TY - JFULL AU - M. R眉st眉 Karaman and Tekin Susam and Fatih Er and Servet Yaprak and Osman Karkac谋er PY - 2009/9/ TI - Simulation of Organic Matter Variability on a Sugarbeet Field Using the Computer Based Geostatistical Methods T2 - International Journal of Geological and Environmental Engineering SP - 253 EP - 257 VL - 3 SN - 1307-6892 UR - https://publications.waset.org/pdf/12640 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 32, 2009 N2 - Computer based geostatistical methods can offer effective data analysis possibilities for agricultural areas by using vectorial data and their objective informations. These methods will help to detect the spatial changes on different locations of the large agricultural lands, which will lead to effective fertilization for optimal yield with reduced environmental pollution. In this study, topsoil (0-20 cm) and subsoil (20-40 cm) samples were taken from a sugar beet field by 20 x 20 m grids. Plant samples were also collected from the same plots. Some physical and chemical analyses for these samples were made by routine methods. According to derived variation coefficients, topsoil organic matter (OM) distribution was more than subsoil OM distribution. The highest C.V. value of 17.79% was found for topsoil OM. The data were analyzed comparatively according to kriging methods which are also used widely in geostatistic. Several interpolation methods (Ordinary,Simple and Universal) and semivariogram models (Spherical, Exponential and Gaussian) were tested in order to choose the suitable methods. Average standard deviations of values estimated by simple kriging interpolation method were less than average standard deviations (topsoil OM 卤 0.48, N 卤 0.37, subsoil OM 卤 0.18) of measured values. The most suitable interpolation method was simple kriging method and exponantial semivariogram model for topsoil, whereas the best optimal interpolation method was simple kriging method and spherical semivariogram model for subsoil. The results also showed that these computer based geostatistical methods should be tested and calibrated for different experimental conditions and semivariogram models. ER -