Quantitative trait locus analysis of seed germination, seedling vigour and seedling‐regulated hormones in <i>Brassica napus</i>
Bibliographic record
Abstract
Abstract Good germination and seedling vigour are major breeding targets in winter oilseed rape (Brassica napus), because seedling vigour and prewinter crop establishment are closely associated with postwinter growth and yield. Here, we identified quantitative trait loci (QTL) related to germination, seedling vigour and seedling‐regulated hormones in a doubled haploid (DH) mapping population from a cross between winter oilseed rape parents with high vigour (Express 617) and low vigour (1012‐98). By phenotyping in a climate‐controlled glasshouse, we identified a total of 13 QTL on nine chromosomes for germination and seedling‐related traits at 7 and 14 days after sowing (DAS), explaining up to 11.2% of the phenotypic variation for seedling vigour. Forty‐seven metabolic QTL on 15 chromosomes were identified for auxin, abscisic acid (ABA) and dihydrophaseic acid (DPA) at 5 and 12 DAS, explaining up to 49.4% of phenotypic variation in seedling hormone composition. Multitrait QTL hot spots contribute to our understanding of the genetics and metabolomics of germination and seeding vigour in B. napus, and represent potential targets to breed high‐vigour 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".