Characterization of a plant-growth-promoting non-nodulating endophytic bacterium (<i>Stenotrophomonas maltophilia</i>) from the root nodules of <i>Mucuna utilis</i> var. <i>capitata</i> L. (Safed Kaunch)
Bibliographic record
Abstract
Nonrhizobial root nodule endophytic bacteria are known to have beneficial effects on host plants and are also considered contaminants or opportunists. They grow either individually or as a co-occupant of the root nodules of legumes. In this study, a nonrhizobial endophytic bacterial strain was isolated from the root nodules of the medicinal legume Mucuna utilis var. capitata L.; phenotypic, genotypic, and agricultural characterization was performed using a HiMedia kit and 16S rRNA sequencing. This strain showed tremendous seedling growth potential (30%), compared with the control, as well as a strong antagonistic nature against the plant pathogenic fungus Fusarium udum when plant growth parameters were analyzed. The strain, identified by 16S rRNA as Stenotrophomonas maltophilia, showed a multitude of plant-growth-promoting attributes both direct (IAA, phosphate solubilization) and indirect (ACC deaminase, siderophore) and enhanced the growth of host plant in field trials. This is the first report of the plant-growth-promoting potential of this endophytic bacterium from the nodules of M. utilis var. capitata L.; hence, it has potential for use in various biotechnological applications in various industries.
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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".