Pedometric mapping for soil fertility management – A case study

• Main Authors: H.U. Leena, B.G. Premasudha, S. Panneerselvam, P.K. Basavaraja
• Format: Article
• Language: English
• Published: Elsevier 2021-02-01
• Series: Journal of the Saudi Society of Agricultural Sciences
• Subjects: Pedometric mapping; Geostatistics; Soil fertility; Soil nutrient assessment
• Online Access: http://www.sciencedirect.com/science/article/pii/S1658077X20301144

Information about soil physico-chemical parameters plays an important role in precision farming. To examine the relationship among soil properties, pedometric mapping is essential and has been widely applied in agricultural activities. This paper is aimed at soil nutrient assessment by generating the geospatial distribution maps for Kestur, a village in Tumakuru district of Karnataka State, India. Using random sampling technique, a total of one hundred and sixty geo-coordinated surface (0–20 cm) soil samples were collected from different land cover regions including irrigated and dryland areas in Kestur village. The samples collected were analysed for pH, electrical conductivity (EC), organic carbon (OC), available nitrogen (N), phosphorus (P as P2O5), and potassium (K as K2O). Also, a structured questionnaire was used to collect data about demographic profile, farming practices, crops grown and fertilizers applied from each farmer under the study. The spatial distribution maps were generated for each soil property and were mapped using spatial variability by adopting Ordinary Kriging geostatistical method. Semivariogram models such as exponential for pH, spherical model for EC and OC and Gaussian for N, P2O5, and K2O were used based on the best-fit selection using least Mean Error (ME) and Root Mean Square Error (RMSE) values. The outcome of the study proved that the geostatistical methods can be utilized to develop the spatial distribution maps thereby resulting in a cost effective solution to soil fertility management.