<p>Poultry is the quickest-growing and expanding entry point for animal protein across the globe. But poultry production is not sustainable and cost-efficient, as it suffers from animal welfare issues and poor housing conditions. Moreover, excessive stocking density and bone health problems are other factors that harm efficiency at the poultry production level. The stress that results from keeping too many animals in an environment that cannot provide good living conditions causes harmful behaviors. It also increases the risk of disease. This includes lameness, breast blistering, trampling due to panic, and condemnation. Current research does not offer a system that combines housing design improvements, population density optimizations, and bone health solutions into a single prediction precision model. To fill this gap, we present the PhD concept. PHD integrates structural design with behavior and skeletal health prediction using AI and precision livestock farming (PLF) technologies. This review synthesizes the literature on the effects of population density, optimization of building design, behavioral response, skeletal health management, and AI-based monitoring tools in poultry. This review synthesizes evidence indicating strong associations between housing conditions, stocking density, stress-related behaviors, and skeletal health outcomes. The study also evidence suggests that an AI-based predictive system, when fed to farm animals, has the potential to detect welfare compromises that may support early intervention and disease prevention. The Precision Housing Dynamics (PHD) framework proposed in this study is intended to provide a systems-level decision-support architecture that may support the optimization of poultry welfare, skeletal health, and production performance. In addition, the framework aligns conceptually with broader sustainability objectives and emerging principles of ethical poultry production. The structural, behavioral, and physiological elements combined in PhD allow for data-based preemptive interventions that may help in the construction of poultry housing systems with a more welfare focus and dynamic population, as well as bone health prediction. The framework operates to promote worldwide food security by following SDG2 (Zero Hunger) standards, which establish fundamental conditions for developing sustainable and ethical poultry farming systems on a global scale.</p> Graphical Abstract <p></p>

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Precision housing dynamics in poultry: AI-driven predictive systems for welfare, behavior, and skeletal health

  • Getahun Belay Mekonnen

摘要

Poultry is the quickest-growing and expanding entry point for animal protein across the globe. But poultry production is not sustainable and cost-efficient, as it suffers from animal welfare issues and poor housing conditions. Moreover, excessive stocking density and bone health problems are other factors that harm efficiency at the poultry production level. The stress that results from keeping too many animals in an environment that cannot provide good living conditions causes harmful behaviors. It also increases the risk of disease. This includes lameness, breast blistering, trampling due to panic, and condemnation. Current research does not offer a system that combines housing design improvements, population density optimizations, and bone health solutions into a single prediction precision model. To fill this gap, we present the PhD concept. PHD integrates structural design with behavior and skeletal health prediction using AI and precision livestock farming (PLF) technologies. This review synthesizes the literature on the effects of population density, optimization of building design, behavioral response, skeletal health management, and AI-based monitoring tools in poultry. This review synthesizes evidence indicating strong associations between housing conditions, stocking density, stress-related behaviors, and skeletal health outcomes. The study also evidence suggests that an AI-based predictive system, when fed to farm animals, has the potential to detect welfare compromises that may support early intervention and disease prevention. The Precision Housing Dynamics (PHD) framework proposed in this study is intended to provide a systems-level decision-support architecture that may support the optimization of poultry welfare, skeletal health, and production performance. In addition, the framework aligns conceptually with broader sustainability objectives and emerging principles of ethical poultry production. The structural, behavioral, and physiological elements combined in PhD allow for data-based preemptive interventions that may help in the construction of poultry housing systems with a more welfare focus and dynamic population, as well as bone health prediction. The framework operates to promote worldwide food security by following SDG2 (Zero Hunger) standards, which establish fundamental conditions for developing sustainable and ethical poultry farming systems on a global scale.

Graphical Abstract