Relating apparent electrical conductivity to soil properties across the north-central USA

  • Authors:

  • K. A. Sudduth;N. R. Kitchen;W. J. Wiebold;W. D. Batchelor;G. A. Bollero;D. G. Bullock;D. E. Clay;H. L. Palm;F. J. Pierce;R. T. Schuler;K. D. Thelen

  • Affiliations:

  • USDA Agricultural Research Service, Cropping Systems and Water Quality Research Unit, 269 Agric. Engineering Bldg., University of Missouri, Columbia, MO 65211, USA;USDA Agricultural Research Service, Cropping Systems and Water Quality Research Unit, 269 Agric. Engineering Bldg., University of Missouri, Columbia, MO 65211, USA;Department of Agronomy, University of Missouri, Columbia, MO 65211, USA;Department of Agricultural and Biosystems Engineering, Iowa State University, Ames, IA 50011, USA;Department of Crop Sciences, University of Illinois, Urbana, IL 61801, USA;Department of Crop Sciences, University of Illinois, Urbana, IL 61801, USA;Department of Plant Science, South Dakota State University, Brookings, SD 57007, USA;Department of Agronomy, University of Missouri, Columbia, MO 65211, USA;Center for Precision Agricultural Systems, Washington State University, Prosser, WA 99350, USA;Department of Biological Systems Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA;Department of Crop and Soil Sciences, Michigan State University, East Lansing, MI 48824, USA

  • Venue:
  • Computers and Electronics in Agriculture
  • Year:
  • 2005

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Abstract

Apparent electrical conductivity (EC"a) of the soil profile can be used as an indirect indicator of a number of soil physical and chemical properties. Commercially available EC"a sensors can efficiently and inexpensively develop the spatially dense datasets desirable for describing within-field spatial soil variability in precision agriculture. The objective of this research was to relate EC"a data to measured soil properties across a wide range of soil types, management practices, and climatic conditions. Data were collected with a non-contact, electromagnetic induction-based EC"a sensor (Geonics EM38) and a coulter-based sensor (Veris 3100) on 12 fields in 6 states of the north-central United States. At 12-20 sampling sites in each field, 120-cm deep soil cores were obtained and used for soil property determination. Within individual fields, EM38 data collected in the vertical dipole orientation (0-150cm depth) and Veris 3100 deep (0-100cm depth) data were most highly correlated. Differences between EC"a sensors were more pronounced on more layered soils, such as the claypan soils of the Missouri fields, due to differences in depth-weighted sensor response curves. Correlations of EC"a with clay content and cation exchange capacity (CEC) were generally highest and most persistent across all fields and EC"a data types. Other soil properties (soil moisture, silt, sand, organic C, and paste EC) were strongly related to EC"a in some study fields but not in others. Regressions estimating clay and CEC as a function of EC"a across all study fields were reasonably accurate (r^2=0.55). Thus, it may be feasible to develop relationships between EC"a and clay and CEC that are applicable across a wide range of soil and climatic conditions.