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Introduction: The ability to accurately predict breed composition using genomic information has many potential uses including increasing the accuracy of genetic evaluations, optimising mating plans and as a parameter for genotype quality control. The objective of the present study was to use a database of genotyped purebred and crossbred cattle to compare breed composition predictions using a freely available software, Admixture, with those from a single nucleotide polymorphism Best Linear Unbiased Prediction (SNP-BLUP) approach; a supplementary objective was to determine the accuracy and general robustness of low-density genotype panels for predicting breed composition. Methods: All animals had genotype information on 49,213 autosomal single nucleotide polymorphism (SNPs). Thirteen breeds were included in the analysis and 500 purebred animals per breed were used to establish the breed training populations. Accuracy of breed composition prediction was determined using a separate validation population of 3,146 verified purebred and 4,330 two and threeway crossbred cattle. Results: When all 49,213 autosomal SNPs were used for breed prediction, a minimal absolute mean difference of 0.04 between Admixture vs. SNP-BLUP breed predictions was evident. For crossbreds, the average absolute difference in breed prediction estimates generated using SNP-BLUP and Admixture was 0.068 with a root mean square error of 0.08. Breed predictions from lowdensity SNP panels were generated using both SNP-BLUP and Admixture and compared to breed prediction estimates using all 49,213 SNPs (representing the gold standard). Breed composition estimates of crossbreds required more SNPs than predicting the breed composition of purebreds. SNP-BLUP required ≥3,000 SNPs to predict crossbred breed composition, but only 2,000 SNPs were required to predict purebred breed status. The absolute mean (standard deviation) difference across all panels <2,000 SNPs was 0.091 (0.054) and 0.315 (0.316) when predicting the breed composition of all animals using Admixture and SNP-BLUP, respectively compared to the gold standard prediction. Discussion: Nevertheless, a negligible absolute mean (standard deviation) difference of 0.009 (0.123) in breed prediction existed between SNP-BLUP and Admixture once ≥3,000 SNPs were considered, indicating that the prediction of breed composition could be readily integrated into SNP-BLUP pipelines used for genomic evaluations thereby avoiding the necessity for a stand-alone software. [ABSTRACT FROM AUTHOR]

The objective of this study was to estimate genetic parameters for the weights of different wholesale cuts, using an experimental and a commercial data set. The experimental and commercial data sets included 413 and 635 crossbred Belgian Blue, Charolais, Limousin, Angus, Holstein, and Simmental animals, respectively. Univariate analyses using a mixed linear animal model with relationships were undertaken to estimate the heritability of cold carcass weight, carcass conformation and fat, and the cut weights, whereas a series of bivariate analyses was used to estimate the phenotypic and genetic correlations between carcass weight, carcass conformation, carcass fat, and the major primal cuts. Heritability estimates for cold carcass weight in both data sets were moderate (>0.48), whereas heritability estimates for carcass conformation and fat grading were greater in the commercial data set (>0.63) than in the experimental study (>0.33). Across both data sets, heritability estimates for wholesale cut weight in the forequarter varied from 0.03 to 0.79, whereas heritability estimates of carcass cut weight in the hindquarter varied from 0.14 to 0.86. Heritability estimates for cut weights expressed as a proportion of the entire carcass weight varied from 0.04 to 0.91. Genetic correlations were strong among the different carcass cut weights within the experimental and the commercial studies. Genetic correlations between the weights of selected carcass cuts and carcass weight were moderate to high (minimum 0.45; maximum 0.88) in both data sets. Positive genetic correlations were observed in the commercial data set between the different wholesale cut weights and carcass conformation, whereas these were positive and negative in the experimental data set. Selection for increased carcass weight will, on average, increase the weight of each cut. However, the genetic correlations were less than unity, suggesting a benefit of more direct selection on high value cuts. Key words: beef, carcass, genetic, heritability, primal, wholesale doi: 10.2527/jas.2008-1510

Lamb live weight is one of the key drivers of profitability on sheep farms. Previous studies in Ireland have estimated genetic parameters for live weight and carcass composition traits using a multi-breed population rather than on an individual breed basis. The objective of the present study was to undertake genetic analyses of three lamb live weight and two carcass composition traits pertaining to purebred Texel, Suffolk and Charollais lambs born in the Republic of Ireland between 2010 and 2017, inclusive. Traits (with lamb age range in parenthesis) considered in the analyses were: pre-weaning weight (20 to 65 days), weaning weight (66 to 120 days), post-weaning weight (121 to 180 days), muscle depth (121 to 180 days) and fat depth (121 to 180 days). After data edits, 137 402 records from 50 372 lambs across 416 flocks were analysed. Variance components were derived using animal linear mixed models separately for each breed. Fixed effects included for all traits were contemporary group, age at first lambing of the dam, parity of the dam, a gender by age of the lamb interaction and a birth type by rearing type of the lamb interaction. Random effects investigated in the pre-weaning and weaning weight analyses included animal direct additive genetic, dam maternal genetic, litter common environment, dam permanent environment and residual variances. The model of analysis for post-weaning, muscle and fat depth included an animal direct additive genetic and litter common environment effect only. Significant direct additive genetic variation existed in all cases. Direct heritability for pre-weaning weight ranged from 0.14 to 0.30 across the three breeds. Weaning weight had a direct heritability ranging from 0.17 to 0.27 and post-weaning weight had a direct heritability ranging from 0.15 to 0.27. Muscle and fat depth heritability estimates ranged from 0.21 to 0.31 and 0.15 to 0.20, respectively. Positive direct correlations were evident for all traits. Results revealed ample genetic variation among animals for the studied traits and significant differences between breeds to suggest that genetic evaluations could be conducted on a per-breed basis. [ABSTRACT FROM AUTHOR]

Body condition score (BCS) is a subjective assessment of the proportion of body fat an animal possesses and is independent of frame size. There is a growing awareness of the importance of mature animal live-weight given its contribution to the overall costs of production of a sector. Because of the known relationship between BCS and live-weight, strategies to reduce live-weight could contribute to the favouring of animals with lesser body condition. The objective of the present study was to estimate the average difference in live-weight per incremental change in BCS, measured subjectively on a scale of 1 to 5. The data used consisted of 19 033 BCS and live-weight observations recorded on the same day from 7556 ewes on commercial and research flocks; the breeds represented included purebred Belclare (540 ewes), Charollais (1484 ewes), Suffolk (885 ewes), Texel (1695 ewes), Vendeen (140 ewes), as well as, crossbreds (2812 ewes). All associations were quantified using linear mixed models with the dependent variable of live-weight; ewe parity was included as a random effect. The independent variables were BCS, breed (n =6), stage of the inter-lambing interval (n =6; pregnancy, lambing, pre-weaning, at weaning, post-weaning and mating) and parity (1, 2, 3, 4 and 5+). In addition, two-way interactions were used to investigate whether the association between BCS and live-weight differed by parity, a period of the inter-lambing interval or breed. The association between BCS and live-weight differed by parity, by a period of the inter-lambing interval and by breed. Across all data, a one-unit difference in BCS was associated with 4.82 (SE=0.08) kg live-weight, but this differed by parity from 4.23 kg in parity 1 ewes to 5.82 kg in parity 5+ ewes. The correlation between BCS and live-weight across all data was 0.48 (0.47 when adjusted for nuisance factors in the statistical model), but this varied from 0.48 to 0.53 by parity, from 0.36 to 0.63 by stage of the inter-lambing interval and from 0.41 to 0.62 by breed. Results demonstrate that consideration should be taken of differences in BCS when comparing ewes on live-weight as differences in BCS contribute quite substantially to differences in live-weight; moreover, adjustments for differences in BCS should consider the population stratum, especially breed. [ABSTRACT FROM AUTHOR]

