Predicting the yield and composition of mature cow carcasses.

Won

Asian Australas. J. Anim. Sci

et al. 2015

The prediction of carcass composition in Hanwoo steers is very important for value-based marketing, and the improvement of prediction accuracy and precision can be achieved through the analyses of independent variables using a prediction equation with a sufficient dataset. The present study was conducted to develop a prediction equation for Hanwoo carcass composition for which data was collected from 7,907 Hanwoo steers raised at a private farm in Gangwon Province, South Korea, and slaughtered in the period between January 2009 and September 2014. Carcass traits such as carcass weight (CWT), back fat thickness (BFT), eye-muscle area (EMA), and marbling score (MAR) were used as independent variables for the development of a prediction equation for carcass composition, such as retail cut weight and percentage (RC, and %RC, respectively), trimmed fat weight and percentage (FAT, and %FAT, respectively), and separated bone weight and percentage (BONE, and %BONE), and its feasibility for practical use was evaluated using the estimated retail yield percentage (ELP) currently used in Korea. The equations were functions of all the variables, and the significance was estimated via stepwise regression analyses. Further, the model equations were verified by means of the residual standard deviation and the coefficient of determination (R2) between the predicted and observed values. As the results of stepwise analyses, CWT was the most important single variable in the equation for RC and FAT, and BFT was the most important variable for the equation of %RC and %FAT. The precision and accuracy of three variable equation consisting CWT, BFT, and EMA were very similar to those of four variable equation that included all for independent variables (CWT, BFT, EMA, and MAR) in RC and FAT, while the three variable equations provided a more accurate prediction for %RC. Consequently, the three-variable equation might be more appropriate for practical use than the four-variable equation based on its easy and cost-effective measurement. However, a relatively high average difference for the ELP in absolute value implies a revision of the official equation may be required, although the current official equation for predicting RC with three variables is still valid.

Section: Discussioncontrasting

confidence: 61%

Prediction of Carcass Composition Using Carcass Grading Traits in Hanwoo Steers

Won

Asian Australas. J. Anim. Sci

et al. 2015

Journal of Animal Science

“…After blooming, the carcass data were collected, including HCW, ribeye area (REA), 12th-rib fat thickness over the ribeye (FOE), preliminary yield grade (PYG), lean maturity (LMAT), bone maturity (BM), subjective lean color (LC), subjective fat color (FC), marbling score (MARB), and muscle score. Percent lean was calculated from carcass characteristics for all groups, and carcass composition was calculated by the ribbed carcass equations of Johnson and Rogers (1997).…”

Section: Carcass Selectionmentioning

confidence: 99%

Benchmarking carcass characteristics and muscles from commercially identified beef and dairy cull cow carcasses for Warner-Bratzler shear force and sensory attributes1

Stelzleni

Patten

Johnson

et al. 2007

Calkins, Chris R.; and Gwartney, B. L., "Benchmarking carcass characteristics and muscles from commercially identified beef and dairy cull cow carcasses for Warner-Bratzler shear force and sensory attributes" (2006 ABSTRACT: The objective of this study was to benchmark carcasses and muscles from commercially identified fed (animals that were perceived to have been fed an increased plane of nutrition before slaughter) and nonfed cull beef and dairy cows and A-maturity, USDA Select steers, so that the muscles could be identified from cull cow carcasses that may be used to fill a void of intermediately priced beef steaks.

Journal of Animal Science

Beef production from cull dairy cows: a review from culling to consumption

Moreira

Rosa

Schaefer

2021

Although more than 3 million head of dairy cows enter the food supply chain in the U.S. every year, research on this topic remains limited and scarce. Meat production from dairy cows is a significant component of beef production, accounting for almost 10% of U.S. commercial beef production. Thus, the purpose of this review is to demonstrate the importance of dairy cows as a beef source, and to provide an overview on topics from farm to meat product – culling, marketing, transportation, welfare, body composition and its relationship with lactation particularities, carcass characteristics, meat quality, and traceability. Current scientific evidence has shown that culling a dairy cow at an appropriate time has beneficial effects on cow welfare and, consequently, cow value. During marketing the dairy cow is visually evaluated for health and factors associated with its expected carcass value; thus, marketing a well-conditioned cow will ensure that the animal is fit for transportation and provides high carcass yield. However, limitations such as low body condition score, lameness or mobility problems, and visual defects remain persistent. Even though beef harvest plants accommodate cows in all body composition states, the current carcass grade system does not reflect the mature cow industry needs. Therefore, improvement of the grading system could maximize carcass utilization and increase cow carcass value by recognizing subprimal cuts that could be merchandised as whole muscle cuts. Lastly, implementation of a traceability system would unify information from the farm to harvest assisting the industry in making further advancements.