Nutritional Composition of Value-added Fish Products from Selected Fish Species in Kenya
Bibliographic record
Abstract
Fish is an important seafood that provides quality nutrients to human beings which is vital for health and development. This is especially critical in the diets of children under two years old and reproductive women (pregnant and lactating). Selected fish species were sampled from both Lake Victoria and fish farms, and their weight was determined using a sensitive weighing balance and fish-based products (powder and gelatin) developed to food-grade standards. The proximate composition of minerals, amino acid, and fatty acid profile were assessed in the laboratory, and data were analyzed using R statistic tool version 4.2.2 to understand the differences between the variables at a significance level of p < 0.05. Results indicated that crude fat ranged from 3-23%, crude protein was highest in Nile perch gelatin at 81.22±1.43 while omena and haplochromine spp. had the highest concentration of calcium at 6347.1±428.5 and 4522.0±233.3 mg/Kg respectively. The highest concentration of essential amino acids was found in omena and Nile perch powder. Among the fatty acids; oleic and palmitic were the dominant fatty acid in the fish products at 25.12±0.56% - 45.12±0.65% and 20.52±0.69% - 44.23±0.74% respectively. The moisture content of the final products was between 4.64 ±0.08% - 8.82±0.35%, which was within limits ensuring little microbial activity thus enhancing the shelf-life of the final products. The developed products had nutrients that are beneficial to human health at desirable concentrations and are recommended for inclusion in the diet of vulnerable groups for a prosperous community free from hunger and malnutrition.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".