Shared stressful experiences affect social proximity in Merino sheep.

While it is well established that humans develop stronger relationship bonds when they share stressful experiences, there is little known on how shared stressful experiences may influence relationship bonding in animals. Here, we present a study looking at social proximity between individuals in small groups of Merino ewes following a shared stressful experience compared with control sheep that were not exposed to stress. Some sheep were familiar to each other. Analyses of social proximity using real-time-kinematic Global Navigation Satellite System (GNSS) on-animal devices showed sheep preferred to be closest to familiar individuals, but across the study duration they also developed a preference for the individuals they shared the stressful experience with, relative to their proximity to control individuals. These results contribute to limited research on what factors may instigate the development of bonds between unfamiliar sheep. Between-individual bonds may develop as a means of socially mediated stress buffering. Social bonding following a shared stressful experience aligns with human social relationships and increases our understanding of how animals perceive their conspecifics in relation to stressful environmental change.

Validation of Real-Time Kinematic (RTK) Devices on Sheep to Detect Grazing Movement Leaders and Social Networks in Merino Ewes.

Understanding social behaviour in livestock groups requires accurate geo-spatial localisation data over time which is difficult to obtain in the field. Automated on-animal devices may provide a solution. This study introduced an Real-Time-Kinematic Global Navigation Satellite System (RTK-GNSS) localisation device (RTK rover) based on an RTK module manufactured by the company u-blox (Thalwil, Switzerland) that was assembled in a box and harnessed to sheep backs. Testing with 7 sheep across 4 days confirmed RTK rover tracking of sheep movement continuously with accuracy of approximately 20 cm. Individual sheep geo-spatial data were used to observe the sheep that first moved during a grazing period (movement leaders) in the one-hectare test paddock as well as construct social networks. Analysis of the optimum location update rate, with a threshold distance of 20 cm or 30 cm, showed that location sampling at a rate of 1 sample per second for 1 min followed by no samples for 4 min or 9 min, detected social networks as accurately as continuous location measurements at 1 sample every 5 s. The RTK rover acquired precise data on social networks in one sheep flock in an outdoor field environment with sampling strategies identified to extend battery life.

Farm and cow factors and their interactions on the incidence of retained placenta in holstein dairy cows.

Risk factors for retained placenta (RP), as a common and economically important disorder, have been widely investigated. However, comprehensive studies are rare. Therefore, this study sought to identify herd-cow factors and their interactions on the risk of RP in Iranian dairy herds. The data were collected from nine Holstein dairy herds in Isfahan province, Iran. The final dataset included 154,048 records for 59,610 cows which calved between March 2011 and December 2018. A logistic regression model was used to separately analyze the risk factors and their interactions for RP in primiparous and multiparous cows. The average rate of RP was 12.3% (9.0-15.4%) at the herd level. The highest rate of RP was recorded in spring compared with other seasons. Regardless of calving season, occurrence of dystocia, stillbirth and twinning increased the odds ratio (OR) of RP. In primiparous cows, occurrence of dystocia and stillbirth increased OR of RP 4.30 and 3.33 times, respectively. In multiparous cows, dystocia, twinning and stillbirth increased OR of RP 4.36, 3.94 and 1.29 times, respectively. Cows with an age at first calving of >28 months had the highest rate of RP compared with other cows. Multiparous and primiparous cows with a short (less than 271 d) and long (more than 281 d) pregnancy, respectively, had the highest risk of RP compared to cows in other groups. Furthermore, multiparous cows with an extended dry period length (more than 75 d) and produced milk yield more than 13,000 kg/lactation were at higher risk of RP with an average of 13.5%. With an interaction analysis, although the potential effect of each factors depends on the effect of other factors, but in general dystocia, stillbirth, an extended age at first calving (>28 months), and calving during the spring increased risk of RP for both groups. In conclusion, identification of risk factors for RP with an interaction analysis can help farm managers to employ the best strategies to reduce the occurrence of this reproductive disorder.

The Influence of Predictability and Controllability on Stress Responses to the Aversive Component of a Virtual Fence.

