For several decades, breeding goals in dairy cattle focussed on increased milk production. However, many functional traits have negative genetic correlations with milk yield, and reductions in genetic merit for health and fitness have been observed. Herd management has been challenged to compensate for these effects and to balance fertility, udder health and metabolic diseases against increased production to maximize profit without compromising welfare. Functional traits, such as direct information on cow health, have also become more important because of growing concern about animal well-being and consumer demands for healthy and natural products. There are major concerns about the impact of drugs used in veterinary medicine on the spread of antibiotic-resistant strains of bacteria that can negatively impact human health. Sustainability and efficiency are also increasingly important because of the growing competition for high-quality, plant-based sources of energy and protein. Disruptions to global environments because of climate change may encourage yet more emphasis on these traits. To be successful, it is vital that there be a balance between the effort required for data recording and subsequent benefits. The motivation of farmers and other stakeholders involved in documentation and recording is essential to ensure good data quality. To keep labour costs reasonable, existing data sources should be used as much as possible. Examples include the use of milk composition data to provide additional information about the metabolic status or energy balance of the animals. Recent advances in the use of mid-infrared spectroscopy to measure milk have shown considerable promise, and may provide cost-effective alternative phenotypes for difficult or expensive-to-measure traits, such as feed efficiency. There are other valuable data sources in countries that have compulsory documentation of veterinary treatments and drug use. Additional sources of data outside of the farm include, for example, slaughter houses (meat composition and quality) and veterinary labs (specific pathogens, viral loads). At the farm level, many data are available from automated and semi-automated milking and management systems. Electronic devices measuring physiological status or activity parameters can be used to predict events such as oestrus, and also behavioural traits. Challenges concerning the predictive biology of indicator traits or standardization need to be solved. To develop effective selection programmes for new traits, the development of large databases is necessary so that high-reliability breeding values can be estimated. For expensive-to-record traits, extensive phenotyping in combination with genotyping of females is a possibility.

Metabolic disorders are disturbances to one or more of the metabolic processes in dairy cattle. Dysfunction of any of these processes is associated with the manifestation of metabolic diseases or disorders. In this review, data recording, incidences, genetic parameters, predictors, and status of genetic evaluations were examined for (1) ketosis, (2) displaced abomasum, (3) milk fever, and (4) tetany, as these are the most prevalent metabolic diseases where published genetic parameters are available. The reported incidences of clinical cases of metabolic disorders are generally low (less than 10% of cows are recorded as having a metabolic disease per herd per year or parity/lactation). Heritability estimates are also low and are typically less than 5%. Genetic correlations between metabolic traits are mainly positive, indicating that selection to improve one of these diseases is likely to have a positive effect on the others. Furthermore, there may also be opportunities to select for general disease resistance in terms of metabolic stability. Although there is inconsistency in published genetic correlation estimates between milk yield and metabolic traits, selection for milk yield may be expected to lead to a deterioration in metabolic disorders. Under-recording and difficulty in diagnosing subclinical cases are among the reasons why interest is growing in using easily measurable predictors of metabolic diseases, either recorded on-farm by using sensors and milk tests or off-farm using data collected from routine milk recording. Some countries have already initiated genetic evaluations of metabolic disease traits and currently most of these use clinical observations of disease. However, there are opportunities to use clinical diseases in addition to predictor traits and genomic information to strengthen genetic evaluations for metabolic health in the future.

Routine recording of claw health status at claw trimming of dairy cattle has been established in several countries, providing valuable data for genetic evaluation. In this review, we examine issues related to genetic evaluation of claw health; discuss data sources, trait definitions, and data validation procedures; and present a review of genetic parameters, possible indicator traits, and status of genetic and genomic evaluations for claw disorders. Different sources of data and traits can be used to describe claw health. Severe cases of claw disorders can be identified by veterinary diagnoses. Data from lameness and locomotion scoring, activity information from sensors, and feet and leg conformation traits are used as auxiliary traits. The most reliable and comprehensive information is data from regular hoof trimming. In genetic evaluation, claw disorders are usually defined as binary traits, based on whether or not the claw disorder was present (recorded) at least once during a defined time period. The traits can be specific disorders, composite traits, or overall claw health. Data validation and editing criteria are needed to ensure reliable data at the trimmer, herd, animal, and record levels. Different strategies have been chosen, reflecting differences in herd sizes, data structures, management practices, and recording systems among countries. Heritabilities of the most commonly analyzed claw disorders based on data from routine claw trimming were generally low, with ranges of linear model estimates from 0.01 to 0.14, and threshold model estimates from 0.06 to 0.39. Estimated genetic correlations among claw disorders varied from -0.40 to 0.98. The strongest genetic correlations were found among sole hemorrhage (SH), sole ulcer (SU), and white line disease (WL), and between digital/interdigital dermatitis (DD/ID) and heel horn erosion (HHE). Genetic correlations between DD/ID and HHE on the one hand and SH, SU, or WL on the other hand were, in most cases, low. Although some of the studies were based on relatively few records and the estimated genetic parameters had large standard errors, there was, with some exceptions, consistency among studies. Various studies evaluate the potential of various data soureces for use in breeding. The use of hoof trimming data is recommended for maximization of genetic gain, although auxiliary traits, such as locomotion score and some conformation traits, may be valuable for increasing the reliability of genetic evaluations. Routine genetic evaluation of direct claw health has been implemented in the Netherlands (2010); Denmark, Finland, and Sweden (joint Nordic evaluation; 2011); and Norway (2014), and other countries plan to implement evaluations in the near future.

