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Review

Application of Digital Twin Technology in Smart Agriculture: A Bibliometric Review

Department of Biosystems Engineering & Soil Science, University of Tennessee, Knoxville, TN 37996, USA
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Author to whom correspondence should be addressed.
Agriculture 2025, 15(17), 1799; https://doi.org/10.3390/agriculture15171799
Submission received: 15 July 2025 / Revised: 11 August 2025 / Accepted: 14 August 2025 / Published: 22 August 2025

Abstract

Digital twin technology is reshaping modern agriculture. Digital twins are the virtual replicas of real-world farming systems, which are continuously updated with real-time data, and are revolutionizing the monitoring, simulation, and optimization of agricultural processes. The literature on agricultural digital twins is multidisciplinary, growing rapidly, and often fragmented across disciplines, which lacks well-curated documentation. A bibliometric analysis includes thematic content analysis and science mapping, which provides research trends, gaps, thematic landscape, and key contributors in this continuously evolving and emerging field. Therefore, in this study, we conducted a bibliometric review that included collecting bibliometric data via keyword search strategies on popular scientific databases. The data was further screened, processed, analyzed, and visualized using bibliometric tools to map research trends, landscapes, collaborations, and themes. Key findings show that publications have grown exponentially since 2018, with an annual growth rate of 27.2%. The major contributing countries were China, the USA, the Netherlands, Germany, and India. We observed a collaboration network with distinct geographic clusters, with strong intra-European ties and more localized efforts in China and the USA. The analysis identified seven major research theme clusters revolving around precision farming, Internet of Things integration, artificial intelligence, cyber–physical systems, controlled-environment agriculture, sustainability, and food system applications. We observed that core technologies, such as sensors, artificial intelligence, and data analytics, have been extensively explored, while identifying gaps in research areas. The emerging interests include climate resilience, renewable-energy integration, and supply-chain optimization. The observed transition from task-specific tools to integrated, system-level approaches underline the growing need for adaptive, data-driven decision support. By outlining research trends and identifying strategic research gaps, this review offers insights into leveraging digital twins to improve productivity, sustainability, and resilience in global agriculture.
Keywords: digital twin; sensors; internet of things; artificial intelligence; smart farming; precision farming digital twin; sensors; internet of things; artificial intelligence; smart farming; precision farming

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MDPI and ACS Style

Gund, R.; Badgujar, C.M.; Samiappan, S.; Jagadamma, S. Application of Digital Twin Technology in Smart Agriculture: A Bibliometric Review. Agriculture 2025, 15, 1799. https://doi.org/10.3390/agriculture15171799

AMA Style

Gund R, Badgujar CM, Samiappan S, Jagadamma S. Application of Digital Twin Technology in Smart Agriculture: A Bibliometric Review. Agriculture. 2025; 15(17):1799. https://doi.org/10.3390/agriculture15171799

Chicago/Turabian Style

Gund, Rajesh, Chetan M. Badgujar, Sathishkumar Samiappan, and Sindhu Jagadamma. 2025. "Application of Digital Twin Technology in Smart Agriculture: A Bibliometric Review" Agriculture 15, no. 17: 1799. https://doi.org/10.3390/agriculture15171799

APA Style

Gund, R., Badgujar, C. M., Samiappan, S., & Jagadamma, S. (2025). Application of Digital Twin Technology in Smart Agriculture: A Bibliometric Review. Agriculture, 15(17), 1799. https://doi.org/10.3390/agriculture15171799

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