Unique markings or body-mounted sensors facilitate data collection from individuals in large groups of similar-looking conspecifics but may have unintended consequences on behavior. A wireless sensor attached to the back of laying hens via a harness has been developed to monitor space use and activity. Prior to collecting experimental data, effects of the sensor on resource use and social interactions were assessed. Four rooms of 135 hens each were weighed and 10 hens/room were randomly fitted with sensors at 11 wk of age (0 d). Instantaneous scan samples recorded the number of hens (SEN: sensor-wearing hen, and NON: hen without sensor) using resources (feeder, water, nest box, perch) every 5 min over 24 h on -5 d, -4 d, -2 d, -1 d, 1 d, 2 d, 4 d, 8 d, and 16 d. Logistic regression determined that SEN feeder use was less on 1 d and 2 d and more on 16 d than NON feeder use. The SEN water use was reduced only on 1 d. The SEN nest box use increased on 1 d, 2 d, and 16 d. The SEN perched more on 1 d, 2 d, and 4 d, and less on 8 d. Initial resource use was affected by wearing a sensor, but by 16 d, all resources were used similarly or more by SEN than NON. No difference in BW was observed on 17 d, suggesting that long-term resource use was not affected. No differences were observed among the number of agonistic observations -5 d, 8 d, and 16 d. With the exception of SEN hens acting as aggressors toward NON hens, agonistic interaction types occurred close to expected proportions. These factors indicate that hens habituate to wearing sensors within 2 wk.
A proof of concept applying wildlife ecology techniques to animal welfare science in intensive agricultural environments was conducted using non-cage laying hens. Studies of wildlife ecology regularly use Geographic Information Systems (GIS) to assess wild animal movement and behavior within environments with relatively unlimited space and finite resources. However, rather than depicting landscapes, a GIS could be developed in animal production environments to provide insight into animal behavior as an indicator of animal welfare. We developed a GIS-based approach for studying agricultural animal behavior in an environment with finite space and unlimited resources. Concurrent data from wireless body-worn location tracking sensor and video-recording systems, which depicted spatially-explicit behavior of hens (135 hens/room) in two identical indoor enclosures, were collected. The spatial configuration of specific hen behaviors, variation in home range patterns, and variation in home range overlap show that individual hens respond to the same environment differently. Such information could catalyze management practice adjustments (e.g., modifying feeder design and/or location). Genetically-similar hens exhibited diverse behavioral and spatial patterns via a proof of concept approach enabling detailed examinations of individual non-cage laying hen behavior and welfare.
Increased mobility of hens in noncaged housing presents possibilities for bone breakage due to crash landings from jumps or flights between perches or housing infrastructure. Because bone breakage is a welfare and economic concern, understanding how movement from different heights affects hen landing impact is important. By tracking 3-dimensional bird movement, an automated sensor technology could facilitate understanding regarding the interaction between noncage laying hens and their housing. A method for detecting jumps and flight trajectories could help explain how jumps from different heights affect hen landing impact. In this study, a wearable sensor-based jump detection mechanism for egg-laying hens was designed and implemented. Hens were fitted with a lightweight (10 g) wireless body-mounted sensor to remotely sample accelerometer data. Postprocessed data could detect occurrence of jumps from a perch to the ground, time of jump initiation, time of landing, and force of landing. Additionally, the developed technology could estimate the approximate height of the jump. Hens jumping from heights of 41 and 61 cm were found to land with an average force of 81.0 ± 2.7 N and 106.9 ± 2.6 N, respectively, assuming zero initial velocity (P < 0.001). This paper establishes the technological feasibility of using body-mounted sensor technology for jump detection by hens in different noncage housing configurations.
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