Quantifying wheat spike morphology by high resolution 3D surface scanning

Quantifying wheat spike morphology by high resolution 3D surface scanning | Research Square Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF comment Quantifying wheat spike morphology by high resolution 3D surface scanning Latifa Greche, Malcolm hawkesford, Nicolas Virlet This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8551193/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Jun, 2026 Read the published version in Plant Methods → Version 1 posted 10 You are reading this latest preprint version Abstract An understanding of spike shape will be of great benefit for improving wheat yields. Traditional manual measurements of spike traits are slow and prone to human error, preventing large-scale phenotyping. Employing imaging techniques will allow researchers to measure multiple morphometric parameters simultaneously. While 2D imaging provides a rapid screening method, 3D imaging offer a more comprehensive understanding of spike shape, revealing complex external structures. This study addresses the challenge of developing a high-resolution 3D surface-scanning pipeline to accurately quantify wheat spike morphology across diverse genotypes. Using a 3D surface-scanner, sharp point clouds of individual spikes were reconstructed and automatically aligned and analysed to extract key morphological features including spike length, volume, and thickness profile. New shape descriptors based on thickness profiles, local extremes, statistical curve fitting, segmentation of spikes into zones of aborted spikelets, base and apical segments as well as the extraction of spike/spikelets branching and endpoints of components were introduced to capture detailed structural variation between genotypes. Correlations between the 3D-derived traits and traditional metrics such as spike weight, spikelet number and seed weight confirmed the biological relevance of the extracted parameters. The method distinguished morphological differences among twelve wheat genotypes, revealing distinct shape types such as long, short, compact, and awned spikes. By combining precise 3D imaging with computational analysis, this approach provides a non-destructive framework for spike phenotyping. These findings demonstrate that 3D surface-scanning can deliver accurate and reproducible measurements of wheat spike architecture, offering new opportunities for linking morphology with genetics and yield potential in modern breeding programs. Wheat Spike shape Surface scanning Yield prediction Mesh reconstruction Trait extraction Full Text Additional Declarations No competing interests reported. Supplementary Files 1TablesS6toS14alltraitsofindividualspikes.xlsx 2TableS15Fittingcurvesoftheindividualspikes.xlsx 3TableS16correlationanalysisbetweenalltraits.xlsx 4TableS17TGWofeachgenotype.xlsx Cite Share Download PDF Status: Published Journal Publication published 15 Jun, 2026 Read the published version in Plant Methods → Version 1 posted Editorial decision: Revision requested 30 Mar, 2026 Reviews received at journal 14 Mar, 2026 Reviewers agreed at journal 18 Feb, 2026 Reviewers agreed at journal 17 Feb, 2026 Reviews received at journal 28 Jan, 2026 Reviewers agreed at journal 27 Jan, 2026 Reviewers invited by journal 26 Jan, 2026 Editor assigned by journal 12 Jan, 2026 Submission checks completed at journal 12 Jan, 2026 First submitted to journal 10 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information

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