samples were collected from diverse climatic and pedogenic conditions with diverse particle size distributions, calcium carbonate and organic matter contents. To evaluate the effect of pretreatment on soil particle-size distribution, four different types of particle size distributions and fractal dimension values were obtained. Treatments included, 1) no pretreated, 2) organic matter removed with H 2 O 2 , 3) calcite (CaCO 3 ) removed with NaOAc, and 4) organic matter and calcium carbonate removed. Clay content ranged from 12.5 to 66.5%, organic matter varied from 0.05 to 4.25%, and calcium carbonate content ranged from 5.57 to 60.09%. The difference in clay content before (42.36%) and after (44.61%) pretreatment of organic matter was significant (P<0.05) but the same pretreatment didn't yield any significant differences in sand, silt and fractals. However, fractal and sand content obtained after calcium carbonate removal were significantly different from those of non-pretreated samples (P<0.01 and P<0.05, respectively). Dissolving calcium carbonate probably removed the clay sized calcium carbonate particles which were considered within the clay fraction. Therefore, the lowest mean fractal values (Ds c =2.8343 and Ds oc =2.8336) were obtained after calcium carbonate removal. The study results revealed that pretreatments affected the rates of particle size distributions. However, the differences in clay, silt, and sand contents obtained when pretreated together with H 2 O 2 and NaOAc were not significantly different. 218 ÖZETToprak parçacık büyüklük dağılımı toprak oluş işlemleri ve ürünleri hakkında önemli bilgiler sağlamaktadır. Bu çalışmanın amacı, ön muamelenin parçacık büyüklük dağılımına ve buna karşılık gelen parçacıkların fraktal boyuna (Ds) etkisini belirlemektir. Farklı iklim ve toprak oluşum işlemleri altında bulunan ve parçacık büyüklük dağılımı, kalsiyum karbonat ve organik madde içerikleri değişken olan yirmi dokuz toprak örneği toplanmıştır. Ön muamelenin parçacık büyüklük dağılımına etkisini değerlendirmek için, dört farklı şekilde parçacık büyüklük dağılımı ve fraktal boyut değerleri elde edilmiştir. Uygulamalar 1)kontrol (muamele yapılmayan), 2) H 2 O 2 ile organik maddenin uzaklaştırılması 3) kalsit'in (CaCO 3 ) NaOAc ile uzaklaştırılması ve 4) organik madde ve kalsiyum karbonatın uzaklaştırılması şeklindedir. Örneklerin kil içeriği %12.5 ile %66.5, organik madde %0.05 ile %4.25 ve kalsiyum karbonat içeriği %5.57 ile %60.09 arasında değişmektedir. Organik madde uzaklaştırılmadan önce ve sonraki kil içeriği istatistiksel olarak önemli (P<0.05) iken bu fark silt ve kum içeriği için ve fraktal değerleri için önemli bulunmamıştır. Bununla birlikte, kalsiyum karbonat uzaklaştırılan örneklerin fraktal değe...

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On Particle‐Size Distributions in Soils

Cited by 130 publications

References 0 publications

Determination of Soil Texture by Laser Diffraction Method

Determination of Soil Texture by Laser Diffraction Method

Fractal analysis in particle dissolution: a review

Soil particle size distribution and solid fractal dimension as influenced by pretreatments

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