Assessing Activity and Location of Individual Laying Hens in Large Groups Using Modern Technology

Low levels of chicken body louse (Menacanthus stramineus) infestations affect chicken welfare in a cage-free housing system

BACKGROUND

The chicken body louse is an obligate ectoparasite of domestic chickens. Chicken body lice feed on feathers, and infestation with this louse is linked to decreases in egg production, hen weight, and feed conversion efficiency. However, it is unknown how chicken body lice impact egg-laying chickens in cage-free environments. Welfare and behavior metrics were collected from flocks of egg-laying chickens either infested with chicken body lice or left uninfested.

METHODS

In two trials, two flocks of cage-free commercial egg-laying chickens were infested with chicken body lice or maintained as uninfested controls. At three timepoints, behavior and welfare of all chickens was measured. On-animal sensors were used to quantify pecking, preening, and dustbathing behavior. Other animal-based welfare metrics included recording comb wounds and skin lesions.

RESULTS

Birds infested with chicken body lice exhibited significantly more preening behaviors than uninfested birds, even at low louse levels. Moderate or severe skin lesions were detected on birds that were moderately infested with chicken body lice while skin lesions were never detected on uninfested birds.

CONCLUSIONS

The welfare of chickens was impacted by the chicken body louse, a chewing louse that primarily feather feeds. Evidence of skin lesions on infested birds suggests that lice may cause more damage to birds than previously thought, and further evaluation of louse economic damage is necessary.

Influence of keel impacts and laying hen behavior on keel bone damage

Keel bone damage, which presents as fractures and/or deviations of the keel, has been detected in laying hens housed in all types of systems. Factors leading to keel bone damage in hens housed with limited vertical space, such as those housed in furnished systems, are not well understood, and are the topic of this study. Ten focal hens from each of 12 furnished cages (4 rooms of 3 cages) were fitted with keel mounted tri-axial accelerometers. Their behavior was video recorded continuously over two 3-wk trials: the first when the hens were between 52 and 60 wk of age, and the second approximately 20 wk later. The integrity of each hen's keel was evaluated at the start and end of each 3-wk trial using digital computed tomography. We identified predominant behaviors associated with acceleration events sustained at the keel (collisions, aggressive interactions and grooming) by pairing accelerometer outputs with video data. For each recorded acceleration event we calculated the acceleration magnitudes as the maximum summed acceleration recorded during the event, and by calculating the area under the acceleration curve. A principle components analysis, which was used as a data reduction technique, resulted in the identification of 4 components that were used in a subsequent regression analysis. A key finding is that the number of collisions a hen has with structures in her environment, and the number of aggressive interactions that a hen is involved, each affect the likelihood that she will develop 1 or more fractures within a 3-wk time span. This relationship between hen behavior and keel fracture formation was independent of the magnitude of acceleration involved in the event. Observed behavior did not have an impact on the formation of keel bone deviations, further supporting reports that the mechanisms underlying the 2 types of keel bone damage are different.

Automating poultry farm management with artificial intelligence: Real-time detection and tracking of broiler chickens for enhanced and efficient health monitoring

The broiler industry plays a vital role in meeting the growing global demand for poultry meat. However, maintaining the health and well-being of broiler birds is crucial to ensure both optimal productivity and animal welfare. The increasing mortality rate of broiler chickens developed into an unavoidable issue that required attention. The major goal of this research is to monitor individual chickens for early disease identification, which will then allow for prompt isolation and treatment of sick birds, stopping the spread of pathogens and preserving the health of the flock as a whole. With an accuracy of 96%, the chosen model, YOLOv5s (You Only Look Once), performed the best. Based on their age, the algorithm was able to categorise broiler chickens. The model is converted to ONNX (Open Neural Network Exchange) format after custom training, and the centroid tracker is used for real-time tracking. After that, the output data is kept in a MySQL (My Structured Query Language) database for later use. The OpenCV (Open-Source Computer Vision Library) library is used to deploy this model on a local machine. This model seeks to identify the broiler chicken in the video frame, classify them, and maintain track of them using the tracker. Based on their age, the birds are divided into categories. Since most monitoring is required between 1 and 4 weeks of age, they are divided into four age groups. The potential application of this model is in the detection of temperature, weight, flock behaviour, etc.

