Genetic and non-genetic factors associated with health and vitality traits in beef calves.

Awareness and interest in calf health and wellbeing is intensifying, prompting change in the management and breeding decisions of producers and associated policy-makers. The objectives of the present study were to 1) quantify the risk factors associated with subjectively measured scores of vigor and birth size as well as diagnoses of scour and pneumonia in a large national dataset of beef calves, and 2) to estimate the contribution of genetic variance to such phenotypic measures. After edits, the data consisted of health and birth size data subjectively scored by producers on 88,207 calves born in 6,126 Irish beef herds. Vigor was recorded on a scale of 1 (very poor) to 5 (very good). Birth size was also scored on a scale of 1 (very small) to 5 (very large). Scour and pneumonia were both scored independently based on the suspected number of occurrence of each (0 = no occurrence, 1 = one occurrence, or 2 = more than one occurrence). On average, 14.7% of calves were recorded as having had at least one occurrence of scour within the first 5 mo of life, whereas 6.4% of calves were recorded as having had at least one occurrence of pneumonia within the first 5 mo of life. Relative to female calves, male calves had a worse vigor score and a suspected greater incidence of both scour and pneumonia. Relative to singletons, twins were, on average, smaller at birth, they had a worse vigor score, and they were more prone to scour. Calves born in the later periods of the calving season (i.e., late and very late) had a greater incidence of scour relative to calves in the herd born earlier in the calving season. Heritability estimates for vigor, birth size, and pneumonia were 0.12 (0.02), 0.33 (0.03), and 0.08 (0.02), respectively; no genetic variance was detected for scour. Breeding for vigorous calves that are less susceptible to pneumonia could provide producers with an additional strategy to ensure consumer concerns regarding food quality, safety, and calf wellbeing are being met.

Large variability in feeding behavior among crossbred growing cattle.

The purpose of this study was to define an extensive suite of feeding behavior traits in growing crossbred cattle and to investigate their phenotypic inter-relationships as well as relationships with other performance and efficiency traits. Time-series feeding behavior data, as well as feed intake and liveweight records, were available for 624 growing crossbred cattle, of which 445 were steers and 179 were heifers. Feeding behavior repeatability estimates were calculated using linear mixed models. Additionally, partial Spearman correlations were estimated among 14 feeding behavior traits, as well as between feeding behavior with both performance and feed efficiency traits, using residuals retained from linear mixed models. The marginal contribution of several feeding behavior traits to the variability in metabolizable energy intake (MEI) was also determined. Repeatability estimates of 0.57, 0.36, and 0.48 were calculated for the number of feed events per day, the total time spent feeding per day, and the feeding rate, respectively. Cattle that ate more frequently each day, ate at a faster rate and consumed less energy in each visit to the feed bunk. More efficient cattle fed less often per day and fed for a shorter duration per day; they also had a slower feeding rate and fed for longer in each visit to the feed bunk. Moreover, heavier cattle fed for a longer duration per day had a faster feeding rate, but fed less often per day; heavier animals also fed first in the pen after the fresh feed was offered. The number of feed events per day and feeding time per day together explained an additional 13.4 percentage points of the variability in MEI above that already explained by all of growth rate, liveweight, and backfat depth. The results from the present study suggest that several repeatable time-series-related feeding behavior traits, that are less resource intensive to measure, may have a role as useful predictor traits of important but relatively difficult to record traits, such as feed intake and efficiency.

Animal-level factors associated with the achievement of desirable specifications in Irish beef carcasses graded using the EUROP classification system.

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.

The achievement of a given carcass specification is under moderate genetic control in cattle.

The objective of the present study was to estimate the genetic parameters associated with the achievement of desirable weight, conformation, and fat specifications, represented by a series of binary traits. The desired specifications were those stipulated by Irish beef processors, in accordance with the EUROP carcass grading system, and were represented by a carcass weight between 270 and 380 kg, a fat score between 2+ and 4= (between 6 and 11 on a 15-point scale), and a conformation score of O= or better (≥5 on a 15-point scale). Using data from 58,868 beef carcasses, variance components were estimated using linear mixed models for these binary traits, as well as their underlying continuous measures. Heritability estimates for the continuous traits ranged from 0.63 to 0.73; heritability estimates for the binary traits ranged from 0.05 to 0.19. An additional trait was defined to reflect if all desired carcass specifications were met. All genetic correlations between this trait and the individual contributing binary traits were positive (0.38 to 0.87), while all genetic correlations between this trait and the continuous carcass measures were negative (-0.87 to -0.07). The genetic parameters estimated in the present study signify that potential exists to breed cattle that more consistently achieve desirable carcass metrics at harvest.

Feed efficiency and carcass metrics in growing cattle1.

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.

Linear classification scores in beef cattle as predictors of genetic merit for individual carcass primal cut yields1.

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.

Potential exists to change, through breeding, the yield of individual primal carcass cuts in cattle without increasing overall carcass weight1.

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.

High imputation accuracy from informative low-to-medium density single nucleotide polymorphism genotypes is achievable in sheep1.

The objective of the present study was to quantify the accuracy of imputing medium-density single nucleotide polymorphism (SNP) genotypes from lower-density panels (384 to 12,000 SNPs) derived using alternative selection methods to select the most informative SNPs. Four different selection methods were used to select SNPs based on genomic characteristics (i.e., minor allele frequency (MAF) and linkage disequilibrium (LD)) within five sheep breeds (642 Belclare, 645 Charollais, 715 Suffolk, 440 Texel, and 620 Vendeen) separately. Selection methods evaluated included (i) random, (ii) splitting the genome into blocks of equal length and selecting SNPs within block based on MAF and LD patterns, (iii) equidistant location while optimizing MAF, (iv) a combination of MAF, distance from already selected SNPs, and weak LD with the SNP(s) already selected. All animals were genotyped on the Illumina OvineSNP50 Beadchip containing 51,135 SNPs of which 44,040 remained after edits. Within each breed separately, the youngest 100 animals were assumed to represent the validation population; the remaining animals represented the reference population. Imputation was undertaken under three different conditions: (i) SNPs were selected within a given breed and imputed for all breeds individually, (ii) all breeds were collectively used to select SNPs and were included as the reference population, and (iii) the SNPs were selected for each breed separately and imputation was undertaken for all breeds but excluding from the reference population, the breed from which the SNPs were selected. Regardless of SNP selection method, mean animal allele concordance rate improved at a diminishing rate while the variability in mean animal allele concordance rate reduced as the panel density increased. The SNP selection method impacted the accuracy of imputation although the effect reduced as the density of the panel increased. Overall, the most accurate SNP selection method for panels with <9,000 SNPs was that based on MAF and LD pattern within genomic blocks. The mean animal allele concordance rate varied from 0.89 in Texel to 0.97 in Vendeen. Greater imputation accuracy was achieved when SNPs were selected and imputed within each breed individually compared with when SNPs were selected across all breeds and imputed using a multi-breed reference population. In all, results indicate that accurate genotype imputation to medium density is achievable with low-density genotype panels with at least 6,000 SNPs.

Cattle stratified on genetic merit segregate on carcass characteristics, but there is scope for improvement.

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.

Factors associated with the weight of individual primal cuts and their inter-relationship in cattle.

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.