Milk Yield In Dairy Cattle Research Articles

Comparison of genomic breeding values of Holstein in Czech Republic

Genomic evaluation by single-step procedure allows efficient implanting of genetic SNP markers into complicated procedure of random regression test-day-model of milk traits. Test-day records and pedigree files on nation-wide scale are combined with genomic relationship into common evaluation of both genotyped and ungenotyped animals. Due to strong import of foreign sperm into small national populations is the reliability of evaluation of young animals low. This is particularly seen in evaluation of young bulls, which frequently have both parents foreign. Genomic evaluation helps and notably improves reliability of evaluation. ssGBLUP procedure is advantageous especially for small populations. Domestic genomic evaluation of young animals has medium to high correlation with foreign Interbull values. Interbull conversion of values of bulls according MACE, which works with progeny tested bulls, is more reliable than conversion according GMACE procedure, which works with genomic evaluation of young animals. Keywords: genomic breeding value, ssGBLUP, test day model, MACE, GMACE References Bauer, J. et al. (2014) Approximation of the reliability of single-step genomic breeding values for dairy cattle in the Czech Republic. Anim. Sci. Papers and Reports, 32, pp. 301-306. Bauer, J., Přibyl, J. and Vostrý, L. (2015) Contribution of domestic production records and Interbull EBV on approximate reliabilities of single-step genomic breeding values in dairy cattle. Czech J. Anim. Sci., 60, 263-267. Christensen, O.F. and Lund, M.S. (2010) Genomic prediction when some animals are not genotyped. Genet.Sel.Evol. 42, pp. 2. Forni, S., Aguilar I. and Misztal, I. (2011) Different genomic relationship matrices for single step analysis using phenotypic, pedigree and genomic information. Genet. Sel. Evol., 43, pp. 1. Legarra A., Aguilar I. and Misztal, I. (2009) A relationship matrix including full pedigree and genomic information. J. Dairy Sci., 92, pp. 4656-4663. Meuwissen, T.H.E., Hayes, B.J. and Goddard, M.E. (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics, 157, pp. 1819–1829. Misztal, I., Legarra A. and Aguilar, I. (2009) Computing procedures for genetic evaluation including phenotypic, full pedigree, and genomic information. J. Dairy Sci., 92, pp. 4648–4655. Pesek, P., Přibyl, J. and Vostrý, L . (2015) Genetic variances of SNP loci for milk yield in dairy cattle. J. Appl. Genet., 56, pp. 339-347. Plemdat, (2015) Descriptions of Breeding values Evaluation. Retrieved on 10 th June 2015 From www.plemdat.cz. Přibyl, J. et al. (2014) Domestic and Interbull information in the single step genomic evaluation of Holstein milk production. Czech J. Anim. Sci., 59, pp. 409-415. Přibyl, J. et al. (2015) Domestic estimated breeding values and genomic enhanced breeding values of bulls in comparison with their foreign genomic enhanced breeding values. Animal, 9, pp. 1635-1642. Vitezica, Z.G. et al. (2011) Bias in genomic predictions for populations under selection. Genet. Res. (Camb), 93, pp. 357-366. Zavadilova, L., Jamrozik, J. and Schaeffer, L.R. (2005a) Genetic parameters for test- day model with random regressions for production traits of Czech Holstein cattle. Czech J. Anim. Sci., 50, pp. 142-154. Zavadilova, L., Němcova, E. and Wolf, J. (2005b) Definition of subgroups for fixed regression in the test-day animal model for milk production of Holstein cattle in the Czech Republic. Czech J. Anim. Sci., 50, pp. 7-13. Zavadilova, L. et al. (2014) Single-step genomic evaluation for linear type traits of Holstein cows in Czech Republic. Anim. Sci. Papers and Reports vol. 32, pp. 201-208.