Three breeds (Fleckvieh, Holstein, and Jersey) were included in a reference population, separately and together, to assess the accuracy of prediction of genomic breeding values in single-breed validation populations. The accuracy of genomic selection was defined as the correlation between estimated breeding values, calculated using phenotypic data, and genomic breeding values. The Holstein and Jersey populations were from Australia, whereas the Fleckvieh population (dual-purpose Simmental) was from Austria and Germany. Both a BLUP with a multi-breed genomic relationship matrix (GBLUP) and a Bayesian method (BayesA) were used to derive the prediction equations. The hypothesis tested was that having a multi-breed reference population increased the accuracy of genomic selection. Minimal advantage existed of either GBLUP or BayesA multi-breed genomic evaluations over single-breed evaluations. However, when the goal was to predict genomic breeding values for a breed with no individuals in the reference population, using 2 other breeds in the reference was generally better than only 1 breed.

A project to establish an Austria-wide health-monitoring system for cattle was launched in 2006. Veterinary diagnostic data subject to documentation by law [Law on the Control of Veterinary Medicinal Products (Tierarzneimittelkontrollgesetz)] are standardized, validated, and recorded in a central database. This Austria-wide project is a collaboration among agricultural and veterinary organizations as well as universities, and is also supported by the Austrian government. In addition to providing information for herd management and preventive measures, further objectives of the project include estimating breeding values for health traits and monitoring the overall health status of Austria's cattle. To ensure a high level of participation from farmers and veterinarians, data security issues are extremely important. Valid data are the prerequisite for the efficient use of health records. The challenge hereby is to distinguish between farms with low frequencies of diseases and incomplete documentation and recording. Measures were undertaken to establish a routine monitoring system for direct health traits. A routine genetic evaluation for direct health traits as part of the joint breeding value estimation program between Germany and Austria was introduced for Fleckvieh in December 2010, based on diagnostic data from 5,428 farms with 147,764 Fleckvieh cows. In 2010 to 2011, the reporting of direct health traits as a compulsory part of performance recording and the breeding program was introduced as well. The overall challenge is the availability of sufficient valid direct health data for reliable breeding values. Practical experience gained in Austria in setting up a health registration system, focusing mainly on the availability of direct health data for breeding purposes with its successes and difficulties, is described.

The genetic correlations (r a ) of milk lactose percentage (LP), lactose yield (LY), and ratios of LP to other milk solids with udder, metabolic, and fertility disorders have not been assessed in dairy cattle so far. To evaluate the potential role of milk lactose as indicator of cow health, 142,285 lactation records of 84,289 Austrian Fleckvieh cows were analyzed with univariate and bivariate animal models. Milk traits were on a 150-d basis and health traits were coded as binary (0/1). Other than LP and LY, 3 new phenotypes were defined and included in the present study, namely the lactose-to-fat, lactose-to-protein, and lactose-tosolids ratios. The most heritable trait was LP (0.566 ± 0.008) and heritability of LY was much lower (0.145 ± 0.005). Heritability estimates close to 0.50 were assessed for the ratios. The frequency of health disorders was higher in multiparous cows yielding milk with low LP (≤4.553%) compared with cows yielding milk with high LP (≥5.045%). Heritabilities of health traits were in the expected ranges, with the highest estimate for ovarian cysts (CYS; 0.037 ± 0.004) and the lowest for retained placenta (0.005 ± 0.001). Mastitis (MAS) genetically correlated with LY (0.518 ± 0.057); considering that the amount of synthesized lactose is the key regulator of milk volume, this result confirmed that high-producing cows are more genetically susceptible to MAS than low-producing animals. Similar to MAS, ketosis (KET) was also positively genetically associated with LY (0.420 ± 0.077) and a weak and unfavorable r a between KET and lactose-to-protein ratio was estimated (0.159 ± 0.077). The r a of LY with milk fever (MFV) and CYS were approximately 0.20. The r a of LP with MAS, KET, and MFV were negative (−0.142 on average), supporting the idea that LP is a potential health indicator. Genetic correlations between health traits ranged from zero (retained placenta with MAS and CYS) to 0.463 ± 0.090 (MAS and MFV). Results of the present study suggest that LP has potentiality to be used as indicator trait to improve udder health in Austrian Fleckvieh population.

