Antioxidant proteins and peptides to enhance the oxidative stability of meat and meat products: A comprehensive review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Lipid oxidation is among the major flaw-grounding processes in meat and meat-based products that can affect interactions among lipids and proteins, leading to critically undesirable changes. Therefore, it is imperative to control lipid oxidation in meat allied products to enhance consumer acceptability. Moreover, lipid oxidation is somber dilemma visage by the meat processing industry, affects food constituents, leading to detrimental alterations that can impart the deleterious effects on human health upon consumption. Various synthetic (butylated hydroxyanisole (BHA), butylated hydroxytoluene (BHT), and tertiary butylhydroquinone (TBHQ)) and natural antioxidants (vitamin C, vitamin A, tocopherols, especially vitamin E, flavonoids particularly quercetin, proteins, and peptides) as well as preservatives are employed to extend the storability of meat and resultants products; however, great consideration is paid to the utilization of natural antioxidants due to the harmful side effects imparted by synthetic counterparts. Recently, bioactive peptides are claimed to thwart lipid oxidation in meat and other products; in addition, these antioxidant peptides have also been reported to possess substantial health-promoting potential besides controlling oxidation. Therefore, the present review is intended to emphasize the sources, production methods, and applications of antioxidant proteins and peptides to control oxidative degradation in meat products and the potential health benefits of bioactive peptides. Furthermore, the techniques available for the extraction, characterization, and assessment of the antioxidant capability of bioactive peptides are discussed critically in this review.
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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 | 0.001 |
| 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 it