Study of Advanced Techniques to Predict the Soil Properties

Information about soil properties helps the farmers to adopt effective and efficient farming practices, which can increase higher yields with optimum usage of farm resources. An attempt has been made in this paper predict using geospatial kriging approaches. This study mainly focuses on predicting pH different methods. Soil dramatically affects many other processes, such as nitrification denitrification, mineralization, precipitation, dissolution organic matter. Total seven semivariogram models, namely spherical, circular, exponential, Gaussian, linear, while two models universal kriging, linear drift quadratic drift, have taken interpolate spatial pH. The performances these entire validated mean error, root square error. Spatial analysis revealed that Universal outperformed ordinary less error 0.016 0.52, respectively. mapping be instrumental adopting real-time on-the-go precision practices.