Current trends in artificial intelligence and bovine mastites research: a bibliometric review approach

Abstract

Mastitis, a major disease in dairy cows, causes significant losses in herd profitability. Accurate diagnosis is crucial for effective control. Studies using artificial intelligence (AI) models to clas-sify, identify, predict, and diagnose mastitis show promise in control improvement. Thus, this bibliometric review aims to evaluate AI and bovine mastitis terms in the most relevant Scopus indexed papers from 2011 to 2021. 62 documents were analyzed, revealing key terms, prom-inent researchers, relevant publications, and keyword clusters. Mastitis and machine learning were most cited, with an increasing trend from 2018 to 2021. Other terms like sensors and masti-tis detection also emerged. The United States was the most cited country, with the highest collab-oration networks. 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 evident potential for further research in this area.