Color stability and antioxidant capacity of yak meat as affected by feeding with pasture or grain
Bibliographic record
Abstract
Chen, C., Han, L., Yu, Q.-L. and Li, R.-R. 2015. Color stability and antioxidant capacity of yak meat as affected by feeding with pasture or grain. Can. J. Anim. Sci. 95: 189–195. The objective of the present study was to analyze the effect of pasture or grain on color stability and antioxidant capacity of M. longissimus lumborum (LL) from pasture-fed (PF) or grain-fed (GF) yaks. The color stability and metmyoglobin percentage (MetMb%) were determined during 9 d of aerobic refrigerated storage. The antioxidant capacity was estimated by the total phenolics content, Trolox equivalent antioxidant capacity (TEAC), and ferric reducing antioxidant power (FRAP). Compared with the GF group, the LL from the PF group showed significantly (P<0.05) higher redness (a* values), with lower decline rate in a* values (P<0.05) over 1 to 7 d of refrigerated storage. The LL from the PF group had a significantly (P<0.05) lower metmyoglobin accumulation rate. At the end of storage, the muscle's MetMb% of the PF and GF group were 46.33 and 56.66%, respectively. The PF group showed significantly higher total phenolics content (+23.94%; P<0.05) in muscles, resulting in greater TEAC and FRAP, which were 24.81 and 3.99% higher than the GF group (P<0.05), respectively. In conclusion, the pasture enhanced antioxidant capacity of yak meat and contributed to improve the meat color stability.
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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 | 0.001 |
| 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".