In Vitro Tetraploidization Towards Enhancement Of Charantin Biosynthesis In Momordica Charantia (L.)
Bibliographic record
Abstract
A practical and reliable method for in vitro tetraploidization of Bitter Gourd [Momordica charantia (L.)] has been established to enhance the production of charantin. Shoot tip from in vitro-grown culture (2n = 22) were exposed to the anti-mitotic chemical, i.e., colchicine, at various concentrations (0, 0.01, 0.05, 0.1, 0.2 and 0.3% along with 2% DMSO) for 12, 24, 36, and 48 h. The treated explants were then incubated and proliferated on Murashige and Skoog (MS) medium fortified with 1.5 mg L-1 benzyladenine and 0.5 mg L-1 naphthalene acetic acid, followed by root induction in 1.0 mg L-1 indole-3 acetic acid enriched 1/2MS medium. Treatment of shoot tips with 0.1% colchicine for 24 h supported the highest tetraploid induction efficiency (33.56 ±0.22%). Morphological, stomatal, and cytological characteristics along with the secondary metabolite content of the in vitro tetraploids were compared to that of diploids. The recovered tetraploid plants possessed superior plant height, stem diameter, leaf size, and increased length and width of stomata but decreased stomatal frequency. The tetraploid plants demonstrated twice the chromosome number (2n = 4x = 44) in respect to diploids as confirmed through cytology, spectrophotometry and flow cytometry. Highperformance liquid chromatography showed 1.09 times enhancement of charantin content in tetraploid plants than that of diploid plants, signifying the prospective of this technique for the trade value improvement.
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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) | 0.001 | 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".