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This article in SSSAJ

  1. Vol. 68 No. 6, p. 2031-2041
     
    Received: July 17, 2003


    * Corresponding author(s): mueller@uky.edu
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doi:10.2136/sssaj2004.2031

Site-Specific Soil Fertility Management

  1. T. G. Mueller *,
  2. N. B. Pusuluri,
  3. K. K. Mathias,
  4. P. L. Cornelius and
  5. R. I. Barnhisel
  1. Dep. of Agronomy, N-122 Agronomy Science North, Univ. of Kentucky, Lexington, KY 40502

Abstract

The performance of site-specific fertility management (SSFM) systems depends on the quality of soil property maps used to develop variable-rate fertilizer recommendations. Map quality assessment, however, may be too expensive for routine site-specific soil sampling. The objectives of this study were (i) to evaluate the quality of soil property maps created with ordinary kriging for five fields in Kentucky, and (ii) to develop a model describing the relationship between map quality and statistical properties of data. Five fields across Kentucky were sampled on 30.5-m grids and samples were analyzed for pH, buffer pH (bpH), P, K, Ca, and Mg. For each field, four 61.0 and nine 91.5-m data subsets were extracted from the 30.5-m grid. Semivariograms could only be adequately modeled for the 30.5- and 61.0-m grid datasets. Therefore, only these data sets were interpolated with ordinary kriging. Map quality was evaluated with an independent data set. Multiple stepwise regression was used to model map quality using data from several Kentucky fields and from a previously published Michigan study. Prediction efficiency (PE) was a function of the relative structural variability, range of spatial correlation, and grid increment (R 2 = 0.82). The range of spatial correlation was the major factor controlling map quality within the range of variation studied. This model may potentially be a useful tool for the development of sampling designs for site-specific management.

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