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United States Department of Agriculture

Agricultural Research Service

Research Project: LANDSCAPE-BASED CROP MANAGEMENT FOR FOOD, FEED, AND BIOENERGY

Location: Cropping Systems and Water Quality Research

Title: Sensor-based nitrogen applications for corn: opportunities, on-farm demonstration results, and obstacles

Authors
item Scharf, Peter -
item Shannon, D. Kent -
item Sudduth, Kenneth
item Kitchen, Newell

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: June 12, 2013
Publication Date: August 13, 2013
Citation: Scharf, P.C., Shannon, D., Sudduth, K.A., Kitchen, N.R. 2013. Sensor-based nitrogen applications for corn: opportunities, on-farm demonstration results, and obstacles [abstract]. Nitrogen Use Efficiency Conference. Available Online.

Technical Abstract: Optimal N fertilizer rate for corn can vary substantially within and among fields. Current N management practices do not address this variability. Crop reflectance sensors offer the opportunity to diagnose crop N need and control N application rates at a fine spatial scale. Fifty-five replicated on-farm demonstrations were conducted from 2004 to 2008. Sensors were installed on the producer’s N application equipment and used to direct variable-rate sidedress N applications to corn at growth stages ranging from V6 to V16. A fixed N rate chosen by the cooperating producer was also applied. Relative to the producer’s N rate, sensors increased partial profit by $42/ha and yield by 110 kg/ha while reducing N use by 16 kg N/ha. This represents a reduction of approximately 25 percent in the amount of N applied beyond what was removed in the grain, thus reducing unused N that can move to water or air. Our results confirm that sensors can vary N rates across landscapes in a way that can out-perform rates chosen by producers. The biggest obstacle to adoption is probably the need to apply N to corn that is at least 12 inches tall, a practice that is used by only a small minority of corn producers. Concerns with applying N at this time include risk of not completing the application at the planned time, cost of equipment to manage timing risk, and conflicts with other field activities. Other obstacles include lack of uniformity in interpreting sensor values, the need to create high-N reference areas, concern about soil interference, sensor cost, effort required to get the system running correctly, and decision errors introduced by changes in sensor values over the course of a day.

Last Modified: 7/22/2014
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