Effects of morphogenetic and diurnal variability on the hypericin content in St. John's Wort ( Hypericum perforatum L.)
Bibliographic record
Abstract
This research was conducted to investigate effects of morphogenetic and diurnal variability on the hypericin content of St. John's Wort (Hypericum perforatum L.) populations originating from Turkey for maximum utilization of the active substance in plants. During 2002 and 2003, field trials were conducted at Uludag University, Faculty of Agriculture, Department of Field Crops, Bursa, Turkey. Samples of bud, flower and capsule of H. perforatum L. populations were collected in the second year of cultivation (2003). Factorial arrangements of three H. perforatum L. populations (Bursa, Edirne, Izmir), three part of plant (bud, flower, capsule) and six collection h (8:00, 10:00 a. m; 12:00 (noon), 2:00, 4:00, 6:00 p. m) were evaluated in a completely randomized block design with three replications. Hypericin content (%) in parts of H. perforatum L. populations was determined according to DAC (1986). Consequently, the content of hypericin in the examined populations varied from 0.260% in Bursa to 0.283% in Izmir. Evaluating plant parts revealed that the hypericin content both in floral parts (0.309%) and buds (0.308%) were higher than capsule tissues (0.208%) for all populations. When collection hours were examined for the hypericin content of plants, the highest content was recorded at 10:00 a. m (0.279%) and the lowest value at 4:00 p. m (0.272%) and 6:00 p. m (0.272%). As a result, this study showed that the highest hypericin ratio was determined in flowers and buds generally collected between 8:00 and 10:00 a. m within a day for examined Hypericum populations.
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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 | 0.001 |
| 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".