Genomic evaluation of heat tolerance in pigs based on reaction norm models and computer vision

• Grant number: 25/02949-5
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: June 01, 2026
• End date: May 31, 2027
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
• Principal Investigator: Aline Silva Mello Cesar
• Grantee: Felipe André Oliveira Freitas
• Supervisor: Luiz Fernando Brito
• Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
• Institution abroad: Purdue University, United States
• Associated to the scholarship: 24/15502-6 - Genomic evaluation of heat tolerance in pigs based on reaction norm models and computer vision, BP.DR

Abstract

Heat stress is a critical challenge for the global swine industry, significantly impacting animal welfare, production efficiency, and reproductive performance. In addition to considerable economic losses, factors such as territorial extension and climate change accentuate the complexity of the study of heat stress in pigs, which highlights the need for approaches that incorporate aspects of resilience to heat stress along with production traits, often used in genetic selection indexes. Thus, our goal is to identify indicator traits of heat tolerance in pigs that can be incorporated into selection programs, aiming to increase climatic resilience without compromising performance traits, such as growth and reproduction. For this purpose, data provided by the PIC company (Genus Company, Hendersonville, TN, USA) will be used, including genomic information and phenotypic records of >30,000 animals, and climate data obtained from the Project for Forecasting World Energy Resources (POWER) of NASA's Langley Research Center (LaRC), based on the location of the farms. The data will be analyzed through reaction norm models exploring the genotype-environment interaction and behavioral aspects of pigs under hot conditions. Eating behavior patterns will be evaluated and correlated with heat tolerance using computer vision models, seeking to identify behavioral indicators of resilience. We expect to identify characteristics of resilience to heat stress, which can be incorporated into genetic improvement strategies that integrate climatic resilience with other performance traits, contributing in a practical way to the sustainability of swine production in scenarios with different climatic patterns.