Smart Sensor-Based Systems for Crop Monitoring
A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Digital Agriculture".
Deadline for manuscript submissions: 31 December 2025 | Viewed by 100
Special Issue Editor
Interests: artificial intelligence; biosystems engineering; automation; yield prediction; crop disease detection; weed management; remote sensing; data fusion; machine learning; deep learning; hyperspectral imaging; fluorescence kinetics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Modern agricultural systems face increasingly complex challenges, including climate variability, population growth, resource depletion, and food security concerns. Precision agriculture systems that employ real-time crop physiology monitoring for the control of crop growth status and health conditions offer transformative potential, integrating direct plant feedback with smart control systems. Such technologies are being integrated into applications that support precision irrigation management, early crop stress detection, automated nutrient delivery, resource optimization, and sustainable crop production, primarily through smart sensor-based systems that can assess crop status.
This Special Issue invites original research articles, reviews, and perspectives that provide valuable insights into the applications of crop physiology monitoring technologies in precision agriculture, focusing on systems that utilize direct plant feedback for crop growth optimization and health condition assessment.
The topics of interest include, but are not limited to, the following:
- Plant physiology status sensors for real-time crop monitoring and automated control;
- Sensor-driven irrigation and nutrient management based on plant physiological status;
- Plant stress detection and early warning systems that use crop physiology monitoring;
- Microcontroller-based systems for crop condition monitoring;
- Machine learning algorithms for plant physiological status data interpretation;
- Decision support systems for comprehensive crop growth status assessment;
- Edge computing solutions for real-time plant physiology status processing and control.
Dr. Xanthoula Eirini Pantazi
Guest Editor
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. 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
- multisensory data fusion
- crop monitoring
- crop stress detection
- smart sensors
- microcontrollers
- machine learning
- edge computing
- precision agriculture
- decision support systems
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