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J Exp Bot. 2015 Sep;66(18):5417-27. doi: 10.1093/jxb/erv271. Epub 2015 Jun 4.

Towards recommendations for metadata and data handling in plant phenotyping.

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Institute of Plant Genetics, Polish Academy of Sciences, ul. Strzeszyńska 34, Poznań, Poland
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), OT Gatersleben, Corrensstrasse 3, D-06466 Stadt Seeland, Germany.
Institute of Plant Genetics, Polish Academy of Sciences, ul. Strzeszyńska 34, Poznań, Poland.
Applied Bioinformatics, Bioscience, Plant Sciences Group, Wageningen University and Research Centre (WUR), Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands.
Forschungszentrum Jülich, IBG-2 Plant Sciences, Jülich, Germany.
The European Molecular Biology Laboratory-The European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK.
Poznań University of Life Sciences, ul. Wojska Polskiego 28, Poznań, Poland.
Keygene N.V., Agro Business Park 90, 6708 PW Wageningen, The Netherlands.
INRA-URGI, Route de Saint Cyr, Versaille, France.
Forschungszentrum Jülich, IBG-2 Plant Sciences, Jülich, Germany RWTH Aachen, Worringer Weg 3, Institute of Biology I, Aachen, Germany.


Recent methodological developments in plant phenotyping, as well as the growing importance of its applications in plant science and breeding, are resulting in a fast accumulation of multidimensional data. There is great potential for expediting both discovery and application if these data are made publicly available for analysis. However, collection and storage of phenotypic observations is not yet sufficiently governed by standards that would ensure interoperability among data providers and precisely link specific phenotypes and associated genomic sequence information. This lack of standards is mainly a result of a large variability of phenotyping protocols, the multitude of phenotypic traits that are measured, and the dependence of these traits on the environment. This paper discusses the current situation of standardization in the area of phenomics, points out the problems and shortages, and presents the areas that would benefit from improvement in this field. In addition, the foundations of the work that could revise the situation are proposed, and practical solutions developed by the authors are introduced.


Data formatting; data interoperability; metadata content; minimum information recommendations; phenotyping; standardization.

[Indexed for MEDLINE]

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