Comparative Studies on the Physicochemical and Sensory Properties of Watermelon (Citrullus lanatus) and Melon (Citrullus vulgaris) Seed Flours Used in “EGUSI” Soup Preparation
Bibliographic record
Abstract
A comparative study on the physicochemical and sensory properties of watermelon (Citrullus lanatus) and melon (Citrullus vulgaris) seed flours in food preparation were investigated. A composite flour containing equal parts of watermelon seed flour and melon seed flour were prepared. Egusi soups were prepared from the melon seed flour; watermelon seed flour and a combination of the two flours in equal proportions. Sensory properties of the three soups were evaluated. The results of the investigation showed that the equal proportions of watermelon/melon seed flours had higher crude protein of 27.73% and crude fat of 47.85% than the water melon seed and melon seed flours. There was no significant difference (P>0.05) in water absorption, foam capacity, viscosity and least gelation properties of the melon seed flour compared to the 50:50 flour sample. The sensory properties showed no significant difference (P>0.05) in appearance, taste, thickness and overall acceptability of egusi soup from melon seed flour and 50:50 flour sample. Therefore watermelon seed flour can be used to replace 50% melon seed flour in the preparation of egusi soup
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".