Understanding the impact of sire lean meat yield breeding value on carcass composition, meat quality, nutrient and mineral content of Australian lamb

Meat Science ◽  
2020 ◽  
Vol 170 ◽  
pp. 108236
Author(s):  
Matthew I. Knight ◽  
Kym L. Butler ◽  
Nick P. Linden ◽  
Viv F. Burnett ◽  
Alex J. Ball ◽  
...  
Keyword(s):  
Meat Quality ◽  
Mineral Content ◽  
Carcass Composition ◽  
Breeding Value ◽  
Meat Yield ◽  
Lean Meat ◽  
The Impact

Using Australian Sheep Breeding Values to increase lean meat yield percentage

2010 ◽  
Vol 50 (12) ◽  
pp. 1098 ◽  
Author(s):  
G. E. Gardner ◽  
A. Williams ◽  
J. Siddell ◽  
A. J. Ball ◽  
S. Mortimer ◽  
...  
Keyword(s):  
Carcass Composition ◽  
Production Traits ◽  
Eye Muscle ◽  
Meat Yield ◽  
Sheep Breeding ◽  
Breeding Values ◽  
Lean Meat ◽  
Target Weight ◽  
Australian Sheep ◽  
The Impact

This study describes the impact of Australian Sheep Breeding Values (ASBV) for post-weaning weight (PWWT), C-site fatness (PFAT) and eye muscle depth (PEMD) on lamb carcasses within the Australian Sheep Industry CRC Information Nucleus Flock. These results are taken from the 2007 drop progeny, consisting of ~2000 lambs slaughtered at a target weight of 21.5 kg. These lambs were the progeny of sires selected to ensure genetic diversity across various production traits. As expected, the PWWT ASBV increased weight at slaughter, and hot standard carcass weight. Dressing percentage was markedly improved by increasing PEMD ASBV, thus prime lamb producers will be maintaining an animal of similar weight on farm, but delivering a markedly larger carcass at slaughter. Lean meat yield % (LMY%) was highest in the progeny of sires with low PFAT ASBV, which decreased whole carcass fatness and increased muscularity. PWWT ASBV affected carcass composition but had little impact on LMY%, as the decreased fatness was largely offset by increased bone, with relatively little change in muscle content. Lastly, PEMD ASBV had little impact on whole carcass LMY%, but did appear to cause some level of muscle redistribution to the higher value loin cuts, in turn increasing the value of the carcass lean.

Predicting lean meat yield in beef cattle using ultrasonic muscle depth and width measurements

2003 ◽  
Vol 83 (3) ◽  
pp. 429-434 ◽  
Author(s):  
R. Bergen ◽  
D. H. Crews ◽  
Jr., S. P. Miller ◽  
J. J. McKinnon
Keyword(s):  
Beef Cattle ◽  
Carcass Composition ◽  
Ultrasound Measurement ◽  
Independent Data ◽  
Data Set ◽  
Meat Yield ◽  
Lean Meat ◽  
Ultrasound Measurements ◽  
Width Measurements ◽  
Highly Correlated

