The effect of N fertilizer placement, formulation, timing, and rate on the agronomic performance in wheat
Bibliographic record
Abstract
Increasing the efficiency of nitrogen fertilizer uptake by crops improves the agronomic, economic, and environmental value of fertilizer N. Band placement of urea below the soil surface increased recovery of N in plants in both conventional and no-tillage systems. The latter systems require all fertilizers be applied before or during the seeding operation. In order to avoid seedling damage caused by fertilizer, side banding and mid-row banding opener systems have been developed to separate the seed and fertilizer. The objective of this study was to compare the agronomic performance in wheat between side banding and mid-row banding N fertilization and estimate effects of fertilizer formulation, timing and rate in an Orthic Brown Chernozem. A three-year experiment (2000-2002) was conducted near Swift Current in the Brown Soil Zone (Swinton silt loam, Orthic Brown Chernozem) of southern Saskatchewan. Seventeen treatments were arranged in a randomized complete block design in four replications with plot size of 3 m × 9.2 m. A Canada Western Red Spring wheat, AC Barrie, was seeded on a no-tillage management. Results showed that the environment had a major impact on the grain yield and biomass production. In general, the difference in agronomic performance between side banding and mid-row banding treatments was small.
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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) | 0.000 | 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".