The objective of the present study was to quantify the extent of genetic variation in three health-related traits namely dagginess, lameness and mastitis, in an Irish sheep population. Each of the health traits investigated pose substantial welfare implications as well as considerable economic costs to producers. Data were also available on four body-related traits, namely body condition score (BCS), live weight, muscle depth and fat depth. Animals were categorised as lambs (<365 days old) or ewes (≥365 days old) and were analysed both separately and combined. After edits, 39 315 records from 264 flocks between the years 2009 and 2015 inclusive were analysed. Variance components were estimated using animal linear mixed models. Fixed effects included contemporary group, represented as a three-way interaction between flock, date of inspection and animal type (i.e. lamb, yearling ewe (i.e. females ≥365 days but <730 days old that have not yet had a recorded lambing) or ewe), animal breed proportion, coefficients of heterosis and recombination, animal gender (lambs only), animal parity (ewes only; lambs were assigned a separate 'parity') and the difference in age of the animal from the median of the respective parity/age group. An additive genetic effect and residual effect were both fitted as random terms with maternal genetic and non-genetic components also considered for traits of the lambs. The direct heritability of dagginess was similar across age groups (0.14 to 0.15), whereas the direct heritability of lameness ranged from 0.06 (ewes) to 0.12 (lambs). The direct heritability of mastitis was 0.04. For dagginess, 13% of the phenotypic variation was explained by dam litter, whereas the maternal heritability of dagginess was 0.05. The genetic correlation between ewe and lamb dagginess was 0.38; the correlation between ewe and lamb lameness was close to zero but was associated with a large standard error. Direct genetic correlations were evident between dagginess and BCS in ewes and between lameness and BCS in lambs. The present study has demonstrated that ample genetic variation exists for all three health traits investigated indicating that genetic improvement is indeed possible. [ABSTRACT FROM AUTHOR]

The objective of this study was to quantify the impact of alternative contemporary group definitions for lambing traits on genetic evaluations in the Irish multibreed sheep population. Three lambing traits were considered for analysis: lambing difficulty, birth weight, and survival. Eight alternative contemporary group definitions were investigated for each lambing trait; all contemporary groups were formed within flock of lambing and included (flock by) week of lambing, week of lambing by litter size (i.e., singles vs. multiples), 2-wk interval (i.e., fortnight) of lambing, fortnight of lambing by litter size, month of lambing, and month of lambing by litter size or were based on an optimized algorithm that creates contemporary groups based on animals from the same flock that are born in close proximity of date. Three alternative scenarios were modeled for each of the lambing traits using the contemporary group definitions: the first scenario (termed Current Scenario) represented the editing criteria currently employed in the Irish national genetic evaluations; the second scenario (No Restriction Scenario) removed any restriction on number of records per contemporary group, and the final scenario (Variation Scenario) included only data from contemporary groups with some variability in the dependent variable. Variance components and EBV for each of the 3 lambing traits were estimated using linear mixed models. The direct heritability estimates ranged from 0.09 ± 0.02 to 0.29 ± 0.02 for lambing difficulty, 0.11 ± 0.01 to 0.24 ± 0.01 for birth weight, and 0.05 ± 0.02 to 0.10 ± 0.02 for lamb survival. Irrespective of lambing trait, greater estimated accuracy of the sire EBV was achieved with the No Restriction Scenario. Results for the ability to predict future lambing characteristics, based on only the direct and maternal EBV, revealed that the area under the receiver operator characteristic curve for the dichotomized lambing assistance phenotype varied from 0.56 to 0.66; a lambing event predicted to be in the worst 10% risk category of a difficult lambing on the basis of genetic merit alone was 5.48 times (95% CI: 3.94 to 7.61; P < 0.001) more likely to require assistance at lambing compared to a lambing event in the best 10%. Results show that the use of contemporary groups formed over short time periods, coupled with moderate editing of the data, yielded superior predictions for all lambing traits. [ABSTRACT FROM AUTHOR]

The objective of this study was to establish the risk factors associated with both lambing difficulty and lamb mortality in the Irish sheep multibreed population. A total of 135 470 lambing events from 42 675 ewes in 839 Irish crossbred and purebred flocks were available. Risk factors associated with producer-scored ewe lambing difficulty score (scale of one (no difficulty) to four (severe difficulty)) were determined using linear mixed models. Risk factors associated with the logit of the probability of lamb mortality at birth (i.e. binary trait) were determined using generalised estimating equations. For each dependent variable, a series of simple regression models were developed as well as a multiple regression model. In the simple regression models, greater lambing difficulty was associated with quadruplet bearing, younger ewes, of terminal breed origin, lambing in February; for example, first parity ewes experienced greater (P<0.001) lambing difficulty (1.56±0.02) than older ewes. The association between lambing difficulty and all factors persisted in the multiple regression model, and the trend in fixed effects level solutions did not differ from the trend observed in the simple regression models. In the simple regression analyses, a greater odds of lamb mortality was associated with male lambs (1.31 times more likely of death than females), lambs of very light (2 to 3 kg) and very heavy (>7.0 kg) birth weights, quadruplet born lambs and lambs that experienced a more difficult lambing (predicted probability of death for lambs that required severe and veterinary assistance of 0.15 and 0.32, respectively); lambs from dual-purpose breeds and born to younger ewes were also at greater risk of mortality. In the multiple regression model, the association between ewe parity, age at first lambing, year of lambing and lamb mortality no longer persisted. The trend in solutions of the levels of each fixed effect that remained associated with lamb mortality in the multiple regression model, did not differ from the trends observed in the simple regression models although the differential in relative risk between the different lambing difficulty scores was greater in the multiple regression model. Results from this study show that many common flock- and animal-level factors are associated with both lambing difficulty and lamb mortality and management of different risk category groups (e.g. scanned litter sizes, ewe age groups) can be used to appropriately manage the flock at lambing to reduce their incidence. [ABSTRACT FROM PUBLISHER]

