Interrelationships of Flour, Dough, and Bread Properties Under Reduced Salt Level Conditions
Bibliographic record
Abstract
The interrelationships between flour quality and the variability in the dough physical properties and bread loaf characteristics were investigated under reduced salt conditions using partial least squares (PLS) regression analysis. Seventy‐two percent of the variability in dough physical properties was explained by the flour quality using a three‐factor PLS model. Damaged starch content (DS), protein content, and farinograph dough development time (DDT) explained the variability of dough creep‐recovery behavior along PLS‐1. Farinograph absorption (FAB), located along PLS‐2, was strongly related to dough adhesiveness, in which adhesiveness was highly correlated to dough stickiness ( r = 0.91). Eighty‐nine percent of the variability in bread loaf characteristics was explained by the flour quality using a four‐factor PLS model; the first two PLS factors explained 66% of the variability. The loaf volume was related to a high number of loaf cells, whose expansion resulted in a greater loaf height. The relation between loaf volume and loaf height was expressed more in PLS‐3 than PLS‐1 and PLS‐2. Mean cell wall thickness and mean cell diameter were closely related negatively along PLS‐1, for which DS and farinograph dough stability explained much of the variability in these loaf characteristics. Along the third PLS factor, FAB explained the variability in loaf weight.
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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".