Bibliographic record
Abstract
The influence of inoculum and nutrient concentrations on the in vitro antagonism of Botrytis cinerea by phylloplane yeasts was investigated with detached leaf disk and conidial germination assays. Rhodosporidium toruloides Y-1091 significantly reduced lesion development after 96 h on geranium leaf disks when co-inoculated at 1 × 10 6 or 1 × 10 7 yeast cells/mL with B. cinerea conidia at 1 × 10 4 or 1 × 10 5 conidia/mL. No effect on lesion development was observed when yeast and fungus were co-inoculated at a 1:1 ratio. Biocontrol activity of R. toruloides was greatest in 20 mM glucose and 20-fold dilute yeast nitrogen base. Twenty-five phylloplane yeasts exhibited a wide range of biocontrol activity when screened for antagonism of B. cinerea on geranium leaf disks (1 × 10 6 yeast cells/mL, 1 × 10 5 conidia/mL). Lesion development was significantly reduced by yeasts initially identified as poor antagonists when inoculated at higher concentrations (5 × 10 6 or 1 × 10 7 yeast cells/mL) with B. cinerea. Both poor and good antagonists significantly reduced in vitro germination of B. cinerea conidia. The presence of B. cinerea conidia had a greater effect on the growth of two poor antagonists compared with two good antagonists on leaf disks. These data suggest that many phylloplane yeasts will antagonize B. cinerea under conditions of low nutrient availability and with high antagonist to pathogen ratios.Key words: yeast, biological control, competition, nutrients, germination, Rhodosporidium toruloides.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".