Search Results (657)

Surgical castration of male piglets is a common practice to prevent boar taint and reduce aggressive behaviour. However, it raises welfare concerns and alters carcass fat deposition. Immunocastration, a vaccine-based alternative targeting gonadotropin-releasing hormone (GnRH), mitigates these welfare issues. This study evaluated carcass traits and meat quality in surgically and immunocastrated pigs slaughtered at two weight classes (approximately 116 kg and 136 kg). We compared growth performance, carcass composition, fat quality, and key meat quality indicators among surgically castrated males, immunocastrated males, and immunocastrated females. Inclusion of uncastrated and immunocastrated females provides novel comparative data for mixed-sex production systems, where such information is scarce. This broader evaluation helps fill current gaps in knowledge about immunocastration effects in female pigs. Surgically castrated males showed higher backfat thickness and fat content, particularly at the heavier weight, while immunocastrated pigs exhibited intermediate traits. Ultimate pH, colour, marbling, water-holding capacity, and moisture loss varied with castration method, sex, and slaughter weight, though many differences were subtle. The findings confirm that immunocastration offers a favourable balance between animal welfare and production traits, producing pork quality comparable to surgical castration. These results provide valuable insights for optimizing pork production systems, balancing welfare, efficiency, and meat quality. Full article

Calf disbudding is a routine practice in the dairy industry to prevent horn growth and reduce the risk of injury to animals and handlers. However, growing public concern about animal welfare has raised questions about the acceptability of common disbudding methods. This study explored public perceptions of caustic paste and hot-iron disbudding using a mixed methods approach. Quantitative survey analyses captured measurable trends while iterative qualitative analysis explored the underlying reasons behind participant’s attitudes. A convenience sample with a total of 511 Texas resident participants completed a 44-item online survey that included demographic questions, the Animal Attitude Scale (AAS-10), and image-based evaluations of the two techniques. Quantitative analysis using factor analysis and multiple regression revealed that concern for animal welfare and justification for animal use were the most significant predictors (p < 0.001) of method acceptability, with caustic paste generally viewed as more humane. Qualitative responses reinforced these results, identifying themes of animal suffering, ethical concerns, and a widespread lack of public knowledge. While caustic paste was preferred, skepticism toward hot-iron disbudding was more pronounced among low-income participants. Nonetheless, when properly performed with pain control, hot-iron disbudding is often considered a more controlled and welfare-conscious method due to faster healing times and reduced risk of injury to other animals from paste exposure. These findings underscore the need for consumer education and transparent communication from the dairy industry. Full article

Artificial Intelligence (AI) is widely recognized as a force that will fundamentally transform traditional chicken farming models. It can reduce labor costs while ensuring welfare and at the same time increase output and quality. However, the breadth of AI’s contribution to chicken farming has not been systematically quantified on a large scale; few people know how far current AI has actually progressed or how it will improve chicken farming to enhance the sector’s sustainability. Therefore, taking “AI + sustainable chicken farming” as the theme, this study retrieved 254 research papers for a comprehensive descriptive analysis from the Web of Science (May 2003 to March 2025) and analyzed AI’s contribution to the sustainable in recent years. Results show that: In the welfare dimension, AI primarily targets disease surveillance, behavior monitoring, stress detection, and health scoring, enabling earlier, less-invasive interventions and more stable, longer productive lifespans. In economic dimension, tools such as automated counting, vision-based weighing, and precision feeding improve labor productivity and feed use while enhancing product quality. In the environmental dimension, AI supports odor prediction, ventilation monitoring, and control strategies that lower emissions and energy use, reducing farms’ environmental footprint. However, large-scale adoption remains constrained by the lack of open and interoperable model and data standards, the compute and reliability burden of continuous multi-sensor monitoring, the gap between AI-based detection and fully automated control, and economic hurdles such as high upfront costs, unclear long-term returns, and limited farmer acceptance, particularly in resource-constrained settings. Environmental applications are also underrepresented because research has been overly vision-centric while audio and IoT sensing receive less attention. Looking ahead, AI development should prioritize solutions that are low cost, robust, animal friendly, and transparent in their benefits so that return on investment is visible in practice, supported by open benchmarks and standards, edge-first deployment, and staged cost–benefit pilots. Technically, integrating video, audio, and environmental sensors into a perception–cognition–action loop and updating policies through online learning can enable full-process adaptive management that improves welfare, enhances resource efficiency, reduces emissions, and increases adoption across diverse production contexts. Full article

