ArticleScientific data2026
X-ray computed tomography images of wheat kernels and reconstructed three-dimensional shapes.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- X-ray computed tomography images of wheat kernels and reconstructed three-dimensional shapes.Scientific data · 2026Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Grain kernel morphology strongly influences aerodynamic loads, breakage susceptibility, and processing performance. Conventional two-dimensional projection imaging and manual measurements lack the accuracy and completeness needed to represent the true three-dimensional structure of kernels. We present an open X-ray computed tomography dataset of wheat kernels that includes axial slice stacks and three-dimensional shape models for 100 individual kernels, together with per-sample morphometrics including principal-axis lengths, elongation index, flatness index, convexity, and sphericity. The dataset supports statistics of kernel shape, enables analysis of internal microstructure from the provided slice stacks, and facilitates high-fidelity discrete element modelling with realistic particle geometry.
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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 OpenQuestion graph.