Methane (CH₄) is a greenhouse gas that is produced and emitted from ruminant animals through enteric fermentation. Methane production from cattle has an environmental impact and is an energetic inefficiency. In the beef industry, CH₄ production from enteric fermentation impacts all three pillars of sustainability: environmental, social, and economic. A variety of factors influence the quantity of CH₄ produced during enteric fermentation, including characteristics of the rumen and feed composition. There are several methodologies available to either quantify or estimate CH₄ production from cattle, all with distinct advantages and disadvantages. Methodologies include respiration calorimetry, the sulfur-hexafluoride tracer technique, infrared spectroscopy, prediction models, and the GreenFeed system. Published studies assess the accuracy of the various methodologies and compare estimates from different methods. There are advantages and disadvantages of each technology as they relate to the use of these phenotypes in genetic evaluation systems. Heritability and variance components of CH₄ production have been estimated using the different CH₄ quantification methods. Agreement in both the amounts of CH₄ emitted and heritability estimates of CH₄ emissions between various measurement methodologies varies in the literature. Using greenhouse gas traits in selection indices along with relevant output traits could provide producers with a tool to make selection decisions on environmental sustainability while also considering productivity. The objective of this review was to discuss factors that influence CH₄ production, methods to quantify CH₄ production for genetic evaluation, and genetic parameters of CH₄ production in beef cattle. Enteric methane production from beef cows is a sustainability concern for the industry. A wide range of factors impact the amount of methane produced by individual animals. Dietary factors include but are not limited to, rumen conditions, dietary lipids, feed type and processing, alternative hydrogen sinks, ionophores, and rumen microbiome composition. The amount of methane produced by individual animals can be quantified with several methodologies including respiration calorimetry, the sulfur-hexafluoride tracer technique, infrared spectroscopy, prediction models, and the GreenFeed system. The accuracy of each method and comparisons between the methods have been published in the literature. Each of the methodologies has distinct advantages and disadvantages for the purpose of phenotype collection for genetic evaluations. The heritability of enteric methane production from phenotypes collected with the various methods varies but is generally moderately heritable. Genetic correlations between different methane production traits and between methane production and performance have been evaluated but are relatively limited in the literature.

Background: Cattle production is dependent upon fertility because it results in producing offspring to offset production costs. A number of semen attributes are believed to affect fertility and are frequently measured as part of routine breeding soundness exams or semen collection procedures. The objective of this study was to perform a single-step genome-wide association study (ssGWAS) for beef bull semen attributes. Beef bull fertility phenotypes including volume (VOL), concentration (CONC), number of spermatozoa (NSP), initial motility (IMot), post-thaw motility (PTMot), three-hour post-thaw motility (3HRPTMot), percentage of normal spermatozoa (%NORM), primary abnormalities (PRIM), and secondary abnormalities (SEC) were obtained from two artificial insemination (AI) centers. A total of 1819 Angus bulls with 50,624 collection records were used for ssGWAS. A five-generation pedigree was obtained from the American Angus Association and consisted of 6521 sires and 17,136 dams. Genotypes on 1163 bulls were also obtained from the American Angus Association and utilized in ssGWAS. Results: A multi-trait animal model was used for the estimation of single nucleotide polymorphism (SNP) effects. Significant SNP were those with a -log₁₀P-value threshold greater than 4.0. Volume, CONC, NSP, IMot, PTMot, 3HRPTMot, %NORM, PRIM, and SEC have five, three, six, seven, two, six, six, and two genome-wide significant SNP, respectively. Conclusions: Several significant SNP were determined to be near or within quantitative trait loci (QTL) associated with beef bull semen attributes. In addition, genes associated with fertility were found to contain or be near the significant SNP found in the study. The results indicate there are regions of the genome that impact fertility, proving inclusion of genomic information into genetic evaluation should be advantageous for genetic improvement of male fertility traits.

