Charting the Digital Frontier: A Comprehensive Bibliometric Analysis of E-Agriculture Research

Abstract

This study presents a statistically validated bibliometric analysis of e-agriculture research published between 2020 and 2025, based on 1,363 peer-reviewed articles indexed in Scopus and Web of Science, and selected according to the PRISMA 2020 guidelines. Bibliometric mapping is combined with inferential statistical analysis and network validation to examine publication dynamics, thematic evolution, citation impact, and global collaboration patterns. Results show rapid growth in research output up to 2023, followed by a contraction in 2024. Core research themes include smart farming, Internet of Things (IoT), artificial intelligence particularly deep learning and precision agriculture. While China, India, and Brazil lead in publication volume, the United States, the Netherlands, and Germany exhibit higher citation impact, indicating a divergence between productivity and influence. Inferential testing confirms these patterns: one-way ANOVA reveals significant temporal variation in citation impact (F(5,1357)=48.5, p<2×10⁻¹⁶), and network modularity analysis (Q=0.519) demonstrates a robust thematic structure. Poisson regression further shows that publication year and thematic focus jointly shape citation performance. To extend beyond descriptive bibliometrics, the study integrates an altmetric perspective, drawing on Twitter sentiment and topic analysis to capture societal engagement with digital agriculture research. Overall, the study advances bibliometric analysis in e-agriculture by combining statistical validation, network robustness assessment, and signals of societal impact.