Georeferenced tractor wheel slip data for prediction of spatial variability in soil physical properties

The upcoming technological breakthrough in the cropping system will offer a more detailed insight into soil-to-plant, man-to-soil, and man-to-plant impacts, thus improving forecasting ensuring efficient in-field management. This study presents various on-the-go sensing procedures which were conducted order to evaluate quality of spatial estimations soil physical properties such as compaction, moisture content, bulk density texture. Standard statistical tools showed high positive correlations between specific resistance compaction (R2 = .75), electromagnetic conductivity content .72) tractor wheel slip .64). Variogram modeling autocorrelation gave highest prediction error for tillage (9.85%), followed by cone index (4.49%), (3.7%), (1.39%), clay + silt (.98%), (.95%) least was obtained (.58%). Central Composite Design (CCD) analysis confirmed significant contribution slip, while fine particle (clay silt) had major impact on measurement. Soil considerable importance CCD slip.