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ARS Home » Plains Area » Lincoln, Nebraska » Agroecosystem Management Research » Research » Publications at this Location » Publication #240384

Title: Use of the Soil Management Assessment Framework in Spatially Variable Fields

item Wienhold, Brian
item Karlen, Douglas
item Andrews, Susan

Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 6/5/2009
Publication Date: 8/27/2009
Citation: Wienhold, B.J., Karlen, D.L., Andrews, S.S. 2009. Use of the Soil Management Assessment Framework in Spatially Variable Fields [abstract]. ASA-CSSA-SSSA Annual Meeting, November 1-5, 2009, Pittsburgh, Pennsylvania. 2009 CDROM. Abstract No. 51-5.

Interpretive Summary:

Technical Abstract: Soil management is typically applied to tracts of land exhibiting spatial variability. Intensive soil sampling to quantify this variability is labor intensive and expensive. Additional approaches are needed to assess soil management within spatially variable fields. Apparent electrical conductivity (ECa) has been used to map spatially variable fields and numerous physical, chemical, and biological soil properties correlate well with ECa. The Soil Management Assessment Framework (SMAF) has been developed as an assessment tool that uses measured soil indicator data to evaluate management effects on soil function. This paper presents initial results from efforts to combine use of ECa with the SMAF. An irrigated field in south central Nebraska was ECa mapped and soil samples were collected based on this map. Available P was determined for these soil samples and regressed against ECa at the soil sampling points. The resulting regression was used to predict available P for the remaining ECa sample points. Estimated available P was then scored using the SMAF. We then generated maps of estimated available P and SMAF available P scores. The map generated using SMAF available P scores delineated areas of the field where P fertilizer should be applied. The described approach has potential for improving management of spatially variable fields.