Effect of Decreasing Saponin Levels to Nutrition of Extracted Moringa Leaf Powder
Bibliographic record
Abstract
Moringa oleifera leaves have been used as food material because it has high nutritional value. Many research have been conducted on moringa leaves extract as functional food and the additional material of nutrient for some food products (biscuit, bread, jelly drink), which it looked that adding moringa leaves extract above 5% decrease the consumer acceptance level toward the product because of the strongest unpleasant aroma and bitter taste, which is caused by saponins content in moringa leaves extract is still high enough.This study aimed to obtain the optimal temperature and time of blanching process to reduce saponin level, and the appropriate solvents to extract nutrients from Moringa oleifera leaves so that Moringa leaves flour is obtained with no bitter taste (low saponin) and nutritious (water, protein, optimal vitamin C and vitamin A) as fortification ingredients for various food products. The results showed that the blanching treatment at 75 ° C for 5 minutes (T1W1) combined with 70% ethanol (P1) solvent was able to produce Moringa leaves flour with the lowest saponin content of 0.790%, but with nutrients that still met the requirements, namely water 6.508%, protein 28.705%, Vitamin C 90.77 mg 100 g-1 and Vitamin A 3590 µg 100 g-1.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".