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Attention is increasing on both cow size and body weight (BW) as energy sinks and thus as contributors to differences in production efficiency among cows. What is not currently clear, however, is how cow BW affects the increase in yield per cow per unit increase in genetic merit for milk production. This void in knowledge was filled in the present study using BW data from 20,470 lactations on 16,980 Holstein-Friesian dairy cows stratified into 4 groups on BW adjusted for differences in parity, days in milk, and body condition score. Using linear mixed models that adjusted for nuisance factors, cow phenotypic milk production variables were regressed on estimates of parental average genetic merit for the respective trait within each stratum of BW defined within contemporary group; estimates of genetic merit were from the national genetic evaluations. Both the intercept and linear regression coefficients on genetic merit were compared across BW strata. The intercepts representing the mean phenotypic yield at a genetic merit of zero differed among BW strata; irrespective of yield trait, the least squares means yield per BW stratum increased numerically as cows got heavier, although not every stepwise increase in BW stratum was associated with significantly greater yield compared with the previous (lighter) stratum. Nonetheless, the yield of the cows in the lightest of the 4 strata was always less than that of the heaviest 2 strata; relative to the lightest stratum, cows in the heaviest BW stratum produced only 3 to 4% more yield. Furthermore, the association between phenotypic yield and its respective measures of genetic merit differed by BW stratum; the response to selection for each of the yield traits was 15 to 23% greater for the heaviest stratum of cows compared with their contemporaries in the lightest stratum. Although BW stratum was associated with mean fat and protein concentration after adjusting for differences in genetic merit for fat and protein concentration, the association did not differ by BW stratum for either fat or protein concentration. The effect of BW on efficiency should consider the association between BW and not only mean phenotypic yield at a given genetic merit, but also how the differences in yield diverge as genetic merit increases.

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.

Swyer syndrome is where an individual has the karyotype of a typical male yet is phenotypically a female. The lack of a (functional) SRY gene located on the Y-chromosome is implicated in some cases of the Swyer syndrome, although many Swyer individuals with an apparently fully functional SRY gene have also been documented. The present study undertook whole genome sequence analyses of eight cattle with suspected Swyer syndrome and compared their genome to that of both a control male and female. Sequence analyses coupled with female phenotypes confirmed that all eight individuals had the 60,XY sex reversal Swyer syndrome. Seven of the eight Swyer syndrome individuals had a deletion on the Y chromosome encompassing the SRY gene (i.e., SRY-). The eighth individual had no obvious mutation in the SRY gene (SRY+) or indeed in any reported gene associated with sex reversal in mammals; a necropsy was performed on this individual. No testicles were detected during the necropsy. Histological examination of the reproductive tract revealed an immature uterine body and horns with inactive glandular tissue of normal histological appearance; both gonads were elongated, a characteristic of most reported cases of Swyer in mammals. The flanking sequence of 11 single nucleotide polymorphisms within 10 kb of the SRY gene are provided to help diagnose some cases of Swyer syndrome. These single nucleotide polymorphisms will not, however, detect all cases of Swyer syndrome since, as evidenced from the present study (and other studies), some individuals with the Swyer condition still contain the SRY gene (i.e., SRY+).

Various studies have validated that genetic divergence in dairy cattle translates to phenotypic differences; nonetheless, many studies that consider the breeding goal, or associated traits, have generally been small scale, often undertaken in controlled environments, and they lack consideration for the entire suite of traits included in the breeding goal. Therefore, the objective of the present study was to fill this void, and in doing so, provide producers with confidence that the estimated breeding values (EBV) included in the breeding goal do (or otherwise) translate to desired changes in performance among commercial cattle; an additional outcome of such an approach is the identification of potential areas for improvements. Performance data on 536,923 Irish dairy cows (and their progeny) from 13,399 commercial spring-calving herds were used. Association analyses between the cow's EBV of each trait included in the Irish total merit index for dairy cows (which was derived before her own performance data accumulated) and her subsequent performance were undertaken using linear mixed models; milk production, fertility, calving, maintenance (i.e., liveweight), beef, health, and management traits were all considered in the analyses. Results confirm that excelling in EBV for individual traits, as well as on the total merit index, generally delivers superior phenotypic performance; examples of the improved performance for genetically elite animals include a greater yield and concentration of both milk fat and milk protein, despite a lower milk volume, superior reproductive performance, better survival, improved udder and hoof health, lighter cows, and fewer calving complications; all these gains were achieved with minimal to no effect on the beef merit of the dairy cow's progeny. The associated phenotypic change in each performance trait per unit change in its respective EBV was largely in line with the direction and magnitude of expectation, the exception being for calving interval. Per unit change in calving interval EBV, the direction of phenotypic response was as anticipated but the magnitude of the response was only half of what was expected. Despite the deviation from expectation between the calving interval EBV and its associated phenotype, a superior total merit index or a superior fertility EBV was indeed associated with an improvement in all detailed fertility performance phenotypes investigated. Results substantiate that breeding is a sustainable strategy of improving phenotypic performance in commercial dairy cattle and, by extension, profit.

