Genetic variability of Canadian elite cultivars of summer turnip rape (<i>Brassica rapa</i> L.) revealed by simple sequence repeat markers
Bibliographic record
Abstract
Canadian public oilseed breeding programs have played a leading role in the development of canola-quality Brassica rapa oilseed cultivars, but the genetic variability of the cultivars developed over the past 60 yr is poorly understood. Simple sequence repeat (SSR) markers were applied to assess the genetic variability of 294 plants representing one landrace introduced from Poland ca. 1940 and nine Canadian elite B. rapa cultivars released by Agriculture and Agri-Food Canada since 1964. Application of 18 SSR primer pairs detected 27 likely loci on five or more linkage groups and 123 polymorphic alleles. The allelic frequencies ranged from 0.003 to 0.997 and averaged 0.262. The estimates of mean heterozygosity for these cultivars ranged from 0.126 to 0.197 and averaged 0.165. Significant decreases of SSR alleles and average dissimilarities were observed over the 60 yr of breeding effort. The proportion of total SSR variation residing among the cultivars was 10.4%; between high vs. low erucic acid cultivars 5% and between high- vs. low-glucosinate cultivars 5%. Pairwise genetic differentiation ranged from 0.025 to 0.184 and averaged 0.104. Genetic clustering of these cultivars revealed AC Sunbeam to be a genetically unique cultivar, and two distinct groups of the other nine cultivars were separated by high- vs. low-glucosinate content. Several distinct genotypes, largely derived from the landrace Polish, were identified. These findings are useful for broadening the genetic base of elite B. rapa germplasm, selecting genetically diverse genotypes for synthetic and hybrid combinations, and conserving this germplasm.Key words: Simple sequence repeat, turnip rape (summer), Brassica rapa, 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 | 0.000 | 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".