Livestock Welfare Research Articles

Opportunities and challenges to enhance the welfare of livestock through positive human-animal relationships

Opportunities and challenges to enhance the welfare of livestock through positive human-animal relationships

Explainable AI for Livestock Disease Detection: An Integrated ML/DL Framework

Livestock diseases lead to significant economic loss and threaten food security. With the increasing demand for dairy and meat products, maintaining animal health has become a critical global priority. Although farmers and agricultural workers often lack deep technical understanding of data processing, modern AI and ML technologies are now central to early disease detection in livestock. Interpretable Machine Learning (IML) and Explainable AI (XAI) provide opportunities to build trust by making model predictions transparent and understandable. This article explores XAI and IML approaches for health monitoring in farm animals, offering insights into early symptom recognition through sensor data and image analysis. XAI integrates CNN-based visual diagnostics and real-time sensor stream interpretation, while IML utilizes SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-agnostic Explanations) for symptom pattern explanation and decision support. Experimental results using publicly available datasets of livestock behavior and visual symptom records demonstrate that XAI/IML-based systems provide farmers and veterinarians with clear, actionable insights to enhance livestock welfare and productivity.

The Role of Prebiotic and Herbal Supplementation in Enhancing Welfare and Resilience of Kenguri Sheep Subjected to Transportation Stress.

A study was conducted to assess the efficacy of prebiotic and herbal supplements to relieve transportation stress based on changes in physiological, hematological, and molecular responses in Kenguri sheep. Thirty healthy female sheep were randomly divided into three groups: a control group (CKS) with no supplementation, a prebiotic supplementation group (PKS), and an herbal supplementation group (HKS). The animals were transported 230 km over seven hours during summer conditions, with temperatures ranging from 32.5 °C to 34.9 °C. The groups that received the prebiotic (75.6 breaths/min; 64.8 beats/min) and herbal supplementation (31.0 breaths/min; 66.8 beats/min) had a significantly reduced respiration rate (RR) and pulse rate (PR) compared to those of the control group (38.7 breaths/min; 75.6 beats/min) (p < 0.01 and p < 0.05, respectively), indicating improved physiological stability. The hemoglobin (HGB) and hematocrit (HCT) levels were also significantly lower in the PKS (24.2 g/dL; 24.8%) and HKS (24.7 g/dL; 24.5%) groups than in the CKS (28.1 g/dL; 24.9%) (p < 0.05), highlighting the mitigation of hematological stress. Further, the plasma glucose level was significantly higher (p < 0.01) in the HKS group (80.0 mg/dL) compared to the CKS group (63.5 mg/dL). However, rectal temperature (RT) and skin temperature (ST), red blood cells (RBCs), mean corpuscular volume (MCV), and white blood cells (WBCs) showed no significant differences among the groups. These findings demonstrate that prebiotic and herbal supplementation can effectively reduce transportation-induced stress in Kenguri sheep, offering a practical strategy to improve the welfare and resilience of livestock under challenging environmental conditions.

AI &amp; ML for Livestock Welfare: Analysing Behaviour and Stress Patterns for Better Care

Monitoring animal health, analysing behaviour, and preventing disease are all being revolutionized by the application of artificial intelligence (AI) and machine learning (ML) in livestock welfare. This study investigates how AI-driven models might improve cattle care by identifying patterns in a variety of data sources, including biometric tracking, video analysis, and sensor-based monitoring. Convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs) are examples of deep learning architectures that are highlighted in the study for their superiority over traditional methods in identifying stress, forecasting illnesses, and improving farm management. Numerous fields, including automated feeding, genetic improvement, environmental monitoring, and precision livestock husbandry, use AI and ML to improve the welfare of animals. This study also addresses the obstacles and potential paths for AI adoption in livestock care, with a focus on data privacy, ethical issues, and the requirement for flexible AI solutions catered to various animal species. Keywords— Artificial Intelligence, Machine Learning, Livestock Welfare, Precision Livestock Farming, Deep Learning, Animal Behavior Analysis, Stress Detection.

