ArticleScientific reports2025
Evaluation of 3D seed structure and cellular traits in-situ using X-ray microscopy.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- High-throughput phenomic survey of seed morphological diversity in common and tartary buckwheat germplasm.Scientific reports · 2026Article
- A pennycress transparent testa 8 knockout mutant has drastic changes in seed coat anatomy and chemical compositions.Journal of experimental botany · 2026Article
- Creating a new oilseed crop, pennycress, by combining key domestication traits using CRISPR genome editing.Nature plants · 2026Article
- Bridging scales: integrated multi-omics and deep phenotyping for climate resilience in crop plants.Frontiers in plant science · 2026Review
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8 authors.
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Abstract
Phenotyping methods for seed morphology are mostly limited to two-dimensional imaging or manual measures. In this study, we present a novel seed phenotyping approach utilizing lab-based X-ray microscopy (XRM) to characterize 3D seed morphology, internal structures, and cellular analysis from a single scan. Seeds of pennycress (Thlaspi arvense L.) an oilseed cover crop, were scanned and segmented using a machine learning model. Seed morphological analysis and a coat thickness map was applied to compare seed volumes of four genotypes. Notably, the 3D seed volume measurement alone was not enough to reveal differences in seed coat between the genotypes. Applying a seed coat thickness map revealed that the Large-Golden genotype had a thinner seed coat compared to wildtype despite a greater seed coat volume. Cellular analysis showed that cotyledon cell size was a driving factor for larger seeds. XRM was compared to traditional seed morphology traits and positive correlations were observed. Between Large-Golden and wildtype, differences could only be resolved by XRM highlighting the limitations of 2D seed area measures. These results demonstrate that XRM can provide quantitative measures extracted from seeds for enhancing our understanding of seed structure, development, and facilitate breeding efforts for enhanced seed quality and crop performance.
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