Monitoring growth of neonatal dairy calves is a useful management tool to assist producers in achieving goals for reproduction and performance. The goal of this study was to examine ultrasound as an in vivo tool to quantify longissimus dorsi muscle (ribeye) linear depth and extensor carpi radialis (ECR) and semitendinosus (ST) muscle cross-sectional areas in postmortem preweaned Holstein calves. Postmortem preweaned calves (n = 137, age 13.1 d ± 15.5 SD, body weight 36.5 kg ± 7.2 SD) were obtained from two California calf ranches between April and July 2013. Two operators collected ultrasound images of the ribeye, ECR, and ST muscles using an Aloka 500V equipped with a 5-cm 7.5-MHz linear transducer. Ultrasound ribeye linear depth and ECR and ST cross-sectional areas were calculated using the Ultrasound Image Capture System. Ultrasound measurements were compared to dissected (carcass) measures. Carcass ribeye linear depth was estimated using a ruler. Dissected ECR and ST muscle cross-sectional areas were estimated by tracing muscle cross sections onto transparency paper and then photocopying, cutting out, and weighing individual paper muscle tracings. Weights of the tracings were then converted to areas using the known area of a standard 8.5 × 11 inch paper. Data were analyzed by regressing carcass estimates on observed ultrasound measurements. The coefficient of determination (R ²) indicated that ultrasound measurements were most closely associated with carcass measurements for the ST muscle (R ² = 0.60, 0.62 for operator 1 and 2, respectively) when compared to the ribeye and ECR muscles (R ² = 0.27, 0.41 for ribeye and 0.43, 0.32 for ECR for operator 1 and 2, respectively). The mean bias showed consistent underestimation by the ultrasound measurements when predicting carcass measurements for all three muscles and for both operators (ribeye bias = 0.15, 0.40; ECR bias = 0.95, 1.15; and ST bias = 0.73, 0.27 for operator 1 and 2, respectively). Operator contributed significantly in explaining a proportion of the variation in the regression equation for the ST muscle only, whereas calf body weight contributed significantly in explaining a proportion of the variation in the regression equation for all three muscles. The results of this study demonstrated that ultrasound measurements of the ST were the most accurate for quantifying the cross-sectional area when compared to both the ECR and ribeye in postmortem Holstein calves.

Extended laboratory culture and antimicrobial susceptibility testing timelines hinder rapid species identification and susceptibility profiling of bacterial pathogens associated with bovine respiratory disease, the most prevalent cause of cattle mortality in the United States. Whole-genome sequencing offers a culture-independent alternative to current bacterial identification methods, but requires a library of bacterial reference genomes for comparison. To contribute new bacterial genome assemblies and evaluate genetic diversity and variation in antimicrobial resistance genotypes, whole-genome sequencing was performed on bovine respiratory disease-associated bacterial isolates (Histophilus somni, Mycoplasma bovis, Mannheimia haemolytica, and Pasteurella multocida) from dairy and beef cattle. One hundred genomically distinct assemblies were added to the NCBI database, doubling the available genomic sequences for these four species. Computer-based methods identified 11 predicted antimicrobial resistance genes in three species, with none being detected in M. bovis While computer-based analysis can identify antibiotic resistance genes within whole-genome sequences (genotype), it may not predict the actual antimicrobial resistance observed in a living organism (phenotype). Antimicrobial susceptibility testing on 64 H. somni, M. haemolytica, and P. multocida isolates had an overall concordance rate between genotype and phenotypic resistance to the associated class of antimicrobials of 72.7% (P < 0.001), showing substantial discordance. Concordance rates varied greatly among different antimicrobial, antibiotic resistance gene, and bacterial species combinations. This suggests that antimicrobial susceptibility phenotypes are needed to complement genomically predicted antibiotic resistance gene genotypes to better understand how the presence of antibiotic resistance genes within a given bacterial species could potentially impact optimal bovine respiratory disease treatment and morbidity/mortality outcomes.