Extraction and Analyses of Flavonoids and Phenolic Acids from Canadian Goldenrod and Giant Goldenrod
Bibliographic record
Abstract
Invasive alien plant species Canadian goldenrod (Solidago canadensis L.) and giant goldenrod (Solidago gigantea Aiton) were investigated as a source of phytochemicals and yellow dyes. Flavonoids and phenolic acids were extracted from the inflorescence of Canadian goldenrod with thirteen extraction solvents ethanol, methanol, acetone, water, and mixtures of organic solvents (70%, 80%, and 90%) with water. High performance thin-layer chromatography (HPTLC) coupled to densitometry and high-performance liquid chromatography with photo-diode array detector (HPLC-PDA) were used for analyses of the obtained sample test solutions (STSs), which showed the best and comparable extraction efficiencies for 70% acetone(aq), 70% methanol(aq), and 70% ethanol(aq). HPTLC combined with image analyses in fluorescent mode resulted in different chromatographic fingerprints for Canadian goldenrod and giant goldenrod STSs (70% acetone(aq)) after development, after post-chromatographic derivatization with NP reagent and after use of PEG reagent. The developed HPLC methods enabled analyses of phenolic acids and flavonoids (aglycones and glycosylated) in STSs and hydrolyzed STSs form inflorescence of Canadian and giant goldenrod. Different contents of chlorogenic acid, rutin, hyperoside, isoquercetin, and quercetin were observed in STSs of both goldenrod species. The analyses of hydrolyzed STSs confirmed that glycosylated flavonoids in Canadian and giant goldenrod inflorescence are mainly glycosides of quercetin, kaempferol, and isorhamnetin. Additional analyses using HPTLC and HPLC coupled to tandem mass spectrometry (MS/MS; HPTLC-MS/MS and LC-MS/MS) enabled tentative identification of phenolic acids and flavonoids (10 with HPTLC-MS/MS and 15 with LC-MS/MS), from which several were identified in Canadian (4 with HPTLC-MS/MS and 8 with LC-MS/MS) and in giant (7 with HPTLC-MS/MS and 9 with LC-MS/MS) goldenrod for the first time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".