The aim of this project was to co-create an animal welfare monitoring system that incorporated both positive and negative welfare measures that would contribute to best practice husbandry standards of farm animals in a real animal research setting. Researchers worked with nine staff to co-design six bespoke welfare assessment protocols to be conducted in addition to legally required welfare monitoring for adult cattle, calves, sheep, pigs, and goats in specific experimental environments. Four protocols were subsequently applied with variable frequency by three staff to cattle, goats, and two pig populations. Assessments were all observational, and included behavioural scan sampling, Qualitative Behaviour Assessment scores, visual analogue mood scores, and physical condition data. Two staff provided feedback on their views of the process. A key finding was that with facilitation, staff could generate protocols that included elements designed to encourage or evaluate interventions to promote positive emotions. However, data collection was sporadic, and although the staff who provided feedback reported that they valued the process highly, they noted that the primary challenge was finding the time to conduct the assessments. We therefore conclude that sustained support is likely to be required to maximise the benefits for the animals and staff of developing and conducting voluntary welfare monitoring of farm animals. Full article

Non-contact, automated health monitoring is a cornerstone of modern precision livestock farming, crucial for enhancing animal welfare and productivity. Infrared thermography (IRT) offers a powerful, non-invasive means to assess physiological status. However, its practical use on farms is limited by a key challenge: accurately locating regions of interest (ROIs), like the eyes and face, in the blurry, low-resolution thermal images common in farm settings. To solve this, we developed a new framework called ID-APM, which is designed for robust ROI registration in agriculture. Our method uses a trinocular system and our RAP-CPD algorithm to robustly match features and accurately calculate the target’s 3D position. This 3D information then enables the precise projection of the ROI’s location onto the ambiguous thermal image through inverse disparity estimation, effectively overcoming errors caused by image blur and spectral inconsistencies. Validated on a self-built dataset of farmed sika deer, the ID-APM framework demonstrated exceptional performance. It achieved a remarkable overall accuracy of 96.95% and a Correct Matching Ratio (CMR) of 99.93%. This research provides a robust and automated solution that effectively bypasses the limitations of low-resolution thermal sensors, offering a promising and practical tool for precision health monitoring, early disease detection, and enhanced management of semi-wild farmed animals like sika deer. Full article

Keel bone lesions (KBLs) represent a relevant welfare concern in laying hens, arising from complex interactions among genetics, housing systems, and management practices. This study presents the development of an image analysis system for the automated detection and classification of KBLs in slaughterhouse videos, enabling scalable and retrospective welfare assessment. In addition to lesion classification, the system can track and count individual carcasses, providing estimates of the total number of specimens with and without significant lesions. Videos of brown laying hens from a commercial slaughterhouse in northeastern Italy were recorded on the processing line using a smartphone. Six hundred frames were extracted and annotated by three independent observers using a three-scale scoring system. A dataset was constructed by combining the original frames with crops centered on the keel area. To address class imbalance, samples of class 1 (damaged keel bones) were augmented by a factor of nine, compared to a factor of three for class 0 (no or mild lesion). A YOLO-based model was trained for both detection and classification tasks. The model achieved an F1 score of 0.85 and a mAP@0.5 of 0.892. A BoT-SORT tracker was evaluated against human annotations on a 5 min video, achieving an F1 score of 0.882 for the classification task. Potential improvements include increasing the number and variability of annotated images, refining annotation protocols, and enhancing model performance under varying slaughterhouse lighting and positioning conditions. The model could be applied in routine slaughter inspections to support welfare assessment in large populations of animals. Full article

The object of the research is the process of intelligent monitoring and diagnosis of animal health using IoT technology in the context of a digital farm. The problem lies in the absence of an integrated approach that can provide near-real-time assessment of an animal’s physiological and behavioral state, predict potential health risks, and adapt decision-making algorithms to specific species and environmental conditions. Traditional monitoring methods rely heavily on periodic manual inspection and limited sensor data, which reduces the timeliness and accuracy of diagnostics, especially for large-scale farms. To address this issue, a comprehensive model is proposed that integrates an IoT-based tag device for livestock, a data collection and transmission system, and an intelligent analysis module. The system utilizes statistical profiling to create baseline health parameters for each animal, applies anomaly detection methods to identify deviations, and leverages machine learning algorithms to predict health deterioration. The novelty of the approach lies in the combination of individualized baseline modeling, continuous sensor-based monitoring, and adaptive decision-making for early intervention. The approach scales across farm sizes and multi-sensor setups, making it practical for precision livestock farming. From a sustainability perspective, the approach enables earlier and more targeted interventions that can reduce unnecessary treatments, avoid preventable productivity losses, and support animal welfare. The design uses energy-aware IoT practices (on-device 60 s aggregation with one-minute uplinks) and lightweight analytics to limit device power use and network load, aligning the system with resource-efficient livestock operations. Full article

