Pre-Plant Soaking of Corms in Growth Regulators Influences the Multiple Sprouting, Floral and Corm Associated Traits in Gladiolus grandiflorus L.
Bibliographic record
Abstract
Gladiolus is an ornamental bulbous plant and is commercially propagated in the world through its corms. Usually, a single bud is sprouted from a mother corm but sprouting of multiple buds favors an increase in production of propagules. Thus, present research work was carried out to enhance the sprouting of multiple buds and evaluate its effects on other growth parameters through pre-plant soaking of corms in solution of plant growth regulators. The corms were soaked in solutions of gibberellic acid (GA3), benzyladenine (BA) or ethrel at 0, 50, 100 or 150 ppm concentrations for 24 hrs before planting in the field. Gibberellic acid at 100ppm concentration increased plant height to 105 cm compared to 97.60 cm in control plants, flowering percentage (84.67%), spike length (40.03 cm) and also boosted the corm weight (68.30 g). Soaking of corms in 150 ppm benzyladenine solution enhanced the number of sprouting per corm (2.14) and reduced the plant height (87.00 cm) while 50 ppm concentration of ethrel increased the spike length (42.14 cm). In conclusion, soaking of corms in benzyladenine favored the modifications in various traits of interest including sprouting of multiple buds and an increase in the production of corms while gibberellic acid improved the floral characteristics of gladiolus spikes.
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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 | 0.001 |
| 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".