Abstract
Plant genetic resources are considered a treasure trove of valuable, untapped diversity that holds the key to breeding the crops of the future. However, the use of these resources in breeding is often limited due to the lack of comprehensive phenotypic characterization. The present study provides extensive historical phenotypic data from nine genebanks as a MIAPPE compliant data set. We compiled and curated phenotypic data from 43,293 wheat accessions, encompassing 460,399 data points across 52 traits, including the three core traits of plant height, heading time, and thousand kernel weight from seven decades. The exceptional quality of the presented dataset was highlighted by predominantly high heritabilities. Phenotypic data of such quantity and quality is a crucial resource for unlocking the valuable diversity of plant genetic resources for agricultural advancement.
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Data availability
The dataset is available both in a MIAPPE compliant tabular excel format at Recherche Data Gouv29 (https://doi.org/10.57745/Y1VWIG, version 1.2), and as a FAIR Digital Object (FDO) in the Annotated Research Context (ARC) format at e!DAL-PGP30 (https://doi.org/10.5447/IPK/2025/11, revision 2). Associated genotypic data was generated for a part of the observed germplasms. The raw sequence data is available at ENA35 (https://www.ebi.ac.uk/ena/browser/view/PRJEB49199, https://www.ebi.ac.uk/ena/browser/view/PRJEB81686). The variant data have been deposited in EVA36 (https://www.ebi.ac.uk/eva/?eva-study=PRJEB106343).
Code availability
The code is available on GitHub (https://github.com/AGENTproject/historic_pheno_data_analysis/), Zenodo (https://doi.org/10.5281/zenodo.15343013), and is archived in Software Heritage (https://archive.softwareheritage.org/swh:1:dir:a95895b0bfdbf346dbb31d656c9ef446c056caec). The code and artifacts from this repository are licensed under the permissive CC-BY-4.0, which allows any kind of reuse with the only condition of giving credit. The code is organised in one Jupyter R40 notebook per crop and per genebank. The computational environment is based on Conda packages. The main packages used are the tidyverse41 meta-package from conda-forge42, bioconductor-multtest43 from bioconda44, and the asreml45 proprietary R package. A full description of the computational environment is included in the repository, to enable reproducibility of the results.
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Acknowledgements
We are sincerely grateful to Hannah F. Oertel (IPK Gatersleben), for her support on biometrics related matters. This study was funded by the AGENT project, which received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 862613. This work was performed using services provided by the URGI bioinformatics facility46.
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All partner genebanks did the historic data digitization and curation. E.L.F. did the data validation, supported by C.P. and S.W. for data collection templates definition, M.B. and R.D.B. for the Excel validator, J.R. for the bioinformatics helpdesk, S.W. and S.K. for accession data validation. E.L.F. did the analysis as an IPK visiting scientist supported by M.O.B. and J.C.R. The CREA-CI (P.V., F.S.) and INIA (D.M.L., M.P.B., M.R.) genebanks volunteered as beta testers for the analysis workflow and provided practical help with data curation. E.L.F. and J.C.R. wrote the manuscript. M.O.B. wrote the Data analyses section. H.F.O. provided biometrics support. Each genebank described their collection in the Plant material section. C.P., M.A., S.W., M.L. contributed to the section presenting the AGENT project phenotyping data flow. M.L, M.P. and J.R.E. integrated and curated the data as a single ISA compliant FAIR Digital Object and published it in e!DAL-PGP. E.B. helped with data curation and publication to recherche.data.gouv.fr. J.C.R. revised the manuscript.
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Le Floch, E., Adam-Blondon, AF., Alaux, M. et al. Wheat historical phenotypic data from European genebanks as an important resource for research and breeding. Sci Data (2026). https://doi.org/10.1038/s41597-026-06908-x
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DOI: https://doi.org/10.1038/s41597-026-06908-x
