Agricultural Education Administration Research

Document Type : Research Paper

Authors

1 Department of Agricultural Extension and Education, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran

2 Associate professor in rural development, faculty of agriculture, Bu-Ali Sina University, Hamedan

10.22092/jaear.2026.372676.2100

Abstract

Drone technology as one of the novel tools for precision and smart agriculture, has attracted researchers’ attention in recent years. This study investigated the growth trend and scientific orientations of research related to drone adoption in agriculture, identifying scientific collaboration patterns and dominant research themes. This study was conducted using a descriptive-analytical scientometric/bibliometric approach with network analysis (scientific collaboration and keyword co-occurrence). Data were extracted from the Scopus database, and relevant articles published between 2005 and 2025 were collected based on their titles, abstracts, and keywords. After refinement, 712 articles were selected as the final dataset. Analyses were performed using scientometric indicators and VOSviewer software, including an examination of publication trends, geographical distribution, active journals, the network of country collaborations, and the keyword co-occurrence network. The results indicated an increase in scientific output in this field over the last two decades, with a more rapid growth observed after 2016. Geographically, China and the United States held the largest share of scientific production and played central roles in the collaboration network. Keyword analysis also revealed four dominant themes: drone applications in agriculture, remote sensing and data analysis, human/behavioral factors influencing adoption, and economic and regulatory challenges. Overall, the findings suggest that drone adoption in agriculture is a result of the interaction between technological advancements, data infrastructures, policy frameworks, and human factors. These results can be utilized to guide future research and improve decision-making in the development of novel agricultural technologies.

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