Categorization of endometritis and its association with ovarian follicular growth and ovulation, reproductive performance, dry matter intake, and milk yield in dairy cattle

The objectives were to evaluate the effect of different categories of endometritis on follicular growth and ovulation, reproductive performance, dry matter intake (DMI), and milk yield (MY) in dairy cows. Lactating Holstein cows (n = 126) were examined for endometritis on 25 ± 1 day postpartum (DPP) using vaginoscopy, transrectal ultrasonography, and endometrial cytology to determine the presence and type of vaginal discharge, uterine fluid, and proportion of polymorphonuclear (PMN) cells, respectively. Cows that had mucopurulent vaginal discharge and/or presence of uterine fluid, no mucopurulent vaginal discharge or uterine fluid but 8% or more PMN, and mucopurulent vaginal discharge and/or uterine fluid and 8% or more of PMN were defined as having clinical (CLIN; n = 45), cytological (CYTO; n = 15), and clinical and cytological (CLINCYTO; n = 30) endometritis, respectively. Cows that had none of the above pathological conditions were classified as unaffected (UNAF; n = 36). The diameter of the largest follicle at first examination, intervals from calving to first dominant (diameter = 10 mm) follicle, preovulatory size (diameter = 16 mm) follicle, ovulation, presence of follicular cyst, and proportion of ovular cows at 35 and 65 DPP were recorded as the measures of follicular growth and ovulation. None of the ovarian follicular parameters analyzed was affected by categories of endometritis. The first service conception rate tended (P = 0.06) to differ among categories of endometritis; cows that had CLIN and CLINCYTO endometritis were four times less likely to conceive to the first insemination compared to UNAF cows. Cows that had CLIN (hazard ratio: 0.52) and CLINCYTO (hazard ratio: 0.40) endometritis had decreased likelihood of pregnancy at 150 DPP compared to UNAF cows. Similarly, cows diagnosed as having CLINCYTO endometritis had decreased likelihood (hazard ratio: 0.48) of pregnancy at 250 DPP compared to UNAF cows. The DMI and MY up to 5 weeks postpartum were not affected by categories of endometritis. In summary, categories of endometritis as determined at 25 DPP did not affect follicular growth and ovulation, DMI, or MY. However, the combined (CLINCYTO endometritis) category had a negative impact on first service conception rate and subsequent services.

The effect of topical application of Stryphnodendron adstringens (Martius) Coville extract and oral biotin supplementation on recovery of wounds from digital dermatitis surgery

A dermatite digital compromete a saúde e produtividade dos bovinos. O controle da enfermidade pode ser feito com a apara corretiva do casco e passagem dos animais em pedilúvio. Os resultados nem sempre são satisfatórios e há o risco de ocorrerem resíduos na carne, leite e no ambiente. No presente estudo avaliou-se a reparação de feridas cirúrgicas de dermatite digital após aplicação tópica do extrato da casca de barbatimão, em pedilúvio ou por pincelamento, e suplementação com biotina, em 90 vacas de aptidão leiteira. Todos os animais eram fêmeas, mestiças (Gir x Holandesa) e apresentavam dermatite digital em graus variados. As feridas foram analisadas em vários momentos durante 45 dias. Os animais foram divididos em seis grupos de 15 de acordo com o protocolo. Avaliou-se a aplicação do barbatimão em pedilúvio com ou sem suplementação de biotina, barbatimão por pincelamento com ou sem biotina e limpeza com água sob pressão com ou sem biotina, considerando os índices e os tempos de recuperação. A suplementação com biotina não influenciou os índices nem o tempo de recuperação das feridas cirúrgicas de dermatite digital e o uso tópico do extrato da casca do barbatimão, independente da forma de aplicação, se mostrou benéfico em relação à aplicação de água.

The global effect of heat on gene expression in cultured bovine mammary epithelial cells.

Heat stress (HS) in hot climates is a major cause that strongly negatively affects milk yield in dairy cattle, leading to immeasurable economic loss. The heat stress response of bovine mammary epithelial cells (BMECs) is one component of the acute systemic response to HS. Gene networks of BMECs respond to environmental heat loads with both intra- and extracellular signals that coordinate cellular and whole-animal metabolism. Our experimental objective was to characterize the direct effects of heat stress on the cultured bovine mammary epithelial cells by microarray analyses. The data identified 2716 differentially expressed genes in 43,000 transcripts which were changed significantly between heat-stressed and normal bovine mammary epithelial cells (fold change ≥2, P ≤ 0.001). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that these differentially expressed genes are involved in different pathways that regulate cytoskeleton, cell cycle, and stress response processes. Our study provides an overview of gene expression profile and the interaction between gene expression and heat stress, which will lead to further understanding of the potential effects of heat stress on bovine mammary glands.

