Mapping soil property variability in oil palm (Elaeis guineensis jacq.) plantations of Krishna basin of Andhra Pradesh through geospatial technologies

Abstract

Sixty seven soil samples were collected from oil palm growing regions of NTR District of Andhra Pradesh and were analysed for different soil properties. The data was subjected to descriptive analysis to find out the variability and then to geostatistical analysis to design best fit models having minimal error for developing prediction maps. Highest variation was observed in exch. Mg and the lowest in pH. The mean values of soil pH, EC (dS/m), OC (g/kg), Olsen-P (mg/kg), NH4OAc-K (mg/kg), Exch. Ca (mg/kg), Exch. Mg (mg/kg), CaCl2-S (mg/kg) and HWB (mg/kg) were 7.32 ± 0.08, 0.25 ± 0.02, 0.87 ± 0.03, 101.47 ± 6.95, 566.14 ± 42.97, 4.72 ± 0.24, 2.46 ± 0.27, 60.86 ± 2.6 and 5.98 ± 0.25 respectively in the surface layer (0-20 cm) of the soil. Geostatistical analysis revealed wider spatial variability in surface soil properties and they had circular, spherical, stable and exponential best fit semi variogram models for evaluating dependency. The wide spatial variability of soil properties warrants site specific nutrient management for higher oil palm production. Nutrient distribution maps could be developed through kriging interpolation to interpolate the nutrient levels in unsampled areas.