Maillard reaction products derived from food protein-derived peptides: insights into flavor and bioactivity
Bibliographic record
Abstract
Food protein-derived peptides serve as food ingredients that can influence flavor and bioactivity of foods. The Maillard reaction plays a crucial role in food processing and storage, and generates a wide range of Maillard reaction products (MRPs) that contribute to flavor and bioactivity of foods. Even though the reactions between proteins and carbohydrates have been extensively investigated, the modifications of food protein-derived peptides and the subsequent impacts on flavor and bioactivity of foods have not been fully elucidated. In this review, the flavor and bioactive properties of food-derived peptides are reviewed. The formation mechanisms with respect to MRPs generated from food protein-derived peptides have been discussed. The state-of-the-art studies on impacts of the Maillard reaction on flavor and bioactivity of food protein-derived peptides are also discussed. In addition, some potential negative effects of MRPs are described.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".