AFLP-based molecular characterization of <i>Brassica rapa</i> and diversity in Canadian spring turnip rape cultivars
Bibliographic record
Abstract
Information on genetic diversity and genetic relationships among taxa of Brassica rapa (n = 10, AA genome) is currently limited. Grown for oil, vegetable and fodder use in Europe and Asia, previous studies have indicated western and eastern groups corresponding to independent centres of origin. This study evaluated patterns and levels of genetic diversity in 93 accessions [includes 25 Agriculture and Agri-Food Canada (AAFC) breeding lines (BL)] of B. rapa based on 307 amplified fragment length polymorphisms (AFLP), testing subspecific separateness and the affiliation of four previously unassigned AA genome species (B. perviridis, B. purpuraria, B. ruvo and B. septiceps). AFLP data revealed three main clusters (I, II, III) corresponding to European (I), Indian (III), and a mixed Asian/European/Indian (II) purported origins of the taxa, with several subclusters observed in I and II. Mean AFLP polymorphism levels for Asian, European, Indian and AAFC-BL accessions were 79, 74, 66 and 62%, respectively. Few of the subspecies formed unique clusters and some, particularly subspecies chinensis and pekinensis, were assigned to several clusters. AFLP-based genetic distance information can be used by breeders to select diverse genotypes for cultivar development and fingerprinting of genotypes/cultivars. For example, a single AFLP primer pair was sufficient to uniquely identify all breeding lines in the AAFC B. rapa breeding programme.
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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) | 0.000 | 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".