Effects of Different Pretreatments and Seed Coat on Dormancy and Germination of Seeds of Senna obtusifolia (L.) H.S. Irwin & Barneby (Fabaceae)
Bibliographic record
Abstract
The seed dormancy of Senna obtusifolia was investigated through various methods, namely pretreatments in concentrated sulfuric acid, 2% potassium nitrate (KNO3), 99% ethanol, 99% methanol, and in hydrogen perioxide; examination of the seed coverings; and the determination of water uptake by the seeds in order to ascertain the most effective technique for breaking dormancy and also determine the dormancy type. The results showed that sulfuric acid treatment recorded the highest germination (100%); followed by 2% hydrogen peroxide treatment (24%) in 15minutes immersion. The methanol and ethanol pretreatments gave 18.33% and 16.5% germinations respectively. Pretreatment in 2% potassium nitrate gave the lowest germination (8.50%), while the intact seeds of S. obtusifiolia (control) gave 0% germination. The anatomy of the seed coat indicated the presence of hard, thickened and specialized cells of cuticle, macrosclereids, osteoscereids, and disintegrated parenchyma layers. The water uptake of intact seeds was low (13.5%) after 24 hr imbibitions. These findings revealed that the seed coat acts as barrier to germination by preventing water absorption, possibly gaseous diffusion in and out of the seed and conferring mechanical resistance to the protrusion of embryo. Pretreatments, such as immersion in H2SO4 will soften the seed coat and permit germination. Seed dormancy in S. obtusifolia can be considered of physical nature and classified as physical dormancy. The results obtained in this study may serve as useful information in the production and improvement of S. obtusifolia seedlings, as knowledge on seed dormancy and germination is a critical factor and requirements to the understanding of the propagation of this plant either in situ or ex-situ, in view of the economic potentials/attributes of this species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".