• Genetic diversity metrics were calculated for six sheep breeds. • The average generation interval was between 2.0 and 3.8 years in all six breeds. • Inbreeding increased by between 0.05% (Charollais) and 0.17% (Belclare) per year. • There was evidence of recent genetic bottlenecks in each population analysed. • Genetic diversity within each population was sufficient for long-term viability. Monitoring the rate of change in inbreeding and genetic diversity within a population is important to guide breeding programmes. Such interest stems from the impact of loss in genetic diversity on sustainable genetic gain but also the impact on performance (i.e. inbreeding depression). The objective of the present study was to evaluate trends in inbreeding and genetic diversity in 43 066 Belclare, 120 753 Charollais, 22 652 Galway, 78 925 Suffolk, 187 395 Texel, and 19 821 Vendeen purebred sheep. The effective population size for each of the six breeds was between 116.0 (Belclare population) and 314.8 (Charollais population). The Charollais population was the most genetically diverse with the greatest number of effective founders, effective ancestors, and effective founder genomes; conversely, the Belclare was the least genetically diverse population with the fewest number of effective founders, effective ancestors, and effective founder genomes for each of the six breeds investigated. Overall, the effective population sizes and the total genetic diversity within each of the six breeds were above the minimum thresholds generally considered to be required for the long-term viability of a population. [ABSTRACT FROM AUTHOR]

• The frequency of prion protein genotype in the Irish sheep population is unknown. • Results show the prion protein genotype is segregating within the population. • The most susceptible haplotype was only detected in Texels and crossbreds. • No association of biological significance was found between scrapie and performance. • Results allow for the development of a mating decision support tool for scrapie. Genetic susceptibility to scrapie, a fatal disease of sheep and goats, is modulated by polymorphisms in the prion protein ( PrP ). Neither the frequency of the PrP genotypes nor their association with animal performance has been investigated in a large multibreed Irish sheep population. Scrapie genotypes were available on 16 416 animals; the breeds represented included purebred Belclare (733), Charollais (333), Suffolk (739), Texel (1 857), Vendeen (191), and crossbreds (12 563). Performance data on lambing, lamb and ewe performance as well as health traits were available. The association between alternative approaches of describing the PrP genotype (i.e. 15 individually called PrP genotypes, five genotype classes representing susceptibility to scrapie, or number of ARR haplotypes) and animal performance were quantified using animal linear mixed models. All 15 of the possible scrapie genotypes were detected, although the frequency differed by breed. The frequency of the five PrP haplotypes in the entire population were 0.70 (ARR), 0.15 (ARQ), 0.11 (ARH), 0.02 (AHQ) and 0.01 (VRQ); the most susceptible haplotype (VRQ) was only detected in purebred Texels and crossbreds. No association was detected between the PrP genotype of either the animal or dam and any of the lambing traits (i.e. lambing difficulty score, perinatal mortality and birth weight). With the exception of ultrasound muscle depth, no association between the PrP genotype and any of the lamb performance traits (i.e. lamb BW and carcass) was observed. Lambs carrying the category four PrP genotype (i.e. ARR/VRQ) had 1.20 (SE = 0.45) mm, 1.38 (SE = 0.12) mm, 1.47 (S = 0.25) mm shallower ultrasound muscle depth relative to lambs of the less susceptible scrapie categories of 1, 2, 3, respectively (P < 0.05). Nonetheless, no association between PrP genotype and lamb carcass conformation, the ultimate end goal of producers, was detected. Ewe litter size, body condition score or lameness did not differ by PrP genotype of the ewe (P > 0.05). For ewe mature BW, ARH/VRQ ewes differed from most other ewe PrP genotypes and were, on average, 3.79 (SE = 1.66) kg heavier than ARR/ARR genotype ewes. Lamb dag score differed by dam PrP genotype (P < 0.05), although the differences were small. Results from this study show that scrapie is segregating within the Irish sheep population, but the PrP genotype was not associated with most traits investigated and, where associations were detected, the biological significance was minimal. This suggests minimal impact of selection on PrP genotype on performance, at least for the traits investigated in the present study. [ABSTRACT FROM AUTHOR]

Interest in selection for improved feed efficiency is increasing, but before any steps are taken towards selecting for feed efficiency, correlations with other economically important traits must first be quantified. The objective of this study was to quantify the genetic associations between feed efficiency measured during performance testing, and linear type traits, BW, live animal value, and carcass traits recorded in commercial herds. Feed efficiency data were available on 2,605 bulls from 1 performance test station. There were between 10,384 and 93,442 performance records on either type traits, BW, animal value, or carcass traits from 17,225 commercial herds. (Co)variance components were estimated using linear mixed animal models. Genetic correlations between the muscular type traits in commercial animals and FCR (-0.33 to -0.25), RFI (-0.33 to -0.22), and RG (0.24 to 0.27) suggests that selection for improved feed efficiency should increase muscling. This is further evidenced by the genetic correlations between carcass conformation of commercial animals and FCR (-0.46), RFI (-0.37), and RG (0.35) measured in performance-tested animals. Furthermore, the genetic correlations between RFI and both ultrasonic fat depth and carcass fat score (0.39 and 0.33, respectively) indicate that selection for improved RFI will result in leaner animals. It can be concluded from the genetic correlations estimated in this study that selection for feed efficiency will have no unfavourable effects on the performance traits measured in this study, and will actually lead to an improvement in performance for some traits such as muscularity, animal price, and carcass conformation. Conversely, this suggests that genetic selection for traits such as carcass quality, muscling traits, and animal value might also be indirectly selecting for more efficient animals. [ABSTRACT FROM AUTHOR]

Pedigree collected by the Interbeef service allowed genetic diversity to be assessed by using pedigree analyses for the European Charolais (CHA) and Limousin (LIM) cattle populations registered in national herdbooks in Denmark (DNK), France (FRA), Ireland (IRL), Sweden (SWE), and, solely for the LIM breed, the United Kingdom (UK). The CHA data set included 2,563,189 calves with weaning performance, of which 96.1% were recorded in FRA, 3.0% in SWE, 0.5% in IRL, and 0.4% in DNK. The LIM data set included 1,652,734 calves with weaning performance, of which 91.9% were recorded in FRA, 4.9% in UK, 1.8% in DNK, 0.9% SWE, and 0.5% in IRL. Pedigree files included 3,191,132 CHA and 2,409,659 LIM animals. Gene flows were rather limited between populations, except from FRA toward other countries. Pedigree completeness was good in all subpopulations for both breeds and allowed the pedigree to be traced back to the French population. A relatively high level of genetic diversity was assessed in each CHA and LIM subpopulation by estimating either effective population sizes (Ne >244 and Ne >345 in the CHA and LIM subpopulations, respectively), relationship coefficients within subpopulations (<1.3% in both breeds), or probability of gene origins. However, in each subpopulation, it was shown that founders and also ancestors had unbalanced genetic contributions, leading to a moderate but continuous reduction in genetic diversity. Analyses between populations suggested that all European CHA and LIM populations were differentiated very little. The Swedish CHA population was assessed as genetically more distant from the other CHA populations because of fewer gene flows from other countries and because of the use of North American sires to introgress the polled phenotype. In each European subpopulation, most of the main ancestors, which explained 50% of gene origin, were born in FRA. However, those main ancestors were different between countries. Moreover, in both breeds, the main ancestors, which explained 50% of the gene origin in DNK, IRL, SWE, and UK for the LIM breed, were found to be infrequently used in FRA. Those results were consistent with the low relationship coefficients estimated between subpopulations (<0.6% in both the CHA and LIM breeds). Therefore, in both breeds, each subpopulation may constitute a reservoir of genetic diversity for the other ones. [ABSTRACT FROM AUTHOR]

