Plant hormone-assisted early family selection in Pinus densiflora via a retrospective approach
Bibliographic record
Abstract
In an even-aged pine forest trees can vary considerably in stem size. We examined the basis for this anomaly using a retrospective approach. Twelve open-pollinated families of Pinus densiflora Sieb. et Zucc. were deliberately chosen for their variation in stem volumes at age 32 years. Seedlings obtained from these families were grown to age 6 months under optimal nursery conditions. Endogenous levels of growth hormones (auxin [IAA] and gibberellins [GAs]) and expression of the GA biosynthesis gene, PdGA20ox1, all assessed at age 3 months, were significantly correlated, across family, with seedling stem and/or shoot dry biomass at age 6 months. Retrospective comparisons of seedling growth, seedling stem tissue GA(20) and seedling stem expression levels of PdGA20ox1 were then made, across family, with tree stem growth at age 32 years. Age 6 months length and shoot dry biomass at age 6 months showed positive and significant Pearson's correlations with age 32 years tree stem diameters and a tree stem volume index, as did seedling stem tissue GA(20). Even seedling stem PdGA20ox1 expression levels were positively and near significantly (P = 0.088) correlated with age 32 years tree stem diameters. Auxin and GAs control nursery growth of seedlings at the family level, and this control also extends, for GAs at least, to field growth of older trees. We propose that family differences in PdGA20ox1 gene expression, and thus endogenous GA levels, may explain much of the natural variation seen for tree stem size in even-aged pine forests. If our hypothesis is correct, then the heritable components of variation in tree stem growth capacity should be predictable by hormonal and gene expression profiling. Such profiling, combined with the measurement of seedling phenotypic growth characters, could have the potential to accelerate the early selection of those conifer families that possess traits for inherently rapid stem wood growth.
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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".