Nutritional and sensory quality of wheat bread supplemented with cassava and soybean flours
Bibliographic record
Abstract
Sixteen composite flours were prepared using D-optimal constrained mixture design within a range of wheat 40–80%, cassava 10–30% and soybean 10–30% to optimize bread nutrient quality and sensory acceptability. Results obtained showed blending had a significant (p < 0.05) effect on protein, ash, energy, iron, calcium, phytate, bread loaf volume, taste and odor. Higher quantities of soybean addition increased protein, energy, mineral, phytate and condensed tannin contents, whereas cassava increased total carbohydrate contents. The optimum blending ratio for both nutritional and sensory acceptability was in the range of 49.0–71.0% wheat, 10.6–29.0% cassava and 18.2–22.0% soybean flours. Loaf volume of bread processed from less than 70% wheat flour in this study was observed to be inferior in terms of quality attributes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".