Influence of source, timing and placement of nitrogen fertilization on seed yield and nitrogen accumulation in the seed of canola under reduced- and conventional-tillage management
Bibliographic record
Abstract
Field studies over 4 yr at two locations in southwestern Manitoba investigated the effect of N source, timing and method of placement on seed yield and N accumulation in the seed of canola (Brassica napus L. “Legend”) under reduced tillage (RT) or conventional-tillage (CT) management. The effect of N management on seed yield and N accumulation in the seed differed with soil type and tillage. Seed yields were frequently lower on the clay loam (CL) soil with fall-applied rather than spring-applied urea and urea ammonium nitrate (UAN), possibly due to losses through immobilization, denitrification and leaching. On the drier fine sandy loam soil (FSL), seed yield and N accumulation in the seed were generally similar with fall and spring N application, possibly because N supply was not as limiting as on the CL soil. Fall-applied anhydrous ammonia tended to produce higher canola seed yields than either fall-applied urea or UAN. Differences among fertilizer sources and between tillage systems were much less frequent with spring than fall N applications. However, under RT spring-banded anhydrous ammonia tended to produce higher canola seed yield than urea or UAN. Canola seed yield was lower with surface applications of N than with in-soil applications more frequently under RT than CT, presumably because surface residue under RT enhanced volatilization and immobilization losses. As differences in seed yield tended to be greater and more frequent under RT than CT, effective N management could provide a greater advantage under RT than CT. Key words: Conservation tillage, direct seeding, nitrogen fertilizer management, Brassica napus
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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 | 0.001 |
| 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 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".