Content and Composition of Essential Oils from <em>Solidago canadensis</em> L. and <em>Solidago virgaurea</em> L. Growing in Estonia
Bibliographic record
Abstract
Both invasive Canadian goldenrod (Solidago canadensis L.) and Common goldenrod (S. virgaurea L., Asteraceae) are recognised in traditional medicine as folk remedies for the treatment of kidney, urinary tract, and liver diseases, among others; however, their pharmaceutical potential remains largely unexplored. The aim of the study was to compare the yield and composition of essential oils (EO) of flowering tops (20 cm long) of S. canadensis and S. virgaurea. The yield of EOs, hydrodistilled from S. canadensis (n=8) and S. virgaurea (n=5) herbs using the European Pharmacopoeia method, ranged from 2.7 to 14.9 mL/kg. The average EO yield in both goldenrod species was similar, but the composition differed. 82 constituents were identified and semiquantified by GC-MS in the EOs of both Solidago species, eight of which have been found in these species for the first time. α-Pinene, (Z)-β-ocimene, D-limonene, and (E)-β-ocimene were the principal compounds in S. canadensis herb EO; and α-pinene, l-β-pinene, β-myrcene, and humulene in S. virgaurea EO. It contained, on average, 39 times more benzyl salicylate than the EO from S. canadensis. Also, the amounts of viridiflorol (more in S. virgaurea), or L-β-bourbonene and (E)-β-ocimene (more in S. canadensis) can be used as a chemical fingerprint of both goldenrod species studied. The qualitative composition of the EO of both goldenrods was very similar, only the content of α-muurolene may be a chemical marker for distinguishing them. The pharmaceutical perspective of V. canadensis as an invasive species is not yet sufficiently clear. Chemical composition of different species of goldenrod and their relationship to biological activity, as well as the potential for internal and external use, remains a topic of ongoing interest.
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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".