The value of live ultrasound longissimus dorsi depth and width measurements as predictors of estimated carcass lean meat yield of steers (CARLEAN-S) and bulls (CARLEAN-B) was studied. In trial 1, equations were developed to predict estimated lean meat yield of steers (n = 116) from carcass weight (Eq. 1) or liveweight (Eq. 2), fat depth and l. dorsi area or liveweight, fat depth and l. dorsi depth × width (Eq. 3). Equation 1 was most precise (RSD = 25.6 g kg-1), followed by Eq. 2 (RSD = 27.8g kg-1) and Eq. 3 (RSD = 30.2g kg-1). Equations 2 and 3 predicted CARLEAN-S with similar accuracy (SEP = 23.8 vs. 24.9 g kg-1, respectively) and were highly correlated with each other (r = 0.89) in an independent data set (n = 118). Repeatability and accuracy of pre-slaughter l. dorsi depth and width measurements were studied in yearling bulls (trial 2; n = 191). When ultrasound measurements were expressed as a percentage of the average ultrasound measurement, repeatabilities of l. dorsi depth (SER = 6.2 to 7.8%) and width (SER = 4.2 to 6.1%) measurements were similar to fat depth and l. dorsi area measurements (SER = 17.9 and 4.5%, respectively). When ultrasound measurements were compared to the corresponding carcass measurements, l. dorsi depth (SEP = 10.3 to 13.9%) and width (SEP = 6.7 to 8.5%) measurements were as accurate as fat depth and l. dorsi area measurements (SEP = 32.9 and 8.4%, respectively). Equations were developed to predict CARLEAN-B of yearling bulls (n = 82) from liveweight, 12th rib ultrasound fat depth and either l. dorsi depth × width measurements (Eqs. 4 and 5) or two l. dorsi depth measurements (Eq. 6). All equations had similar precision (RSD = 19.4 to 19.5 g kg-1) and predicted CARLEAN-B similarly (SEP = 25.0, 24.6 and 26.1g kg-1 for Eqs. 4, 5 and 6, respectively) in an independent data set (n = 109). All equations were highly correlated (r ≥0.97) with an equation using ultrasound fat depth and l. dorsi area in the independent data set. Longissimus muscle depth and width measurements were as valuable as l. dorsi area for predicting carcass composition of yearling beef bulls in the present study. Key words: Ultrasound, beef cattle, carcass traits

Selection indices for terminal sires to improve lean meat production from sheep in the United Kingdom

1987 ◽  
Vol 45 (1) ◽  
pp. 87-96 ◽  
Author(s):  
A. C. Parratt ◽  
G. Simm
Keyword(s):  
Growth Rate ◽  
Carcass Composition ◽  
Breeding Value ◽  
Meat Production ◽  
Lean Meat ◽  
The United Kingdom ◽  
Ct Measurements ◽  
Selection Indices ◽  
Efficiency Of Selection ◽  
Terminal Sire

AbstractSelection indices to improve lean meat production of terminal sire breeds of sheep were derived. An aggregate breeding value which comprised growth rate, killing-out proportion and carcass lean proportion was examined. Selection criteria included growth rate and ultrasonic or X-ray computer tomography (CT) estimates of carcass composition. Correlations betwen the index and the aggregate breeding value were about 0·38 for indices using ultrasonic fat measurements, and about 0·40 for those using CT measurements. Dropping ultrasonic or CT measurements from the indices reduced the correlations with the aggregate breeding value by only about 0·01 and 002 respectively, indicating that selection on growth rate alone under current economic conditions was highly efficient. Changes in economic weights, and genetic parameters had little effect on the efficiency of selection. The total national discounted value of returns from a single round of selection on the indices was expected to be between £6 and £30·5 million, depending on penetration rates of improved stock, the breeding scheme used, and with a time horizon of 20 years.

Current and future issues facing red meat quality in a competitive market and how to manage continuous improvement

2011 ◽  
Vol 51 (1) ◽  
pp. 13 ◽  
Author(s):  
D. W. Pethick ◽  
A. J. Ball ◽  
R. G. Banks ◽  
J. F. Hocquette
Keyword(s):  
Meat Quality ◽  
Nutritive Value ◽  
Cost Effective ◽  
Future Research ◽  
Eating Quality ◽  
Biological Interactions ◽  
Quality Improvements ◽  
Meat Yield ◽  
Lean Meat ◽  
Important Quality

This paper discusses current and future issues facing lamb and beef meat quality and proposes strategies to manage quality improvements into the future. Based on survey data of Australian consumers and whole supply chain profit drivers, it is argued that the three most important quality areas for future research are lean meat yield, eating quality and human nutritive value. These areas have complex biological interactions, both antagonistic and complimentary, which require careful management so as to produce the best outcome for industry and the consumer. It is argued that the best way forward is to undertake collaborative research that encompasses industry production, meat science and genetics simultaneously. The case study of the Australian lamb industry is used as a suggested model for future progression, whereby a large breeding program forms the central focus of numerous research and delivery activities. Another issue raised is the need for strong and cost-effective industry systems that are able to effectively utilise outcomes from genetics, lean meat yield and eating quality to deliver the research results.

