The influence of nitrogen source and stabilization in fertilizer formulations on Western Canadian spring wheat
Bibliographic record
Abstract
Urea fertilizer has become the dominant form of nitrogen (N) fertilization with N use efficiencies near 60% in the Canadian prairies. Utilization of fertilizers such as ammonium sulfate nitrate (ASN) or calcium ammonium nitrate (CAN) could provide spring wheat growers with a viable alternative N formulation. Inclusion of nitrogen-stabilizers, such as nitrification inhibitor 3,4-dimethylpyrazole succinic acid (DMPSA) or urease inhibitor N-(n-butyl) thiophosphoric triamide (NBPT) have been shown to hinder N loss and enhance crop productivity. A 2-year field-study assessing different N-based banded fertilizer formulations was carried out in a Dark Grey Luvisol and Dark Brown Chernozem soil within Alberta. In the Dark Grey soil, urea displayed more consistent crop yield responses than ASN or CAN, while the crop yield response was similar across formulations in the Dark Brown soil zone. In both soil types, use of banded nitrogen-stabilizers among the N formulations failed to show significant and continuous improvements to crop productivity; however, addition of DMPSA to CAN numerically surpassed the grain yield of un-stabilized CAN. The impacts of DMPSA were less consistent in urea, where only 63% of comparisons resulted in a positive outcome for crop yield over untreated urea. Across both soil zones, banded urea + NBPT and urea + double inhibitor (NBPT + DMPSA) led to inconsistent yield differences over un-stabilized urea. Overall, the influence of environment and soil type played a major factor in determining the crop productivity outcome across N formulations and wheat class.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".