Seed yield and components of alkaloid of meadow saffron (<i>Colchicum autumnale</i>) in natural grassland and under cultivation
Bibliographic record
Abstract
Alkaloids extracted from meadow saffron seeds are used in numerous medicines. To test the influence of cultivation and climatic conditions on the production and the quality of meadow saffron seeds, we studied seed alkaloid yield on a natural site (grassland) and in a cultivated crop over several years. Seeds contained in capsules harvested before their dehiscence were dried and ground. The alkaloids of the extracts (colchicoside, demethylcolchicine and colchicine) were analyzed by high-pressure liquid chromatography. Seed alkaloid content was not influenced by year, inter-plant competition, or number of capsules per plant. Seed dry matter yield per plant, however, practically tripled in the cultivated crop due to an increase in the number of capsules per plant compared to the grassland. In the cultivated crop, 47% of fruiting plants produced two new plants (corms) every year. Four years after planting, this vegetative multiplication resulted in intraspecific competition, inducing a decline in seed yield per plant linked to a decrease in the weight of seeds per capsule. We were able to show that cultivated production of meadow saffron greatly increased dry matter and alkaloid yield per plant and per hectare, but that it could lead to the need to thin after several years. Key words: meadow saffron, alkaloids, colchicine, cultivation
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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".