A Rapid and Efficient Protocol for Clonal Propagation of Phenolic-Rich Lavandula multifida
Bibliographic record
Abstract
Lavandula multifida (fernleaf lavender) grows in confined regions of Portugal. This species is known for its interesting chemical profile, rich in phenolic compounds, and significant antifungal and anti-inflammatory properties, making it an interesting plant for industrial exploitation and justifying alternative propagation methods. Therefore, the present study aims the development of an efficient protocol for large scale propagation of this species, assuring plant uniformity and aiming a sustainable industrial exploitation with preservation of natural resources. In vitro cultures were established on Murashige and Skoog medium (MS) with different concentrations of benzyladenine (BA) and zeatin (ZEA). Best multiplication rates (6.14 shoots per explant) were achieved using MS supplemented with 1.0 mg/L ZEA and rooting occurred spontaneously on the propagation medium avoiding additional rooting steps. Moreover, plants flowered during the acclimatization phase, confirming a more rapid in vitro development and shorter breeding cycle. This is a very interesting aspect for essential oil extraction. Trichome morphology was examined by scanning electron microscopy and the secretion analyzed through histochemical tests. Trichomes of micropropagated plantlets were identical to those of field-growing plants, and essential oil production was observed at early stages of development. The present study confirms that micropropagation under controlled conditions could be an interesting alternative for field production of L. multifida, since higher amounts of plants can be obtained in less time with guarantee of genetic stability and phytossanitary quality, very important features regarding essential oil production and commercialization.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".