Nutritional Value and Sensory Acceptability of M. oleifera Fortified Finger Millet Porridge for Children with Cerebral Palsy in Nairobi County, Kenya
Bibliographic record
Abstract
Nutritional deficiencies and other nutritional comorbidities commonly affect children with cerebral palsy. Interventions through fortification to enhance nutrient densities of foods for these groups may improve their intakes and consequently their nutritional and health status. This study was undertaken to determine the nutritional value and sensory acceptability of a finger millet porridge fortified with Moringa oleifera leaf powder. Standard methods approved by the Association of Official Analytical Chemists were adopted for determination of nutrient and anti-nutrient content of samples. Sensory evaluation was conducted according to the method of Larmond (1977). Statistical analysis was conducted with the aid of Statistical Package for Social Sciences software version 20. One-way analysis of variance with a post-hoc test of Least Significant Difference to separate the means was used to compare the nutrient and anti-nutrient content of samples. Independent t-test was used to test difference in mean sensory scores between fortified and control porridge. The results showed that M. oleifera leaf powder had significantly higher contents of protein and β-carotene, which were the target nutrients for fortification of the fermented finger millet flour. Fermentation reduced the levels of anti-nutrients in finger millet flour. Fortification of the fermented finger millet flour with M. oleifera leaf powder at the ratio of 9:1 significantly improved the protein and β-carotene content of the fortified flour and did not significantly affect the sensory acceptability of the fortified porridge. This study confirmed the potential for M. oleifera as suitable fortificant in finger millet porridge formulations to improve both protein and β-carotene intake in target populations
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".