The correlation between Longissimus thoracis muscle ageing extent, growth and carcass traits in Simmental bulls: preliminary results
Bibliographic record
Abstract
Submitted 2020-07-24 | Accepted 2020-09-16 | Available 2020-12-01 https://doi.org/10.15414/afz.2020.23.mi-fpap.282-289 A common practice to improve meat quality is aging under controlled conditions, which results in improved tenderness, a key factor in the consumer acceptance of beef meat. Among other traits, the tenderness and the effect of ageing are also genetically determined. Therefore, a trial was performed to assess the effect of ageing in the progeny of young bulls included in the routine breeding program for Simmental breed in Slovenia. In the trial, 127 young bulls were included, and the shear force of grilled Longissimus thoracis muscle was measured fresh and after three weeks of ageing. There was a significant difference between the fresh and aged muscle in shear force, but growth and other carcass traits did not affect it as it was expected. We assume that after enlarging the number of animals, the data will be usable to be included in the genetic evaluation of the breeding program for Simmental breed in Slovenia. Keywords: Longissimus thoracis, beef, ageing, shear force References Carvalho, M. E. et al. (2014). Heat shock and structural proteins associated with meat tenderness in Nellore beef cattle, a Bos indicus breed. Meat Science, 96, 1318-1324. https://doi.org/10.1016/j.meatsci.2013.11.014 Dikeman, M. and Devine, C. (2014). Encyclopedia of Meat Sciences. Academic Press. Dikeman, M. E. et al. (2005). Phenotypic ranges and relationships among carcass and meat palatability traits for fourteen cattle breeds, and heritabilities and expected progeny differences for Warner-Bratzler shear force in three beef cattle breeds. Journal of Animal Science, 83, 2461-2467. https://doi.org/10.2527/2005.83102461x Florek, M. et al. (2007). Changes of physicochemical properties of bullocks and heifers meat during 14 days of ageing under vacuum. Polish Journal of Food and Nutrition Sciences, 57(3), 281–287. Hanzelková, Š. et al. (2011). The effect of breed, sex and aging time on tenderness of beef meat. Acta Veterinaria Brno, 80, 191-196. https://doi.org/10.2754/avb201180020191 Harper, G. S. (1999). Trends in skeletal muscle biology and the understanding of toughness in beef. Australian Journal of Agricultural Research, 50, 1105-1129. https://doi.org/10.1071/AR98191 Holloway, J. W. and Wu, J. (2019). Tenderness Intrinsic Character. In: Red Meat Science and Production. Springer, Singapore. https://doi.org/10.1007/978-981-13-7860-7_5 Koohmaraie, M. et al. (2002). Meat tenderness and muscle growth: Is there any relationship? Meat Science, 62, 345-352. https://doi.org/10.1016/S0309-1740(02)00127-4 Lawrence, T. E. et al. (2001). Evaluation of electric belt grill, forced-air convection oven, and electric broiler cookery methods for beef tenderness research. Meat Science, 58(3), 239–246. https://doi.org/10.1016/S0309-1740(00)00159-5 Miller, M. F. et al. (1995). Retail consumer acceptance of beef tenderized with calcium chloride. Journal of Animal Science, 73, 2308-2314. https://doi.org/10.2527/1995.7382308x Purslow, P. P. (2005). Intramuscular connective tissue and its role in meat quality. Meat Science, 70, 435-447. https://doi.org/10.1016/j.meatsci.2004.06.028 Sazili, A. Q. et al. (2004). The effect of altered growth rates on the calpain proteolytic system and meat tenderness in cattle. Meat Science, 66, 195-201. https://doi.org/10.1016/S0309-1740(03)00091-3 Shackelford, S. D., Koohmaraie, M. and Wheeler, T. L. (1995). Effects of slaughter age on meat tenderness and USDA carcass maturity scores of beef females. Journal of Animal Science, 73, 3304-3309. https://doi.org/10.2527/1995.73113304x Splan, R. K. et al. (2002). Estimates of parameters between direct and maternal genetic effects for weaning weight and direct genetic effects for carcass traits in crossbred cattle. Journal of Animal Science, 80(12), 3107-3111. https://doi.org/10.2527/2002.80123107x Wall, K. R. et al. (2019). Grilling temperature effects on tenderness, juiciness, flavor and volatile aroma compounds of aged ribeye, strip loin, and top sirloin steaks. Meat Science, 150, 141–148. https://doi.org/10.1016/j.meatsci.2018.11.009 Wulf, D. M. et al. (1996). Genetic influences on beef Longissimus palatability in Charolais- and Limousin-sired steers and heifers. Journal of Animal Science, 74, 2394-2405. https://doi.org/10.2527/1996.74102394x Yancey, J. W. S., Wharton, M. D. and Apple, J. K. (2011). Cookery method and end-point temperature can affect the Warner-Bratzler shear force, cooking loss, and internal cooked color of beef longissimus steaks. Meat Science, 88, 1–7. https://doi.org/10.1016/j.meatsci.2010.11.020 Zwambag, A. et al. (2013). Heritability of beef tenderness at different aging times and across breed comparisons. Canadian Journal of Animal Science, 93, 307312. https://doi.org/10.4141/CJAS2012-100
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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 | 0.000 |
| 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) | 0.002 | 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".