Efficient Induction of Papaya Embryogenic Callus and Plant Regeneration
Bibliographic record
Abstract
Papaya ( Carica papaya L.) has high medicinal and production value, and it is of great significance to carry out efficient induction and plant regeneration of embryogenic callus of papaya for its industrial development. In this study, Zhongbai, the main papaya cultivar from Hainan was used as explants to explore the effects of different hormones and their additive combinations on embryogenic callus induction and plant regeneration. The results showed that the most suitable medium for papaya callus induction was K5: 1/2 MS+5 mg/L 2, 4-D+0.5 mg/L KT+3% sucrose+3.6 g/L phypagel. The most suitable medium for papaya embryogenic callus induction was M13: 1/2 MS+5 mg/L 2,4-D+0.6 mg/ L-proline+3% sucrose+3.6 g/L phypagel. And the most suitable medium for papaya bud differentiation was Ci: 1/2 MS+0.2 mg/L 6-BA, 0.2 mg/L NAA+3% sucrose+3.6 g/L phypagel. The best method for rooting of papaya was treatment with 100 mg/L rooting powder and soil plantation. This ‘two-steps’ embryogenic callus induction system we created can significantly shorten the growth cycle of embryogenic callus. Furthermore, the system has a certain broad spectrum in different varieties of papaya, this study provides a solid foundation for further improving the efficiency of genetic transformation of papaya.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".