Because a growing proportion of the beef output in many countries originates from dairy herds, the most critical decisions about the genetic merit of most carcasses harvested are being made by dairy producers. Interest in the generation of more valuable calves from dairy females is intensifying, and the most likely vehicle is the use of appropriately selected beef bulls for mating to the dairy females. This is especially true given the growing potential to undertake more beef × dairy matings as herd metrics improve (e.g., reproductive performance) and technological advances are more widely adopted (e.g., sexed semen). Clear breed differences (among beef breeds but also compared with dairy breeds) exist for a whole plethora of performance traits, but considerable within-breed variability has also been demonstrated. Although such variability has implications for the choice of bull to mate to dairy females, the fact that dairy females themselves exhibit such genetic variability implies that "one size fits all" may not be appropriate for bull selection. Although differences in a whole series of key performance indicators have been documented between beef and beef-on-dairy animals, of particular note is the reported lower environmental hoofprint associated with beef-on-dairy production systems if the environmental overhead of the mature cow is attributed to the milk she eventually produces. Despite the known contribution of beef (i.e., both surplus calves and cull cows) to the overall gross output of most dairy herds globally, and the fact that each dairy female contributes half her genetic merit to her progeny, proxies for meat yield (i.e., veal or beef) are not directly considered in the vast majority of dairy cow breeding objectives. Breeding objectives to identify beef bulls suitable for dairy production systems are now being developed and validated, demonstrating the financial benefit of using such breeding objectives over and above a focus on dairy bulls or easy-calving, short-gestation beef bulls. When this approach is complemented by management-based decision-support tools, considerable potential exists to improve the profitability and sustainability of modern dairy production systems by exploiting beef-on-dairy breeding strategies using the most appropriate beef bulls.

Lactation yield estimates standardized to common lactation lengths of 270-d or 305-d equivalents are commonly used in management decision support tools and dairy cow genetic evaluations. The use of such measurements to quantify the (genetic) merit of individual cows fails to penalize cows that do not reach the standardized lactation length, or indeed reward cows that lactate for more than the standardized lactation length. The objective of the present study was to quantify the genetic and nongenetic factors associated with lactation length in seasonal-calving, pasture-based dairy cows. A total of 616,350 lactation length records from 285,598 Irish cows were used. Linear mixed models were used to quantify the associations between lactation length and calving month, parity, age at calving, previous dry period length, calving difficulty score, heterosis, recombination loss, breed, and herd size, as well as to estimate the genetic and residual variance components of lactation length. The median lactation length in the edited data set was 288 d, with 27% of cows achieving lactations of at least 305 d. Relative to cows calving in January, the lactations of cow calving in February, March, or April was, on average, 4.2, 12.7, and 21.9 d shorter, respectively. The lactation length of a first parity cow was, on average, 7.8, 8.6, and 8.4 d shorter than that of second, third, and fourth parity cows, respectively. Norwegian Red and Montbéliarde cows had, on average, a 4.7- and 1.6-d shorter lactation than Holstein-Friesian cows, respectively. The heritability estimate, coefficient of genetic variation, and repeatability estimate of lactation length were 0.02, 1.2%, and 0.04, respectively. Based on the genetic standard deviation for lactation length estimated in the present study (3.3 d), cows ranked in the top 20% for genetic merit for lactation length would be expected to have lactations 9.2 d longer than cows in the bottom 20%, demonstrating exploitable genetic variability. Given the vast array of genetic and nongenetic factors associated with lactation length, an approach which combines improved management practices and selective breeding may be an efficient and effective strategy to lengthen lactations.

