Diversity and Functionality of Culturable Endophytic Bacterial Communities in Chickpea Plants
Bibliographic record
Abstract
The aims of this study were to isolate, identify and characterize culturable endophytic bacteria from chickpea (Cicer arietinum L.) roots grown in different soils. In addition, the effects of rhizobial inoculation, soil and stress on the functionality of those culturable endophytic bacterial communities were also investigated. Phylogenetic analysis based on partial 16S rRNA gene sequences revealed that the endophytic bacteria isolated in this work belong to the phyla Proteobacteria, Firmicutes and Actinobacteria, with Enterobacter and Pseudomonas being the most frequently observed genera. Production of indoleacetic acid and ammonia were the most widespread plant growth-promoting features, while antifungal activity was relatively rare among the isolates. Despite the fact that the majority of bacterial endophytes were salt- and Mn-tolerant, the isolates obtained from soil with Mn toxicity were generally more Mn-tolerant than those obtained from the same soil amended with dolomitic limestone. Several associations between an isolate’s genus and specific plant growth-promoting mechanisms were observed. The data suggest that soil strongly impacts the Mn tolerance of endophytic bacterial communities present in chickpea roots while rhizobial inoculation induces significant changes in terms of isolates’ plant growth-promoting abilities. In addition, this study also revealed chickpea-associated endophytic bacteria that could be exploited as sources with potential application in agriculture.
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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 | 0.001 | 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".