Impact on prime animal beef merit from breeding solely for lighter dairy cows.

As the proportion of prime carcasses originating from dairy herds increases, the focus is shifting to the beef merit of the progeny from dairy herds. Several dairy cow total merit indexes include a negative weight on measures of cow size. However, there is a lack of knowledge on the impact of genetic selection, solely for lighter or smaller-sized dairy cows, on the beef performance of their progeny. Therefore, the objective of this study was to quantify the genetic correlations among cow size traits (i.e., cow body weight (BW), cow carcass weight (CW)), cow body condition score (BCS), cow carcass conformation (CC), and cow carcass fat cover (CF), as well as the correlations between these cow traits and a series of beef performance slaughter-related traits (i.e., CW, CC, CF, and age at slaughter (AS)) in their progeny. After data editing, there were 52,950 cow BW and BCS records, along with 57,509 cow carcass traits (i.e., CW, CC, and CF); carcass records from 346,350 prime animals along with AS records from 316,073 prime animals were also used. Heritability estimates ranged from moderate to high (0.18 to 0.62) for all cow and prime animal traits. The same carcass trait in cows and prime animals were strongly genetically correlated with each other (0.76 to 0.85), implying that they are influenced by very similar genomic variants. Selecting exclusively for cows with higher BCS (i.e., fatter) will, on average, produce more conformed prime animals carcasses, owing to a moderate genetic correlation (0.30) between both traits. Genetic correlations revealed that selecting exclusively for lighter BW or CW cows will, on average, result in lighter prime animal carcasses of poor CC, while also delaying slaughter age. Nonetheless, selective breeding through total merit indexes should be successful in breeding for smaller dairy cows, and desirable prime animal carcass traits concurrently, because of the non-unity genetic correlations between the cow and prime animal traits; this will help to achieve a more ethical, environmentally sustainable, and economically viable dairy-beef industry.

Choice of artificial insemination beef bulls used to mate with female dairy cattle.

Understanding the preferences of dairy cattle producers when selecting beef bulls for mating can help inform beef breeding programs as well as provide default parameters in mating advice systems. The objective of the present study was to characterize the genetic merit of beef artificial insemination (AI) bulls used in dairy herds, with particular reference to traits associated with both calving performance and carcass merit. The characteristics of the beef AI bulls used were compared with those of the dairy AI bulls used on the same farms. A total of 2,733,524 AI records from 928,437 females in 5,967 Irish dairy herds were used. Sire predicted transmitting ability (PTA) values and associated reliability values for calving performance and carcass traits based on national genetic evaluations from prior to the insemination were used. Fixed effects models were used to relate both genetic merit and the associated reliability of the dairy and beef bulls used on the farm with herd size, the extent of Holstein-Friesian × Jersey crossbreeding adopted by the herd, whether the herd used a technician insemination service or do-it-yourself, and the parity of the female mated. The mean direct calving difficulty PTA of the beef bulls used was 1.85 units higher than that of the dairy bulls but with over 3 times greater variability in the beef bulls. This 1.85 units equates biologically to an expectation of 1.85 more dystocia events per 100 dairy cows mated in the beef × dairy matings. The mean calving difficulty PTA of the dairy AI bulls used reduced with increasing herd size, whereas the mean calving difficulty PTA of the beef AI bulls used increased as herd size increased from 75 cows or fewer to 155 cows; the largest herds (>155 cows) used notably easier-calving beef bulls, albeit the calving difficulty PTA of the beef bulls was 3.33 units versus 1.67 units for the dairy bulls used in these herds. Although we found a general tendency for larger herds to use dairy AI bulls with lower reliability, this trend was not obvious in the beef AI bulls used. Irrespective of whether dairy or beef AI bulls were considered, herds that operated more extensive Holstein-Friesian × Jersey crossbreeding (i.e., more than 50% crossbred cows) used, on average, easier calving, shorter gestation-length bulls with lighter expected progeny carcasses of poorer conformation. Mean calving difficulty PTA of dairy bulls used increased from 1.39 in heifers to 1.79 in first-parity cows and to 1.82 in second-parity cows, remaining relatively constant thereafter. In contrast, the mean calving difficulty PTA of the beef bulls used increased consistently with cow parity. Results from the present study demonstrate a clear difference in the mean acceptable genetic merit of beef AI bulls relative to dairy AI bulls but also indicates that these acceptable limits vary by herd characteristics.

Genetic selection for hoof health traits and cow mobility scores can accelerate the rate of genetic gain in producer-scored lameness in dairy cows.

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.

Differences in the choice of beef artificial insemination sires used by dairy producers versus beef producers.

