Impact of fava bean flour particle size on the quality of blended flour and bread made from it
Bibliographic record
Abstract
Fava beans are recognized for their nutritional richness and sustainability, presenting a promising ingredient for various food products. This study explores the potential of fava bean flour in bread production, focusing on how particle size and substitution levels influence product characteristics. Fava beans were milled into three particle sizes (0.14 mm, 0.50 mm, and 1.0 mm) using a single-stage Ferkar multipurpose knife mill. Physicochemical analyses revealed significant differences (p ˂ 0.05) among flour samples, with the 0.14 mm size exhibiting higher starch damage, protein, and fat contents. Functionality assessments showed varied properties across particle sizes, indicating diverse applications in food formulations. Moreover, in vitro digestibility assays showed improved starch digestion (p ˂ 0.05) with increasing flour particle size, emphasizing the importance of particle size in tailoring fava bean flour for specific culinary and nutritional needs. Further study examined the rheological properties, baking characteristics, and microstructure of bread produced using X-ray µ-CT with different levels of fava bean flour substitution (10%, 20%, and 30%) and the three particle sizes in wheat flour blends. Evaluation of baking characteristics revealed that fava bean flour substitution levels had a more pronounced impact on bread quality characteristics than particle size variation. For the three particle sizes, the bread produced with a 10% substitution level exhibited baking characteristics closest to those made with wheat flour alone. Additionally, hyperspectral imaging (HSI) demonstrated high classification accuracy (> 99%) in classifying fava bean-fortified bread into high and low-protein samples and based on colour characteristics, suggesting its reliability for quality monitoring in commercial bakeries. In conclusion, the study provides insights into optimizing fava bean-fortified bread formulations, guiding decisions on particle size, substitution levels, and final product quality. With the growing demand for alternative protein sources, integrating fava beans into wheat flour offers opportunities for innovation and sustainability in the food 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".