Inter Simple Sequence Repeat (ISSR) Markers and Pedigree Information to Assess Genetic Diversity and Relatedness Within Raspberry Genotypes
Bibliographic record
Abstract
Genetic diversity and relatedness among nine North American red raspberry (Rubus idaeus L.) cultivars and four Canadian breeding lines were studied using inter simple sequence repeat (ISSR) markers and pedigree analysis. Eighteen primers generated 306 polymorphic ISSR-PCR bands. Cluster analysis by the unweighted pair-group method with arithmetic averages (UPGMA) revealed a substantial degree of genetic diversity among the 13 genotypes, similarity values ranged from 24% to 49% that were in agreement with the principal coordinate (PCO) analysis. Geographical distribution for the place of breeding program explained only 1.0% of total variation as revealed by analysis of molecular variance (AMOVA). The UPGMA clustering for coancestry identified 3% to 25% similarity among the nine cultivars. The correlation coefficient between the genetic similarity values calculated from the Jaccard-based ISSR data and pairwise coefficients of coancestry of nine cultivars was positive but insignificant. The ISSR markers detected a sufficient degree of polymorphism to differentiate among raspberry genotypes, making this technology valuable for cultivar identification and for the more efficient choice of parents in the current raspberry 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".