Current Trends in Artificial Intelligence and Bovine Mastitis Research: A Bibliometric Review Approach
Thatiane Mendes Mitsunaga,
Breno Luis Nery Garcia,
Ligia Beatriz Rizzanti Pereira,
Yuri Campos Braga Costa,
Roberto Fray da Silva,
Alexandre Cláudio Botazzo Delbem,
Marcos Veiga dos Santos
Affiliations
Thatiane Mendes Mitsunaga
Luiz de Queiroz College of Agriculture—ESALQ, University of São Paulo, Av. Pádua Dias, 11, Piracicaba 13418-900, SP, Brazil
Breno Luis Nery Garcia
School of Veterinary Medicine and Animal Science, University of São Paulo, Pirassununga 13635-900, SP, Brazil
Ligia Beatriz Rizzanti Pereira
School of Veterinary Medicine and Animal Science, University of São Paulo, Pirassununga 13635-900, SP, Brazil
Yuri Campos Braga Costa
São Paulo State College of Technology, Americana 13469-111, SP, Brazil
Roberto Fray da Silva
Biosystems Engineering Department, Luiz de Queiroz College of Agriculture—ESALQ, University of São Paulo, Av. Pádua Dias, 11, Piracicaba 13418-900, SP, Brazil
Alexandre Cláudio Botazzo Delbem
Center for Artificial Intelligence—C4AI, University of Sao Paulo, Av. Prof. Lúcio Martins Rodrigues, 370-Butantã, São Paulo 05508-020, SP, Brazil
Marcos Veiga dos Santos
School of Veterinary Medicine and Animal Science, University of São Paulo, Pirassununga 13635-900, SP, Brazil
Mastitis, an important disease in dairy cows, causes significant losses in herd profitability. Accurate diagnosis is crucial for adequate control. Studies using artificial intelligence (AI) models to classify, identify, predict, and diagnose mastitis show promise in improving mastitis control. This bibliometric review aimed to evaluate AI and bovine mastitis terms in the most relevant Scopus-indexed papers from 2011 to 2021. Sixty-two documents were analyzed, revealing key terms, prominent researchers, relevant publications, main themes, and keyword clusters. “Mastitis” and “machine learning” were the most cited terms, with an increasing trend from 2018 to 2021. Other terms, such as “sensors” and “mastitis detection”, also emerged. The United States was the most cited country and presented the largest collaboration network. Publications on mastitis and AI models notably increased from 2016 to 2021, indicating growing interest. However, few studies utilized AI for bovine mastitis detection, primarily employing artificial neural network models. This suggests a clear potential for further research in this area.
