Potential of chemical stabilizers to prolong urease inhibition in the soil–plant system#
Bibliographic record
Abstract
Abstract Background Urea is the most common nitrogen fertilizer applied to agricultural lands, and it is often treated with urease inhibitors to prevent loss of ammonia during urea hydrolysis. However, urease inhibitors like N‐(n‐butyl) thiophosphoric triamide (NBPT) are susceptible to degradation in soil. Aims This study tested dimethyl sulfoxide, ethylene glycol and glycerol as stabilizers that could extend the inhibition effect of NBPT in a soil–plant system that received liquid urea fertilizer. Methods We undertook a pot experiment in which two soil types (brown and black soils) were amended with liquid urea plus NBPT, with and without chemical stabilizers, then planted with bok choy. The urease activity, urea and mineral N concentration in soil and nitrogen uptake in bok choy were monitored for the next 30 days. Results Five days after adding fertilizer, urease activity was 27%–51% lower in brown soil amended with the urea‐NBPT solutions and 32%–75% less when black soil received urea‐NBPT solution than in the control soil that received urea solution. Nearly 100% of the urea was hydrolyzed in control soil receiving urea solution after 5 days, but only 21%–41% of urea was hydrolyzed in soil amended with urea‐NBPT solution after 5 days. Stabilizers did not improve the stability of NBPT, nor did they affect the nitrogen uptake by bok choy, which was similar in the urea‐amended control soil (124 mg N pot–1) and the urea‐NBPT‐treated soil (117 mg N pot–1) during the growth period. Conclusions Chemical stabilizers did not prolong the NBPT inhibition of urease activity, probably because the stabilizer compounds are vulnerable to degradation in well‐watered and planted soils.
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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 | 0.000 |
| 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".