Journal of Agronomy and Field Innovations

Background: The soil fertility levels in Zea mays L. are characterized by inherent heterogeneity, while traditional methods of applying fertilizers evenly do not consider the variability of soil properties within the fields, thus leading to under-utilization of fertilizers and unstable crop yields. The application of GIS in combination with geostatistics allows for accurate descriptions of the variability of soil properties.
Objective: The purpose of the current study was to evaluate the variability of the properties of soil along a maize crop growing area using GIS techniques and to create the areas of precise management of soil fertility for specific locations.
Methods: Soil samples were collected using the grid sampling method with the reference of GPS coordinates. The samples were tested for their pH, electrical conductivity, organic matter, nitrogen, phosphorus and potassium content as well as for the presence of micronutrients. The process of spatial interpolation was carried out with the application of ordinary kriging and inverse distance weighting methods in GIS with the use of the semivariogram modeling technique.
Result: The properties of soil have demonstrated moderate to high spatial dependence with available Phosphorous and potassium having high spatial variability. Kriging method has shown superior performance compared to IDW regarding cross-validation accuracy. The fertility map has shown the presence of different fertility regions representing low, medium, and high fertility with high prospects for variable rate fertilization.
Conclusion: GIS-based spatial variability analysis offers an effective way of assessing soil fertility and can result in location-specific nutrient management which enhances fertilizer efficiency and helps enhance sustainable maize production.