Spatial Variability Of Soil Nutrients And Influencing Factors In Kongzhan Farm

As an important component of commodity grain production base in the northeast,Heilongjiang reclamation area is also a region where the degree of agricultural mechanization isthe highest in China. Here, precision agriculture on fertilization, sowing and insect diseaseprevention is practiced according to spatial variation of soil and growth characteristics of crops,which not only increases the grain output but also reduce a waste of resources and environmentalpollution resulted from excessive use of pesticide and fertilizer. This research has studied spatialvariation of soil organic matters and influencing factors from perspective of precision agricultureby basing on that precision agriculture needs spatial variation of soil, taking spatial heterogeneityof soil organic matters and the influencing factors as research content, selecting typical slopcropland and designing different sampling densities.The slop cropland of Heshan farm under agricultural reclamation Jiusan Administration istaken as object of research; surface soil samples are collected according to30m×30m grid fortesting content of organic matters in the soil; then30m×30m is taken as a standard for generatingthree other sampling densities, including60m×60m,90m×90m and120m×120m. In terms ofcontents of organic matters of4sampling densities, SPSS software is applied for making atraditional statistical analysis and GS+7.0is applied for making a semivariable function.Moreover, spatial Kriging interpolation is practiced upon Arcgis9.3and a comparative analysisof interpolation precision is made according to the actual testing result and interpolation result.In general, the completed content is as follow:(1) Surface soil samples are collected from Mangang section of Heshan farm with griddingmethod for testing and analyzing contents of organic matters. It is concluded that contents oforganic matters of soil in this section lie between5.99%and2.34%and the mean value is5.21%.(2) An analysis is made with traditional statistical method. It is concluded that averagecontents of organic matters attained from different sampling densities are close to each otherthough there is difference between the highest and lowest contents.(3) Spatial variation of organic matters of surface level is analyzed with semi-variancefunction. It is concluded that there is no spatial autocorrelation regarding content of organicmatters in the farming level after the research area is380.6m. Spatial variation of organic matters of farming level is primarily caused by non-artificial reasons; meanwhile, there is a high degreeof spatial correlation with contents of organic matters in the farming level and a high degree ofspatial heterogeneity.(4) Analyses of spatial interpolation under different sampling densities are made. It isconcluded that the spatial distribution hierarch of organic matters becomes weaker and thenumerical distribution scope of interpolation results gradually get concentrated as distancesbetween involved interpolation sample points increase. In local scope, in particular, the error ofspatial distribution increases with the increase of sampling distance...