Morphology and AFLP markers suggest three <i>Hordeum chilense</i> ecotypes that differ in avoidance to rust fungi
Bibliographic record
Abstract
In Hordeum chilense Roem. & Schult., a high variation in the level of avoidance to infection of barley leaf rust (Puccinia hordei Otth) occurs. Probably resulting from the properties of the stomata, the rust germ tube overgrows stomata, and the infection process fails in an early stage. In the present study we tested the hypothesis that the avoidance character occurs in certain morphologically and molecularly distinct ecotypes of H. chilense. Eighty-eight H. chilense accessions were inoculated with P. hordei to assess the level of avoidance. The accessions were described for 30 morphological characters and three AFLP primer combinations. Cluster analysis using both morphological and AFLP fingerprint data suggested three distinct clusters of accessions. One of the clusters had a particularly high level of avoidance. This putative subspecific taxon was characterized by shorter and wider spikes, more erect culms, a greater number of stomata per square centimetre on the abaxial leaf side, and a shorter uppermost internode until flag leaf. All accessions clustered in this subspecific taxon were collected from humid habitats. We conclude that H. chilense consists of at least three rather well defined, morphologically and genetically distinct subspecific taxa, one of which has a very high level of avoidance to barley leaf rust.Key words: AFLP fingerprinting, diversity, Hordeum chilense, avoidance, rust fungi, Puccinia hordei.
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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) | 0.002 | 0.001 |
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".