Genetic Relationships among Lowbush Blueberry Genotypes as Determined by Randomly Amplified Polymorphic DNA Analysis
Bibliographic record
Abstract
Twenty-six genotypes of lowbush blueberry ( Vaccinium angustifolium Aiton) representing four geographical zones (Maine, United States; New Brunswick, northern Nova Scotia, and western Nova Scotia, Canada) were selected to obtain DNA fingerprints and to estimate genetic similarity by randomly amplified polymorphic DNA analysis. The genotypes were either native accessions or selections from crosses involving native accessions as parents or grandparents. Thirty 10-base RAPD primers were initially screened; 11 proved to be polymorphic, resulting in 73 consistent RAPD bands. All 26 genotypes could be distinguished by their unique RAPD banding patterns and three unlabeled samples were correctly identified. The RAPD band data set was analyzed with Genstat5 to calculate similarity and distance matrices. Average similarity across all genotypes was 56%. Results from average linkage cluster analysis were used to construct a dendogram which demonstrated six main clusters with an average similarity linkage of 70%. The selection `Fundy' and its parent `Augusta' clustered at 77% similarity. The corresponding principal coordinate analysis supported the clusters and identified two distinct outliers. There was a small association by geographic grouping for five genotypes from Maine. It was concluded that RAPD analysis is a useful tool for genotypic identification and estimates of genetic similarity in lowbush blueberry.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".