Considerable resources are required to routinely measure detailed milk compositional traits. Hence, an insufficient volume of phenotypic data can hinder genetic progress in these traits within dairy cow breeding programmes. The objective of the present study was to quantify the opportunities for breeding for improved milk protein and free amino acid (FAA) composition by exploiting mid-infrared spectroscopy (MIRS) predictions routinely recorded from milk samples. Genetic parameters for protein fractions and FAA composition were estimated using 134,546 test-day records from 16,166 lactations on 9,572 cows using linear mixed models. Heritability of MIRS-predicted protein fractions ranged from 0.19 (α-lactalbumin) to 0.55 (β-lactoglobulin A), while heritability of MIRS-predicted FAA ranged from 0.08 for glycine to 0.29 for glutamic acid. Genetic correlations among the MIRS-predicted FAA were moderate to strong ranging from −0.44 (aspartic acid and lysine) to 0.97 (glutamic acid and total FAA). Adjustment of the genetic correlations for the genetic merit of 24-h milk yield did not greatly affect the correlations. Results from the current study highlight the presence of exploitable genetic variation for both protein fractions and FAA in dairy cow milk. Besides, the direction of genetic correlations reveals that breeding programmes directly selecting for greater milk protein concentration carry with them favourable improvement in casein and whey fractions.

How animals, particularly livestock, adapt to various climates and environments over short evolutionary time is of fundamental biological interest. Further, understanding the genetic mechanisms of adaptation in indigenous livestock populations is important for designing appropriate breeding programs to cope with the impacts of changing climate. Here, we conducted a comprehensive genomic analysis of diversity, interspecies introgression, and climate-mediated selective signatures in a global sample of sheep and their wild relatives. By examining 600K and 50K genome-wide single nucleotide polymorphism data from 3,447 samples representing 111 domestic sheep populations and 403 samples from all their seven wild relatives (argali, Asiatic mouflon, European mouflon, urial, snow sheep, bighorn, and thinhorn sheep), coupled with 88 whole-genome sequences, we detected clear signals of common introgression from wild relatives into sympatric domestic populations, thereby increasing their genomic diversities. The introgressions provided beneficial genetic variants in native populations, which were significantly associated with local climatic adaptation. We observed common introgression signals of alleles in olfactory-related genes (e.g., ADCY3 and TRPV1) and the PADI gene family including in particular PADI2, which is associated with antibacterial innate immunity. Further analyses of whole-genome sequences showed that the introgressed alleles in a specific region of PADI2 (chr2: 248,302,667–248,306,614) correlate with resistance to pneumonia. We conclude that wild introgression enhanced climatic adaptation and resistance to pneumonia in sheep. This has enabled them to adapt to varying climatic and environmental conditions after domestication.

Much of the research to date on dairy × beef matings has focused only on the greater revenue attainable from these beef-cross calves. The objective of the present study was to quantify the mean effect on cow performance following the birth of calves differing in beef merit; all calves were born without calving assistance. Beef merit in the present study was based on the breed of the sire but also its genetic merit for carcass weight and conformation. The cross-sectional study used up to 346,765 calving events from 230,255 Holstein-Friesian cows in 3,604 herds. Performance traits of interest were those associated with milk production, including somatic cell count, as well as female reproductive performance. Sire breed was associated with all yield traits, somatic cell count, and both pregnancy rate and the interval from calving to first service; no association existed with either submission rate or number of services. Relative to a Holstein-Friesian sire, the mean 305-d milk yield (in kg) was 45.22 (standard error, SE = 4.0), 62.0 (SE = 36.8), 65.4 (SE = 9.6), 101.1 (SE = 31.6), 36.7 (SE = 4.9), 51.5 (SE = 10.7), 53.3 (SE = 31.5), and 43.3 (SE = 23.4) less for cows that gave birth to Angus-, Aubrac-, Beligan Blue-, Charolais-, Hereford-, Limousin-, Saler-, or Simmental-sired calves, respectively. Service sire accounted for only 1% of the phenotypic variation in all 3 milk production traits when fitted as a random effect in the model. The regression coefficients of phenotypic milk, fat, and protein yields on sire (of calf) predicted transmitting ability for carcass weight were -1.84 (SE = 0.17), -0.10 (SE = 0.01), and -0.08 kg (SE = 0.01), respectively. The respective regression coefficients on sire (of calf) predicted transmitting ability for carcass conformation (scale of 1 to 15; 1 = poor and 15 = excellent) were -23.46 (SE = 1.81), -1.20 (SE = 0.08), and -1.05 units (SE = 0.06). The biological significance of the sire breed effects or the measure of sire genetic merit on the reproductive traits was either not different from zero or biologically small. Although statistically significant associations existed between sire beef merit and both milk and reproductive performance of the mate, the actual size of the associations was biologically small.

