Plant growth regulators for enhancing Alberta native grass and forb seed germination
Bibliographic record
Abstract
A germination trial was conducted to screen effects of plant growth regulators (PGRs) on 9 Alberta native grass and forb species with the aim of identifying PGRs with the capacity to improve seed germination and early plant development in disturbed and reconstructed soil conditions. Seeds were treated with 500 mg/L of various gibberellins (GA 3_ 40 [40% GA 3 ], GA 3_ 90 [90% GA 3 ], and GA 4/7 ), 5 mg/L cytokinin (kinetin), and 0.1 mg/L brassinosteroids (brassinolide). Experiments were conducted in a growth chamber following a 24 h soaking period. PGR seed treatment did not significantly increase percent (%) germination for the majority of species, but rather assisted in breaking seed dormancy and enhancing early radical emergence. Early germination at day 7 was measured for Fragaria virginiana (130–150% increase over the control for GA 3_ 40, GA 3_ 90, GA 4/7 , and brassinolide), Koeleria macrantha (36% increase for GA 3 40), Poa palustris (98–123% increase for all PGRs), Agrostis scabra (42–56% increase for all PGRs) and Festuca hallii (85–93% increase for kinetin and brassinolide). Gibberellin treatments were significantly more effective in improving shoot growth; kinetin and brassinolide were significantly more effective in enhancing root development for the majority of tested plant species. PGRs having the greatest overall impact on seed germination and plant development, as measured by vigor index were brassinolide and GA 4/7 . Tested PGRs have the potential to benefit native grass and forb restoration and revegetation efforts, improving the efficacy of planting prescriptions, with the aim of increasing early ground cover, stabilizing soils, enhancing biodiversity, and reducing the time to reclamation certification.
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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) | 0.001 | 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".