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Soil Science Society of America Journal Abstract - Soil & Water Management & Conservation

Relationship of Apparent Soil Electrical Conductivity to Claypan Soil Properties


This article in SSSAJ

  1. Vol. 69 No. 3, p. 883-892
    Received: June 21, 2004

    * Corresponding author(s): KitchenN@missouri.edu
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  1. W. K. Junga,
  2. N. R. Kitchen *b,
  3. K. A. Sudduthb,
  4. R. J. Kremerb and
  5. P. P. Motavallia
  1. a Dep. of Soil, Environmental and Atmospheric Sciences, 148 Agricultural Engineering Building, Univ. of Missouri-Columbia, Columbia, MO 65211
    b USDA-ARS, Cropping Systems and Water Quality Research Unit, 269 Agricultural Engineering Building, Univ. of Missouri-Columbia, Columbia, MO 65211


Understanding relationships between sensor-based measurements and soil properties related to soil quality may help in developing site-specific management. The primary objective of this research was to examine whether sensor-based apparent soil electrical conductivity (ECa) could be used to predict soil properties for claypan soil. Soil samples were obtained at three depths intervals (0- to 7.5-, 7.5- to 15-, and 15- to 30-cm depths) at 65 locations within a 4-ha area of an agricultural field located in north central Missouri in 2002. Samples were analyzed for numerous physical, chemical, and microbiological properties that serve as soil quality indicators. The ECa measurements were also collected at the coring locations with an electromagnetic induction-based sensor. A combine equipped with a commercial yield-sensing, GPS based recording system was used to map corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] yields from 1993 to 2002. At the deepest sampling depth, soil bulk density (Db), clay, silt, cation exchange capacity (CEC), and Bray-1 P were the most significantly correlated (r > 0.55) with ECa Soil properties were regressed against ECa, and R 2 values were often improved using a quadratic term of ECa, especially at the 0- to 7.5-cm depth. Selected regression models were validated with an independent soil sample data set (n = 20). Soil properties were similar between measured and predicted. Some soil properties (e.g., clay and CEC) and ECa that were positively correlated to yield in years with average or greater than average cumulative July to August precipitation (>15 cm) were negatively correlated to yield for years with less than average precipitation (<15 cm). Our results suggest that sensor-based ECa can be a quick and economical way of estimating some claypan soil quality measurements.

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