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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #197908


item Sudduth, Kenneth - Ken
item Kitchen, Newell

Submitted to: ASABE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: 7/5/2006
Publication Date: 7/10/2006
Citation: Sudduth, K.A., Kitchen, N.R. 2006. Increasing information with multiple soil electrical conductivity datasets. In: ASABE Annual International Meeting Technical Papers. ASABE Annual Meeting, July 9-12, 2006, Portland, Oregon. Paper No. 061055.

Interpretive Summary: As farmers have become familiar with the technologies of precision agriculture, such as yield monitors and GPS, there has been increasing interest in being able to map soil variability within fields. One on-the-go soil sensing technology is soil apparent electrical conductivity (EC), for which there are several sensors commercially available. Each of the commercial sensors measures EC as a single reading averaged over a measurement depth, and this measurement depth is different for the different sensors. Because of this, we wanted to find out if combining data from multiple EC sensors would give a better picture of soil variability than data from just one sensor. We collected data with three commercial EC sensors on two fields in Missouri and related the EC readings to several soil properties. We found that the best sensor for a particular application depended on whether information was needed about just the surface soil layer or the entire root zone. Combining data from multiple EC sensors gave better results only in some cases. One area where there was improvement with multiple sensors was in estimating topsoil depth, where we saw a 30% reduction in error. Topsoil depth is an important parameter because it is strongly related to crop production on the claypan soils found in the study fields. The results of this research will benefit users of EC instruments, showing them a way to improve the accuracy of EC in estimating soil properties. The results will also benefit scientists and extension personnel who may need to recommend the best EC instrument to use in a particular situation.

Technical Abstract: Maps of apparent electrical conductivity (ECa) of the soil profile are widely used in precision agriculture practice and research. Because ECa is often strongly related to clay content, soil water holding capacity, and other soil physical properties that also relate to crop productivity, ECa maps can provide insight into the causes of within-field yield variations. A number of ECa sensors are commercially available, each with a unique response profile (i.e., the relative contribution of soil at each depth to the integrated ECa reading provided by the sensor). The objective of this research is to determine if combining ECa datasets from multiple sensors with different response profiles can increase the ability of the combined dataset to estimate soil properties, particularly in strongly layered soils. Data were obtained on two Missouri claypan-soil fields with pronounced layering in soil clay content and within-field variability in the depth of topsoil above the clay layer. Numerous soil cores were also obtained to provide calibration data for soil characteristics. The sensor with the shallowest response profile provided the best estimates of surface-layer soil properties, while the sensor with the deepest response profile provided the best estimates of profile-average soil properties. Using multiple ECa datasets improved results in only some cases, primarily for profile-average properties. However, claypan soil topsoil depth estimations were improved when combining data from multiple sensors. Improved results might be obtained with approaches that consider the nonlinear depth-weighting functions of the sensors as part of the analysis.