Spatial Variability of Organic Carbon and Soil pH by Geostatistical Approach in Deccan Plateau of India

Abstract

Proper soil nutrient management is necessary to meet India’s rising population without degrading the environment. However, the state of soil organic carbon (SOC) and soil pH is a concern, especially in Indian vertisols that are productive when well managed. Due to a lack of scientific knowledge and poor soil management among the small-scale farmers (most Indian farmers hold less than 2 ha), the crop yield has declined. The current study examines the correlation between soil pH and SOM and their spatial variability in vertisols (Black-Cotton soil). Geostatistics and conventional statistics are used to produce the spatial distribution maps, with the R software and the SpaceStat. Sixty-eight soil samples at the root zone level (0–15 cm depth) are collected from Gulbarga Taluk, Karnataka, India. The random sampling method is adopted according to the agriculture fields distribution, and each sample consists of five subsamples. The soil pH was estimated by pH meter and SOC by Walkley and black method. The violin plots indicate that most soil pH samples range from 8.5 to 7.5 and SOM 0.20–0.50%. The Pearson correlation indicated a negative correlation between the two parameters (r = −0.21). In semivariogram analysis, the spherical and exponential models were best fitted for soil pH and SOM, respectively. The ordinary kriging accomplished by a traditional estimator is adapted for generating spatial distribution maps. In line with the negative correlation of soil pH and SOC, the predictable maps are the mirror images. The spatial variability maps give an overview of how extrinsic and intrinsic factors affect the availability of soil pH and SOC. In this region, the parent materials, fertilizers application, and agricultural practices are affecting the soil variability. Small scale farmers should assess these spatial variability maps before applying the fertilizers.