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Blood pressure levels review with in-ear photoplethysmography.
We demonstrate how the estimated total genetic merit is invariant to the specification of a FE trait within a selection index. That is, economic weights for a selection index involving one particular FE trait readily convert into the economic weights for a selection index involving a different linear function of that FE trait. We use these different specifications of FE to provide insight as to the effect of the degree of missingness (e.g., paucity of DMI relative to milk yield records) on the EBV accuracies of the various derivative FE traits. We particularly highlight that the generally observed higher EBV accuracies for DMI, then for FS, and lastly for RFI are partly driven by the greater genetic correlations of DMI with BW and MilkE and of FS with BW. Finally, we advocate a genetic regression approach to deriving FS and RFI recognizing that genetic versus residual relationships between FE component traits may differ substantially from each other. Genomic selection was adopted very quickly in the 10 yr after first implementation, and breeders continue to find new uses for genomic testing. Breeding values with higher reliability earlier in life are estimated by combining DNA genotypes for many thousands of loci using existing identification, pedigree, and phenotype databases for millions of animals. Quality control for both new and previous data is greatly improved by comparing genomic and pedigree relationships to correct parent-progeny conflicts and discover many additional ancestors. Many quantitative trait loci and gene tests have been added to previous assays that used only evenly spaced, highly polymorphic markers. Imputation now combines genotypes from many assays of differing marker densities. Prediction models have gradually advanced from normal or Bayesian distributions within trait and breed to single-step, multitrait, or other more complex models, such as multibreed models that may be needed for crossbred prediction. Genomic selection was inrther incentive to cooperate internationally. The genomic prediction methods developed for dairy cattle are now applied widely to many animal, human, and plant populations and could be applied to many more. During the last decade, genomic selection has revolutionized dairy cattle breeding. For example, Nordic dairy cows (Denmark, Finland, and Sweden) born in 2018 were >90% sired by young genomically tested bulls. Thus, the average age of sires for Red Dairy Cattle cows born in 2018 was only 3.1 yr, whereas in 2011 it was 5.7 yr. Earlier the key driver of genetic progress was the selection of progeny-tested sires, but now it is the genomic preselection of young sires. This leads to a biased estimation of genetic progress by the traditional genetic evaluations. When these are used as input for multi-step genomic evaluations also they became distorted. The only long-term solution to maintain unbiasedness is to include the genomic information in evaluations. Although means for single-step evaluation models were introduced in 2010, they have not yet been implemented in large-scale national dairy evaluations. At first, single-step evaluations were hindered by computational cost. This has been largely solved, either bygenotypes. These problems are more pronounced with low-heritability traits and in multi-trait models with high genetic correlations among traits. Problems are also related to the unbalancedness of pedigrees and diverse genetic groups. In many cases, the problem can be solved by properly accounting for contributions of the genotyped animals to genetic groups. The standard solving approach is preconditioned conjugate gradient iteration, in which the convergence has been improved by better preconditioning matrices. Another difficulty to be considered is inflation in genomic evaluations of candidate animals; genomic models seem to overvalue the genomic information. The problem is usually smaller in single-step evaluations than in multi-step evaluations but is more difficult to mitigate by ad hoc adjustments. Caprine arthritis encephalitis (CAE) is a chronic disease caused by a retrovirus from the Lentivirus genus. No effective vaccines or treatments exist, and therefore genetic selection for CAE resistance might be a feasible alternative. To our best knowledge, no other studies have investigated the genetic architecture of CAE resistance in dairy goats. In this context, this study was designed to estimate genetic parameters for CAE infection in Alpine and Saanen goats using a Bayesian threshold model. A total of 542 adult goats (and >3-generation pedigree), which were group-housed in a population with high CAE prevalence, were tested based on a serological infection assessment test (negative = 1 or positive = 2) and used for this study. Genetic parameters were estimated using the BLUPF90 family programs. There was considerable genetic variability for CAE resistance, and pedigree-based heritability was significantly different from zero (0.026 less then heritability less then 0.128). Our findings indicate that the prevalence of CAE in goat herds can be reduced or eliminated through direct genetic selection for CAE resistance in addition to proper management strategies. Hoof lesions represent an important issue in modern dairy herds, with reported prevalence in different countries ranging from 40 to 70%. This high prevalence of hoof lesions has both economic and social consequences, resulting in increased labor expenses and decreasing animal production, longevity, reproduction, health, and welfare. Therefore, a key goal of dairy herds is to reduce the incidence of hoof lesions, which can be achieved both by improving management practices and through genetic selection. The Canadian dairy industry has recently released a hoof health sub-index. This national genetic evaluation program for hoof health was achieved by creating a centralized data collection system that routinely transfers