Basal medium improvement for routine micropropagation of <i>Olea maderensis</i>: physiological comparative studies
Bibliographic record
Abstract
The routine micropropagation of Olea maderensis (Lowe) Rivas Mart. & Del Arco requires an adequate basal medium. To find the optimal basal medium, shoots were grown on four different media: olive medium (OM) and three modified OM media enriched with 2, 4, and 10 times the iron (Fe), magnesium (Mg), and manganese (Mn) concentrations of the OM medium, respectively (OMG, OMG4, and OMG10). For the elongation–proliferation stage, media were supplemented with 9.12 µmol·L–1 zeatin. Doubling the Fe, Mg, and Mn concentrations (OMG) provided green and healthy shoots, while in other media leaf chlorosis or necrosis and abscission occurred because of either deficiency (OM) or toxicity of the elements (OMG4 and OMG10). Shoots grown in the OMG medium also had the highest elongation–proliferation rates. Physiological studies were then performed only between OMG- and OM-grown shoots. Chlorophyll a and b contents and fluorescence (Fv, Fm) were higher in OMG-grown shoots. Doubling the concentration of Fe, Mg, and Mn (which are important in photosynthesis) stimulated leaf survival and photosynthesis. OMG-grown leaves had higher Mg, Fe, and Mn levels. Compared with field leaves, in vitro leaves had higher protein contents. Other physiological parameters (membrane integrity, water content, and osmolality) did not differ between the two media. The best rooting rates were obtained for shoots grown in OMG (>85%), and plants were successfully acclimatized. These studies improved the efficiency and quality of micropropagation of O. maderensis, thereby allowing germplasm preservation of this endangered species.
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 | 0.001 | 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".