Growth effects in oregano plants (<i>Origanum vulgare</i> L.) assessment through inoculation of bacteria isolated from crop fields located on desert soils
Bibliographic record
Abstract
Bacteria can establish beneficial interactions with plants by acting as growth promoters and enhancing stress tolerance during plant interactions. Likewise, bacteria can develop multispecies communities where multiple interactions are possible. In this work, we assessed the physiological effects of three bacteria isolated from an arid environment (Bacillus niacini, Bacillus megaterium, and Moraxella osloensis) applied as single species or as a consortium on oregano (Origanum vulgare L.) plants. Moreover, we assessed the quorum-sensing (QS) signaling activity to determine the molecular communication between plant-growth-promoting bacteria. The plant inoculation with B. megaterium showed a positive effect on morphometric and physiologic parameters. However, no synergistic effects were observed when a bacterial consortium was inoculated. Likewise, activation of QS signaling in biofilm assays was observed only for interspecies interaction within the Bacillus genus, not for either interaction with M. osloensis. These results suggest a neutral or antagonistic interaction for interspecific bacterial biofilm establishment, as well as for the interaction with oregano plants when bacteria were inoculated in a consortium. In conclusion, we were able to determine that the bacterial interactions are not always positive or synergistic, but they also might be neutral or antagonistic.
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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 | 0.001 |
| 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".