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Soil Electrical Conductivity as a Covariate to Improve the Efficiency of Field Experiments

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Paper number  053048,  2005 ASAE Annual Meeting . (doi: 10.13031/2013.19069) @2005
Authors:   Alexandra Kravchenko, Timothy M. Harrigan, Benjamin B. Bailey
Keywords:   Soil electrical conductivity, statistical analysis, manure, aeration tillage

An accurate comparison of treatment means over a range of conditions is a primary objective of most field experiments. The spatial variability of soil properties can have adverse effects on the accuracy and efficiency of field trials. Apparent soil profile electrical conductivity (ECa) has been shown to be useful in predicting soil variability. Compared to conventional soil sampling, measurements of ECa are rapid and inexpensive. Soil ECa was used as a covariate in evaluating the effect of manure application on soil phosphorus (P) concentration. Compared to a standard analysis of variance (ANOVA), an analysis of covariance (ANCOVA) with soil ECa as a covariate improved the accuracy of estimates of P concentrations for both treatment means and aeration tool tine position means within treatments. Standard errors for means with ECa as a covariate were smaller than those of the analysis without the covariate. Different conclusions were drawn regarding treatment effects with and without ECa as a covariate. For example, an ANOVA-based conclusion was that the control (no manure) treatment was not different from the surface applied manure treatment. The ANCOVA-based conclusion was that only in soils with low ECa values were the two treatments not different. In soils with medium and high ECa the control treatment had a significantly lower P concentration.

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