Lameness assessment with automatic monitoring of activity in commercial broiler flocks

Effect of on-farm hatching and elevated platforms on behavior and performance in fast-growing broiler chickens

Alternative hatching systems compared to conventional hatchery-hatched systems showed positive effects on welfare of broiler chickens. In order to investigate an additional positive effect of elevated platforms, two hatching methods (on-farm [OH] vs. hatchery-hatched [HH]) and two environments from the first day onwards (with elevated platforms [enriched] vs. without elevated platforms [control]) were combined and investigated using a 2 × 2 factorial design. In three consecutive trials, the combination of the four treatments were repeated eight times each. One thousand six hundred fast-growing broiler chickens (Ross strain) were reared in a mixed-sex system. Chick quality was assessed at hatch and performance parameters and behavior parameters were measured during the entire rearing period of 35 d. For the statistical analysis, LME's and GLMM's were used depending on the data. In general, hatching system and housing environment showed no interaction. There were no differences in hatchability between treatment groups (p=0.93). However, OH chickens showed a higher body weight throughout the rearing period (all p<0.001). OH chickens had a lower body temperature than HH chickens (p=0.002) during the rearing period. OH chickens compared to HH chickens tended to show a higher usage of elevated platform at night (p=0.07). The enriched groups showed higher activity (p<0.0001), but no improved walking ability (p=0.82) than the control groups. The differences in performance and behavior were low between hatching systems and may be related to the short period of feed and water deprivation and the lack of long commercial processing and transportation procedures in the HH treatment group in our experiment. Overall, both on-farm hatching and elevated platforms can lead to an improvement of performance and activity parameters and, thus, an improvement of certain aspects of animal welfare but both factors do not seem to interact with each other.

Automatic analysis of high, medium, and low activities of broilers with heat stress operations via image processing and machine learning

Heat stress is a major welfare problem in the poultry industry, altering broilers' activity levels. Advancements in image processing and machine learning provide opportunities to automatically quantify and analyze broiler activity. This study aimed to evaluate the effects of moderate heat exposure on broiler behavioral activity via image processing and machine learning. 132 Cobb 500 broilers were raised in 2 nutritional treatment groups, each with 3 replicates. The control groups were fed a basal diet, while the variation groups were fed a diet with 0.05 % 25-hydroxyvitamin D3. All birds were raised under standard environmental conditions for 27 days before exposure to cyclic heat of 29.56 ± 1.34 °C and humidity of 76.97 % ± 5.98 % from 8:00-18:00 and thermoneutral conditions of 26.67 ± 1.76 °C and 80.23 % ± 3.05 % from 18:00-8:00. Birds were continuously video recorded, and the bird activity index (BAI) was analyzed by subtracting consecutive frames and summing up pixel differences. The treatment effect was analyzed using two-way ANOVA with a P-value < 0.05. K-means clustering was used to determine BAI as high, medium, and low levels. The result showed a significantly higher (P < 0.01) activity index in the variation group in contrast to the control. Absolute values of high and medium BAI were significantly lower with cyclical heating operations than those without heating operations. The BAI was also higher at the onset and end of the heating operations and moderately correlated to flock age (|r| = 0.35-0.45). The high, medium, and low BAI performed differently with different nutritional treatments, temperature ranges, and relative humidity ranges. It is concluded that the BAI is a useful tool for predicting broiler heat stress, but the prediction effectiveness could be influenced by bird age, diets, temperature, humidity, and behavior metrics.

Genetics of gait score in broilers: Genetic parameters of gait score in purebred broiler lines

Leg health assessment is a vital component of poultry breeding goals; it includes a range of skeletal disorders and contact dermatitis traits as well as a general assessment of a bird's walking ability in the form of gait score (GS). If trained scorers are used, GS correlates well with more objective walking assessment methods and allows for high throughput data collection from large numbers of individuals. The paper describes for the first time GS heritabilities for broilers. The Aviagen GS system (AGS) consists of an 8-class scale of 10-45 in increments of 5, whereby 10 is the best score and 45 the worst. It has sufficient variation between categories to enable a clear distinction of GS classes for selection purposes. The results of GS at 4-5 weeks of age show GS heritabilities between 0.14 and 0.24 which is higher than turkey (0.08-0.13) or duck (0.06-0.12) heritabilities. Genetic correlations with body weight and breast percentage were unfavorable but moderate. Correlations among leg health traits (AGS, long bone deformities, crooked toes, hockburn and footpad dermatitis) were generally low (-0.16-0.10) for most traits and lines. While genetic correlations between AGS and production traits were unfavorable, both AGS and other leg health and production traits can be improved simultaneously in a multi-trait selection strategy combining production and welfare characteristics. AGS has been included in the Aviagen breeding goal since 2011.

