Effects of Plant Growth Regulators for Seed Embryos Development of <i>Cremastra appendiculata</i>
Bibliographic record
Abstract
In order to understand the process of embryo development of Rhododendron seed embryo under different plant growth regulators, the seed of Rhododendron was used as the experimental material for the rapid development and maturation of Cremastra appendiculata seeds embryo. Using Cremastra appendiculata seeds as experimental materials, the plant growth regulators naphthaleneacetate (NAA), 6-benzylaminopurine (6-BA), kinetin (KT), zeatin (ZT), beta-indolebutyric acid (IBA), Effects of 2, 4-dichlorophenoxyacetic acid (2, 4-D) on the development of azalea seed embryos. The results showed that the addition of six plant growth regulators to the medium had different effects on the development of azalea seed embryos. 2,4-D inhibited the development of embryo; adding KT and ZT, the seeds began to expand after 40 days, and the development of embryo was slow; NAA, IBA and 6-BA could accelerate the growth of embryo, and NAA had the best effect on promoting the development of embryo when it was added alone, in which NAA and 6-BA were used together and NAA: 6-BA=1 mol/L:1 mol/L, the speed of embryo development was the fastest, and the germination rate of seed reached 88.11% after 40 days. Therefore, it is necessary to fill the blank in the field of embryo development of Rhododendron so as to provide theoretical basis for the construction of rapid propagation system of Cremastra appendiculata seedlings.
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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".