Heterozygote advantage: the effect of artificial selection in livestock and pets.

There are a number of mutants in livestock and pets that have a heterozygote advantage because of artificial selection for these mutants in heterozygotes and strong detrimental effects from natural selection in homozygotes. In livestock, these mutants include ones that influence milk yield in dairy cattle, fecundity in sheep, litter size in pigs, muscling in beef cattle, color in horses, lean meat content in pigs, and comb morphology in chickens. In pets, these mutants include ones that influence tail length in cats and hairlessness, muscling, color, or ridgeback hair in dogs. A large variety of mutants are responsible, including small or large deletions or insertions and single base-pair nonsynonymous changes. Many of the mutants cause loss of function for the genes involved, a change that results in the pleiotropic effects of a desired phenotype in heterozygotes and low fitness or an undesirable phenotype in mutant homozygotes. I examine how selection changes the frequency of these mutants and provide an approach to estimate the amount of artificial selection that is necessary to maintain these mutants at the high frequencies often observed. The amount of artificial selection ranges from low selection favoring heterozygotes for double muscling in whippet dogs to very strong selection favoring the "flash" (part white, part solid) heterozygote in boxer dogs and the rose comb in chickens. In several examples (rose comb in Wyandotte chickens and the hair ridge in Rhodesian ridgeback dogs), there is actually stronger selection for the mutant than against it, making the frequency of the mutant greater than 50%.

Genetic variances of SNP loci for milk yield in dairy cattle.

Regression coefficients and genetic variances for 40,890 single nucleotide polymorphisms (SNPs) for milk yield were calculated using mixed model equations, with deregressed proof (DRP) as the dependent variable. Bulls were genotyped using the Illumina BovineSNP50 v2 BeadChip and SNPs were edited according the minor allele frequency (MAF) and high incidence of missing genotype. Evaluation was conducted in two rounds. In the preliminary round, the direct genetic values (DGVs) of all genotyped bulls (2,904) were computed and the absolute difference between the DGV and the input DRP of each bull was investigated. Bulls with an absolute difference greater than the mean absolute difference plus two standard deviations were eliminated from the data set prior to the final analysis (2,766 bulls remaining). SNP regression coefficients from the final analysis had a mean absolute value of 0.506 kg and a standard deviation of 0.409 kg. The SNP with the highest regression coefficient and genetic variance was ARSBFGLNGS4939 on chromosome 14. This SNP is located within the gene DGAT1 (diacylglycerol O-acyltransferase 1). Other SNPs with high regression coefficients and genetic variance are localised in proximity to DGAT1. The mean genetic variance of an individual SNP was 0.170, with a standard deviation of 0.384 and a mean heterozygosity of 0.372. The sum of genetic variances of all SNPs was only 6,968.8, probably because of the existence of genetic covariances between loci. The largest sum of genetic variances was on chromosome 14 (498.4, 7.15 % of the total). After the final analysis, the correlation between the DGV and the input DRP was 0.951 for all bulls. The variance of the predicted DGV was 98.11 % of the variance of the input estimated breeding value (EBV) and 63.65 % of the variance of the DRP.

