Mediterranean Native Leguminous Plants: A Reservoir of Endophytic Bacteria with Potential to Enhance Chickpea Growth under Stress Conditions
Bibliographic record
Abstract
Bacterial endophytes, a subset of a plant’s microbiota, can facilitate plant growth by a number of different mechanisms. The aims of this study were to assess the diversity and functionality of endophytic bacterial strains from internal root tissues of native legume species grown in two distinct sites in South of Portugal and to evaluate their ability to promote plant growth. Here, 122 endophytic bacterial isolates were obtained from 12 different native legume species. Most of these bacteria possess at least one of the plant growth-promoting features tested in vitro, with indole acetic acid production being the most common feature among the isolates followed by the production of siderophores and inorganic phosphate solubilization. The results of in planta experiments revealed that co-inoculation of chickpea plants with specific endophytic bacteria along with N2-fixing symbionts significantly improved the total biomass of chickpea plants, in particular when these plants were grown under saline conditions. Altogether, this study revealed that Mediterranean native legume species are a reservoir of plant growth-promoting bacteria, that are also tolerant to salinity and to toxic levels of Mn. Thus, these bacterial endophytes are well adapted to common constraints present in soils of this region which constitutes important factors to consider in the development of bacterial inoculants for stressful conditions in the Mediterranean region.
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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".