ArticlePlant communications2021
A deep learning-integrated micro-CT image analysis pipeline for quantifying rice lodging resistance-related traits.
Article in Plant communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Review
- Stem microanatomical phenomic uncovers a potential role for ZmLSM2 in regulating maize stem bending strength.Journal of integrative plant biology · 2026Article
- Integrative transcriptome-metabolome dissection of the molecular basis of lodging resistance in oat (Avena sativa L.) basal internodes.BMC plant biology · 2026Article
- Multi-scale lodging in rice and wheat: bridging biomechanical traits, phenotypic detection, and intelligent harvesting systems.Frontiers in plant science · 2026Review
- Integrating dynamic high-throughput phenotyping and genetic analysis to monitor growth variation in foxtail millet.Plant methods · 2024Article
- Strong culm: a crucial trait for developing next-generation climate-resilient rice lines.Physiology and molecular biology of plants : an international journal of functional plant biology · 2024Review
- Plant microphenotype: from innovative imaging to computational analysis.Plant biotechnology journal · 2024Review
- Article
- Opportunities and Challenges in Applying AI to Evolutionary Morphology.Integrative organismal biology (Oxford, England) · 2024Review
- Advanced deep learning models for phenotypic trait extraction and cultivar classification in lychee using photon-counting micro-CT imaging.Frontiers in plant science · 2024Article
- An Overview of High-Throughput Crop Phenotyping: Platform, Image Analysis, Data Mining, and Data Management.Methods in molecular biology (Clifton, N.J.) · 2024Review
- CT image-based 3D inflorescence estimation ofFrontiers in plant science · 2024Article
- Designing artificial synthetic promoters for accurate, smart, and versatile gene expression in plants.Plant communications · 2023Review
- A Strategy for the Acquisition and Analysis of Image-Based Phenome in Rice during the Whole Growth Period.Plant phenomics (Washington, D.C.) · 2023Article
- Research on the evolutionary history of the morphological structure of cotton seeds: a new perspective based on high-resolution micro-CT technology.Frontiers in plant science · 2023Article
- Proximal and remote sensing in plant phenomics: 20 years of progress, challenges, and perspectives.Plant communications · 2022Review
- Plant synthetic epigenomic engineering for crop improvement.Science China. Life sciences · 2022Review
- A New Year's spotlight on two years of publication.Plant communications · 2022Article
- Tiller estimation method using deep neural networks.Frontiers in plant science · 2022Article
- Mask R-CNN-based feature extraction and three-dimensional recognition of rice panicle CT images.Plant direct · 2021Article
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
Lodging is a common problem in rice, reducing its yield and mechanical harvesting efficiency. Rice architecture is a key aspect of its domestication and a major factor that limits its high productivity. The ideal rice culm structure, including major_axis_culm, minor axis_culm, and wall thickness_culm, is critical for improving lodging resistance. However, the traditional method of measuring rice culms is destructive, time consuming, and labor intensive. In this study, we used a high-throughput micro-CT-RGB imaging system and deep learning (SegNet) to develop a high-throughput micro-CT image analysis pipeline that can extract 24 rice culm morphological traits and lodging resistance-related traits. When manual and automatic measurements were compared at the mature stage, the mean absolute percentage errors for major_axis_culm, minor_axis_culm, and wall_thickness_culm in 104
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