Effects of Mycotoxin Sequestering Agents Added Into Feed on Health, Reproduction and Milk Yield of Dairy Cattle

Effects of mycotoxin sequestering agents in feed on health, reproduction and milk yield of dairy cattle were studied in a 5-month long experiment on 300 dairy cows divided into two groups and six subgroups. The experiment was conducted in adding a mycotoxin sequestering agent based on 1,3 and 1,6 β-glucans to standard cattle nutrition (TMR), which was regularly tested for content of important mycotoxins, in order to gain knowledge about possible positive effect of this agent on the health of dairy cattle and about possible avoidance of negative effects of mycotoxins on dairy cattle due to their structural elimination caused by the agent. The experiment’s setting and conditions during it were in all aspects common and comparable within the European Union, the experiment’s results should be therefore seen as relevant. Health, pregnancy rate and milk yield were carefully monitored during the experiment. Indicators of state of health (occurrence of mastitis and somatic cell count in milk) did not show any significant differences between test and control groups of dairy cows. The average milk yield of dairy cows which were fed the agent enriched feed (30.2 kg a day) was slightly lower in comparison to control groups (31 kg a day, both results with P < 0.001), however, fat content of milk of test groups’ cows (4.02%) was considerably higher than that of control groups’ cows (3.79%). The average pregnancy rate of cows which were fed the agent enriched feed also manifested considerable increase in percentage and stability (from 42.95% of control groups’ cows to 62.25% of test groups’ cows, the standard deviation decreased from 21.1% to 14.4% which means smaller differences among pregnancy rate of test groups’ cows, hence higher stability), this increase manifested even long after the cows had been fed regular feed again.

Selection for complex traits leaves little or no classic signatures of selection

BackgroundSelection signatures aim to identify genomic regions underlying recent adaptations in populations. However, the effects of selection in the genome are difficult to distinguish from random processes, such as genetic drift. Often associations between selection signatures and selected variants for complex traits is assumed even though this is rarely (if ever) tested. In this paper, we use 8 breeds of domestic cattle under strong artificial selection to investigate if selection signatures are co-located in genomic regions which are likely to be under selection.ResultsOur approaches to identify selection signatures (haplotype heterozygosity, integrated haplotype score and FST) identified strong and recent selection near many loci with mutations affecting simple traits under strong selection, such as coat colour. However, there was little evidence for a genome-wide association between strong selection signatures and regions affecting complex traits under selection, such as milk yield in dairy cattle. Even identifying selection signatures near some major loci was hindered by factors including allelic heterogeneity, selection for ancestral alleles and interactions with nearby selected loci.ConclusionsSelection signatures detect loci with large effects under strong selection. However, the methodology is often assumed to also detect loci affecting complex traits where the selection pressure at an individual locus is weak. We present empirical evidence to suggests little discernible ‘selection signature’ for complex traits in the genome of dairy cattle despite very strong and recent artificial selection.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-246) contains supplementary material, which is available to authorized users.

Enhanced udder health and milk yield of dairy cattle on compost bedding systems during the dry period: A comparative study

Housing and, specifically, bedding are of utmost importance for health, productivity and longevity of dairy cattle. “Compost bedding” (CB) is an alternative way of loose-housing that is currently being implemented in many regions world-wide. It has verifiable positive effects on lactating cows, and it can be expected to be beneficial also for dried cows. The objective of the present study was to analyze the possible benefits of applying a CB system during the dry-period for the health (udder and uterine health), and for reproductive and productive performance during the following lactation of mature cows when compared to cows allocated on straw bedding. A total of 423 Holstein cows were randomly distributed at drying-off into a CB-Group (n=242) and a straw-bedded group (S-group; n=181). After calving, the management was the same for all cows. Data on milk yield, pregnancy after first insemination (P/FAI), somatic cell counts (SCC), incidence of clinical mastitis, metritis and cytological endometritis, and mortality/culling rate were recorded. While no differences in P/FAI and mortality rate, nor in the incidence of clinical metritis or endometritis between groups were detected, there did emerge positive effects of CB-systems on udder health [lower incidence of the first mastitis-cases, 22.1 vs. 35%; P=0.004, of second-mastitis cases, 6.8 vs. 15%; P=0.009, and a positive tendency in SCC (96.1±135.2 vs. 139.5±242.6cells/L; P=0.08)]. Moreover, increased milk yield/cow during the first 100 days of the following lactation (3778±887 vs. 3538±991L/lactation; P=0.011) and milk yield/day-in-milk (38.38±7.3 vs. 36.70±7.5L/d; P=0.022) were observed. These findings, added to the saving of straw costs and waste disposal, encourage the implementation of CB-systems in dairy farms.

