Comparison of Chemical Composition and Antioxidant Activity of Extracted Zingiberaceae Rhizome using Subcritical Water Extraction
Bibliographic record
Abstract
In Malaysia, many local herbs can take advantage of their benefit for health products, cosmetics, and food production. In this research, fresh Zingiberacea rhizomes including Curcuma Longa, Curcuma Zedoaria, Curcuma Xanthorrhiza, Zingiber Officinale, and Zingiber Zerumbet rhizomes were extracted using the subcritical water extraction (SWE) unit located at AM Zaideen Ventures Sdn Bhd in Kuala Lumpur (Malaysia). The focus of this research is to analyze the freeze-dried powder extracts from the fresh Zingiberaceae rhizome for the phytochemical screening and bioactive compounds. Operating parameter used in the extraction process was fixed at temperature of 110°C, pressure at 10 bar and extraction time of 15 minutes. The freeze-dried powder extracts were screened for its phytochemicals inclusive alkaloids, steroids, terpenoids, glycosides, tannin and saponin. For bioactive compounds analysis, extracts were evaluated for Total Phenolic Content, Total Flavonoid Content, DPPH scavenging activity assay, and bioactive compound using Gas-Chromatography Mass Spectrophotometry analysis. The results show that there was a different presence of phytochemicals compounds in different Zingiberaceae extracts. At 10mg/ml concentration of powder extract, Zingiberaceae rhizomes showed variations in total phenol and flavonoid content, ranging from 134.65 to 285.19 mg GAE/g and from 22.58 to 181.62 mg QE/g, respectively. For DPPH radical scavenging activity, observed at 10mg/ml of freeze-dried extract, all Zingiberacea demonstrated significance antioxidant activity of more than 85% inhibition. Bioactive compounds detected in Zingiberaceae rhizomes shows significance quality. This finding supports the exploration of indigenous herbs market in Malaysia and the potential of water-based extracts on fresh Zingiberaceae rhizomes.
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".