SSSAJ Journal of Natural Resources and Life Sciences Education
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


This Article
Right arrow Figures Only
Right arrow Full Text Free
Right arrow Full Text (PDF) Free
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via ISI Web of Science (4)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Mueller, T. G.
Right arrow Articles by Barnhisel, R. I.
Right arrow Search for Related Content
PubMed
Right arrow Articles by Mueller, T. G.
Right arrow Articles by Barnhisel, R. I.
Agricola
Right arrow Articles by Mueller, T. G.
Right arrow Articles by Barnhisel, R. I.
Related Collections
Right arrow Soil Fertility and Productivity
Right arrow Spatial Distribution
Right arrow Geostatistics
Right arrow Spatial Variability
Right arrow Site-Specific Analysis
Published in Soil Sci. Soc. Am. J. 68:2031-2041 (2004).
© 2004 Soil Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA

Division S-8—Nutrient Management & Soil & Plant Analysis

Site-Specific Soil Fertility Management

A Model for Map Quality

T. G. Mueller, N. B. Pusuluri, K. K. Mathias, P. L. Cornelius and R. I. Barnhisel

Dep. of Agronomy, N-122 Agronomy Science North, Univ. of Kentucky, Lexington, KY 40502

* Corresponding author (mueller{at}uky.edu)

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 (R2 = 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.

Abbreviations: bpH, buffer pH • PE, prediction efficiency • SSFM, site-specific fertility management • VIDS, validation with an independent data set







HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
The SCI Journals Agronomy Journal Crop Science
Journal of Natural Resources
and Life Sciences Education
Vadose Zone Journal
Journal of Plant Registrations Journal of
Environmental Quality
The Plant Genome
Copyright © 2004 by the Soil Science Society of America.