Functional Groups and Individual Phenolic Compounds in Different Fractional Polarities Extracts of Rhizophora apiculata
Bibliographic record
Abstract
The mangrove forest is often regarded as an unpleasant environment with less intrinsic values. Rhizophora apiculata has an important value as it provides several benefits to people, for example, it is a traditional medicinal plant that is also used in construction, as a source of food, dye and so forth. This study aims to identify types of functional groups and individual phenolic compounds from R. apiculata. An analytical method for R. apiculata was developed with different fractional extracts from water extraction. The result from the FT-IR analysis presented all fractional extract detected with different types of functional groups. The results revealed that four types of individual phenolic acids, which are Caffeic acid, Vanillic acid, trans-p-Coumaric acid and Ferulic acid, were detected in ethyl acetate and butanol extracts. However, none of the phenolic acids was detected in petroleum ether extract. All the phenolic acids detected in the study have not been exploited to their full potential. More research on optimizing the isolation and purification of these pigments as well as their usage in food systems is needed to enable their use in food applications or textile industries.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".