Study on novel vaccines and adjuvants for rabbit infectious diseases

Epidemic diseases have seriously damaged the development of the global rabbit industry. Vaccination plays a vital role in improving the health and welfare of livestock and preventing animal-tohuman transmission, thereby constituting a major public health strategy. There is continued demand for effective and safe adjuvants capable of enhancing antigen-specific responses to a target pathogen of rabbits. Pathogens such as Rabbit Haemorrhagic Disease Virus type 2 (RHDV2), Pasteurella multocida and Eimeria sp. coccidia are lethal and highly contagious for rabbits worldwide. Scientists have been working on screening for immunogenic proteins and designing adjuvant systems for safer and more effective vaccines against these highly prevalent pathogens. With the rapid development of genetic engineering technology and biotechnology, recombinant vaccines, genetic engineering vector vaccines, nucleic acid vaccines and other new vaccines have gradually been developed. Novel adjuvants such as new oil adjuvants, herbal medicine adjuvants, cytokine adjuvants, nano-adjuvants and polysaccharide adjuvants have been applied in the new vaccines to enhance their immunogenicity of new vaccines. Researchers are committed to developing new vaccines with broad spectrum and high efficiency. This review will briefly overview the current research on vaccines and adjuvants against viral, bacterial and parasitic pathogens prevalent in rabbits.

Microbiome and metabolomic changes in rabbits induced by Folium sennae.

Diarrhea is a serious health concern in livestock, affecting productivity and animal welfare. However, it remains a significant threat. Various practical therapies are being explored, such as prebiotics, probiotics, and organic acids, as well as chemical treatments including antibiotics, to combat this disorder. This study aims to explore the microbiome and metabolomic changes in rabbits with diarrhea. In the present study, diarrhea was induced in rabbits via oral gavage of Folium Sennae (FSAE), to assess body weights, diarrhea index, serum biochemical indicators, histopathology, microbiota, and metabolomics changes. Our study provides new insights into the mechanism of FSAE-induced diarrhea in rabbits and offers a novel mechanism for the interaction between gut microbiota, metabolomics, and gastrointestinal (GIT) dysfunction. Our results revealed that rabbits receiving FSAE showed a markedly higher diarrhea index and reduced body weight. Notably, levels of somatostatin, substance P, cholecystokinin, 5-hydroxytryptamine, vasoactive intestinal peptide, and acetylcholinesterase were significantly increased compared to control (P < 0.01). However, the levels of gastrin, motilin, enkephalin, and β-Endorphins were significantly decreased (P < 0.01). Microbial analysis revealed a significant reduction in microbial diversity (Shannon, Simpson, ACE, and chao1) and a decrease in Firmicutes, Campilobacterota, and Proteobacteria populations in FSAE-exposed rabbits. Additionally, 13 key metabolites associated with taurine and hypotaurine metabolism, alanine, aspartate and glutamate metabolism, starch and sucrose metabolism, histidine metabolism, and citrate cycle were identified in the colonic tissues. The present study concludes that FSAE-induced diarrhea in rabbits is associated with significant histopathological alterations in the colon, dysregulation of serum biochemical markers, and dysbiosis in metabolomics and gut microbiota. Our findings offer a novel model for investigating GIT dysfunction and its potential treatments.

Application of Needle-Free Vaccination in Piglets

Abstract One of the most common barriers we see in human medicine is a fear of needles, and this is mainly related to the experience of pain. Needles are routinely used in livestock production as the main route to deliver vaccines and consideration should be made towards the pain induced to livestock. Livestock production is essential to meet the growing increase of the human population with pork being the second most consumed meat product globally. The importance of disease prevention has been stated, however, the welfare of livestock is at the forefront for consumers and stakeholders. Research to enhance and promote positive welfare practices is crucial to improve animal health and welfare. Currently, vaccination is associated with stress and pain for piglets and is an area that needs addressing to reach welfare goals. This case study will refer to a recently published study comparing piglets vaccinated either intramuscularly or intradermally via a needle-free device. Physical parameters and behavioural responses were measured as indicators of welfare. This case study demonstrated no negative response from piglets vaccinated using a needle-free device and an opportunity to improve piglet welfare. Information © The Author 2025

The potential of silvopasture in the mid-atlantic USA: insights from land managers on motivations, challenges, and production features

