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United States Department of Agriculture

Agricultural Research Service

Title: Relationships Between Soil Bulk Electrical Conductivity and the Principal Component Analysis of Topography and Soil Fertility Values

Authors
item Officer, Sally J - UNIV OF IL
item Kravchenko, A - UNIV OF IL
item Bollero, German - UNIV OF IL
item SUDDUTH, KENNETH
item KITCHEN, NEWELL
item Wiebold, William - UNIV OF MO
item Palm, Harlan - UNIV OF MO
item Bullock, Donald - UNIV OF IL

Submitted to: Plant and Soil
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: September 4, 2003
Publication Date: January 15, 2004
Repository URL: http://www.ars.usda.gov/sp2UserFiles/Place/36221500/cswq-0017-128245.pdf
Citation: OFFICER, S.J., KRAVCHENKO, A., BOLLERO, G.A., SUDDUTH, K.A., KITCHEN, N.R., WIEBOLD, W.J., PALM, H.L., BULLOCK, D.G. RELATIONSHIPS BETWEEN SOIL BULK ELECTRICAL CONDUCTIVITY AND THE PRINCIPAL COMPONENT ANALYSIS OF TOPOGRAPHY AND SOIL FERTILITY VALUES. PLANT AND SOIL JOURNAL. 2004. v. 258(1). P. 269-280.

Interpretive Summary: For widespread adoption of precision agriculture methods, efficient and cost-effective ways of obtaining field data are required. Currently, measurements of soil fertility status, such as pH, phosphorous and potassium levels, are generally done by collecting soil samples on a grid for laboratory analysis. Because of costs and time involved, these samples sare usually obtained on about a 2.5-acre grid, which previous research has shown is much too coarse for accurate mapping of fertility variations. In this research, we investigated the use of sensor measurements of soil electrical conductivity (EC) and topography to improve the accuracy of soil fertility maps. These sensor-based data can be collected much more quickly and at a much higher density than soil fertility data. By analyzing the soil fertility and EC datasets together, we were able to obtain improved estimates for soil cation exchange capacity, calcium, magnesium, and organic matter. Topography was less useful than EC in developing improved fertility maps. Also, it was not possible to use this approach to improve maps of those fertility parameters, such as phosphorous and soil pH, that are primarily a result of man-made disturbances (i.e., application of chemical fertilizers). This research may benefit researchers, crop consultants, and extension personnel who want to deliver accurate, cost- effective soil fertility maps to farmers. Ultimately, farmers using such maps may obtain economic benefits by more closely matching fertilizer applications to within-field variability.

Technical Abstract: Measures of in-situ soil electrical conductivity (EC) and elevation are relatively inexpensive to collect and can be gathered in great intensity from a field, resulting in high quality maps. Soil chemistry information is expensive to collect, so that relatively few samples are made and many attributes are measured from each sample. This results in maps of poor quality and limited usefulness for site-specific applications in precision agriculture. Principal component (PC) cokriging can be applied to create meaningful field scale summaries of the attributes and improve the quality of the maps of summarized attributes. Deep (0-1 m) and shallow (0-300 mm) EC, elevation, and soil fertility attributes were measured in fields under a corn-soybean (Zea mays L., Glycine max L.) rotation, at two sites in Illinois and two sites in Missouri. Soil fertility and topography attributes were summarized by PC analysis. The first topography PC (TopoPC1) for all sites contrasted flow accumulation with elevation and curvature to describe the main topographic pattern of fields in gently sloping glacial till landscapes. The first soil fertility PC (SoilPC1) consistently grouped together cation exchange capacity (CEC), Ca, Mg, and organic matter (OM). SoilPC1 was consistently well correlated to soil EC, and principal component cokriging improved the quality of maps of SoilPC1. The second and third soil fertility PCs (SoilPC2 and SoilPC3) were mainly concerned with soil pH and P, describing man-made disturbance of the soil fertility patterns. Maps of SoilPC2 and SoilPC3 had little relationship to the soil EC or topography patterns and could not be improved by cokriging.

Last Modified: 9/29/2014
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