Awards issued prior to january 20, 2025, were funded under previous administrations and may not reflect the priorities and policies of the current administration.** animal welfare directly impacts the…

Awards issued prior to january 20, 2025, were funded under previous administrations and may not reflect the priorities and policies of the current administration.** animal welfare directly impacts the economic return, environmental efficiency, and consumers acceptability of animal products. As animal welfare is a multifaceted concept, there is a clear need to identify and integrate quantifiable measurements of physical, behavioral, emotional and physiological aspects to accurately predict future welfare status. This multidisciplinary proposal aims to integrate large-scale datasets generated in precision dairy and PIG farms with multiomic datasets through machine learning methods to optimize management practices and genomic selection for improved animal welfare and resilience. Our specific objectives are to: 1) evaluate computational and statistical algorithms and develop tools to process high-throughput datasets and derive novel indicators and predictors of animal welfare; 2) perform data mining analyses to identify novel indicators of animal welfare based on a multitude of high-throughput datasets collected in precision farms; and, 3) integrate multiple phenotypic and multiomic variables to accurately predict animal welfare status and the genetic merit of breeding animals. For a broader applicability of our findings and greater representability, we will focus on different welfare issues in pigs and dairy cattle: heat stress, pre-weaning mortality, and overall resilience; and temperament in automated milking systems (milking robots). Various datasets and stakeholders support are available for the research and the proposal aligns well with the USDA strategic goals and dsfas program area priorities. Altogether, we will recommend best practices, build the methods and tools to process and integrate large-scale datasets, and generate innovative and trustworthy strategies for management and genomic-enhanced breeding for improve welfare and resilience in livestock.