Assessment of saturated hydraulic conductivity of red and lateritic soils under diverse land topography and vegetation using classical statistical analysis.
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Title |
Assessment of saturated hydraulic conductivity of red and lateritic soils under diverse land topography and vegetation using classical statistical analysis.
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Creator |
Momin, B.G., Ray, R., Patra, S.K.
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Subject |
Saturated hydraulic conductivity, Red and lateritic soil, Multiple regression equation, Principal component analysis, Minimum data set
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Description |
Not Available
Saturated hydraulic conductivity of the red and lateritic soils was assessed from the basic properties using multivariate analysis techniques. The descriptive statistics showed that all the soil variables were normally distributed and mostly displayed moderate to strong correlation with each other. The stepwise multiple regression equation demonstrated that clay fraction was the key indicator in explaining most variability of the saturated hydraulic conductivity. The principal component analysis (PCA) was applied to reduce the number of original variables. It indicated that sand, particle density and porosity were the highest loaded variables in the first PCs; while silt, water holding capacity, porosity, electrical conductivity and organic carbon in the second PCs and clay, bulk density and water holding capacity in the third PCs, which altogether predicted 93.4% of the total variance. The regressive model for saturated hydraulic conductivity using minimum data set (MDS) from PCA such as sand, silt and WHC accounted for 94.3% of the variance was highly predictive than the other models studied. The MDS model may thus provide a potential tool for assessing the saturated hydraulic conductivity of the soils. Not Available |
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Date |
2019-11-26T04:52:47Z
2019-11-26T04:52:47Z 2018-09-10 |
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Type |
Article
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Identifier |
Momin, B.G., Ray, R., Patra, S.K., 2018. Assessment of saturated hydraulic conductivity of red and lateritic soils under diverse land topography and vegetation using classical statistical analysis. International Journal of Current Microbiology and Applied Sciences 7, 963-972.
ISSN: 2319-7706 http://krishi.icar.gov.in/jspui/handle/123456789/25402 |
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Language |
English
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Relation |
Not Available;
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Publisher |
Excellent Publishers
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