• Four lambing traits were considered in the analysis: lambing difficulty score, lambing dystocia, lamb perinatal mortality and birth weight. • Considerable genetic variation existed for all lambing traits investigated. • All direct genetic effects for the lambing traits were positively correlated with each other, except for lamb birth weight and perinatal mortality. • Results from this study provide a greater understanding of the potential contribution of breeding programs to enhancing lambing performance. • Also quantified is the role of genotype-by-environment interactions between mating types or litter size in the genetic control of lambing performance. The high demand for resources at lambing necessitates strategies to reduce such requirements; one such strategy is breeding programs that enable selection for fewer lambing events requiring assistance as well as less perinatal mortality. The objective of the present study was to estimate the genetic (co)variances for a range of lambing traits in sheep, based on alternative trait definitions that considered differences in mating type and litter size. A total of 158,561 lambing events from both crossbred and purebred Irish sheep were available. Four lambing traits were considered in the analysis: lambing difficulty score, lambing dystocia, lamb perinatal mortality and birth weight. Variance components for each trait were estimated using animal linear mixed models either in the entire data as a whole, or within sub-populations stratified by litter size (i.e., single versus multiple) or stratified by mating type (i.e., crossbred versus purebred animals). The presence of significant re-scaling and re-ranking across population strata were investigated to determine if genotype-by-environmental interactions existed. Considerable genetic variation existed for all lambing traits investigated. Irrespective of the dataset analysed, direct heritability estimates for lambing difficulty score (0.04 ± 0.02 to 0.12 ± 0.03), lambing dystocia (0.04 ± 0.01 to 0.09 ± 0.03), and lamb mortality (0.01 ± 0.01 to 0.09 ± 0.02) were all low. In contrast, lamb birth weight (0.11 ± 0.02 to 0.20 ± 0.04) exhibited a low to moderate direct heritability. Using the entire dataset, the maternal heritability ranged from 0.01 ± 0.005 (lamb mortality) to 0.15 ± 0.02 (birth weight). All direct genetic effects for the lambing traits were positively correlated with each other, except between lamb birth weight and perinatal mortality (-0.15; SE=0.16). Significantly different genetic variances in different environments and significant re-ranking between environments was detected for lamb mortality (across different mating types and litter sizes), and for lambing difficulty score (only across different litter sizes). Results clearly indicate that ample genetic variation exists for the lambing-related traits investigated. [ABSTRACT FROM AUTHOR]

The contribution of animal breeding to changes in animal performance is well documented across a range of species. Once genetic variation in a trait exists, then breeding to improve the characteristics of that trait is possible, if so desired. Considerable genetic variation exists in a range of meat quality attributes across a range of species. The genetic variation that exists for meat quality is as large as observed for most performance traits; thus, within a well-structured breeding program, rapid genetic gain for meat quality could be possible. The rate of genetic gain can be augmented through the integration of DNA-based technologies into the breeding program; such DNA-based technologies should, however, be based on thousands of DNA markers dispersed across the entire genome. Genetic and genomic technologies can also have beneficial impact outside the farm gate as a tool to segregate carcasses or meat cuts based on expected meat quality features. [ABSTRACT FROM AUTHOR]

The objective of the present study was to quantify, using simulated data, the impact on estimated heritability of varying the number of panellists and their inter-correlations using meat sensory tenderness in cattle as an example. Estimated parameters from actual sensory-based tenderness scores from 9 individual panellists on 1252 beef cattle were used to parameterise the simulation. A single “tenderness score” for each of 10 panellists was simulated for 15,000 cattle. Heritability estimates were calculated for each of the 10 panellists individually as well as the mean score per animal for all n combinations of panellists. Heritability estimates improved with increasing number of panellists in line with expectations from a deterministic equation. The increase in heritability was due to a reduction in the residual variance, albeit the rate of reduction in residual variance declined with each additional panellist included in the calculated mean tenderness score. Results highlight the importance of reporting the number of panellist scores per animal as well as their inter-correlations in sensory-based studies. [ABSTRACT FROM AUTHOR]

Sheep production industries face the challenge of increasing farm production and profit while reducing environmental impacts. Genetic selection using multi-trait breeding indices can be used to improve flock productivity, profitability, and greenhouse gas (GHG) emissions intensities (kg CO 2 -eq /kg of product), however validation of the improved performance of animals ranked higher on breeding indices at a flock level is required. Phenotypic data from 387,580 production records of animals born between 2018 and 2020 of known genetic merit in commercial flocks were inputted to an established bio-economic model. Two contrasting flocks were compared, a flock of ewes ranked High (top 20%) on the Irish replacement Index bred with rams ranked High on the replacement and terminal indices, and a flock of ewes ranked Low (bottom 20%) on the Irish replacement Index bred with rams ranked Low on the replacement and terminal indices. The two flocks were then simulated using life cycle assessment to estimate the GHG emissions profile for both systems. Flock weaning rates were 1.70 and 1.53 lambs weaned per ewe presented for breeding for the High and Low genetic merit flocks, respectively. The flock of High genetic merit ewes sold 0.17 more lambs per ewe, equating to 3.29 kg more lamb carcass per ewe, than the flock of Low genetic merit ewes; lambs from the High genetic merit flock were also sold at an earlier age. The greater production of the High genetic merit flocks resulted in an additional €18/ewe net profit than the Low genetic merit flock. Although total flock GHG emissions were higher for the High genetic merit flock, GHG emissions intensities were lower at 21.7 and 23.3 kg CO 2 -eq /kg lamb carcass sold for the High and Low genetic merit flocks, respectively. The lower emissions intensity of the High genetic merit flock was due to the dilution effect of higher lamb production and lambs being drafted for slaughter ealier. The results suggest Irish sheep producers can make substantial profit gains through selection according to the national breeding indices while also reducing their environmental impact, and farmers should consider genetic merit when purchasing their rams, particularly sires of replacement ewe lambs. [Display omitted] • Field data from animals divergent in genetic merit was input to bio-economic and life-cycle analysis models. • The flock of high genetic merit had net profit €18/ewe higher than the flock of low genetic merit. • Higher ranking on the replacement index had larger increases in profit than from the terminal index. • GHG emissions intensity was 6.9% lower for the flock of high genetic merit. • Farmers can improve profitability while reducing GHG emissions intensities through selection using the national indices. [ABSTRACT FROM AUTHOR]

