Evaluating the biocontrol potential of Canadian strain Bacillus velezensis 1B-23 via its surfactin production at various pHs and temperatures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Microorganisms, including Bacillus species are used to help control plant pathogens, thereby reducing reliance on synthetic pesticides in agriculture. Bacillus velezensis strain 1B-23 has been shown to reduce symptoms of bacterial disease caused by Clavibacter michiganensis subsp. michiganensis in greenhouse-grown tomatoes, with in vitro studies implicating the lipopeptide surfactin as a key antimicrobial. While surfactin is known to be effective against many bacterial pathogens, it is inhibitory to a smaller proportion of fungi which nonetheless cause the majority of crop diseases. In addition, knowledge of optimal conditions for surfactin production in B. velezensis is lacking. RESULTS: Here, B. velezensis 1B-23 was shown to inhibit in vitro growth of 10 fungal strains including Candida albicans, Cochliobolus carbonum, Cryptococcus neoformans, Cylindrocarpon destructans Fusarium oxysporum, Fusarium solani, Monilinia fructicola, and Rhizoctonia solani, as well as two strains of C. michiganensis michiganensis. Three of the fungal strains (C. carbonum, C. neoformans, and M. fructicola) and the bacterial strains were also inhibited by purified surfactin (surfactin C, or [Leu7] surfactin C15) from B. velezensis 1B-23. Optimal surfactin production occurred in vitro at a relatively low temperature (16 °C) and a slightly acidic pH of 6.0. In addition to surfactin, B. velenzensis also produced macrolactins, cyclic dipeptides and minor amounts of iturins which could be responsible for the bioactivity against fungal strains which were not inhibited by purified surfactin C. CONCLUSIONS: Our study indicates that B. velezensis 1B-23 has potential as a biocontrol agent against both bacterial and fungal pathogens, and may be particularly useful in slightly acidic soils of cooler climates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it