Artículo

Current Trends in Artificial Intelligence and Bovine Mastitis Research: A Bibliometric Review Approach

Resumen

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.
Mitsunaga, Thatiane Mendes (57449705800); Nery Garcia, Breno Luis (59143353700); Pereira, Ligia Beatriz Rizzanti (59235333500); Costa, Yuri Campos Braga (59235148000); da Silva, Roberto Fray (55597493400); Delbem, Alexandre Cláudio Botazzo (8575424400); dos Santos, Marcos Veiga (59157868800)
Current Trends in Artificial Intelligence and Bovine Mastitis Research: A Bibliometric Review Approach
2024
10.3390/ani14142023
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199661733&doi=10.3390%2fani14142023&partnerID=40&md5=d5c1c0cfea95125fd7c6b24d065a99d4
Luiz de Queiroz College of Agriculture—ESALQ, University of São Paulo, Av. Pádua Dias, 11, SP, Piracicaba, 13418-900, Brazil; School of Veterinary Medicine and Animal Science, University of São Paulo, SP, Pirassununga, 13635-900, Brazil; São Paulo State College of Technology, SP, Americana, 13469-111, Brazil; Biosystems Engineering Department, Luiz de Queiroz College of Agriculture—ESALQ, University of São Paulo, Av. Pádua Dias, 11, SP, Piracicaba, 13418-900, Brazil; Center for Artificial Intelligence—C4AI, University of Sao Paulo, Av. Prof. Lúcio Martins Rodrigues, 370-Butantã, SP, São Paulo, 05508-020, Brazil; Institute of Mathematics and Computer Sciences, University of São Paulo, São Carlos, SP, 13560-970, Brazil
All Open Access; Gold Open Access
Scopus
Artículo obtenido de:
Scopus
Fuente
0 0 votos
Califica el artículo
Subscribirse
Notificación de
Campus Samborondón
Vía Samborondón Km. 13.5
Call Center: 5150400
metricas@ecotec.edu.ec
Facebook Instagram Youtube

Mapa del sitio