Journal of Integrative Agriculture ›› 2025, Vol. 24 ›› Issue (4): 1220-1233.DOI: 10.1016/j.jia.2024.05.003

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  • 收稿日期:2023-10-30 接受日期:2024-03-30 出版日期:2025-04-20 发布日期:2025-03-14

Tracing the contribution of cattle farms to methane emissions through bibliometric analyses

Shakoor Abdul1*, Zaib Gul2,3*, Ming Xu4,5,1#   

  1. 1 College of Geography and Environmental Science, Henan University, Kaifeng 475004, China

    2 Institute of Epigenetics and Epigenomics, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China

    3 College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China

    4 Guangdong-Hong Kong Joint Laboratory for Carbon Neutrality, Jiangmen Laboratory of Carbon Science and Technology, Jiangmen 529199, China

    5 BNU-HKUST Laboratory for Green Innovation, Advanced Institute of Natural Sciences, Beijing Normal University at Zhuhai, Zhuhai 519087, China

  • Received:2023-10-30 Accepted:2024-03-30 Online:2025-04-20 Published:2025-03-14
  • About author:# Correspondence Ming Xu, E-mail: 91122020071@bnu.edu.cn * These authors contributed equally to this study.
  • Supported by:
    This study was supported by the Special Fund for Science and Technology Innovation Strategy of Guangdong Province, China (2022660500250009604).

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Abstract:

Methane contributes to global warming, and livestock is one of the sources of methane production.  However, methane emission studies using bibliometric tools in livestock are lacking.  Given the negative impact of climate change on the ecosystem and the rise in methane emissions, it is essential to conduct a bibliometrics study to provide an overview and research trends.  We used the Bibliometrix package and VOSviewer to decipher bibliometric indices for methane emissions in cattle farms (MECF).  Current dataset were collected from the Web of Science (Core Collection) database, and 8,998 publications were analyzed.  The most co-occurring keywords scientists preferred were methane (1,528), greenhouse gas (443), methane emissions (440), and cattle (369).  Methane was the most frequently used keyword in the published scientific literature.  Thematic evolution of research themes and trend results highlighted carbon dioxide, methane, dairy cattle, cattle, and risk factors during 1999–2017.  Chinese Academy of Sciences ranked on top with 485 publications, followed by Agriculture & Agri-Food Canada, University of Colorado, National Oceanic and Atmospheric Administration, and Aarhus University.  Chinese Academy of Sciences was also the most cited organization, followed by the University of Colorado, Agriculture & Agri-Food Canada, National Oceanic and Atmospheric Administration, and United States Geological Survey.  Source analysis showed that the Science of the Total Environment was cited with the highest total link strength.  Science of the Total Environment ranked first in source core 1 with 290 citation frequencies, followed by Journal of Dairy Science with 223 citation frequencies.  Currently, no bibliometric study has been conducted on MECF, and to fill this knowledge gap, we carried out this study to highlight methane emissions in cattle farms, aiming at a climate change perspective.  In this regard, we focused on the research productivity of countries authors, journals and institutions, co-occurrence of keywords, evolution of research trends, and collaborative networking.  Based on relevance degree of centrality, methane emissions and greenhouse gases appeared as basic themes, cattle, and dairy cattle appeared as emerging/declining themes, whereas, methane, greenhouse gas and nitrous oxide appeared to fall amongst basic and motor themes.  On the other hand, beef cattle, rumen and dairy cow seem to be between motor and niche themes, and risk factors lie in niche themes.  The present bibliometric analysis provides research progress on methane emissions in cattle farms.  Current findings may provide a framework for understanding research trends and themes in MECF research. 

Key words: methane emission ,  cattle farms ,  climate change ,  greenhouse gases ,  networking ,  bibliometrics