Scopus-based bibliometric analysis of research trends in silage feed and its impact on rumen fermentation in ruminants
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background and Aim: Silage plays a pivotal role in ruminant nutrition, significantly influencing rumen fermentation, animal productivity, and environmental sustainability. Despite extensive research on silage and fermentation, a comprehensive synthesis of global trends and collaborations in this domain has not been systematically explored. This study aimed to conduct a bibliometric analysis of global research on silage feed and its effects on rumen fermentation in ruminants. It sought to identify publication trends, leading contributors, research themes, and international collaboration networks, thereby informing future directions in ruminant nutrition research. Materials and Methods: A total of 1,007 documents published between 1961 and 2024 were retrieved from the Scopus database using targeted keywords. Bibliometric and network analyses were performed using VOSviewer, Bibliometrix (R package), and Microsoft Excel. Inclusion criteria were limited to peer-reviewed English-language articles focused on silage feed and rumen fermentation in ruminants. Data cleaning and preprocessing involved harmonization of author names, keywords, and institutional affiliations. Results: Publication output has increased significantly since 2010, with China, the United States, and Canada emerging as the top contributors. Major research themes include silage quality, microbial fermentation, methane mitigation, and feed efficiency. Core journals identified include Journal of Dairy Science and Journal of Animal Science. Leading institutions such as China Agricultural University and the University of Florida demonstrated high productivity and citation impact. Keyword analysis highlighted emerging trends, including microbiome, methanogenesis, and sustainability. Collaboration network analysis revealed strong regional clusters, with North America and Europe forming central hubs, while Asia and South America showed growing but less integrated networks. Conclusion: Research on silage and rumen fermentation has evolved from foundational studies to interdisciplinary approaches integrating microbiology, environmental science, and precision agriculture. The field is rapidly expanding, with increasing emphasis on reducing methane emissions and enhancing livestock performance through improved silage practices. However, global collaboration remains fragmented, particularly in underrepresented regions. Future research should focus on metagenomics, smart technologies (e.g., Artificial Intelligence and Internet of Things), and policy-driven strategies to optimize feed systems and support sustainable livestock production. Keywords: bibliometric analysis, international collaboration, methane mitigation, microbiome, rumen fermentation, ruminants, silage feed, sustainability.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.033 | 0.169 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it