Evaluation and modeling of responses of laying hens subjected to different illuminance levels

Abstract

The results of this thesis demonstrate impacts in several aspects. Technologically, two software applications were developed and registered with the Instituto Nacional da Propriedade Industrial (INPI – Brazilian National Institute of Industrial Property). These tools incorporate artificial intelligence to predict laying hens' physiological and productive responses, enabling more precise decision-making in environmental and productive management. These systems directly benefit producers and technicians by promoting cost reduction and resource efficiency. Economically, the validation of LED lighting indicates potential energy savings and operational cost reductions. These benefits contribute directly to the financial sustainability of both small and large-scale producers. Socially, the study reinforces ethical management practices and animal well-being. These practices align with market demands and animal welfare organizations while enhancing higher productivity without compromising animal comfort. This impact also extends to final consumers by increasing the availability of affordable and high-quality animal protein. Thus, the impacts span national and international territories, offering concrete contributions to environmental and productive sustainability, as well as influencing

industrial practices and public policies focused on sustainable development and animal well- being. Therefore, this study presents significant social, technological, and environmental

impacts, with strong potential to contribute to sustainable development in alignment with the United Nations Sustainable Development Goals (SDGs), particularly SDGs 2, 3, 9, 10, and 12.