Animal Welfare has a significant impact on the dairy cow’s health, behaviour, productivity and milk quality. By implementing husbandry practices that respect the physical, behavioural and emotional needs of dairy cows, the dairy industry can improve the sustainability of its operations and meet rising expectations. The aim of this study is to evaluate the impact of housing systems (free vs. tied) on dairy cow health through musculoskeletal health indicators and lameness scores. The hypothesis that dairy cows reared in free housing have a better quality of health than cows reared in restrained housing is tested. Thus, 300 dairy cows of the Holstein and Montbeliarde breeds were selected from dairy farms in five municipalities of Constantine province (eastern Algeria). The results showed that the frequency of severe lameness did not exceed 12% in stalls with restraints and more than 42% of light lameness are in free-stall housing (p < 0.001). These results reflect a lack of comfort in restricted housing, with an impact on dairy performances. Moreover, the monitoring of lame cows and the functional trimming of their hooves should be frequent. It is also important to implement a cull policy for unproductive cows. Finally, it is very important to provide adequate training to farmers in order to improve the well-being of dairy cows. Full article

Estimated population growth and increased demand for food production bring with them the evident need for more efficient and sustainable production systems. Because of this, computer vision plays a fundamental role in the development and application of solutions that help producers with the issues that limit livestock production in Brazil and the world. In addition to being stressful for the producer and the animal, the conventional pig weighing system causes productive losses and can compromise meat quality, being considered a practice that does not value animal welfare. The objective was to develop a computational procedure to predict the live weight of pigs in the growth and finishing phases, through the volume of the animals extracted through the processing of 3D images, as well as to analyze the real and estimated biometric measurements to define the relationships of these with live weight and volume obtained. The study was conducted at Roçadinho farm, in the municipality of Capoeiras, located in the Agreste region of the state of Pernambuco, Brazil. The variables weight and 3D images were obtained using a Kinect^®—V2 camera and biometric measurements of 20 animals in the growth phase and 24 animals in the finishing phase, males and females, from the crossing of Pietrain and Large White, totaling 44 animals. To analyze the images, a program developed in Python (PyCharm Community Edition 2020.1.4) was used, to relate the variables, principal component analyses and regression analyzes were performed. The coefficient of linear determination between weight and volume was 73.3, 74.1, and 97.3% for pigs in the growing, finishing, and global phases, showing that this relationship is positive and satisfactorily expressed the weight of the animals. The relationship between the real and estimated biometric variables had a more expressive coefficient of determination in the global phase, having presented values between 77 and 94%. Full article

Open-mouth panting in broiler chickens is a visible and critical indicator of heat stress and compromised welfare. However, detecting this behavior in densely populated cages is challenging due to the small size of the target and frequent occlusions and cluttered backgrounds. To overcome these issues, we proposed an enhanced object detection method based on the lightweight YOLOv8n framework, incorporating four key improvements. First, we add a dedicated P2 detection head to improve the recognition of small targets. Second, a space-to-depth grouped convolution module (SGConv) is introduced to capture fine-grained texture and edge features crucial for panting identification. Third, a bidirectional feature pyramid network (BIFPN) merges multi-scale feature maps for richer representations. Finally, a squeeze-and-excitation (SE) channel attention mechanism emphasizes mouth-related cues while suppressing irrelevant background noise. We trained and evaluated the method on a comprehensive, full-cycle broiler panting dataset covering all growth stages. Experimental results show that our method significantly outperforms baseline YOLO models, achieving 0.92 mAP@50 (independent test set) and 0.927 mAP@50 (leakage-free retraining), confirming strong generalizability while maintaining real-time performance. The initial evaluation had data partitioning limitations; method generalizability is now dually validated through both independent testing and rigorous split-then-augment retraining. This approach provides a practical tool for intelligent broiler welfare monitoring and heat stress management, contributing to improved environmental control and animal well-being. Full article

Biotechnological applications in animals are increasingly developed for use in agriculture and aquaculture to tackle breeding challenges in animal production. By examining two case studies of genetically modified (GM) farmed animals relevant to the European Union, slick-haired cattle and growth-enhanced carp, we highlight the challenges for environmental risk assessment and discuss available assessment approaches to address broader societal concerns. We find that the existing guidance for environmental risk assessment of GM animals available in the European Union faces several challenges. Assessing risks of GM animals in agriculture and aquaculture requires consideration of the farming systems of these animals. In addition, we find that there is a lack of guidance and practical implementation to address wider issues, including cultural, societal, ethical, and socio-economic issues, as well as animal health and welfare issues, related to GM farmed animals. We propose using existing assessment frameworks to address the sustainability of GM farmed animals beyond environmental risk assessment. Sustainability assessment approaches should also address potential farm-level sustainability claims of GM animal applications. We note that issues related to animal health and welfare are cross-disciplinary topics that require special attention when commercializing GM farmed animals. We recommend developing a comprehensive framework, including risk assessment, sustainability assessment, and technology assessment, that will enable policymakers to better anticipate and address the societal, legal, ethical, and governance issues associated with emerging biotechnologies in farmed animals. Full article

