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

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Autor(es):
Mitsunaga, Thatiane Mendes ; Garcia, Breno Luis Nery ; Pereira, Ligia Beatriz Rizzanti ; Costa, Yuri Campos Braga ; da Silva, Roberto Fray ; Delbem, Alexandre Claudio Botazzo ; dos Santos, Marcos Veiga
Número total de Autores: 7
Tipo de documento: Artigo Científico
Fonte: ANIMALS; v. 14, n. 14, p. 19-pg., 2024-07-01.
Resumo

Simple Summary Artificial intelligence has become essential for aiding in different knowledge domains by improving knowledge extraction from raw data and process automation. In dairy production, artificial intelligence offers promising applications in detecting and managing bovine mastitis, the most critical disease affecting the mammary gland in dairy cows, impacting milk production and profitability in dairy farms. This research evaluated the evolution of artificial intelligence applications in bovine mastitis between 2011 and 2021 using the Scopus database and the frequency of terms cited in titles, abstracts, and keywords. We selected the 62 papers that were the most relevant according to their citation index. Our results pointed out that the terms "machine learning" and "mastitis" were the most cited, with a significant increase between 2018 and 2021. There was an increase in artificial intelligence applications for bovine mastitis per country, showing applications primarily aimed at improving the current mastitis detection systems. The most cited model was artificial neural networks. We concluded that using artificial intelligence in bovine mastitis was related to mastitis detection as a vital tool to prevent this disease, considering its major impacts on dairy production and economic return.Abstract 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. (AU)

Processo FAPESP: 23/00286-3 - Predição da cura da mastite clínica usando machine learning
Beneficiário:Breno Luis Nery Garcia
Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Doutorado
Processo FAPESP: 21/05400-3 - Uso responsável de antimicrobianos e resistência bacteriana na produção de leite
Beneficiário:Marcos Veiga dos Santos
Modalidade de apoio: Auxílio à Pesquisa - Temático