Efficacy of a new <i>N</i>-(<i>n</i>-butyl) thiophosphoric triamide formulation in reducing ammonia volatilization from urea-based fertilizers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
N-(n-Butyl)thiophosphoric triamide (NBPT) has been reported to reduce ammonia volatilization from surface-applied urea and urea ammonium nitrate (UAN). A new NBPT formulation (ARM U™, 18% NBPT) that contains a polymer allowing for lower application rate of NBPT was evaluated for its efficacy relative to Agrotain ® (30% NBPT) and Arborite ® (24% NBPT). Trials consisted of (i) a greenhouse study that compared two rates of ARM U-treated urea (360 and 540 mg NBPT kg −1 urea) with Arborite- or Agrotain-treated urea (480 and 600 mg NBPT kg −1 urea, respectively) and (ii) a field study that compared urea and UAN treated with either ARM U (360 mg NBPT kg −1 urea) or Agrotain (600 mg NBPT kg −1 urea) at two sites. Static chambers fitted with acid-charged discs were used to measure ammonia volatilization at six or seven dates over 28 d. In the greenhouse study, ammonia volatilization was reduced by 96% with either ARM U or Agrotain and 95% with Arborite. In the field study, ARM U and Agrotain reduced ammonia volatilization from urea by 80% and 66%, respectively, across sites. Similarly, ammonia volatilization from UAN was reduced by 46% and 60% with ARM U and Agrotain, respectively. Despite the lower NBPT application rates with ARM U, ammonia reduction by ARM U, Agrotain, and Arborite was not significantly different. The addition of ARM U to urea and UAN enabled lower application rate of NBPT without compromising its efficacy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it