Heteropaternal superfecundation may be defined as the fertilisation of two or more ova during the same oestrus cycle as a result of more than one coital act from different males; this results in foetuses being born in the same litter of the same age but different paternity. Heteropaternal superfecundation is more likely to occur in poly-ovulatory species like sheep; moreover, female sheep are often mob-mated with several rams concurrently, thus providing an opportunity for a given female to be served by multiple males during the same oestrus cycle. The objective of the present study was to determine the frequency of heteropaternal superfecundation in six sheep flocks where most of the ewes, lambs and rams were genotyped. A total of 685 multiple-birth litters were available where the sire, dam and all lambs were genotyped. Of the 539 pairs of twins included in the analysis, 160 (i.e. 30%) were sired by two different rams. Of the 137 sets of triplets included in the analysis, 73 (i.e. 53%) were sired by more than one ram. Of the nine sets of quadruplets, eight were sired by two rams with the remaining litter being mono-paternal. The overall incidence of heteropaternal superfecundation among litters was therefore 35%. Given that the incidence of multiple births in these flocks was 65%, heteropaternal superfecundation is expected to be relatively common in sheep; this is especially true as all but two of the litter-mates were polyzygotic. Genotyping of progeny is one practical solution to identity such individuals.

Background The trading of individual animal genotype information often involves only the exchange of the called genotypes and not necessarily the additional information required to effectively call structural variants. The main aim here was to determine if it is possible to impute copy number variants (CNVs) using the flanking single nucleotide polymorphism (SNP) haplotype structure in cattle. While this objective was achieved using high-density genotype panels (i.e., 713,162 SNPs), a secondary objective investigated the concordance of CNVs called with this high-density genotype panel compared to CNVs called from a medium-density panel (i.e., 45,677 SNPs in the present study). This is the first study to compare CNVs called from high-density and medium-density SNP genotypes from the same animals. High (and medium-density) genotypes were available on 991 Holstein-Friesian, 1015 Charolais, and 1394 Limousin bulls. The concordance between CNVs called from the medium-density and high-density genotypes were calculated separately for each animal. A subset of CNVs which were called from the high-density genotypes was selected for imputation. Imputation was carried out separately for each breed using a set of high-density SNPs flanking the midpoint of each CNV. A CNV was deemed to be imputed correctly when the called copy number matched the imputed copy number. Results For 97.0% of CNVs called from the high-density genotypes, the corresponding genomic position on the medium-density of the animal did not contain a called CNV. The average accuracy of imputation for CNV deletions was 0.281, with a standard deviation of 0.286. The average accuracy of imputation of the CNV normal state, i.e. the absence of a CNV, was 0.982 with a standard deviation of 0.022. Two CNV duplications were imputed in the Charolais, a single CNV duplication in the Limousins, and a single CNV duplication in the Holstein-Friesians; in all cases the CNV duplications were incorrectly imputed. Conclusion The vast majority of CNVs called from the high-density genotypes were not detected using the medium-density genotypes. Furthermore, CNVs cannot be accurately predicted from flanking SNP haplotypes, at least based on the imputation algorithms routinely used in cattle, and using the SNPs currently available on the high-density genotype panel.

Knowledge of population structure and breed composition of a population can be advantageous for a number of reasons; these include designing optimal (cross)breeding strategies in order to maximise non-additive genetic effects, maintaining flockbook integrity by authenticating animals being registered and as a quality control measure in the genotyping process. The objectives of the present study were to 1) describe the population structure of 24 sheep breeds, 2) quantify the breed composition of both flockbook-recorded and crossbred animals using single nucleotide polymorphism BLUP (SNP-BLUP), and 3) quantify the accuracy of breed composition prediction from low-density genotype panels containing between 2000 and 6000 SNPs. In total, 9334 autosomal SNPs on 11 144 flockbook-recorded animals and 1172 crossbred animals were used. The population structure of all breeds was characterised by principal component analysis (PCA) as well as the pairwise breed fixation index (Fst). The total number of animals, all of which were purebred, included in the calibration population for SNP-BLUP was 2579 with the number of animals per breed ranging from 9 to 500. The remaining 9559 flockbook-recorded animals, composite breeds and crossbred animals represented the test population; three breeds were excluded from breed composition prediction. The breed composition predicted using SNP-BLUP with 9334 SNPs was considered the gold standard prediction. The pairwise breed Fst ranged from 0.040 (between the Irish Blackface and Scottish Blackface) to 0.282 (between the Border Leicester and Suffolk). Principal component analysis revealed that the Suffolk from Ireland and the Suffolk from New Zealand formed distinct, non-overlapping clusters. In contrast, the Texel from Ireland and that from New Zealand formed integrated, overlapping clusters. Composite animals such as the Belclare clustered close to its founder breeds (i.e., Finn, Galway, Lleyn and Texel). When all 9334 SNPs were used to predict breed composition, an animal that had a majority breed proportion predicted to be ≥0.90 was defined as purebred for the present study. As the panel density decreased, the predicted breed proportion threshold, used to identify animals as purebred, also decreased (≥0.85 with 6000 SNPs to ≥0.60 with 2000 SNPs). In all, results from the study suggest that breed composition for purebred and crossbred animals can be determined with SNP-BLUP using ≥5000 SNPs.