Commercial laying hens exhibit long-term consistent individual differences and behavioural syndromes in spatial traits

Past research has supported the importance of animal personalities for the productivity and welfare of farm animals. However, current assessments of personality traits are commonly conducted over short periods using standardized assays and may not reflect all important aspects of behaviours in commercial settings throughout the production period. This study aimed to evaluate consistent behavioural differences between 194 commercial laying hens within an aviary across most of the production period (eight months). We used five spatial behaviours related to various aspects of commercial hens' daily routine, including the sleeping, feeding, nesting, indoor movements and outdoor usage. All behaviours were repeatable over time and across contexts, with consistent differences between individuals explaining between 23% and 66% of the variation. These long-term consistencies revealed the potential applicability of the behaviours as personality traits of commercial hens. Moreover, we identified behavioural syndromes comprising all behaviours except the nesting-related behaviour, indicating two axes of spatial personalities that may be driven by different mechanisms. We discussed the significance of such individual differences in using personality traits to breed more resilient farm animals. Future research should evaluate associations of these behaviours with animal welfare and productivity to inform breeding efforts.

Mapping Welfare: Location Determining Techniques and Their Potential for Managing Cattle Welfare—A Review

Several studies have suggested that precision livestock farming (PLF) is a useful tool for animal welfare management and assessment. Location, posture and movement of an individual are key elements in identifying the animal and recording its behaviour. Currently, multiple technologies are available for automated monitoring of the location of individual animals, ranging from Global Navigation Satellite Systems (GNSS) to ultra-wideband (UWB), RFID, wireless sensor networks (WSN) and even computer vision. These techniques and developments all yield potential to manage and assess animal welfare, but also have their constraints, such as range and accuracy. Combining sensors such as accelerometers with any location determining technique into a sensor fusion system can give more detailed information on the individual cow, achieving an even more reliable and accurate indication of animal welfare. We conclude that location systems are a promising approach to determining animal welfare, especially when applied in conjunction with additional sensors, but additional research focused on the use of technology in animal welfare monitoring is needed.

An IoT-Based Breeding Egg Identification and Coding System for Selection of High-Quality Breeding Geese

Simple Summary

In the process of breeding geese, manually recording data causes the problems of missing and confusing characterization data; furthermore, manual intervention can lead to the stress response of breeding geese and affect the laying efficiency of breeding geese. In this study, we tried to combine the Internet of things and computer image technology to improve the accuracy of data recording, so as to achieve an accurate correspondence between breeding goose individual data and egg-laying data. Therefore, we developed and tested a breeding egg identification and coding system to realize the selection of high-quality breeding geese. The test results showed that the system realized a correspondence of 97.8% between breeding goose individual data and egg-laying data. The system realized the information recording of breeding geese under nonmanual intervention, realized the correspondence between individual data and egg-laying data, and improved the health and welfare of breeding geese.

Abstract

The selection of breeding geese requires the recording of egg production information to correspond to the identity of the breeding geese. However, due to the special physiological characteristics of breeding geese, manual recording in practice can affect the egg-laying performance of breeding geese and can also lead to problems of missing and confusing individual breeding goose data with the number of eggs laid by the geese. For contactless recording of breeding goose identity and egg production information for high-quality breeding, this paper proposes an Internet of things (IoT)-based breeding egg identification and coding method for the selection of high-quality breeding geese. At the sensing level, we deployed a radiofrequency identification (RFID)-based sensor. Each breeding goose wore a foot ring RFID tag on its leg, and the individual information was read by foot ring RFID readers placed at the bottom of the devices. Individual information was uploaded to the cloud server for database management through structured query language (MySQL). The target detection modules were mounted on top of the devices, and the breeding geese and eggs were detected in the delivery rooms by an improved single-shot multi-box detector (SSD) target detection algorithm. The egg body limit transmission device and contactless coding device were activated only in the case of breeding eggs, and the breeding goose information was printed on the egg bodies in the form of quick response codes (QR codes), which enabled the breeding egg information to correspond with the breeding goose information. An evaluative experiment was performed using a system for the selection of high-quality breeding geese, with web cameras and a cloud monitoring platform. The breeding geese were allowed 14 days to become accustomed to the experimental environment before monitoring began. The evaluative experiment results showed that the pass rate of egg body coding reached 98.25%, the improved SSD algorithm was 8.65% more accurate and 62.6 ms faster than traditional SSD, and the accuracy rate corresponding to the individual information of the breeding geese and the surface information of the goose eggs was 97.8%. The experimental results met the requirements of accurate marking of individual information of breeding geese, which can provide technical support for the selection of high-quality breeding geese.

The Relationships between Damaging Behaviours and Health in Laying Hens

Simple Summary

The design of housing systems and genetic selection of laying hens have in the past focused mainly on productivity, excluding issues around the animals’ behavioural needs and welfare. Because of inadequate housing conditions and especially a barren environment, behavioural disorders such as feather and body pecking, as well as cannibalism, occur in the modern layer industry. Since conventional cages for egg production were banned in the European Union in January 2012, alternative systems such as floor, aviary, free-range, and organic systems have become increasingly common and now concern over 50% of hens housed in Europe. Despite the many advantages that come with non-cage systems, the shift to a housing system where laying hens are kept in larger groups and more complex environments has given rise to new challenges related to management, health, and welfare. We have carried out a review showing the close relationships between damaging behaviours and health in modern husbandry systems for laying hens.

