Genetic resistance to western gall rust in jack pine and its relationship with tree height growth
Bibliographic record
Abstract
Developing resistance to western gall rust (WGR) is important for maintaining healthy and productive jack pine plantations. In this study, we estimated genetic parameters of resistance to WGR and its relationship with tree height growth, based on data collected from three second-generation full-sib progeny testing series of jack pine planted in New Brunswick, Canada. Results indicated that (i) resistance to WGR in jack pine was controlled by both additive and dominance gene effects, with the latter playing a greater role; (ii) narrow-sense heritability estimates for resistance to WGR were low (mean = 0.05; series range = 0.00∼0.09), and broad-sense heritability estimates were moderate on an individual-tree basis (mean = 0.53) and considerably higher on the full-sib family mean basis (mean = 0.87); (iii) additive genetic correlation between tree height growth and WGR incidence was low (≤0.06) in two series and only slightly higher and favorable (–0.19) in one series, suggesting that selection on growth traits would not negatively affect WGR resistance; and (iv) mid-parental additive genetic and dominance effects on WGR were empirically correlated (>0.65), indicating that incorporating breeding for WGR resistance into current jack pine tree improvement programs with a seed orchard approach could partly capture the benefit from dominance effects. Although genetic gains in WGR resistance could be realized through various breeding and deployment schemes, it appeared that rapid improvement could be achieved through backward selection on full-sib family means.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".