The effect of adenosine 5′‐monophosphate (<scp>AMP</scp>) on tenderness, microstructure and chemical–physical index of duck breast meat
Bibliographic record
Abstract
BACKGROUND: Adenosine 5'-monophosphate (AMP) is often used in meat and poultry soups as a flavor enhancer (flavor modifier), or as food additives for specific nutritional purposes. Our previous research as well as evidence from others showed that actomyosin could be dissociated into myosin and actin by AMP in extracted muscle solution. However, there is no report available on the application of AMP to dissociate actomyosin and to improve meat tenderness. The objectives of this study were to evaluate the effect of AMP on duck meat tenderness and other quality traits and to explore the mechanism of the action of AMP on meat tenderness. RESULTS: Duck breast muscle was treated with 0, 10, 20, 30, 40 mmol L(-1) AMP at 5 °C for 10 h and examined for shear force, microstructure, actomyosin dissociation, myofibril fragmentation index (MFI), pH, water content, cooking loss, CIE* color (L*, a*, b*), inosine monophosphate (IMP) and free amino acid (FAA) contents. Results showed that shear force, cooking loss, L* and b* of the muscles significantly decreased after AMP treatment (P < 0.05); actomyosin dissociation, MFI, pH, water content, fiber diameter, sarcomere length, IMP and ammonia significantly increased (P < 0.05); no significant change in a* or other FAA content was observed (P > 0.05), and muscle shrinkage in transverse and longitudinal directions were restrained after AMP treatment. CONCLUSION: The results suggest that AMP could notably improve meat tenderness, and this effect was probably mainly through increasing muscle pH, promoting actomyosin dissociation and disrupting the Z-line; meanwhile, the conversion of AMP to IMP may contribute to the flavor of meat.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".