Silvopasture is an intentional integration of trees, livestock, and forages within a common land management unit. Despite the significant potential opportunity, silvopasture is not widely adopted by landowners in the mid-Atlantic U.S.A. Limited information exists on silvopasture establishment and its overall management in a real farming context. These case studies were conducted to observe and document various establishment and management approaches for silvopasture among early adopters in Virginia to provide practical information to other producers interested in developing these systems. A questionnaire was developed and four producers in different physiographic regions of Virginia were interviewed. All the producers interviewed manage beef cattle operations. A common motivation behind silvopasture adoption was the opportunity to utilize the shade within the system for livestock health and welfare benefits. In cases where silvopastures were thinned from existing timber stands, the ability to expand grazable land was also a strong motivator. Producers utilized different methods for establishing and managing silvopasture based on their available resources and expertise. Climate change was not a consideration for any producers interviewed in their decision to create or manage silvopasture on their farm. Limited access to information and resources on silvopasture during the early adoption stage was a common experience for all interviewees. Each participant felt that silvopasture has great aesthetic value and can increase biodiversity within the farm. All producers interviewed were interested in expanding the silvopasture land area on their farm but also described various constraints that may hinder their ability to do so.

A review of behavioral testing in decapod shrimp (Caridea) and prawns (Dendrobranchiata) with applications for welfare assessment in aquaculture.

Evolving societal expectations are driving increasing interest in the welfare of decapod crustaceans, such as prawns and shrimp, grown in aquaculture. A key aspect of understanding an animal's welfare-related needs is through assessing their behavior to determine how the animal is perceiving and interacting with their environment. Behavioral testing has been applied to livestock animals for decades, providing insight into their wants and needs to guide housing structure design and husbandry practices that improve their welfare. This review collated studies that have applied behavioral testing, primarily at the individual level, to decapod shrimp and prawns in the Dendrobranchiata and Caridea sub- and infra-orders respectively. This review aims to understand the types of assessments that can be successfully applied to these taxa, and what the results of testing may be able to inform us about in regard to the welfare of these species. While the sentience capabilities of these decapod taxa is still under debate, the behavioral testing applied to date across varying species demonstrates they exhibit preferences across multiple contexts, individual differences indicative of personality, cognitive capabilities, and behavioral indicators consistent with negative affective states. There is scope to learn from livestock welfare assessment using behavioral testing and increase the research focused on penaeid shrimp and prawn species of aquaculture interest. Application and validation of new behavioral tests can guide system optimization for aquaculture shrimp and prawns in relation to the welfare of the animals.

Investigating the potential of geothermal heat pump and precision air supply system for heat stress abatement in dairy cattle barns.

Investigating the potential of geothermal heat pump and precision air supply system for heat stress abatement in dairy cattle barns.

A framework for handling uncertainty in a large-scale programme estimating the Global Burden of Animal Diseases.

Livestock provide nutritional and socio-economic security for marginalized populations in low and middle-income countries. Poorly-informed decisions impact livestock husbandry outcomes, leading to poverty from livestock disease, with repercussions on human health and well-being. The Global Burden of Animal Diseases (GBADs) programme is working to understand the impacts of livestock disease upon human livelihoods and livestock health and welfare. This information can then be used by policy makers operating regionally, nationally and making global decisions. The burden of animal disease crosses many scales and estimating it is a complex task, with extensive requirements for data and subsequent data synthesis. Some of the information that livestock decision-makers require is represented by quantitative estimates derived from field data and models. Model outputs contain uncertainty, arising from many sources such as data quality and availability, or the user's understanding of models and production systems. Uncertainty in estimates needs to be recognized, accommodated, and accurately reported. This enables robust understanding of synthesized estimates, and associated uncertainty, providing rigor around values that will inform livestock management decision-making. Approaches to handling uncertainty in models and their outputs receive scant attention in animal health economics literature; indeed, uncertainty is sometimes perceived as an analytical weakness. However, knowledge of uncertainty is as important as generating point estimates. Motivated by the context of GBADs, this paper describes an analytical framework for handling uncertainty, emphasizing uncertainty management, and reporting to stakeholders and policy makers. This framework describes a hierarchy of evidence, guiding movement from worst to best-case sources of information, and suggests a stepwise approach to handling uncertainty in estimating the global burden of animal disease. The framework describes the following pillars: background preparation; models as simple as possible but no simpler; assumptions documented; data source quality ranked; commitment to moving up the evidence hierarchy; documentation and justification of modelling approaches, data, data flows and sources of modelling uncertainty; uncertainty and sensitivity analysis on model outputs; documentation and justification of approaches to handling uncertainty; an iterative, up-to-date process of modelling; accounting for accuracy of model inputs; communication of confidence in model outputs; and peer-review.

