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Objective: This study aimed to assess the knowledge, attitudes, and practices (KAP) of key stakeholders regarding African swine fever (ASF) and its reporting in Abuyog, Leyte, Philippines. It also aimed to identify sociodemographic factors associated with KAP levels. Materials and Methods: A cross-sectional survey was performed on 392 respondents, including pig farmers (n = 333), butchers (n = 38), live pig/meat sellers (n = 11), and Local Government Unit personnel (n = 10) between November 2023 and February 2024. KAP scores were calculated and categorized into \"poor\" and \"good\" using a median cutoff. Logistic regression analyses were conducted to investigate the association between sociodemographic variables and KAP levels. Results: Most participants showed poor knowledge of ASF causative agents, transmission, and clinical signs (83.93%) and disease recognition (60.20%), but many have good knowledge of ASF reporting protocols (70.92%). Attending ASF seminars/training was associated with improved basic ASF knowledge, disease recognition, and case reporting. Basic knowledge of ASF could enhance disease recognition. Disease recognition could then enhance ASF case reporting. Younger stakeholders showed better knowledge of basic ASF concepts. Pig farmers exhibited poor knowledge of disease recognition. Most participants showed good attitudes toward ASF reporting (97.7%), which was associated with overall knowledge of ASF. Most participants showed good practices in the early steps of case reporting (85.20%), relatively balanced reporting protocol (49.23%), and relatively poor knowledge-seeking behavior (45.41%). Pig farmers were less likely to report than other stakeholders. Good overall knowledge translates into good practices. Overall practices are influenced by the primary source of income. Conclusion: The findings reveal a notable gap in knowledge concerning ASF among participants, highlighting an essential need for enhanced educational initiatives. Strengthening basic ASF knowledge is vital, as it positively impacts disease recognition and, in turn, case reporting. Although there is a generally positive attitude toward ASF reporting, the lack of knowledge-seeking behavior and the variability in reporting practices based on income sources suggest a need for tailored educational programs.

Objective: This review examines Japan’s pig farming landscape, highlighting key barriers while exploring projects that foster large-scale sustainable development efforts by emphasizing precision technologies integration and policy implications. Materials and Methods: A literature review was conducted using keyword searches across Google Scholar, covering studies published between 2018 and 2024. The review encompassed studies on Japan’s pig farming, addressing prospects, production metrics, challenges, consumption patterns, market trends, precision technologies, and insights from peer-reviewed journals, credible websites, government reports, and conference proceedings. Results: Japan, one of Asia’s largest pork consumers, relies on imports, with domestic production covering only 47.08% of consumption, highlighting a need for greater efficiency. Although small-scale farms continue to dominate the pig industry, the sector is navigating a pivotal shift toward modernization and the expansion of large-scale operations. Farmers face mounting pressures from feed costs, labor shortages, diseases, and strict environmental regulations. Precision pig farming technologies address these by optimizing resource use, enabling early disease detection to reduce costs, improving herd health to promote better welfare, and managing manure to reduce emissions. Conclusion: Integrating large-scale operations with precision pig farming technologies can redefine Japanese pig farming, promoting animal welfare and environmental sustainability. The government must secure financial backing (partial or full subsidies) to support large-scale operations, tax reductions on imported tools, and grants to foster domestic tools and renewable energy innovations to achieve this. Future life-cycle assessment research will be essential for evaluating the long-term environmental impacts, ensuring viability, and promoting sustainability in Japan’s pork production sector.

The search for new sources of energy has intensified these days due to the environmental impacts caused by fossil fuels. The tripod composed of energy, food and water is the base of human existence. Food production implies the generation of organic waste and the need to manage it properly. The dairy and pig farming sectors have an essential role in the Brazilian economy, producing a large amount of waste. One energy and environmental alternative to treat this issue is anaerobic digestion. Here we aimed to optimize the production and composition of biogas obtained from cheese whey and swine manure. Batch-scale laboratory tests were performed on bench anaerobic digesters for 65 days with 6 triplicates loaded with different proportions of cheese whey and swine manure. The proportion of 50% cheese whey and 50% swine manure presented the highest biogas production and methane concentration (CH4).

