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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #257173
Title: Integration of an Active Sensor Algorithm with Soil-Based Management Zones for Nitrogen Management in Corn

Author
item ROBERTS, DARRIN - Mississippi State University
item SHANAHAN, JOHN - Pioneer Hi-Bred Seed Company
item FERGUSON, RICHARD - University Of Nebraska
item ADAMCHUK, VIACHESLAV - McGill University - Canada
item Kitchen, Newell

Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 11/1/2010
Publication Date: 11/1/2010
Citation: Roberts, D., Shanahan, J., Ferguson, R., Adamchuk, V., Kitchen, N.R. 2010. Integration of an Active Sensor Algorithm with Soil-Based Management Zones for Nitrogen Management in Corn [abstract]. ASA-CSSA-SSSA Annual International Meeting, October 31-November 4, 2011, Long Beach, CA. ASA-CSSA-SSSA Annual Meeting Abstracts. Paper No. 316-7.

Interpretive Summary:

Technical Abstract: Active crop canopy sensors have been studied as a possible proximal sensing tool to assess in-season plant N status and direct spatially-variable N applications, and thereby increase NUE compared to uniform N application. A sensor-based N application algorithm was previously developed on small plots for use in corn. Some have also suggested the integration of crop-based sensing with soil-based management zones (MZ) as a more robust decision tool to guide variable-rate N application. The objectives of this study were to (1) evaluate a proposed [Solari et al. (2010)] active sensor algorithm against uniform N application in a variety of soil and climatic conditions, and (2) explore the usefulness of an integrated MZ and active sensor approach for improving N management. Research was conducted on 6 irrigated producer cornfields in central Nebraska during the 2007 and 2008 growing seasons. Five N application strategies were applied to field-length strips in a RCBD with 3 replications per field. In-season sensing and yield measurements were collected, and partial factor productivity (PFP) was calculated for each treatment. Additionally, 8 different soil data layers were collected for MZ delineation. Compared to uniform N application, integrating MZ and sensor-based N application resulted in substantial N savings for fine-textured soils with eroded slopes (~40-120 kg/ha). Sensor-based treatments in these soil types increased PFP ~13-75 kg grain/kg N applied. In other soil conditions, however, the current sensor-based N application algorithm may require further calibration, or may not provide substantial benefits compared to conventional uniform N management.