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Spatial patterns of soil fertility parameters, and other extrinsic factors need to be iden-tified to develop farming practices that match agricultural inputs with local crop needs. Little is known about the spatial structure of yield and weed density across fields. In this study, geostatistics was used to describe and map spatial patterns of soil total nitrogen, available phosphorus, available potassium, grain yield and density of Sisymbrium irio L. (tumble mustard), as a common annual weed of wheat fields at Shahre Kord university. The spatial continuity of each variable was examined by variogram function. The variograms showed that the distribution of all variables is not random but spatially-dependent as their estimated variogram values increase with increasing distance. The av-erage range values were 26.5, 23.4, 31.4, 27.7, and 27.2 m for total nitrogen, available phosphorus, available potassium, grain yield and weed density, respectively. Thus, the range beyond which the property is not longer spatially dependent was almost the same for total nitrogen, grain yield and weed density. This implied close spatial interactions among these variables over the field. Applying the variogram models with the kriging al-gorithm, the values for each variable were estimated on a 55 grid. The disrribution of all variables is spatially dependent and continuous over a short distance. Furthermore, the maps illustratc a joint spatial dependence between grain yield and weed density. Spatial patterns of soil properties identified by these geostatistical techniques are of great impor-tance in the fertility management of spatially variable soils. By studying the spatial struc-ture of yield and mapping, it could be used in determining different factors controlling yield over the field. Moreover, a better knowledge of annual or perennial weed density distribution over fields might be helpful in better designing long-term field experiments in weed control programs.

Keywords: Grain yield, geostatistics, kriging, Variogram, Weed density

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