To ensure animal welfare is not compromised, virtual fencing must be predictable and controllable, and this is achieved through associative learning. To assess the influence of predictability and controllability on physiological and behavioral responses to the aversive component of a virtual fence, two methods of training animals were compared. In the first method, positive punishment training involved sheep learning that after an audio stimulus, an electrical stimulus would follow only when they did not respond by stopping or turning at the virtual fence (predictable controllability). In the second method, classical conditioning was used to associate an audio stimulus with an electrical stimulus on all occasions (predictable uncontrollability). Eighty Merino ewes received one of the following treatments: control (no training and no stimuli in testing); positive punishment training with an audio stimulus in testing (PP); classical conditioning training with only an audio stimulus in testing (CC1); and classical conditioning training with an audio stimulus followed by electrical stimulus in testing (CC2). The stimuli were applied manually with an electronic collar. Training occurred on 4 consecutive days with one session per sheep per day. Sheep were then assessed for stress responses to the cues by measuring plasma cortisol, body temperature and behaviors. Predictable controllability (PP) sheep showed no differences in behavioral and physiological responses compared with the control treatment (P < 0.05). Predictable uncontrollability of receiving the aversive stimulus (CC2) induced a higher cortisol and body temperature response compared to the control but was not different to CC1 and PP treatments. CC2 treatment sheep showed a higher number of turning behaviors (P < 0.001), and more time spent running (P < 0.001) than the control and PP treatment groups, indicating that predictability without controllability was stressful. The behavior results also indicate that predicting the event without receiving it (CC1) was less stressful than predicting the event then receiving it (CC2), suggesting that there is a cost to confirmation of uncontrollability. These results demonstrate that a situation of predictability and controllability such as experienced when an animal successfully learns to avoid the aversive component of a virtual fence, induces a comparatively minimal stress response and does not compromise animal welfare.

Virtual Fence Responses Are Socially Facilitated in Beef Cattle.

Group-living can be socially advantageous where the behavior of individuals may be modified by group members through socially facilitative processes. Virtual fencing contains cattle by providing audio and electrical signals via a neckband device. However, little is known about social influences on learning to appropriately respond to the virtual fence (VF) cues. This study aimed to determine whether cattle respond to the behavior of conspecifics during their initial interactions with a VF across 3 days. Sixty-four Angus steers, naïve to virtual fencing, were placed into 8 paddocks (8 animals/group), divided with a VF into two areas- an inclusion and exclusion zone. The animals received an audio cue if they approached the VF followed by an electrical pulse if they continued into the exclusion zone. The GPS and audio and electrical stimuli data were recorded. To quantify social facilitation, individual VF interactions were grouped into 179 "events" across 3 days; starting from when the first animal (leader) approached the VF. The responses of other animals were categorized as (1) followed the leader to move into the exclusion zone (followers, F), (2) accompanied the leader back into the inclusion zone (facilitated, Fa), (3) did not show any reaction (non-facilitated, NFa). A social facilitation score (SFaS) was calculated as SFaS (%) = (F/(Fa+NFa+F)) * 100. A single leader animal led on average 37% of events with 76.2% of all reactions categorized as facilitated by other individuals. Animals responded to the behavior of conspecifics more during the VF implementation compared with facilitated movement during natural grazing patterns when no VF was present (P < 0.001). On average, cattle stopped or turned away to 3.8 (± 2.9 SE) audio cues before ever receiving their first electrical pulse. There was a positive correlation (R = 0.34, P = 0.006) between the number of audio cues received prior to the first electrical pulse and the proportion of all audio cues that were not followed by an electrical pulse. In conclusion, cattle stayed within the inclusion zone based on the response of conspecifics, including some social impacts on individual rates of associative learning between the audio and electrical cues.

Effect of abortion on milk production, health, and reproductive performance of Holstein dairy cattle.

The objective of this study was to identify the effect of abortion on performance of Iranian Holstein cows that calved between 2005-2014. Abortion records were categorized in two groups: 1) new abortion (NLA), and 2) rebreeding abortion (RA). Production data (305-d milk, fat, and protein yields) were analyzed using PROC MIXED, number of inseminations per lactation period (INS), postpartum health disorders (PPHD), and culling records using PROC GLIMMIX, and calving to conception records using PROC PHREG of SAS software (SAS Institute, 2013). For each separate model, main herd-cow factors and all two-way significant interactions were considered in the analyses with results being reported for each calving status by lactation period. In total, 12.5 % of lactation periods were associated with at least one case of abortion, while 1.9 % of the lactation periods commenced with an abortion. Based on results from the present study, milk production decreased for cows having abortion classified as NLA or RA. Overall, when there was a RA, there was an increase in median days non-pregnant (DNP) by 132 d and INS by 1.6, whereas cows with NLA had median DNP of 15 d less and an INS of 0.17 less than cows with normal parturitions. Compared with cows with normal parturitions, cows with a NLA were 1.24, 1.88, and 2.41 times more likely to have PPHD, and be culled from the herd for involuntary reasons and reasons related to reproduction, respectively. The results of this study indicate abortions were associated with cow health and milk production and reproductive performance, indicating losses due to abortion are not only a direct result of the loss of a pregnancy.

