Ammonia volatilization from soils fertilized with urea and varying rates of urease inhibitor NBPT
Bibliographic record
Abstract
Loss of N as ammonia (NH 3 ) from surface-applied urea fertilizer may be high if hydrolysis takes place at the soil surface. The urease inhibitor N-(n-butyl) thiophosphoric triamide (NBPT) may reduce NH 3 loss from urea by delaying hydrolysis. Field studies using surface chambers were conducted in 1996 and 1997 to compare the amount of NH 3 volatilized from surface applications of granular urea (100 kg N ha –1 ) treated with varying concentrations of NBPT (0, 0.05, 0.10 and 0.15% NBPT wt/wt). The studies were conducted on two Orthic Black Chernozemic soils, a Stockton fine sandy loam and a Newdale clay loam, in May and again in July to determine the relative influence of soil texture and temperature on NBPT performance at the varying rates. Ammonia losses were measured at various times to 12 d after fertilization (DAF) in 1996 and to 21 DAF in 1997. Total NH 3 losses decreased in the order of 0% > 0.05% > 0.15% > 0.10% where use of NBPT reduced total NH 3 loss by 28-88% over the entire study duration, and by 82 to 96% during periods of peak loss from unamended urea. Ammonia volatilization losses from NBPT-amended urea treatments were lower in May than in July. The total loss measured at all rates of NBPT was higher for the fine sandy loam soil except in May 1997 where cool conditions resulted in slightly lower loss than for the clay loam soil. Amending urea with NBPT at a rate as low as 0.05% wt/wt can reduce NH 3 loss from surface-placed urea fertilizer, so that a greater proportion of fertilizer N is retained in the soil for plant use. The inhibitor helps reduce the amount of NH 3 derived from urea entering the atmosphere to react or to be deposited elsewhere, and may lessen the need to overfertilize to compensate for potential NH 3 losses. Key words: N-(n-butyl) thiophosphoric triamide, urease inhibitor, surface applications
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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 | 0.000 |
| 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 | 0.001 |
| 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".