The growing demand among dairy producers for suitable beef sires to mate to their females creates the possibility of separate breeding programs to generate beef sires for the dairy sector versus those for the beef sector. Informing such a decision is the extent of the genetic differences among beef sires used by dairy producers relative to those used by beef producers. The objective therefore of the present study was to use a large national database of artificial insemination (AI) records in dairy and beef cow herds to establish the difference in mean genetic merit of beef AI sires used by dairy producers versus those used by cow-calf beef producers. The traits explored were gestation length, calving difficulty, and perinatal mortality as well as the 3 carcass traits of carcass weight, conformation, and fat score. Carcass conformation and fat score are mechanically assessed on a scale of 1 (poor conformation and low fat cover) to 15 (excellent conformation and high fat cover). Sire genetic merit differences for feed intake and docility were also examined. Estimates of genetic merit for all 8 traits on individual AI sires available at the time of service were used. A total of 1,230,622 AI records comprised 909,719 services from dairy herds and 320,903 services from beef herds were used. Of the 1,802 beef AI sires represented in the entire dataset, over half were used by both dairy and beef herds representing ≥98% of the services in each production system. However, the usage rate of individual AI sires differed between dairy and beef herds with the Spearman rank correlation between the quantity of inseminations per sire in dairy and beef herds being just 0.38. This correlation means that beef AI sires used heavily in the beef herd were not always those heavily used in dairy herds. A clear difference in the mean genetic merit of beef AI sires selected by dairy producers relative to those selected by beef cow-calf producers was obvious with the extent of the difference being a function of whether the female served was a nulliparous heifer or a cow. Much of the differences in genetic merit of chosen beef AI sires between dairy and beef producers was actually attributable to differences in breed choice, albeit some within-breed selection was also evident. Irrespective, dairy producers, on average, chose shorter gestation length sires whose progeny were genetically less predisposed to require intervention during the birthing process; these sires had genetic merit estimates expected to result in lighter and less conformed progeny carcasses relative to the beef AI sires used by beef producers. Results point to large differences in genetic merit of the beef AI sires chosen by dairy versus beef producers, much of which actually reflected differences in breed choice among dairy and beef producers.

Quantifying genetic differences between exported dairy bull calves and those sold for domestic beef production.

Selection bias is introduced when selection among individuals exists but the information used to inform that selection decision is not considered in downstream genetic evaluations. Genetic evaluations are undertaken in several countries for carcass-related metrics in prime cattle; no consideration is generally taken for animals that are harvested at a younger age for veal production and thus do not express the prime carcass phenotype. Although no veal industry exists in Ireland, dairy calves are routinely exported to continental Europe for veal production. The objective of the present study, based on a cross-sectional analysis of calf export data, was to determine quantitatively if genetic variability exists in whether purchased dairy-bred bull calves are immediately exported or retained within the country for domestic production. Also of interest was whether such a genetic difference was associated with differences in carcass weight, conformation score, and fat score in prime cattle relatives. Editing criteria were imposed to consider only Holstein-Friesian bull calves. Post-editing, the fate of 43,890 Holstein-Friesian bull calves (<100 d of age) was available; variance components for the binary phenotype (sold for export or not) were estimated using both linear and threshold animal models, and genetic correlations with carcass traits from 56,366 prime cattle were estimated. The heritability (standard error) of whether or not a calf was exported was 0.04 (0.01) on the linear scale and 0.07 (0.02) on the threshold scale. Although no explicit maternal genetic effect was detected, the proportion of the phenotypic variance due to maternal effects was 0.03 to 0.07. The genetic correlation (standard error) between the export phenotype with carcass weight, conformation score [scale 1 (poor) to 15 (excellent)], and fat score [scale 1 (thin) to 15 (fat)] in prime cattle was 0.002 (0.12), -0.25 (0.12), and -0.32 (0.11), respectively. The low heritability of the calf export phenotype and lack of a strong genetic correlation with carcass metrics suggest that other calf features might be greater determinants of the eventual fate of the calf. Accounting for the export phenotype in genetic evaluations of carcass traits in prime cattle had a negligible effect on the estimated breeding values for carcass merit.

Genetic parameters for both a liver damage phenotype caused by and antibody response to phenotype in dairy and beef cattle.

is a helminth parasite of economic importance to the global cattle industry, with documented high international herd prevalence. The objective of the present study was to generate the first published genetic parameter estimates for liver damage caused by as well as antibody response to in cattle. Abattoir data on the presence of live , or -damaged livers, were available between the years 2012 and 2015, inclusive. A second data set was available on cows from 68 selected dairy herds with a blood ELISA test for antibody response to in autumn 2015. Animals were identified as exposed by using herd mate phenotype, and only exposed animals were retained for analysis. The abattoir data set consisted of 20,481 dairy cows and 75,041 young dairy and beef animals, whereas the study herd data set consisted of 6,912 dairy cows. (Co)variance components for phenotypes in both data sets were estimated using animal linear mixed models. Fixed effects included in the model for both data sets were contemporary group, heterosis coefficient, recombination loss coefficient, parity, age relative to parity/age group, and stage of lactation. An additional fixed effect of abattoir by date of slaughter was included in the model for the analysis of the abattoir data. Direct additive genetic effects and a residual effect were included as random effects for all analyses. After data edits, the prevalence of liver damage caused by in cows and young cattle was 47% and 20%, respectively. The prevalence of a positive antibody response to in cows from the study herd data was 36% after data edits. The heritability of as a binary trait for dairy cows in abattoir data and study herd data was 0.03 ± 0.01 and 0.09 ± 0.02, respectively; heritability in young cattle was 0.01 ± 0.005. The additive genetic SD of as a binary trait was 0.069 and 0.050 for cows and young cattle from the abattoir data, respectively, and 0.112 from the study herd cows. The genetic correlation between liver damage caused by in young cattle and cows from the abattoir data was 0.94 ± 0.312 and the genetic correlation between liver damage caused by in cows and positive antibody response to in cows in the study herd data was 0.37 ± 0.283.