Evolution of Bayesian Methods in Animal Sciences with a Bibliometric Approach

Abstract

This study was conducted to examine the use of Bayesian statistical methods in published research in the field of animal sciences between 2000 and 2025 and to reveal thematic, structural and geographical trends in this field. A total of 1124 original research articles from the Web of Science database were analysed using the Bibliometrix R package and the Biblioshiny interface. Annual publication trends, most productive authors, countries and journals were examined, and structural and contextual patterns in literature were assessed through keyword co-occurrence network, thematic map and trend analysis. The prevalence of Bayesian methods in literature has increased significantly in the last 15 years. The USA, China, and Brazil have been identified as the most prolific publishing countries, while the Journal of Dairy Science and Genetics Selection Evolution has been identified as one of the most prolific journals. Thematic analysis revealed a concentration of methods on topics such as genetic value estimation, milk yield, genomic selection, diagnostic test analysis, and animal behavior. An analysis of the most frequently cited studies revealed the utilization of models such as BayesB, BayesRC, and BayesA. Bayesian methods are not only an alternative analysis approach but also an increasingly indispensable and powerful tool in animal sciences, thanks to their suitability for high-dimensional data, uncertain structures, and a priori knowledge. This bibliometric analysis reveals existing gaps in literature and the potential for improvement, providing strategic directions for future research in the field.

Keywords

• Bayesian analysis
• Animal science
• Bibliometric analysis
• R bibliometrix

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