In growing cattle, the phenotypic and genetic relationships between feeding behavior and both live animal ultrasound measures and subsequent carcass merit are generally poorly characterized. The objective of the current study was to quantify the phenotypic and genetic associations between a plethora of feeding behavior traits with both pre-slaughter ultrasound traits and post-slaughter carcass credentials in crossbred Bos taurus cattle. Carcass data were available on 3,146 young bulls, steers, and heifers, of which 2,795 and 2,445 also had records for pre-slaughter ultrasound muscle depth and intramuscular fat percentage, respectively; a total of 1,548 steers and heifers had information on all of the feeding behavior, ultrasound, and carcass traits. Young bulls were fed concentrates, while steers and heifers were fed a total mixed ration. Feeding behavior traits were defined based on individual feed events or meal events (i.e., individual feed events grouped into meals). Animal linear mixed models were used to estimate (co)variance components. Phenotypic correlations between feeding behavior and both ultrasound and carcass traits were generally weak and not different from zero, although there were phenotypic correlations of 0.40, 0.26, and 0.37 between carcass weight and feeding rate, energy intake per feed event, and energy intake per meal, respectively. Genetically, cattle that had heavier carcass weights, better carcass conformation, or a higher dressing percentage fed for a shorter time per day (genetic correlations [±SE] of −0.46 ± 0.12, −0.39 ± 0.11, and −0.50 ± 0.10, respectively). Genetic correlations of 0.43 ± 0.12 and 0.68 ± 0.13 were estimated between dressing difference (i.e., differential between live weight pre-slaughter and carcass weight) and energy intake per feed event and energy intake per meal, respectively. Neither intramuscular fat percentage measured on live animals nor carcass fat score (i.e., a measure of subcutaneous fat cover of the carcass) was genetically associated with any of the feeding behavior traits. The genetic associations between some feeding behavior traits and both ultrasound and carcass traits herein suggested that indirect responses in the feeding behavior of growing cattle from selection for improved carcass merit would be expected. Such changes in feeding behavior patterns in cattle may be reduced by measuring and including feeding behavior in a multiple-trait selection index alongside carcass traits.

Made available in DSpace on 2022-05-01T10:18:55Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-12-01 The Canchim composite breed was developed in Brazil combining the attributes of adaptation to the tropical environment of the Nelore breed with the growth performance of the Charolais breed. We aimed to identify overlapping haplotype blocks between Canchim and Nelore and Canchim and Charolais and, in doing so, characterize those haploblocks identified in each founder breeds that were shared with the Canchim. Haploblocks that were in overlap revealed segments of 418.29 kb (chromosome 13) and 553.17 kb (chromosome 19) between Canchim and Nelore; and 407.51 kb (chromosome 5), 419.72 kb (chromosome 8), and 578.51 kb (chromosome 10) between Canchim and Charolais. Long segments of shared haploblocks revealed genes associated with productive and reproductive traits. Furthermore, these segments include genes with functions associated with the immune system, disease resistance, and adaptability, being highlighted as important results for beef cattle raised in tropical conditions. The use of genomic data from founder breeds can assist to understand the genetic composition of Canchim and contribute to future studies on genome-wide association and genomic selection using a multi-breed evaluation. Departamento de Zootecnia Universidade Federal da Paraíba Embrapa Southeast Livestock Teagasc Animal and Grassland Research and Innovation Centre, Fermoy Co., Moorepark Departamento de Engenharia e Ciências Exatas Universidade Estadual Paulista Departamento de Engenharia e Ciências Exatas Universidade Estadual Paulista

