Functional role of citrus fiber as an emulsifier in dough rheology, gluten structure formation and bread quality characteristics
Bibliographic record
Abstract
BACKGROUND: Citrus fiber (CF) is a promising clean label emulsifier to replace commonly used emulsifiers such as propylene glycol alginate (PGA) in breadmaking. However, most previous studies have focused primarily on the physical and sensory attributes of CF-enriched bread while the mechanisms underlying these effects remain poorly understood. RESULTS: The addition of CF significantly increased β sheet structure of gluten proteins and improved both the storage modulus (G') and loss modulus (G″) of dough, with a more pronounced effect on G' compared to PGA. White bread containing the optimum CF level (0.6% CF) displayed the highest specific loaf volume, improved crumb structure and reduced staling, whereas a higher level (0.9%) led to a decline in bread quality. Quantitative protein network analysis indicated that CF enhanced dough properties by increasing total gluten length, area and junction density. CONCLUSION: Overall, CF demonstrates potential as a clean label functional ingredient that improves the structural and textural quality of bread for health-conscious consumers. However, its optimal incorporation level must be carefully controlled to avoid adverse effects on product quality. © 2025 Society of Chemical 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) | 0.001 | 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".