Core Collection of a Representative Germplasm Population in Brassica napus
Bibliographic record
Abstract
【Objective】Investigating the genetic diversity and selecting core collection of rapeseed.【Method】According to previous researches, 500 accessions from Europe, Asia, Canada, Australia and China were divided into four groups based on their qualities, geographic regions and growth habits. A primary core collection of 87 accessions was sampled from each group in same proportion. EST-STS and SSR markers were applied to measure their genetic diversities, eliminate the genetic redundancy and evaluate diversity indices of molecular markers for developing core collection. Phenotypes of individual core gene pool were analyzed and compared. 【Result】 Under the same selection background, two types of marker showed similar polymorphism rate (39%-40%), and polymorphic fragments number. Cluster analysis divided the 87 accessions into two groups (Ⅰ, Ⅱ) at similarity coefficient of 0.65, further two subgroups from each group were generated, respectively. A core collection consisted of 78 accessions was constructed after eliminating genetic redundancy above 0.85 genetic similarity coefficients. 【Conclusion】The results indicated that EST-STS was economic, effective and functional marker with similar efficacy compared with normal SSRs. The genetic diversity and cluster analysis supported the classification of four groups in Brassica napus. 78 accessions retaining the most genetic diversity and structure could be utilized and preserved as core germplasm collection for 500 initial rapeseed resources.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".