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United States Department of Agriculture

Agricultural Research Service


item Shillito, Rose
item Timlin, Dennis

Submitted to: BARC Poster Day
Publication Type: Abstract Only
Publication Acceptance Date: 4/29/2004
Publication Date: 4/29/2004
Citation: Shillito, R.M., Timlin, D.J. 2004. Spatial variability in landscape-scale agricultural experimentation [abstract]. BARC Poster Day. Abstract No. 21.

Interpretive Summary:

Technical Abstract: Spatial variability of field conditions has long been recognized as problematic in agricultural experimentation. Traditionally, spatial variability has been either ignored or removed from analysis. We hypothesize that using spatial variability can increase the effectiveness and efficiency of sampling and lead to improved crop yield predictions. In concert with our efforts to develop realistic and viable biophysical crop models, we planted a 0.18 ha field of potatoes at the Beltsville Agricultural Research Center, West. Spatially-distributed field data (topography, soil texture, soil nitrate content) were collected to establish initial field conditions. After planting, four levels of nitrogen fertilizer were applied throughout the field in a sinusoidally varying pattern. At the end of the growing season, potato counts and weights were recorded throughout the field. Clay content and initial soil nitrogen were higher at one end of the field than at the other. Potato yield response depended largely on field position such that the response was larger where clay content was higher. The use of autoregressive statistical methods allowed us to estimate the component of error due to spatial variability of soil properties. Using relatively inexpensive but easily measured data that are distributed throughout the field will aid in extrapolating plant-based crop yield models more realistically over given field conditions.

Last Modified: 10/15/2017
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