Urea fertilizer forms affect grain corn yield and nitrogen use efficiency
Bibliographic record
Abstract
Gagnon, B., Ziadi, N. and Grant, C. 2012. Urea fertilizer forms affect grain corn yield and nitrogen use efficiency. Can. J. Soil Sci. 92: 341-351. Controlled-release urea may be a good management strategy to increase the efficiency of N fertilizers. In a 3-yr study (2008-2010) conducted on a clay soil near Quebec City, Canada, we compared the effect of polymer-coated urea (PCU), nitrification inhibitor urea (NIU), dry urea and urea ammonium nitrate 32% (UAN) on corn yield, plant N accumulation and soil NO3-N remaining at harvest. Corn was fertilized with urea and PCU at 50, 100 and 150 kg N ha-1 in addition to an unfertilized control (0 N), and NIU and UAN at 150 kg N ha-1. Urea, PCU, and NIU were pre-plant broadcast whereas UAN was side-banded at the six-leaf stage of corn. Response to N fertilization occurred in all years, but the magnitude of the response varied with years. In wet years (2008 and 2009), PCU and NIU resulted in higher grain yield than urea, but the increase was greater for PCU (+0.8 to 1.6 Mg ha-1) than for NIU (+0.3 to 0.6 Mg ha-1). In a dry year (2010), no significant difference was found between urea, PCU and NIU. Yields and apparent N recovery were comparable for PCU and UAN except in the dry year, when plant N accumulation was much higher for the UAN treatment. At harvest, soil NO3-N was increased by PCU in all years. Economic analysis revealed that despite 30% higher cost, PCU gave comparable net returns at equivalent N rate than UAN in wet years. We conclude that controlled-release urea, particularly PCU, would be an additional option to farmers instead of sidedressed UAN application for fertilizing corn grown in eastern Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".