In-soil banded versus post-seeding liquid nitrogen applications in no-till spring wheat and canola
Bibliographic record
Abstract
Delaying nitrogen (N) applications into the growing season as a risk management tool is a concept that has received considerable attention in recent years. A 3-yr field study with spring wheat (Triticum aestivum L.) and canola (Brassica napus L.) was conducted at two Saskatchewan locations, Indian Head and Scott. The effects of postponing N applications for up to 30 d after seeding and several application methods were evaluated against mid-row banded urea at seeding. Liquid urea ammonium-nitrate (UAN) was applied at four separate times relative to seeding, either as an in-soil coulter band or a surface band. The surface band applications were applied either with or without the addition of 5% ammonium thiosulphate (ATS), a potential urease inhibitor. The dependent variables considered included plant density and grain yield for both crops, and grain protein in wheat. The only effect on plant density occurred in canola, where the post-seeding coulter applications slightly reduced stands compared with the other treatments. Postponing N fertilization for up to 30 d after seeding compared with N fertilization at seeding did not affect the yield of canola or protein in spring wheat, but reduced the yield of spring wheat at Indian Head in 2003, which was a very dry growing season. The coulter applications only showed a slight advantage over the surface band applications. For the surface band applications, the addition of 5% ATS did not provide a noticeable advantage over UAN alone. Canola appeared to be less sensitive to post-seeding applications than spring wheat. Deferring the entire amount of fertilizer N into the growing season appears to be a viable option but it is not without risk, especially when dry conditions are encountered. Key words: Triticum aestivum L., Brassica napus L., nitrogen management, no-till, surface dribble, urea-ammonium nitrate
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".