Toward Modern Pesticide Use Reduction Strategies in Advancing Precision Agriculture: A Bibliometric Review

Abstract

Precision agriculture technologies (PATs) are revolutionizing the agricultural sector by minimizing the reliance on plant protection products (PPPs) in crop management. This approach integrates a broad range of advanced solutions employed to help farmers in optimizing PPP application, while minimizing input and maintaining effective crop protection. These technologies include sensors, drones, robotics, variable rate systems, and artificial intelligence (AI) tools that support site-specific pesticide applications. The objective of this review was to perform a bibliometric analysis to identify scientific trends and gaps in this field. The analysis was conducted using Scopus and Web of Science databases for the period of 2015–2024, by applying a data filtering process to ensure a clean and reliable dataset. The methodology involved citation, co-authorship, co-citation, and co-occurrence analysis. VOSviewer software (version 1.6.20) was used to generate maps and assess global research developments. Results identified AI, sensor, and data processing categories as the most central and interconnected scientific topics, emphasizing their vital role in the evolution of precision spraying technology. Bibliometric analysis highlighted that China, the United States, and India were the most productive countries, with strong collaborations within Europe. The co-occurrence and co-citation analyses revealed increasing interdisciplinarity and the integration of AI tools across various technologies. These findings help identify key experts and research leaders in the precision agriculture domain, thus underscoring the shift toward a more sustainable, data-driven, and synergistic approach in crop protection.