Some definitions of feed efficiency such as residual energy intake (REI) and residual gain (RG) may not truly reflect production efficiency. The energy sinks used in the derivation of the traits include metabolic live-weight; producers finishing cattle for slaughter are, however, paid on the basis of carcass weight, as opposed to live-weight. The objective of the present study was to explore alternative definitions of REI and RG which are more reflective of production efficiency, and quantify their relationship with performance, ultrasound, and carcass traits across multiple breeds and sexes of cattle. Feed intake and live-weight records were available on 5,172 growing animals, 2,187 of which also had information relating to carcass traits; all animals were fed a concentrate-based diet representative of a feedlot diet. Animal linear mixed models were used to estimate (co)variance components. Heritability estimates for all derived REI traits varied from 0.36 (REICWF; REI using carcass weight and carcass fat as energy sinks) to 0.50 (traditional REI derived with the energy sinks of both live-weight and ADG). The heritability for the RG traits varied from 0.24 to 0.34. Phenotypic correlations among all definitions of the REI traits ranged from 0.90 (REI with REICWF) to 0.99 (traditional REI with REI using metabolic preslaughter live-weight and ADG). All were different (P < 0.001) from one suggesting reranking of animals when using different definitions of REI to identify efficient cattle. The derived RG traits were either weakly or not correlated (P > 0.05) with the ultrasound and carcass traits. Genetic correlations between the REI traits with carcass weight, dressing difference (i.e., live-weight immediately preslaughter minus carcass weight) and dressing percentage (i.e., carcass weight divided by live-weight immediately preslaughter) implies that selection on any of the REI traits will increase carcass weight, lower the dressing difference and increase dressing percentage. Selection on REICW (REI using carcass weight as an energy sink), as opposed to traditional REI, should increase the carcass weight 2.2 times slower but reduce the dressing difference 4.3 times faster. While traditionally defined REI is informative from a research perspective, the ability to convert energy into live-weight gain does not necessarily equate to carcass gain, and as such, traits such as REICW and REICWF provide a better description of production efficiency for feedlot cattle.

Comparison of alternative dairy (cross-)breeding programs requires full appraisals of all revenues and costs, including beef merit. Few studies exist on carcass characteristics of crossbred dairy progeny originating from dairy herds as well as their dams. The objective of the present study was to quantify, using a national database, the carcass characteristics of young animals and cows differing in their fraction of Jersey. The data set consisted of 117,593 young animals and 42,799 cows. The associations between a combination of sire and dam breed proportion (just animal breed proportion when the dependent variable was on cows) with age at slaughter (just for young animals), carcass weight, conformation, fat score, price per kilogram, and total carcass value were estimated using mixed models that accounted for covariances among herdmates of the same sex slaughtered in close proximity in time; we also accounted for age at slaughter in young animals (which was substituted with carcass weight and carcass fat score when the dependent variable was age at slaughter), animal sex, parity of the cow or dam (where relevant), and temporal effects represented by a year-by-month 2-way interaction. For young animals, the heaviest of the dairy carcasses were from the mating of a Holstein-Friesian dam and a Holstein-Friesian sire (323.34 kg), whereas the lightest carcasses were from the mating of a purebred Jersey dam to a purebred Jersey sire which were 46.31 kg lighter (standard error of the difference = 1.21 kg). The young animal carcass weight of an F 1 Holstein-Friesian × Jersey cross was 20.4 to 27.0 kg less than that of a purebred Holstein-Friesian animal. The carcass conformation of a Holstein-Friesian young animal was 26% superior to that of a purebred Jersey, translating to a difference of 0.78 conformation units on a scale of 1 to 15. Purebred Holstein-Friesians produced carcasses with less fat than their purebred Jersey counterparts. The difference in carcass price per kilogram among the alternative sire-dam breed combinations investigated was minimal, although large differences existed among the different breed types for overall carcass value; the carcass value of a Holstein-Friesian animal was 20% greater than that of a Jersey animal. Purebred Jersey animals required, on average, 21 d longer to reach a given carcass weight and fat score relative to a purebred Holstein-Friesian. The difference in age at slaughter between a purebred Holstein-Friesian animal and the mating between a Holstein-Friesian sire with a Jersey dam, and vice versa, was between 7.0 and 8.9 d. A 75.8-kg difference in carcass weight existed between the carcass of a purebred Jersey cow and that of a Holstein-Friesian cow; a 50% Holstein-Friesian-50% Jersey cow had a carcass 42.0 kg lighter than that of a purebred Holstein-Friesian cow. Carcass conformation was superior in purebred Holstein-Friesian compared with purebred Jersey cows. Results from this study represent useful input parameters to populate simulation models of alternative breeding pro...