Abstract

Since the ban in January 2012 of conventional cages for egg production in the European Union (Council Directive 1999/74/EC), alternative systems such as floor, aviary, free-range, and organic systems have become increasingly common, reaching 50% of housing for hens in 2019. Despite the many advantages associated with non-cage systems, the shift to a housing system where laying hens are kept in larger groups and more complex environments has given rise to new challenges related to management, health, and welfare. This review examines the close relationships between damaging behaviours and health in modern husbandry systems for laying hens. These new housing conditions increase social interactions between animals. In cases of suboptimal rearing and/or housing and management conditions, damaging behaviour or infectious diseases are likely to spread to the whole flock. Additionally, health issues, and therefore stimulation of the immune system, may lead to the development of damaging behaviours, which in turn may result in impaired body conditions, leading to health and welfare issues. This raises the need to monitor both behaviour and health of laying hens in order to intervene as quickly as possible to preserve both the welfare and health of the animals.

In pursuit of a better broiler: a comparison of the inactivity, behavior, and enrichment use of fast- and slower growing broiler chickens

Selection for rapid growth has produced heavier, more efficient broiler chickens, but has also introduced health and welfare issues, which may cause or be caused by inactivity. Rapid growth may also limit the performance of motivated behaviors, whereas the provision of enrichment may increase these behaviors and general activity. This study aimed to evaluate the inactivity, behavior patterns, and enrichment use of 2 fast- (CONV) and 12 slower growing broiler strains (categorized as fastest [FAST], moderate [MOD], and slowest slow [SLOW]), based on their growth rates; 4 strains/category]. To evaluate inactivity, one male and one female from 153 pens were outfitted with omni-directional accelerometers from d 21 until processing (14-24 birds/strain from 8 to 12 pens/strain). Additionally, to supplement inactivity data, 5-min continuous behavioral observations of four focal birds per pen (2 males, 2 females) were conducted on days 26, 42, and 56 (72-148 observations of 8-12 pens/strain) to quantify the duration and frequency of various behaviors; at the same time, 5 to 11 instantaneous scan samples were also performed for pen-based enrichment use. Inactivity peaked at 78 to 80% of the day for all strains; however, those with slower growth rates reached these levels at older ages. Compared to slower growing strains at the same age, faster growing strains were more inactive, spent more time sitting and feeding, spent less time standing and walking, and used enrichments less; these differences mostly occurred at younger ages. Generally, at the same age, strains with similar growth rates (within the same category) behaved similarly, with only a few exceptions. Results suggest that not all strains identified as "slow-growing" broilers behave differently from fast-growing broilers, nor do they all behave similarly to each other. As such, results suggest that improved broiler welfare, particularly with respect to reduced inactivity, the performance of a wider range of normal, motivated behaviors, and/or increased enrichment use, is related to the broiler strain's specific growth rate.

Associations between weather conditions and individual range use by commercial and heritage chickens

Ranging area use by domestic poultry is not always optimal and differences in it exist on the levels of breed, flock and individual bird. Outdoor shelters are usually not protective for all weather parameters and may not fulfil a protective role to all birds within the flock all time, if individuals are sensitive to different weather conditions. The aim of this study was to investigate associations between different weather parameters and the use of the range by individual Green-legged Partridge and Sasso C44 chickens. In August 2018, 60 birds per genetic strain were housed in groups of 10 from wks 5 to 10, under conditions exceeding minimal EU requirements of organic meat chicken production. Birds in each pen had access to an outdoor range that was video-recorded during the experiment to obtain frequencies of individual birds' use of the ranges. Weather data were collected each minute throughout the whole experiment by an automatic weather station. In each pen, birds tagged individually with a laminated color tag, had access to an outdoor range that was video-recorded during the experiment. Frequencies of individual birds' use of the ranges were manually obtained from the recordings. Univariate and multivariate linear regression models were used to investigate the associations between the variables. The results showed significant associations between weather parameters and range use for one third of Green-legged Partridge and Sasso chickens (n = 21 in both breeds). Between breeds, range use associations with different weather parameters were identified. Negative associations with relative humidity occurred most frequently in Green-legged Partridges (n = 8; R2 from 0.1 to 0.17), while positive associations with atmospheric pressure (n = 7; R2 from 0.09 to 0.17) were most common in Sasso chickens. Further investigations into the reasons behind individual sensitivity of meat-purpose chickens to specific weather conditions would increase the understanding of their preferences and needs, which over time will improve animal welfare.

