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Articles by R. Sivasamy
Total Records ( 2 ) for R. Sivasamy
  Saravanan Sivarajan , M. Nagarajan and R. Sivasamy
  The spatial variability studies performed to see the varying effect of soil properties across the fields and to make efficient crop management decisions in the future. The goal of this study was to determine spatial variability of selected soil properties that influences crop growth and its crop yields. The study was conducted in an agricultural field Coimbatore, Tamil Nadu, India. The data collected were analyzed using geostatistics tool with semivariograms, kriging and classical statistics that involved mean, range, standard deviation and coefficient of variation. The statistical analysis showed a high variability for soil pH having a Cv of 11.88%. The parameters such as infiltration, porosity, Field Capacity (FC), Wilting Point (WP) and phosphorus showed considerable variability with a coefficient of variation between 5 and 9% and least variability was found to exist for electrical conductivity (EC), available potassium (K), available nitrogen (N) and Bulk Density (BD) with Cv of 0.037, 0.29, 0.62 and 2.01, respectively. The semivariograms were calculated for the study area with a sampling distance of 5 m and the N, P, K and EC were linear with sill models and each showed a considerable range of spatial dependence measuring a distance between 10 and 25 m. The kriged surface was created for all the soil properties with the exception of BD, porosity and WP as these parameters were found to be spatially uncorrelated. These spatial variations in soil properties in the field may arise from management activities or due to soil textural effects.
  K. Manikandan , S. Natarajan and R. Sivasamy
  Hydro-chemical ground water data of coastal region of Cuddalore district was subjected to cluster analysis to group the ground water based on its homogeneity and to find out the influencing factor on ground water quality. The twenty-seven water samples were collected during summer and post monsoon season of 2007 and characterized for nine physico-chemical parameters. These physicochemical parameters were subjected to cluster analysis. From the analysis, four and five distinct clusters were identified in summer and post monsoon season respectively. The different cluster recognized in the cluster analysis differed in chemical composition. It also had significant correlation with spatial distance from the sea as well as landform.
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