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Abstract：
The advancement of technology has significantly transformed the livestock landscape, particularly in the management of dairy cattle, through the incorporation of digital and precision approaches. This study presents a bibliometric analysis focused on these technologies involving dairy farming to explore and map the extent of research in the scientific literature. Through this review, it was possible to investigate academic production related to digital and precision livestock farming and identify emerging patterns, main research themes, and author collaborations. To carry out this investigation in the literature, the entire timeline was considered, finding works from 2008 to November 2023 in the scientific databases Scopus and Web of Science. Next, the Bibliometrix (version 4.1.3) package in R (version 4.3.1) and its Biblioshiny software extension (version 4.1.3) were used as a graphical interface, in addition to the VOSviewer (version 1.6.19) software, focusing on filtering and creating graphs and thematic maps to analyze the temporal evolution of 198 works identified and classified for this research. The results indicate that the main journals of interest for publications with identified affiliations are \"Computers and Electronics in Agriculture\" and \"Journal of Dairy Science\". It has been observed that the authors focus on emerging technologies such as machine learning, deep learning, and computer vision for behavioral monitoring, dairy cattle identification, and management of thermal stress in these animals. These technologies are crucial for making decisions that enhance health and efficiency in milk production, contributing to more sustainable practices. This work highlights the evolution of precision livestock farming and introduces the concept of digital livestock farming, demonstrating how the adoption of advanced digital tools can transform dairy herd management. Digital livestock farming not only boosts productivity but also redefines cattle management through technological innovations, emphasizing the significant impact of these trends on the sustainability and efficiency of dairy production.
摘要：
技术的进步极大地改变了牲畜的景观，特别是在奶牛管理方面，通过数字和精确方法的结合。本研究提供了针对涉及奶牛养殖的这些技术的文献计量分析，以探索和绘制科学文献中的研究范围。通过这次审查,有可能调查与数字和精准畜牧业相关的学术生产，并确定新兴模式，主要研究主题,和作者合作。为了在文献中进行这项调查，考虑了整个时间表，在科学数据库Scopus和WebofScience中查找2008年至2023年11月的作品。接下来,R（4.3.1版）中的Bibliometrix（4.1.3版）软件包及其Biblioshiny软件扩展（4.1.3版）用作图形界面，除了VOSviewer（版本1.6.19）软件，专注于过滤和创建图表和专题地图，以分析本研究确定和分类的198件作品的时间演变。结果表明，具有已确定隶属关系的出版物感兴趣的主要期刊是“农业中的计算机和电子产品”和“乳制品科学杂志”。据观察，作者专注于机器学习等新兴技术，深度学习,和用于行为监测的计算机视觉，奶牛鉴定,以及这些动物的热应激管理。这些技术对于制定提高牛奶生产健康和效率的决策至关重要。促进更可持续的做法。这项工作突出了精准畜牧业的演变，并介绍了数字畜牧业的概念，展示了采用先进的数字工具如何改变奶牛场管理。数字畜牧业不仅提高了生产力，还通过技术创新重新定义了牛的管理。强调这些趋势对乳制品生产的可持续性和效率的重大影响。
