Ammonium and nitrate levels of soil inoculated with Azospirillum brasilense in maize
Bibliographic record
Abstract
Azospirillum brasilense is a nitrogen fixing bacteria used in maize crop production due to its high capacity for plant growth promotion and yield increase. The present study aimed to evaluate ammonium and nitrate levels from soil inoculated with A. brasilense in maize crop production. The experiment was carried out in greenhouse conditions, using randomized blocks with split plots for 20 days with four replicates and two treatments where ammonium and nitrate levels were measured daily. The numbers of colony forming units of diazotrophic bacteria at initial and final stages of the experiment were counted in addition to the shoot and root dry mass measurement. The results were analyzed using F, Scott and Knott tests. The treatment which received inoculation did not show any statistically significant difference in the ammonium, nitrate levels either root or shoot dry mass as compared to the control. Also, there was no increase in the colony counts of diazotrophic bacteria. Taken together, the results showed that A. brasilense was not able to promote ammonium and nitrate levels after 20 days of its inoculation, suggesting that the plant growth promoting effect are not by fixing nitrogen during the initial plant development period and this period would be not appropriate for the plants to receive the inoculation. Key words: Azospirillum brasilense, maize, nitrogen fixer.
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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".