Analysis of Cluster and Unrest Behaviors of Laying Hens Housed under Different Thermal Conditions and Light Wave Length

Simple Summary

The effects of lighting wavelength on the behavior of laying hens are not yet completely known. This study observed three groups of birds housed under different lighting colors (blue, green, and red) for 90 days. Important differences were found regarding the unrest and cluster behaviors of the birds. It was found that, at shorter wavelengths (blue light), birds became more agitated, while, at longer wavelengths (red light), birds became more clustered. When subjected to cold or heat stress, birds expressed unrest and cluster behaviors in different ways, indicating that further studies should be conducted to better clarify the effects of lighting on the behavior and well-being of laying hens.

Abstract

Laying hens are affected by the intensity, wavelength, and duration of light, and the behavioral patterns of these animals are important indicators of stress. The objective of the present study was to evaluate cluster and unrest behaviors of lying hens submitted to three environments with different treatments of monochromatic lighting (blue, green, and red). For 29 weeks, 60 laying hens from the Lohmann variety were divided into three groups and monitored by surveillance cameras installed on each shed ceiling and directed to the floor. Each group was housed in a small-scale shed and maintained under a monochromatic lighting treatment. The recordings were made at two times of the day, 15 min in the morning and 15 min in the afternoon, and the videos were processed, segmented, and analyzed computationally. From the analysis of the images, the cluster and unrest indexes were calculated. The results showed the influence of lighting on these behaviors, displaying that the birds were more agitated in the treatments with shorter wavelengths. Cluster behavior was higher in birds housed under red light. There was an interaction between the lighting treatments and the thermal environment, indicating that more studies should be carried out in this area to better understand these behavioral changes.

Heritability of perching behavior and its genetic relationship with incidence of floor eggs in Rhode Island Red chickens

Background

As cage-free production systems become increasingly popular, behavioral traits such as nesting behavior and temperament have become more important. The objective of this study was to estimate heritabilities for frequency of perching and proportion of floor eggs and their genetic correlation in two Rhode Island Red lines.

Results

The percent of hens observed perching tended to increase and the proportion of eggs laid on the floor tended to decrease as the test progressed. This suggests the ability of hens to learn to use nests and perches. Under the bivariate repeatability model, estimates of heritability in the two lines were 0.22 ± 0.04 and 0.07 ± 0.05 for the percent of hens perching, and 0.52 ± 0.05 and 0.45 ± 0.05 for the percent of floor eggs. Estimates of the genetic correlation between perching and floor eggs were − 0.26 ± 0.14 and − 0.19 ± 0.27 for the two lines, suggesting that, genetically, there was some tendency for hens that better use perches to also use nests; but the phenotypic correlation was close to zero. Random regression models indicated the presence of a genetic component for learning ability.

Conclusions

In conclusion, perching and tendency to lay floor eggs were shown to be a learned behavior, which stresses the importance of proper management and training of pullets and young hens. A significant genetic component was found, confirming the possibility to improve nesting behavior for cage-free systems through genetic selection.

Symposium review: Precision technologies for dairy calves and management applications

There is an increasing interest in using precision dairy technologies (PDT) to monitor real-time animal behavior and physiology in livestock systems around the world. Although PDT in adult cattle is extensively reviewed, PDT use for the management of preweaned dairy calves has not been reviewed. We systematically reviewed research on the use and application of precision technologies in calves. Accelerometers have the potential to be used to monitor lying behavior, step activity, and rumination, which are useful to detect changes in behavior that may be indicative of disease, responses to painful procedures, or positive welfare behaviors such as play. Automated calf feeding systems can control delivery of nutritional plans to individualize feeding and weaning of calves; changes in feeding behaviors (such as milk intake, drinking speed, and unrewarded visits) may also be used to identify early onset of disease. The PDT devices also measure physiological and physical attributes in dairy calves. For instance, temperature monitoring devices such as infrared thermography, ruminal boluses, and implanted microchips have been assessed in calves, but no herd management-based commercial system is available. Many other PDT are in development with potential to be used in dairy calf management, such as image and acoustic-based monitoring, real-time location, and use of enrichment items for monitoring positive emotional states. We conclude that PDT have great potential for application in dairy calf management, enabling precise behavioral and physiological monitoring, targeted feeding programs, and identification of calves with poor health or behavioral impairments. We strongly encourage further development and validation of commercially available technologies for on-farm application of the monitoring of dairy calf welfare, performance, and health.

Parasitic mites alter chicken behaviour and negatively impact animal welfare

The northern fowl mite, Ornithonyssus sylviarum, is one of the most common and damaging ectoparasites of poultry. As an obligate blood feeding mite, the northern fowl mite can cause anaemia, slower growth, and decreased egg production of parasitized birds. However, the impact of mites or other ectoparasites on hen behaviour or welfare is not well studied. Here, we use activity sensors (three-axis accelerometers) affixed to individual birds to continuously record hen movement before, during, and after infestation with mites. Movements recorded by sensors were identified to specific bird behaviours through a previously trained algorithm, with frequency of these behaviours recorded for individual birds. Hen welfare was also determined before, during, and after mite infestation of hens using animal-based welfare metrics. Northern fowl mites significantly increased hen preening behaviour and resulted in increased skin lesions of infested birds.

