Beef-on-dairy: current and potential meat quality of dairy-based beef production with culled Holstein cows and Danish Blue × Holstein crossbred calves
Bibliographic record
Abstract
This study characterizes rosé veal from 412 Danish Blue × Holstein heifer and bull calves and beef from 183 highly marbled culled Holstein dairy cows. Furthermore, it investigates the potential for breeding higher meat quality in dairy crossbreeds via genetic parameter estimation. Carcasses were split between the 5th and 6th thoracic vertebra and the meat quality of M. longissimus thoracis was evaluated for pH, color, cooking loss, Warner-Bratzler shear force (WBSF), and chemical intramuscular fat concentration (IMF%). Genetic parameters were estimated using an animal model. The crossbred bull calves outperformed heifers in carcass characteristics, while heifers were superior in redness, cooking loss, WBSF and IMF%. Heritability was significant for WBSF, cooking loss, and IMF%, indicating that meat quality can be improved through selective breeding. The meat quality of highly marbled Holstein cows did not vary across parities, highlighting them as an under-utilized potential source of high-quality beef from a beef-on-dairy system.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".