Plant Phenotyping and Machine Learning
A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Development and Morphogenesis".
Deadline for manuscript submissions: 30 June 2025 | Viewed by 41
Special Issue Editor
2. Key Laboratory of Agricultural Equipment for the Middle and Lower Reaches of the Yangtze River, Ministry of Agriculture, Wuhan 430070, China
Interests: plant phenotyping; computer vision; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Plant phenotyping quantifies the structural and functional attributes of plants, essential for non-destructive and continuous crop morphology and physiology analysis. The complexity of plant growth, including variations in size, morphology, color, texture, and organ development, as well as the impact of environmental factors, poses challenges in plant phenotyping. Machine learning, particularly deep learning, offers robust solutions for complex issues, providing new tools for analyzing, predicting, and understanding plant traits. This Special Issue invites submissions addressing plant phenotyping and machine learning. Specific topics of interest include, but not limited to, the following:
- Image-based phenotyping, including plant classification, segmentation, and detection.
- Extraction and selection of plant phenotypic traits.
- Plant growth monitoring, analysis, modeling, and prediction.
- Disease detection and monitoring.
- Assessment and prediction of plant resistance (including biotic and abiotic stresses).
- Temporal image processing and analysis of plants.
- Data analysis algorithm and software for plant phenotyping.
- Phenotype prediction and classification.
Dr. Lingfeng Duan
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. 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
- plant phenotyping
- machine learning
- image processing
- growth analysis
- data analysis
