Journal of Experimental Agriculture International

Crop production is governed by three factors, viz., soil, inputs and climatic condition. Climatic conditions are beyond human control whereas soil and other inputs can be altered to enhance crop production. An understanding of soil properties is required for sustainable management of soil to reduce soil erosion and enhance soil health and fertility level. The variability of soil properties is needed for agricultural productivity, food safety and environmental modelling. The present study was conducted in soils of Muzaffarpur district in Bihar, India to understand the soil properties mapping using geostatistical Techniques. Soil pH, electrical conductivity (EC), organic carbon (OC), sulphur (S) and zinc (Zn)were measured. Spatial maps of soil properties were prepared using the semivariogram model through kriging techniques. The nugget-sill ratio for pH ranged between 0.25- 0.75, indicating a moderate level of spatial dependence among the variables. For soil properties such as EC, OC, S, and Zn, the nugget-sill ratio was greater than 0.75, indicating a weak level of spatial dependence for these variables. The cross-validation results illustrated the smoothing effect of the spatial prediction. The maps developed by kriging were observed to be superior to assuming mean of observed value for any un-sampled location. These maps may help farmers to adopt need based variable rate of fertilizer application thus optimizing resource utilization. The present study suggests that the geostatistical model can directly reveal the spatial variability of soils.