Use of live ultrasound, weight and linear measurements to predict carcass composition of young beef bulls

2005 ◽  
Vol 85 (1) ◽  
pp. 23-35 ◽  
Author(s):  
R. Bergen ◽  
S. P. Miller ◽  
I. B. Mandell ◽  
W. M. Robertson
Keyword(s):  
Prediction Models ◽  
Carcass Composition ◽  
Muscle Size ◽  
Yield Prediction ◽  
Longissimus Muscle ◽  
Marbling Score ◽  
Meat Yield ◽  
Lean Meat ◽  
Short Probe ◽  
Beef Bulls

Pre-slaughter ultrasound and whole side dissection data from 47 crossbred bulls were used to assess (1) the relative value of six previously published equations based on live animal measurements, (2) the value of alternative pre-slaughter measurements, and (3) the value of alternative ultrasound probes as predictors of whole side lean meat yield. Analysis of absolute bias-corrected residuals indicated that all six previously published equations predicted whole side lean meat yield with similar accuracy (P = 0.62), but analysis of absolute rank residuals indicated that an equation originally based on carcass measurements tended (P = 0.17) to rank bulls less precisely than five ultrasound-based equations. Breed composition, age, liveweight, hip width, heart girth, and round muscle depths did not contribute to new lean meat yield prediction equations (P > 0.10), but height, 12th/13th rib body wall, rump fat, and gluteus medius muscle depths and marbling score did (P < 0.10). However, examination of absolute residuals and absolute rank residuals indicated that accuracy (P = 0.55) and precision (P = 0.64) did not improve significantly compared to equations based only on height, rib fat and longissimus muscle size. Similarly, analysis of absolute residuals and absolute rank residuals indicated that fat and longissimus muscle depth measurements collected with a short probe predicted whole side lean meat yield as accurately and precisely as measurements collected with a long probe. Results indicated that (1) equations based on live measurements may provide more precise predictions of lean meat yield than equations derived from carcass measurements, (2) supplementing ultrasonic rib fat and longissimus muscle measurements with additional ultrasound measurements did not improve the accuracy or precision of lean meat yield prediction, and (3) lean meat yield of yearling bulls can be accurately predicted using fat and longissimus muscle depth measurements collected with a short probe. Key words: Ultrasound, beef bulls, carcass composition, prediction models

scholarly journals Microbiability of meat quality and carcass composition traits in swine

2020 ◽  
Author(s):  
Piush Khanal ◽  
Christian Maltecca ◽  
Clint Schwab ◽  
Justin Fix ◽  
Francesco Tiezzi
Keyword(s):  
Meat Quality ◽  
Gut Microbiome ◽  
Complex Traits ◽  
Carcass Composition ◽  
Intestinal Microbiome ◽  
Quality Traits ◽  
Microbial Composition ◽  
Meat Quality Traits ◽  
Genomic Heritability ◽  
The Impact

Abstract BackgroundSwine gut microbiome constitutes a portion of the whole genome and has potential to affect different phenotypes. More recently, research is more directed towards association of gut microbiome and different traits in swine. However, the contribution of microbial composition to the phenotypic variation of meat quality and carcass composition traits in pigs has not been explored yet. The objectives of this study are to estimate the microbiabilities for different meat quality and carcass composition traits; to investigate the impact of intestinal microbiome on heritability estimates; to estimate the correlation between microbial diversity and meat quality and carcass composition traits; and to estimate the microbial correlation between the meat quality and carcass composition traits in a commercial swine population.ResultsThe contribution of the microbiome to carcass composition and meat quality traits was prominent although it varied over time, increasing from weaning to off test for most traits. Microbiability estimates of carcass composition traits were greater than that of meat quality traits. Among all of the traits analyzed, belly weight had higher microbiability estimate (0.29 ± 0.04). Adding microbiome information did not affect the estimates of genomic heritability of meat quality traits but affected the estimates of carcass composition traits. Fat depth had greater decrease (10%) in genomic heritability. High microbial correlations were found among several traits. This suggested that genomic correlation was partially contributed by genetic similarity of microbiome composition.ConclusionsResults indicate that better understanding of microbial composition could aid the improvement of complex traits, particularly the carcass composition traits in swine by inclusion of microbiome information in the genetic evaluation process.

