Glucosinolate profiling in <i>Cleome gynandra</i> L. aerial parts based on two extraction methods
Bibliographic record
Abstract
Glucosinolates and their degradation products from Cleome gynandra L. are known for their beneficial effects in traditional medical use. As part of daily nutrient intake, the areal parts of this herb are cooked and consumed, whereas the residual water from boiling is discarded. However, it may contain valuable bioactive metabolites. Therefore, we focus our investigations on Cleome gynandra L. for the presence of glucosinolates using two extraction methods (conventional and unconventional) and according to the physiological stage of growth of the plant. The results showed that glucosinolate contents expressed in mg of glucocapparin/g dry matter (mg/g) differed quantitatively according to the extraction method and physiological development stage. Glucocapparin content was 8.24 mg/g dry matter for the methanolic extract (conventional method) compared to 5.01 mg/g dry matter for the aqueous extract at the fruiting stage of the plants. LC-MS and 1H NMR analysis confirmed the identity of the major glucosinolate as glucocapparin. Quantification revealed the same variation trend in glucosinolate content according to the physiological stage of plant growth with the two extraction methods, i.e., 2.58, 4.74, and 5.01 mg glucocapparin/g dry matter for aqueous extracts (unconventional method) and according to the vegetative, flowering, and fruiting stages, respectively. However, it appears that aqueous extracts (cooking wastewater) obtained from areal parts of Cleome gynandra L. could constitute enriched extracts in glucosinolates from Cleome gynandra L. for phytoprotective applications from the fruiting stage.
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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) | 0.000 | 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".