Non-aureus staphylococci (NAS) are ubiquitous bacteria in livestock-associated environments where they may act as reservoirs of antimicrobial resistance (AMR) genes for pathogens such as Staphylococcus aureus. Here, we tested whether housing conditions in pig farms could influence the overall AMR-NAS burden. Two hundred and forty porcine commensal and environmental NAS isolates from three different farm types (conventional, alternative, and organic) were tested for phenotypic antimicrobial susceptibility and subjected to whole genome sequencing. Genomic data were analysed regarding species identity and AMR gene carriage. Seventeen different NAS species were identified across all farm types. In contrast to conventional farms, no AMR genes were detectable towards methicillin, aminoglycosides, and phenicols in organic farms. Additionally, AMR genes to macrolides and tetracycline were rare among NAS in organic farms, while such genes were common in conventional husbandries. No differences in AMR detection existed between farm types regarding fosfomycin, lincosamides, fusidic acid, and heavy metal resistance gene presence. The combined data show that husbandry conditions influence the occurrence of resistant and multidrug-resistant bacteria in livestock, suggesting that changing husbandry practices may be an appropriate means of limiting the spread of AMR bacteria on farms.

Pork accounts for an important proportion of livestock products. For pig farming, a lot of manpower, material resources and time are required to monitor pig health and welfare. As the number of pigs in farming increases, the continued use of traditional monitoring methods may cause stress and harm to pigs and farmers and affect pig health and welfare as well as farming economic output. In addition, the application of artificial intelligence has become a core part of smart pig farming. The precision pig farming system uses sensors such as cameras and radio frequency identification to monitor biometric information such as pig sound and pig behavior in real-time and convert them into key indicators of pig health and welfare. By analyzing the key indicators, problems in pig health and welfare can be detected early, and timely intervention and treatment can be provided, which helps to improve the production and economic efficiency of pig farming. This paper studies more than 150 papers on precision pig farming and summarizes and evaluates the application of artificial intelligence technologies to pig detection, tracking, behavior recognition and sound recognition. Finally, we summarize and discuss the opportunities and challenges of precision pig farming.

Pig instance segmentation is a critical component of smart pig farming, serving as the basis for advanced applications such as health monitoring and weight estimation. However, existing methods typically rely on large volumes of precisely labeled mask data, which are both difficult and costly to obtain, thereby limiting their scalability in real-world farming environments. To address this challenge, this paper proposes a novel approach that leverages simpler box annotations as supervisory information to train a pig instance segmentation network. In contrast to traditional methods, which depend on expensive mask annotations, our approach adopts a weakly supervised learning paradigm that reduces annotation cost. Specifically, we enhance the loss function of an existing weakly supervised instance segmentation model to better align with the requirements of pig instance segmentation. We conduct extensive experiments to compare the performance of the proposed method that only uses box annotations, with that of five fully supervised models requiring mask annotations and two weakly supervised baselines. Experimental results demonstrate that our method outperforms all existing weakly supervised approaches and three out of five fully supervised models. Moreover, compared with fully supervised methods, our approach exhibits only a 3% performance gap in mask prediction. Given that annotating a box takes merely 26 seconds, whereas annotating a mask requires 94 seconds, this minor accuracy trade-off is practically negligible. These findings highlight the value of employing box annotations for pig instance segmentation, offering a more cost-effective and scalable alternative without compromising performance. Our work not only advances the field of pig instance segmentation but also provides a viable pathway to deploy smart farming technologies in resource-limited settings, thereby contributing to more efficient and sustainable agricultural practices.

