Agricultural Imagery and Machine Vision
A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Precision and Digital Agriculture".
Deadline for manuscript submissions: 31 January 2026 | Viewed by 28
Special Issue Editors
Interests: wireless sensor networks; agricultural monitoring; Intelligent decision-making
Special Issue Information
Dear Colleagues,
In the present era, global agriculture stands at a pivotal juncture of accelerated transition from conventional methodologies to intelligent, precision-driven systems. Agricultural imagery and machine vision technologies have emerged as indispensable linchpins, powerfully steering the course of smart agriculture's development. From the real-time monitoring of crop growth trends in the fields, through the early and precise warning systems for pests and diseases and the autonomous operation of agricultural robots, to the intelligent management of agricultural resources, the application of these technologies is reshaping the production models and decision-making systems of traditional agriculture. However, as research continues to deepen and application scenarios expand, this field is encountering a variety of issues, such as fragmented research outcomes, insufficient interdisciplinary communication, and a pressing need for breakthroughs in key technologies. In practical applications, issues such as the insufficient accuracy of image recognition in complex field environments, the need to expand the depth and breadth of multi-source data fusion, and the excessively high cost of implementing the technology on the ground severely limit the large-scale promotion and application of these technologies.
Within this Special Issue, research areas encompass crop phenotyping analysis using imagery and machine vision; pest, disease, and weed identification through image recognition and machine learning; yield prediction with machine learning models; robotics and automation systems for agricultural tasks; multi-source data fusion to improve decision-making; and novel imaging technologies and sensors, including drone imaging, satellite remote sensing, and LiDAR for agricultural data acquisition.
Dr. Ximing Li
Prof. Dr. Xuejun Yue
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
- smart agriculture
- agricultural imagery
- image recognition
- crop monitoring
- remote sensing
- sensor technology
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