Effect of Stinging Nettle Leaf Flour Substitution on the Quality Characteristics of Fermented Corn Complementary Foods
Bibliographic record
Abstract
Proper complementary feeding is required to provide essential nutrients to growing infants. However, most families in developing countries are severely food insecure, leading to constant child malnutrition. This study developed fermented corn complementary foods (pap) supplemented with abundantly available and affordable stinging nettles. Stinging nettle leaf flour was incorporated into pap at 5%, 10%, 15% and 20% and evaluated in relation to nutritional, functional, and sensory properties. Soybeans were used to compare the nutritional and health benefits of nettles in infant nutrition. A gradual incorporation of nettle leaf flour increased (p<0.05) the ash, protein, and dietary fibre content of pap from 0.72%, 3.48% and 2.87% to 9.46%, 18.98% and 4.56% respectively. Likewise, nettle-enriched pap contained higher carotenoids (4.99mg/100g), vitamin C (48.76mg/100g), calcium (176.49mg/100g), phosphorus (35.21mg/100g), potassium (210.54mg/100g), and iron (284.55mg/100g) than soybean-enriched pap: 0.96, 4.40, 50.99, 29.29, 204.78 and 64.02mg/100g respectively. While total phenolic content and antioxidant activity index increased (p<0.05) with increasing addition of nettle leaf flour from 1.23mgGAE/g and 0.15 to 125.45mgGAE/g and 2.01 respectively, the metabolic glycaemic response decreased (p<0.05) from 68.53% to 35.60%. In addition, all functional qualities were within acceptable limits for complementary feeding. Nursing mothers rated the overall acceptability between 7.14 (5% nettle-enriched pap) and 6.23 (20% nettle-enriched pap), and 12 of these 20 mothers accepted to feed their babies with stinging nettle leaf flour. Our findings indicated that stinging nettle leaves are nutritionally important for improving low-cost complementary feeding and thus could contribute to the combat of infant malnutrition in rural communities.
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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 | 0.004 | 0.000 |
| 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".