Enteric fermentation from cattle results in greenhouse gas production that is an environmental concern and also an energetic loss. Several methods exist to quantify gas fluxes; however, an open circuit gas quantification system (OCGQS) allows for unencumbered quantification of methane (CH4), carbon dioxide (CO2), and oxygen (O2) from grazing cattle. While previous literature has proven the accuracy of an OCGQS, little work has been done to establish the minimum number of spot samples required to best evaluate an individual grazing animal’s gas fluxes and metabolic heat production. A GreenFeed system (C-Lock Inc.) was used to collect at least 100 spot samples each from 17 grazing cows. The mean gas fluxes and metabolic heat production were computed starting from the first 10 visits (forward) and increasing by increments of 10 until an animal had 100 visits. Mean gas fluxes and metabolic heat production were also computed starting from visit 100 (reverse) in increments of 10 using the same approach. Pearson and Spearman correlations were computed between the full 100 visits and each shortened visit interval. A large increase in correlations were seen between 30 and 40 visits. Thus, mean forward and reverse gas fluxes and metabolic heat production were also computed starting at 30 visits and increasing by 2 until 40 visits. The minimum number of spot samples was determined when correlations with the full 100 visits were greater than 0.95. The results indicated that the minimum numbers of spot samples needed for accurate quantification of CH4, CO2, and O2 gas fluxes are 38, 40, and 40, respectively. Metabolic heat production can be calculated using gas fluxes collected by the OCGQS with 36 spot samples. Practically, calculation of metabolic heat production will require 40 spot samples because the component gases for metabolic heat calculation require up to 40 spot samples. Published literature from nongrazing (confined) environments recommended a similar number of total spot samples. Large variation existed around the average number of spot samples for an animal per day, therefore a wide range of test durations may be needed to meet the same number of spot samples in different populations. For this reason, protocols for the OCGQS should be based on the total number of spot samples, rather than a test duration.

Heart disease, specifically congestive heart failure, has become of increased interest to geneticists and cattle feeders. Data on cohort associations of risk factors related to heart disease and when heart disease deaths occur in U.S. feedlot cattle are limited. The study objectives were to 1) determine potential associations between feedlot cohort demographics and the risk of at least one noninfectious heart disease (NIHD) death occurrence and 2) determine potential association between feedlot cohort demographics and the timing of NIHD deaths during the feeding phase. Data were downloaded from commercial feedyard software and analyzed by constructing a generalized linear mixed model for both analyses. A binomial and Gaussian distributions for risk of NIHD death and timing of NIHD were utilized as link functions for their respective models. Our study population consisted of 28,950 cohorts (representing 4,596,205 cattle) that were placed in 22 U.S. commercial feedlots from January 01, 2016, to January 01, 2019. There were 3,282 cases of NIHD deaths from a population of 75,963 cattle that died during the 3-yr study period. Average cohort arrival weight’s effect on NIHD probability was influenced by arrival quarter and arrival year of placement (P < 0.01). Cohorts with steers were associated with a greater probability of at least one NIHD death (2.38%) compared with heifers (1.95%; P < 0.01). Increasing cohort size was associated with an increased probability of a cohort having at least one NIHD death (P < 0.01). The probability of a cohort having at least one NIHD death increased with increasing DOF categories from 1.51% in cattle fed 100 to 175 d, to 2.12% in cattle fed 176 to 250 d, and 2.87% for cattle fed 251 to 326 d. Cattle > 326 DOF were no different in the probability of a NIHD death compared with the other feeding categories. Timing of a NIHD death had a mean and median occurrence of 110 DOF with an interquartile range of 64 to 153 DOF. The effect of arrival weight on days at death was influenced by year placed with heavier cattle generally decreasing the model adjusted means of DOF at NIHD death. Arrival quarter was influenced by year placed on model adjusted means on the timing of a NIHD death. Steers with NIHD died later compared with heifers (P < 0.01) diagnosed with NIHD. In conclusion, multiple factors are associated with the probability and timing of a NIHD death. Probability of having at least one NIHD death within a cohort was low, and half of the deaths occurred before 110 DOF.

