A BIBLIOMETRIC EVALUATION OF SMART AGRICULTURE RESEARCH

Smart agriculture, leveraging technologies such as the Internet of Things, machine learning, and artificial intelligence, offers innovative solutions to enhance productivity, minimize environmental impact, and support data-driven decision-making. This study aimed to perform a bibliometric analysis of research published in the field of smart agriculture from 2014 to 2024. Data were collected from two major databases, Web of Science and Scopus, and analyzed using VOSviewer software. Key indicators examined included annual publication trends, citation metrics, researcher co-authorship networks, and keyword co-occurrence patterns. The results reveal that the number of publications in this field has increased more than twelvefold over the past decade, with emerging technologies forming the core of the main conceptual clusters. Countries such as China, the United States, and India have been leading contributors to scientific output. Six major thematic clusters were identified: technology, resource management, sustainability, data analytics, policymaking, and economics. However, the involvement of social sciences and humanities remains relatively limited. Despite significant advances, challenges persist, including a lack of indigenous research from developing countries and insufficient integration of interdisciplinary data. The findings of this study provide valuable insights to inform innovative policymaking, guide investment in technological infrastructure, and shape future research directions in smart agriculture.