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Digital and Precision Technologies in Dairy Cattle Farming: A Bibliometric Analysis.
de Oliveira, Franck Morais; Ferraz, Gabriel Araújo E Silva; André, Ana Luíza Guimarães; Santana, Lucas Santos; Norton, Tomas; Ferraz, Patrícia Ferreira Ponciano.
Afiliación
  • de Oliveira FM; Department of Agricultural Engineering, School of Engineering, Federal University of Lavras (UFLA), Lavras 37200-900, Brazil.
  • Ferraz GAES; Department of Agricultural Engineering, School of Engineering, Federal University of Lavras (UFLA), Lavras 37200-900, Brazil.
  • André ALG; Department of Animal Science, Federal University of Lavras (UFLA), Lavras 37200-900, Brazil.
  • Santana LS; Department of Agricultural and Environmental Engineering (EEA), Institute of Agricultural Sciences (ICA), Federal University of Vales Jequitinhonha and Mucuri-Campus Unaí, Avenida Universitária, nº 1.000, B. Universitários, Unai 38610-000, Brazil.
  • Norton T; M3-BIORES-Measure, Model & Manage Bioresponses, KU Leuven, Kasteelpark Arenberg 30, B-3001 Leuven, Belgium.
  • Ferraz PFP; Department of Agricultural Engineering, School of Engineering, Federal University of Lavras (UFLA), Lavras 37200-900, Brazil.
Animals (Basel) ; 14(12)2024 Jun 20.
Article en En | MEDLINE | ID: mdl-38929450
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Animals (Basel) Año: 2024 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Animals (Basel) Año: 2024 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Suiza