Delineation of nutrient management zones for precise fertilizer management in wheat crop using geo-statistical techniques

Understanding the variability in crop yield in relation to the spatial variationsin soil properties can help to more efficiently apply agricultural inputs on a site-specific basis. This study was designed to characterize and quantify the spatialvariation in soil properties and wheat yield and to delineate prescription maps forsite- specific fertilization. A wheat field was selected at the research farm of theUniversity of Agriculture, Faisalabad, Pakistan, and a grid pattern (30 m * 30 m)was established at the experimental sites to collect soil and crop yield samples attwo sampling depths (0– 15 & 15– 30 cm). The soil samples were analysed for soilnitrogen (N), phosphorus (P), potassium (K), pH, electrical conductivity (EC),soil organic matter (SOM) and saturation (S) at both sampling depths. The loca-tions of the sampling points and field boundary were marked with a GPS receiver.Results of classical, geo-statistical and interpolated maps revealed significant spa-tial variability in soil properties and crop yield, demanding for site-specific nutri-ent management. The cluster analysis was performed to group the soil and yielddata into five productivity zones termed as 'very low', 'low', 'medium', 'high' and'very high' without prior knowledge of productivity potential with the internalhomogeneity and external heterogeneity at a similarity level of greater than 70%.Results of correlation matrix suggested significant relationships among the cropyield and the soil properties. Results of means comparison in different produc-tivity zones indicated that the crop yield and soil properties were significantlydifferent in developed management zones except 'low' and 'very low' zones. Significant variation of soil nutrients in very low-to-very high productivity zones at both sampling depths suggested that the soil nutrients in combination with soil pH and organic matter can be used to develop prescription maps for site-specific fertilization. Furthermore, the results of this study emphasize the need to predict soil and crop variables using sensors, in future studies, to delineate pre-scription maps, as soil sampling and analysis is expansive and time consuming. Site-specific fertilization based on soil and crop needs can improve economic and environmental efficiency.