Failure to remove bluetongue serotype 8 virus (BTV-8) from in vitro produced and in vivo derived bovine embryos and subsequent transmission of BTV-8 to recipient cows after embryo transfer

The behavior of BTV-8 in cattle is different from most other serotypes not only with regards to clinical signs but certainly with respect to virus transmission (transplacental, contact). Therefore, the possibility of virus transmission by means of embryo transfer was examined by in vitro exposure of in vitro produced and in vivo derived bovine blastocysts to BTV-8 followed by different washing protocols, including longer exposure times (up to 120 s) to 0.25% trypsin at room temperature or at 37 degrees C. None of the washing protocols used was successful in removing the viral genome completely from the in vitro produced and in vivo derived embryos as was demonstrated by real-time PCR. Moreover, BTV-8 virus was transmitted to recipient cows after embryo transfer of in vivo derived BTV8-exposed embryos, which had been subjected to routine decontamination as recommended by IETS, consisting of 5 washes in PBS followed by a double treatment of 0.25% trypsin for 45s at 37 degrees C, and an additional 5 washes in PBS with 2% FCS. This study clearly demonstrates the necessity of vigorous application of the directives for screening of potential donors and the collected embryos, especially in regions with BTV-8, to prevent transmission of the disease

Characterization of the on-body path Loss at 2.45 GHz and energy efficient WBAN design for dairy cows

Wireless body area networks (WBANs) provide promising applications in the healthcare monitoring of dairy cows. The characterization of the path loss (PL) between on-body nodes constitutes an important step in the deployment of a WBAN. In this paper, the PL between nodes placed on the body of a dairy cow was determined at 2.45 GHz. Finite-difference time domain simulations with two half-wavelength dipoles placed 20 mm above a cow model were performed using a 3-D electromagnetic solver. Measurements were conducted on a live cow to validate the simulation results. Excellent agreement between measurements and simulations was achieved and the obtained PL values as a function of the transmitter-receiver separation were well fitted by a lognormal PL model with a PL exponent of 3.1 and a PL at reference distance ( 10 cm) of 44 dB. As an application, the packet error rate ( PER) and the energy efficiency of different WBAN topologies for dairy cows (i.e., single-hop, multihop, and cooperative networks) were investigated. The analysis results revealed that exploiting multihop and cooperative communication schemes decrease the PER and increase the optimal payload packet size. The analysis results revealed that exploiting multihop and cooperative communication schemes increase the optimal payload packet size and improve the energy efficiency by 30%

On the use of on-cow accelerometers for the classification of behaviours in dairy barns

Analysing behaviours can provide insight into the health and overall well-being of dairy cows. Automatic monitoring systems using e.g., accelerometers are becoming increasingly important to accurately quantify cows' behaviours as the herd size increases. The aim of this study is to automatically classify cows' behaviours by comparing leg- and neck-mounted accelerometers, and to study the effect of the sampling rate and the number of accelerometer axes logged on the classification performances. Lying, standing, and feeding behaviours of 16 different lactating dairy cows were logged for 6 h with 3D-accelerometers. The behaviours were simultaneously recorded using visual observation and video recordings as a reference. Different features were extracted from the raw data and machine learning algorithms were used for the classification. The classification models using combined data of the neck- and the leg-mounted accelerometers have classified the three behaviours with high precision (80-99%) and sensitivity (87-99%). For the leg-mounted accelerometer, lying behaviour was classified with high precision (99%) and sensitivity (98%). Feeding was classified more accurately by the neck-mounted versus the leg-mounted accelerometer (precision 92% versus 80%; sensitivity 97% versus 88%). Standing was the most difficult behaviour to classify when only one accelerometer was used. In addition, the classification performances were not highly influenced when only X, X and Z, or Z and Y axes were used for the classification instead of three axes, especially for the neck-mounted accelerometer. Moreover, the accuracy of the models decreased with about 20% when the sampling rate was decreased from 1 Hz to 0.05 Hz

Localization and accelerometer sensors for the detection of oestrus in dairy cattle

The aim of this work was to combine ultra-wide band (UWB) localisation tracking, a neck-mounted accelerometer and a leg-mounted accelerometer for the detection of oestrus in dairy cows. Twelve Holstein cows with successful artificial insemination (AI) were used in this study. The sensors were attached two weeks before the expected day of oestrus and removed after AI. Different cow variables (e.g. lying time, number of steps, ruminating time, travelled distance) were extracted from the raw sensor data and used to build and test the detection models. Logistic regression models were developed for each individual sensor as well as for each combination of sensors (two or three). The performances were similar when one sensor was used only as when combining the neck- and leg-mounted accelerometer (sensitivity (Se) =75-78%, area under curve (AUC) =93-94%). The performance increased when localisation was combined with either the neck- or leg-mounted accelerometer, especially for the sensitivity (80% for leg accelerometer + localisation and 88% for neck accelerometer + localisation). The AUC were nearly the same (97%). The best performance was obtained with the combination of all three sensors (Se = 90%, AUC = 99%). Future work will consist of expanding this research to other herds with larger sample size as well as considering cows’ anomalies (e.g. mastitis, lameness) and other sensors (e.g. bolus or eartag to measure the temperature)