Influence of source, timing and placement of nitrogen on grain yield and nitrogen removal of durum wheat under reduced- and conventional-tillage management
Bibliographic record
Abstract
Effective fertilizer management is critical to maintain economic production and protect long-term environmental quality. Field studies were conducted over 4 yr at two locations in southwestern Manitoba to determine the effect of source, timing and placement of N on grain yield and N recovery of durum wheat (Triticum durum L. ‘Sceptre’) under reduced-tillage (RT) and conventional-tillage (CT) management. The effect of N management on durum grain yield and N recovery differed with soil type and tillage system. On the clay loam (CL) soil, lower yields with fall- as compared with spring-banded N were more frequent under RT than CT. Lower yields occurred more frequently with fall-applied as compared with spring-applied urea ammonium nitrate (UAN) than when urea or NH 3 was the N source. On the drier fine sandy loam (FSL) soil, fall applications of N generally produced similar to higher grain yield than did spring applications. Differences among fertilizer sources and tillage systems were much less frequent with spring than fall applications of N. Where differences occurred, durum grain yields were higher with in-soil than surface applications of urea or UAN. In-soil applications of urea and UAN increased durum grain yield as compared with surface applications more frequently under RT than CT on the CL soil where yield potential was high, whereas increases on the FSL were as common under CT as under RT. On soils with a high yield potential, enhanced immobilisation and/or volatilisation of surface-applied N may reduce grain yield by reducing available N, particularly under RT. Selection of a suitable source-timing and placement combination to optimise crop yield may be more important under RT than CT. Key words: Conservation tillage, direct seeding, placement
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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 | 0.001 |
| 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".