Assessment of pig welfare at slaughterhouse level: A systematic review of animal-based indicators suitable for inclusion in monitoring protocols

Pig welfare constitutes a strategic pillar of sustainability within the pork industry. Consequently, there is a need to identify, develop and/or validate indicators for assessing pig wellbeing under commercial conditions. A systematic review following PRISMA guidelines identified 95 pig welfare indicators (PWIs) categorized into physiological, behavioral, health and post-mortem, and product quality. The review evaluated their validity and feasibility (V&F) for use in abattoirs to measure welfare during transport and slaughter. Thirty V&F indicators were found: one physiological (body temperature), 12 behavioral (human-animal relationship, aggression, falling, vocalization, slipping, panting, lying down, sitting, turning back), 13 health and post-mortem (presence of entry points, hernias, body lesions, ear lesions, tail lesions, pericarditis, pneumonia, bursitis, lameness, dead animals, walking and non-walking animals), and four product quality (pH, bruises, body condition, carcass weight). This information might help to identify the factors that affect the risk level of particular pig welfare problems, thereby aiding in the application of risk-based strategies.

Do Activity Sensors Identify Physiological, Clinical and Behavioural Changes in Laying Hens Exposed to a Vaccine Challenge?

This study aimed to identify if sensor technology could be used to detect sickness-type signs (caused by a live vaccine) in laying hens compared to physiological and clinical sign scoring and behaviour observation. The experiment comprised 5 replicate batches (4 hens and 12 days per batch) using previously non-vaccinated hens (n = 20). Hens were moved on day 1 to a large experimental room with various designated zones (e.g., litter, perches, nest box), where they wore two sensors (FitBark, TrackLab). Saline was applied using ocular and nasal drops on day 3 as a control. A live vaccine (Infectious Laryngotracheitis, ILT, vaccine), applied using the same method on day 6, was used to induce mild respiratory and other responses. Physiological and clinical signs, and behaviour from videos were also recorded by a single observer. There were significant changes in body weight (p < 0.001), feed intake (p = 0.031), cloacal temperature (p < 0.001) and three out of five clinical signs (ocular discharge (p < 0.001), conjunctivitis (p < 0.001) and depression (p = 0.009)) over days. A significant decrease (p < 0.001) in activity level (FitBark) and distance travelled (both sensors) were identified over the study days, and activity and distance travelled were highly significantly associated (p < 0.001) with total clinical scores, with hens showing reduced activity and distance travelled with worsening total clinical scores. With behaviour observations from videos, the proportions of sitting, foraging and feeding behaviours (p = 0.044, 0.036 and 0.004, respectively), the proportion of total visit duration to the litter zone (p < 0.001) and perch (p = 0.037) with TrackLab and the proportions of visit counts of hens in the litter zone (p = 0.012) from video scanning changed significantly with days. This study suggests that the vaccine challenge caused associated changes in clinical/physiological signs and activity/distance travelled data from the sensors. Sensors may have a role in detecting changes in activity and movement in individual hens indicative of health or welfare problems.

Overview of the various methods used to assess walking ability in broiler chickens

BACKGROUND

Walking ability is a highly important animal-based indicator of welfare in broilers that warrants monitoring across commercial production.

METHODS

A review of the technical and scientific literature on existing methods for assessing walking ability in broilers was conducted, and the reliability, validity and feasibility of the different methods were assessed when relevant information was available.

RESULTS

Visual gait scoring has high validity, minimal equipment needs and is relatively quick to perform; however, this method is subjective and requires extensive training. Due to this, more objective tests, such as the latency to lie test, have been developed, although more validation of these tests is required. Other identified methods, such as obstacle courses, the rotarod test and kinetic and kinematic approaches, require considerable amounts of equipment, making them impractical for use during on-farm inspections. Automated methods that rely on movement or activity data have potential for future development but currently lack the resolution of traditional gait scoring and require equipment such as cameras or accelerometers.

CONCLUSIONS

Objective, seemingly valid, repeatable and feasible options exist for the assessment of walking ability that would facilitate the monitoring of commercial broiler welfare; however, more validation of these methods is required, especially in commercial farm settings.

