Journal
AGRONOMY JOURNAL
Volume 113, Issue 2, Pages 1961-1973Publisher
WILEY
DOI: 10.1002/agj2.20521
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Funding
- Canada First Research Excellence Fund
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Corn producers often overapply nitrogen fertilizer due to uncertainty in actual corn N requirements. On-farm nitrogen trials using delta yield method can help producers better understand their N needs and estimate economic optimum N rates reliably. The dY-EONR estimation model has shown promising results with low return losses and offers a practical method for optimizing nitrogen fertilizer use in corn production.
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.
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