Smart Sensing, Artificial Intelligence and Robotic Solutions for Precision Horticulture, Tree Ecophysiology and Phenotyping
A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Modeling".
Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 285
Special Issue Editors
Interests: agricultural engineering; biosystems engineering; robotics; precision horticulture; 3D phenotyping; fruit detection; LiDAR
Interests: tree-crop physiology; precision orchard management (POM); precision horticulture; robotics; computer vision; sensors; agricultural engineering
Interests: application of new technologies and precision management techniques; effects of the environment on fruit tree physiology; developing new management strategies to improve orchards’ sustainability, maintaining a high level of quality and yields
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent years, smart sensors, artificial intelligence (AI), and robotics have witnessed remarkable advancements in the agricultural sector.
These advancements primarily aim to optimize crop production while concurrently conserving resources in order to mitigate environmental impact. Smart sensing devices, such as IoT networks, aerial and terrestrial platforms, and proximal sensors, have revolutionized data collection by providing real-time spatio-temporal information on soil conditions, crop vigor, microclimate, and many other parameters. Coupled with artificial intelligence (AI), these technologies enable intelligent decision-making processes based on physiological models, enhancing agricultural practices. Together, smart sensing and AI can drive physiological-based automation in horticulture, as well as in those more complex scenario or activities.
This Issue aims to explore the intersection of smart sensing, artificial intelligence, and robotics within the context of precision horticulture, tree ecophysiology and phenotyping. We invite researchers to contribute their original works on topics including, but not limited to:
- IoT technologies and innovative approaches for both invasive and non-invasive monitoring of tree ecophysiology including water stress, photosynthesis, and carbon assimilation, combined with smart sensing technologies for monitoring and managing plant growth, water usage, and nutrient levels in horticultural systems.
- Artificial intelligence application for data analysis, prediction, and the optimization of management in precision horticulture.
- Robotic solutions easing/automating in situ plant phenotyping crop monitoring, harvesting, and maintenance in orchards and greenhouses.
- Digital twins and models for non-invasive monitoring and prediction of plant physiology
- High-throughput phenotyping techniques using advanced machine vision technologies and machine learning/AI algorithms.
Bringing together diverse perspectives and cutting-edge research, this SI aims to foster interdisciplinary collaborations and promote the adoption of smart sensing, artificial intelligence, and robotic solutions in the field of horticultural science.
We believe that this convergence of technologies has the potential to revolutionize horticultural practices, improve crop productivity, and contribute to sustainable agricultural systems.
Dr. Nikos Tsoulias
Dr. Gianmarco Bortolotti
Dr. Luigi Manfrini
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. Plants 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 2700 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
- sensing
- artificial intelligence (AI)
- robotics
- phenotyping
- precision horticulture
- precision orchard management (POM)
- IoT
- digital twin
