Advances in Proximal and Remote Sensing for Optimizing Agricultural and Horticultural Production and Postharvest Systems
A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Precision and Digital Agriculture".
Deadline for manuscript submissions: 31 August 2025 | Viewed by 1226
Special Issue Editors
Interests: viticulture; phenotyping; image analysis; RGB-based vegetation indices; morphometry
Special Issues, Collections and Topics in MDPI journals
Interests: UAV; crop; precision agriculture; phytosanitary monitoring with remote sensing
Interests: digital image processing; computer vision; data analysis; simulation; biophysics; food physics; food science and technology
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Remote sensing offers an innovative and efficient alternative to traditional ground-based manual scouting, enabling more precise crop monitoring, disease inspection, insect prediction, weed classification, water management, yield estimations, and land-use analysis. By providing accurate and timely data, remote sensing supports the development and implementation of both short- and long-term strategies for improving agricultural productivity and sustainability. Key agronomic practices, such as monitoring crop growth, assessing soil quality, tracking plant health, and optimizing irrigation systems, greatly benefit from these technologies.
In recent years, the agricultural sector has increasingly adopted advanced tools, including satellites, drones, robots, and handheld proximal sensing devices. While satellite-based remote sensing has been extensively utilized over the past five decades, challenges such as cloud cover and limited spatial resolution have spurred interest in higher-resolution imagery and on-demand data acquisition through Unmanned Aerial Systems (UAS). These flying platforms, along with ground-based robots, provide detailed and frequent insights into crop health and soil conditions, enabling precision interventions in irrigation scheduling, pest and disease control, and nutrient management.
Moreover, advancements in software technologies—leveraging artificial intelligence (AI) and machine learning (ML)—have significantly enhanced data analysis capabilities. These systems enable near real-time decision-making, facilitating efficient farm operations such as field-level variability assessments, varietal performance evaluations in breeding programs, and the timely adjustment of management practices. By integrating hardware and software innovations, precision agriculture offers transformative potential to sustainably manage resources, increase yields, and maintain soil and plant health for long-term productivity.
Dr. Bodor-Pesti Péter
Dr. Rocío Arias-Calderón
Prof. Dr. László Baranyai
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
- crop monitoring
- data-driven farming
- irrigation management
- plant health monitoring
- precision agriculture
- proximal sensing
- remote sensing
- sustainable farming
- soil quality assessments
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