PHYTOCHEMICAL ANALYSIS AND ANTIOXIDANT ACTIVITIES OF SENNA OCCIDENTALIS (L.) LEAVES
Bibliographic record
Abstract
Senna occidentalis (L.) is a plant belonging to the family Fabaceae and is also known as the coffee plant. It is used in various skin diseases, wounds, sores, and bone fractures as traditional medicine. Antioxidant, antimalarial, hepatoprotective, and antimalarial activities are recorded in this plant. The preliminary phytochemical screening in methanol, acetone, hexane and chloroform extracts of leaves records the presence of alkaloids, carbohydrates, glycosides, diterpenes, triterpenes, phytosterols, saponins, lactones, tannins, proteins and steroids in the present study. TLC in different solvent systems proves the ethyl acetate: hexane (2:8) as the best solvent system for the separation of phytoconstituents in methanolic extract of leaves. This study also examines the quantity of protein, total sugars, reducing sugars, phenols, and starch in fresh leaves by using biochemical assays. TFC and TPC were performed in methanol, acetone, and chloroform extracts, which proves that acetone extraction is the best choice for the TFC (452.15 ± 1.38 mg QE/g) and TPC (938.79 ± 10.98 mg GAE/g) content. Antioxidant assays such as DPPH, FRAP, CUPRAC, PMA, H2O2, and ABTS are also examined in methanolic and acetone extracts of leaves. This study can be useful for pharmaceutical industries for further analysis for drug preparations as leaves possess very good antioxidant activities and various bioactive compounds.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".