Globally, laying hen production systems are a focus of concern for animal welfare. Recently, the impacts of rearing environments have attracted atten

Virtual fencing technology restricts animal movement via communicated signals without physical boundaries. Specifically, the eShepherdTM 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 six-hectare area across eight separate paddocks for four weeks following one 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 four-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 four weeks than the virtual fence groups (P = 0.006) 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 less than 20 minutes 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 four weeks without substantial behavioural and welfare impacts on the cattle.

Global Positioning System (GPS)-based virtual fences offer the potential to improve the management of grazing animals. Prototype collar devices utilising patented virtual fencing algorithms were placed on six Angus heifers in a 6.15 hectare paddock. After a “no fence” period, sequential, shifting virtual fences restricted the animals to 40%, 60%, and 80% of the paddock area widthways and 50% lengthways across 22 days. Audio cues signaled the virtual boundary, and were paired with electrical stimuli if the animals continued forward into the boundary. Within approximately 48 h, the cattle learned the 40% fence and were henceforth restricted to the subsequent inclusion zones a minimum of 96.70% (±standard error 0.01%) of the time. Over time, the animals increasingly stayed within the inclusion zones using audio cues alone, and on average, approached the new fence within 4.25 h. The animals were thus attentive to the audio cue, not the fence location. The time spent standing and lying and the number of steps were similar between inclusion zones (all p ≥ 0.42). More lying bouts occurred at the 80% and lengthways inclusion zones relative to “no fence” (p = 0.04). Further research should test different cattle groups in variable paddock settings and measure physiological welfare responses to the virtual fencing stimuli.

To be ethically acceptable, new husbandry technologies and livestock management systems must maintain or improve animal welfare. To achieve this goal, the design and implementation of new technologies need to harness and complement the learning abilities of animals. Here, from literature on the cognitive activation theory of stress (CATS), we develop a framework to assess welfare outcomes in terms of the animal's affective state and its learned ability to predict and control engagement with the environment, including, for example, new technologies. In CATS, animals' perception of their situation occurs through cognitive evaluation of predictability and controllability (P/C) that influence learning and stress responses. Stress responses result when animals are not able to predict or control both positive and negative events. A case study of virtual fencing involving avoidance learning is described. Successful learning occurs when the animal perceives cues to be predictable (audio warning always precedes a shock) and controllable (operant response to the audio cue prevents receiving the shock) and an acceptable welfare outcome ensues. However, if animals are unable to learn the association between the audio and shock cues, the situation retains low P/C leading to states of helplessness or hopelessness, with serious implications for animal welfare. We propose a framework for determining welfare outcomes and highlight examples of how animals' cognitive evaluation of their environment and their ability to learn relates to stress responses. New technologies or systems should ensure that predictability and controllability are not at low levels and that operant tasks align with learning abilities to provide optimal animal welfare outcomes.