IMPACTS OF CLIMATE CHANGE ON LIVESTOCK HEALTH AND WELFARE IN NIGERIA'S NORTH-EAST REGION

This paper studies the influence of climate change on health and welfare in Nigerian North-East livestock, covering direct and indirect impacts. An increased temperature, changing patterns of precipitation, and an increased humidity culminate into heat stress affecting the physiology, behaviour, and productivity of the livestock.Long-term exposure to extreme heat reduces feed intake, reproductive performance, and immune function due to metabolic disorders, oxidative stress, and increased vulnerability to diseases. Besides, climatic changes favored the dissemination of vector-borne diseases, such as trypanosomiasis and Rift Valley fever, further compromising the health status of livestock and creating zoonotic risks in humans.It also cites nutritional problems caused by higher fungal proliferation caused by climate and leading to mycotoxicoses in feeds. Such changes add pressure on the livelihoods of those depending on the livestock, especially small-scale farmers, who incur enhanced veterinary costs and mortality hence reducing food security.The impact is deep at the socio-economic level, as livestock farming is one of the most important sources of income and sustenance in the region. Thus, the paper calls for a multidimensional adaptive approach through improvements in the management of livestock, nutritional interventions, vector control, and disease surveillance systems to mitigate such challenges. This therefore further underlines the importance of policy development and community involvement in creating resilience and thus assuring a sustainable livestock farming system in the face of a changing climate. It is expected that these findings will inform policy, researchers, and other stakeholders on how to build adaptive capacity within the livestock sector in order to secure livelihoods and improve food security in Northeast Nigeria.

Measuring on-farm welfare in rabbits: a review with emphasis on animal-based indicators

Based on current definitions, animal welfare has to be linked to a life worth living, as perceived by animals, thanks to positive experiences rather than to the mere absence of negative ones. The measure of on-farm welfare of livestock is crucial to improve farming systems, identify critical points and compare different farming systems in view of welfare labelling protocols. To this end, species-specific protocols are necessary, which should use different types of indicators, i.e. resources-based indicators, management-based indicators and, especially, animal-based indicators. These indicators should work under different farming systems and for different animal categories and can be used to assess welfare in the short term or during the productive life of the animal. Last but not least, indicators should be able to measure the affective state of animals in terms of positive emotions. In this scenario, rabbits are quite unique, as little information is available about i) their behavioural needs under farming conditions; ii) the degree of suffering associated with the behavioural restrictions that can occur under farming conditions; iii) the indicators to be used in the very different housing and management conditions in which rabbits can be farmed; and iv) the relationships between emotions and affective states of animals as well as the effect on resiliency of rabbits under different conditions. In this context, the present review is aimed at summarising the state of the art and designing a road map for assessing on-farm rabbit welfare based on the most recent knowledge and approaches with special emphasis on candidate animalbased indicators for measuring both negative and positive affective states of rabbits. The identification of positive welfare indicators is a big challenge, given the biological and behavioural characteristics of rabbits. Accordingly, a comprehensive and robust assessment of rabbit welfare on farms cannot do without structure- and management-based indicators, which should be included in validated and standardised protocols using a multi-indicator approach.

PROGRESS IN DIGITAL TECHNOLOGIES FOR LIVESTOCK EXTERIOR AND FATNESS

The use of digital technologies in livestock management has revolutionized the assessment of body condition and fatness. Traditional methods, while widely used, face limitations related to time, accuracy, and stress on animals. This review provides a comprehensive overview of the most recent advancements in technologies such as LiDAR, machine learning, artificial intelligence, and 3D visualization systems, which are transforming the field. These technologies enable the non-invasive, accurate, and efficient collection of data, improving livestock productivity, welfare, and management strategies. Additionally, complementary tools like thermal imaging and ultrasound offer further improvements in data collection and analysis. The findings highlight the potential of these digital solutions to optimize livestock management practices, enhance decision-making, and contribute to sustainable and ethical livestock farming.

