Effect of foliar disease on the epiphytic yeast communities of creeping bentgrass and tall fescue
Bibliographic record
Abstract
The effect of mechanical wounding or foliar diseases caused by Sclerotinia homoeocarpa or Rhizoctonia solani on the epiphytic yeast communities on creeping bentgrass and tall fescue were determined by leaf washing and dilution plating. Total yeast communities on healthy bentgrass and tall fescue leaves ranged from 7.9 x 103 to 1.4 x 105 CFU.cm-2 and from 2.4 x 103 to 1.6 x 104 CFU.cm-2, respectively. Mechanically wounded leaves (1 of 2 trials) and leaves with disease lesions (11 of 12 trials) supported significantly larger communities of phylloplane yeasts. Total yeast communities on S. homoeocarpa infected or R. solani infected bentgrass leaves were 3.6-10.2 times and 6.2-6.4 times larger, respectively, than the communities on healthy leaves. In general, healthy and diseased bentgrass leaves supported larger yeast communities than healthy or diseased tall fescue leaves. We categorized the majority of yeasts as white-pigmented species, including Cryptococcus laurentii, Cryptococcus flavus, Pseudozyma antarctica, Pseudozyma aphidis, and Pseudozyma parantarctica. The percentage of pink yeasts in the total yeast community ranged from 2.6% to 9.9% on healthy leaves and increased to 32.0%-44.7% on S. homoeocarpa infected leaves. Pink-pigmented yeasts included Rhodotorula glutinis, Rhodotorula mucilaginosa, Sakaguchia dacryoidea, and Sporidiobolus pararoseus. Foliar disease significantly affected community size and composition of epiphytic yeasts on bentgrass and tall fescue.
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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".