The author(s) declare that no financial support was received for the research and/or publication of this article. Data availability statement The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://doi.org/10.26165/JUELICH-DATA/KZDQYD . Author contributions DK: Formal Analysis, Investigation, Validation, Visualization, Writing – original draft, Writing – review & editing. AF: Investigation, Methodology, Resources, Software, Writing – review & editing. VS: Formal Analysis, Investigation, Methodology, Resources, Software, Writing – review & editing. JK: Method
Open resource ↗JUELICH-DATA · 10.26165/JUELICH-DATA/KZDQYD · lines:333-387Unverified paper record
Seed-to-plant-tracking: automated phenotyping of seeds and corresponding plants of Arabidopsis
Frontiers in Plant Science · 28 Apr 2025 · 10.3389/fpls.2025.1539424
Abstract
Plants adapt seed traits in response to different environmental triggers, supporting the survival of the next generation. To elucidate the mechanistic understanding of such adaptations it is important to characterize the distributions of seed traits by phenotyping seeds on an individual scale and to correlate these traits with corresponding plant properties. Here we introduce a seed-to-plant-tracking pipeline which enables automated handling and high precision phenotyping of Arabidopsis seeds as well as germination detection and early growth quantification of emerging plants. It includes previously published measurement platforms ( pheno Seeder, Growscreen), which were improved for very small seeds. We demonstrate the performance of the pipeline by comparing seeds from two consecutive generations of elevated temperature during flowering with control seeds. Relative standard deviation of repeated seed mass measurements was reduced to 0.2%. We identified an increase in seed mass, volume, length, width, height, and germination time as well as a darkening of the seeds under the treatment. A correlation analysis revealed relationships between seed and plant traits, e.g., a highly significant negative correlation between seed brightness and germination time, and a positive correlation between seed mass and early growth rate, but no correlation between time of emergence and morphometric seed traits (e.g., mass, volume). Thus, the seed-to-plant tracking provides the basis for investigating the mechanism of seed and plant trait variation and transgenerational inheritance.
Plant phenotyping relevance
種子から植物までを追跡し、種子形質の高精度自動計測、発芽検出、初期成長定量を行うパイプラインを開発・改良しており、表現型取得法が研究の中心である。
abstractHere we introduce a seed-to-plant-tracking pipeline which enables automated handling and high precision phenotyping of Arabidopsis seeds as well as germination detection and early growth quantification of emerging plants.
abstractIt includes previously published measurement platforms ( pheno Seeder, Growscreen), which were improved for very small seeds.
abstractRelative standard deviation of repeated seed mass measurements was reduced to 0.2%.
Code and data availability
The paper deposits its seed and plant phenotyping datasets in Jülich DATA (DOI 10.26165/JUELICH-DATA/KZDQYD), explicitly stated in the data availability statement. Supplementary tables also contain the paper's measurement data. No author analysis code repository is stated.
of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. Supplementary material The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpls.2025.1539424/full#supplementary-material Supplementary Table 1 Data of seed mass vs volume and projected seed area, respectively, shown in Figure 6 . Supplementary Table 2 Data of repeatability measurements analysed in Table 1 and 2 . Supplementary Table 3 Data of leaf area time series used for estimation of plant grow
Open resource ↗lines:333-387This is an automatically classified, unverified record. Curator approval is required before any resource enters the Catalog.