ArticlePlant methods2024
Integrating dynamic high-throughput phenotyping and genetic analysis to monitor growth variation in foxtail millet.
Article in Plant methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Advances in mutant characterization for detecting causal mutations in crop plants.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Review
- Genome-Wide, High-Density Genotyping Approaches for Plant Germplasm Characterisation (Methods and Applications).International journal of molecular sciences · 2025Review
- Automatic 3D Plant Organ Instance Segmentation Method Based on PointNeXt and Quickshift+.Plant phenomics (Washington, D.C.) · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
backgroundFoxtail millet [Setaria italica (L.) Beauv] is a C
resultsThis study introduces a high-throughput imaging system (HIS) with advanced image processing techniques to enhance monitoring efficiency and data quality. The HIS can accurately extract a range of key growth feature parameters, such as plant height (PH), convex hull area (CHA), side projected area (SPA) and colour distribution, from foxtail millet images. Compared with traditional manual measurements, this HIS improved data quality and phenotyping of the key foxtail millet growth traits. High-throughput phenotyping combined with a genome-wide association study (GWAS) revealed genetic loci associated with dynamic growth traits, particularly plant height (PH), in foxtail millet. The loci were linked to genes involved in the gibberellic acid (GA) synthesis pathway related to PH.
conclusionThe HIS developed in this study enables the efficient and dynamic monitoring of foxtail millet phenotypic traits. It significantly improves the quality of data obtained for phenotyping key growth traits. The integration of high-throughput phenotyping with GWAS provides new insights into the genetic underpinnings of dynamic growth traits, particularly plant height, by identifying associated genetic loci in the GA synthesis pathway. This methodological advancement opens new avenues for the precise phenotyping and exploration of genetic resources in foxtail millet, potentially enhancing its utilisation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.