Evaluating broiler welfare and behavior as affected by growth rate and stocking density

This study evaluated the welfare and behaviors of Cobb 700 broilers as affected by growth rate (GR) and stocking density (SD). Slower-growth (weight gain < 50 g/d) and medium-growth (weight gain = 50-60 g/d) broilers were produced by providing 57.1% and 78.6% of the feed intake listed in the Cobb 700 production manual for standard (fed ad libitum) broilers (weight gain > 60 g/d). Broilers at all 3 GRs were reared at 2 SDs of 30 and 40 kg/m2. Broiler welfare indicators, including gait score, tibia strength, feather coverage, and footpad condition were evaluated when birds reached 1, 2, and 3 kg of body weight. The activity index was determined by overhead cameras and image processing, and the time spent at feeders was recorded using the radio-frequency identification (RFID) systems. The results show that it took 45 d for standard, 52 d for medium-growth, and 62 d for slower-growth broilers to reach a 3 kg market body weight. Feed conversion ratios (FCR, kg/kg) were 1.57 for standard, 1.67 for medium-growth, and 1.80 for slower-growth broilers. Growth rate and SD had an interaction effect on feather cleanliness (P = 0.03), and belly feather coverage (P = 0.02). Slower-growth broilers were more active and had better feather coverage and gait scores than medium-growth and standard broilers (all P < 0.01) but may feel hungry and depressed, medium-growth broilers spent the most time at the feeder among the 3 growth groups (P = 0.02), and standard broilers showed the best production performance. Broilers at 30 kg/m2 showed better bone strength (P = 0.04), and footpad condition (P < 0.01) compared to those at 40 kg/m2. In conclusion, reducing GR and SD may slightly improve broiler leg health at the high expense of compromised production performance and prolonged production cycles.

Active walking in broiler chickens: a flagship for good welfare, a goal for smart farming and a practical starting point for automated welfare recognition

Automated assessment of broiler chicken welfare poses particular problems due to the large numbers of birds involved and the variety of different welfare measures that have been proposed. Active (sustained, defect-free) walking is both a universally agreed measure of bird health and a behavior that can be recognized by existing technology. This makes active walking an ideal starting point for automated assessment of chicken welfare at both individual and flock level.

Farmers' Perspectives of the Benefits and Risks in Precision Livestock Farming in the EU Pig and Poultry Sectors

More efficient livestock production systems are necessary, considering that only 41% of global meat demand will be met by 2050. Moreover, the COVID-19 pandemic crisis has clearly illustrated the necessity of building sustainable and stable agri-food systems. Precision Livestock Farming (PLF) offers the continuous capacity of agriculture to contribute to overall human and animal welfare by providing sufficient goods and services through the application of technical innovations like digitalization. However, adopting new technologies is a challenging issue for farmers, extension services, agri-business and policymakers. We present a review of operational concepts and technological solutions in the pig and poultry sectors, as reflected in 41 and 16 European projects from the last decade, respectively. The European trend of increasing broiler-meat production, which is soon to outpace pork, stresses the need for more outstanding research efforts in the poultry industry. We further present a review of farmers' attitudes and obstacles to the acceptance of technological solutions in the pig and poultry sectors using examples and lessons learned from recent European projects. Despite the low resonance at the research level, the investigation of farmers' attitudes and concerns regarding the acceptance of technological solutions in the livestock sector should be incorporated into any technological development.

Automated pose estimation reveals walking characteristics associated with lameness in broilers

Walking ability of broilers can be improved by selective breeding, but large-scale phenotypic records are required. Currently, gait of individual broilers is scored by trained experts, however, precision phenotyping tools could offer a more objective and high-throughput alternative. We studied whether specific walking characteristics determined through pose estimation are linked to gait in broilers. We filmed male broilers from behind, walking through a 3 m × 0.4 m (length × width) corridor one by one, at 3 time points during their lifetime (at 14, 21, and 33 d of age). We used a deep learning model, developed in DeepLabCut, to detect and track 8 keypoints (head, neck, left and right knees, hocks, and feet) of broilers in the recorded videos. Using the keypoints of the legs, 6 pose features were quantified during the double support phase of walking, and 1 pose feature was quantified during steps, at maximum leg lift. Gait was scored on a scale from 0 to 5 by 4 experts, using the videos recorded on d 33, and the broilers were further classified as having either good gait (mean gait score ≤2) or suboptimal gait (mean gait score >2). The relationship of pose features on d 33 with gait was analyzed using the data of 84 broilers (good gait: 57.1%, suboptimal gait: 42.9%). Birds with suboptimal gait had sharper hock joint lateral angles and lower hock-feet distance ratios during double support on d 33, on average. During steps, relative step height was lower in birds with suboptimal gait. Step height and hock-feet distance ratio showed the largest mean deviations in broilers with suboptimal gait compared to those with good gait. We demonstrate that pose estimation can be used to assess walking characteristics during a large part of the productive life of broilers, and to phenotype and monitor broiler gait. These insights can be used to understand differences in the walking patterns of lame broilers, and to build more sophisticated gait prediction models.

