The influence of plant growth hormones on St. John's Wort (Hypericum perforatum L.) the formation of phytochemical compounds and antioxidant activity.
Bibliographic record
Abstract
St. John's wort (Hypericum perforatum L.) accumulates numerous secondary metabolites that provide beneficial properties such as antidepressant, antioxidant, antibacterial, and others. In modern society, there is a search for means to replace synthetic compounds with naturally derived ones that possess similar beneficial qualities, and St. John's wort is an excellent source of various useful compounds. However, cultivating the plant in vivo and extracting targeted compounds is a long process that depends on various factors. One significant advantage of in vitro cultivation is the ability to standardize environmental factors, optimize conditions and plant growth hormones to obtain high yields of beneficial substances, significantly shortening the process from sowing to product extraction. This work investigates the influence of plant growth hormones on the in vitro cultivation of St. John's wort, evaluating the antioxidant activity, concentrations of phenolic compounds, phenolic acids, flavonoids, anthocyanins, chlorophylls, as well as carotenoids, proteins, and some antioxidative enzymes in cultures of St. John's wort induced by plant growth hormones. Three extracts obtained from St. John's wort cultures grown in MS medium with plant growth hormones were used for the research: 0.5 mg/l TDZ and 0.1 mg/l IAA; 0.11 μM kinetin and 0.9 μM 2,4-D; 0.1 mg/l NAA, 0.2 mg/l BAP, and 0.5 mg/l 2,4-D. The recommendation section provides a scheme for obtaining hypericin which could be applied and optimized in the industry by manipulating the combination of plant growth hormones.
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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 | 0.000 | 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) | 0.001 | 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".