A Research on Comparative Methods of Isolation, Evaluation and Identification of Clitoria ternatea Plant
Bibliographic record
Abstract
Clitoria ternatea (Butterfly pea) is a traditional medicinal plant known for its therapeutic properties, including antimicrobial, antioxidant, and anti-inflammatory activities. This study aimed to evaluate its phytochemical composition, physicochemical characteristics, and extraction efficiency using different techniques to support its pharmacological potential. Ethanolic extracts of Clitoria ternatea flowers were prepared using maceration, Soxhlet extraction, and ultrasonic-assisted extraction. Qualitative phytochemical screening was conducted to identify secondary metabolites, while physicochemical parameters such as total ash, water-soluble ash, loss on drying, and alcohol- and water-soluble extractives were assessed. The Soxhlet method yielded the highest extractive value (89%), followed by maceration (62%) and ultrasonic extraction (57%). Phytochemical screening confirmed the presence of key bioactive compounds, including flavonoids, alkaloids, saponins, tannins, steroids, and cardiac glycosides. Physicochemical evaluations were within acceptable limits, supporting extract quality and reproducibility. This study validates the traditional use of Clitoria ternatea and demonstrates its potential for further development as a phytopharmaceutical agent. Soxhlet extraction is recommended for optimal recovery of bioactive constituents. Further research is warranted to isolate specific compounds and explore their therapeutic applications through pharmacodynamic and clinical studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".