Characterising Free-Range Layer Flocks Using Unsupervised Cluster Analysis

This study aimed to identify sub-populations of free-range laying hens and describe the pattern of their resource usage, which can affect hen performance and welfare. In three commercial flocks, 3125 Lohmann Brown hens were equipped with radio-frequency identification (RFID) transponder leg bands and placed with their flock companions, resulting in a total of 40,000 hens/flock. Hens were monitored for their use of the aviary system, including feeder lines, nest boxes, and the outdoor range. K-means and agglomerative cluster analysis, optimized with the Calinski-Harabasz Criterion, was performed and identified three clusters. Individual variation in time duration was observed in all the clusters with the highest individual differences observed on the upper feeder (140 ± 1.02%) and the range (176 ± 1.03%). Hens of cluster 1 spent the least amount time on the range and the most time on the feed chain located at the upper aviary tier (p < 0.05). We conclude that an uneven load on the resources, as well as consistent and inconsistent movement patterns, occur in the hen house. Further analysis of the data sets using classification models based on support vector machines, artificial neural networks, and decision trees are warranted to investigate the contribution of these and other parameters on hen performance.

Keel bone fractures induce a depressive-like state in laying hens

In commercial flocks of laying hens, keel bone fractures (KBFs) are prevalent and associated with behavioural indicators of pain. However, whether their impact is severe enough to induce a depressive-like state of chronic stress is unknown. As chronic stress downregulates adult hippocampal neurogenesis (AHN) in mammals and birds, we employ this measure as a neural biomarker of subjective welfare state. Radiographs obtained longitudinally from Lohmann Brown laying hens housed in a commercial multi-tier aviary were used to score the severity of naturally-occurring KBFs between the ages of 21-62 weeks. Individual birds' transitions between aviary zones were also recorded. Focal hens with severe KBFs at 3-4 weeks prior to sampling (n = 15) had lower densities of immature doublecortin-positive (DCX+) multipolar and bipolar neurons in the hippocampal formation than focal hens with minimal fractures (n = 9). KBF severity scores at this time also negatively predicted DCX+ cell numbers on an individual level, while hens that acquired fractures earlier in their lives had fewer DCX+ neurons in the caudal hippocampal formation. Activity levels 3-4 weeks prior to sampling were not associated with AHN. KBFs thus lead to a negative affective state lasting at least 3-4 weeks, and management steps to reduce their occurrence are likely to have significant welfare benefits.

Can breeders solve mortality due to feather pecking in laying hens?

Mortality due to feather pecking (FP) has large economic and welfare consequences in the commercial poultry industry, and reduces survival of birds. With FP, the survival time of a hen depends both on her own genetic ability to avoid becoming the victim of FP (direct genetic effect; DGE), and on the genetic tendency of her group mates to perform FP (indirect genetic effect; IGE). Thus, to improve survival time of laying hens, it is important to use a breeding strategy that captures both the DGE and the IGE of selection candidates. Here, we investigate the prospects for solving mortality due to FP in laying hens by genetic selection. First, we review genetic parameters for survival time. Second, we use deterministic simulation to predict response to selection for 2 multi-trait crossbred breeding programs, a traditional recurrent testing scheme (RT) and a genomic selection scheme (GS). Finally, we investigate the prospects for sustained improvement of survival time when mortality becomes low. Results show that survival time has considerable heritable variation; most estimates of the total additive genetic standard deviation are larger than 1 mo. As expected, predicted single generation response to selection in survival time with GS is substantial larger than with RT. Particularly when the correlation between survival time and other breeding goal traits is zero, the GS scheme yields substantial improvement in survival time. For example, when mortality is 35%, the genetic correlation between survival time and other traits is 0, allowing for a 10% reduction of response in other traits, and when selection takes place in both the sire line and dam line, survival time can be improved with ∼23 D in one generation, using GS. Results, however, also show a strong decrease in heritability when mortality decreases, indicating that continued improvement becomes increasingly difficult. In summary, our results show that breeders can considerably reduce mortality due to FP with limited reduction of improvement in other breeding goal traits.