The objective of this study was to estimate genetic parameters for various reproductive disorders based on veterinary diagnoses for Austrian Fleckvieh (Simmental) dual-purpose cattle. The health traits analyzed included retained placenta, puerperal diseases, metritis, silent heat and anestrus, and cystic ovaries. Three composite traits were also evaluated: early reproductive disorders, late reproductive disorders, and all reproductive disorders. Heritabilities were estimated with logit threshold sire, linear sire, and linear animal models. The threshold model estimates for heritability ranged from 0.01 to 0.14, whereas the linear model estimates were lower, ranging from 0.005 to 0.04. Rank correlations among random effects of sires from linear and threshold sire models were high (>0.99), whereas correlations between any sire model (linear, threshold) and the linear animal model were lower (0.88-0.92). Genetic correlations among reproductive disorders, fertility traits, and milk yield were estimated with bivariate linear animal models. Fertility traits included interval from calving to first insemination, nonreturn rate at 56 d, and interval between first and last insemination. Milk yield was calculated as the mean from test-day 1 and test-day 2 after calving. Estimated genetic correlations were 1 among metritis, retained placenta, and puerperal diseases and 0.85 between silent heat-anestrus and cystic ovaries. Low to moderate correlations (-0.01 to 0.68) were obtained among the other disorders. Genetic correlations between reproductive disorders and fertility traits were favorable, whereas antagonistic relationships were observed between milk yield in early lactation and reproductive disorders. Pearson correlations between estimated breeding values for reproductive disorders and other routinely evaluated traits were computed, which revealed noticeable favorable relationships to longevity, calving ease maternal, and stillbirth maternal. The results showed that data from the Austrian health monitoring project can be used for genetic selection against reproductive disorders in Fleckvieh cattle.

2019) Analysis of lactating cows in commercial Austrian dairy farms: diet composition, and influence of genotype, parity and stage of lactation on nutrient intake, body weight and body condition score, Italian ABSTRACT This study characterises diets used on-farm and examines nutrient and feed intake (DMI) together with other animal specific traits (body weight, milk yield, body condition score). Data came from the project 'Efficient Cow' to develop efficiency traits for Austrian cattle breeding (161 farms, 6105 cows, one-year data collection). Most diets were grass silage-or maize silagebased. Nearly half (42.8%) of the records were diets with separately fed concentrate or were partial mixed rations (PMR, 42.9%), and 12.0% were total mixed rations (TMR). Feedstuffs from permanent grassland ranged between 62% (TMR) and 84% (pure forage diets) of forage. Partial mixed rations and TMR showed the highest average proportion of maize silage (30%). The little importance of pure forage diets and pasture reflected the above-average production level of the farms. Most production traits increased from Fleckvieh (FV) over FV groups with increasing Red Holstein (RH) genes to Holstein Friesian (HF). The FV group with highest RH proportion and HF had the highest energy corrected milk yield (ECM) and DMI (29.3 vs. 29.2 kg ECM/d; 20.8 vs. 20.9 kg DMI/d). Brown Swiss (BS) and FV had lower levels (26.5 vs. 26.7 kg ECM/d; 19.8 vs. 19.7 kg DMI/d). Body condition declined in relation to proportion of RH genes from FV to HF (FV 3.42 Pt., BS 2.88 Pt., HF 2.61 Pt.). The study allowed a broad view on the continuous spectrum between dual-purpose and dairy breeds due to the different characteristics of metabolism and on the common diets on Austrian dairy farms. HIGHLIGHTS Study to develop efficiency traits for cattle breeding Broad view on feed intake and common diets on Austrian dairy farms ARTICLE HISTORY 132 132 132 132 131 131 132 131 b 132 a 131 a,b 132 a,b 131 132 131 132 132 131 131 132 132 132 132 131