Bibliometric Analysis to Recognize Precision Agriculture Research Trends
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Bibliometric Analysis to Recognize Precision Agriculture Research TrendsAbstract
This study employs bibliometric analysis to examine the evolution and trends in Precision Agriculture (PA) research from 1980 to 2024, utilizing Scopus as the primary data source. The objectives are to identify key technological advancements driving PA, explore emerging themes and trends within PA research, and uncover gaps in the literature as well as opportunities for future development. The findings reveal a consistent growth in PA-related research, particularly from 2013 onward, highlighting the increasing importance of PA in addressing global agricultural challenges. Citation analysis emphasizes the pivotal role of core technologies such as the Internet of Things (IoT), remote sensing, machine learning, and Unmanned Aerial Vehicles (UAVs) in enhancing agricultural efficiency and sustainability. The insights from this study provide a comprehensive framework for advancing PA research, supporting researchers, policymakers, and practitioners in designing and promoting modern agricultural technologies. Furthermore, these findings lay the foundation for innovations aimed at improving agricultural efficiency and sustainability in the future.
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