Physicochemical and Sensory Properties of Cookies Produced From Composite Flours of Wheat, Cocoyam and African Yam Beans
Bibliographic record
Abstract
Cookies were produced from wheat, African yam bean and fermented cocoyam flour blends and their physicochemical and sensory properties were determined. Five flour formulations designated as samples A, B, C, D, E were produced. Sample A consisted of 100% wheat flour and served as the control. Samples B and C comprised of 80% wheat, 10% cocoyam, 10% African yam bean flours and 60% wheat, 20% cocoyam and 20% African yam bean flours. The composition of D and E were 40% wheat, 30% cocoyam, 30% African yam bean flours and 20% wheat, 40% cocoyam, and 40% African yam bean flours respectively. The result of the proximate composition showed that there was significant increase (P<0.05) in the protein, fat, fibre, ash content and energy values. The values range from 10.44-14.73%, 3.01-6.73%, 1.63-2.43%, 2.44-3.64% and 356.21-375.25% respectively. The carbohydrate content ranged from 63.94-71.84% while the values for moisture content vary from 8.54-10.68%. These values decreased significantly (P<0.05) with increase in cocoyam and African yam bean flours. The physical properties revealed the weight, diameter, thickness, and spread ratio ranges as; 18.01-20.15g, 6.48-6.82cm, 0.45-0.55cm, and 11.78-15.16, respectively. The sensory scores showed that the cookies produced from 100% wheat flour compared favourably with the cookies from the composite flours of wheat, African yam bean and fermented cocoyam and therefore cookies could be successfully prepared from the composite flours of wheat, African yam bean and fermented cocoyam flour. This would enhance the utilization of these underutilized crops and help in alleviating protein energy malnutrition problems in developing countries.
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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 | 0.001 |
| 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".