Artificial Intelligence in Agriculture

Artificial intelligence (AI) in agriculture holds great promise for improving farming, productivity, sustainability, and efficiency. This study investigates the changing landscape of agriculture-based AI by reviewing the rapid growth of academic publications found in Scopus. We highlight trends in AI research, citation trends, key areas of research, and major contributors to the field. Our analysis shows a significant rise in AI and related publications, particularly in precision agriculture, machine learning, and computer vision. Utilizing data on citation counts up to October 2023 to enable analysis of this substantial resource, the classic citation distribution is skewed, with certain key seminal works maintaining significant influence over time. Additionally, author collaboration networks show that certain researchers play a central role in the momentum of the field. We extracted important research domains concentrating on different AI applications in farming (such as resource management, pest control, and sustainability) using K-means clustering. However, challenges such as data quality, adoption barriers for smallholder farmers, and infrastructure limitations remain. Another aspect highlighted by this study is the interdisciplinary nature of AI research in the agriculture field, placing the need for cross-sector collaboration at the centre of the debate. Finally, we propose research areas for future work, focusing on improved accessibility of data, challenges to adoption, and synergy between AI and other emerging technologies. In conclusion, we believe that this study provides valuable insights into the significant potential of AI in agriculture, as well as the key opportunities and challenges as AI progresses.