Effect of phased reduction of dietary digestible lysine density on growth performance, thigh meat, and biomechanical characteristics of tibia in broiler chickens

In this study, growth performance, nutrient intake, thigh meat quality, fatty acid composition of thigh meat, and biomechanical characteristics of tibia of broiler chickens in response to phased restriction of dietary digestible lysine (dLys) were evaluated. A total of 180 male broiler chickens distributed to 3 experimental groups were fed control diets, 85% dLys diet in grower phase (GRO 85% dLys), or 85% dLys diets in grower and finisher phases (GRO-FIN 85% dLys). Feeding 85% dLys suppressed the feed intake that suppressed the growth performance, slaughter weight, and thigh weight of broiler chickens compared to control group (P < 0.05). Average daily dLys, Ca, and P intakes were suppressed in groups fed 85% dLys diets in comparison with control group (P < 0.05) due to the suppression of feed intake. While most fatty acid concentrations in thigh meat were not different among the groups, eicosanoic acid (C20:0) in thigh meat was greater in GRO-FIN 85% dLys group than control group (P = 0.002). Antioxidant status of thigh meat of broiler chickens was not affected by the phased restriction of dietary dLys compared to control group. Bone breaking strength and ultimate strength were greater in control group than 85% dLys groups (P < 0.05). In conclusion, phased dilution of dietary dLys to 85% of the required allowance yields weaker legs and tibia bones by suppressing the Ca and P intakes as a function of reduced feed intake in broiler chickens.

When Everything Becomes Bigger: Big Data for Big Poultry Production

In future decades, the demand for poultry meat and eggs is predicted to considerably increase in pace with human population growth. Although this expansion clearly represents a remarkable opportunity for the sector, it conceals a multitude of challenges. Pollution and land erosion, competition for limited resources between animal and human nutrition, animal welfare concerns, limitations on the use of growth promoters and antimicrobial agents, and increasing risks and effects of animal infectious diseases and zoonoses are several topics that have received attention from authorities and the public. The increase in poultry production must be achieved mainly through optimization and increased efficiency. The increasing ability to generate large amounts of data ("big data") is pervasive in both modern society and the farming industry. Information accessibility-coupled with the availability of tools and computational power to store, share, integrate, and analyze data with automatic and flexible algorithms-offers an unprecedented opportunity to develop tools to maximize farm profitability, reduce socio-environmental impacts, and increase animal and human health and welfare. A detailed description of all topics and applications of big data analysis in poultry farming would be infeasible. Therefore, the present work briefly reviews the application of sensor technologies, such as optical, acoustic, and wearable sensors, as well as infrared thermal imaging and optical flow, to poultry farming. The principles and benefits of advanced statistical techniques, such as machine learning and deep learning, and their use in developing effective and reliable classification and prediction models to benefit the farming system, are also discussed. Finally, recent progress in pathogen genome sequencing and analysis is discussed, highlighting practical applications in epidemiological tracking, and reconstruction of microorganisms' population dynamics, evolution, and spread. The benefits of the objective evaluation of the effectiveness of applied control strategies are also considered. Although human-artificial intelligence collaborations in the livestock sector can be frightening because they require farmers and employees in the sector to adapt to new roles, challenges, and competencies-and because several unknowns, limitations, and open-ended questions are inevitable-their overall benefits appear to be far greater than their drawbacks. As more farms and companies connect to technology, artificial intelligence (AI) and sensing technologies will begin to play a greater role in identifying patterns and solutions to pressing problems in modern animal farming, thus providing remarkable production-based and commercial advantages. Moreover, the combination of diverse sources and types of data will also become fundamental for the development of predictive models able to anticipate, rather than merely detect, disease occurrence. The increasing availability of sensors, infrastructures, and tools for big data collection, storage, sharing, and analysis-together with the use of open standards and integration with pathogen molecular epidemiology-have the potential to address the major challenge of producing higher-quality, more healthful food on a larger scale in a more sustainable manner, thereby protecting ecosystems, preserving natural resources, and improving animal and human welfare and health.

