Digital Twins in Precision Agriculture
A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Precision and Digital Agriculture".
Deadline for manuscript submissions: 20 May 2026 | Viewed by 54
Special Issue Editors
Interests: smart farming; crop monitoring; precision agriculture; remote sensing; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
2. Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen 518000, China
Interests: computer vision; deep learning; brain-inspired computing; edge computing; remote sensing; agricultural engineering; smart agriculture; precision agriculture; agricultural aviation; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Digital twin technology is being increasingly applied in agriculture. This progress is driven by the integration of real-time data from satellite remote sensing, UAVs, IoT field sensors, and machine learning algorithms to create dynamic, data-driven virtual models of agricultural systems. Building on its origins in industry and systems engineering, this paradigm enables continuous monitoring, scenario simulation, and decision support for complex crop environments.
This Special Issue focuses on the integration of AI-driven modeling, multispectral and hyperspectral imaging, data fusion frameworks, and physics-informed neural networks to develop robust digital twins for precision agriculture. Core topics include crop growth simulation, stress detection, yield forecasting, and feedback-based control systems.
We invite contributions exploring novel architectures, real-world deployments, sensor-to-model pipelines, and interoperable platforms that connect Earth observation data with predictive analytics. Both methodological innovations and application-focused case studies are welcome, especially those addressing climate resilience, explainability in AI, and scalable digital infrastructure for smart farming systems.
Dr. Nathalie Guimarães
Dr. Yuxing Han
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- digital twins
- precision agriculture
- remote sensing
- machine learning
- deep learning
- crop simulation
- smart farming
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