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The spatial variability characterization of micronutrients is needed for agricultural quality produce and environmental safety. However, study on this aspect is weakly implicit. In present study, Global Positioning System (GPS)-based 283 surface soil samples were collected and analyzed for pH, electrical conductivity (EC), organic carbon (OC), and micronutrients. Classical results revealed that soils are slightly acidic pH, safe in EC, low to medium in OC, and non-calcareous. OC was in order of  Typic Haplustalfs-Chromic Haplusterts  (S8)&gt; Vertic Ustochrepts-Chromic Haplusterts  (S3)&gt; Typic Haplustalfs-Typic Haplustalfs  (S9)&gt; Typic Haplustalfs-Typic Ustipsammarts  (S7)&gt; Typic Haplusterts-Typic Ustorthents  (S6)&gt; Vertic Ustochrepts -Chromic Haplusterts  (S5)&gt;  Lithic Ustochrepts -Typic Haplusterts  (S4)&gt; Typic Haplusterts -Vertic Ustochrepts (S2)&gt; Typic Haplusterts-Typic Haplusterts  (S1). In soils, zinc (Zn) and hot water-soluble boron (HWS-B) in order of S4&gt;S5&gt;S7&gt;S9&gt;S3&gt;S2&gt;S8&gt;S1&gt;S6 and S1&gt;S2&gt;S3&gt;S4&gt;S5&gt;S9&gt;S6&gt;S7&gt;S8, respectively. Overall, about 54.06 and 9.89% soil samples to be deficient in Zn and HWS-B in study area, respectively. Geo-statistical results showed that the exponential model was best-fitted for pH, calcium carbonate (CaCO 3 ), OC, Zn and HWS-B and spherical model for EC and iron (Fe). However, the circular model was fitted for copper (Cu) and Manganese (Mn). The pH, EC, OC Zn, Cu, and Fe fall between 26 and 71%, which exhibit moderate spatial dependency. However, CaCO 3  and Mn show 81 and 76% Nugget/sill ratios, respectively. Variability maps also showed the prediction of micronutrients using geo-statistical method better than classical methods.

Characterization of Spatial Variability of Micro Nutrients in Soils: Classical Vs . Geo-Statistical Approach