Antagonistic potential of forestry compost bacteria on <i>Sclerotinia sclerotiorum</i> (Lib.) de Bary, causal agent of carrot white mould
Bibliographic record
Abstract
Composts are known to contain beneficial bacteria, which may be antagonistic to plant pathogens. This work evaluated whether carrot white mould, causal agent Sclerotinia sclerotiorum, can be reduced using antagonistic bacteria isolated from forestry compost. In vitro and in vivo experiments demonstrated that bacteria from the genera Pseudomonas and Bacillus can inhibit mycelial growth and reduce white mould. Bacillus subtilis strains F9–2 and F9–12 and Pseudomonas arsenicoxydans strain F9–7 showed the highest inhibitory properties. Three cyclic dipeptides (diketopiperazines) were characterized from the antifungal culture filtrates of P. arsenicoxydans F9–7. When assayed against S. sclerotiorum, the diketopiperazines showed the following inhibitory activity, in increasing order: cyclo-(l-Pro-l-Val), cyclo-(l-Pro-l-Phe) and cyclo-(l-Pro-l-Leu). The combination of these diketopiperazines indicated additive and, occasionally, synergistic antifungal effects. These results indicated a potential for some bacteria to inhibit the growth of S. sclerotiorum and reduce its associated disease on carrots postharvest.
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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".