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Particle-size distribution models for the conversion of Chinese data to FAO/USDA system.

Shangguan W, Dai Y, García-Gutiérrez C, Yuan H - ScientificWorldJournal (2014)

Bottom Line: The performance of PSD models was affected by soil texture and classification of fraction schemes.The performance of PSD models also varied with clay content of soils.The Anderson, Fredlund, modified logistic growth, Skaggs, and Weilbull models were the best.

View Article: PubMed Central - PubMed

Affiliation: College of Global Change and Earth System Science, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China.

ABSTRACT
We investigated eleven particle-size distribution (PSD) models to determine the appropriate models for describing the PSDs of 16349 Chinese soil samples. These data are based on three soil texture classification schemes, including one ISSS (International Society of Soil Science) scheme with four data points and two Katschinski's schemes with five and six data points, respectively. The adjusted coefficient of determination r (2), Akaike's information criterion (AIC), and geometric mean error ratio (GMER) were used to evaluate the model performance. The soil data were converted to the USDA (United States Department of Agriculture) standard using PSD models and the fractal concept. The performance of PSD models was affected by soil texture and classification of fraction schemes. The performance of PSD models also varied with clay content of soils. The Anderson, Fredlund, modified logistic growth, Skaggs, and Weilbull models were the best.

Show MeSH
Percentage of soils of T3 scheme for which radj2 or AIC are the best for a given model.
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Related In: Results  -  Collection


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fig3: Percentage of soils of T3 scheme for which radj2 or AIC are the best for a given model.

Mentions: Though the performances evaluated by radj2 and AIC were quite similar on the whole (Figures 1 and 2), the best model according to different criteria can be different for a specific soil. Figure 3 shows the percentage of cases where a model was the best according to radj2 and AIC for soils of the T3 scheme. The percentage of best cases according to radj2 for the AD and F4P models was smaller than that according to AIC, while the opposite happened to the S and ONL models.


Particle-size distribution models for the conversion of Chinese data to FAO/USDA system.

Shangguan W, Dai Y, García-Gutiérrez C, Yuan H - ScientificWorldJournal (2014)

Percentage of soils of T3 scheme for which radj2 or AIC are the best for a given model.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4121012&req=5

fig3: Percentage of soils of T3 scheme for which radj2 or AIC are the best for a given model.
Mentions: Though the performances evaluated by radj2 and AIC were quite similar on the whole (Figures 1 and 2), the best model according to different criteria can be different for a specific soil. Figure 3 shows the percentage of cases where a model was the best according to radj2 and AIC for soils of the T3 scheme. The percentage of best cases according to radj2 for the AD and F4P models was smaller than that according to AIC, while the opposite happened to the S and ONL models.

Bottom Line: The performance of PSD models was affected by soil texture and classification of fraction schemes.The performance of PSD models also varied with clay content of soils.The Anderson, Fredlund, modified logistic growth, Skaggs, and Weilbull models were the best.

View Article: PubMed Central - PubMed

Affiliation: College of Global Change and Earth System Science, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China.

ABSTRACT
We investigated eleven particle-size distribution (PSD) models to determine the appropriate models for describing the PSDs of 16349 Chinese soil samples. These data are based on three soil texture classification schemes, including one ISSS (International Society of Soil Science) scheme with four data points and two Katschinski's schemes with five and six data points, respectively. The adjusted coefficient of determination r (2), Akaike's information criterion (AIC), and geometric mean error ratio (GMER) were used to evaluate the model performance. The soil data were converted to the USDA (United States Department of Agriculture) standard using PSD models and the fractal concept. The performance of PSD models was affected by soil texture and classification of fraction schemes. The performance of PSD models also varied with clay content of soils. The Anderson, Fredlund, modified logistic growth, Skaggs, and Weilbull models were the best.

Show MeSH