Wood Quality and Growth Characterization across Intra- and Inter-Specific Hybrid Aspen Clones
Bibliographic record
Abstract
Trembling aspen (Populus tremuloides Michx.) is one of the most abundant poplar species in North America; it is native, displays substantial breadth in distribution inhabiting several geographical and climatic ecoregions, is notable for its rapid growth, and is ecologically and economically important. As the demand for raw material continues to increase rapidly, there is a pressing need to improve both tree quality and growth rates via breeding efforts. Hybridization is considered one of the most promising options to simultaneously accelerate these tree characteristics, as it takes advantage of heterosis. Two aspen species showing particular promise for hybridization with trembling aspen are European aspen (P. tremula) and Chinese aspen (P. davidiana) because their native climates are similar to that of P. tremuloides and are also very easy to hybridize. In 2003, aspen clones were planted in Athabasca, Alberta from the following species crosses: open pollinated (OP) P. tremuloides (NN), OP P. davidiana (CC), P. tremula × P. tremula (EE), P. tremula × P. tremuloides (EN), and P. tremuloides × P. davidiana (CN). In November 2010, growth measurements and core samples were taken from seven-year field grown clones. Comparisons of the mean growth and cell wall traits were made between crosses using generalized linear model least squares means tests for stem volume, fiber length, fiber width, coarseness, wood density, microfibril angle, total cell wall carbohydrate and lignin content, and lignin composition. The results clearly indicated that the inter-specific crosses offer a means to breed for more desirable wood characteristics than the intra-specific Populus spp. crosses.
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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".