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Delta yield–based optimal nitrogen rate estimates for corn are often economically sound
Author(s) -
Janovicek Ken,
Banger Kamaljit,
Sulik John,
Nasielski Joshua,
Deen Bill
Publication year - 2021
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.1002/agj2.20521
Subject(s) - yield (engineering) , mathematics , zea mays , fertilizer , nitrogen fertilizer , agronomy , calibration , statistics , physics , biology , thermodynamics
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 ( R 2 = .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.