Publications by authors named "Christa Egger-Danner"

The increased uptake of sensor technologies and precision farming tools for the dairy cattle sector is enabling real-time monitoring of animal health, welfare, and productivity. These digital advancements provide high-frequency, objective, and large-scale phenotypic data for breeding purposes. This review explores the potential of sensor-derived data to improve genetic and genomic evaluations in dairy cattle and outlines key challenges, opportunities, and approaches associated with their implementation.

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The deployment of diverse data-generating technologies in livestock farming holds the promise of early disease detection and improved animal well-being. In this paper, we combine routinely collected dairy farm and herd data with weather and high-frequency sensor data from 6 farms to predict new lameness events in various future periods, spanning from the following day to 3 wk. A Random Forest classifier, using input features selected by the Boruta algorithm, was used for the prediction task; effects of individual features were further assessed using partial dependence plots.

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Genetic improvement of udder health in dairy cows is of high relevance as mastitis is one of the most prevalent diseases. Since it is known that the heritability of mastitis is low and direct data on mastitis cases are often not available in large numbers, auxiliary traits, such as somatic cell count (SCC) are used for the genetic evaluation of udder health. In previous studies, models to predict clinical mastitis based on mid-infrared (MIR) spectral data and a somatic cell count-derived score (SCS) were developed.

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The aim of this study was to investigate the prevalence of ESBL/AmpC-producing and the resistance pattern of commensal , as well as the link between the use of antibiotics (AMU) and the occurrence of resistance in on Austrian dairy farms. AMU data from 51 farms were collected over a one-year period in 2020. Fecal samples were collected from cows, pre-weaned and weaned calves in 2020 and 2022.

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Mid-infrared (MIR) spectroscopy is routinely applied to determine major milk components, such as fat and protein. Moreover, it is used to predict fine milk composition and various traits pertinent to animal health. MIR spectra indicate an absorbance value of infrared light at 1060 specific wavenumbers from 926 to 5010 cm.

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This study aimed to develop a tool to detect mildly lame cows by combining already existing data from sensors, AMSs, and routinely recorded animal and farm data. For this purpose, ten dairy farms were visited every 30-42 days from January 2020 to May 2021. Locomotion scores (LCS, from one for nonlame to five for severely lame) and body condition scores (BCS) were assessed at each visit, resulting in a total of 594 recorded animals.

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Monitoring for mastitis on dairy farms is of particular importance, as it is one of the most prevalent bovine diseases. A commonly used indicator for mastitis monitoring is somatic cell count. A supplementary tool to predict mastitis risk may be mid-infrared (MIR) spectroscopy of milk.

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While benchmarking is already used for the assessment of performance gaps in cattle herd management and welfare concerns, its application to quantifying claw health performance is relatively new. The goal here was to establish a benchmarking system for claw health in Austrian dairy cattle. We used electronically registered claw health data of cows from 512 dairy herds documented by professional hoof trimmers, culling data from the same herds, and locomotion scores taken at regular milk performance testings in 99 dairy herds during 2020.

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In this study we present systematic framework to analyse the impact of farm profiles as combinations of environmental conditions and management practices on common diseases in dairy cattle. The data used for this secondary data analysis includes observational data from 166 farms with a total of 5828 dairy cows. Each farm is characterised by features from five categories: husbandry, feeding, environmental conditions, housing, and milking systems.

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Livestock farming is currently undergoing a digital revolution and becoming increasingly data-driven. Yet, such data often reside in disconnected silos making them impossible to leverage their full potential to improve animal well-being. Here, we introduce a precision livestock farming approach, bringing together information streams from a variety of life domains of dairy cattle to study whether including more and diverse data sources improves the quality of predictions for eight diseases and whether using more complex prediction algorithms can, to some extent, compensate for less diverse data.

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Genetic heterogeneity denotes the situation when different genetic architectures underlying diverse populations result in the same phenotype. In this study, we explore the genetic background underlying differences in the incidence of hoof disorders between Braunvieh and Fleckvieh cattle in the context of genetic heterogeneity between the breeds. Despite potentially higher power of testing due to twice as large sample size, none of the SNPs was significantly associated with the total number of hoof disorders in Fleckvieh, while 15 SNPs were significant in Braunvieh.

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This study reports on the exploration of temporal relationships between milk mid-infrared predicted biomarkers and lameness events. Lameness in dairy cows is an issue that can vary greatly in severity and is of concern for both producers and consumers. Metabolic disorders are often associated with lameness.

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The aim of this study was twofold: first, to evaluate the influence of body weight on the efficiency of dairy cows, and second, to analyze the current state of dairy cattle populations as part of the Austrian Cattle Breeding Association's Efficient Cow project. Data of Fleckvieh (FV, dual-purpose Simmental), Fleckvieh Red Holstein (FV RH), Holstein (HF) and Brown Swiss (BS) dairy cows (161 farms, 6098 cows) were collected at each performance recording during the year 2014. In addition to routinely recorded data (e.

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Antimicrobial use in livestock production is a controversial subject. While antimicrobials should be used as little as possible, it is still necessary, from both an animal health and welfare point of view, to treat infected animals. The study presented here aimed to analyse antimicrobial use on Austrian dairy farms by calculating the number of Defined Course Doses (DCD) administered per cow and year for dry cow therapy.

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Bovine mastitis is the most frequently reported disease among dairy cows worldwide. Treatment of udder disease often involves the use of antimicrobial substances, which is difficult to justify with respect to their possible effect on the development and spread of antimicrobial resistance. Prevention of udder disease is therefore always preferable to treatment.

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The objective of this study was to predict cows' body weight from body size measurements and other animal data in the lactation and dry periods. During the whole year 2014, 6306 cows (on 167 commercial Austrian dairy farms) were weighed at each routine performance recording and body size measurements like heart girth (HG), belly girth (BG), and body condition score (BCS) were recorded. Data on linear traits like hip width (HW), stature, and body depth were collected three times a year.

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Background: Antimicrobial use in livestock production is an important contemporary issue, which is of public interest worldwide. Antimicrobials are not freely available to Austrian farmers and can only be administered to livestock by veterinarians, or by farmers who are trained members of the Animal Health Service. Since 2015, veterinarians have been required by law to report antimicrobials dispensed to farmers for use in food-producing animals.

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To optimize breeding objectives of Fleckvieh and Brown Swiss cattle, economic values were re-estimated using updated prices, costs, and population parameters. Subsequently, the expected selection responses for the total merit index (TMI) were calculated using previous and newly derived economic values. The responses were compared for alternative scenarios that consider breeders' preferences.

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