Unveiling the phytochemical variability of fatty acids in world marigold (Calendula officinalis L.) germplasm affected by genotype
Bibliographic record
Abstract
Marigold is an annual herbaceous medicinal and aromatic plant, native to the Mediterranean region. Although marigold flowers have attracted considerable attention, the noteworthy characteristics of marigold seeds have often been overlooked. The industrial sector holds keen interest in marigold due to the presence of calendic acid in its seeds. Moreover, calendic acid exhibits promising anti-cancer properties, adding to the growing interest in the medicinal potential of this plant. In this study, a total of 31 marigold genotype seeds from fifteen different countries were used as experimental material. The observed seed oil content exhibited a range of values spanning from 6.00% to 20.33%, with a mean value of 11.59%. GC/MS analysis was conducted to evaluate the chemical variability associated with genotypic changes. Notably, the main fatty acids observed in the oil of these genotypes were α-calendic acid (ranging from 6.91% to 51.42%), linoleic acid (ranging from 30.50% to 48.25%), oleic acid (ranging from 8.26% to 22.50%), and palmitic acid (ranging from 3.86% to 9.28%). Particularly noteworthy is the emergence of genotypes PI 420376, PI 545694, PI 545701, PI 578109, PI 597588, PI 597591, and PI 597594, boasting calendic acid content exceeding 50%. Furthermore, the values of calendic acid exhibit significant variation across countries. The range extends from the United Kingdom, displaying one of the lower values, to Ontario, Canada, which represents countries with notably higher values. Consequently, there exists a necessity to enhance the proportion of calendic acid within marigold through strategic plant breeding techniques. This can be achieved through the selection and development of marigold cultivars with higher calendic acid contents.
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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 | 0.001 | 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".