• Economic values are widely used in the development of breeding objectives internationally. • An economic value is the value of a one unit change in an individual trait, while keeping all other traits constant. • Economic values of fourteen traits representing maternal, lambing, production and health characteristics were calculated. • All economic values were calculated within a whole farm bio-economic model. • This study will enable the implementation of new economic values into the Irish national sheep breeding objectives. The economic value of a trait in a breeding objective can be defined as the value of a unit change in an individual trait, while keeping all other traits constant and are widely used in the development of breeding objectives internationally. The objective of this study was to provide a description of the development of economic values for the pertinent traits included in the Irish national sheep breeding objectives using a whole farm system bio-economic model. A total of fourteen traits of economic importance representing maternal, lambing, production and health characteristics were calculated within a whole farm bio-economic model. The model was parameterised to represent an average Irish flock of 107 ewes with a mean lambing date in early March, stocked at 7.5 ewes per hectare and weaning 1.5 lambs per ewe joined to the ram. The economic values (units in parenthesis) calculated for maternal traits were: €39.76 for number of lambs born (per lamb), €0.12 for ewe mature weight cull value (per kg), −€0.57 for ewe mature weight maintenance value (per kg), −€0.09 for ewe mature weight replacement value (per kg) and −€0.84 for ewe replacement rate (per%). The economic values calculated for lambing traits were: €54.84 for lamb surviving at birth (per lamb), −€0.27 and −€0.30 for direct lambing difficulty in single and multiple-bearing ewes, respectively (per%); the corresponding values for maternal single and multiple lambing difficulty (per%) were −€0.25 and −€0.27, respectively. The calculated economic values for production traits were: −€0.25 for days to slaughter (per day), €3.70 for carcass Conformation (per EUROP grade) and −€0.84 for carcass fat (per fat score). The economic values for health traits were: −€0.24 for ewe lameness (per%), −€0.08 for lamb lameness (per%), −€0.25 for mastitis (per%), −€0.34 for dag score (per dag score) and −€0.08 for faecal egg count (per 50 eggs/g). Within the two Irish breeding objectives, the terminal and replacement breeding objective, the greatest emphasis was placed on production traits across both the terminal (62.56%) and replacement (41.65%) breeding objectives. The maternal and lambing traits accounted for the 34.19% and 23.45% of the emphasis within the replacement breeding objective, respectively. Results from this study will enable the implementation of new economic values within the national terminal and replacement Irish sheep breeding objectives which highlights the traits of importance for increasing overall farm profitability. [ABSTRACT FROM AUTHOR]

Cattle breeding programs that strive to reduce the animal-level incidence of lameness are often hindered by the availability of informative phenotypes. As a result, indicator traits of lameness (i.e., hoof health and morphological conformation scores) can be used to improve the accuracy of selection and subsequent genetic gain. Therefore, the objectives of the present study were to estimate the variance components for hoof health traits using various phenotypes collected from a representative sample of Irish dairy cows. Also of interest to the present study was the genetic relationship between both hoof health traits and conformation traits with producer-scored lameness. Producer-recorded lameness events and linear conformation scores from 307,657 and 117,859 Irish dairy cows, respectively, were used. Data on hoof health (i.e., overgrown sole, white line disease, and sole hemorrhage), mobility scores, and body condition scores were also available from a research study on up to 11,282 Irish commercial dairy cows. Linear mixed models were used to quantify variance components for each trait and to estimate genetic correlations among traits. The estimated genetic parameters for hoof health traits in the present study were greater (i.e., heritability range: 0.005 to 0.27) than previously reported in dairy cows. With the exception of analyses that considered hoof health traits in repeatability models, little difference in estimated variance components existed among the various hoof-health phenotypes. Results also suggest that producer-recorded lameness is correlated with both hoof health (i.e., genetic correlation up to 0.48) and cow mobility (i.e., genetic correlation = 0.64). Moreover, cows that genetically tend to have rear feet that appear more parallel when viewed from the rear are also genetically more predisposed to lameness (genetic correlation = 0.39); genetic correlations between lameness and other feet and leg type traits, as well as between lameness and frame type traits, were not different from zero. Results suggest that if the population breeding goal was to reduce lameness incidence, improve hoof health, or improve cow mobility, genetic selection for either of these traits should indirectly benefit the other traits. Results were used to quantify the genetic gains achievable for lameness when alternative phenotypes are available. [ABSTRACT FROM AUTHOR]

Genetic selection has been identified as a promising approach for reducing enteric methane (CH4) emissions; a prerequisite for genetic evaluations; however, these are estimates of the necessary genetic parameters based on a population representative of where the genetic evaluations will be used. The objective of this study was, therefore, to derive genetic parameters for a series of definitions of CH4, carbon dioxide (CO2), and dry matter intake (DMI) as well as genetic correlations between CH4, CO2, and DMI in a bid to address the paucity of studies involving methane emissions measured in beef cattle using GreenFeed systems. Lastly, estimated breeding values (EBV) were generated for nine alternative definitions of CH4 using the derived genetic parameters; the EBV were validated against both phenotypic performance (adjusted for non-genetic effects) and the Legarra and Reverter method comparing EBV generated for a subset of the dataset compared to EBV generated from the entire dataset. Individual animal CH4 and CO2 records were available from a population of 1,508 multi-breed growing beef cattle using 10 GreenFeed Emission Monitoring systems. Nine trait definitions for CH4 and CO2 were derived: individual spot measures, the average of all spot measures within a 3-h, 6-h, 12-h, 1-d, 5-d, 10-d, and 15-d period and the average of all spot measures across the full test period (20 to 114 d on test). Heritability estimates from 1,155 animals, for CH4, increased as the length of the averaging period increased and ranged from 0.09 ± 0.03 for the individual spot measures trait to 0.43 ± 0.11 for the full test average trait; a similar trend existed for CO2 with the estimated heritability ranging from 0.17 ± 0.04 to 0.50 ± 0.11. Enteric CH4 was moderately to strongly genetically correlated with DMI with a genetic correlation of 0.72 ± 0.02 between the spot measures of CH4 and a 1-d average DMI. Correlations, adjusted for heritability, between the adjusted phenotype and (parental average) EBV ranged from 0.56 to 1.14 across CH4 definitions and the slope between the adjusted phenotype and EBV ranged from 0.92 to 1.16 (expectation = 1). Validation results from the Legarra and Reverter regression method revealed a level bias of between -0.81 and -0.45, a dispersion bias of between 0.93 and 1.17, and ratio accuracy (ratio of the partial evaluation accuracies on whole evaluation accuracies) from 0.28 to 0.38. While EBV validation results yielded no consensus, CH4 is a moderately heritable trait, and selection for reduced CH4 is achievable., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Society of Animal Science.)

The construction of covariance matrices that account for the genetic relationships among individuals, using pedigree or genotype data, is integral to genetic evaluations, which are now routinely used in the field of animal breeding. The objective of the present study was to estimate the standard deviation in the proportion of the segregating genome that is shared between pairs of full-sibling cattle and sheep independently. Post edits, genotype data comprising 46,069 autosomal single nucleotide polymorphisms (SNPs) were available for 4532 unique full-sibling sheep pairs, as well as for their respective parents. Post edits, genotypes from 50,493 autosomal SNPs were also available for 10,000 unique full-sibling cattle pairs, as well as their respective parents. Genomic relationship matrices were constructed for the sheep and cattle populations, separately. After accounting for both parental genomic inbreeding and the genomic relationship between both parents, the standard deviation in full-sibling cattle and sheep genomic relationships was 0.040 and 0.037 units, respectively. In addition, the intercept value from a linear regression model which regressed each full-sibling genomic relationship on both sire and dam inbreeding, as well as the genomic relationship between the parents, was 0.499 (0.001) for sheep and 0.500 (0.001) for cattle, conforming to the expectation that full-siblings, on average, share 50% of their segregating genome., (© 2023. The Author(s).)

