QTL for meat tenderness in the M. longissimus lumborum of cattle
Bibliographic record
Abstract
Meat tenderness has been difficult to improve using standard genetic selection. Marker assisted selection holds great promise if markers for meat tenderness can be identified. Here, we report quantitative trait loci (QTL) for beef tenderness identified in 598 animals of three Charolais-Brahman x Belmont Red pedigrees after screening the whole genome using 183 DNA markers. In addition to the usual Warner-Bratzler peak force measurements, tenderness was also measured using compression, adhesion and pressure-heat-treated peak force. Three QTL for meat tenderness in the M. longissimus lumborum muscle were found, two of which have not been reported before. One is located in the HEL9-CSSM47 interval on bovine chromosome 8 with a LOD of 3.1 and an effect of 1.02 phenotypic standard deviations for tensile strength of cooked muscle as measured by adhesion. A second QTL is located near CSRM60 on bovine chromosome 10 with a LOD of 2.4 and an effect of 0.48 phenotypic standard deviations for compression. The third QTL is in a region of bovine chromosome 7 that has previously been reported to have a QTL affecting peak force. This region also shows effects on compression and a combined tenderness index. These QTL are all for the myofibrillar component of meat tenderness. No QTL were found for pressure-treated peak force, which is an estimate of the connective tissue component muscle of meat tenderness.
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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 | 0.000 |
| 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 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".