Antioxidant and antibacterial activities of indigenous plant leaf ethanolic extracts and their use for extending the shelf‐life of Nile tilapia ( <i>Oreochromis niloticus</i> ) mince
Bibliographic record
Abstract
Summary Long pepper (LP), soursop (SS), green vein kratom (GK), and red vein kratom (RK) leaf ethanolic extracts were prepared using an ultrasonic device, followed by dechlorophyllization by the sedimentation process. Antioxidant and antimicrobial activities of the extracts were studied. Highest yield and total phenolic content were found in RK extract ( P < 0.05). In general, RK extract showed the lowest minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) towards four bacteria ( Escherichia coli , Staphylococcus aureus , Pseudomonas aeruginosa , and Shewanella sp.), when compared with other extracts. Addition of GK extract at 600 mg kg −1 retarded chemical changes and lowered microbiological growth in Nile tilapia mince within 12 days at 4 °C. Lipid oxidation was also impeded with the aid of GK extract. Therefore, GK extract inhibited both spoilage and pathogenic bacteria, and prevented lipid oxidation, thus extending the shelf‐life of tilapia mince.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".