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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
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National Academy of Agricultural Sciences (NAAS)
NAAS Score: *5.38 (2020)
[Effective from January 1, 2020]
For more details click here

ICV 2018: 95.39
Index Copernicus ICI Journals Master List 2018 - IJCMAS--ICV 2018: 95.39
For more details click here

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PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : editorijcmas@gmail.com / submit@ijcmas.com
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2018: 95.39
NAAS RATING 2020: 5.38

Int.J.Curr.Microbiol.App.Sci.2018.7(10): 963-972
DOI: https://doi.org/10.20546/ijcmas.2018.710.107


Assessment of Saturated Hydraulic Conductivity of Red and Lateritic Soils under Diverse Land Topography and Vegetation Using Classical Statistical Analysis
B.G. Momin1*, R. Ray1 and S.K. Patra2
1Department of Soil and Water Conservation
2Department of Agricultural Chemistry and Soil Science, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur- 741 252, West Bengal, India
*Corresponding author
Abstract:

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.


Keywords: Saturated hydraulic conductivity, Red and lateritic soil, Multiple regression equation, Principal component analysis, Minimum data set
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How to cite this article:

Momin, B.G., R. Ray and Patra, S.K. 2018. Assessment of Saturated Hydraulic Conductivity of Red and Lateritic Soils under Diverse Land Topography and Vegetation Using Classical Statistical Analysis.Int.J.Curr.Microbiol.App.Sci. 7(10): 963-972. doi: https://doi.org/10.20546/ijcmas.2018.710.107