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American Aberdeen (AD) cattle in the USA descend from an Aberdeen Angus herd originally brought to the Trangie Agricultural Research Centre, New South Wales, AUS. Although put under specific selection pressure for yearling growth rate, AD remain genomically uncharacterized. The objective was to characterize the genetic diversity and structure of purebred and crossbred AD cattle relative to seven common USA beef breeds using available whole-genome SNP data. A total of 1140 animals consisting of 404 purebred ( n = 8 types) and 736 admixed individuals ( n = 10 types) was used. Genetic diversity metrics, an analysis of molecular variance, and a discriminant analysis of principal components were employed. When linkage disequilibrium was not accounted for, markers influenced basic diversity parameter estimates, especially for AD cattle. Even so, intrapopulation and interpopulation estimates separate AD cattle from other purebred types (e.g., Latter's pairwise F ST ranged from 0.1129 to 0.2209), where AD cattle were less heterozygous and had lower allelic richness than other purebred types. The admixed AD-influenced cattle were intermediate to other admixed types for similar parameters. The diversity metrics separation and differences support strong artificial selection pressures during and after AD breed development, shaping the evolution of the breed and making them genomically distinct from similar breeds.

Ewe lifetime productivity has economic implications for producers because shorter lifetime productivity results in less profit. Productive years of ewes from extensive, range-based systems of the United States West are generally less than ewes from more temperate regions of the United States. Accordingly, ewes from range-based systems, especially those employing shed-lambing strategies, have been selected for increased litter size to offset decreased lifetime productivity. However, the relationship of the ewe's birth litter size (ELS B ) has not been considered a potential contributor to lifetime productivity. Longevity (number of productive years, n = 1 per population) and stayability (probability to survive to the next age; ages 2-7 years, n = 6 per population) were investigated to understand ELS B effects on productive life. Columbia, Polypay, Rambouillet, and Targhee breeds were used in this study. Across-breed (n = 11 550) and within-breed (Columbia, n = 4 398; Polypay, n = 4 534; Rambouillet, n = 5 922; Targhee, n = 6 482) analyses were used. Depending on the population, records spanned from 1950 to 2008, where ewe's birth year was included as a fixed effect in the animal model using restricted maximum likelihood estimation procedures. Fixed effects investigated included ELS B (single-, twin-, or triplet-born) and ewe breed (across-breed analyses only). Regardless of trait or population used, heritability ranged from 0.06 ± 0.02 to 0.34 ± 0.03, where stayability at younger ages had the highest estimates. The breed effect was significant in all across-breed analyses (0.0001 ≤ P ≤ 0.038; n = 7), where Polypay, a breed selected for accelerated lambing and increased fertility, averaged shorter productive life or had a lower probability of survival to the next age compared with other breeds (longevity: 0.009 ≤ P ≤ 0.223; stayability: 0.000 ≤ P ≤ 0.842). The ELS B was significant in 60% (n = 5) and 37% (n = 30) of longevity and stayability analyses, respectively. Except for Targhee, all analyses showed ewes born in smaller litter sizes were associated with longer productive lives or higher probability of surviving to the next age, particularly in across-breed analyses (e.g., longevity: single- vs twin-born ewes, P = 0.004; vs triplet-born ewes, P = 0.003). This study provides evidence that increasing prolificacy in ewes from extensive, range-based production systems may impact productive life. Due to the low heritability of these traits, additional investigation into modeling these traits with dominance effects and litter size needs to be conducted., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

