Delta yield–based optimal nitrogen rate estimates for corn are often economically sound

Corn producers often overapply nitrogen (N) fertilizer to minimize risk of yield loss because of uncertainty regarding actual corn N requirements. On‐farm N trials, which are simple to deploy and interpret, may enable producers to better understand their corn N fertilizer requirements. We analyzed a...

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Veröffentlicht in:Agronomy journal 2021-03, Vol.113 (2), p.1961-1973
Hauptverfasser: Janovicek, Ken, Banger, Kamaljit, Sulik, John, Nasielski, Joshua, Deen, Bill
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Sprache:eng
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Zusammenfassung:Corn producers often overapply nitrogen (N) fertilizer to minimize risk of yield loss because of uncertainty regarding actual corn N requirements. On‐farm N trials, which are simple to deploy and interpret, may enable producers to better understand their corn N fertilizer requirements. We analyzed a database of corn yield response to N trials conducted in Ontario, Canada to determine if delta yield (dY) N trials can reliably estimate economic optimum N rates (EONRs) and to assess the financial liability of dY‐EONR estimates. Delta yield is calculated as the yield difference between nonlimiting and very low (starter only) N rates. The dY‐EONR estimation relationship is derived from a rectangular hyperbolic relationship between agronomic efficiency and dY. The derived dY‐EONR relationship has a rapid initial estimated EONR rate of increase that diminishes with increasing dY and that approaches a constant increase rate of 16.1 kg N ha–1. At a N‐corn price ratio of 7, the dY‐EONR estimation model has RMSE = 29.1 kg N ha–1 (R2 = .64). Within range of recent corn and N prices, 64–80% of dY‐EONR estimates in combined calibration and validation data (n = 746) had return losses less than $25 ha–1 relative to the actual EONR. Return losses exceeding $50 ha–1 occurred for 8–18% of the dY‐EONR estimates, most of which (83–98%) were due to overestimation. Delta yield trials provide an easily implemented method for corn producers to conduct on‐farm yield response trials repeatedly over years in order to obtain a better idea of their N requirements.
ISSN:0002-1962
1435-0645
DOI:10.1002/agj2.20521