大数据
生产力
持续性
分析
动物福利
数据科学
计算机科学
牲畜
人工智能
业务
生物技术
知识管理
风险分析(工程)
生物
生态学
经济
宏观经济学
操作系统
作者
Francisco Alberto García‐Vázquez
标识
DOI:10.1016/j.anireprosci.2024.107538
摘要
Livestock management is evolving into a new era, characterized by the analysis of vast quantities of data (big data) collected from both traditional breeding methods and new technologies such as sensors, automated monitoring system, and advanced analytics. Artificial intelligence (A-In), which refers to the capability of machines to mimic human intelligence, including subfields like machine learning and deep learning, is playing a pivotal role in this transformation. A wide array of A-In techniques, successfully employed in various industrial and scientific contexts, are now being integrated into mainstream livestock management practices. In the case of swine breeding, while traditional methods have yielded considerable success, the increasing amount of information requires the adoption of new technologies such as A-In to drive productivity, enhance animal welfare, and reduce environmental impact. Current findings suggest that these techniques have the potential to match or exceed the performance of traditional methods, often being more scalable in terms of efficiency and sustainability within the breeding industry. This review provides insights into the application of A-In in porcine breeding, from the perspectives of both sows (including welfare and reproductive management) and boars (including semen quality and health), and explores new approaches which are already being applied in other species.
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