Literature DB >> 26044092

Towards recommendations for metadata and data handling in plant phenotyping.

Paweł Krajewski1, Dijun Chen2, Hanna Ćwiek3, Aalt D J van Dijk4, Fabio Fiorani5, Paul Kersey6, Christian Klukas2, Matthias Lange2, Augustyn Markiewicz7, Jan Peter Nap4, Jan van Oeveren8, Cyril Pommier9, Uwe Scholz2, Marco van Schriek8, Björn Usadel10, Stephan Weise2.   

Abstract

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.
© The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

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

Mesh:

Year:  2015        PMID: 26044092     DOI: 10.1093/jxb/erv271

Source DB:  PubMed          Journal:  J Exp Bot        ISSN: 0022-0957            Impact factor:   6.992


  44 in total

1.  Unlocking historical phenotypic data from an ex situ collection to enhance the informed utilization of genetic resources of barley (Hordeum sp.).

Authors:  Maria Y González; Norman Philipp; Albert W Schulthess; Stephan Weise; Yusheng Zhao; Andreas Börner; Markus Oppermann; Andreas Graner; Jochen C Reif
Journal:  Theor Appl Genet       Date:  2018-06-29       Impact factor: 5.699

Review 2.  The Quest for Understanding Phenotypic Variation via Integrated Approaches in the Field Environment.

Authors:  Duke Pauli; Scott C Chapman; Rebecca Bart; Christopher N Topp; Carolyn J Lawrence-Dill; Jesse Poland; Michael A Gore
Journal:  Plant Physiol       Date:  2016-08-01       Impact factor: 8.340

Review 3.  Design Considerations for In-Field Measurement of Plant Architecture Traits Using Ground-Based Platforms.

Authors:  Piyush Pandey; Sierra Young
Journal:  Methods Mol Biol       Date:  2022

Review 4.  Capturing crop adaptation to abiotic stress using image-based technologies.

Authors:  Nadia Al-Tamimi; Patrick Langan; Villő Bernád; Jason Walsh; Eleni Mangina; Sónia Negrão
Journal:  Open Biol       Date:  2022-06-22       Impact factor: 7.124

5.  A genome-wide association and prediction study in grapevine deciphers the genetic architecture of multiple traits and identifies genes under many new QTLs.

Authors:  Timothée Flutre; Loïc Le Cunff; Agota Fodor; Amandine Launay; Charles Romieu; Gilles Berger; Yves Bertrand; Nancy Terrier; Isabelle Beccavin; Virginie Bouckenooghe; Maryline Roques; Lucie Pinasseau; Arnaud Verbaere; Nicolas Sommerer; Véronique Cheynier; Roberto Bacilieri; Jean-Michel Boursiquot; Thierry Lacombe; Valérie Laucou; Patrice This; Jean-Pierre Péros; Agnès Doligez
Journal:  G3 (Bethesda)       Date:  2022-07-06       Impact factor: 3.542

Review 6.  Crop breeding for a changing climate: integrating phenomics and genomics with bioinformatics.

Authors:  Jacob I Marsh; Haifei Hu; Mitchell Gill; Jacqueline Batley; David Edwards
Journal:  Theor Appl Genet       Date:  2021-04-14       Impact factor: 5.699

Review 7.  The INCREASE project: Intelligent Collections of food-legume genetic resources for European agrofood systems.

Authors:  Elisa Bellucci; Orlando Mario Aguilar; Saleh Alseekh; Kirstin Bett; Creola Brezeanu; Douglas Cook; Lucía De la Rosa; Massimo Delledonne; Denise F Dostatny; Juan J Ferreira; Valérie Geffroy; Sofia Ghitarrini; Magdalena Kroc; Shiv Kumar Agrawal; Giuseppina Logozzo; Mario Marino; Tristan Mary-Huard; Phil McClean; Vladimir Meglič; Tamara Messer; Frédéric Muel; Laura Nanni; Kerstin Neumann; Filippo Servalli; Silvia Străjeru; Rajeev K Varshney; Marta W Vasconcelos; Massimo Zaccardelli; Aleksei Zavarzin; Elena Bitocchi; Emanuele Frontoni; Alisdair R Fernie; Tania Gioia; Andreas Graner; Luis Guasch; Lena Prochnow; Markus Oppermann; Karolina Susek; Maud Tenaillon; Roberto Papa
Journal:  Plant J       Date:  2021-09-23       Impact factor: 7.091

8.  Phenotyping in Plants. Preface.

Authors:  Roland Pieruschka; Tracy Lawson
Journal:  J Exp Bot       Date:  2015-09       Impact factor: 6.992

9.  PGP repository: a plant phenomics and genomics data publication infrastructure.

Authors:  Daniel Arend; Astrid Junker; Uwe Scholz; Danuta Schüler; Juliane Wylie; Matthias Lange
Journal:  Database (Oxford)       Date:  2016-04-17       Impact factor: 3.451

Review 10.  Data integration in biological research: an overview.

Authors:  Vasileios Lapatas; Michalis Stefanidakis; Rafael C Jimenez; Allegra Via; Maria Victoria Schneider
Journal:  J Biol Res (Thessalon)       Date:  2015-09-02       Impact factor: 1.889

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