Exploring digital twins in agriculture with current applications and implications for research, policy and practice

Digital twin (DT) technology is transforming agriculture. The DT refers to the virtual replicas of actual farming systems that are updated with real-time data, thereby transforming the way agricultural processes are monitored, simulated, and optimized. In recent years, DT in agriculture has attracted significant interest due to its innovations. This paper highlights the research landscape of DT in agriculture, describes key trends and major publications, and identifies new research directions. A total of 657 publications were identified across 23 academic disciplines, published in 87 countries, representing 32% of research articles. China leads with 118 (17.9%) articles, and Wageningen University & Research stands out with 21 (3.19%) publications, indicating the field’s emergence. Co-occurrence analysis of the identified keywords revealed five major themes related to DT in agriculture. The results indicate a growing interest in this area from 2018 to 2025, as evidenced by an increase in the number of publications, authors, and participating countries. We have observed that some core technologies, such as sensors, artificial intelligence, and data analytics, have been widely explored, but research gaps remain. Emerging interests also include climate resilience, renewable energy integration, and supply chain optimisation. This paper also discusses implications of DT for research, practice and policy and offers a way forward for using DT to increase productivity, sustainability, and resilience in agriculture.