The objective of this study was to develop, using alternative algorithms, low-density SNP genotyping panels (384 to 12,000 SNP), which can be accurately imputed to higher-density panels across independent cattle populations. Single nucleotide polymorphisms were selected based on genomic characteristics (i.e., linkage disequilibrium [LD], minor allele frequency [MAF], and genomic distance) in a population of 1,267 Holstein-Friesian animals genotyped on the Illumina Bovine50 Beadchip (54,001 SNP). Single nucleotide polymorphism selection methods included 1) random; 2) equidistant location; 3) combination of SNP MAF and LD structure while maintaining relatively equal genomic distance between adjacent SNP; 4) a combination of high MAF, genomic distance between selected and candidate SNP, and correlation between genotypes of selected and candidate SNP; and 5) a machine learning algorithm. The panels were validated separately in 1) a population of 750 Holstein-Friesian animals with masked genotypes to reflect the lower-density SNP densities under investigation (1,249 animals with complete genotypes included in reference population) and 2) a population of 359 Limousin and Charolais cattle with high (777,962 SNP)-density genotypes (1,918 animals with complete genotypes included in the reference population). Irrespective of SNP selection method, imputation accuracy in both populations improved at a diminishing rate as the number of SNP included in the lower-density genotype panel increased. Additionally, the variability in mean imputation accuracy per individual decreased as the panel density increased. The SNP selection method had a major impact on the mean allele concordance rate, although its impact diminished as the panel density increased. Imputation accuracy for SNP selected using a combination of high SNP MAF, LD structure, and relatively equal genomic distance between SNP outperformed all other selection methods in densities < 12,000 SNP. Using this method of SNP selection, the correlation between the imputed and actual genotypes for the 3,000 SNP panel was 0.90 and 0.96 when applied to the beef and dairy populations, respectively; the respective correlations for the 6,000 SNP panel were 0.95 and 0.98. It is necessary to include between 3,000 and 6,000 SNP in a low-density panel to achieve adequate imputation accuracy to either medium density (approximately 50,000 SNP in the dairy population) or high density (approximately 700,000 SNP in the beef population) across diverse and independent populations.

The ability to alter the morphology of cattle towards greater yields of higher value primal cuts has the potential to increase the value of animals at slaughter. Using weight records of 14 primal cuts from 31,827 cattle, the objective of the present study was to quantify the extent of genetic variability in these primal cuts; also of interest was the degree of genetic variability in the primal cuts adjusted to a common carcass weight. Variance components were estimated for each primal cut using animal linear mixed models. The coefficient of genetic variation in the different primal cuts ranged from 0.05 (bavette) to 0.10 (eye of round) with a mean coefficient of genetic variation of 0.07. When phenotypically adjusted to a common carcass weight, the coefficient of genetic variation of the primal cuts was lesser ranging from 0.02 to 0.07 with a mean of 0.04. The heritability of the 14 primal cuts ranged from 0.14 (bavette) to 0.75 (topside) with a mean heritability across all cuts of 0.48; the heritability estimates reduced, and ranged from 0.12 (bavette) to 0.56 (topside), when differences in carcass weight were accounted for in the statistical model. Genetic correlations between each primal cut and carcass weight were all ≥0.77; genetic correlations between each primal cut and carcass conformation score were, on average, 0.59 but when adjusted to a common carcass weight, the correlations weakened to, on average, 0.27. The genetic correlations among all 14 primal cut weights was, on average, strong (mean correlation of 0.72 with all correlations being ≥0.37); when adjusted to a common carcass weight, the mean of the genetic correlations among all primal cuts was 0.10. The ability of estimated breeding values for a selection of primal cuts to stratify animals phenotypically on the respective cut weight was demonstrated; the weight of the rump, striploin, and fillet of animals estimated to be in the top 25% genetically for the respective cut, were 10 to 24%, 12 to 24%, and 7 to 17% heavier than the weight of cuts from animals predicted to be in the worst 25% genetically for that cut. Significant exploitable genetic variability in primal carcass cuts was clearly evident even when adjusted to a common carcass weight. The high heritability of many of the primal cuts infers that large datasets are not actually required to achieve high accuracy of selection once the structure of the data and the number of progeny per sire is adequate.

Abstract Beef carcasses in Europe are classified on measures of carcass weight, conformation, and fat cover. These measurements provide the basis for payment to producers, with financial penalties for carcasses that do not conform to desirable characteristics. The objective of the present study was to identify animal-level factors associated with the achievement of a desirable carcass weight, conformation score, fat score, and age at harvest, as stipulated by Irish beef processors in accordance with the EUROP carcass classification system. The stipulated specifications were a EUROP conformation score ≥O=, a carcass weight between 270 and 380 kg, a EUROP fat score between 2+ and 4=, and an age at harvest ≤ 30 mo. In the present study, 59% of cattle failed to achieve at least one of these desired specifications. The logit of the probability of achieving the desired specifications was estimated using multivariable logistic regression and carcass data from 4,717,989 cattle finished and harvested in Ireland between the years 2003 and 2017. In comparison to beef-origin carcasses and after accounting for breed differences, the likelihood of dairy-origin carcasses achieving the desired age, conformation, fat, and weight specifications was 0.97, 0.88, 1.14, and 1.05, respectively. In comparison to heifer carcasses, the odds ratio (OR) of bull and steer carcasses simultaneously achieving all of the desired specifications (i.e. the overall specification) was 0.35 and 0.95, respectively. Additionally, after accounting for breed differences, heifers from the dairy herd were half as likely as heifers from the beef herd to achieve the overall specification, whereas the odds of dairy-origin bulls (OR = 3.46) and steers (OR = 2.41) achieving the overall specification was greater than that of their respective beef-origin counterparts. Finally, cattle with a greater breed proportion of Angus were most likely to achieve the overall specification. Results from the present study could provide a deeper understanding as to why animals fail to achieve desirable carcass specifications and could be implemented into the management decisions made on farm to ensure that the supply of beef carcasses that achieve the desired metrics is maximized.