In a collaboration among the Wageningen University & Research (WUR) Animal Breeding & Genomics unit, Breed4Food and the COST Action GroupHouseNet, a review paper was written on how sensor technologies can aid in selecting against feather pecking (FP) in laying hens, WUR said in an announcement.
Under commercial conditions, livestock and poultry are often kept in large groups, and identifying and monitoring individuals in these groups can be a challenge, especially for monitoring damaging behaviors such as FP in laying hens, WUR said.
FP in laying hens often leads to welfare and economic problems in commercial poultry production. FP is a socially affected trait, i.e., it depends both on the hen’s ability to avoid being pecked (direct genetic effect or victim effect) and on the pecking behavior of her group mates (indirect genetic effect or actor effect), the announcement explained.
So far, behavioral observations have been used to collect information on activity, fearfulness and FP behavior. However, this is time consuming and difficult to apply in commercial situations, WUR said. With the use of sensor technologies, such as ultra-wideband (UWB) tracking, computer vision (CV), accelerometers or radio-frequency identification (RFID), there is potential to track and monitor individuals in large groups and to identify FP and its victims.
Furthermore, WUR said developments in the field of animal breeding can be used to link information obtained from sensor technologies to an individual’s genotype, which could help researchers identify regions or gene expression patterns that offer further insights into FP behavior and provide tools to reduce the incidence of FP behavior.
In the collaboration, researchers studied how sensor technologies can aid in studying FP in laying hens. The goals of this study were to provide an overview of sensor technologies that can be used to identify individual birds and phenotype FP behavior, describe the use of “-omics” approaches to understand FP and discuss indicator traits from both -omics and sensor technologies as well as discuss applications to animal breeding, WUR said.
The review paper with the results from this study was published recently.
According to WUR, a variety of sensor technologies could be used to identify and monitor individual birds kept in a group. So far, most of the studies focus on using body-worn sensor technologies in small groups or using body-worn sensors to monitor pop holes, range and nest usage.
Previous studies in the the WUR Phenolab showed that the UWB system was able to detect the location of a bird with 85% accuracy compared to a human observer. Furthermore, the system was able to detect differences in activity between hens selected as high-FP birds and low-FP birds. The UWB system could also be used to examine the proximity of hens in relation to each other.
CV has been used to recognize and follow individual animals, but application in poultry is limited. The collaboration researchers said it is difficult to identify individual birds due to: (1) problems in initial object recognition, i.e., separating birds from a uniform background (litter), (2) the birds piling on top of each other and (3) the birds flocking together.
However, they said a combination of different sensor technologies might offer solutions. For instance, the combination of RFID/UWB and accelerometers enables investigators to register the location of a bird and the directional movement and speed, which could indicate FP behavior, whereas a combination of RFID/UWB and CV enables investigators to monitor distribution patterns of birds and register proximity.
Current developments in -omics and sensor technologies offer possible solutions to reduce FP, WUR said, noting that the collaboration partners argued that a combined sensor and -omics approach shows great promise in contributing to breeding programs to select against complex behavioral traits such as FP, particularly when different sensor types, such as CV and RFID/UWB, are combined.