Individual Monitoring of Activity and Lameness in Conventional and Slower-Growing Breeds of Broiler Chickens Using Accelerometers

Accelerometers are increasingly being investigated to detect animal behavior as a method for monitoring individual welfare that overcomes manual challenges associated with time, resource, and discrete sampling. We investigated the effects of broiler chicken hybrid (hereafter breed) and weight on accelerometer activity (activityA; calculated as percentage of time spent active (%)) and its association with lameness as a major broiler welfare concern. Accelerometers were attached to birds of different breeds on between 2 and 4 occasions from 26 to 30 days old (conventional breed CNV) and 26 to 49 days old (two slower-growing breeds SGH; SGN). At 2.2 kg, lameness was scored using a 6-point gait scoring system (0: unaffected to 5: severely lame). Linear mixed effects models and breed-stratified generalized linear models together with a random-effect meta-analysis were used for data analyses. ActivityA was lower in faster-growing, heavier birds compared to slower-growing, lighter birds, showing overall consistency with previous behavioral research, but did not vary linearly with gait score. Accelerometers offer the potential for simple broad-scale continuous monitoring of broiler chicken activity behavior that requires limited data processing. Exploration of the ability of accelerometers to capture more subtle and specific changes in behavioral patterning, such as non-linear acceleration with gait score that could indicate early development of lameness, warrants further investigation.

Tracking and Characterizing Spatiotemporal and Three-Dimensional Locomotive Behaviors of Individual Broilers in the Three-Point Gait-Scoring System

Gait scoring is a useful measure for evaluating broiler production efficiency, welfare status, bone quality, and physiology. The research objective was to track and characterize spatiotemporal and three-dimensional locomotive behaviors of individual broilers with known gait scores by jointly using deep-learning algorithms, depth sensing, and image processing. Ross 708 broilers were placed on a platform specifically designed for gait scoring and manually categorized into one of three numerical scores. Normal and depth cameras were installed on the ceiling to capture top-view videos and images. Four birds from each of the three gait-score categories were randomly selected out of 70 total birds scored for video analysis. Bird moving trajectories and 16 locomotive-behavior metrics were extracted and analyzed via the developed deep-learning models. The trained model gained 100% accuracy and 3.62 ± 2.71 mm root-mean-square error for tracking and estimating a key point on the broiler back, indicating precise recognition performance. Broilers with lower gait scores (less difficulty walking) exhibited more obvious lateral body oscillation patterns, moved significantly or numerically faster, and covered more distance in each movement event than those with higher gait scores. In conclusion, the proposed method had acceptable performance for tracking broilers and was found to be a useful tool for characterizing individual broiler gait scores by differentiating between selected spatiotemporal and three-dimensional locomotive behaviors.

EFSA AHAW Panel (EFSA Panel on Animal Health and Welfare), Nielsen SS, Alvarez J, Bicout DJ, Calistri P, Canali E, Drewe JA, Garin‐Bastuji B, Gonzales Rojas JL, Schmidt CG, Herskin MS, Miranda Chueca MÁ, Padalino B, Pasquali P, Roberts HC, Spoolder H, Stahl K, Velarde A, Viltrop A, Winckler C, Tiemann I, de Jong I, Gebhardt‐Henrich SG, Keeling L, Riber AB, Ashe S, Candiani D, García Matas R, Hempen M, Mosbach‐Schulz O, Rojo Gimeno C, Van der Stede Y, Vitali M, Bailly‐Caumette E, Michel V. Welfare of broilers on farm

This Scientific Opinion considers the welfare of domestic fowl (Gallus gallus) related to the production of meat (broilers) and includes the keeping of day-old chicks, broiler breeders, and broiler chickens. Currently used husbandry systems in the EU are described. Overall, 19 highly relevant welfare consequences (WCs) were identified based on severity, duration and frequency of occurrence: 'bone lesions', 'cold stress', 'gastro-enteric disorders', 'group stress', 'handling stress', 'heat stress', 'isolation stress', 'inability to perform comfort behaviour', 'inability to perform exploratory or foraging behaviour', 'inability to avoid unwanted sexual behaviour', 'locomotory disorders', 'prolonged hunger', 'prolonged thirst', 'predation stress', 'restriction of movement', 'resting problems', 'sensory under- and overstimulation', 'soft tissue and integument damage' and 'umbilical disorders'. These WCs and their animal-based measures (ABMs) that can identify them are described in detail. A variety of hazards related to the different husbandry systems were identified as well as ABMs for assessing the different WCs. Measures to prevent or correct the hazards and/or mitigate each of the WCs are listed. Recommendations are provided on quantitative or qualitative criteria to answer specific questions on the welfare of broilers and related to genetic selection, temperature, feed and water restriction, use of cages, light, air quality and mutilations in breeders such as beak trimming, de-toeing and comb dubbing. In addition, minimal requirements (e.g. stocking density, group size, nests, provision of litter, perches and platforms, drinkers and feeders, of covered veranda and outdoor range) for an enclosure for keeping broiler chickens (fast-growing, slower-growing and broiler breeders) are recommended. Finally, 'total mortality', 'wounds', 'carcass condemnation' and 'footpad dermatitis' are proposed as indicators for monitoring at slaughter the welfare of broilers on-farm.

