Biodegradable PASP can effectively inhibit nitrification, moderate NH <sub>3</sub> emission, and promote crop yield
Bibliographic record
Abstract
Polyaspartic acid (PASP) is a low-cost, environmentally friendly, and multifunctional polymer material. The knowledge regarding the effects of PASPs, especially the PASPs with a different molecular weight (MW), on nitrogen use efficiency (NUE), ammonia (NH3) volatilization and nitrous oxide (N2O) emission in crop fields is scarce. In this study, maize pot experiments were conducted to evaluate three types of PASPs with different MW. Five treatments were designed: (1) application of chemical phosphorus (P) and potassium (K) fertilizer (PK), (2) PK plus urea (NPK), (3) NPK plus PASP-1 (PASPT1, MW: 5517), (4) NPK plus PASP-2 (PASPT2, MW: 6934), and (5) NPK plus PASP-3 (PASPT3, MW: 7568). The yield indicators of crop height, straw dry weight and 100-grain weight showed that PASP application improved the crop growth. In PASP3, NUE reached 46.1%, almost double of that in NPK (28.6%). Moreover, there were significantly less N losses in the forms of NH3 volatilization and NO2 emission following PASP amendment than regular urea application. Another positive impact revealed that PASP inhibited the transformation of NH4+-N to NO3–N. Among the three PASPs, PASP-3 with the highest MW overall presented optimal effects, implying that MW was a major driving factor for PASP performance on maize production.
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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".