Artificial intelligence and porcine breeding.

IF 2.2 2区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE
Francisco A García-Vázquez
{"title":"Artificial intelligence and porcine breeding.","authors":"Francisco A García-Vázquez","doi":"10.1016/j.anireprosci.2024.107538","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":7880,"journal":{"name":"Animal Reproduction Science","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Animal Reproduction Science","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1016/j.anireprosci.2024.107538","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, DAIRY & ANIMAL SCIENCE","Score":null,"Total":0}
引用次数: 0

Abstract

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.

人工智能与猪育种
家畜管理正在进入一个新时代,其特点是从传统饲养方法以及传感器、自动监控系统和高级分析等新技术中收集的大量数据(大数据)进行分析。人工智能(A-In)是指机器模仿人类智能的能力,包括机器学习和深度学习等子领域,它在这场变革中发挥着举足轻重的作用。各种 A-In 技术已成功应用于各种工业和科学领域,现在正被纳入主流畜牧业管理实践中。就养猪业而言,虽然传统方法取得了相当大的成功,但由于信息量不断增加,需要采用 A-In 等新技术来提高生产率、改善动物福利并减少对环境的影响。目前的研究结果表明,这些技术有可能达到或超过传统方法的性能,通常在育种行业的效率和可持续性方面更具可扩展性。本综述从母猪(包括福利和繁殖管理)和公猪(包括精液质量和健康)的角度深入分析了A-In在猪育种中的应用,并探讨了已在其他物种中应用的新方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Animal Reproduction Science
Animal Reproduction Science 农林科学-奶制品与动物科学
CiteScore
4.50
自引率
9.10%
发文量
136
审稿时长
54 days
期刊介绍: Animal Reproduction Science publishes results from studies relating to reproduction and fertility in animals. This includes both fundamental research and applied studies, including management practices that increase our understanding of the biology and manipulation of reproduction. Manuscripts should go into depth in the mechanisms involved in the research reported, rather than a give a mere description of findings. The focus is on animals that are useful to humans including food- and fibre-producing; companion/recreational; captive; and endangered species including zoo animals, but excluding laboratory animals unless the results of the study provide new information that impacts the basic understanding of the biology or manipulation of reproduction. The journal''s scope includes the study of reproductive physiology and endocrinology, reproductive cycles, natural and artificial control of reproduction, preservation and use of gametes and embryos, pregnancy and parturition, infertility and sterility, diagnostic and therapeutic techniques. The Editorial Board of Animal Reproduction Science has decided not to publish papers in which there is an exclusive examination of the in vitro development of oocytes and embryos; however, there will be consideration of papers that include in vitro studies where the source of the oocytes and/or development of the embryos beyond the blastocyst stage is part of the experimental design.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信