Antifungal activity of <i>Bacillus velezensis</i> and <i>Pseudomonas azotoformans</i> isolated from compost tea against anthracnose ( <i>Colletotrichum</i> spp.) on strawberry fruit
Bibliographic record
Abstract
Abstract Anthracnose, caused by Colletotrichum spp., is a threat to strawberry production globally. Unlike their chemical counterparts, microbial biofungicides offer a method of postharvest fungal disease control that is safe, sustainable and less affected by pathogen resistance. The present study evaluated the antifungal effects of three bacteria, Bacillus velezensis strains SH1 and SH2 and Pseudomonas azotoformans strain SH3, obtained from sheep manure compost tea. The bacteria or their cell‐free filtrates were tested against Colletotrichum acutatum and Colletotrichum gloeosporioides in bioassays and against strawberry anthracnose. In addition, precipitated or extracted extracellular fractions were tested to determine the effects on membrane permeability of Colletotrichum spp. spores. Confrontation assay results showed all bacteria inhibited mycelial growth, with B . velezensis SH1 and P . azotoformans SH3 being the most effective. All cell‐free filtrates inhibited mycelial growth with B . velezensis SH1 and SH2 resulting in the highest inhibition. The bacteria suppressed anthracnose lesions on strawberry fruit although effective treatments varied by causal mould. B. velezensis SH1 and SH2 significantly permeabilized spore membranes, indicating antibiosis as a possible mode of action. Investigation into antimicrobial compound production found various homologues of the lipopeptides fengycin, iturin and surfactin were produced by B . velezensis SH1 and SH2. Results suggest that lipopeptides produced by B . velezensis strains permeabilize Colletotrichum cell membranes, and that fengycins were the most inhibitory of the lipopeptides against Colletotrichum spp.
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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".