Enrichment of Fermented Sorghum Flour with Pumpkin Pulp and Seed for Production of A Vitamin A and Iron Enhanced Supplementary Food
Bibliographic record
Abstract
Vitamin A and iron deficiencies are prevalent in preschool children being a public health concern. The study aimed at developing a flour blend formulation made of sorghum, pumpkin pulp and seeds and examining its contribution to the daily nutrient requirement for iron and vitamin A among preschool children. Three flour blends were formulated using a mixture of fermented sorghum flour, pumpkin seed flour and pumpkin pulp flour with the following ratios 80:10:10 (FP1), 70:15:15 (FP2) and 60:20:20 (FP3), respectively whereas control was made of 100% fermented sorghum flour. The flour blends and the control were analyzed for moisture content, protein, crude fiber, crude fat, ash, carbohydrate, beta-carotene and iron content. Further, sensory tests were conducted using a nine-hedonic scale to evaluate consumers acceptability of porridge made of the flour samples. Microbial analysis was conducted to establish the safety of developed flours. The results show that as the proportion of pumpkin pulp and pumpkin seed flours increased the protein content, ash, vitamin A and iron content significantly (P<0.05) increased. The flour blend FP3 recorded the highest amount of protein (22.87%), vitamin A (875.00 µg RAE/100g) and iron (27.51 mg/100g). The FP2 flour blend was the most preferred with sensory score of 7.91 and had ability to meet >70% of daily protein, iron and vitamin A requirements of preschool children thus most suitable for a feeding trial. The findings of this study demonstrate that pumpkin pulp and pumpkin seed can be used to enhance the nutritive value of sorghum and as such meet the protein, iron and vitamin A requirements of preschool children aiding in the eradication of nutritional deficiencies.
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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 | 0.000 |
| 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".