Journal of Animal Science and Technology (JAST) is a peer-reviewed, open access journal publishing original research, review articles and notes in all fields of animal science. Topics covered by the journal include: genetics and breeding, physiology, nutrition of monogastric animals, nutrition of ruminants, animal products (milk, meat, eggs and their by-products) and their processing, grasslands and roughages, livestock environment, animal biotechnology, animal behavior and welfare.

Journal of Animal Science and Technology (JAST) is a peer-reviewed, open access journal publishing original research, review articles and notes in all fields of animal science. Topics covered by the journal include: genetics and breeding, physiology, nutrition of monogastric animals, nutrition of ruminants, animal products (milk, meat, eggs and their by-products) and their processing, grasslands and roughages, livestock environment, animal biotechnology, animal behavior and welfare.

Journal of Animal Science and Technology (JAST) is a peer-reviewed, open access journal publishing original research, review articles and notes in all fields of animal science. Topics covered by the journal include: genetics and breeding, physiology, nutrition of monogastric animals, nutrition of ruminants, animal products (milk, meat, eggs and their by-products) and their processing, grasslands and roughages, livestock environment, animal biotechnology, animal behavior and welfare.

Background: The study evaluated the effects of bacteriophage cocktail (BP) and ZnO administered during weaning time for piglets exposed to a non-sanitary environment. The bacteriophages were designed to eliminate Escherichia coli (K88, K99 and F41), Salmonella (typhimurium and enteritidis), and Clostridium perfreingens (types A and C). Forty 21-day-old crossbreed piglets were assigned to four treatments, including the PC (sanitary environment), NC (non-sanitary environment), BP (NC plus 10⁸ pfu/kg BP), and ZO (NC plus 2,500 mg/kg ZnO). Piglets in the NC, BP and ZO were kept in a non-sanitary environment for 14 d, which was contaminated with the feces of infected pigs. Results: Pigs in the BP and ZO treatments had a higher final body weight compared with the NC. The NC treatment showed the highest concentration of inflammatory cytokines including interleukin (IL)-1β, IL-6 and tumor necrosis factor-α in the plasma. The administration of BP and ZO showed lower myeloperoxidase concentrations compared with the NC. The NC treatment showed a lower concentration of superoxide dismutase in serum compared with the PC. Among the treatments in non-sanitary environment, the NC treatment showed a higher concentration of malondialdehyde compared with the ZO. The PC treatment showed a lower concentration of butyric acid in the feces compared with the BP treatment. Among non-sanitary treatments, the villus height in the duodenum was greater in the BP and ZO compared with the NC. The lower abundance of Proteobacteria phylum was observed in the BP and PC treatments compared with the NC. The highest relative abundance of Eubacterium was recorded in the BP treatment. The abundance of Megasphaera and Schwartzia was higher in the NC pigs compared with the BP piglets. The abundance of Desulfovibrio was lower in the supplemented treatments (BP and ZO) compared with non-supplemented (NC and PC). The abundance of Cellulosilyticum genera was higher in the BP and ZO treatments rather than in the NC. The piglets in the NC treatment had the highest abundance of Escherichia-Shigella, followed by the PC and ZO treatments. Conclusion: In conclusion, these results suggest that the supplementation of bacteriophage cocktail could effectively control Proteobacteria phylum, Clostridium spp. and coliforms population and mitigated the adverse influences of weaning stress in piglets.

Effective livestock management has become essential owing to an aging workforce and the growth of large-scale farming operations in the agricultural industry. Conventional monitoring methods, primarily reliant on manual observation, are increasingly reaching their limits, necessitating the development of innovative automated solutions. This study developed a system, termed mixed-ELAN, for real-time sow and piglet behavior detection using an extended ELAN architecture with diverse kernel sizes. The standard convolution operations within the ELAN framework were replaced with MixConv using diverse kernel sizes to enhance feature learning capabilities. To ensure high reliability, a performance evaluation of all techniques was conducted using a k-fold cross-validation (k = 3). The proposed architecture was applied to YOLOv7 and YOLOv9, yielding improvements of 1.5% and 2%, with mean average precision scores of 0.805 and 0.796, respectively, compared with the original models. Both models demonstrated significant performance improvements in detecting behaviors critical for piglet growth and survival, such as crushing and lying down, highlighting the effectiveness of the proposed architecture. These advances highlight the potential of AI and computer vision in agriculture, as well as the system’s benefits for improving animal welfare and farm management efficiency. The proposed architecture enhances the real-time monitoring and understanding of livestock behavior, establishing improved benchmarks for smart farming technologies and enabling further innovation in livestock management.