Essential Oil Composition and Bioactivity of Two Juniper Species from Bulgaria and Slovakia
Bibliographic record
Abstract
Juniperus excelsa M. Bieb and J. sabina L. contain essential oil (EO), while J. sabina also contains podophyllotoxin, which is used as a precursor for anti-cancer drugs. Two studies were conducted. The first assessed the variability in the EO profile and podophyllotoxin concentration of the two junipers, depending on the location and tree gender. The main EO constituents of J. excelsa were α-cedrol, α-limonene and α-pinene, while the constituents in J. sabina were sabinene, terpinen-4-ol, myrtenyl acetate and α-cadinol. The podophyllotoxin yield of 18 J. sabina accessions was 0.07–0.32% (w/w), but this was not found in any of the J. excelsa accessions. The second study assessed the effect of hydrodistillation (Clevenger apparatus) and steam distillation (in a semi-commercial apparatus) on the EO profile and bioactivity. The extraction type did not significantly alter the EO composition. The EO profiles of the two junipers and their accessions were different and may be of interest to the industry utilizing juniper leaf EO. Breeding and selection programs could be developed with the two junipers (protected species) in order to identify chemotypes with (1) a high EO content and desirable composition, and (2) a high concentration of podophyllotoxin in J. sabina. Such chemotypes could be established as agricultural crops for the commercial production of podophyllotoxin and EO.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".