Predicting expected progeny difference for marbling score in Angus cattle using artificial neural networks and Bayesian regression models

BackgroundArtificial neural networks (ANN) mimic the function of the human brain and are capable of performing massively parallel computations for data processing and knowledge representation. ANN can capture nonlinear relationships between predictors and responses and can adaptively learn complex functional forms, in particular, for situations where conventional regression models are ineffective. In a previous study, ANN with Bayesian regularization outperformed a benchmark linear model when predicting milk yield in dairy cattle or grain yield of wheat. Although breeding values rely on the assumption of additive inheritance, the predictive capabilities of ANN are of interest from the perspective of their potential to increase the accuracy of prediction of molecular breeding values used for genomic selection. This motivated the present study, in which the aim was to investigate the accuracy of ANN when predicting the expected progeny difference (EPD) of marbling score in Angus cattle. Various ANN architectures were explored, which involved two training algorithms, two types of activation functions, and from 1 to 4 neurons in hidden layers. For comparison, BayesCπ models were used to select a subset of optimal markers (referred to as feature selection), under the assumption of additive inheritance, and then the marker effects were estimated using BayesCπ with π set equal to zero. This procedure is referred to as BayesCpC and was implemented on a high-throughput computing cluster.ResultsThe ANN with Bayesian regularization method performed equally well for prediction of EPD as BayesCpC, based on prediction accuracy and sum of squared errors. With the 3K-SNP panel, for example, prediction accuracy was 0.776 using BayesCpC, and ranged from 0.776 to 0.807 using BRANN. With the selected 700-SNP panel, prediction accuracy was 0.863 for BayesCpC and ranged from 0.842 to 0.858 for BRANN. However, prediction accuracy for the ANN with scaled conjugate gradient back-propagation was lower, ranging from 0.653 to 0.689 with the 3K-SNP panel, and from 0.743 to 0.793 with the selected 700-SNP panel.ConclusionsANN with Bayesian regularization performed as well as linear Bayesian regression models in predicting additive genetic values, supporting the idea that ANN are useful as universal approximators of functions of interest in breeding contexts.

Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models.

BackgroundGenetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model.MethodsWe assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters.ResultsDesigns with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed.ConclusionThe algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.

LACTATION BIOLOGY SYMPOSIUM: The effect of nutrient intake from milk or milk replacer of preweaned dairy calves on lactation milk yield as adults: A meta-analysis of current data1

Data from calf studies conducted over the past 20 yr has shown that preweaning nutrient intake, from milk or milk replacer, can have profound effects on development of the calf that enhance first lactation and lifetime productivity. Many of the studies show positive but not significant effects of preweaning nutrition on long-term productivity, primarily due to a lack of power, usually due to inadequate animal numbers per treatment. Meta-analyses were conducted using Comprehensive Meta-Analysis (CMA) software (version 2.2.064; Biostat, Englewood, NJ; Borenstein et al., 2005) to evaluate the effects of preweaning nutrient intake and preweaning ADG on first lactation milk production from studies where milk yield and preweaning treatment data were adequately described. Currently, 12 studies have been reported, describing milk yield of calves that had been fed various levels of preweaning nutrients, from both milk and milk replacer, and 11 evaluated the effect of preweaning ADG on long-term productivity. The estimated effect size for treatment (level of milk or milk replacer intake) and ADG were calculated. Using a random effects model, the overall milk yield response based on treatment was 435 ± 117 kg/lactation (P < 0.001), demonstrating that among the data sets milk yield in the first lactation was increased by increasing nutrient intake from milk or milk replacer in preweaned calves. Meta-regression of the effect of ADG resulted in the following equation: milk yield = -106 kg + 1,551.4 kg × ADG (kg/d; P = 0.01) indicating that for every kilogram of preweaning ADG, first lactation milk yield increased by 1,550 kg. Furthermore, the meta-analysis yielded an odds ratio of 2.09 (P = 0.001) indicating that calves fed for greater preweaning ADG were 2 times more likely to have greater milk yield in the first lactation. Finally, the 2001 Dairy NRC calf model was used to estimate the difference, within study, of intake over maintenance from milk replacer, using either the actual data or the published ADG; the difference in intake over maintenance was used as a predictor in a meta-regression and resulted in the following equation: milk yield = -60 kg + 1,100 kg × estimated difference in intake over maintenance (P = 0.02). The data demonstrate that nutrient intake from milk or milk replacer during the preweaning period positively impacted long-term productivity of dairy calves and provides new management opportunities to improve milk yield of dairy cattle. These data appear to indicate that there are significant developmental functions being programmed in the neonatal calf that require further investigation.

