133 Genetic Parameter Estimation for Dry Matter Required in Angus Cattle

Abstract Dry matter intake (DMI) is critical to determine feed efficiency in cattle. However, this trait is expensive and difficult to measure on an individual basis. An alternative to overcome such limitations is to approximate DMI by using mathematical models to estimate the dry matter required (DMR) for animals originally fed in groups. High genetic correlations (e.g., rg>0.95) have been informed between DMI and DMR. Thus, DMR has been proposed as an indicator trait for DMI in genetic evaluations. Few reports exist about genetic parameters associated to DMR and, when available, estimates have been obtained with datasets of limited size (~1,500 animals with phenotypes). Additionally, previous reports have focused on older animals during the finishing phase, such that mathematical models employed to derive DMR have not explicitly accounted for the presence of weaner calves on the data. Therefore, the objective was to estimate genetic parameters for DMR using a moderately large dataset that included weaning and yearling Angus bulls. A total of 8,121 records of estimated DMR were available for analyses. From these records, 6,324 belonged to weaned males whose phenotype was obtained using an equation proposed by NRC to predict DMR for calves. The 1,797 remaining records pertained to yearling bulls for which a different NRC equation was employed. First, a single-trait animal model was implemented to estimate genetic parameters for DMR, with contemporary group (defined as year of test and pen within the testing facility), test length and age of the animal when entering to the test (linear covariate) being included as fixed effects, while animal was considered a random effect. Afterwards, a bivariate model that included weaning weight (WW) as a correlated trait was implemented. In this model, the same effects were included for DMR but for WW, fixed effects included sex, weaning contemporary group and age of dam (BIF classes), while direct genetic, maternal genetic, and maternal permanent environmental effects were considered as random. For both models, a reduced pedigree was used to estimate variance components by tracing back 5 generations from animals having phenotypes. A total of 12,212 and 56,023 animals were included in the univariate analysis and the bivariate analysis, respectively. Heritability (h2) estimates (± SE) for DMR were 0.43 (± 0.04) and 0.49 (± 0.03) under univariate and bivariate model, respectively. Genetic correlation between DMR and WW was 0.69 (± 0.03), with a h2 estimate of 0.29 (± 0.01) for WW. Heritability estimates for DMR obtained with both models resembled those of DMR reported in literature. Results suggested that substantial additive genetic variation exists for DMR and, consequently, indirect genetic progress for DMI can be attained if selecting for DMR. Further studies are required to validate DMR as an indicator trait for DMI in larger Angus populations.