Factors Affecting Biological Control of <i>Sclerotinia sclerotiorum</i> by Fungal Antagonists
Bibliographic record
Abstract
Abstract Studies were conducted to determine the effects of soil moisture (9, 16 or 24% w/w) and temperature (5, 15, 20 or 25°C) on the control of sclerotia of Sclerotinia sclerotiorum by five fungal agents in sterile and natural field soil. All five biocontrol agents were effective in reducing the survival of sclerotia of S. sclerotiorum in sterile soil under dry (9% moisture) or wet (24% moisture) conditions at 20°C, but only Coniothyrium minitans was effective in natural soil. Coniothyrium minitans was the most effective in reducing sclerotial viability at the temperature range of 15–25°C. Trichoderma virens was effective against sclerotia of S. sclerotiorum to a lesser extent than C. minitans, and in non‐autoclaved soil, it performed best at 25°C. Although Epicoccum purpurascens, Talaromyces flavus and Trichothecium roseum were effective against sclerotia of S. sclerotiorum in some instances, they were less effective than C. minitans and T. virens. Sclerotia of S. sclerotiorum conditioned for myceliogenic germination were more vulnerable to attack by the biocontrol agents than dormant sclerotia. The implications are discussed with respect to enhancement of biological control of crop diseases caused by S. sclerotiorum in different geographic regions.
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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".