HPLC-DAD analysis of flavonoids and hydroxycinnamic acids in Aster novi-belgii L.
Bibliographic record
Abstract
Aster novi-belgii is a perennial ornamental herb native to eastern Canada and the United States of America, cultivated in Ukraine. This species should be considered a possible source of phenolic compounds, principally hydroxycinnamic acids and flavonoids. Therefore, in this study, the aim was to determine these compounds in Aster novi-belgii by HPLC-DAD analysis, and validation of this chromatographic method and lay a scientific and technical basis for the utilization and development of the plant resources of the cultivated plants of the genus Aster. The HPLC-DAD method determined the flavonoids and hydroxycinnamic acids composition and content in the herb of Aster novi-belgii L. The HPLC-DAD method allowed the detection of 13 phenolic compounds, namely 6 hydroxycinnamic acids (chlorogenic, sinapic, caffeic, syringic, trans-cinnamic, trans-ferulic acids), and 7 flavonoids (kaempferol 3-O-beta-D-glucoside, naringin, quercetin, luteolin, rutin, kaempferol, rhamnetin). The quantitative detection showed that the main hydroxycinnamic acids were chlorogenic acids (15069.21 ± 0.34 µg/g) and sinapic acids (949.95 ±0.22 µg/g). Concerning flavonoids, the largest amounts were kaempferol 3-O-beta-D-glucoside (8989.79 ±0.31 µg/g) and naringin (2092.02 ± 0.26 µg/g). HPLC-DAD method was evaluated in terms of linearity, precision, accuracy, limits of quantification, and limits of detection. The calibration curves of reference substances were linear (R2 ≥ 0.997), the LODs were in the range of 0.21–1.71 µg/mL, and the LOQs – of 0.48–5.19 µg/mL, respectively. Our phytochemical research confirms that the study material is a rich source of hydroxycinnamic acids and flavonoids. Findings mean that Aster novi-belgii is a promising plant because of the important role of these phenolic compounds in many biological processes.
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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 | 0.000 |
| 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".