Heritability and phenotypic and genetic correlations of coastal Douglas-fir (<i>Pseudotsuga menziesii</i>) wood quality traits
Bibliographic record
Abstract
Genetic control and relationships among coastal Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco var. menziesii) growth and wood quality traits were assessed by estimating heritability and phenotypic and genetic correlations using 600 trees representing 15 full-sib families sampled from four progeny test sites. Heritability estimates ranged from 0.23 to 0.30 for growth traits, 0.19 for fibre coarseness, from 0.21 to 0.54 for wood density, from 0.16 to 0.97 for cell wall carbohydrates, and 0.79 and 0.91 for lignin content at two sites, Squamish River and Gold River, respectively. Glucose content, indicative of cell wall cellulose composition, and lignin were shown to be under strong genetic control, whereas fibre coarseness was shown to be under weak genetic control. Phenotypic correlations revealed that larger trees generally have longer fibres with higher fibre coarseness, lower density, lower carbohydrate content, a greater proportion of cell wall lignin, and higher microfibril angle. Genetic correlations and correlated response to selection suggest that breeding for height growth would result in a reduction in wood quality, whereas breeding for improved earlywood density in Douglas-fir would result in negligible reductions in volume and appears to be an ideal target for selecting for improved wood quality (density) while maintaining growth in the sample population.
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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 | 0.001 | 0.002 |
| 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".