Patterns of Heterosis in Three Distinct Inbred Populations of Spring <i>Brassica napus</i> Canola
Bibliographic record
Abstract
Allelic diversity of the allied species of Brassica napus L. as well as of the winter form of this species has been demonstrated to be related with increasing productivity of hybrid spring B. napus cultivars. To compare potential value of the different gene pools of Brassica species three spring B. napus inbred populations were developed by use of a B. oleracea L. line, a spring B. napus breeding line, and a winter B. napus cultivar crossed to a spring B. napus ‘Hi‐Q’; and test hybrids of these inbred lines were produced by crossing with Hi‐Q as the common tester. Mid‐parent heterosis (MPH) showed a negative correlation with seed yield of the inbred lines in all three populations; however, a positive correlation existed between seed yield of the inbred lines and heterosis over Hi‐Q (HiQH) (or, inbred vs. hybrid yield). On average, the level of MPH in hybrid of the inbred lines derived from B. napus × B. oleracea cross was twice greater than the level of heterosis found for the inbred lines derived from spring × spring or winter × spring B. napus crosses. The inbred population derived from winter × spring cross gave highest seed yield, and this population also gave highest HiQH. The results suggested that B. oleracea and winter canola could be used in spring B. napus canola breeding for accumulating additive and non‐additive effect genes for increased seed yield in hybrid cultivars.
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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 | 0.000 |
| 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".