|Bobryk, C - University Of Missouri|
|Myers, D - Dupont Pioneer Hi-Bred|
|Shanahan, J - Dupont Pioneer Hi-Bred|
|Sudduth, Kenneth - Ken|
Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 8/31/2015
Publication Date: 11/15/2015
Citation: Bobryk, C., Myers, D.B., Kitchen, N.R., Shanahan, J., Sudduth, K.A., Drummond, S.T. 2015. Validating a high-resolution digital soil map for precision agriculture across multiple fields [abstract]. ASA-CSSA-SSSA International Annual Meeting, November 15-18, 2015, Minneapolis, Minnesota. Paper No. 94667.
Technical Abstract: Digital soil mapping (DSM) for precision agriculture (PA) management is aimed at developing models that predict soil properties or classes using legacy soil data, sensors, and environmental covariates. The utility of DSM for PA is based on its ability to provide useful spatial soil information for optimizing crop yields while reducing input costs and associated environmental impacts from improved management activities, such as variable rate nutrient applications. However, the accuracy of output from a DSM should be quantified in order to assess how well the digital representations of soils match existing soil properties. Inherent productivity of a soil is affected by differences in soil profile properties, such as organic matter, texture, nutrient availability, or hydraulic conductivity. Therefore, soil profile validation is needed to support the efficacy of high-resolution DSM output for management decisions, especially at regional scales. The overall objective of this investigation was to determine the accuracy of a new, high-resolution PA DSM, termed Environmental Response Unit (ERU), for predicting soil profile properties. Predictions from the DSM were compared with independent sample point observations containing soil profile information collected in several fields across the U.S. Midwest Corn Belt region with a broad range in measured soil properties. These types of large-scale validation efforts are necessary to determine the accuracy, and ultimately the utility, of DSM products designed to better inform PA management decisions for producers.