Seeing is caring – automated assessment of resource use of broilers with computer vision techniques

Routine monitoring of broiler chickens provides insights in the welfare status of a flock, helps to guarantee minimum defined levels of animal welfare and assists farmers in taking remedial measures at an early stage. Computer vision techniques offer exciting potential for routine and automated assessment of broiler welfare, providing an objective and biosecure alternative to the current more subjective and time-consuming methods. However, the current state-of-the-art computer vision solutions for assessing broiler welfare are not sufficient to allow the transition to fully automated monitoring in a commercial environment. Therefore, the aim of this study was to investigate the potential of computer vision algorithms for detection and resource use monitoring of broilers housed in both experimental and commercial settings, while also assessing the potential for scalability and resource-efficient implementation of such solutions. This study used a combination of detection and resource use monitoring methods, where broilers were first detected using Mask R-CNN and were then assigned to a specific resource zone using zone-based classifiers. Three detection models were proposed using different annotation datasets: model A with annotated broilers from a research facility, model B with annotated broilers from a commercial farm, and model A+B where annotations from both environments were combined. The algorithms developed for individual broiler detection performed well for both the research facility (model A, F1 score &gt; 0.99) and commercial farm (model A+B, F1 score &gt; 0.83) test data with an intersection over union of 0.75. The subsequent monitoring of resource use at the commercial farm using model A+B for broiler detection, also performed very well for the feeders, bale and perch (F1 score &gt; 0.93), but not for the drinkers (F1 score = 0.28), which was likely caused by our evaluation method. Thus, the algorithms used in this study are a first step to measure resource use automatically in commercial application and allow detection of a large number of individual animals in a non-invasive manner. From location data of every frame, resource use can be calculated. Ultimately, the broiler detection and resource use monitoring might further be used to assess broiler welfare.

Research Progress in the Early Warning of Chicken Diseases by Monitoring Clinical Symptoms

Global animal protein consumption has been steadily increasing as a result of population growth and the increasing demand for nutritious diets. The poultry industry provides a large portion of meat and eggs for human consumption. The early detection and warning of poultry infectious diseases play a critical role in the poultry breeding and production systems, improving animal welfare and reducing losses. However, inadequate methods for the early detection and prevention of infectious diseases in poultry farms sometimes fail to prevent decreased productivity and even widespread mortality. The health status of poultry is often reflected by its individual physiological, physical and behavioral clinical symptoms, such as higher body temperature resulting from fever, abnormal vocalization caused by respiratory disease and abnormal behaviors due to pathogenic infection. Therefore, the use of technologies for symptom detection can monitor the health status of broilers and laying hens in a continuous, noninvasive and automated way, and potentially assist in the early warning decision-making process. This review summarized recent literature on poultry disease detection and highlighted clinical symptom-monitoring technologies for sick poultry. The review concluded that current technologies are already showing their superiority to manual inspection, but the clinical symptom-based monitoring systems have not been fully utilized for on-farm early detection.

Computer-Vision-Based Indexes for Analyzing Broiler Response to Rearing Environment: A Proof of Concept

Simple Summary

We tested two computer-vision-based indexes to analyze the rearing-environment enrichment on broiler movement as a function of comfort temperature and heat stress. The results indicated that the simultaneous application of cluster and unrest indexes could monitor the movement of the group of broilers under different environmental conditions. Future monitoring and alert systems based on computer vision should consider the complexity of the environment for detecting heat stress in broiler production.

