Quality of Bread and Cookie Baked from Frozen Dough and Batter Containing <i><scp>β</scp></i>‐Glucan‐Rich Barley Flour Fraction
Bibliographic record
Abstract
Abstract Prolonged frozen storage of dough and batter unfavorably affects the quality of end baked products. The effect of air‐classified barley flour fraction rich in β‐glucan (∼25%) on the quality of bread and cookie baked from frozen dough/batter was investigated. Dough and batter were stored at −18C for 8 and 4 weeks, respectively, and evaluated for baking quality at weekly intervals. Bread made from fresh control dough produced the highest loaf specific volume (LSV) compared with those baked from composite dough. Control and composite frozen dough breads exhibited similar LSV and crumb texture profile up to 4 weeks of storage. Frozen storage of batter for 4 weeks resulted in no significant changes in either hardness or stickiness of batter and spread factor of cookie compared with control, while breaking force of cookie decreased. The addition of β‐glucan‐rich barley flour fraction holds a promise for developing fiber‐rich bread or cookie from frozen dough or batter. Practical Applications Incorporation of air‐classified barley flour fraction rich in β‐glucan in bread dough and cookie batter stored at freezing temperature (−18C) improves their shelf life through the restriction of water mobility in dough or batter without compromising the quality of baked end products. Such data can be invaluable in the baking industry.
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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) | 0.002 | 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".