Rumen methanogenesis results in the loss of 6% to 10% of gross energy intake in cattle and globally is the single most significant source of anthropogenic methane (CH4) emissions. The purpose of this study was to analyze greenhouse gas traits recorded in a commercial feedlot unit to gain an understanding into the relationships between greenhouse gas traits and production traits. Methane and carbon dioxide (CO2) data recorded via multiple GreenFeed Emission Monitoring (GEM), systems as well as feed intake, live weight, ultrasound scanning data, and slaughter data were available on 1,099 animals destined for beef production, of which 648 were steers, 361 were heifers, and 90 were bulls. Phenotypic relationships between GEM emission measurements with feed intake, weight traits, muscle ultrasound data, and carcass traits were estimated. Utilization of GEM systems, daily patterns of methane output, and repeatability of GEM system measurements across averaging periods were also assessed. Methane concentrations varied with visit number, duration, and time of day of visit to the GEM system. Mean CH4 and CO2 varied between sex, with mean CH4 of 256.1 g/day ± 64.23 for steers, 234.7 g/day ± 59.46 for heifers, and 156.9 g/day ± 55.98 for young bulls. A 10-d average period of GEM system measurements were required for steers and heifers to achieve a minimum repeatability of 0.60; however, higher levels of repeatability were observed in animals that attended the GEM system more frequently. In contrast, CO2 emissions reached repeatability estimates >0.6 for steers and heifers in all averaging periods greater than 2-d, suggesting that cattle have a moderately consistent CO2 emission pattern across time periods. Animals with heavier bodyweights were observed to have higher levels of CH4 (correlation = 0.30) and CO2 production (correlation = 0.61), and when assessing direct methane, higher levels of dry matter intake were associated with higher methane output (correlation = 0.31). Results suggest that reducing CH4 can have a negative impact on growth and body composition of cattle. Methane ratio traits, such as methane yield and intensity were also evaluated, and while easy to understand and compare across populations, ratio traits are undesirable in animal breeding, due to the unpredictable level of response. Methane adjusted for dry matter intake and liveweight (Residual CH4) should be considered as an alternative emission trait when selecting for reduced emissions within breeding goals., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Society of Animal Science.)

Genetic evaluations provide producers with a tool to aid in breeding decisions and highlight the increase in performance achievable at the farm level through genetic gain. Despite this, large-scale validation of sheep breeding objectives using field data is lacking in the scientific literature. The objective of the present study was to evaluate the phenotypic differences for a range of economically important traits for animals divergent in genetic merit for the Irish national maternal and terminal sheep breeding objectives. A dataset of 17,356 crossbred ewes and 54,322 progeny differing in their maternal and terminal breeding index recorded in 139 commercial flocks was available. The association of the maternal index of the ewe or terminal index of the ram and a range of phenotypic performance traits, including lambing, lamb performance, ewe performance, and health traits, were undertaken. Ewes excelling on the maternal index had higher litter sizes and produced progeny with greater perinatal lamb survival, heavier live weights from birth to postweaning and reduced days to slaughter ( P  < 0.05). Ewe maternal index had no quantifiable impact on lambing ease, carcass conformation, or fat, the health status of the ewe or lamb, ewe barren rate, or ewe live weight. Lambs born to rams of superior terminal index produced heavier lambs from preweaning onwards, with a reduced day to slaughter ( P  < 0.05). Lambing traits, lamb health, and carcass characteristics of the progeny did not differ between sires stratified as low or high on the terminal index ( P  > 0.05). Results from this study highlight that selecting either ewes or rams of superior maternal or terminal attributes will result in an improvement on pertinent performance traits of the national sheep flock, resulting in greater flock productivity and profitability., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Society of Animal Science.)

Deep Learning (DL) has proven to be a successful tool for many image classification problems but has yet to be applied to carcass images. The aim of this study was to train DL models to predict carcass cut yields and compare predictions to more standard machine learning (ML) methods. Three approaches were undertaken to predict the grouped carcass cut yields of Grilling cuts and Roasting cuts from a large dataset of 54,598 and 69,246 animals respectively. The approaches taken were (1) animal phenotypic data used as features for a range of ML algorithms, (2) carcass images used to train Convolutional Neural Networks, and (3) carcass dimensions measured directly from the carcass images, combined with the associated phenotypic data and used as feature data for ML algorithms. Results showed that DL models can be trained to predict carcass cuts yields but an approach that uses carcass dimensions in ML algorithms performs slightly better in absolute terms., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Understanding the phenotypic factors that affect lamb live weight and carcass composition is imperative to generating accurate genetic evaluations and further enables implementation of functional management strategies. This study investigated phenotypic factors affecting live weight across the growing season and traits associated with carcass composition in lambs from a multibreed sheep population. Four live weight traits and two carcass composition traits were considered for analysis namely; birth, preweaning, weaning, and postweaning weight, and ultrasound muscle depth and fat depth. A total of 427,927 records from 159,492 lambs collected from 775 flocks between the years 2016 and 2019, inclusive were available from the Irish national sheep database. Factors associated with live weight and carcass composition were determined using linear mixed models. The heaviest birth, preweaning, and weaning weights were associated with single born lambs ( P < 0.001), however by postweaning, there was no difference observed in the weights of single and twin born lambs ( P > 0.01). Breed class affected lamb live weight and carcass composition with terminal lambs weighing heaviest and having greater muscle depth than all other breed classes investigated ( P < 0.001). Lambs born to first parity dams were consistently lighter, regardless of time of weighing ( P < 0.001), while dams lambing for the first time as ewe lambs produced lighter lambs than those lambing for the first time as hoggets ( P < 0.001). Greater heterosis coefficients (i.e., >90% and ≤100%) resulted in heavier lambs at weaning compared with lambs with lower levels of heterosis coefficients ( P < 0.001). A heterosis coefficient class <10% resulted in lambs with greater muscle depth while recombination loss of <10% increased ultrasound fat depth ( P < 0.001). Results from this study highlight the impact of multiple animal level factors on lamb live weight and carcass composition which will enable more accurate bio-economic models and genetic evaluations going forward., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Society of Animal Science.)

Input parameters for decision support tools are comprised of, amongst others, knowledge of the associated factors and the extent of those associations with the animal-level feature of interest. The objective of the present study was to quantify the association between animal-level factors with primal cut yields in cattle and to understand the extent of the variability in primal cut yields independent carcass weight. The data used consisted of the weight of 14 primal carcass cuts (as well as carcass weight, conformation, and fat score) on up to 54,250 young cattle slaughtered between the years 2013 and 2017. Linear mixed models, with contemporary group of herd-sex-season of slaughter as a random effect, were used to quantify the associations between a range of model fixed effects with each primal cut separately. Fixed effects in the model were dam parity, heterosis coefficient, recombination loss, a covariate per breed representing the proportion of Angus, Belgian Blue, Charolais, Jersey, Hereford, Limousin, Simmental, and Holstein-Friesian and a three-way interaction between whether the animal was born in a dairy or beef herd, sex, and age at slaughter, with or without carcass weight as a covariate in the mixed model. The raw correlations among all cuts were all positive varying from 0.33 (between the bavette and the striploin) to 0.93 (between the topside and knuckle). The partial correlation among cuts, following adjustment for differences in carcass weight, varied from -0.36 to 0.74. Age at slaughter, sex, dam parity, and breed were all associated ( P < 0.05) with the primal cut weight. Knowledge of the relationship between the individual primal cuts, and the solutions from the models developed in the study, could prove useful inputs for decision support systems to increase performance., (© The Author(s) 2019. Published by Oxford University Press on behalf of the American Society of Animal Science.)

