Franck Morais de Oliveira, Gabriel Araújo E Silva Ferraz, Ana Luíza Guimarães André, Lucas Santos Santana, Tomas Norton, Patrícia Ferreira Ponciano Ferraz
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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.</p>","PeriodicalId":7955,"journal":{"name":"Animals","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11201094/pdf/","citationCount":"0","resultStr":"{\"title\":\"Digital and Precision Technologies in Dairy Cattle Farming: A Bibliometric Analysis.\",\"authors\":\"Franck Morais de Oliveira, Gabriel Araújo E Silva Ferraz, Ana Luíza Guimarães André, Lucas Santos Santana, Tomas Norton, Patrícia Ferreira Ponciano Ferraz\",\"doi\":\"10.3390/ani14121832\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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. 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Digital and Precision Technologies in Dairy Cattle Farming: A Bibliometric Analysis.
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.
AnimalsAgricultural and Biological Sciences-Animal Science and Zoology
CiteScore
4.90
自引率
16.70%
发文量
3015
审稿时长
20.52 days
期刊介绍:
Animals (ISSN 2076-2615) is an international and interdisciplinary scholarly open access journal. It publishes original research articles, reviews, communications, and short notes that are relevant to any field of study that involves animals, including zoology, ethnozoology, animal science, animal ethics and animal welfare. However, preference will be given to those articles that provide an understanding of animals within a larger context (i.e., the animals'' interactions with the outside world, including humans). There is no restriction on the length of the papers. Our aim is to encourage scientists to publish their experimental and theoretical research in as much detail as possible. Full experimental details and/or method of study, must be provided for research articles. Articles submitted that involve subjecting animals to unnecessary pain or suffering will not be accepted, and all articles must be submitted with the necessary ethical approval (please refer to the Ethical Guidelines for more information).