Changes in Phenolic Acids and Antioxidant Properties during Baking of Bread and Muffin Made from Blends of Hairless Canary Seed, Wheat, and Corn
Bibliographic record
Abstract
Phenolic acids are the major polyphenols in cereal grains and they undergo changes in their composition and structure during processing. This study investigated changes in phenolic acids and antioxidant properties during baking of bread and muffin made from hairless canary seed (HCS), Phalaris canariensis L., alone or in blends with corn and wheat. The changes were monitored after dry mixing, dough/batter formation, and oven baking. Phenolic acids were quantified in products using HPLC and antioxidant activity was based on DPPH, ABTS, and ORAC assays. Eight phenolic acids were primarily present in the bound fraction extracts, while only a few phenolic acids were detected in the free or unbound fraction extracts. Ferulic was the dominant phenolic acid in wheat, corn, and HCS followed by p-coumaric acid but the latter was extremely high in HCS compared to wheat and corn. After baking, bound phenolic acids decreased in breads and muffins, while the unbound phenolic acids increased. Dough preparation resulted in about 5–13% reductions in bound ferulic acid in addition to 2–9% after oven baking with a total reduction of about 10–20% subject to bread formulation. On the contrary unbound ferulic acid increased by 48–307% after dough preparation and 138–225% after oven baking with a total increase 273–495%. Similarly, muffin-making process resulted in 26–30% reductions in bound ferulic acid after batter preparation and 4–7% after oven baking with reductions of 34–37% in muffins, while the unbound ferulic acid increased by about 35–105% and 9–29%, respectively, with a total increase 47–116%. The baking process resulted in improved DPPH, ABTS, and ORAC antioxidant activities in breads and muffins despite the initial reductions after dough preparation. In general, baking process resulted in tangible increases in unbound phenolic acids which eventually could improve their bioavailability and bioactivity.
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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) | 0.001 | 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".