Genetic Diversity for Pink Snow Mold Resistance in Greens‐Type Annual Bluegrass
Bibliographic record
Abstract
Unseeded annual bluegrass (Poa annua L.) is an important component of golf greens in many regions of Canada and the United States. Although this turfgrass species has desirable playing attributes, it suffers from susceptibility to environmental and biological stresses including subfreezing temperatures and snow molds. In this study, we compared 29 genotypes collected from golf greens located in Québec and Ontario for their resistance to pink snow mold (SM). Plants were inoculated with Microdochium nivale [(Fries) Samuels & Hallett], causal agent of SM, and incubated under controlled conditions. High levels of variation in SM resistance were detected within the collection and between genotypes. Analysis of the relationship between climatic parameters at the sites of origin and SM susceptibility revealed that level of resistance was positively correlated to the duration of snow cover. Genetic diversity within the Poa collection was estimated using the sequence related amplified polymorphism (SRAP) technique. The UPGMA (unweighted‐pair group method arithmetic average) dendrogram yielded two main clusters that differed markedly in their proportion of SM‐resistant genotypes. Our results show that SM disease is a major selection pressure for the generation of genetic diversity among annual bluegrass biotypes that evolved on golf greens in northern climates. SRAP polymorphisms between bulked genotypes with contrasting resistance to SM were identified and could be used as markers for SM resistance in annual bluegrass.
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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 | 0.001 | 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".