The identification of different meat cuts for labeling and quality control on production lines is still largely a manual process. As a result, it is a labor-intensive exercise with the potential for not only error but also bacterial cross-contamination. Artificial intelligence is used in many disciplines to identify objects within images, but these approaches usually require a considerable volume of images for training and validation. The objective of this study was to identify five different meat cuts from images and weights collected by a trained operator within the working environment of a commercial Irish beef plant. Individual cut images and weights from 7,987 meats cuts extracted from semimembranosus muscles (i.e., Topside muscle), post editing, were available. A variety of classical neural networks and a novel Ensemble machine learning approaches were then tasked with identifying each individual meat cut; performance of the approaches was dictated by accuracy (the percentage of correct predictions), precision (the ratio of correctly predicted objects relative to the number of objects identified as positive), and recall (also known as true positive rate or sensitivity). A novel Ensemble approach outperformed a selection of the classical neural networks including convolutional neural network and residual network. The accuracy, precision, and recall for the novel Ensemble method were 99.13%, 99.00%, and 98.00%, respectively, while that of the next best method were 98.00%, 98.00%, and 95.00%, respectively. The Ensemble approach, which requires relatively few gold-standard measures, can readily be deployed under normal abattoir conditions; the strategy could also be evaluated in the cuts from other primals or indeed other species.

Understanding dairy producer mindset in service sire selection can provide useful information for different junctures along the commercial and extension animal breeding chain. It can aid the targeted marketing of bulls based on farm production systems but also provide useful information for delivering bespoke extension services. The objective of the present study was to examine if differences exist among dairy producers in their choice of dairy and beef service sires depending on the life stage at which the surplus progeny generated from such matings exit the dairy farm. This was predominantly based on evaluating the breed of beef sires used but also their genetic merit for calving difficulty and carcass traits, namely, carcass weight, conformation, and fat score; differences in genetic merit among dairy sires as well as among the dairy cows themselves were also considered. The objective was accomplished through the cross-sectional analyses of progeny fate data from 1,092,403 progeny born in 4,117 Irish dairy herds. Herd-years were categorized into one of four systems based on when the surplus progeny exited the dairy farm: (1) calves sold

To the best of our knowledge, the genetic variability in feeding behavior, as well as relationships with performance and feed efficiency, has not been investigated in a cattle population of greater than 1,500 animals. Our objective was to quantify the genetic parameters of several feeding behavior traits, and their genetic associations with both performance and feed efficiency traits, in crossbred growing cattle. Feed intake and live-weight data were available on 6,088 bulls, steers and heifers; of these, 4,672 cattle had backfat and muscle ultrasound data, and 1,548 steers and heifers had feeding behavior data. Genetic (co)variance parameters were estimated using animal linear mixed models; fixed effects included test group, heterosis, recombination loss, dam parity, age in months at the end of test, and the two-way interaction between age in months at the end of test and sex. Heritability was estimated to be 0.51 (0.097), 0.61 (0.100), 0.44 (0.093), 0.48 (0.094), and 0.47 (0.095) for feed events per day, feeding time per day, feeding rate, feed event duration, and energy intake per feed event, respectively. Coefficients of genetic variation ranged from 0.11 (feeding time per day) to 0.22 (feed event duration). Genetically heavier cattle with a higher energy intake per day, and faster growth rate, had a faster feeding rate and a greater energy intake per feed event. Genetic correlations between feeding behavior and feed efficiency were generally not different from zero, however, there was a genetic correlation of 0.36 (0.11) between feeding time per day and residual energy intake. Significant heritable and exploitable genetic variation exists in several feeding behavior traits in crossbred growing cattle which are also correlated with several performance traits. As some feeding behavior traits may be relatively less resource intensive to measure, they could be useful as predictor traits in beef cattle genetic evaluations.

The objectives of the present study were to estimate genetic parameters for several feeding behavior traits in growing cattle, as well as the genetic associations among and between feeding behavior and both performance and feed efficiency traits. An additional objective was to investigate the use of feeding behavior traits as predictors of genetic merit for feed intake. Feed intake and live-weight data on 6,088 growing cattle were used of which 4,672 had ultrasound data and 1,548 had feeding behavior data. Feeding behavior traits were defined based on individual feed events or meal events (where individual feed events were grouped into meals). Univariate and bivariate animal linear mixed models were used to estimate (co)variance components. Heritability estimates (± SE) for the feeding behavior traits ranged from 0.19 ± 0.08 for meals per day to 0.61 ± 0.10 for feeding time per day. The coefficient of genetic variation per trait varied from 5% for meals per day to 22% for the duration of each feed event. Genetically heavier cattle, those with a higher daily energy intake (MEI), or those that grew faster had a faster feeding rate, as well as a greater energy intake per feed event and per meal. Better daily feed efficiency (i.e., lower residual energy intake) was genetically associated with both a shorter feeding time per day and shorter meal time per day. In a validation population of 321 steers and heifers, the ability of estimated breeding values (EBV) for MEI to predict (adjusted) phenotypic MEI was demonstrated; EBVs for MEI were estimated using multi-trait models with different sets of predictor traits such as liveweight and/or feeding behaviors. The correlation (± SE) between phenotypic MEI and EBV for MEI marginally improved (P < 0.001) from 0.64 ± 0.03 to 0.68 ± 0.03 when feeding behavior phenotypes from the validation population were included in a genetic evaluation that already included phenotypic mid-test metabolic live-weight from the validation population. This is one of the largest studies demonstrating that significant exploitable genetic variation exists in the feeding behavior of young crossbred growing cattle; such feeding behavior traits are also genetically correlated with several performance and feed efficiency metrics. Nonetheless, there was only a marginal benefit to the inclusion of time-related feeding behavior phenotypes in a genetic evaluation for MEI to improve the precision of the EBVs for this trait.

