Submitted to: Soil Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: March 23, 2006
Publication Date: August 1, 2006
Citation: Jabro, J.D., Evans, R.G., Kim, Y., Stevens, W.B., Iversen, W.M. 2006. Characterization of spatial variability of soil electrical conductivity and cone index using coulter and penetrometer-type sensors. Soil Science. 171(8):627-637. Interpretive Summary: Sensors’ based measurements of soil ECa and CI can provide important information to assess and examine spatial variability for precision farming. Spatial data were collected using both Veris 3100 and Veris 3000 to investigate and evaluate spatial variability in ECa and CI for 1.4 ha grass-alfalfa field at the Nesson Valley research site in North Dakota. Descriptive statistics, semivariance analysis, and point kriging were employed to assess the magnitude and spatial range of variability in the soil measured properties. Interpolated spatial maps for ECa and CI using a 1 m2 grid pixel may be used as a baseline for precision farming and future management decisions. The soil ECa and CI variability was spatially structured and these maps had the potential of explaining the variability within the field. From this study, the ECa and CI maps have the potential to aid farmers with site-specific soil use and define problematic areas within their fields.
Technical Abstract: Assessment and management of spatial variability of soil chemical and physical properties are very important for precision farming. The spatial variability of apparent electrical conductivity (ECa) and penetration resistance expressed as cone index (CI) for soil compaction was investigated with Veris 3100 and Veris 3000 sensing technologies. The study was conducted in April 2005 at the research farm located near Williston, ND on a sandy loam soil (Sandy, mixed, frigid Entic Haplustoll). The ECa data from both Veris 3100 and Veris 3000 exhibited similar spatial trends across the field that may characterize the variability of soil for a variety of important physical and chemical properties. The coefficient of variations of ECa from Veris 3100 and Veris 3000 were 19.2 and 11.3%, respectively. However, the averages of ECa measurements for Veris 3100 and Veris 3000 were 4.92 and 3.31 mS/m, respectively that were significantly different. The ECa mean difference, Md between these two devices was also significantly different from zero (Md= 1.71 mS/m; t=34.23, n=138; pr<0.0001). Geostatistical tools were used to evaluate spatial dependency and assess the overall soil variability. It was found that soil ECa and CI parameters were spatially distributed and presented weak to medium spatial dependency within the mapped field area. Further, ECa measurements from both sensors exhibited approximately log normal distribution and the CI values were normally distributed using probability distribution functions. The spatial data produced from this direct sensing technology can be used as baseline for precision farming and making future management decisions.