Although pet ownership is rapidly increasing in developing countries like Turkey, information on how animals are cared for and fed and on perceived animal welfare remains limited. To address this gap, a survey was conducted with 410 participants from 65 provinces, representing over 80% of the country. The study collected data on pet owner demographics, care and feeding practices, and awareness of animal welfare. The results show that most participants (80.6%) have at least a bachelor’s degree, and most pets (80.9%) were acquired within the last 10 years. Monthly spending on pet care typically ranges from USD 30 to 90. Ingredient quality emerged as the primary factor driving food choices (51%), driven by a growing interest in premium and super-premium products aimed at improving health and well-being. Veterinary clinics play a significant role in shaping feeding decisions. Most pet owners consider their pets family members and feel quite knowledgeable about their welfare and nutrition. The results suggest that recent trends in human nutrition, such as increasing interest in functional foods and higher ingredient standards, are also shaping pet feeding practices, and that closer collaboration between veterinarians and the pet food industry is needed. Full article

Although long neglected, sound is now an increasing topic of interest in zoo and aquarium science. Research has examined the impact of sounds, from various sources, on zoo-housed species, noting that the influence of sound is varied and very context specific. The zoo’s sound environment is influenced by the animals, the built environment, vegetation, climatic, temporal and seasonal factors, equipment use, husbandry practices, and human presence. Different sounds can dominate an enclosure at certain times. This article discusses a workshop involving 12 zoo professionals, held in March 2020, that explored how sound is considered or overlooked in zoo animal management. Although insights are based on a small group, limiting generalisability, the findings highlight areas where further understanding is required and should encourage research extension to other groups of stakeholders. Delegates emphasised that the auditory needs of animals are often underappreciated and that the influence of sound depends on the species involved and how the sound may be perceived. Delegates highlighted the importance of species- and individual-specific approaches, predictability, and how animals have (any) control over sounds experienced in their enclosure. Routine operational sounds, such as closing gates or doors, may inadvertently stress animals, suggesting the need to consider sound in enclosure design and husbandry schedules. Outputs also stated that sound, when carefully managed, can act as enrichment through (for example) structured auditory cues or naturalistic sounds if ecologically relevant. Overall, our findings support integrating sound measurement into broader welfare assessment frameworks and enclosure planning, and they identify practical applications including sound mitigation, enrichment strategies, and staff training. Future research should include a wider range of species (especially understudied taxa), consider the experiences of a wider stakeholder demographic, and evaluate how sound is management in complex or high-traffic areas of the zoo. Full article

Environmental sound and animal vocalizations provide non-invasive information for welfare assessment in livestock systems. This systematic review surveys their application in beef and dairy cattle, poultry, and swine, with a focus on environmental noise, vocalizations and the characterization of acoustic sources. Searches in Scopus and Web of Science followed PRISMA guidance and the PICO framework. After applying strict criteria that required peer-reviewed experimental studies in English, quantifiable acoustic data, and clear descriptions of measurement procedures, the review included 36 studies. Four approaches recur: vocalizations as welfare indicators; characterization of acoustic sources; combined analyses of vocalizations and sources; and evaluation of animal responses to acoustic stimuli. Recent work reports advances in recording equipment, signal processing, and precision livestock tools. Important challenges remain, including heterogeneous acoustic metrics, limited physiological validation, and difficulties applying models under commercial conditions. Overall, the evidence supports sound as a candidate for real-time monitoring and highlights the need for accessible, standardized methods. The findings provide a basis for future research and practical applications in welfare assessment. Full article

Zootechnical practices such as tail docking are still in use in dairy sheep farming, performed in the first week of life, mainly by rubber ring and only rarely by surgical methods. In this study, we evaluated the impact of caudectomy on ovine stress levels, inflammation, and health status by comparing tail docking carried out using rubber rings or surgical amputation. Twenty-one lambs were randomly selected and equally allocated into three groups: controls (n = 7), lambs with tail cut by rubber rings (n = 7), and lambs with caudectomy performed by surgical practice (n = 7). Several biochemical parameters and inflammatory markers were monitored at different times post-caudectomy, as well as wool levels of the stress marker cortisol. Our data revealed that lambs that underwent tail docking by rubber rings, but not by surgical procedure, presented inflammation and stress, as well as a moderate increase in muscular damage markers. These results are useful for the evaluation of animal welfare in dairy sheep that underwent caudectomy, highlighting the need to re-evaluate this procedure, as well as the ways in which it is performed. Full article