With the increasing use of cage-free housing systems for laying hens comes the challenge of monitoring the behaviour of individual hens in large enclosures where they can be not only on the floors but on different levels. The aim of the present study by Gebhardt-Henrich et al., (2023) was to validate a Radio Frequency Identification (RFID) system with the capacity to track a large number of hens for different research and applied purposes where behaviour monitoring is relevant, such as heritability estimates for breeding programs.

In a housing system with 225 birds per pens, 26 antennae were placed at different locations. All birds in 5 pens were equipped with a glass tag in a custom-developed leg band. For validation purposes, the behaviour of three hens who could move between two pens was also monitored on video. Equipping these hens with colour-coded backpacks made them identifiable on video.

Matching the antennae detection of the focal birds with the behaviour observation showed that the antennae were able to detect a hen on the right tier in > 90% of cases, but that match on antenna level was lower.

The limitations of the system are also discussed in this concise methods paper that will be helpful to many researchers interested in tracking laying hens in loose housing systems.

Gebhardt-Henrich, S.G., Kashev, A., Petelle, M.B., Toscano, M.J., 2023. Validation of a Radio frequency identification system for tracking location of laying hens in a quasi-commercial aviary system. bioRxiv 2023.02.16.528820. ver. 3 peer-reviewed and recommended by Peer Community in Animal Science. https://doi.org/10.1101/2023.02.16.528820

In production animals, behavioural activity plays a crucial role across a wide range of scientific disciplines and is often measured for various purposes depending on the field: ethology, animal welfare, reproduction, animal production, and so on. Historically, direct observation was the primary method of collecting such data, a process that was time-consuming and prone to possible observer bias. With the advent of automated systems and sensors, behavioural activity can now be recorded continuously and non-invasively, leading to a growing body of more reliable data  (1). However, the lack of standardisation in how these data are calculated and interpreted has created challenges for cross-study comparisons. To fully harness the potential of studying behavioural activity, scientific studies must harmonise the methods used to calculate this measure. Standardising these methods would make it easier to compare results and identify possible gaps in knowledge.

In the work by van Dixhoorn et al.(2), the authors examine the various metrics most commonly used to study behavioural activity. Through a series of examples, they address the definitions, calculation methods, and biological significance of metrics such as overall activity, fluctuations around mean activity, cyclicity of activity, and synchrony between animals. The authors suggest how these different metrics can be applied in specific contexts and guide readers in using appropriate terminology to ensure future studies are more easily comparable. In addition, by clarifying these concepts, the authors provide researchers with the tools to make informed decisions about which metric best suits their study's objectives.

A key contribution of this work is its emphasis on standardising the metrics and terminology used in behavioural activity studies. Studies using different metrics may arrive at conclusions that appear contradictory, not because of actual differences in animal behaviour, but due to inconsistencies in how behaviour is quantified. By advocating for a common framework, the authors aim to improve the replicability of studies, facilitate meta-analyses, and allow for a more cohesive understanding of animal behaviour across different research groups. This, in turn, could accelerate the identification of key behavioural indicators, ultimately leading to better animal management practices and welfare assessments.

This article provides a timely and valuable contribution to the field of animal science. As technology continues to evolve, so too must our methods for interpreting the vast amounts of data it generates (3). By ensuring that studies are comparable and data is interpreted consistently, the research community can work towards more meaningful discoveries in animal behaviour. I highly recommend this paper to researchers looking to deepen their understanding of activity metrics in animal behaviour studies.

References

1. Rushen J, Chapinal N, de Passilé AM (2012). Automated monitoring of behavioural-based animal welfare indicators. Animal Welfare 21(3):339-50. https://doi.org/10.7120/09627286.21.3.339 

2. van Dixhoorn IDE, Aubé L, van Zyl C, de Mol R, van der Werf J, Lardy R, Mialon MM, van Reenen CG, and Veissier I (2024). From data on gross activity to the characterization of animal behaviour: which metrics for which purposes?. Zenodo, 10420600, ver.5 peer-reviewed and recommended by PCI Animal Science. https://doi.org/10.5281/zenodo.10420600 

3. Riaboff L, Shalloo L, Smeaton AF, Couvreur S, Madouasse A, Keane MT (2022). Predicting livestock behaviour using accelerometers: A systematic review of processing techniques for ruminant behaviour prediction from raw accelerometer data. Computers and Electronics in Agriculture 192:106610. https://doi.org/10.1016/j.compag.2021.106610 
 

To limit the use of antibiotics in the few days after hatching, it is necessary to improve the robustness of chicks during the early post-hatch period. This can be achieved by ensuring immediate access to feeds, optimizing the implantation and maturation of the microbiota and immune system of each chick, and minimizing exposure of stressors such as transportation. The study conducted by Guilloteau and colleagues (2024) compared the performance and health of chicks raised in conventional hatching systems with those raised in on-farm hatching systems. The authors showed that both systems yielded similar hatching percentage of eggs. Chicks from on-farm hatching systems exhibited higher body weights during the post-hatch period compared to those from conventional hatching, whereas health parameters were not affected by the system. An originality of the study was the examination of the benefits of the presence of an adult hen in hatching systems. The effects on chick traits were interpreted in relation to the hen behavior at hatching and a classification according to maternal or agonistic activities towards the chicks. However, the experimental design did not allow to make statistical correlations between hen behavior pattern and chick traits. Importantly, the presence of a hen decreased the hatching percentage, and this was likely associated with hen aggressiveness in the pen. The presence of the hen deteriorated the quality scores of the chicks in the on-farm hatching system, and increased mortality of chicks at hatching, negatively impacting chick weight gain and feed efficiency during the few days after hatching in both conventional and on-farm hatching systems. Thereafter, the effect of the presence of a hen on chick body weight was different according to the sex of the chicks and the type of hatching system. The presence of a hen did not reduce the parasitic load of the chicks nor improved clinical signs. No specific characterization of the fecal microbiota of the chicks was conducted, preventing the testing whether or not the presence of the hen affected the early implantation and maturation of the chick microbiome. Altogether, the data indicate that on-farm hatching systems are at least equivalent (in terms of health traits, feed efficiency) or even favorable (for faster growth in the early period after hatching) for chicks. Training the hens (considered as foster adults) to the presence of eggs and chicks or selecting hens according to specific activity behavioral patterns could be ways to establish better interactions between hens and chicks. Although the number and type of environmental stressors tested in the experiment differ from those in commercial farms, the article opens new perspectives for alternative hatching and farming practices.

Reference

Guilloteau LA, Bertin A, Crochet S, Bagnard C, Hondelatte A, Ravon L, Schouler C, Germain K, Collin A (2024) On-farm hatching and contact with adult hen post hatch induce sex-dependent effects on performance, health and robustness in broiler chickens. bioRxiv, 2023.05.17.541117. ver. 3 peer-reviewed and recommended by Peer Community in Animal Science. https://doi.org/10.1101/2023.05.17.541117.