Characterization of Phenolic Compounds of Olea europaea L. andCeratonia siliqua L. Leaf Extracts by HPLC-ESI-MS
Bibliographic record
Abstract
Background: Olive (Olea europaea L.) and carob (Ceratonia siliqua L.), which contain considerable amounts of phenolic compounds, are the most important nutritional and therapeutic plants in the Mediterranean basin. Objectives: The goal of this work is to revalue carob and olive leaves as key sources of polyphenols, hence increasing the value of waste goods. Methods: In this study, aqueous acetone or ethanol (80% v/v) extracts of olive (O. europaea L. cultivar aimel) and carob (C. siliqua L.) leaves from Algeria were evaluated for phenolic content, and the extracts were characterized by reverse-phase high-performance liquid chromatography-electrospray ionization mass spectrometry (HPLC-ESI-MS). Discussion and Results: The total phenolic content of olive and carob leaf extracts ranged from 5.6 to 23 mg GAE/g. The use of HPLC-ESI-MS to investigate phenolics revealed that the extracts included a variety of phenolic compounds, including 23 compounds in olive leaf extracts and 17 compounds in carob leaf extracts. In olive and carob, the major phenolic components are oleuropein and myricetin rhamnoside, respectively. Conclusion: According to our findings, olea europaea and Ceratonia siliqua appear to be rich suppliers of natural chemicals. These plants have a lot of potential in terms of medications and functional foods.
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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 | 0.000 | 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 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".