Screening of Diazotrophs as Plant Growth Promoters and Their Effect in the Development of Maize Seed
Bibliographic record
Abstract
Free-living diazotrophs play an important role as plant growth promoters by supplementing nitrogen to deficient soils. In this study, six diazotrophic isolates were selected from 36 previously screened diazotrophic isolates for their mode of action to promote plant growth. A nitrogen free medium was used to screen nitrogen fixing diazotrophs. All strains have exhibited some activity of indole-3-acetic acid production. Strain MAF7-1 shown the highest (0.448 mg ml-1), while strain NUL3-2 exhibited the least (0.032 mg ml-1) production of IAA. Though all isolates were unable to solubilize inorganic phosphate, were able to inhibit the growth of Fusarium oxysporum that causes wilting to plants. There was no significant difference in maize seed germination vigour and rate. However, MAF7-1 had better germination rate and seed vigour (27.5%) when compared to the control (16%). Except strain NUL3-2, all showed significant increase of root length and dry weight of maize seedlings. Therefore, the choice of strain to be used for production of biofertilizer should not only be based on the nitrogenase activity, but also on ability to produce phytohormones. Strain NUL3-2, MAF7-1 and MAF7-3 are potential strains that can be used in the production of biofertilizer. Further study of these strains in depth as plant growth agents and biofertilizer is commendable for future application.
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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) | 0.000 | 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".