Nitrogen form, time and rate of application, and nitrification inhibitor effects on crop production
Bibliographic record
Abstract
Karamanos, R., Hanson, K. and Stevenson, F. C. 2014. Nitrogen form, time and rate of application, and nitrification inhibitor effects on crop production. Can. J. Plant Sci. 94: 425–432. Nitrogen management options for anhydrous ammonia (NH 3 ) and urea were compared in a barley–wheat–canola–wheat cropping sequence (2007–2010) at Watrous and Lake Lenore, SK. The treatment design included a factorial arrangement of N fertilizer form (NH 3 versus urea), nitrification inhibitor application, time of N application (mid-September, mid- to late October, and spring) and four N fertilizer rates (0, 40, 80 and 120 kg ha −1 ). Anhydrous ammonia applications at 40 kg N ha −1 in 2008 (fall) and in 2010 (all times of application) resulted in wheat yield reductions relative to the same applications for urea. For wheat years, yield was reduced for both fall versus spring N fertilizer applications, when no nitrification inhibitor was applied and the inclusion of nitrification inhibitor maintained wheat yield at similar levels across all times of N fertilizer applications, regardless of form. Protein concentration was approximately 2 g kg −1 greater with urea compared with NH 3 at both sites in 2008 and only at Watrous in 2010. Also, early versus late fall N fertilizer applications consistently increased N concentration of grain only for the 40 and/or 80 kg N ha −1 rates. Effects of nitrification inhibitor on N concentration were not frequent and appeared to be minimal. Urea had greater agronomic efficiency (AE) than NH 3 at the lower N fertilizer rates. The nitrification inhibitor had a positive effect on wheat AE only for early fall N fertilizer applications. It can be concluded that for maximum yields NH 3 or urea will be suitable if applied at rates of 80 kg N ha −1 and greater. If N fertilizer is applied at 40 kg N ha −1 , especially in fall without inhibitor, urea is better. In terms of protein concentration for wheat, urea seemed to better than NH 3 and fall was better than spring application.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".