Phytohormones and their metabolites during long shoot development in Douglas-fir following cone induction by gibberellin injection
Bibliographic record
Abstract
Changes in plant hormones and metabolites in long-shoot stems of interior Douglas-fir (Pseudotsuga menziesii var. glauca (Beissn.) Franco) during cone induction by gibberellic acid (GA) treatment were analyzed by high performance liquid chromatography-electrospray ionization tandem mass spectrometry in multiple reaction monitoring mode. A mixture of GA(4) and GA(7), including small amounts of GA(3) and GA(1), was stem-injected into each tree in amounts of 0, 4, 40 or 400 mg. One week after injection, concentrations of GA(4), GA(7) and GA(3) were elevated in all GA-treated samples. The ratio of GA(4) to GA(7) decreased significantly at Week 3. Absolute concentrations of all gibberellins declined sharply at Week 3 after GA application. After 5 weeks, GA(1) and GA(4) were below detection limits in all samples, and GA(7) and GA(3) were found only in the samples from trees treated with 40 or 400 mg of GA. Endogenous indole-3-acetic acid (IAA) concentrations increased following GA injection, and peaked at Week 2 or Week 3 in the trees treated with 40 or 400 mg GA, respectively. Injection of 400 mg of GA brought about a twofold increase in IAA concentration compared with control values. Injection of 40 and 400 mg of GA caused significant increases in stem dry mass in Week 5. Seed orchard data revealed that injection of either 40 or 400 mg GA enhanced female cone formation, whereas male cone formation was enhanced only by 400 mg GA. Slight decreases in concentrations of abscisic acid (ABA) and isopentenyl adenosine were observed after GA application. No significant changes were detected in the concentrations of ABA metabolites except for a slight decrease in the concentration of 7'-hydroxy ABA. The concentration of ABA declined during the growing season and the concentration of ABA glucose ester increased correspondingly.
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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 | 0.000 | 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 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".