Effect of preplant seed conditioning treatment on the germination of switchgrass (Panicum virgatum L.).
Bibliographic record
Abstract
Switchgrass (Panicum virgatum. L.) is being developed and evaluated as summer forage and for biomass production in eastern Canada. Uneven germination and slow seedling growth in spring are some of the factors limiting its cultivation. A study was conducted to reduce seed dormancy and to improve germination at suboptimal temperatures in switchgrass cultivars Cave-in-Rock (CIR), Dakota (DK) and New Jersey 50 (NJ). Seeds of these cultivars were conditioned either with 0.2% potassium nitrate (KNO 3 ) or 1mM gibberellic acid or osmo-conditioned with polyethylene glycol 8000 (PEG) solution with or without 0.2% KNO 3 or 1 mM gibberellic acid (GA 3 ); or matriconditioned with Micro-Cel E (MC) with either water, 0.2% KNO 3 or 1 mM GA 3 . The seeds were conditioned at 8 or 16°C for 4 days and then germinated at 8, 16 or 24°C. Conditioning treatment and temperature influenced germination. For CIR seeds germinated at 8°C, conditioning with PEG at 8°C increased germination from 0 (control) to 22%. All the conditioning treatments germinated earlier and the proportion of seeds that eventually germinated was higher than for the unconditioned control. In the cultivar NJ conditioning at 16°C with water or 1 mM GA 3 increased germination to 12 and 17% respectively (0 for the control) when seeds were germinated at 8°C. When germinated at 16°C treatments containing 1 mM GA 3 germinated earlier. Osmoconditioning in PEG with 1 mM GA 3 had the highest final germination at 56% (37% for control). Cultivar DK did not significantly respond to the various conditioning treatments. Overall, both osmoconditioning and matriconditioning hastened germination and total germination in switchgrass cultivars CIR and NJ.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".