Rheological, Baking and Sensory Characteristics of Bread from Wheat-Cassava Composite Dough
Bibliographic record
Abstract
Uganda produces cassava, which has potential as a raw material for agro-industry. In this study, wheat flour was blended with high quality cassava flour in the ratios 100:0, 90:10; 80:20; 70:30; 60:40; 50:50 and 40:60 and the composite dough used to prepare bread. The doughs were subjected to rheological analysis using mixolab, consistograph and alveograph. Bread physical properties were measured and sensory qualities evaluated to correlate rheological characteristics of flour/dough with bread quality. Inclusion of cassava flour in the composite dough negatively affected the quality of the composite bread compared to the control. Bread volume (631.0 to 516.7 cm3) decreased, specific volume (2.065 to 1.574 cm3/g) decreased, bread density (0.49 to 0.63 g/cm3) increased. Mean scores for sensory quality parameters reduced: crust colour (6.88 to 4.63), taste (7.13 to 4.25), crumb texture (6.5 to 4.63) and overall acceptability (8.13 to 4.5). Bread quality was positively correlated with mixolab parameters protein weakening (C2), dough stability and dough development time (DDT); alveograph parameters tenacity (P) and deformation energy (W); and consistograph parameter maximum pressure (PrMax). Results showed that bread of acceptable quality can be processed using wheat composite containing 20 % cassava flour. Rheological properties can be used to assess suitability of flour for bread making.
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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 | 0.001 | 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) | 0.000 | 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".