期刊
COMPUTERS AND ELECTRONICS IN AGRICULTURE
卷 174, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.compag.2020.105459
关键词
RGB imaging; Imaging spectroscopy; Fluorescence imaging; High-throughput phenotyping platform; Data analysis; Image processing; Plant nutrition analysis
资金
- EU FP7 Framework Plan [619137]
- Beijing Municipal Science and Technology Commission Project [Z171100001517016]
Plants show morphology, physiology and biochemical change when they encounter abiotic stress. Image-based plant nutrition analysis is based on this principle and focus on the relationships between plant nutrition content and phenotyping changes, such as leaf color, leaf texture, height, light reflectance ratio, etc. As a non-destructive method, imaging technology can be deployed to support automated plant diagnose and production. Current imaging technologies used in plant nutrition analysis include red-green-blue (RGB) imaging, imaging spectroscopy and fluorescence imaging. This article summarizes the development of imaging technologies for plant nutrition analysis over the past decade and presents their basic concepts and principles. The pros and cons of each imaging method are discussed and future research directions are highlighted. We focus on imaging applications describing the phenotyping of plant canopy instead of root architecture. Advancement in imaging technology has greatly accelerated the application of image-based plant nutrition analysis. This paper provides new ideas for researchers who are committed to plant nutrition analysis and production management.
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