Review of Sensor Technologies in Animal Breeding: Phenotyping Behaviors of Laying Hens to Select Against Feather Pecking

Simple Summary

The European Cooperation in Science and Technology (COST) Action GroupHouseNet aims to provide synergy among scientists to prevent damaging behavior in group-housed pigs and laying hens. One goal of this network is to determine how genetic and genomic tools can be used to breed animals that are less likely to perform damaging behavior on their pen-mates. In this review, the focus is on feather-pecking behavior in laying hens. Reducing feather pecking in large groups of hens is a challenge, because it is difficult to identify and monitor individual birds. However, current developments in sensor technologies and animal breeding have the potential to identify individual animals, monitor individual behavior, and link this information back to the underlying genotype. We describe a combination of sensor technologies and “-omics” approaches that could be used to select against feather-pecking behavior in laying hens.

Abstract

Damaging behaviors, like feather pecking (FP), have large economic and welfare consequences in the commercial laying hen industry. Selective breeding can be used to obtain animals that are less likely to perform damaging behavior on their pen-mates. However, with the growing tendency to keep birds in large groups, identifying specific birds that are performing or receiving FP is difficult. With current developments in sensor technologies, it may now be possible to identify laying hens in large groups that show less FP behavior and select them for breeding. We propose using a combination of sensor technology and genomic methods to identify feather peckers and victims in groups. In this review, we will describe the use of “-omics” approaches to understand FP and give an overview of sensor technologies that can be used for animal monitoring, such as ultra-wideband, radio frequency identification, and computer vision. We will then discuss the identification of indicator traits from both sensor technologies and genomics approaches that can be used to select animals for breeding against damaging behavior.

A review of environmental enrichment for laying hens during rearing in relation to their behavioral and physiological development

Globally, laying hen production systems are a focus of concern for animal welfare. Recently, the impacts of rearing environments have attracted attention, particularly with the trend toward more complex production systems including aviaries, furnished cages, barn, and free-range. Enriching the rearing environments with physical, sensory, and stimulatory additions can optimize the bird's development but commercial-scale research is limited. In this review, "enrichment" is defined as anything additional added to the bird's environment including structurally complex rearing systems. The impacts of enrichments on visual development, neurobehavioral development, auditory stimulation, skeletal development, immune function, behavioral development of fear and pecking, and specifically pullets destined for free-range systems are summarized and areas for future research identified. Visual enrichment and auditory stimulation may enhance neural development but specific mechanisms of impact and suitable commercial enrichments still need elucidating. Enrichments that target left/right brain hemispheres/behavioral traits may prepare birds for specific types of adult housing environments (caged, indoor, outdoor). Similarly, structural enrichments are needed to optimize skeletal development depending on the adult layer system, but specific physiological processes resulting from different types of exercise are poorly understood. Stimulating appropriate pecking behavior from hatch is critical but producers will need to adapt to different flock preferences to provide enrichments that are utilized by each rearing group. Enrichments have potential to enhance immune function through the application of mild stressors that promote adaptability, and this same principle applies to free-range pullets destined for variable outdoor environments. Complex rearing systems may have multiple benefits, including reducing fear, that improve the transition to the layer facility. Overall, there is a need to commercially validate positive impacts of cost-effective enrichments on bird behavior and physiology.

Finding hens in a haystack: Consistency of movement patterns within and across individual laying hens maintained in large groups

We sought to objectively quantify and compare the recorded movement and location patterns of laying hens within a commercial system. Using a custom tracking system, we monitored the location within five zones of a commercial aviary for 13 hens within a flock of 225 animals for a contiguous period of 11 days. Most hens manifested a hen-specific pattern that was (visually) highly consistent across days, though, within that consistency, manifested stark differences between hens. Three different methods were used to classify individual daily datasets into groups based on their similarity: (i) Linear Discriminant Analysis based on six summary variables (transitions into each zone) and total transitions; (ii) Hierarchical Clustering, a naïve clustering analysis technique, applied to summary variables and iii) Hierarchical Clustering applied to dissimilarity matrices produced by Dynamic Time Warping. The three methods correctly classified more than 85% of the hen days and provided a unique means to assess behaviour of a system indicating a considerable degree of complexity and structure. We believe the current effort is the first to document these location and movement patterns within a large, complex commercial system with a large potential to influence the assessment of animal welfare, health, and productivity.

An RFID-Based Smart Nest Box: An Experimental Study of Laying Performance and Behavior of Individual Hens

This study designed a radio-frequency identification (RFID)-based Internet of Things (IoT) platform to create the core of a smart nest box. At the sensing level, we have deployed RFID-based sensors and egg detection sensors. A low-frequency RFID reader is installed in the bottom of the nest box and a foot ring RFID tag is worn on the leg of individual hens. The RFID-based sensors detect when a hen enters or exits the nest box. The egg-detection sensors are implemented with a resistance strain gauge pressure sensor, which weights the egg in the egg-collection tube. Thus, the smart nest box makes it possible to analyze the laying performance and behavior of individual hens. An evaluative experiment was performed using an enriched cage, a smart nest box, web camera, and monitoring console. The hens were allowed 14 days to become accustomed to the experimental environment before monitoring began. The proposed IoT platform makes it possible to analyze the egg yield of individual hens in real time, thereby enabling the replacement of hens with egg yield below a pre-defined level in order to meet the overall target egg yield rate. The results of this experiment demonstrate the efficacy of the proposed RFID-based smart nest box in monitoring the egg yield and laying behavior of individual hens.