Abstract

Computer-vision systems for herd detection and monitoring are increasingly present in precision livestock. This technology provides insights into how environmental variations affect the group’s movement pattern. We hypothesize that the cluster and unrest indexes based on computer vision (CV) can simultaneously assess the movement variation of reared broilers under different environmental conditions. The present study is a proof of principle and was carried out with twenty broilers (commercial strain Cobb^®), housed in a controlled-environment chamber. The birds were divided into two groups, one housed in an enriched environment and the control. Both groups were subjected to thermal comfort conditions and heat stress. Image analysis of individual or group behavior is the basis for generating animal-monitoring indexes, capable of creating real-time alert systems, predicting welfare, health, environment, and production status. The results obtained in the experiment in a controlled environment allowed the validation of the simultaneous application of cluster and unrest indexes by monitoring the movement of the group of broilers under different environmental conditions. Observational results also suggest that research in more significant proportions should be carried out to evaluate the potential positive impact of environmental enrichment in poultry production. The complexity of the environment is a factor to be considered in creating alert systems for detecting heat stress in broiler production. In large groups, birds’ movement and grouping patterns may differ; therefore, the CV system and indices will need to be recalibrated.

Effects of barrier perch access and early dietary protein and energy dilution on some welfare parameters, tibiotarsus measurements, fear and mobility level in broiler chickens

1. This experiment determined the effect of increasing mobility in broiler chickens by placing barrier perches between feeders and drinkers. In addition, the limitation of early weight gain by dietary energy and protein dilution on some welfare parameters, tibiotarsus measurements, fear and mobility level was examined.2. A total of 504 male, one-day-old broiler chickens (Ross 308) were randomly allocated to four treatments with three replicate pens per treatment and 42 broiler chickens per pen as a 2 × 2 factorial arrangement. Treatments included feeding the basal control diet between 0-42 days or a diet diluted by 10% energy and 20% crude protein fed between 0-21 d, with the control diet fed between 22-42 d. The second factor was the presence or absence of barrier perches. All treatments were allocated as a completely randomised design. Welfare parameters (foot pad dermatitis, hock burn, gait score, feather score, breast blister), tibiotarsus measurements (bone mineral content, bone mineral density, fluctuating asymmetry and relative fluctuating asymmetry), tonic immobility and mobility level were recorded.3. Results showed that access to a barrier perch and the diluted diet increased the mobility in broiler chickens. However, access to a barrier perch had no significant effect on tibiotarsus and welfare parameters. Broiler chickens had better gait scores (P < 0.05) and lower foot pad dermatitis incidence (P < 0.01) in groups fed the diluted diet. The diluted diet had no significant effect on bone mineral density but reduced the tibiotarsus bone mineral content (P < 0.05).4. In conclusion, the diluted diet provided positive effects in terms of leg health due to weight gain limitations in the early period, thus improving broiler chicken welfare.

Movement Analysis to Associate Broiler Walking Ability with Gait Scoring

The genetic development of the commercial broiler has led to body misconfiguration and consequent walking disabilities, mainly at the slaughter age. The present study aimed to identify broiler locomotion ability using image analysis automatically. A total of 40 broilers that were 40 d old (male and female) were placed to walk on a specially built runway, and their locomotion was recorded. An image segmentation algorithm was developed, and the coordinates of the bird’s center of mass were extracted from the segmented images for each frame analyzed, and the unrest index (UI) was applied. We calculated the center of mass’s movement of the broiler walking lateral images capturing the bird’s displacement speed in the onward direction. Results indicated that broiler walking speed on the runway tends to decrease with the increase of the gait score. The locomotion did not differ between males or females. The proposed algorithm was efficient in predicting the broiler gait score based on their displacement speed.

The relationship between gait and automated recordings of individual broiler activity levels

Gait, or walking ability, is an often-measured trait in broilers. Individual gait scores are generally determined manually, which can be time-consuming and subjective. Automated methods of scoring gait are available, but are often implemented at the group level. However, there is an interest in automated methods of scoring gait at the individual level. We hypothesized that locomotor activity could serve as a proxy for gait of individual broilers. Locomotor activity of 137 group-housed broilers from four crosses was recorded from approximately 16 to 32 days old, using an ultra-wideband tracking system. These birds were divided over four trials. Individual gait scores were determined at the end of the tracking period, on a scale from 0 to 5, with higher scores representing worse gait. Given the limited number of birds, birds were subsequently categorized as having a good gait (GG; scores 0–2) or a suboptimal gait (SG; scores 3–5). Relationships between activity and gait classification were studied to determine whether individual activity has the potential to serve as a proxy for gait. When comparing GG and SG birds using robust linear regression, SG birds showed a lower 1) activity around the start of tracking (estimate = −1.33 ± 0.56, P = 0.019), 2) activity near the end of tracking (estimate = −1.63 ± 0.38, P < 0.001), and 3) average activity (estimate = −1.12 ± 0.41, P = 0.007). When taking day of tracking, trial, cross and body weight category (heavy versus light at approximately 2 wk old) into account, a tendency was still observed for SG birds having lower activity levels within lightweight birds, but not within heavyweight birds. This study provides indications for activity differences between gait classifications. However, given that there was considerable overlap in activity levels between the gait classifications, future research implementing additional activity-related variables is required to allow a more complete distinction between birds with different gait classifications.

