Image-Based Technologies in Seed Science
A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Seed Science and Technology".
Deadline for manuscript submissions: 25 September 2026 | Viewed by 204
Special Issue Editors
Interests: instrumentation; optical metrology; laser application; dynamic laser speckle; agricultural phenomena
Special Issues, Collections and Topics in MDPI journals
Interests: seed physiology; germination; vigor; longevity; seed maturation; dormancy; artificial intelligence; image analysis; seed testing; laser application
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Seeds are the cornerstone of agriculture, and assessing their physiological, physical, and sanitary qualities are essential for global food security. With the dawn of the digital era, monitoring agricultural processes has shifted toward modern instrumentation, with most being driven largely by the adoption of image-based technologies. Today, seed analysis is increasingly performed using a variety of sophisticated and reliable imaging methodologies.
Digital agriculture—often referred to as Agriculture 5.0—describes the integration of high-definition digital cameras, rapid data assembly procedures, and dataset processing into farming and research. These advancements allow for non-destructive, high-throughput analysis that was previously impossible.
Current imaging techniques encompass a wide array of methods, including the following:
- Hyperspectral Imaging;
- LiDAR (Light Detection and Ranging);
- NIR (Near-Infrared) and Fluorescence Spectroscopy;
- X-ray Imaging;
- Thermal Imaging;
- Laser Interferometry.
When integrated, these tools form the basis of machine vision, enabling the automation of seed quality protocols and phenotype characterization.
The transition to digital imaging demands significant storage capacity and sophisticated processing power. Consequently, Artificial Intelligence (AI), Machine Learning, Deep Learning (YOLO models), and other technologies have become critical pillars in managing and interpreting the vast datasets generated by these sensors, translating raw image data into biological actionable insights into precise biological data.
We welcome submissions on new image-based technologies in seed science for this Special Issue. The topics listed below are suggestions; please do not feel limited by them.
- Seed Production: Monitoring crop health and maturity, phenological stage, and harvest timing.
- Germination Processes: Real-time tracking of physiological changes and radicle emergence detection.
- High-throughput vigor phenomena and Viability: Automated and non-automated new assessments of seed performance.
- Pathology: Identification of pathogens or contaminants via machine vision.
- Purity: Varietal identification.
Prof. Dr. Roberto Alves Braga Júnior
Dr. Edvaldo Aparecido Amaral Da Silva
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-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
- seed physiology
- germination
- vigor
- longevity
- pathology
- purity
- machine vision
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