Simplified, Digital and Intelligent Tea Production
A Special Issue of Agriculture (ISSN 2077-0472) belonging to the section "Artificial Intelligence and Digital Agriculture".
Deadline for manuscript submissions: 28 February 2027 | Viewed by 47
Editors
Interests: smart agriculture; remote sensing in agriculture; precision tea plantation management; crop phenotyping and growth monitoring; machine learning; tea quality and stress monitoring
Special Issues, Collections and Topics in MDPI journals
Interests: tea plant; ecological cultivation; tea breeding; digital agriculture; precision management
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Tea is a major perennial cash crop worldwide, supporting agricultural production, rural livelihoods, food systems, and human health. However, tea production remains largely dependent on experience-based management, manual surveys, and coarse cultivation practices. Complex canopy structures, heterogeneous environments, substantial spatiotemporal variability in plant growth and quality, and strong links between field conditions and processing create challenges for precision management, consistent quality, and sustainable production, particularly in smallholder and fragmented systems.
Rapid advances in digital agriculture are enabling data-driven tea production. Multi-source sensing technologies, including satellite and UAV remote sensing, proximal sensing, hyperspectral and multispectral imaging, thermal imaging, LiDAR, and IoT sensors, support continuous and non-destructive monitoring of tea plants and production environments. AI-driven approaches further enable digital phenotyping, nutritional and physiological diagnosis, growth and yield prediction, quality assessment, pest and disease detection, and intelligent decision-making. Digital transformation is moving beyond individual technologies toward integrated systems linking sensing, intelligence, decision-making, and autonomous operations. Digital twins, decision-support systems, robotics, and intelligent machinery can optimize management and enable precise field operations, while digital technologies can connect pre-harvest conditions with processing and final quality to support quality-oriented production and traceability from field to cup. Together, these innovations offer new pathways to improve resource efficiency, reduce environmental impacts, enhance climate resilience, and promote more precise, intelligent, and sustainable tea production.
For this Special Issue, we welcome the contribution of original research articles, review articles, communications, and methodological studies addressing, but not limited to, the following topics:
- Smart phenotyping and digital monitoring of tea growth, yield and quality;
- Artificial intelligence and data-driven modeling for tea production;
- Precision management of water, nutrients, and crop protection;
- Digital twins, intelligent decision support and robotics for tea production;
- Digital technologies for tea processing, quality control and traceability;
- Climate-smart and sustainable digital tea production.
Dr. Jie Jiang
Prof. Dr. Wanping Fang
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 250 words) can be sent to the Editorial Office for assessment.
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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access semimonthly 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
- smart agriculture
- artificial intelligence
- remote sensing
- digital phenotyping
- digital twins
- intelligent robotics
- tea production
- tea quality
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