Methane (CH4) from livestock, particularly enteric CH4 emission (EME), is one contributor to greenhouse gas emissions and climate change. This review analyzed 1294 scientific abstracts on EME in ruminants from 1986 to May 2024, using Scopus® data. Descriptive statistics, text mining, and topic analysis were performed. Publications on EME have risen significantly since 2005, with the Journal of Dairy Science being the most frequent publisher. Most studies (82.1%) were original research, with Northern Hemisphere countries leading in publication numbers. The most frequent terms were “milk”, “cow”, and “diet”, while key research topics included greenhouse gas emissions from livestock, diet composition, and prediction models. Despite progress, some areas like CH4 emission from animals need further investigation.

Evangelista, C., Milanesi, M., Pietrucci, D., Chillemi, G., Bernabucci, U. (2024). Enteric Methane Emission in Livestock Sector: Bibliometric Research from 1986 to 2024 with Text Mining and Topic Analysis Approach by Machine Learning Algorithms. ANIMALS, 14(21), 1-24 [10.3390/ani14213158].

Enteric Methane Emission in Livestock Sector: Bibliometric Research from 1986 to 2024 with Text Mining and Topic Analysis Approach by Machine Learning Algorithms

Daniele Pietrucci;Giovanni Chillemi;
2024-01-01

Abstract

Methane (CH4) from livestock, particularly enteric CH4 emission (EME), is one contributor to greenhouse gas emissions and climate change. This review analyzed 1294 scientific abstracts on EME in ruminants from 1986 to May 2024, using Scopus® data. Descriptive statistics, text mining, and topic analysis were performed. Publications on EME have risen significantly since 2005, with the Journal of Dairy Science being the most frequent publisher. Most studies (82.1%) were original research, with Northern Hemisphere countries leading in publication numbers. The most frequent terms were “milk”, “cow”, and “diet”, while key research topics included greenhouse gas emissions from livestock, diet composition, and prediction models. Despite progress, some areas like CH4 emission from animals need further investigation.
2024
Pubblicato
Rilevanza internazionale
Review
Esperti anonimi
Settore AGR/17 - Zootecnica Generale e Miglioramento Genetico
Settore AGRI-09/A - Zootecnia generale e miglioramento genetico
English
Con Impact Factor ISI
enteric methane
machine learning
ruminants
text mining
topic analysis
https://mdpi.com/2076-2615/14/21/3158
Evangelista, C., Milanesi, M., Pietrucci, D., Chillemi, G., Bernabucci, U. (2024). Enteric Methane Emission in Livestock Sector: Bibliometric Research from 1986 to 2024 with Text Mining and Topic Analysis Approach by Machine Learning Algorithms. ANIMALS, 14(21), 1-24 [10.3390/ani14213158].
Evangelista, C; Milanesi, M; Pietrucci, D; Chillemi, G; Bernabucci, U
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/395886
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