Behavioural and physiological responses of laying hens to automated monitoring equipment

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Monitoring devices affected adult hen behaviour on the day of fitting.

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Hens prioritized (re)moving newly fitted devices over exploration.

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Devices did not increase aggressive behaviour towards equipped hens.

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From two days after fitting on, only a very minor effect on behaviour was observed.

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Peripheral eye temperature seemed related to preening behaviour rather than stress.

Automated monitoring of behaviour can offer a wealth of information in circumstances where observing behaviour is difficult or time consuming. However, this often requires attaching monitoring devices to the animal which can alter behaviour, potentially invalidating any data collected. Birds often show increased preening and energy expenditure when wearing devices and, especially in laying hens, there is a risk that individuals wearing devices will attract aggression from conspecifics. We studied the behavioural and physiological response of 20 laying hens to backpacks containing monitoring devices fastened with elastic loops around the wing base. We hypothesised that backpacks would lead to a stress-induced decrease in peripheral temperature, increased preening, more aggression from conspecifics, and reduced bodyweights. This was evaluated by thermography of the eye and comb (when isolated after fitting backpacks), direct observations of behaviour (when isolated, when placed back into the group, and on later days), and weighing (before and after each 7-day experimental period). Each hen wore a backpack during one of the two experimental periods only and was used as her own control. Contrary to our hypothesis, eye temperature was higher when hens wore a backpack (No backpack: 30.2 °C (IQR: 29.0–30.6) vs. Backpack: 30.9 °C (IQR: 30.0–32.0), P < 0.001). Eye temperature of hens wearing a backpack was strongly correlated to the time spent preening (r_s = 0.8, P < 0.001), suggesting that the higher temperatures may have been due to preening itself, or to a low head position or decreased heat dissipation when preening under the wings. Aggressive behaviour was very rare and no effect of the backpacks was found. In line with our hypothesis, backpacks increased preening on the day of fitting, both when isolated (No backpack: 0% (IQR: 0–1) vs. Backpack: 22% (IQR: 1–43), P < 0.01) and when back in the group (No backpack: 0% (IQR: 0–27) vs. Backpack: 43% (IQR: 5–77), P < 0.001). However, no effect on preening was observed 2–7 days afterwards. Other behavioural changes suggested that on the day of fitting hens prioritized attempts to (re)move the backpack and were less attentive to their surroundings. However, only equipment pecking (i.e., pecking the backpack or leg rings) was still affected 2–7 days after fitting (No backpack: 0 pecks/hen/minute (IQR: 0–0), vs. Backpack: 0 (IQR: 0–0.07), P < 0.05). We found no effect of our backpacks on bodyweight. In conclusion, our backpacks seem suitable to attach monitoring equipment to hens with only a very minor effect on their behaviour after a short acclimation period (≤2 days).

Development of a Machine Vision Method for the Monitoring of Laying Hens and Detection of Multiple Nest Occupations

Free range systems can improve the welfare of laying hens. However, the access to environmental resources can be partially limited by social interactions, feeding of hens, and productivity, can be not stable and damaging behaviors, or negative events, can be observed more frequently than in conventional housing systems. In order to reach a real improvement of the hens' welfare the study of their laying performances and behaviors is necessary. With this purpose, many systems have been developed. However, most of them do not detect a multiple occupation of the nest negatively affecting the accuracy of data collected. To overcome this issue, a new "nest-usage-sensor" was developed and tested. It was based on the evaluation of thermografic images, as acquired by a thermo-camera, and the performing of patter recognitions on images acquired from the nest interior. The sensor was setup with a "Multiple Nest Occupation Threshold" of 796 colored pixels and a template of triangular shape and sizes of 43 × 33 pixels (high per base). It was tested through an experimental nesting system where 10 hens were reared for a month. Results showed that the evaluation of thermografic images could increase the detection performance of a multiple occupation of the nest and to apply an image pattern recognition technique could allow for counting the number of hens in the nest in case of a multiple occupation. As a consequence, the accuracy of data collected in studies on laying performances and behaviors of hens, reared in a free-range housing system, could result to be improved.