data recorded by hoof trimmers into a coherent and sustainable national database. The 8 most prevalent lesions (digital dermatitis, interdigital dermatitis, interdigital hyperplasia, heel horn erosion, sole hemorrhage, sole ulcer, toe ulcer, and white line lesion) in Canada are analyzed with a multiple-trait model using a single-step genomic BLUP method. Estimated genomic breeding values for each lesion are combined into a sub-index according to their economic value and prevalence. In addition, data recorded within this system were used to create an interactive management report for dairy producers by Canadian DHI, including the prevalence of lesions on farm, their trends over time, and benchmarks with provincial and national averages. The aim of this study was to detect the genomic region or regions associated with metabolic clusters in early-lactation Holstein cows. This study was carried out in 2 experiments. In experiment I, which was carried out on 105 multiparous Holstein cows, animals were classified through k-means clustering on log-transformed and standardized concentrations of blood glucose, insulin-like growth factor I, free fatty acids, and β-hydroxybutyrate at 14 and 35 d in milk (DIM), into metabolic clusters, either balanced (BAL) or other (OTR). Forty percent of the animals were categorized in the BAL group, and the remainder were categorized as OTR. The cows were genotyped for a total of 777,962 SNP. A genome-wide association study was performed, using a case-control approach through the GEMMA software, accounting for population structure. We found 8 SNP (BTA11, BTA23, and BTAX) associated with the predicted metabolic clusters. In experiment II, carried out on 4,267 second-parity Holstein cows, milk samples collected starti gland development. The heritability for metabolic clustering was 0.17 (SD 0.03), indicating that the use of FT-MIR spectra in milk to predict metabolic clusters in early-lactation across a large number of cows has satisfactory potential to be included in genetic selection programs for modern dairy cows. Hoof trimming is used to prevent and treat lameness in dairy cows; however, hoof trimming itself increases daily time spent lying down, possibly due to discomfort. We hypothesized that treatment of lame and nonlame cows with an anti-inflammatory analgesic drug at the time of hoof trimming would mitigate discomfort, thereby improving locomotion scores and reducing post-trimming increases in lying time. We further hypothesized that drug treatment would improve post-trimming milk production. Our objective was to determine the effects of treatment with the nonsteroidal anti-inflammatory drug flunixin meglumine (2.2 mg/kg of BW) at the time of hoof trimming on locomotion, lying times, and milk production in lame and nonlame lactating dairy cows. All cows were filmed for locomotion scoring 1 d before and 1, 8, and 28 d after hoof trimming. Daily time spent standing and lying was recorded for 4 d before and 4 wk after hoof trimming, and daily milk production was recorded for 1 wk before and 8 wk after trimming. Thir lying behavior after trimming can be accommodated. Haptoglobin (Hp), one of the major positive acute phase proteins in cattle, is released in response to proinflammatory cytokines. Colostrum intake might influence the response of the innate immune system, including Hp gene expression. Thus, we hypothesized that plasma concentrations and tissue mRNA expression of Hp in neonatal calves might be influenced by early nutrition in the neonatal calf and would thus be greater if receiving colostrum compared with milk-based formula. Two trials were performed. In trial 1, German Holstein calves were fed either colostrum (COL; n = 7) or milk-based formula (FOR; n = 7) up to 4 d of life. Blood was sampled from d 1 to 4 before morning feeding and before and 2 h after feeding on d 4. Tissue samples from liver, kidney fat, duodenum, and ileum were collected after slaughter on d 4 at 2 h after feeding. In trial 2, calves born preterm (n = 7) or at term (n = 7) received colostrum only at 24 h post natum. selleck chemicals Blood was sampled at birth, and before and 2 h after feeding. Tissue samold greater in term than in preterm calves, whereas its abundance in kidney fat did not differ between groups. Contrasting our hypothesis, formula, but not colostrum feeding was associated with greater Hp mRNA abundance in liver and adipose tissue, indicating that the response of innate immune system seems to be modulated by formula feeding because of the lack of immunoglobulin intake. The lower hepatic abundance of Hp mRNA in preterm calves than in term calves may indicate lower synthetic capacity of the liver for Hp in preterm calves shortly after birth. The objective of this study was to compare culture- and algorithm-guided selective dry-cow therapy (SDCT) programs with blanket dry-cow therapy (BDCT) in a multi-site, randomized, natural exposure clinical trial for the following cow-level outcomes clinical mastitis, removal from the herd, and Dairy Herd Improvement Association (DHIA) test-day milk yield and SCC measures during the first 120 d in milk (DIM). Two days before planned dry-off, cows in each of 7 herds were randomly allocated to BDCT, culture-guided SDCT (cult-SDCT), or algorithm-guided SDCT (alg-SDCT). At dry-off, BDCT cows received an intramammary antibiotic (500 mg of ceftiofur hydrochloride) in all 4 quarters. Antibiotic treatments were selectively allocated to quarters of cult-SDCT cows by only treating quarters from which aseptically collected milk samples tested positive on a rapid culture system after 30 to 40 h of incubation. For alg-SDCT cows, antibiotic treatments were selectively allocated at the cow level, with all quarters receiving antibiotic treatment if the cow met at least one of the following criteria (1) any DHIA test with a somatic cell count >200,000 cells/mL during the current lactation, and (2) ≥2 clinical mastitis cases during the current lactation.
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