Snow mould resistance under controlled conditions and winter survival in the field in populations of perennial ryegrass, meadow fescue, and <i>Festulolium</i> are partly dependent on ploidy level and degree of northern adaptation
Bibliographic record
Abstract
Pink snow mould caused by Microdochium nivale is a serious cereal and grass disease in several temperate regions. In this study, resistance to snow mould was evaluated under controlled conditions in nine promising breeding populations and two cultivars of Festulolium, three cultivars of Festuca pratensis, six cultivars and two breeding populations of Lolium perenne and one cultivar of hybrid ryegrass using non-hardened plants. In addition, winter survival was evaluated in field plots inoculated with M. nivale. Under controlled conditions, tetraploid entries of Festulolium had a significantly better resistance to snow mould than diploid entries in three out of four tests. Diploid and tetraploid entries of L. perenne showed similar levels of resistance under controlled conditions. In the field trial, entries of both L. perenne and Festulolium that had been exposed to natural selection in northern Norway (above 65°N) showed good levels of winter survival. In general, under controlled conditions snow mould resistance of Festulolium entries was associated with ploidy level, whereas under field conditions winter survival of L. perenne entries was associated with their degree of northern adaptation. However, resistance to snow mould in non-hardened plants tested under controlled conditions was not correlated with winter survival in the field.
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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".