Carotenoid Content and Composition in 20 Medicinal Plant Species of Traditional Malay Midwifery Postnatal Bath
Bibliographic record
Abstract
Today in Malay community, midwifery traditional knowledge of herbal medicine has disappeared and extinct. The facts are Malay midwives are becoming rare and the more crucial is medicinal plants are over-harvested. The aim of this research is to identify and investigate the active pharmaceutical ingredients content in 20 selected species used in the Malay traditional bath. There is a solid need to analyse the potential of these natural bioactive compounds, particularly carotenoids to be fully utilised and commercialised especially in halal market and health advantages. Through High performance liquid chromatography (HPLC) analysis, all 20 species were found to have at least four individual carotenoid pigments with a relatively high concentration of lutein and β-carotene and lower concentrations of zeaxanthin. Strobilanthes crispus (Pecah Kaca) leaf was detected to have the highest total carotenoid content (1546.80±283.45 μg/g DW)while Psidium guajava (Jambu Batu) shoot has the lowest total carotenoid content (112.9±82.2 μg/g DW). The significant outcome of the research was a new findings of new natural bioactive compound sources as health promoting agents which covers not only the Shariah requirement, but also safety aspects. Moreover, it will preserve the traditional knowledge of Malay traditional bath practices.
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 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 | 0.001 | 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".