Inclusion of plant growth regulators into priming solution improves low-temperature germination and emergence of watermelon seeds
Bibliographic record
Abstract
The effects of incorporating plant growth regulators into the priming solution on low temperature germination and emergence performance of watermelon [Citrullus lanatus (Thunb.) Matsum. & Nakai. cv. Crimson Sweet] seeds were investigated. Seeds were primed in 2.5% (0.25 M) KNO3 solution for 6 d at 25°C in darkness containing one of the following: 1, 3 or 5 µM methyl jasmonate (MeJA), or 1, 3 or 5 mM spermine. Following priming, seeds were subjected to germination and emergence tests at 15°C. Priming watermelon seeds in the presence or absence of plant growth regulators significantly improved germination percentage and rate at 15°C compared to untreated seeds, which failed to germinate. Seeds primed in KNO3 solution containing 1 or 3 µM of MeJA had significantly higher germination percentages, 96 and 85%, respectively, compared to seeds primed in KNO3 only (69%). Germination rate and synchrony were improved by 1 and 3 µM of MeJA added to the priming solution. Emergence was enhanced by priming seeds in the presence of 1 µM (75%) and 3 µM (63%) MeJA compared to seeds primed in KNO3 solution, (35%) while non-primed seeds were unable to emerge at 15°C. Inclusion of spermine at all three concentrations into the priming solution did not significantly improve germination and emergence characteristics of watermelon seeds compared to seeds that were primed in KNO3 solution only. Therefore, priming watermelon seeds in 1 or 3 µM of MeJA incorporated into the KNO3 solution can be used as an effective method to improve low temperature performance of watermelon seeds. Key words: Watermelon, methyl jasmonate, polyamines, germination, emergence.
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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".