Genetic diversity of<i>Sinapis alba</i>germplasm as revealed by AFLP markers
Why this work is in the frame
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Bibliographic record
Abstract
Sinapis alba L. is a major specialty crop grown as a condiment in western Canada, but little is known about its genetic diversity. The objective of this study was to assess the level and pattern of genetic diversity in a collection of 127 S. alba accessions held at Plant Gene Resources of Canada using amplified fragment length polymorphism (AFLP) markers. Five AFLP primer pairs were applied, and 134 polymorphic bands were scored for each accession. These scored bands had frequencies of occurrence ranging from 0.02 to 0.99 with an average of 0.69. More AFLP variation was found within single (79.1%) than between (20.9%) S. alba accessions. A small degree of AFLP difference (1.7%) was observed among the accessions of various regions, while relatively large variation (9.2%) existed among the accessions of various countries. A large AFLP difference (15.6%) also existed between the yellow- and brown-seeded accessions, but only 6.2% difference was observed between the cultivar and landrace accessions. Two distinct groups of S. alba germplasm were identified on the basis of the seed colour (yellow or brown), although a few mixtures also existed. No apparent ‘duplicated’ accessions were observed. The most diverse accessions were from Italy, Spain, France and Greece. Among the most genetically distinct accessions were SA97 from Portugal, SA89 and SA88 from France, SA83 from Russia and SA57 from Italy. These findings are significant not only for managing S. alba germplasm, but also for identifying diverse germplasm that can be used by plant breeders to improve S. alba seed yield and quality parameters.
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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 it