Study of the genetic structure of a <i>Brassica napus</i> L. canola population derived from six interspecific crosses of <i>B. napus</i> × <i>B. oleracea</i>
Bibliographic record
Abstract
Broadening the genetic base of the C genome of Brassica napus L. canola is needed for continued improvement of this crop. For this, we developed few hundred canola lines from B. napus × Brassica oleracea L. interspecific crosses involving a B. napus canola line and six B. oleracea accessions belonging to four varieties, viz. vars. alboglabra, botrytis, capitata, and italica, and following two breeding methods [F2 and BC1 (F1 × B. napus) derived lines]. The objective of this study was to understand the genetic structure of this population regarding the alleles introgressed from B. oleracea by using simple sequence repeat markers and to investigate the inheritance of B. oleracea alleles in these reconstituted canola lines. Marker analysis showed that the four B. oleracea varieties were genetically quite distinct. Several canola lines derived from these six crosses tended to group together with their B. oleracea parent demonstrating that the wide diversity of the B. oleracea gene pool can be exploited for broadening the genetic base of the C genome of B. napus canola. Loss of several B. oleracea alleles occurred during the development of these inbred lines. While comparing the two breeding methods for introgression of B. oleracea alleles, significantly greater loss of alleles occurred in the F2-derived population as compared with the BC1-derived population. Thus, the knowledge from this study can be used for efficient introgression of exotic alleles from B. oleracea into B. napus for broadening the genetic base of this crop.
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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 | 0.001 |
| 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".