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Unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection

The scarce knowledge on phenotypic characterization restricts the usage of genetic diversity of plant genetic resources in research and breeding. We describe original and ready-to-use processed data for approximately 60% of ~22,000 barley accessions hosted at the Federal ex situ Genebank for Agricul...

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Autores principales: Gonzalez, Maria Y., Weise, Stephan, Zhao, Yusheng, Philipp, Norman, Arend, Daniel, Börner, Andreas, Oppermann, Markus, Graner, Andreas, Reif, Jochen C., Schulthess, Albert W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6278694/
https://www.ncbi.nlm.nih.gov/pubmed/30512010
http://dx.doi.org/10.1038/sdata.2018.278
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author Gonzalez, Maria Y.
Weise, Stephan
Zhao, Yusheng
Philipp, Norman
Arend, Daniel
Börner, Andreas
Oppermann, Markus
Graner, Andreas
Reif, Jochen C.
Schulthess, Albert W.
author_facet Gonzalez, Maria Y.
Weise, Stephan
Zhao, Yusheng
Philipp, Norman
Arend, Daniel
Börner, Andreas
Oppermann, Markus
Graner, Andreas
Reif, Jochen C.
Schulthess, Albert W.
author_sort Gonzalez, Maria Y.
collection PubMed
description The scarce knowledge on phenotypic characterization restricts the usage of genetic diversity of plant genetic resources in research and breeding. We describe original and ready-to-use processed data for approximately 60% of ~22,000 barley accessions hosted at the Federal ex situ Genebank for Agricultural and Horticultural Plant Species. The dataset gathers records for three traits with agronomic relevance: flowering time, plant height and thousand grain weight. This information was collected for seven decades for winter and spring barley during the seed regeneration routine. The curated data represent a source for research on genetics and genomics of adaptive and yield related traits in cereals due to the importance of barley as model organism. This data could be used to predict the performance of non-phenotyped individuals in other collections through genomic prediction. Moreover, the dataset empowers the utilization of phenotypic diversity of genetic resources for crop improvement.
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spelling pubmed-62786942018-12-05 Unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection Gonzalez, Maria Y. Weise, Stephan Zhao, Yusheng Philipp, Norman Arend, Daniel Börner, Andreas Oppermann, Markus Graner, Andreas Reif, Jochen C. Schulthess, Albert W. Sci Data Data Descriptor The scarce knowledge on phenotypic characterization restricts the usage of genetic diversity of plant genetic resources in research and breeding. We describe original and ready-to-use processed data for approximately 60% of ~22,000 barley accessions hosted at the Federal ex situ Genebank for Agricultural and Horticultural Plant Species. The dataset gathers records for three traits with agronomic relevance: flowering time, plant height and thousand grain weight. This information was collected for seven decades for winter and spring barley during the seed regeneration routine. The curated data represent a source for research on genetics and genomics of adaptive and yield related traits in cereals due to the importance of barley as model organism. This data could be used to predict the performance of non-phenotyped individuals in other collections through genomic prediction. Moreover, the dataset empowers the utilization of phenotypic diversity of genetic resources for crop improvement. Nature Publishing Group 2018-12-04 /pmc/articles/PMC6278694/ /pubmed/30512010 http://dx.doi.org/10.1038/sdata.2018.278 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.
spellingShingle Data Descriptor
Gonzalez, Maria Y.
Weise, Stephan
Zhao, Yusheng
Philipp, Norman
Arend, Daniel
Börner, Andreas
Oppermann, Markus
Graner, Andreas
Reif, Jochen C.
Schulthess, Albert W.
Unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection
title Unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection
title_full Unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection
title_fullStr Unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection
title_full_unstemmed Unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection
title_short Unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection
title_sort unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6278694/
https://www.ncbi.nlm.nih.gov/pubmed/30512010
http://dx.doi.org/10.1038/sdata.2018.278
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