Transformation of Fall‐Banded Urea: Application Date, Landscape Position, and Fertilizer Additive Effects
Bibliographic record
Abstract
A 2‐yr study was initiated in the fall of 2000 to generate fundamental information on the effects of application date, landscape position, and a combined urease and nitrification inhibitor (NBPT [N‐(n‐butyl) thiophosphoric triamide] and DCD [dicyandiamide], respectively) on the rate of transformation of fall‐banded urea fertilizer into NH4+ and eventually NO3− under conditions typical for Manitoba, Canada. Landscape position did not have a large effect on the conversion of banded urea to NO3− under the moisture conditions present during the autumn period at the sites. Delaying application of fall‐banded urea fertilizer into the late fall and the presence of NBPT and DCD slowed nitrification and increased the recovery of fertilizer N as NH4+ (%RFN as NH4+) in the soil before it froze. Date of application, the soil temperature on the date of application, and the accumulation of SHU (soil heat units) and NHU (nitrification heat units) were all linearly related to the %RFN as NH4+ Accumulated SHU and NHU were most strongly correlated with the %RFN as NH4+ at the end of the fall, with and without inhibitors. The interactions between time, temperature, and nitrification demonstrate that producers in the Northern Great Plains region must consider the overall length of time that fall‐applied N fertilizer will be exposed to the soil before the soil freezes, even after the soil temperature has reached a given level and even if the fertilizer is banded.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".