Evaluation of RAPD markers as a marker-assisted selection tool for variety type and erucic acid content in rapeseed
Bibliographic record
Abstract
Random amplification of polymorphic DNA (RAPD) analysis was performed on twelve rapeseed genotypes from Institute of Field and Vegetable Crops, Novi Sad, Serbia, genepool in order to identify markers that could be used in marker assisted selection (MAS) for different growing type and selection of the varieties with low or zero level of erucic acid. Out of fifteen RAPD markers, three were monomorphic, whereas twelve had polymorphic profiles. Three primers amplified specific fragments in spring varieties. UBC 25 and UBC 191 amplified the fragments of 450 and 750 bp, respectively, in all tested spring varieties, except in JR-NS-36. Primer UBC 72 generated a fragment of 700 bp that was present in all spring varieties. These fragments were not present in any of winter varieties. None of the tested RAPD primers amplified fragment(s) uniquely present either in varieties with or without (0%) erucic acid or with different erucic acid content. Cluster analysis showed a concordance between the position of varieties in the cluster and their pedigree information, but also enabled separation of spring and winter varieties. Contingency analysis confirmed that fragment UBC 72_700 is specific for spring varieties, while for erucic acid content, only moderate association was found with UBC 137_750.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".