The decision on which ewe lamb to retain versus which to sell is likely to vary by producer based on personal preference. What is not known, however, is if any commonality exists among producers in the characteristics of ewe lambs that influence their eventual fate. The objective of the present study was to determine what genetic and nongenetic factors associate with the fate of maiden ewe lambs. The fate of each ewe lamb born in the present study was defined as either subsequently: 1) having lambed in the flock, or 2) was slaughtered without any recorded lambing event. A total of 9,705 ewe lamb records from 41 crossbred flocks were used. The logit of the odds of the ewe lamb being retained for lambing was modeled using logistic regression. Variance components were then estimated for the binary trait representing the fate of the ewe lamb using animal linear and threshold mixed models. The genetic correlations between fate of the ewe lamb and preweaning, weaning, or postweaning liveweight were also estimated. From the edited data set, 45% of ewe lambs born entered the mature flock as ewes. Ewe lambs reared as singles, with greater levels of heterosis but lower levels of recombination loss, born to dams that lambed for the first time as hoggets, with greater breed proportion of the Belclare, Suffolk, Texel, and Llyen breeds were more likely ( P < 0.001) to eventually lamb in the flock than be slaughtered without ever lambing. Irrespective of the age of the animal when weighed, heavier ewe lambs were more likely to eventually lamb ( P < 0.001). The genetic SD and direct heritability of fate of the ewe lamb estimated in the univariate linear model was 26.58 percentage units and 0.31 (SE = 0.03), respectively; the heritability was 0.30 when estimated using the threshold model. The corresponding direct heritability of fate of the ewe lamb estimated in the bivariate analyses with liveweight ranged from 0.29 (SE = 0.03; preweaning weight) to 0.35 (SE = 0.04; postweaning weight). The genetic correlations estimated between fate of the ewe lamb and the liveweight traits were weak to moderate but strengthened as the age of the ewe lamb at weighing increased. Results from this study provide an understanding of the factors producers consider when selecting females for retention versus slaughter which may form useful parameters in the development of a decision support tool to identify suitable ewe lambs for retention., (© The Author(s) 2019. Published by Oxford University Press on behalf of the American Society of Animal Science.)

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., (© The Author(s) 2019. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Having access to early predictions of both the genetic merit and expected phenotypic performance of an individual or its progeny can contribute to more informed decision-making. The objective here was to evaluate the usefulness of routinely available subjectively scored linear conformation information on live animals to predict genetic merit for primal carcass cut yields of their relatives. Data on 6 muscular and 6 skeletal traits on 43,078 live animals were used; the weights of up to 14 primal cuts plus 3 groups of primal cuts of 31,827 cattle were also used. Genetic correlations between the linear scores and the primal cut weights were estimated using sire linear mixed models; correlations were estimated with or without phenotypic adjustment of the primal cut weights to a constant carcass weight. The genetic correlations between each of the muscular and skeletal linear type traits with each of the primal cut weights (not adjusted for carcass weight) were all positive with the exception of the correlations between both chest width and pelvic length with cuberoll. On average, the muscular type traits were more strongly correlated (on average 0.42) with the primal cut weights than the skeletal traits (on average 0.35). Moreover, the average of the genetic correlations between each of the 6 muscular traits with all 8 hindquarter traits was, on average, 10% to 18% stronger than the average of the genetic correlations between the same muscular traits with all 5 forequarter primal cuts. When adjusted for differences in carcass weight, the correlations between all linear scores and the carcass traits regressed to zero or became negative. The skeletal traits were, in general, weakly genetically correlated with the primal cuts adjusted to a common carcass weight. The average of the genetic correlation between the muscular type traits and the primal cuts adjusted for differences in carcass weight was only 0.09 with only 13 of the 84 pairwise correlations being stronger than 0.30; the genetic correlation between silverside with the muscular traits was all stronger than 0.30, whereas the majority of the muscular traits had a correlation stronger than 0.30 with the topside primal cut. In fact, the average of the genetic correlations between the topside and silverside cuts with all the muscular traits was 0.50 and 0.42, respectively, with none of the correlations being negative., (© The Author(s) 2019. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The study objective was to quantify the ability of genetic merit for a generated carcass index to differentiate animals on primal carcass cut weights using data from 1,446 herds on 9,414 heifers and 22,413 steers with weights for 14 different primal carcass cuts (plus 3 generated groups of cuts). The carcass genetic merit index was compromised of carcass weight (positive weight), conformation (positive weight), and fat score (negative weight), each equally weighted within the index. The association analyses were undertaken using linear mixed models; models were run with or without carcass weight as a covariate. In a further series of analyses, carcass weight and carcass fat score were both included as covariates in the models. Whether the association between primal cut yield and carcass weight differed by genetic merit stratum was also investigated. Genetic merit was associated ( P < 0.001) with the weight of all cuts evaluated even when adjusted to a common carcass weight ( P < 0.01); when simultaneously adjusted to a common carcass weight and fat score, genetic merit was not associated with the weight of the cuberoll or the group cuts termed minced-meat. The weight of the different primal cuts increased almost linearly within increasing genetic merit, with the exception of the rump and bavette. The difference in mean primal cut weight between the very low and very high genetic merit strata, as a proportion of the overall mean weight of that cut in the entire data set, varied from 0.05 (bavette) to 0.28 (eye of round); the average was 0.17. Following adjustment for differences in carcass weight, there was no difference in cut weight between the very low and very high strata for the rump, chuck tender, and mince cut group; the remaining cuts were heavier in the higher index animals with the exception of the cuberoll and bavette, which were lighter in the very high index animals. The association between carcass weight and the weight of each of the evaluated primal cuts differed ( P < 0.05) by genetic merit stratum for all cuts evaluated with the exception of the rump, striploin, and brisket as well as the group cuts of frying and mincing. With the exception of these 5 primal (group) cuts, the regression coefficients of primal cut weight on carcass weight increased consistently for all traits with increasing genetic merit stratum, other than for the fillet, cuberoll, bavette, chuck and neck, and heel and shank., (© The Author(s) 2019. Published by Oxford University Press on behalf of the American Society of Animal Science.)