Predictive analytics of cattle behavior using machine learning techniques: A case study

Livestock management is a critical aspect of agricultural sustainability and food security. Today, there is a pressing need for advanced tools in cattle behavior analysis to improve livestock welfare and productivity. We aimed to enhance cattle behavior classification by using accelerometers fitted in wearable collars. Deep learning techniques were employed to classify behavioral patterns in cattle such as feeding, moving, and lying. Ultimately, our study sought to improve livestock management practices, including the monitoring of health and overall well-being. The study was conducted in a local barn, where cattle were outfitted with specially designed collars with accelerometer sensors. These sensors recorded intricate movements, facilitating the collection of comprehensive behavioral data. Deep learning algorithms were used to process and analyze the accelerometer data, enabling precise classification of various behaviors exhibited by the cattle. Our results showed the effectiveness of AI-driven classification techniques in distinguishing cattle behaviors with a high degree of accuracy. Our findings underscore the potential of deep learning techniques in optimizing livestock management practices. This research significantly advances livestock management by offering a simple continuous monitoring solution for cattle behavior. Deep learning techniques not only enhance our understanding of cattle behavior but also pave the way for intelligent systems that empower farmers to make informed decisions. By promoting healthier and more productive livestock, this research contributes to the broader goal of enhancing global food security and sustainability in the livestock industry.

EFFECT OF AFLATOXIN EXPOSURE IN LIVESTOCK AND PUBLIC HEALTH: REVIEW

Aflatoxins are toxic metabolites produced by the fungi Aspergillus parasiticus and Aspergillus flavus, which commonly infest various nutritious foods and animal feed. Given the widespread occurrence of aflatoxins and their significant impact on livestock and public health, understanding the mechanisms of toxicity, routes of exposure and economic implications is crucial. This review aims to investigate the causes and effects of aflatoxin exposure on both human and animal health while proposing strategies for preventing and controlling contamination. Aflatoxin contamination impacts the entire food chain, affecting the production, storage, processing, trade and consumption of both plant and animal products. Its consequences extend to human health, livestock welfare, agricultural productivity, environmental integrity and trade, particularly in regions with inadequate aflatoxin control measures. Aflatoxicosis can result in acute mortality, cancer, immune suppression and other chronic health issues. Effective control measures include pre-harvest interventions, careful management during harvest and post-harvest decontamination. Strategies such as selecting resistant crop varieties, employing biological decontamination using microorganisms, physically removing contaminated materials and chemically inactivating aflatoxins are crucial for prevention. Regulating aflatoxin levels in food and feed is essential for protecting public health and promoting equitable trade, necessitating the establishment and enforcement of maximum allowable limits.

Melatonin as a multifunctional modulator: emerging insights into its role in health, reproductive efficiency, and productive performance in livestock.

Melatonin, a pleiotropic hormone plays a vital role in enhancing livestock performance not only by regulating circadian rhythms but also by exhibiting antioxidant, immunomodulatory, and metabolic regulatory effects that collectively improve resilience, fertility, and productivity. Melatonin's synthesis is predominantly influenced by light exposure, with increased production in darkness; however, factors such as diet and health status further modulate its levels. By helping animals adapt to environmental stressors, melatonin boosts immune responses, mitigates chronic illnesses, and optimizes production efficiency. Its regulatory influence extends to the hypothalamic-pituitary-gonadal (HPG) axis, enhancing hormone secretion, synchronizing estrous cycles, and improving embryo viability. This results in improved reproductive outcomes through the protection of gametes, increased sperm motility, and enhanced oocyte quality, all of which benefit the fertilization process. Additionally, melatonin positively impacts productive performance, promoting muscle growth, development, and optimizing milk yield and composition through its interaction with metabolic and endocrine systems. As ongoing research continues to uncover its broader physiological effects, melatonin supplementation emerges as a promising approach to improving livestock welfare, productivity, and sustainability in modern animal husbandry.