The objective of the present study was to determine if animals who were genetically divergent in the predicted tenderness of their meat actually produced more tender meat, as well as what the implications were for other organoleptic properties of the meat. The parental average genetic merit for meat tenderness was used to locate 20 “Tough genotype” heifers and 17 “Tender genotype” heifers, M. longissimus thoracis steaks from all heifers were subjected to sensory affective analysis (140 consumers) and sensory profiling using two trained sensory panels. All sample steaks were treated identically regarding pre- and post-mortem handling, storage, cooking and presentation (i.e., randomised, blind coded). For the affective consumer study, eight steaks were sectioned from the same location of the striploin muscles from each of the heifers. In total, 108 steaks from the Tender genotype and 118 from the Tough genotype were tested in the consumer study to determine the preference or liking of these steaks for appearance, aroma, flavour, tenderness, juiciness and overall acceptability. The consumer study found that the Tender genotype scored higher (p &lt, 0.0001) for liking of tenderness, juiciness, flavour and overall acceptability compared to the Tough genotype. Similar results were generally found for the separate consumer age cohorts (18–64 years) with lower sensory acuity in the 65+ age cohort. For the descriptive analysis, the Tender genotype scored numerically more tender, juicy and flavoursome, although the differences were only significant for one of the panels. The critical outcome from this study is that parental average genetic merit can be used to pre-select groups of animals for tenderness, which, in turn, can be detected by consumers.

Information on body weight and average daily gain (ADG) of growing animals is key not only to monitoring performance, but also for use in genetic evaluations in the pursuit of achieving sustainable genetic gain. Accurate calculation of ADG, however, requires serial measures of body weight over at least 70 days. This can be resource intensive and thus alternative approaches to predicting individual animal ADG warrant investigation. One such approach is the use of continuously collected individual animal partial body weights. The objective of the present study was to determine the utility of partial body weights in predicting both body weight and ADG; a secondary objective was to deduce the appropriate length of test to determine ADG from partial body weight records. The dataset used consisted of partial body weights, predicted body weights and recorded body weights recorded for 8,972 growing cattle from a range of different breed types in 35 contemporary groups. The relationships among partial body weight, predicted body weight and recorded body weight at the beginning and end of the performance test were determined and calculated ADG per animal from each body weight measure were also compared. On average, partial body weight explained 90.7 ± 2.0% of the variation in recorded body weight at the beginning of the postweaning gain test and 87.9 ± 2.9% of the variation in recorded body weight at its end. The GrowSafe proprietary algorithm to predict body weight from the partial body weight strengthened these coefficients of determination to 95.1 ± 0.9% and 94.9 ± 0.8%, respectively. The ADG calculated from the partial body weight or from the predicted body weight were very strongly correlated (r = 0.95); correlations between these ADG values with those calculated from the recorded body weights were weaker at 0.81 and 0.78, respectively. For some applications, ADG may be measured with sufficient accuracy with a test period of 50 days using partial body weights. The intended inference space is to individual trials which have been represented in this study by contemporary groups of growing cattle from different genotypes.

