ArticleJournal of visualized experiments : JoVE2018
Micron-scale Phenotyping Techniques of Maize Vascular Bundles Based on X-ray Microcomputed Tomography.
Article in Journal of visualized experiments : JoVE, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- The ZmmiR169o/ZmNF-YA13 module orchestrates maize kernel texture by fine-tuning starch biosynthesis and endosperm architecture.BMC plant biology · 2026Article
- Plant microphenotype: from innovative imaging to computational analysis.Plant biotechnology journal · 2024Review
- A robust and efficient automatic method to segment maize FASGA stained stem cross section images to accurately quantify histological profile.Plant methods · 2022Article
- Particle-Based Imaging Tools Revealing Water Flows in Maize Nodal Vascular Plexus.Plants (Basel, Switzerland) · 2022Article
- High throughput phenotyping of cross-sectional morphology to assess stalk lodging resistance.Plant methods · 2022Article
- Dissecting the phenotypic components and genetic architecture of maize stem vascular bundles using high-throughput phenotypic analysis.Plant biotechnology journal · 2021Article
- Phenotyping analysis of maize stem using micro-computed tomography at the elongation and tasseling stages.Plant methods · 2020Article
- MVS-Pheno: A Portable and Low-Cost Phenotyping Platform for Maize Shoots Using Multiview Stereo 3D Reconstruction.Plant phenomics (Washington, D.C.) · 2020Article
- Multi-omics analysis of the development and fracture resistance for maize internode.Scientific reports · 2019Article
- Crop Phenomics: Current Status and Perspectives.Frontiers in plant science · 2019Review
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Authors and funding
6 authors.
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Abstract
It is necessary to accurately quantify the anatomical structures of maize materials based on high-throughput image analysis techniques. Here, we provide a 'sample preparation protocol' for maize materials (i.e., stem, leaf, and root) suitable for ordinary microcomputed tomography (micro-CT) scanning. Based on high-resolution CT images of maize stem, leaf, and root, we describe two protocols for the phenotypic analysis of vascular bundles: (1) based on the CT image of maize stem and leaf, we developed a specific image analysis pipeline to automatically extract 31 and 33 phenotypic traits of vascular bundles; (2) based on the CT image series of maize root, we set up an image processing scheme for the three-dimensional (3-D) segmentation of metaxylem vessels, and extracted two-dimensional (2-D) and 3-D phenotypic traits, such as volume, surface area of metaxylem vessels, etc. Compared with traditional manual measurement of vascular bundles of maize materials, the proposed protocols significantly improve the efficiency and accuracy of micron-scale phenotypic quantification.
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