Effect of Deodorization Microorganisms on Release of NH_3 and H_2S and Matter Transformation
Bibliographic record
Abstract
In this study,the deodorization strains for cow mattle compost were selected by hyperthermia and ammonia sequential domestication,these strains's effect on release amount of NH3 and H2S and matter transformation were investigated.Deodorization strains B1 and A1 showed the best effect on deodorization,the total release amount of NH3 decreased by 68.59% and 61.00% compared to control,NH+4-N just increased by 4.47% and 7.19%,NO3-N increased slightly,organic nitrogen increased by 28.99% and 27.42%,and total nitrogen increased by 19.81% and 18.80% respectively,the result indicated that deodorization strains can not only stimulate nitrogen transformation,from inorganic nitrogen into organic nitrogen,but also reduce nitrogen loss effectively;Total release amount of H2S decreased by 89.69% and 86.88% compared to control,sulfate increased by 40.77%,36.49% and total sulphur content increased by 40.77%,36.49% respectively,the experimental result showed that deodorization strains promoted transformation of sulfate and reduced sulphur loss.The correlation analysis showed that release amount of NH3 had a extremely significant positive correlation with release amount of H2S and pH and a negative correlation with total nitrogen,organic nitrogen and sulfate.Release amount of H2S had a significant positive correlation with pH and a negative correlation wih total sulphur and sulfate.The analysis of variance showed that release amount of NH3 and H2S for treatment and control had a significant difference,the results displayed that deodorization strains can control release of NH3 and H2S on cow mattle compost effectively,and keeping nitrogen and sulphur.
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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) | 0.001 | 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".