Spatial Variability of Soil Organic Carbon and Available Nutrients under Different Topography and Land Uses in Meghalaya, India

Abstract

Nutrient loss from the soil is influenced by topography and crop uptake. Knowledge of spatial variability of soil properties can help in site-specific nutrient management. It was attempted to study the effect of topography and land uses on spatial variability of soil organic carbon (SOC), available nitrogen (N), available phosphorus (P) and available potassium (K) in acidic soils of the research farm of National Bureau of Plant Genetic Resource having annual crop (ginger/turmeric) with 25% slope (NBPGR 1), buckwheat-pulse, maize-fallow, perennial medicinal plants with 9% slope (NBPGR 2), Indian Council of Agricultural Research-Krishi Vigyan Kendra farm having ginger/turmeric, maize-vegetable, pulse-vegetable with 9% slope (ICAR-KVK) and ICAR-Horticulture farm having guava/mandarin with 25% slope. The SOC content was in the order of guava (2.15%) > mandarin (2.06%) > ginger/turmeric at NBPGR 1(1.98%) > maize-vegetable (1.87%) > medicinal plants (1.81%) > buckwheat-pulse (1.78%) > maize-fallow (1.76%) = pulses-vegetable (1.76%) > ginger/turmeric at ICAR-KVK (1.56%). The N was higher in buckwheat-pulse (460.35 kg/ha) followed by guava (420.85 kg/ha), maize-fallow (409.92 kg/ha), ginger/turmeric of ICAR-KVK (404.50 kg/ha), medicinal plants (402.2 kg/ha), pulse-vegetable (377.46 kg/ha), mandarin (366.14 kg/ha), maize-vegetable (364.68 kg/ha) and ginger/turmeric of NBPGR 1 (348.06 kg/ha). The P was in the order of maize-vegetable (52.07 kg/ha) > pulse-vegetable (40.14 kg/ha1) > ginger/turmeric of ICAR-KVK (35.67 kg/ha) > buckwheat-pulses (22.23 kg/ha) > mandarin (21.06 kg/ha) > guava (20.83 kg/ha) > maize-fallow (16.58 kg/ha) > ginger/turmeric of NBPGR 1 (15.71 kg/ha) > medicinal plants (13.33 kg/ha). The K was observed higher in guava (422.80 kg/ha) followed by buckwheat-pulse (330.86 kg/ha), ginger/turmeric of NBPGR 1 (192.13 kg/ha) and maize-vegetable (181.73 kg/ha). The nugget/sill ratio of P had strong to moderate and SOC, N and K had moderate to weak spatial autocorrelation in NBPGR 1 and NBPGR 2. All the nutrients in ICAR-KVK farm were found to have weak spatial correlation. Most suitable interpolation technique for SOC and K was the Radial Basis Function (RBF), ordinary kriging for N and P and gaussian model for ICAR-KVK farm. In ICAR-Horticulture farm, the exponential and pentaspherical semivariogram model best described the SOC, N, K and P, respectively. The nugget/sill ratio of P and K showed moderate spatial dependence and this was weak for SOC and N.