Early rooting and flooding tolerance in cuttings from a <i>Populus deltoides</i> full-sib family under greenhouse conditions
Bibliographic record
Abstract
Eastern cottonwood (Populus deltoides Bartr. ex Marsh.) is an important forest tree, with elite genotypes propagated mainly as unrooted dormant cuttings. Several areas where P. deltoides is planted periodically experience flooding episodes. The aims of this work were to analyze the early rooting capability and flooding tolerance of a P. deltoides full-sib family, and to identify growth, wood, and leaf traits that correlate with flooding tolerance. We analyzed the early rooting capability of the parental genotypes and 30 clones from the F1 generation under greenhouse conditions. The rooting percentage of the cuttings ranged from 50% to 100%. There was a positive genetic correlation between shoot weight and root traits (number, biomass, and total length). In a separate experiment, 2-month-old plants growing in pots from the same genotypes were subjected to two treatments: watering (control) and flooding for 35 days. Most genotypes showed an intermediate flooding tolerance with respect to the parental clones. Height, diameter, growth rate, biomass, plant leaf area, leaf number, and leaf increase rate had a positive phenotypic correlation with flooding tolerance, while wood density did not. Height and diameter are traits recommended for selection because they correlate with flooding tolerance, are easy to measure, and have moderate to high narrow sense heritability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".