Plant Image Science serves as an academic platform for promoting knowledge exchange and collaboration among researchers, educators, and professionals in the fields of plant image science and phenomics. The journal pursues the following aims and scope:
- To promote the sharing of research findings, technologies, and information in plant image science and phenomics
- To foster the expansion of the academic ecosystem and encourage interdisciplinary research
- To support the foundation and dissemination of education, research, and industrial applications in related fields
- To enhance scholarly exchange and international cooperation among researchers
The journal publishes original research articles, review articles, technical reports, and perspectives covering a broad spectrum of topics in plant image science, including but not limited to:
- Imaging technologies for plant phenotyping (e.g., hyperspectral imaging, thermal imaging, 3D imaging, LiDAR, etc.)
- High-throughput image-based analysis systems and automation technologies
- AI and machine learning–based trait extraction and data interpretation
- Applied research in precision agriculture, growth monitoring, and pest/disease detection
- Integrated analyses of phenotypic information with genomic and environmental data
- Case studies on educational applications, industrial technologies, and real-world deployments