Ranging Behaviour of Commercial Free-Range Broiler Chickens 1: Factors Related to Flock Variability

Simple Summary

Free-range chicken meat consumption has increased. However, little is known about how meat chickens use the outdoor range. Understanding ranging behaviour could help improve management and shed and range design to ensure optimal ranging opportunities. We tracked 1200 individual broiler chickens in four mixed sex flocks on one commercial farm across two seasons. More chickens accessed the range in summer than winter. Chickens that accessed the range in winter did so less frequently and for a shorter period of time daily than chickens ranging in summer. The number of chickens ranging and the frequency and duration of range visits increased over the first two weeks of range access and stabilised thereafter. More chickens entered and exited the range through particular doors in the shed. More chickens ranged in the morning and evening compared to the middle of the day. Ranging behaviour decreased with increased rainfall and shed dew point. This study provides knowledge regarding ranging behaviour in commercial conditions that may guide improvements on farm to provide chickens with optimal ranging opportunities.

Abstract

Little is known about the ranging behaviour of chickens. Understanding ranging behaviour is required to improve management and shed and range design to ensure optimal ranging opportunities. Using Radio Frequency Identification technology, we tracked 300 individual broiler chickens in each of four mixed sex ROSS 308 flocks on one commercial farm across two seasons. Ranging behaviour was tracked from the first day of range access (21 days of age) until 35 days of age in winter and 44 days of age in summer. Range use was higher than previously reported from scan sampling studies. More chickens accessed the range in summer (81%) than winter (32%; p < 0.05). On average, daily frequency and duration of range use was greater in summer flocks (4.4 ± 0.1 visits for a total of 26.3 ± 0.8 min/day) than winter flocks (3.2 ± 0.2 visits for a total of 7.9 ± 1.0 min/day). Seasonal differences were only marginally explained by weather conditions and may reflect the reduction in range exposure between seasons (number of days, hours per day, and time of day). Specific times of the day (p < 0.01) and pop-holes were favoured (p < 0.05). We provide evidence of relationships between ranging and external factors that may explain ranging preferences.

Individual Ranging Behaviour Patterns in Commercial Free-Range Layers as Observed through RFID Tracking

Simple Summary

Understanding of how free-range laying hens on commercial farms utilize the outdoor space provided is limited. In order to optimise use of the range, it is important to understand whether hens vary in their ranging behaviour, both between and within individual hens. In our study, we used individual tracking technology to assess how hens in two commercial free-range flocks used the range and whether they varied in their use of the range. We assessed use of three areas at increasing distance from the shed; the veranda [0–2.4 m], close range [2.4–11.4 m], and far range [>11.4 m]. Most hens accessed the range every day (68.6% in Flock A, and 82.2% in Flock B), and most hens that ranged accessed all three areas (73.7% in Flock A, and 84.5% in Flock B). Hens spent half of their time outside in the veranda adjacent to the shed. We found that some hens within the flocks would range consistently (similar duration and frequency) daily, whereas others would range inconsistently. Hens that were more consistent in their ranging behaviour spent more time on the range overall than those that were inconsistent. These different patterns of range use should be taken into account to assess the implications of ranging for laying hens.

Abstract

In this exploratory study, we tracked free-range laying hens on two commercial flocks with Radio Frequency Identification (RFID) technology with the aim to examine individual hen variation in range use. Three distinct outdoor zones were identified at increasing distances from the shed; the veranda [0–2.4 m], close range [2.4–11.4 m], and far range [>11.4 m]. Hens’ movements between these areas were tracked using radio frequency identification technology. Most of the hens in both flocks (68.6% in Flock A, and 82.2% in Flock B) accessed the range every day during the study. Of the hens that accessed the range, most hens accessed all three zones (73.7% in Flock A, and 84.5% in Flock B). Hens spent half of their time outdoors in the veranda area. Within-individual consistency of range use (daily duration and frequency) varied considerably, and hens which were more consistent in their daily range use spent more time on the range overall (p < 0.001). Understanding variation within and between individuals in ranging behaviour may help elucidate the implications of ranging for laying hens.

Technology and Poultry Welfare

Consideration of animal welfare is essential to address the consumers’ demands and for the long term sustainability of commercial poultry. However, assessing welfare in large poultry flocks, to be able to detect potential welfare risks and to control or minimize its impact is difficult. Current developments in technology and mathematical modelling open new possibilities for real-time automatic monitoring of animal welfare and health. New technological innovations potentially adaptable to commercial poultry are appearing, although their practical implementation is still being defined. In this paper, we review the latest technological developments with potential to be applied to poultry welfare, especially for broiler chickens and laying hens. Some of the examples that are presented and discussed include the following: sensors for farm environmental monitoring, movement, or physiological parameters; imaging technologies such as optical flow to detect gait problems and feather pecking; infrared technologies to evaluate birds’ thermoregulatory features and metabolism changes, that may be indicative of welfare, health and management problems. All these technologies have the potential to be implemented at the commercial level to improve birds’ welfare and to optimize flock management, therefore, improving the efficiency of the system in terms of use of resources and, thus, long term sustainability.