Amplified fragment length polymorphism analysis of 96 Canadian oat cultivars released between 1886 and 2001
Bibliographic record
Abstract
Canadian oat breeders have developed and released more than 130 cultivars since 1886, but no systematic analyses of the genetic diversity of Canadian oat have been made. Ninety-six Canadian oat cultivars released between 1886 and 2001 were examined for genetic diversity and relationships using amplified fragment length polymorphism (AFLP) markers. Ten AFLP primer pairs were applied and over 442 polymorphic bands were generated for each cultivar. Most of the cultivars were found to be interrelated, although a few genetically distinct cultivars were also identified. The genetic variation observed among these cultivars was low. Only 42.8% of the total scorable bands were polymorphic, of which 59 polymorphic bands were observed frequently (f ≥ 0.90) and 130 bands were detected infrequently (f ≤ 0.01) among the 96 cultivars. The mean proportion of fixed recessive bands for all cultivars was high (60.2%) and ranged from 52.3% in cultivar ‘Erban’ to 65.2% in cultivar ‘Glen’. The genetic variability did not change significantly in the Canadian oat breeding programs; only about 1% of the AFLP variation might have been fixed during the 115 years of oat breeding. These findings demonstrate the narrowness of the Canadian oat gene pool and the urgent need to broaden the gene pool for sustainable oat improvement in Canada. Key words: Amplified fragment length polymorphism (AFLP), oat, Avena sativa, genetic diversity, genetic relationship
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".