Spatial variability assessment of soil fertility in black soils of central India using geostatistical modeling. Issue 7 (7th June 2021) - Sharma, R. P.; Chattaraj, S.; Vasu, D.; Karthikeyan, K.; Tiwary, P.; Naitam, R. K.; Dash, B.; Tiwari, G.; Jangir, A.; Daripa, A.; Singh, S. K.; Anantwar, S. G.; et al.
ABSTRACT: Capturing site-specific variability in soil attributes is crucial for precision agriculture. A study was conducted in Kelapur block of Yavatmal district, Maharashtra, covering 83, 000 ha area in the basaltic region of central India for investigating the spatial distribution of soil fertility parameters viz., pH, EC, organic matter, available macro (AvN, AvP, AvK and AvS) and cationic micronutrients (Fe, Mn, Zn and Cu). Total 4627 surface samples (0–15 cm depth) were collected using grid sampling method at 325 m interval and analysed for the soil properties. The geo-database was subjected to kriging through best-fit experimental semivariogram based on lowest root mean squared error. Spherical model was found best fit for AvP, AvK and AvS whereas exponential model was best fit for remaining soil parameters. The spatial distribution of maps showed deficiency of AvN, AvP, Zn and Fe whereas AvK was high in most of the study area. Spatial dependence was moderate for all soil fertility parameters (N:S ratio 0.25–0.75) whereas AvP exhibited strong spatial dependency (N:S ratio 0.19). Strong spatial dependence of AvP is mainly regulated by pH and smectitic clay minerals. This study can support site-specific plant nutrient management at cadastral level for precision farming.