Somatic Cells Count and Its Genetic Association with Milk Yield in Dairy Cattle Raised under Thai Tropical Environmental Conditions.

Somatic cells count (SCC), milk yield (MY) and pedigree information of 2,791 first lactation cows that calved between 1990 and 2010 on 259 Thai farms were used to estimate genetic parameters and trends for SCC and its genetic association with MY. The SCC were log-transformed (lnSCC) to make them normally distributed. An average information-restricted maximum likelihood procedure was used to estimate variance components. A bivariate animal model that considered herd-yr-season, calving age, and regression additive genetic group as fixed effects, and animal and residual as random effects was used for genetic evaluation. Heritability estimates were 0.12 (SE = 0.19) for lnSCC, and 0.31 (SE = 0.06) for MY. The genetic correlation estimate between lnSCC and MY was 0.26 (SE = 0.59). Mean yearly estimated breeding values during the last 20 years increased for SCC (49.02 cells/ml/yr, SE = 26.81 cells/ml/yr; p = 0.08), but not for MY (0.37 kg/yr, SE = 0.87 kg/yr; p = 0.68). Sire average breeding values for SCC and MY were higher than those of cows and dams (p<0.01). Heritability estimates for lnSCC and MY and their low but positive genetic correlation suggested that selection for low SCC may be feasible in this population as it is in other populations of dairy cows. Thus, selection for high MY and low SCC should be encouraged in Thai dairy improvement programs to increase profitability by improving both cow health and milk yield.

Association of milk protein genes with fertilization rate and early embryonic development in Holstein dairy cattle

Concomitant with intensive selection for increased milk yield, reproductive performance of dairy cows has declined in the last decades, in part due to an unfavourable genetic relationship between these traits. Given that the six main milk protein genes (i.e. whey proteins and caseins) are directly involved in milk production and hence have been a target of the strong selection aimed at improving milk yield in dairy cattle, we hypothesized that these genes could show selection footprints associated with fertility traits. In this study, we used an in-vitro fertilization (IVF) system to test genetic association between 66 single nucleotide polymorphisms (SNPs) in the four caseins (αS1-casein, αS2-casein, β-casein and κ-casein) and the two whey protein genes (α-lactalbumin and β-lactoglobulin) with fertilization rate and early embryonic development in the Holstein breed. A total of 6893 in-vitro fertilizations were performed and a total of 4661 IVF embryos were produced using oocytes from 399 ovaries and semen samples from 12 bulls. Associations between SNPs and fertility traits were analysed using a mixed linear model with genotype as fixed effect and ovary and bull as random effects. A multiple testing correction approach was used to account for the correlation between SNPs due to linkage disequilibrium. After correction, polymorphisms in the LALBA and LGB genes showed significant associations with fertilization success and blastocyst rate. No significant associations were detected between SNPs located in the casein region and IVF fertility traits. Although the molecular mechanisms underlying the association between whey protein genes and fertility have not yet been characterized, this study provides the first evidence of association between these genes and fertility traits. Furthermore, these results could shed light on the antagonistic relationship that exists between milk yield and fertility in dairy cattle.

Heat stress on reproductive function and fertility in mammals.

