ISSN: 2381-8719
P Vanitha*, PP Mahendran, P Saravana Pandian, R Geetha, K. Kumutha
The present study aimed to assess the spatial variability and mapping of micronutrients under the sugarcane growing block of the Sivagangai district using geostatistics and the Geographic Information System (GIS). Totally, 100 georeferenced surface samples (0 cm-30 cm) were collected and analysed for soil physicochemical properties. Descriptive statistics showed that the variance values coefficient ranged from 7.32% to 49.83%. Geostatistical analysis was executed for mapping the soil fertility properties with aid of well-fitted semivariogram models. Through crossvalidation techniques, the Standardized Root Mean Square Error (RMSSE) was computed and utilized for good prediction of the model. Geostatistical analysis revealed exponential for pH, EC, free CaCO3 and B, circular model for OC and Zn, Spherical for Fe and Mn, and the Gaussian model fitted well for Cu. Multivariate statistics viz., Pearson’s correlation coefficient and stepwise multiple regression were carried out and results showed significant correlations and interrelationships among the soil parameters. The principal component analysis provides the four principal components (PC1, PC2, PC3, and PC4) pertain to eigenvalues >1 and together elucidated 71.29% of the pattern variance. The kriged map of available Fe, Cu, Zn, Mn, and hot water soluble B showed areas under deficiency of about 57.3%, 52.2%, 50.2%, 44.5%, and 83.2%. The spatial variability of various parameters helps in site specific soil nutrient management and crop planning decisions to enhance sugarcane productivity.