Do we automatically detect health- or general welfare-related issues? A framework

The early detection of health disorders is a central goal in livestock production. Thus, a great demand for technologies enabling the automated detection of such issues exists. However, despite decades of research, precision livestock farming (PLF) technologies with sufficient accuracy and ready for implementation on commercial farms are rare. A central factor impeding technological development is likely the use of non-specific indicators for various issues. On commercial farms, where animals are exposed to changing environmental conditions, where they undergo different internal states and, most importantly, where they can be challenged by more than one issue at a time, such an approach leads inevitably to errors. To improve the accuracy of PLF technologies, the presented framework proposes a categorization of the aim of detection of issues related to general welfare, disease and distress and defined disease. Each decision level provides a different degree of information and therefore requires indicators varying in specificity. Based on these considerations, it becomes apparent that while most technologies aim to detect a defined health issue, they facilitate only the identification of issues related to general welfare. To achieve detection of specific issues, new indicators such as rhythmicity patterns of behaviour or physiological processes should be examined.

Accuracy of Broiler Activity Index as Affected by Sampling Time Interval

Simple Summary

Broiler activity index is a measure of bird movement through determining bird-representative pixel changes between consecutive images. Since the concept of activity index was coined, different sampling time intervals of consecutive images have been used to determine broiler activity. In this study, we found that accuracy of broiler activity decreased at longer sampling time intervals, with the 0.04-s interval yielding the most accurate activity index among all intervals investigated. In addition, broiler activity in the commercial house generally decreased as birds aged and varied at different monitoring locations. The research provides insights into image-sampling strategies for accurately determining broiler activity index, which may help to address growing public concerns on poultry welfare and health.

Abstract

Different time intervals between consecutive images have been used to determine broiler activity index (AI). However, the accuracy of broiler AI as affected by sampling time interval remains to be explored. The objective of this study was to investigate the effect of the sampling time interval (0.04, 0.2, 1, 10, 60, and 300 s) on the accuracy of broiler AI at different bird ages (1–7 weeks), locations (feeder, drinker, and open areas) and times of day (06:00–07:00 h, 12:00–13:00 h, and 18:00–19:00 h). A ceiling-mounted camera was used to capture top-view videos for broiler AI calculations. The results show that the sampling time interval of 0.04 s yielded the highest broiler AI because more bird motion details were captured at this short time interval. The broiler AIs at longer time intervals were 1–99% of that determined at the 0.04-s interval. The broiler AI at 0.2-s interval showed an acceptable accuracy with 80% less computational resources. Broiler AI decreased as birds aged but increased after week 4 at the drinker area. Broiler AI was the highest at the open area for weeks 1–4 and at the feeder and drinker areas for weeks 5–7. It is concluded that the accuracy of broiler AI was significantly affected by sampling time intervals. Broiler AI in commercial housing showed both temporal and spatial variations.

How Are Information Technologies Addressing Broiler Welfare? A Systematic Review Based on the Welfare Quality® Assessment

This systematic review aims to explore how information technologies (ITs) are currently used to monitor the welfare of broiler chickens. The question posed for the review was “which ITs are related to welfare and how do they monitor this for broilers?”. The Welfare Quality® (WQ) protocol for broiler assessment was utilized as a framework to analyse suitable articles. A total of 57 studies were reviewed wherein all principles of broiler welfare were addressed. The “good health” principle was the main criteria found to be addressed by ITs and IT-based studies (45.6% and 46.1%, respectively), whereas the least observed principle was “good feeding” (8.8%). This review also classified ITs and IT-based studies by their utilization (location, production system, variable measured, aspect of production, and experimental/practical use). The results show that the current focus of ITs is on problems with conventional production systems and that less attention has been given to free-range systems, slaughterhouses, and supply chain issues. Given the valuable results evidenced by the exploitation of ITs, their use in broiler production should continue to be encouraged with more attention given to farmer adoption strategies.