The spatial pattern and epidemiology of backyard pig farming and other low bio-security pig production systems and their role in the occurrence of classical swine fever (CSF) is described and evaluated. A spatial Bayesian model was used to explore the risk factors, including human demographics, socioeconomic and environmental factors. The analyses were performed for Bulgaria, which has a large number of backyard farms (96% of all pig farms in the country are classified as backyard farms), and it is one of the countries for which both backyard pig and farm counts were available. Results reveal that the high-risk areas are typically concentrated in areas with small family farms, high numbers of outgoing pig shipments and low levels of personal consumption (i.e. economically deprived areas). Identification of risk factors and high-risk areas for CSF will allow to targeting risk-based surveillance strategies leading to prevention, control and, ultimately, elimination of the disease in Bulgaria and other countries with similar socio-epidemiological conditions.

The perception of the importance of animal health and its relationship with biosecurity has increased in recent years with the emergence and re-emergence of several diseases difficult to control. This is particularly evident in the case of pig farming as shown by the recent episodes of African swine fever or porcine epidemic diarrhoea. Moreover, a better biosecurity may help to improve productivity and may contribute to reducing the use of antibiotics. Biosecurity can be defined as the application of measures aimed to reduce the probability of the introduction (external biosecurity) and further spread of pathogens within the farm (internal biosecurity). Thus, the key idea is to avoid transmission, either between farms or within the farm. This implies knowledge of the epidemiology of the diseases to be avoided that is not always available, but since ways of transmission of pathogens are limited to a few, it is possible to implement effective actions even with some gaps in our knowledge on a given disease. For the effective design of a biosecurity program, veterinarians must know how diseases are transmitted, the risks and their importance, which mitigation measures are thought to be more effective and how to evaluate the biosecurity and its improvements. This review provides a source of information on external and internal biosecurity measures that reduce risks in swine production and the relationship between these measures and the epidemiology of the main diseases, as well as a description of some systems available for risk analysis and the assessment of biosecurity. Also, it reviews the factors affecting the successful application of a biosecurity plan in a pig farm.

The development of intensive and large-scale livestock farming, such as pig husbandry, is significantly increasing the amount of manure globally. Mineral additives are commonly used in animal feed, and heavy metal(loid)s (HMs) are introduced to the feed via incomplete purification processes of those mineral additives, which leads to inevitable environmental pollution by HMs in conjunction with manure production. When these toxic-metal-containing manures are used as fertilizer, the HMs accumulate in soils and crops, which further causes potential risks to human health and the ecological environment. In this review, the focus is on seven HMs that are related to human activities or frequently contained in animal feed, including copper, zinc, cadmium, chromium, lead, mercury, and arsenic. The toxicities of these HMs and the elimination methods to reduce the HM toxicity of pig manure when it is added to soil, i.e., liquid–solid separation, adsorption, bioleaching, and composting, are summarized. The ultimate aim of this review is to outline the systematic pollution management strategies for HMs from pig farming.

Objective: The study aims to compare the economic and financial viability of expanding the pig farming activity carried out in the finishing system, on a rural property in the municipality of Xavantina/SC.   Search method: Methodologically, the research is descriptive, carried out through a case study and qualitative analysis. From the collection of data relating to batches from the period 2019 and 2020, a statement of the results of the pig farming activity was prepared. Discounted payback, Internal Rate of Return (IRR) and Net Present Value (NPV) were used for analysis.   Main results: Economic results demonstrate the net margin per batch of pigs of up to 64% in the current finishing system. With the increase in investments, the net margin is up to 44% per lot. The results show a financial return time of 10 years, 11 months and 8 days, with an IRR of 10.08% in the current situation. Considering the investments in expanding the new piggery and the revenue and expense projections, the financial return will occur in 18 years, 11 months and 8 days, with the IRR at 10.02%. In general, the results demonstrate the importance of rural accounting as a support instrument in monitoring activities developed to support the economic-financial analysis of investments and the decision-making process.