Nutritional and Organoleptic Properties of Wheat (Triticum aestivum) and Beniseed (Sesame indicum) Composite Flour Baked Foods
Bibliographic record
Abstract
Eating snacks during lunch periods has become a way of life for school children and the busy working class people in most urban cities in developing nations like Nigeria. Providing nutritious and healthy snacks remains a major challenge for the food industry to tackle, including the issue of sugar and carbohydrate contents in snacks which predisposes obesity. Nutritional and sensory characteristics of baked foods produced from wheat/beniseed flour composite were investigated with the aim of producing healthy and nutritious baked foods. Beniseed was substituted in wheat flour so as to increase the protein content and enhance the nutritive value of baked food produced from such composite flour. Beniseed was substituted in wheat flour at 3 levels (10%, 20%, 30%) with other ingredients to produce bread and cake. The samples were analyzed for proximate content, vitamin A and C, antinutrients, minerals and sensory properties. Proximate and mineral contents, as well as Vitamin A and C content of the bread and cake showed significant increases (P>0.05) with increase in beniseed substitution levels. The level of total oxalate and soluble oxalate significantly increased (P<0.05), while phytate and tannins significantly (P<0.05) decreased with increase in beniseed substitution level. There was no significant difference (P<0.05) in the panelist ratings for taste, color, flavor, texture and overall acceptability of 10% beniseed substitution for bread and up to 20% beniseed substitution for cake with the control. The results indicate that a healthy and nutritious snack could be produced from wheat and beniseed flour composite. This study is of public health significance in Nigeria.
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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 | 0.000 | 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) | 0.001 | 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".