Research Area: Machine Learning
Veins are a critical component of the plant growth and development system, playing an integral role in supporting and protecting leaves, as well as transporting water, nutrients, and photosynthetic products. A comprehensive understanding of the form and function of veins requires a dual approach that combines plant physiology with cutting-edge image recognition technology. The latest advancements in computer vision and machine learning have facilitated the creation of algorithms that can identify vein networks and explore their developmental progression. Here, we review the functional, environmental, and genetic factors associated with vein networks, along with the current status of research on image analysis. In addition, we discuss the methods of venous phenotype extraction and multi-omics association analysis using machine learning technology, which could provide a theoretical basis for improving crop productivity by optimizing the vein network architecture.
Keywords:
Deep learning
enviromics analysis
growth prediction model
image analysis
multi-omics analysis
phenotype omics
vein network
Author(s) Name: Yubin Zhang, Ning Zhang, Xiujuan Chai, Tan Sun
Journal name: Journal of Experimental Botany
Conferrence name:
Publisher name: Oxford Academic
DOI: 10.1093/jxb/erad251
Volume Information: Volume 74
