Genetic and Phenotypic Analysis of Meat Quality Traits in Buffalo Beef and Correlations to Carcass Composition
Bibliographic record
Abstract
Abstract: Meat quality traits in buffalo beef were examined and their genetic parameters and genetic correlations to carcass composition were estimated. Dissection was performed on 40 buffalo beef carcasses and all traits recorded for each animal, as well as the weight on muscle lungissimus dorsi (LD). The temperature and pH were recorded at 1 and 48h post-slaughter. Intramuscular fat, protein, dry matter, meat colour (redness, a*, yellowness b* and lightness L*) were recorded. Hereditability estimates ranged from 0.12 and 0.99 for dissection traits and 0.61 and 0.68 for meat quality traits, which was significant for all traits except for ultimate pH and b*. Genetic correlation with L* were negative for a* and high and positive for b*. Intramuscular fat was moderate to highly genetically correlated to the a*, b* and half hot carcass weight. The not significant genetic correlation found between several of the meat quality traits, and between meat quality traits and carcasses composition traits, suggests that the meat quality traits analyzed should be implemented into breeding programme with care since their full effect on the other traits under selection cannot be accurately estimated. For more accurate estimates, further studies that especially include a large number of records for colour meat measures are needed.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".