Development of ISSR markers for genetic diversity studies in <i>Vaccinium angustifolium</i>
Bibliographic record
Abstract
Understanding of the genetic relationship within wild lowbush blueberry ( Vaccinium angustifolium Ait.) germplasm is important to establish a broad genetic base for safeguarding and for future use of the existing genetic resources. The objective of this study was to assess the genetic variability within 43 wild lowbush blueberry clones, collected from 10 communities of four Canadian provinces, and the cultivar ‘Fundy’ by using inter simple sequence repeat (ISSR) markers, with the hope to establish a reference set of lowbush blueberry germplasm for blueberry conservation, breeding and research. Thirteen primers generated 242 polymorphic ISSR‐PCR bands. A substantial degree of genetic similarity was found among the wild collections. Cluster analysis by the unweighted pair‐group method with arithmetic averages (UPGMA) separated the 41 genotypes into two main clusters, and identified the three remaining clones as outliers. Furthermore, within one main cluster, the genotypes tended to form sub‐clusters that were in agreement with the principal coordinate (PCO) analysis. Geographical distribution contributed to 27% of total variation as revealed by analysis of molecular variance (AMOVA). The ISSR‐PCR method was simple, fast and relatively inexpensive to produce useful DNA fragments and detected a sufficient degree of polymorphism to differentiate among lowbush blueberry clones, making this technology valuable for germplasm management and the more efficient choice of parents in current blueberry breeding program.
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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) | 0.001 | 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".