Heritability and Correlations for Biomass Production and Allocation in White Spruce Seedlings
Bibliographic record
Abstract
Abstract Tree growth is a multidimensional trait and families vary for components of growth such as height, diameter, foliage and roots. Therefore, variation in tree growth is better studied by analysing biomass production and allocation than simple traits. In addition, biomass is better linked to products such as pulp and wood energy than simple traits. We analysed biomass of 3-year old open-pollinated greenhouse seedlings of white spruce to determine (1) heritability for biomass production and allocation to shoot and root components, (2) correlations between biomass traits, and biomass traits with primary traits, and (3) correlation between biomass production in the greenhouse and height growth for the same families in the field. The study had a randomised complete block design with single-tree plots, 30 blocks and 58 open-pollinated families. Individual-tree heritability (h i 2 ) and family mean heritability (h f 2 ) ranged from 0.200 to 0.333 and 0.374 to 0.516 for green weight, respectively. Likewise, h i 2 and h i 2 ranged from 0.186 to 0.359 and 0.352 to 0.536 for dry weight, respectively. Genetic correlation (r a ) between green and dry weight ranged from 0.943 to 1.015, while r a between shoot and root dry weight ranged from 0.947 to 0.955. In contrast, r a between biomass traits and field height ranged from -0.403 to -0.124. Thus, we conclude (1) variation in biomass production and allocation exhibited low genetic basis, (2) testing and selection for green or dry weight should lead to similar genotypes, (3) biomass allocation may not be easily altered by selection and breeding, and (4) indirect early selection based on seedling biomass
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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 | 0.000 | 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".