Abuzaid, A., Bassouny, M. (2018). Multivariate and Spatial Analysis of Soil Quality in Kafr El-Sheikh Governorate, Egypt. Journal of Soil Sciences and Agricultural Engineering, 9(8), 333-339. doi: 10.21608/jssae.2018.35804
A. Abuzaid; M. Bassouny. "Multivariate and Spatial Analysis of Soil Quality in Kafr El-Sheikh Governorate, Egypt". Journal of Soil Sciences and Agricultural Engineering, 9, 8, 2018, 333-339. doi: 10.21608/jssae.2018.35804
Abuzaid, A., Bassouny, M. (2018). 'Multivariate and Spatial Analysis of Soil Quality in Kafr El-Sheikh Governorate, Egypt', Journal of Soil Sciences and Agricultural Engineering, 9(8), pp. 333-339. doi: 10.21608/jssae.2018.35804
Abuzaid, A., Bassouny, M. Multivariate and Spatial Analysis of Soil Quality in Kafr El-Sheikh Governorate, Egypt. Journal of Soil Sciences and Agricultural Engineering, 2018; 9(8): 333-339. doi: 10.21608/jssae.2018.35804
Multivariate and Spatial Analysis of Soil Quality in Kafr El-Sheikh Governorate, Egypt
Soil and Water Department, Faculty of Agriculture, Benha University, Egypt
Abstract
A precise evaluation of soil quality (SQ) is important for sustainable land-use planning. An assessment of SQ was done in 674.13 km2 (67413 ha) of the agricultural lands in west of Kafr El-Sheikh Governorate, Egypt. Thirty soil profiles were dug and samples were collected and analyzed for different physicochemical properties. A score was assigned for each SQ indicator using linear scoring function. The soil quality index (SQI) was computed using three indices; additive index, weighted additive index and Nemoro index. Each SQI was calculated using two methods of indicator selection; total dataset (TDS) and minimum dataset (MDS) extracted by principal component analysis (PCA). Results showed that electrical conductivity, calcium carbonate, silt, bulk density and water holding capacity were included in the MDS that accounted for 84.37% of the total variance of the TDS. High significant correlations occurred between SQIs calculated using TDS and MDS under the three models, indicating high efficiency of the PCA to establish a MDS for the study area. The highest correlation and most prediction occurred when applying the weighted additive index. Further investigations are recommended to appraise indicators included in the MDS.
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