Broadening genetic diversity in Brassica napus canola: Development of canola-quality spring B. napus from B. napus×B. oleracea var. alboglabra interspecific crosses
Bibliographic record
Abstract
Rahman, H., Bennett, R. A. and Séguin-Swartz, G. 2015. Broadening genetic diversity in Brassica napus canola: Development of canola-quality spring B. napus from B. napus × B. oleracea var. alboglabra interspecific crosses. Can. J. Plant Sci. 95: 29-41. The narrow genetic base in spring Brassica napus (AACC) canola is a limitation for continued improvement of this crop. This research focused on broadening of genetic diversity in spring canola by using B. oleracea (CC). Seeds of B. oleracea contain high levels of erucic acid and glucosinolates, which are undesired in canola. Therefore, inheritance of these traits and the prospect of developing spring canola with allelic diversity introgressed from B. oleracea were investigated in B. napus×B. oleracea interspecific progenies. Zero-erucic plants in F2 generation occurred at a lower frequency than expected based on segregation involving only the C-genome erucic acid alleles. Selection in F2 to F3 focused on zero erucic acid, while focus in later generation was for low glucosinolate and B. napus plants. In the F6, 31% zero-erucic families had low glucosinolate content. Flow cytometry analysis of the F8 families showed no significant difference from the B. napus parent. Genetic diversity analysis by using simple sequence repeat markers from the C-genome chromosomes showed that the F8 families received up to 54% alleles from B. oleracea. The results demonstrate the feasibility of enriching genetic diversity in B. napus canola by using B. oleracea.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".