Marker‐trait association analysis for postharvest needle retention/abscission in balsam fir (<i>Abies balsamea</i>)
Bibliographic record
Abstract
Abstract Balsam fir the principal tree species of the Christmas tree industry, is a major export commodity of Atlantic Canada region. However, postharvest needle abscission poses a main concern leading to low consumer satisfaction and a shift in preference towards artificial trees. The search for diverse balsam fir lines with high needle retention is very crucial for quality improvement programmes. In this regard, a panel of 75 balsam fir genotypes exhibiting diversity for needle retention traits were randomly selected from a set of 220 genotypes evaluated for needle retention characteristics for two consecutive years (2012 and 2013) and genotyped with 41 bi‐allelic single nucleotide polymorphism (SNP)/insertion/deletion markers. The cluster analysis and population structure identified four and seven subpopulations. We observed an SNP marker with significant association (p < 0.05) with the needle retention/abscission trait by using general linear model and mixed linear model approaches. The present study lays the foundation for analysing the genetic mechanisms underlying needle retention/abscission, as well as the use of molecular markers to target specific traits in balsam fir.
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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".