Brugmansia suaveolens Leaf Productivity and Alkaloid Contents Under Different Doses of Organic Fertilizer
Bibliographic record
Abstract
According to the World Health Organization, the use of mineral fertilizers and pesticides should be avoided in the cultivation of medicinal plants due to their potential antagonistic actions. Brugmansia spp. is a perennial bush native to South America, but it is also cultivated in Europe, Central America, and Asia due to its ornamental characteristics. Aerial parts of this plant are used in ethnomedicine to alleviate ulcers and pain, as well as to treat abscesses, fungal infection of the skin, and dermatitis. Tropane alkaloids scopolamine and atropine are recognized as active principles of this plant. This study evaluated the applicability of organic agricultural techniques in the cultivation of Brugmansia suaveolens. The influence of different dosages (0-60 tons/ha) of organic fertilizer on the mass productivity of plant shoot as well as their atropine and scopolamine contents were investigated. The average dry matter of leaves (26.54±5.12-55.41±12.85 g) and stems (26.73±8.51-58.60±17.62 g) per plant increased with increasingly availability of organic fertilizer (0-60 ton/ha). The same behavior was observed when the contents of the active tropane alkaloids scopolamine (0.72±0.03-0.86±0.13 mg/g) and atropine (0.79±0.03-0.96±0.11 mg/g) were monitored by gas chromatography coupled with mass spectrometer. Overall, the treatment at the maximum level tested in this work (60 ton/ha) should be preferred over the other treatments. B. suaveolens could be a potential source of tropane alkaloids for the community of Botucatu city, which is a leading city in Brazil for the cultivation of food products under organic, biodynamic, and agroecology premises.
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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 | 0.000 | 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".