Validating Ultra-Wideband Positioning System for Precision Cow Tracking in a Commercial Free-Stall Barn.

UWB positioning systems offer innovative solutions for precision monitoring dairy cow behaviour and social dynamics, yet their performance in complex commercial barn environments requires thorough validation. This study evaluated the TrackLab 2.13 (Noldus) UWB system in a dairy barn housing 44-49 cows. We assessed stationary tag positioning using ten fixed tags over seven days, proximity detection between eight cows and ten stationary tags, and moving tag positioning using three tags on a stick to simulate cow movement. System performance varied by tag location, with reliability ranging from 4.09% to 96.73% and an overall mean accuracy of 0.126 ± 0.278 m for stationary tags. After the provider updated the software, only 0.62% of measures exceeded the declared accuracy of 0.30 m. Proximity detection between moving cows and stationary tags showed 81.42% accuracy within a 2-m range. While generally meeting specifications, spatial variations in accuracy and reliability were observed, particularly near barn perimeters. These findings highlight UWB technology's potential for precision livestock farming, welfare assessment, and behaviour research, including social interactions and space use patterns. Results emphasise the need for careful system setup, regular updates, and context-aware data interpretation in commercial settings to maximise benefits in animal welfare monitoring.

It’s not Merely a Struggle, the Way We Live, it’s Wonderful, too! The Changing Life and Role of Women Herders in the Last 120 Years in Hungary

Women have always played a significant role in herding in Hungary, although their tasks and recognition have changed substantially over time. Nowadays, the vital role of women is becoming increasingly visible and recognised in Hungary. In this paper, members of the Hungarian Women Herders group and three researchers reviewed the scattered ethnographic, autobiographical and other literature, and conducted interviews with five active and retired women herders as well as with the husbands of three of them, and documented the role of women from the beginning of the twentieth century to the present day. Women have long played a fundamental role in holding the family together, providing food, and raising children. As in the past, women herders take part in milk processing and raising the lambs, but several also herd and even shear. After the 1989 revolution, many herders started herding privately again, and some women who had not been born into farming families chose livestock grazing as a profession. More recently, women in herding families have increasingly been responsible for handling the paperwork required for livestock welfare accountability, marketing and other differentiated needs requiring patience and computer skills. In 2021 the “Hungarian Women Herders” group was established, which currently has over 60 members. The group was founded with the aim of self-help and knowledge sharing, but they also participate in festivals, events and international conferences, and they are in contact with the association of Spanish women herders. Pastoral animal husbandry has not become obsolete in the face of industrial food systems. As its knowledge-intensive practices make use of spatially and temporally variable vegetation, it is becoming recognized as a more ecological alternative. It is necessary to recognize women herders’ important contribution to building a more sustainable common future, as their activities and knowledge are integral to this type of livestock production system. Moving forward, women must be included in initiatives to support pastoralism—whether it is the collection of best practices for other farmers and the coming generations to learn from, or the development of locally-based innovations, rooted in tradition while looking to the future.

Penilaian Implementasi GDFP (&lt;i&gt;Good Diary Farming Practice&lt;/i&gt;) Pada Peternakan Rakyat Di Kecamatan Ngancar, Kabupaten Kediri, Jawa Timur

Good dairy farming practice is a guideline used by smallholder farmers and companies in carrying out good dairy farming agribusiness and meeting standards so that cow productivity is maintained and milk is protected from health threats. This research took place in Ngancar District, Kediri Regency with 30 dairy farmers as respondents. The survey method is the method used in this research by collecting data using questionnaires, interviews and direct observation in the cage. The questionnaire contains questions from six aspects, namely livestock health, milking hygiene, nutrition, livestock welfare, environment and socio-economic management. The grouping of breeders based on livestock ownership is divided into 3 strata. Data analysis in this research is descriptive with a comparison of quantitative and qualitative aspects of GDFP. The results of the assessment of GDFP implementation in Ngancar District in the three breeder strata received good scores (3.28; 3.32; and 3.44). The implementation of GDFP has a high value in all strata in the milking hygiene aspect and a low value in the socio-economic management aspect of strata 1 (2.84). Increased attention to aspects of socio-economic management on smallholder farms is expected to contribute to increased implementation of GDFP