Identification, evaluation and selection of a bacterial endophyte able to colonize tomato plants, enhance their growth and control <i>Xanthomonas vesicatoria</i>, the causal agent of the spot disease
Bibliographic record
Abstract
Beneficial endophytes are key factors in plant productivity and disease control; therefore, research is ongoing to characterize the potential of endophytes as microbial inoculants to promote plant growth and act as biocontrol agents. In this study, we searched for and identified a set of endophytes occurring naturally in a few important crops. Beneficial endophytes were shown to antagonize several important fungi and bacteria, in particular those affecting tomato (Solanum lycopersicum), including Rhizoctonia solani, Alternaria alternata, Clavibacter michiganensis pv. michiganensis, Ralstonia solanacearum, and Xanthomonas vesicatoria. We characterized the most promising as potential inoculants of tomato, aiming to foster plant growth and control the bacterial spot disease caused by Xanthomonas vesicatoria. Among the selected endophytes, we identified a novel streptomycetes, taxonomically related to Streptomyces avermitilis and a pseudomonad, identified as Pseudomonas granadensis. The beneficial effects of these two bacteria, used as single inoculants or as a combination of both, were seen in a significant increase in root and shoot length (approximately 31% and 34% for the streptomycetes and 18% and 16% for the pseudomonad) and dry root biomass (90% for the streptomycetes and 70% for the pseudomonad). Additionally, both inoculants reduced disease progression and severity following inoculation with X. vesicatoria. There was no significant difference between plants treated with single inoculants and plants treated with both. The penetration and efficient colonization of tomato tissues by a green fluorescent protein-tagged culture of the streptomycetes was observed by confocal microscopy, confirming its endophytic nature.
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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) | 0.001 | 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".