Machine learning algorithms, bull genetic information, and imbalanced datasets used in abortion incidence prediction models for Iranian Holstein dairy cattle.

The ability to predict abortion incidence, especially in regions with high abortion rates (e.g., Iran), helps improve reproductive performance and, thereby, dairy farm profitability. The objective of this study was to predict pregnancy loss in Iranian dairy herds. For this purpose, the cow history records and bull genetic information available at 6 large commercial dairy farms with cows calved between 2005 and 2014 were extracted from an on-farm record-keeping software. Using WEKA, 12 commonly used machine learning (ML) algorithms were applied to the dataset. The algorithms belonged to 5 classifier groups which were Bayes, meta, functions, rules, and trees. The original dataset including herd-cow factors was randomly divided into 2 subsets: a training dataset and a test one (at a ratio of 60:40). The original dataset was combined with the bull genetic information to create a full dataset. The average abortion rate was 15.4 %, which represented an imbalanced dataset. Therefore, 2 down- and up-sampling techniques were additionally implemented on the original dataset (more specifically on the training one) to create 2 balanced datasets. This ultimately yielded 4 datasets; original, full, down-sampling, and up-sampling. Different algorithms and models were evaluated based on F-measure and area under the curve (AUC). Based on the results obtained, ML algorithms exhibited a high performance in predicting abortion when applied to the balanced dataset. However, their performance varied from 32.3 % (poor) to 69.2 % (medium upward) when applied to the imbalanced original dataset. In addition to the imbalance in the original dataset, the reason for these poor results were attributed to the high proportion of unknown risk factors underlying abortion incidence. Even when including the bull genetic information, it did not lead to any significant improvements in the prediction model. From among the datasets used, the Bayes algorithms outperformed the others in predicting pregnancy losses while rules had the worst performance. Furthermore, while the Bayes algorithms were not affected by the type of dataset (balanced or imbalanced), substantial increases in F-measure and AUC were observed for rules, trees, and functions with balanced datasets. Overall, the balanced models outperformed the others, with the down-sampling method exhibiting the highest performance. Despite the fact that the prediction models used in this study did not perform as expected, it was shown that they can be beneficially used to predict and reduce pregnancy losses, despite their moderate accuracy, especially when used for herds with high abortion rates and low reproductive performances.

Virtual Fencing Is Comparable to Electric Tape Fencing for Cattle Behavior and Welfare.

Virtual fencing technology restricts animal movement via communicated signals without physical boundaries. Specifically, the eShepherd™ automated virtual fencing system operates via GPS technology and provides stimuli via a neckband device. An audio warning tone is emitted at the virtual boundary which is followed by an electrical pulse if the animal continues moving forward. Animal welfare is a priority consideration for the commercial implementation of virtual fencing systems. The current study assessed the effects of a virtual fence, in comparison to an electric tape fence, to contain eight groups of eight 12-14 month old steers within a 6-ha area across eight separate paddocks for 4 weeks following 1 week acclimation to the paddocks. Cattle were assessed across two cohorts (four groups/cohort) from January until March 2019 in Australia. Body weight and fecal samples from each animal were taken weekly. Fecal samples were processed for fecal cortisol metabolite (FCM) concentrations. IceQube R®'s fitted to the leg measured individual lying and standing time and the virtual fencing neckbands recorded GPS location and all administered audio and electrical stimuli. Cattle were maintained within their allocated area by both fence types across the 4-week period and those with the virtual fences were responding correctly to the audio cue with an average of 71.51 ± 2.26% of all cues across all animals being audio only. There was individual variation in rate of learning. The electric tape groups in cohort 1 showed a greater increase in body weight over 4 weeks than the virtual fence groups (P < 0.001) but this difference was not confirmed in cohort 2. The fence type statistically influenced the total daily lying time (P = 0.02) with less lying in cattle from the virtual fence groups but this difference equated to an average of <20 min per day. There were no differences between fence types in FCM concentrations (P = 0.39) and the concentrations decreased across time for all cattle (P < 0.001). These results indicate that virtual fencing technology effectively contains animals in a prescribed area across 4 weeks without substantial behavioral and welfare impacts on the cattle.