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Precision Livestock Farming Research: A Global Scientometric Review

SIMPLE SUMMARY: In recent years, there has been a significant increase in research on precision livestock farming. The aim of this paper is to provide a comprehensive review of the current state of research on precision livestock farming. Using the visualization tool CiteSpace, this study creates kn...

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Autores principales: Jiang, Bing, Tang, Wenjie, Cui, Lihang, Deng, Xiaoshang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10340063/
https://www.ncbi.nlm.nih.gov/pubmed/37443894
http://dx.doi.org/10.3390/ani13132096
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author Jiang, Bing
Tang, Wenjie
Cui, Lihang
Deng, Xiaoshang
author_facet Jiang, Bing
Tang, Wenjie
Cui, Lihang
Deng, Xiaoshang
author_sort Jiang, Bing
collection PubMed
description SIMPLE SUMMARY: In recent years, there has been a significant increase in research on precision livestock farming. The aim of this paper is to provide a comprehensive review of the current state of research on precision livestock farming. Using the visualization tool CiteSpace, this study creates knowledge maps to display data on research countries, institutions, author collaborations, and keyword networks. Through these analyses, this study objectively reveals the dynamics, development process, and evolutionary trends of precision livestock farming research while identifying the frontiers and hotspots in the field. ABSTRACT: Precision livestock farming (PLF) utilises information technology to continuously monitor and manage livestock in real-time, which can improve individual animal health, welfare, productivity and the environmental impact of animal husbandry, contributing to the economic, social and environmental sustainability of livestock farming. PLF has emerged as a pivotal area of multidisciplinary interest. In order to clarify the knowledge evolution and hotspot replacement of PLF research, based on the relevant data from the Web of Science database from 1973 to 2023, this study analyzed the main characteristics, research cores and hot topics of PLF research via CiteSpace. The results point to a significant increase in studies on PLF, with countries having advanced livestock farming systems in Europe and America publishing frequently and collaborating closely across borders. Universities in various countries have been leading the research, with Daniel Berckmans serving as the academic leader. Research primarily focuses on animal science, veterinary science, computer science, agricultural engineering, and environmental science. Current research hotspots center around precision dairy and cattle technology, intelligent systems, and animal behavior, with deep learning, accelerometer, automatic milking systems, lameness, estrus detection, and electronic identification being the main research directions, and deep learning and machine learning represent the forefront of current research. Research hot topics mainly include social science in PLF, the environmental impact of PLF, information technology in PLF, and animal welfare in PLF. Future research in PLF should prioritize inter-institutional and inter-scholar communication and cooperation, integration of multidisciplinary and multimethod research approaches, and utilization of deep learning and machine learning. Furthermore, social science issues should be given due attention in PLF, and the integration of intelligent technologies in animal management should be strengthened, with a focus on animal welfare and the environmental impact of animal husbandry, to promote its sustainable development.
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spelling pubmed-103400632023-07-14 Precision Livestock Farming Research: A Global Scientometric Review Jiang, Bing Tang, Wenjie Cui, Lihang Deng, Xiaoshang Animals (Basel) Review SIMPLE SUMMARY: In recent years, there has been a significant increase in research on precision livestock farming. The aim of this paper is to provide a comprehensive review of the current state of research on precision livestock farming. Using the visualization tool CiteSpace, this study creates knowledge maps to display data on research countries, institutions, author collaborations, and keyword networks. Through these analyses, this study objectively reveals the dynamics, development process, and evolutionary trends of precision livestock farming research while identifying the frontiers and hotspots in the field. ABSTRACT: Precision livestock farming (PLF) utilises information technology to continuously monitor and manage livestock in real-time, which can improve individual animal health, welfare, productivity and the environmental impact of animal husbandry, contributing to the economic, social and environmental sustainability of livestock farming. PLF has emerged as a pivotal area of multidisciplinary interest. In order to clarify the knowledge evolution and hotspot replacement of PLF research, based on the relevant data from the Web of Science database from 1973 to 2023, this study analyzed the main characteristics, research cores and hot topics of PLF research via CiteSpace. The results point to a significant increase in studies on PLF, with countries having advanced livestock farming systems in Europe and America publishing frequently and collaborating closely across borders. Universities in various countries have been leading the research, with Daniel Berckmans serving as the academic leader. Research primarily focuses on animal science, veterinary science, computer science, agricultural engineering, and environmental science. Current research hotspots center around precision dairy and cattle technology, intelligent systems, and animal behavior, with deep learning, accelerometer, automatic milking systems, lameness, estrus detection, and electronic identification being the main research directions, and deep learning and machine learning represent the forefront of current research. Research hot topics mainly include social science in PLF, the environmental impact of PLF, information technology in PLF, and animal welfare in PLF. Future research in PLF should prioritize inter-institutional and inter-scholar communication and cooperation, integration of multidisciplinary and multimethod research approaches, and utilization of deep learning and machine learning. Furthermore, social science issues should be given due attention in PLF, and the integration of intelligent technologies in animal management should be strengthened, with a focus on animal welfare and the environmental impact of animal husbandry, to promote its sustainable development. MDPI 2023-06-24 /pmc/articles/PMC10340063/ /pubmed/37443894 http://dx.doi.org/10.3390/ani13132096 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Jiang, Bing
Tang, Wenjie
Cui, Lihang
Deng, Xiaoshang
Precision Livestock Farming Research: A Global Scientometric Review
title Precision Livestock Farming Research: A Global Scientometric Review
title_full Precision Livestock Farming Research: A Global Scientometric Review
title_fullStr Precision Livestock Farming Research: A Global Scientometric Review
title_full_unstemmed Precision Livestock Farming Research: A Global Scientometric Review
title_short Precision Livestock Farming Research: A Global Scientometric Review
title_sort precision livestock farming research: a global scientometric review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10340063/
https://www.ncbi.nlm.nih.gov/pubmed/37443894
http://dx.doi.org/10.3390/ani13132096
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