scholarly journals Effect of MSTN Mutation on Growth and Carcass Performance in Duroc × Meishan Hybrid Population

Animals ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 932
Author(s):  
Weijian Li ◽  
Rongyang Li ◽  
Yinghui Wei ◽  
Xueqing Meng ◽  
Binbin Wang ◽  
...  
Keyword(s):  
Average Daily Gain ◽  
Carcass Composition ◽  
Hybrid Population ◽  
Market Demand ◽  
Muscle Area ◽  
Meat Yield ◽  
Female Ratio ◽  
Lean Meat ◽  
Carcass Performance ◽  
Crossbred Pigs

The Meishan pig is a traditional Chinese native breed, known for its excellent reproduction performance that is widely used in commercial pig production through two-way or three-way crossbreeding systems. However, the lean meat yield of Meishan crossbred pigs is still very low and cannot meet the market demand. To evaluate the lean meat yield of Meishan crossbred pigs, six wild-type Meishan sows were artificially inseminated by using the MSTN+/− Duroc boar semen in this experiment. Some reproductive performance-related traits of Meishan sows were recorded to ensure that semen from MSTN knockout Duroc boar did not affect offspring production, including total births, live births, sex, and litter weight. In total, 73 piglets were obtained and 63 were alive. Male to female ratio was close to 1: 1. because of factors such as disease, only 43 pigs were utilized, including 28 MSTN mutant pigs (MSTN+/−) and 15 MSTN homozygous pigs (MSTN+/+). We compared the growth performance and carcass performance of these full or half-sib populations and found that there were no differences between MSTN+/− and MSTN+/+ genotypes for live animal measures including average daily gain (ADG), body dimensions, or ultrasonic measurement of fat thickness when pigs were harvested after 120 days of feeding. Conversely, the MSTN+/− pigs had higher dressing percentage and lean meat percentage, lower level of carcass fat, larger longissimus muscle area, less percentage of skin and skeleton, thinner average backfat thickness, and lower intramuscular fat (IMF) content than MSTN+/+ pigs. In conclusion, the production of MSTN+/− mutant progeny from Meishan females resulted in improved carcass composition, providing a feasible solution to improve the lean meat yield of Chinese local fat-type pig breeds.

scholarly journals Microbiability of meat quality and carcass composition traits in swine

2019 ◽  
Author(s):  
Piush Khanal ◽  
Christian Maltecca ◽  
Clint Schwab ◽  
Justin Fix ◽  
Francesco Tiezzi
Keyword(s):  
Meat Quality ◽  
Fixed Effects ◽  
Carcass Composition ◽  
Quality Traits ◽  
Microbiome Composition ◽  
Meat Quality Traits ◽  
Genomic Heritability ◽  
Genomic Correlation ◽  
Weight Decrease ◽  
The Impact

AbstractThe impact of gut microbiome composition was investigated at different stages of production (Wean, Mid-test, and Off-test) on meat quality and carcass composition traits of 1,123 three-way-crossbred pigs. Data were analyzed using linear mixed models which included the fixed effects of dam line, contemporary group and gender as well as the random effects of pen, animal and microbiome information at different stages. The contribution of the microbiome to all traits was prominent although it varied over time, increasing from weaning to Off-test for most traits. Microbiability estimates of carcass composition traits were greater compared to meat quality traits. Adding microbiome information did not affect the estimates of genomic heritability of meat quality traits but affected the estimates of carcass composition traits. High microbial correlations were found among different traits, particularly with traits related to fat deposition with decrease in genomic correlation up to 20% for loin weight and belly weight. Decrease in genomic heritabilities and genomic correlations with the inclusion of microbiome information suggested that genomic correlation was partially contributed by genetic similarity of microbiome composition.

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