Exploring definitions of daily enteric methane emission phenotypes for genetic evaluations using a population of indoor-fed multi-breed growing cattle with feed intake data.

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 ±â€…0.03 for the individual spot measures trait to 0.43 ±â€…0.11 for the full test average trait; a similar trend existed for CO2 with the estimated heritability ranging from 0.17 ±â€…0.04 to 0.50 ±â€…0.11. Enteric CH4 was moderately to strongly genetically correlated with DMI with a genetic correlation of 0.72 ±â€…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.

Livestock production is a significant contributor to greenhouse gas emissions. Animal breeding programs have been proposed as a sustainable mitigation strategy to reduce enteric methane emissions in livestock production. Before creating a genetic evaluation for enteric methane production, it is important to estimate how much inter-animal genetic variability contributes to the observed differences in enteric methane production. The purpose of this study was to explore multiple enteric methane phenotypes and estimate how much phenotypic variation was due to genetic differences among 1,508 growing cattle of multiple breeds and crosses; also of interest was the extent of similarity in the genetic control of enteric methane, carbon dioxide, and feed intake (i.e., the genetic correlation) and to determine if selection of animals on the estimated genetic merit for methane emissions of their parents would manifest itself in differences in actual methane produced by those animals. Between 9% and 43% of the inter-animal differences in daily enteric methane production were due to differences in the genetic composition of those animals; the genetic control influencing methane production was similar to that of feed intake (i.e., a strong genetic correlation between methane emissions and feed intake of up to 0.72).

Variation in the proportion of the segregating genome shared between full-sibling cattle and sheep.

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.

Phenotypic relationship and repeatability of methane emissions and performance traits in beef cattle using a GreenFeed system.

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.

Methane production from cattle digestion 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 of economic importance. Methane and carbon dioxide emissions recorded using Greenfeed systems were available on a total of 1,099 animals. In addition, performance indicators such as feed intake, live weight, ultrasound scanning data, and slaughter data were also available on all animals. Phenotypic repeatability of CH4 ranged from 0.13 to 0.74, with a CH4 repeatability of >0.6 achieved by both heifers and steers in 10-d measuring period. Due to the high repeatability of CH4 measures, an accurate portrayal of CH4 production can be observed from a 10-d measuring period when measures are averaged. Methane emission data were positively correlated with traits of economic importance. Phenotypically, animals with heavier body weights and greater feed intake had higher emissions.

Validation of maternal and terminal sheep breeding objectives using Irish field data.

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.

Predicting carcass cut yields in cattle from digital images using artificial intelligence.

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.

Genetic and nongenetic factors associated with the fate of maiden ewe lambs: slaughtered without ever lambing versus retained for breeding.

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.

Phenotypic factors associated with lamb live weight and carcass composition measurements in an Irish multi-breed sheep population.

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.

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.

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.

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.

A novel measure of ewe efficiency for breeding and benchmarking purposes.

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.