Propagation of goldenrod (Solidago canadensis L.) from leaf and nodal explants
Bibliographic record
Abstract
Goldenrod (Solidago canadensis L.) is an invasive plant species in many countries except North America but a cut-flower species worldwide. There is a need to generate and propagate goldenrod clones efficiently for research and commercial purposes. A callus induction and plantlet regeneration system was developed by studying the influence of explant type and different concentrations of plant growth regulators. The highest callus production from leaf segments was obtained on Murashige and Skoog’s medium (MS medium) supplemented with 1.0 mg/L naphthalene acetic acid (NAA) and 1.0 mg/L 6-benzylaminopurine (BA). Adventitious shoots could be regenerated directly from leaf explants without an intermediate callus phase with the highest shoot induction percentage of 87.2%. The largest number of adventitious shoots per leaf explant (3.2) was obtained on MS medium supplemented with 0.4 mg/L NAA and 2.0 mg/L BA. MS medium supplemented with 0.1 mg/L NAA and 1.0 mg/L BA was the best medium for axillary shoot regeneration from nodal segments. The highest root number and longest roots occurred on half-strength MS without the addition of any growth regulator. Rooted plantlets were then transferred to a soil-based growth medium, placed in a greenhouse, and acclimatized with 100% success. All surviving plants grew normally without showing any morphological variation when compared to those grow from seed. This regeneration protocol may be used to produce certain biotypes of goldenrod suitable for genetic transformation rapid propagation of goldenrod for commercial purposes or for screening fungi and toxins as potential biocontrol agents against this weed.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".