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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #329654
Title: Sensor-based nitrogen applications out-performed producer-chosen rates for corn in on-farm demonstrations

Author
item SCHARF, PETER - University Of Missouri
item SHANNON, D - University Of Missouri
item Sudduth, Kenneth - Ken
item Kitchen, Newell

Submitted to: International Conference on Precision Agriculture Abstracts & Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 6/27/2016
Publication Date: 7/31/2016
Citation: Scharf, P.C., Shannon, D.K., Sudduth, K.A., Kitchen, N.R. 2016. Sensor-based nitrogen applications out-performed producer-chosen rates for corn in on-farm demonstrations. In: International Conference on Precision Agriculture Proceedings, July 31-August 3, 2016, St. Louis, Missouri. Avaialble: https://ispag.org/proceedings/?action=abstract&id=2150&search=topics.

Interpretive Summary:

Technical Abstract: Optimal nitrogen 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 potential to diagnose crop N need and control N application rates at a fine spatial scale. Our objective was to evaluate the performance of sensor-based variable-rate N applications to corn, relative to constant N rates chosen by the producer. 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 (P = 0.0007) and yield by 110 kg/ha (P = 0.18) while reducing N use by 16 kg N/ha (P = 0.015). This represents a 24 to 26% reduction 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 choose N rates for corn that perform better than rates chosen by producers.