Simulation of Organic Matter Variability on a Sugarbeet Field Using the Computer Based Geostatistical Methods

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dc.contributor.authorKaraman, M. Rüştü
dc.contributor.authorSusam, Tekin
dc.contributor.authorEr, Fatih
dc.contributor.authorYaprak, Servet
dc.contributor.authorKarkacıer, Osman
dc.date.accessioned2020-03-26T17:45:53Z
dc.date.available2020-03-26T17:45:53Z
dc.date.issued2009
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractComputer 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 × 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 ± 0.48, N ± 0.37, subsoil OM ± 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.en_US
dc.identifier.citationKarkacıer, O., Yaprak, S., Er, F., Susam, T., Karaman, M. R., (2009). Simulation of Organic Matter Variability on a Sugarbeet Field Using the Computer Based Geostatistical Methods. World Academy of Science Engineering and Technology, 3(8), 254-257.
dc.identifier.endpage257en_US
dc.identifier.issn2010-376Xen_US
dc.identifier.issue8
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage254en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/24186
dc.identifier.volume3en_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorSusam, Tekin
dc.language.isoenen_US
dc.relation.ispartofWorld Academy of Science, Engineering and Technologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectGeostatisticen_US
dc.subjectKrigingen_US
dc.subjectOrganic matteren_US
dc.subjectSugarbeeten_US
dc.titleSimulation of Organic Matter Variability on a Sugarbeet Field Using the Computer Based Geostatistical Methodsen_US
dc.typeArticleen_US

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