Ewe efficiency has traditionally been defined as the ratio of litter weight to ewe weight; given the statistical properties of ratio traits, an alternative strategy is proposed in the present study. The concept of using the deviation in performance of an animal from the population norm has grown in popularity as a measure of animal-level efficiency. The objective of the present study was to define novel measures of efficiency for sheep, which considers the combined weight of a litter of lambs relative to the weight of their dam, and vice versa. Two novel traits, representing the deviation in total litter weight at 40 d (DEV40L) or weaning (DEVweanL), were calculated as the residuals of a statistical model, with litter weight as the dependent variable and with the fixed effects of litter rearing size, contemporary group, and ewe weight. The deviation in ewe weight at 40-d postlambing (DEV40E) or weaning (DEVweanE) was derived using a similar approach but with ewe weight and litter weight interchanged as the dependent variable. Variance components for each trait were estimated by first deriving the litter or ewe weight deviation phenotype and subsequently estimating the variance components. The phenotypic SD in DEV40L and DEVweanL was 8.46 and 15.37 kg, respectively; the mean litter weight at 40 d and weaning was 30.97 and 47.68 kg, respectively. The genetic SD and heritability for DEV40L was 2.65 kg and 0.12, respectively. For DEVweanL, the genetic SD and heritability was 4.94 kg and 0.13, respectively. The average ewe weight at 40-d postlambing and at weaning was 66.43 and 66.87 kg, respectively. The genetic SD and heritability for DEV40E was 4.33 kg and 0.24, respectively. The heritability estimated for DEVweanE was 0.31. The traits derived in the present study may be useful not only for phenotypic benchmarking of ewes within flock on performance but also for benchmarking flocks against each other; furthermore, the extent of genetic variability in all traits, coupled with the fact that the data required to generate these novel phenotypes are usually readily available, signals huge potential within sheep breeding programs.

The objective of the present study was to quantify the impact of the systematic environmental effects of both birth and rearing type on pre-weaning lamb live weight, and to evaluate the repercussions of inaccurate recording of birth and rearing type on subsequent genetic evaluations. A total of 32,548 birth weight records, 35,770 forty-day weight records and 32,548 records for average daily gain (ADG) between birth and 40-day weight from the Irish national sheep database were used. For each lamb, a new variable, birth-rearing type, reflecting both the birth and rearing type of a lamb was generated by concatenating both parameters. The association between birth-rearing type and birth weight, 40-day weight, and ADG was estimated using linear mixed models. The repercussions of inaccurate recording of birth type were determined by quantifying the impact on sire estimated breeding value (EBV; with an accuracy of ≥ 35%), where one of the lambs born in a selection of twin litter births was assumed to have died at birth but the farmer recorded the birth and rearing type as a singleton. The heaviest mean birth weight was associated with lambs born and subsequently reared as singles (5.47 kg); the lightest mean birth weight was associated with lambs born and reared as triplets (4.10 kg). The association between birth-rearing type and 40-day weight differed by dam parity ( P < 0.001). Lambs reared by first parity dams as singles, irrespective of birth type were, on average, heavier at 40-day weighing than lambs reared as multiples, but as parity number increased, single-born lambs reared as twins outperformed triplet-born lambs reared as singles. Irrespective of the trait evaluated, the correlation between sire EBV estimated from the accurately recorded data and sire EBV estimated from the data with recording errors was strong ranging from 0.93 (birth weight) to 0.97 (ADG). The EBV for sires with progeny data manipulated were 0.14 kg, 0.34 kg and 5.56 g/d less for birth weight, 40-day weight and ADG, respectively, compared to their equivalent EBV calculated using accurately recorded data. Results from this study highlight the importance of precise recording of birth-rearing type by producers for the generation of accurate genetic evaluations.

The objective of this study was to quantify the genetic associations between a range of carcass-related traits including wholesale cut weights predicted from video image analysis (VIA) technology, and a range of pre-slaughter performance traits in commercial Irish cattle. Predicted carcass cut weights comprised of cut weights based on retail value: lower value cuts (LVC), medium value cuts (MVC), high value cuts (HVC) and very high value cuts (VHVC), as well as total meat, fat and bone weights. Four main sources of data were used in the genetic analyses: price data of live animals collected from livestock auctions, live-weight data and linear type collected from both commercial and pedigree farms as well as from livestock auctions and weanling quality recorded on-farm. Heritability of carcass cut weights ranged from 0.21 to 0.39. Genetic correlations between the cut traits and the other performance traits were estimated using a series of bivariate sire linear mixed models where carcass cut weights were phenotypically adjusted to a constant carcass weight. Strongest positive genetic correlations were obtained between predicted carcass cut weights and carcass value (min r g(MVC) = 0.35; max r(g(VHVC)) = 0.69), and animal price at both weaning (min r(g(MVC)) = 0.37; max r(g(VHVC)) = 0.66) and post weaning (min r(g(MVC)) = 0.50; max r(g(VHVC)) = 0.67). Moderate genetic correlations were obtained between carcass cut weights and calf price (min r g(HVC) = 0.34; max r g(LVC) = 0.45), weanling quality (min r(g(MVC)) = 0.12; max r (g(VHVC)) = 0.49), linear scores for muscularity at both weaning (hindquarter development: min r(g(MVC)) = -0.06; max r(g(VHVC)) = 0.46), post weaning (hindquarter development: min r(g(MVC)) = 0.23; max r(g(VHVC)) = 0.44). The genetic correlations between total meat weight were consistent with those observed with the predicted wholesale cut weights. Total fat and total bone weights were generally negatively correlated with carcass value, auction prices and weanling quality. Total bone weight was, however, positively correlated with skeletal scores at weaning and post weaning. These results indicate that some traits collected early in life are moderate-to-strongly correlated with carcass cut weights predicted from VIA technology. This information can be used to improve the accuracy of selection for carcass cut weights in national genetic evaluations.

The objective of this study was to quantify the genetic variation in carcass cuts predicted using digital image analysis in commercial cross-bred cattle. The data set comprised 38,404 steers and 14,318 heifers from commercial Irish herds. The traits investigated included the weights of lower value cuts (LVC), medium value cuts (MVC), high value cuts (HVC), very high value cuts (VHVC) and total meat weight. In addition, the weights of total fat and total bones were available on the steers. Heritability of carcass cut weights, within gender, was estimated using an animal linear model, whereas genetic and phenotypic correlations among cuts were estimated using a sire linear model. Carcass weight was included as a covariate in all models. In the steers, heritability ranged from 0.13 (s.e. = 0.02) for VHVC to 0.49 (s.e. = 0.03) for total bone weight, and in the heifers heritability ranged from 0.15 (s.e. = 0.04) for MVC to 0.72 (s.e. = 0.06) for total meat weight. The coefficient of genetic variation for the different cuts varied from 1.4% to 3.6%. Genetic correlations between the different cut weights were all positive and ranged from 0.45 (s.e. = 0.08) to 0.89 (s.e. = 0.03) in the steers, and from 0.47 (s.e. = 0.14) to 0.82 (s.e. = 0.06) in the heifers. Genetic correlations between the wholesale cut weights and carcass conformation ranged from 0.32 (s.e. = 0.06) to 0.45 (s.e. = 0.07) in the steers, and from 0.10 (s.e. = 0.12) to 0.38 (s.e. = 0.09) in the heifers. Genetic correlations between the same wholesale cut traits in steers and heifers ranged from 0.54 (s.e. = 0.14) for MVC to 0.79 (s.e. = 0.06) for total meat weight; genetic correlations between carcass weight and carcass classification for conformation and fat score in both genders varied from 0.80 to 0.87. The existence of genetic variation in carcass cut traits, coupled with the routine availability of predicted cut weights from digital image analysis, clearly shows the potential to genetically improve carcass value.