In most mammalian species including cattle, heat stress has deleterious effects on nutritional, physiological and reproductive functions. Exposure of animals to a hot environment causes an increase in body temperature in mammals, including domestic animals. High ambient temperature also causes a decrease in the length and intensity of estrus by disturbing ovarian function as well as decreasing pregnancy rate after artificial insemination. Therefore, it is important to understand the effects of heat stress on reproductive function in order to improve the production of domestic animals. Heat stress decreases appetite, weight gain, and milk yield in dairy cattle. It also adversely affects the reproductive performance of both sexes. In males, it reduces spermatogenic activity, while in females it adversely impacts oogenesis, oocyte maturation, fertilization development and implantation rate. Detection and evaluation of the deteriorating effects of heat stress on reproductive organs and cells can help to design measures to prevent them and improve reproductive functions. In this review, we discuss the impacts of heat stress on reproductive functions.

Application of support vector regression to genome-assisted prediction of quantitative traits

A byproduct of genome-wide association studies is the possibility of carrying out genome-enabled prediction of disease risk or of quantitative traits. This study is concerned with predicting two quantitative traits, milk yield in dairy cattle and grain yield in wheat, using dense molecular markers as predictors. Two support vector regression (SVR) models, ε-SVR and least-squares SVR, were explored and compared to a widely applied linear regression model, the Bayesian Lasso, the latter assuming additive marker effects. Predictive performance was measured using predictive correlation and mean squared error of prediction. Depending on the kernel function chosen, SVR can model either linear or nonlinear relationships between phenotypes and marker genotypes. For milk yield, where phenotypes were estimated breeding values of bulls (a linear combination of the data), SVR with a Gaussian radial basis function (RBF) kernel had a slightly better performance than with a linear kernel, and was similar to the Bayesian Lasso. For the wheat data, where phenotype was raw grain yield, the RBF kernel provided clear advantages over the linear kernel, e.g., a 17.5% increase in correlation when using the ε-SVR. SVR with a RBF kernel also compared favorably to the Bayesian Lasso in this case. It is concluded that a nonlinear RBF kernel may be an optimal choice for SVR, especially when phenotypes to be predicted have a nonlinear dependency on genotypes, as it might have been the case in the wheat data.

인공수정 및 수정란이식 후 젖소의 혈액과 유즙에서 Progesterone과 Estrogen 농도 변화와 수태율과의 상관관계

Early pregnancy diagnosis of bovine is an essential component for efficient reproductive plan in farms because long term of non-pregnancy results in economic losses by failure of offspring production and low milk yield in dairy cattle. The major steroid hormones related with reproduction are known to be progesterone and estrogen in bovine pregnancy. To evaluate detection level of hormones in milk, plasma and milk progestrone and estrogen of Holstein cows was analyzed during artificial insemination (AI) and embryo transfer (ET). Progesterone concentration at 21 days postestrus was significantly different in plasma and milk between pregnant and non-pregnant cows. Estrogen concentration at estrus was higher in pregnant recipients than that in non-pregnant recipients. To analyze correlation between hormone levels and conception rates in Holstein, the conception and return rates were checked following AI, and the returned cows were on the track of pregnancy after consecutive AI. Pregnant cows following first AI were considered as high conception group while pregnant cows following third AI were rated as low conception group. Proportion of high and low conception groups in this study was 78.2% and 9.1%, respectively. Hormone analysis indicated that high conception group had higher estrogen level during estrus than low conception group (26.45±3.32 vs 19.017±2.97). Progesterone level was not different between high and low conception groups during estrus but increased significantly after 21 days postestrus (21 day: 4.95±1.12 vs 0.95±0.23, 35 day: 12.47±3.82 vs 2.41±1.21). In conclusion, the pattern of progesterone and estrogen secretion in Holstein milk samples could be a good candidate for early pregnancy detection and selection of recipients during ET.

