<i>Bacillus subtilis</i> and <i>Bacillus velezensis</i> population dynamics and quantification of spores after inoculation on ornamental plants
Bibliographic record
Abstract
Bacillus subtilis and Bacillus velezensis are used in organic agriculture as an alternative to chemical pesticides to fight against phytopathogen organisms. These Gram-positive soil-dwelling bacteria are able to resist harsh conditions and survive by differentiating into endospores. Few studies have examined how bacterial populations change on plants over time, and whether they remain active or enter a dormant state. Nonetheless, these characteristics are strikingly important to determine the usage of B. subtilis and B. velezensis and their efficacy in environmental conditions. Here, we investigated the population dynamics of B. subtilis NCIB3610 and B. velezensis QST713 when applied as spores on different ornamental plants. We report that on all the plants studied (Echinacea purpurea ‘Salsa red’, Echinacea purpurea ‘Fatal attraction’, and Lavandula angustifolia ‘Hidecote blue’), spores rapidly germinated and colonized the rhizoplane, maintaining a relatively low proportion of spores in the population over time, whereas the bacterial population on the leaves rapidly declined. Bacteria in the surrounding soil did not germinate and persisted as spores. Taken together, these results suggest that only cells found at the rhizosphere remain metabolically active to allow the formation of a lasting relationship with the plant, making possible beneficial effects from the inoculated bacteria.
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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".