Variable rate nitrogen management in corn: Response in two crop rotations

Abstract

Decision-making criteria to accurately predict nitrogen (N) rates in corn (Zea mays L.) would greatly benefit canopy sensor-guided variable rate N (VRN) management with positive implications for water quality. The objectives of this study were to measure corn yield response to VRN applied at the midvegetative corn growth stage and compare yield and agronomic efficiency (AE) between a one-time spring-N application (preplant or early sidedress) and two VRN management strategies, split-N (VRN^S) and rescue-N (VRN^R). Field sites located across Iowa received spring-N fertilizer at six application rates, with additional N potentially applied with each VRN spring-N rate and for the VRN^S and VRN^R strategies at the V10 growth stage based on canopy sensing. Drought conditions were evident during 2012 and 2013 in Iowa, which resulted in reduced corn yield and requirement for N fertilizer at many site-years. The VRN with 0 and 56 kg N ha⁻¹ (50 lb N ac⁻¹) applied in the spring was most closely aligned with calculated economic optimum N rate and AE. The VRN^S and VRN^R strategies applied more N than was needed, compared to spring-N only. Canopy sensors did not detect adequate to excess N, and therefore N applied prior to VRN application should be part of sensing-based algorithm criteria. Mean corn yield with the soybean (Glycine max [L.] Merr.)–corn rotation was not maintained with VRN when no spring-N was applied. Yield comparison showed no differences between spring-N, VRN^S, and VRN^R for both rotations. However, the greatest AE was achieved with spring-N and the VRN^S strategy in the soybean–corn rotation. Weather events that occur during and after canopy sensing and VRN application remain an important factor for successful corn yield response to N rate and timing, and should be considered with canopy sensor VRN. Results from this study provide feedback on how to translate remote sensing data into VRN management.