Stability of Vitamin A in Nigerian Retailed Biscuits
Bibliographic record
Abstract
Vitamin A deficiency is a major public health problem affecting poor populations in developing countries. Biscuits baked with Nigerian vitamin A fortified flour (30 IU/g) have been consumed by pre-school children. This study aims at determining vitamin A content and stability in retailed biscuits at point of consumption. Pre-tested, semi-structured, interviewer-administered questionnaire was used to collect biscuit consumption pattern of pre-school children (n=1600). Out of 18 brands of biscuits reported, eight cartons of 8 commonly consumed brands were purchased from major markets in Lagos. Vitamin A (retinol) stability was determined by storing biscuit samples for 30 days. Pre- and post-storage retinol analyses were carried out using high performance liquid chromatography. Vitamin A stability was calculated as percentage of initial vitamin A biscuit values. Crunchiness and packaging of biscuit samples were also assessed. Data were analysed using descriptive and T-test at p<0.05. At pre-storage level, 62.5 % and 37.5 % samples had vitamin A and zero contents respectively. At post-storage, 25% had vitamin A content while 75% had zero content. Pre- and post-storage vitamin A content of samples was 5.2±4.9 IU/g and 1.9±1.8 IU/g. Mean vitamin A stability and loss in retailed biscuits at 2 months was 16.8% and 83.2% respectively. A significant difference was found in vitamin A content and stability of biscuits at pre- and post-storage levels. Biscuits lost crunchiness at post-storage level. Vitamin A content of retailed biscuit samples was below 30 IU/g resulting in very low stability. Use of fortified quality raw materials and compliance are essential.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".