Studies on Pollen Viability and Germinability in Accessions of Stevia rebaudiana Bertoni
Bibliographic record
Abstract
Stevia rebaudiana produces sweet steviol glycosides extractable from the leaves. With zero calorie contents, it represented inevitable health diet for diabetic patients. Poor seed germination (10%) posed obstacles towards large scale establishment. Pollens play fundamental role in fertilization and seed sets. Studying pollen in vitro germination and growth of pollen tube are essential for explaining lack of fertility in spermatophytes. Limited studies exist on the pollen profile of this crop. Pollen viability and germinability in Stevia accessions MS007, MS012 and SBK were studied. 3000 pollen grains per accession were examined for viability. Evaluated parameter includes pollen staining ability in Cotton blue in lacto phenol. Boric acid concentrations (0.025 g, 0.05 g and 0.1 g) prepared with 20 g of sucrose in 100 ml distilled water were formulated into pollen germination medium (GM), 300 pollens per accession were scored for germinability. Analysis of variance revealed no significant difference with pollen viability at p<.424 among all the accessions; while though gernminabilty showed no significant difference at p<.478 and p<.246 for MS007 and MS012 respectively, the SBK differed significantly, with 0.1% treatment, at p<.000. The pollens were viable and possess germination ability. Optimum germination medium comprised 0.025g Boric acid. Poor seed germination in Stevia is unconnected with its pollen profile.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".