Spatial variability assessment of soil available phosphorus using geostatistical approach - Mondal, Bhabani Prasad; Sekhon, Bharpoor Singh; Sadhukhan, Rahul; Singh, Rajiv Kumar; Hasanain, Mohammad; Mridha, Nilimesh; Das, Bappa; dhyay, Arghya Chattopa; Banerjee, Koushik (The Indian Journal of Agricultural Sciences, 2020)
Soil available phosphorus (P), a major plant nutrient, exhibits a high degree of spatial variability. Spatial variability assessment of P is necessary for its precise management using geostatistics. Therefore, the present study was conducted in an intensely cropped region of Ladian village of Ludhiana, Punjab during 2014-2016 to assess the spatial variability status of P under three prevalent land use systems, viz. berseem-based land use, rice-wheat system and poplar-wheat based agroforestry system. The classical statistics showed the variability of available-P in terms of percent coefficient of variation (%CV), but unable to distinguish variability between rice-wheat (CV=38.79%) and poplar-wheat system (CV=38.58%). Lower variability was observed in berseem-based land use (CV=15.21%), though the mean available-P content (46 kg/ha) was higher in this land use. However, the geostatistical techniques successfully demonstrated the spatial dependence of P within and in between land uses using nugget-sill (NS) ratio. Gaussian model was found suitable for describing the spatial structure of available-P under berseem-based land use; while, Exponential models were found suitable for rice-wheat and poplar-wheat systems. The value of NS ratio of available-P was 0.17 for poplar-wheat based land use, suggesting strong spatial dependence, whereas the rest other land uses exhibited moderate (NS=0.74) to weak (NS=0.82) spatial dependence of available P. The spatial variability maps of P were generated using ordinary kriging technique, demonstrated significantly the higher variability of P in poplar-wheat system than other systems. This variability should be considered before applying phosphatic fertilizers to this land use to get optimum response. The generated maps would assist the farmers for site-specific P management in the study area.