Incidence of foot and mouth disease and its effect on milk yield in dairy cattle at Andassa dairy farm, Northwest Ethiopia

A study on incidence of foot and mouth disease (FMD) was conducted at Andassa Government Dairy Farm during July to August 2008 with the objective of determining the incidence rate and to evaluate the effect of the disease on milk yield. The overall incidence of foot and mouth disease in dairy cattle of the farm was 14.55%. The incidence rate in Fogera cattle (15.52%) was significantly (p > 0.05) higher than that of Holstein-Friesian cross cattle (2.50%). The average milk yield ahead of 10 days of FMD infection (1182.86±32.13) was found significantly (p<0.05) higher than that of the milk yield 10 days after infection (602.86±18.86).The overall mortality rate of the disease was 2.24% during the study period and the mortality rate in cross cattle (2.50%) was found higher than that of Fogera cattle (2.22%). In conclusion, the results of this study indicated that the complex epidemiological situation of the disease in Ethiopia needs more detailed investigation for improved vaccine-based control is to be achieved efficiently.

Multiplex ready flow cytometric immunoassay for total insulin like growth factor 1 in serum of cattle

The European Union has banned the use of recombinant bovine somatotropins (rbST, growth hormones) to increase milk yield in dairy cattle. As direct detection of rbST in serum is problematic, methods based on the detection of changes in multiple rbST-dependent biomarkers have high potential for monitoring rbST abuse. In this study immunoassays were developed for total insulin-like growth factor 1 (IGF-1) in cow sera. Ultimately aiming at combination with other rbST-dependent biomarker assays two multiplex formats were studied and compared critically, a multi-channel surface plasmon resonance (SPR)-based biosensor and flow cytometry combined with color encoded microbeads. Moreover, a new dedicated sample pretreatment was developed for the dissociation of complexed IGF-1 in serum, while keeping other biomarkers in solution. Compared to the SPR biosensor immunoassay, the flow cytometric immunoassay (FCIA) was more sensitive, less antibody-consuming and less vulnerable to necessary but interfering reagents from the sample treatment. In an initial in-house validation study the developed FCIA showed to be fast, specific, robust, and a high repeatability and reliability, and generated realistic IGF-1 values for bovine serum, without compromising the potential for simultaneous detection of other biomarkers. Due to the xMAP technology, in which 100 different bead sets can be measured simultaneously, the total IGF-1 assay can easily be extended with other immunoassays for candidate biomarkers. Preliminary results about a FCIA for IGF-1 multiplexing with insulin-like growth factor binding protein 2 (IGFBP2) are presented which strongly supported both the FCIA multiplex format as well as the generic nature of the developed sample pretreatment.

Forced traffic in automatic milking systems effectively reduces the need to get cows, but alters eating behavior and does not improve milk yield of dairy cattle

Eighty-five lactating Holstein dairy cows in loose housing conditions in 2 symmetrical pens, each containing 28 feeding places, 3 waterers, and 1 automatic milking system (AMS), were used to evaluate the effects of the traffic type imposed on lactating cows through an AMS on milking frequency, feeding behavior, and milk production. The study was a crossover design with 2 periods and 2 treatments. Each period lasted 3 mo, with 1 mo of adaptation within each period. All cows were fed a partial mixed ration twice daily and up to 3 kg/d of a concentrate during the visits to the AMS. Treatments consisted of allowing free traffic of cows throughout the pen or forcing cows to pass through the AMS to access the feed troughs (forced traffic). Individual eating behavior and feed consumption were continuously monitored throughout the study using a computerized system. Individual milk production was recorded at each milking, and milk composition was recorded monthly. In addition, the number of cows brought to the AMS was recorded. The number of daily meals was less, whereas meal duration and meal size were greater with forced traffic (6.6±0.3 meals/d, 20.4±0.65 min/meal, and 2.7±0.09 kg/meal, respectively) than with free traffic (10.1±0.3 meals/d, 15.7±0.65 min/meal, and 1.8±0.09 kg/meal, respectively). Total dry matter intake (21.1±0.5 and 20.4±0.58 kg/d, respectively) and milk production (29.8±0.79 and 30.9±0.79 kg/d, respectively) were similar in the 2 systems. The number of voluntary and total daily milkings was greater with forced traffic (2.4±0.04 and 2.5±0.06 milkings/d, respectively) than with free traffic (1.7±0.06 and 2.2±0.04 milkings/d, respectively). Forced traffic improved the number of voluntary milkings, but altered milk quality and eating behavior of dairy cattle.