About Us | Help Videos | Contact Us | Subscriptions
 

Abstract

 

This article in SSSAJ

  1. Vol. 66 No. 5, p. 1562-1570
     
    Received: Mar 1, 2001


    * Corresponding author(s): candcook@vt.edu
 View
 Download
 Alerts
 Permissions
 Share

doi:10.2136/sssaj2002.1562

Differentiating Soil Types Using Electromagnetic Conductivity and Crop Yield Maps

  1. C. M. Anderson-Cook *a,
  2. M. M. Alleyb,
  3. J. K. F. Roygardb,
  4. R. Khoslac,
  5. R. B. Nobled and
  6. J. A. Doolittlee
  1. a Dep. of Statistics (0439), Virginia Tech, Blacksburg, VA 24061
    b Dep. of Crop and Soil Environmental Sciences (0403), Virginia Tech, Blacksburg, VA 24061
    c Dep. of Soil and Crop Science, Colorado State Univ., Fort Collins, CO 80523
    d Dep. of Mathematics and Statistics, University of Miami (Ohio) Oxford, OH 45056
    e USDA-Forest Service, 11 Campus Blvd. (Suite 200), Newton Square, PA 19073-3200

Abstract

Variable rate technology enables management of individual soil types within fields. However, correct classification of soil types for mid-Atlantic coastal plain soils are currently impractically expensive using an Order I Soil Survey, yet variable rate fertilizer application based on soil type can be highly effective. The objectives of this study were to determine if apparent electromagnetic conductivity (ECa) alone or combined with previous year crop yields using global positioning system technology can provide a useful alternative to detailed soil mapping. The site contained alluvial soils ranging from Bojac 1 and 2 (coarse-loamy, mixed, thermic, Hapludults) to Wickham 3 and 4 (fine-loamy, mixed, thermic, Ultic Hapludalfs). The two fields totaled approximately 24 ha. A statistical nonparametric classification method, called recursive binary classification trees, was used to determine how well soil types could be classified. Electromagnetic conductivity readings and crop yields were positively correlated. Broad patterns in the relationship between soil types and ECa readings and crop yields existed for all crop combinations considered. Lower ECa readings and crop yields corresponded to the Bojac soils, while higher ECa readings and crop yields were categorized as Wickham soils. Electromagnetic induction alone correctly classified the soils into broad categories of Bojac or Wickham with over 85% accuracy. When ECa was combined with crop yield data, correct classification rose to over 90%. More precise classification into Bojac 1, Bojac 2, and Wickham soils yielded slightly lower correct classifications ranging from 62.6 to 81.2% for ECa alone, and 80.3 to 91.5% when combined with various crop yields.

  Please view the pdf by using the Full Text (PDF) link under 'View' to the left.

Copyright © 2002. Soil Science SocietyPublished in Soil Sci. Soc. Am. J.66:1562–1570.