Genetic diversity of Canadian elite summer rape (<i>Brassica napus</i> L.) cultivars from the pre- to post-canola quality era
Bibliographic record
Abstract
The development of canola quality Brassica napus oilseed cultivars was a major achievement of Canadian public oilseed breeding programs. Simple sequence repeat (SSR) markers were applied to assess the genetic diversity of 300 plants representing one landrace introduced from Argentina in 1943, seven Canadian elite cultivars developed and released by Agriculture and Agri-Food Canada since 1954, and two European cultivars that were the source of the low erucic acid and low glucosinolate traits that define canola quality. Application of 22 SSR primer pairs from eight linkage groups detected 88 polymorphic alleles from 33 likely loci. The allelic frequencies in 300 samples ranged from 0.003 to 0.993 and averaged 0.388. The estimates of mean heterozygosity for these cultivars ranged from 0.055 to 0.203 and averaged 0.139. The most SSR variation was detected in the cultivars Argentine, Golden and Oro. A trend of decline in SSR variation was observed over the years of breeding effort. The proportion of total SSR variation residing among the cultivars was 51.4%; between high vs. low erucic acid cultivars 15% and between high vs. low glucosinolate cultivars 21.2%. Pairwise genetic differentiations among these cultivars ranged from 0.140 to 0.819 and averaged 0.500. Cluster analysis revealed that the genetic relationships of these cultivars were consistent with their known pedigrees. These findings are useful for broadening the genetic base of improved B. napus gene pools, selecting genetically diverse genotypes for hybrid combinations, and conserving summer rape germplasm.Key words: Simple sequence repeat, summer rape, Brassica napus, genetic diversity, genetic relationship, genetic structure
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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 | 0.001 |
| 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".