Publications by authors named "Claudia Bahr"

The objective of this study was to determine if a 3-dimensional computer vision automatic locomotion scoring (3D-ALS) method was able to outperform human observers for classifying cows as lame or nonlame and for detecting cows affected and nonaffected by specific type(s) of hoof lesion. Data collection was carried out in 2 experimental sessions (5 mo apart). In every session all cows were assessed for (1) locomotion by 2 observers (Obs1 and Obs2) and by a 3D-ALS; and (2) identification of different types of hoof lesions during hoof trimming (i.

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Three sources of sensory data: cow's individual rumination duration, activity and milk yield were evaluated as possible indicators for clinical diagnosis, focusing on post-calving health problems such as ketosis and metritis. Data were collected from a computerised dairy-management system on a commercial dairy farm with Israeli Holstein cows. In the analysis, 300 healthy and 403 sick multiparous cows were studied during the first 3 weeks after calving.

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The objective of this study was to design and validate a mathematical model to detect post-calving ketosis. The validation was conducted in four commercial dairy farms in Israel, on a total of 706 multiparous Holstein dairy cows: 203 cows clinically diagnosed with ketosis and 503 healthy cows. A logistic binary regression model was developed, where the dependent variable is categorical (healthy/diseased) and a set of explanatory variables were measured with existing commercial sensors: rumination duration, activity and milk yield of each individual cow.

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Bovine respiratory disease (BRD) complex in calves impairs health and welfare and causes severe economic losses for the Stockperson. Early recognition of BRD should lead to earlier veterinary (antibiotic/anti-inflammatory) treatment interventions thereby reducing the severity of the disease and associated costs. Coughing is one of the clinical manifestations of BRD.

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Despite the research on opportunities to automatically measure lameness in cattle, lameness detection systems are not widely available commercially and are only used on a few dairy farms. However, farmers need to be aware of the lame cows in their herds in order treat them properly and in a timely fashion. Many papers have focused on the automated measurement of gait or behavioral cow characteristics related to lameness.

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Lameness is still an important problem in modern dairy farming. Human observation of locomotion, by looking at different traits in one go, is used in practice to assess locomotion. The objectives of this article were to determine which individual locomotion traits are most related to locomotion scores in dairy cows, and whether experienced raters are capable of scoring these individual traits consistently.

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Image processing systems have been widely used in monitoring livestock for many applications, including identification, tracking, behavior analysis, occupancy rates, and activity calculations. The primary goal of this work was to quantify image processing performance when monitoring laying hens by comparing length of stay in each compartment as detected by the image processing system with the actual occurrences registered by human observations. In this work, an image processing system was implemented and evaluated for use in an environmental animal preference chamber to detect hen navigation between 4 compartments of the chamber.

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The objective of this review was to describe, compare and evaluate agreement, reliability, and validity of manual and automatic locomotion scoring systems (MLSSs and ALSSs, respectively) used in dairy cattle lameness research. There are many different types of MLSSs and ALSSs. Twenty-five MLSSs were found in 244 articles.

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Locomotion scores are used for lameness detection in dairy cows. In research, locomotion scores with 5 levels are used most often. Analysis of scores, however, is done after transformation of the original 5-level scale into a 4-, 3-, or 2-level scale to improve reliability and agreement.

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It is known that pigs raised in enriched environments express less aggressive behaviour. For this reason, a new method of cognitive environmental enrichment was experimented at the University of Veterinary Medicine Hannover, Germany. In the first phase, 78 suckling piglets were trained to learn the link between a sound given by an electronic feeder and a feed reward in the form of chocolate candies during a period of 8 days.

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The aim of this study was to identify, quantify, and describe pre-signs of aggression in pigs and the early stages of aggressive interactions. The experiment was carried out at a commercial farm on a group of 11 male pigs weighing on average 23 kg and kept in a pen of4 m x 2.5 m.

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One of the largest animal welfare problems in modern pig production is tail biting. This abnormal behaviour compromises the well-being of the animals, can seriously impair animal health and can cause considerable economic losses. Tail biting has a multifactorial origin and occurs mainly in fattening pigs.

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Objective: Xylosyltransferase I (XT-I) is the chain-initiating enzyme in the biosynthesis of proteoglycans in basement membranes. It catalyzes the transfer of xylose to selected serine residues in the core protein. The XYLT-II gene codes for a protein highly homologous to XT-I.

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Xylosyltransferase I (XT-I) catalyzes the transfer of xylose from UDP-xylose to serine residues in proteoglycan core proteins. This is the first and apparently rate-limiting step in the biosynthesis of the tetrasaccharide linkage region in glycosaminoglycan-containing proteoglycans. The XYLT-II gene codes for a highly homologous protein, but its physiological function is not yet known.

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