The objective was to estimate genetic parameters for udder traits in Hereford cattle. American Hereford Association (AHA) members initially recorded an overall score based on all udder characteristics. In 2008, the Beef Improvement Federation established guidelines, which were subsequently adopted by the AHA, for evaluating udder suspension and teat size. Therefore, a female was scored for either overall score or udder suspension and teat size for a single lactation, and females may be evaluated for overall score for a parity and then for udder suspension and teat size at a later parity. In all cases, subjective scores were assigned at parturition and ranged from 1 to 9, with a score of 9 considered ideal. Records on 48,191 animals and a 3-generation pedigree with 126,814 animals were obtained from the AHA, Kansas City, MO. These records contained repeated observations for overall score (n = 73,469), suspension (n = 38,412), and teat size (n = 38,412). Because the distribution of scores for all traits peaked at 7, a linear approximation was used in the analysis. Data were modeled using a multiple-trait animal model with random effects of additive genetic and permanent environment, fixed effect of contemporary group (herd–year–season), and a linear covariate for age in days. Heritability estimates (SE) for overall score, suspension, and teat size were 0.32 (0.01), 0.32 (0.01), and 0.28 (0.01), respectively. Through genetic selection for these traits, beef producers could improve udder traits. Repeatability estimates (SE) for overall score, suspension, and teat size were 0.45 (0.005), 0.47 (0.01), and 0.44 (0.01), respectively. Producers should continue evaluating udder traits repeatedly throughout a cow’s lifetime. The phenotypic correlation (SE) between suspension and teat size was 0.64 (0.004) with 57% of records for suspension and teat size having the same score for both traits. The genetic correlations (SE) between teat size and suspension, overall score and teat size, and overall score and suspension were 0.81 (0.01), 0.71 (0.03), and 0.69 (0.03), respectively, and selection for one trait should result in correlated responses in the other traits. In conclusion, traits were moderately repeatable with scores from a parity being informative for subsequent parities. Because overall score, udder suspension, and teat size were moderately heritable with strong, positive genetic correlations, genetic improvement for these traits can be achieved through selection. Copyright © 2015. American Society of Animal Science .

The objective of this study was to estimate genetic parameters for feet and leg traits, relationships within feet and leg traits, and relationships between feet and leg traits and production traits in Red Angus cattle. Subjective scores for 14 traits including body condition score (BCS), front hoof angle (FHA), front heel depth (FHD), front claw shape (FCS), rear hoof angle (RHA), rear heel depth (RHD), rear claw shape (RCS), size of hoof (SIZE), front side view (FSV), knee orientation (KNEE), front hoof orientation (FHO), rear side view (RSV), rear view (RV), and a composite score (COMP) were collected by trained evaluators on 1,720 Red Angus cattle. All traits except COMP were scored as intermediate optimum traits. Performance data, and EPD were obtained on all animals measured and a three-generation pedigree was obtained from the Red Angus Association of America (RAAA) that contained 13,306 animals. Data were modeled using a linear bivariate animal model with random additive genetic and residual effects, and fixed effects of age and contemporary group (herd-year) implemented in ASREML 4.0. Heritability estimates of BCS, FHA, FHD, FCS, RHA, RHD, RCS, SIZE, FSV, KNEE, FHO, RSV, RV, and COMP were 0.11, 0.20, 0.17, 0.09, 0.19, 0.25, 0.17, 0.36, 0.16, 0.17, 0.17, 0.30, 0.14, and 0.12, respectively. These results demonstrate feet and leg traits are lowly to moderately heritable. Strong, positive genetic correlations were observed between FHA and FHD (0.89), FHA and RHA (0.88), FHD and RHA (0.85), FHA and RHD (0.85), FHD and RHD (0.94), and FHO and KNEE (0.95), indicating these traits were highly related to each other. Strong and negative genetic correlations were observed between KNEE and FSV (−0.59) and FHO and FSV (−0.75). The strongest Pearson correlation between front limb traits (FHA, FHD, FSV, FHO, KNEE, and COMP) and Stayability EPD (STAY) was FSV (r = 0.16) and for rear limb traits (RHA, RHD, RCS, RSV, RV, and COMP) and STAY was RCS (r = −0.12). This suggests cattle with more slope to the angle of the shoulder and cattle with less evidence of hoof curl may stay in the herd longer. Further investigation into the economic viability of feet and leg trait genetic prediction with a larger population of animals is required to help validate these findings.