Validation of beef total merit breeding indexes for improving performance and profitability has previously been undertaken at the individual animal level; however, no herd-level validation of beef genetic merit and profit has been previously investigated. The objective of the present study was to quantify the relationship between herd profitability and both herd-average terminal and maternal genetic merit across 1,311 commercial Irish beef herds. Herd-level physical and financial performance data were available from a financial benchmarking tool used by Irish farmers and their extension advisors. Animal genetic merit data originated from the Irish Cattle Breeding Federation who undertake the national beef and dairy genetic evaluations. Herd-average genetic merit variables included the terminal index of young animals, the maternal index of dams, and the terminal index of service sires. The herds represented three production systems: 1) cow-calf to beef, 2) cow-calf to weanling/yearling, and 3) weanling/yearling to beef. Associations between herd financial performance metrics and herd average genetic merit variables were quantified using a series of linear mixed models with year, production system, herd size, stocking rate, concentrate input, and the two-way interactions between production system and herd size, stocking rate, and concentrate input included as nuisance factors. Herd nested within the county of Ireland (n = 26) was included as a repeated effect. Herds with young cattle excelling in terminal index enjoyed greater gross and net profit per hectare (ha), per livestock unit (LU), and per kg net live-weight output. The change in gross profit per LU per unit change in the terminal index of young animals was €1.41 (SE = 0.23), while the respective regression coefficient for net profit per LU was €1.37 (SE = 0.30); the standard deviation of the terminal index is €37. Herd-average dam maternal index and sire terminal index were both independently positively associated with gross profit per ha and gross profit per LU. Each one unit increase in dam maternal index (standard deviation of €38) was associated with a €1.40 (SE = 0.48) and €0.76 (SE = 0.29) greater gross profit per ha and per LU, respectively. Results from the present study at the herd-level concur with previous validation studies at the individual animal level thus instilling further confidence among stakeholders as to the expected improvement in herd profitability with improving genetic merit.

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.

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.

This study investigated the effects of alternative mating programs that incorporate genomic information on expected progeny herd performance and inbreeding, as well as methods to include un-genotyped animals in such mating programs. A total of 54,535 Holstein-Friesian cattle with imputed high-density genotypes (547,650 SNP after edits) were available. First, to quantify the accuracy of imputing un-genotyped animals (often an issue in populations), a sub-population of 729 genotyped animals had their genotypes masked, and their allele dosages were imputed, using linear regression exploiting information on genotyped relatives. The reference population for imputation included all genotyped animals, excluding the 729 selected animals and their sires, dams, and grandsires, and had either (1) their sires' genotypes, (2) their dams' genotypes (3) both their sires' and their dams' genotypes, or (4) both their sires' and maternal grandsires' genotypes introduced into the reference population. The correlations between true genotypes and the imputed allele dosages ranged from 0.58 (sire only) to 0.68 (both sire and dam). A herd of 100 cows was then simulated (1,000 replicates) from the sub-population of 729 imputed animals. The top 10 bulls from the genotyped population, based on their total genetic merit index (TMI) were selected to be used as sires. Three mating allotment methods were investigated: (1) random mating, (2) sequential mating based on maximizing only the expected TMI of the progeny, and (3) linear programming to maximize a generated index constructed to maximize genetic merit and minimize expected progeny inbreeding as well as intra- and inter-progeny variability in genetic merit. Relationships among candidate parents were calculated using either the pedigree relationship matrix or the genomic relationship matrix; the latter was constructed using either the true genotypes of both parents or the true genotypes of the sire plus the imputed allele dosages of the dam. Using the genomic co-ancestry estimates resulted in lower average herd expected genomic inbreeding levels compared with using the pedigree-based co-ancestry estimates. Additionally, if the dams were not genotyped, using their imputed allele dosages also resulted in lower average herd expected inbreeding levels compared with using the pedigree co-ancestry estimates. The inter-progeny coefficient of variation for selected traits, milk and fertility, estimated breeding values were reduced by 12 to 65% using the linear programing method compared with sequential mating.

peer-reviewed Teagasc Publication Irish Journal of Agricultural and Food Research | Volume 58: Issue 1 Prediction of 24-hour milk yield and composition in dairy cows from a single part-day yield and sample S. McParlandemail , B. Coughlan , B. Enright , M. O’Keeffe , R. O’Connor , L. Feeney and D.P. Berry DOI: https://doi.org/10.2478/ijafr-2019-0007 | Published online: 09 Aug 2019 PDF       Abstract Article PDF References Recommendations Abstract The objective was to evaluate the accuracy of predicting 24-hour milk yield and composition from a single morning (AM) or evening (PM) milk weight and composition. A calibration dataset of 37,481 test-day records with both AM and PM yields and composition was used to generate the prediction equations; equations were validated using 4,644 test-day records. Prediction models were developed within stage of lactation and parity while accounting for the inter-milking time interval. The mean correlation between the predicted 24-hour yields and composition of milk, fat and protein and the respective actual values was 0.97 when based on just an AM milk yield and composition with a mean correlation of 0.95 when based on just a PM milk yield and composition. The regression of predicted 24-hour yield and composition on the respective actual values varied from 0.97 to 1.01 with the exception of 24-hour fat percentage predicted from a PM sample (1.06). A single AM sample is useful to predict 24-hour milk yield and composition when the milking interval is known.

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.