The relationship between weather variables and dry matter intake (DMI) in beef steers was examined using daily intake data from 790 beef steers collected through a computer-controlled feeding system in nonsummer months. Daily data were condensed into weekly averages (N = 13,895 steer-weeks). The variables considered to predict DMI (2.50 to 23.60 kg/d) were body weight (197 to 796 kg), dietary net energy for maintenance (NEm; 0.79 to 2.97 Mcal/kg), ambient temperature (-23.73 °C to 21.40 °C), range of temperature (2.79 °C to 19.43 °C), dew point (-27.84 °C to 14.34 °C), wind speed (2.08 to 6.49 m/s), solar radiation (30.8 to 297.1 W/m2), and 2-wk lag (average of previous 2 wk's values) and monthly lag (average of previous 4 wk's values) of each weather variable. Toeplitz variance-covariance structure for repeated measures was used to determine the model to predict DMI, while accounting for the effects of body weight, dietary NEm, and other variables in the model. Two-week lag of ambient temperature interacted (P ≤ 0.005) with 2-wk lag of range of temperature, monthly lag of wind speed, 2-wk lag of solar radiation, and dew point to predict DMI. Interactions (P = 0.0001) between 2-wk lag of range of temperature vs. dew point and monthly lag of wind speed vs. 2-wk lag of solar radiation were also detected. This study reports important weather variables associated with differences in DMI of growing and finishing steers and will help improve the accuracy of DMI prediction equations for beef cattle. Improvements in the accuracy of predicting DMI should give producers better tools to plan and execute efficient feeding management programs. The R2 of the overall model was 0.8891., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The animal's reaction to human handling (i.e., temperament) is critical for work safety, productivity, and welfare. Subjective phenotyping methods have been traditionally used in beef cattle production. Even so, subjective scales rely on the evaluator's knowledge and interpretation of temperament, which may require substantial experience. Selection based on such subjective scores may not precisely change temperament preferences in cattle. The objectives of this study were to investigate the underlying genetic interrelationships among temperament measurements using genetic factor analytic modeling and validate a movement-based objective method (four-platform standing scale, FPSS) as a measure of temperament. Relationships among subjective methods of docility score (DS), temperament score (TS), 12 qualitative behavior assessment (QBA) attributes and objective FPSS including the standard deviation of total weight on FPSS over time (SSD) and coefficient of variation of SSD (CVSSD) were investigated using 1,528 calves at weaning age. An exploratory factor analysis (EFA) identified two latent variables account for TS and 12 QBA attributes, termed difficult and easy from their characteristics. Inclusion of DS in EFA was not a good fit because it was evaluated under restraint and other measures were not. A Bayesian confirmatory factor analysis inferred the difficult and easy scores discovered in EFA. This was followed by fitting a pedigree-based Bayesian multi-trait model to characterize the genetic interrelationships among difficult, easy , DS, SSD, and CVSSD. Estimates of heritability ranged from 0.18 to 0.4 with the posterior standard deviation averaging 0.06. The factors of difficult and easy exhibited a large negative genetic correlation of -0.92. Moderate genetic correlation was found between DS and difficult (0.36), easy (-0.31), SSD (0.42), and CVSSD (0.34) as well as FPSS with difficult (CVSSD: 0.35; SSD: 0.42) and easy (CVSSD: -0.35; SSD: -0.4). Correlation coefficients indicate selection could be performed with either and have similar outcomes. We contend that genetic factor analytic modeling provided a new approach to unravel the complexity of animal behaviors and FPSS-like measures could increase the efficiency of genetic selection by providing automatic, objective, and consistent phenotyping measures that could be an alternative of DS, which has been widely used in beef production., (Copyright © 2020 Yu, Morota, Celestino, Dahlen, Wagner, Riley and Hulsman Hanna.)

The objectives of this study were to 1) compare four models for breeding value prediction using genomic or pedigree information and 2) evaluate the impact of fixed effects that account for family structure. Comparisons were made in a Nellore-Angus population comprising F2, F3 and half-siblings to embryo transfer F2 calves with records for overall temperament at weaning (TEMP; n = 769) and Warner-Bratzler shear force (WBSF; n = 387). After quality control, there were 34,913 whole genome SNP markers remaining. Bayesian methods employed were BayesB (π̃ = 0.995 or 0.997 for WBSF or TEMP, respectively) and BayesC (π = 0 and π̃), where π̃ is the ideal proportion of markers not included. Direct genomic values (DGV) from single trait Bayesian analyses were compared to conventional pedigree-based animal model breeding values. Numerically, BayesC procedures (using π̃) had the highest accuracy of all models for WBSF and TEMP (ρ̂gĝ = 0.843 and 0.923, respectively), but BayesB had the least bias (regression of performance on prediction closest to 1, β̂y,x = 2.886 and 1.755, respectively). Accounting for family structure decreased accuracy and increased bias in prediction of DGV indicating a detrimental impact when used in these prediction methods that simultaneously fit many markers.