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The world's growing population is highly dependent on animal agriculture. Animal products provide nutrient-packed meals that help to sustain individuals of all ages in communities across the globe. As the human demand for animal proteins grows, the agricultural industry must continue to advance its efficiency and quality of production. One of the most commonly farmed livestock is poultry and their significance is felt on a global scale. Current poultry farming practices result in the premature death and rejection of billions of chickens on an annual basis before they are processed for meat. This loss of life is concerning regarding animal welfare, agricultural efficiency, and economic impacts. The best way to prevent these losses is through the individualistic and/or group level assessment of animals on a continuous basis. On large-scale farms, such attention to detail was generally considered to be inaccurate and inefficient, but with the integration of artificial intelligence (AI)-assisted technology individualised, and per-herd assessments of livestock became possible and accurate. Various studies have shown that cameras linked with specialised systems of AI can properly analyse flocks for health concerns, thus improving the survival rate and product quality of farmed poultry. Building on recent advancements, this review explores the aspects of AI in the detection, counting, and tracking of poultry in commercial and research-based applications.
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http://dx.doi.org/10.3390/ani12030232 | DOI Listing |
BMC Vet Res
September 2025
Department of Poultry Production, Faculty of Agriculture, Fayoum University, Fayoum, 63514, Egypt.
This study investigated the impact of dietary zeolite supplementation on growth, cecal microbiota and digesta viscosity, digestive enzymes, carcass traits, blood constituents, and antioxidant parameters of broilers. A completely randomized design was used with 240 one-day-old broiler chicks randomly assigned to three dietary treatments (0%, 1.5%, and 3% zeolite as a feed additive) with four replicates of 20 chicks each.
View Article and Find Full Text PDFEcotoxicol Environ Saf
September 2025
Department of Veterinary Medicine, College of Coastal Agricultural Sciences, Guangdong Ocean University, Zhanjiang, Guangdong 524088, China; South China Branch of National Saline-Alkali Tolerant Rice Technology Innovation Center Zhanjiang, Guangdong 524088, China. Electronic address:
Aflatoxin B1 (AFB1)-induced hepatotoxicity is a common toxic disease in poultry farming. However, there is currently a lack of effective pharmaceutical interventions for treating AFB1. Astaxanthin (AST), a natural carotenoid, exhibits potent antioxidant and immune-enhancing properties.
View Article and Find Full Text PDFPLoS One
September 2025
School of Animal and Comparative Biomedical Sciences, College of Agriculture and Life Sciences, University of Arizona, Tucson, Arizona, United States of America.
The Gram-negative bacterium Campylobacter jejuni is part of the commensal gut microbiota of numerous animal species and a leading cause of bacterial foodborne illness in humans. Most complete genomes of C. jejuni are from strains isolated from human clinical, poultry, and ruminant samples.
View Article and Find Full Text PDFAvian Pathol
September 2025
Department of Animal Medicine, Production and Health (MAPS), University of Padua, Legnaro (PD), Italy.
Infectious bursal disease virus (IBDV) is a highly contagious, economically relevant immunosuppressive pathogen of chickens. Despite belonging to a single serotype, virulent IBDVs display a remarkable heterogeneity in genetic and functional features. Traditionally, strains are categorized into classical, variant and very virulent viruses, but many atypical IBDVs have been recently identified.
View Article and Find Full Text PDFInt J Gynaecol Obstet
September 2025
UCD Perinatal Research Center, School of Medicine, National Maternity Hospital, University College Dublin, Dublin, Ireland.
Objective: To identify potential nutritional risks for women using the FIGO Nutrition Checklist in relation to region, age and pregnancy/intention.
Methods: A retrospective analysis was conducted using 1515 responses from the online version of the FIGO Nutrition Checklist available on the FIGO website. Participants who responded "No" to at least one dietary question were classified as at potential nutritional risk.