Nutrient Composition and Adequacy of two Locally Formulated Winged Termite (Macrotermes Bellicosus) Enriched Complementary Foods
Bibliographic record
Abstract
<p>The period from birth to two years of age constitute critical window of opportunity for promoting optimal growth and development of a child. Inadequate food intake and poor feeding practices are causes of malnutrition among Nigerian children, as many locally formulated complementary foods are deficient in protein and micronutrients. Roasted <em>Macrotermes bellicosus</em> (MB) is nutritious and relished as snack by people living the traditional lifestyle. This study was carried out to investigate possible use of MB in formulating nutrient-dense complementary foods from maize and sorghum. <em>Macrotermes bellicosus</em> was collected in Ibadan, Nigeria during their swarming, roasted, de-winged, powdered and added to fermented corn (CF) and sorghum (SF) flour in the ratio 100%flour, 90%flour+10%MB, 85%flour+15%MB, and 80%flour+20%MB to give eight complementary foods, which were analysed for proximate, mineral, vitamin and antinutrient composition using AOAC methods.</p><p>Hundred grammes of CF and SF contained 11.7g, 10.6g moisture, 8.9g, 9.7g crude protein, 3.1g, 2.8g fat, 74.3g, 74.8g total carbohydrates, 6.67mg, 26.60mg calcium, 295.50mg, 325.43mg phosphorus, 2.61mg, 7.61mg iron, 3.19mg, 2.41mg zinc, and yielded 353.9kcal, 358.6kcal energy respectively. Significant reduction occurred in moisture and carbohydrate content of MB-incorporated complementary foods while their crude protein, ash, fat, calcium, iron, zinc, vitamins B<sub>3</sub>, B<sub>6</sub> B<sub>12</sub> and beta-carotene content increased significantly as the level of inclusion of MB increased (p&lt;0.05). Level of atinutritional factors were insignificantly low in the blends, and cannot pose any health risk. <em>Macrotermes bellicosus</em> can be used in enriching cereal-based complementary foods as means of reducing infant and young child malnutrition in Nigeria.</p>
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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 | 0.001 | 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) | 0.000 | 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".