Degradation of N-(n-butyl) Thiophosphoric Triamide (NBPT) with and without Nitrification Inhibitor in Soils
Bibliographic record
Abstract
Recent studies have shown that nitrification inhibitor (NI) impairs the efficacy of urease inhibitor, N-(n-butyl) thiophosphoric triamide (NBPT), in reducing ammonia volatilization and urea hydrolysis rate. A laboratory study was conducted to evaluate the influence of NI (specifically 3,4-dimethyl pyrazole phosphate) on the degradation of NBPT in six soils. Soils were amended with either NBPT (10 mg NBPT kg−1 soil) or NBPT plus NI (DI; 10 mg NBPT + 2.5 mg NI kg−1 soil), incubated at 21 °C, and destructively sampled eight times during a 14-day incubation period. The degradation of NBPT in soil was quantified by measuring NBPT concentration with high-performance liquid chromatography-mass spectrometry, and the degradation rate constant was modeled with an exponential decay function. The study showed that the persistence of NBPT in soil was not influenced by the presence of NI, as the NBPT degradation rate constant across soils was 0.5 d−1 with either NBPT or DI. In contrast, the degradation rate constant was significantly dependent on soils, with values ranging from 0.4 to 1.7 d−1. Soil pH was the most important variable affecting the persistence of NBPT in soils. The half-life of NBPT was 0.4 d in acidic soil and 1.3 to 2.1 d in neutral to alkaline soils. The faster degradation of NBPT in acidic soils may explain its reduced efficacy in such soils.
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.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".