Effects of Heat Stress on Poultry Production: Challenges and New Solutions Based on Artificial Intelligence

Background: Heat stress is considered one of the most destructive factors threatening health, welfare, and productivity in the poultry industry. As climate change intensifies, this challenge has grown and requires new, efficient management solutions. The physiological effects of heat stress, including reduced feed intake, impaired acid-base balance, weakened immune system, and reduced production performance, cause substantial economic losses to this industry. In this regard, artificial intelligence (AI) technology, capable of analyzing complex data and providing predictive solutions, has tremendous potential to transform the management of this problem. This systematic review examines the effects of heat stress on poultry and explains the strategic capabilities of AI in monitoring, predicting, and mitigating these effects. Methods: This study was conducted according to the PRISMA protocol and a systematic search of the Scopus, Web of Science, PubMed, and Google Scholar databases between January ۲۰۱۸ and December ۲۰۲۴. Keywords related to heat stress and AI were used. The screening, data extraction, and quality assessment of studies were conducted, and the findings were synthesized qualitatively. Results: The effects of heat stress on the physiology and performance of chickens have been demonstrated to fall into a broad variety of categories, according to a comprehensive assessment of ۱۶ studies. The use of sensors connected to the Internet of Things (IoT) and computer vision to monitor environmental (temperature, humidity) and behavioral (water diffusion, movement, breathing patterns) changes in birds, which serve as early indications of stress. Using machine learning models to analyze historical and real-time data in order to forecast the occurrence of heat waves and provide preventive warnings to poultry managers, as well as integrating AI with management systems (such as ventilation, misting, and feeding) in order to provide automated and optimized responses to stressful conditions and reduce reliance on human decision-making. Conclusion: AI is driving a paradigm shift in the treatment of heat stress in poultry, moving away from reactive approaches toward predictive and preventive ones.

کلیدواژه ها:

AI ، Machine learning ، Poultry heat stress ، Real-time monitoring ، Systematic review