Literature DB >> 24637194

Phenotyping and beyond: modelling the relationships between traits.

Christine Granier1, Denis Vile2.   

Abstract

Plant phenotyping technology has become more advanced with the capacity to measure many morphological and physiological traits on a given individual. With increasing automation, getting access to various traits on a high number of genotypes over time raises the need to develop systems for data storage and analyses, all congregating into plant phenotyping pipelines. In this review, we highlight several studies that illustrate the latest advances in plant multi-trait phenotyping and discuss future needs to ensure the best use of all these quantitative data. We assert that the next challenge is to disentangle how plant traits are embedded in networks of dependencies (and independencies) by modelling the relationships between them and how these are affected by genetics and environment.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2014        PMID: 24637194     DOI: 10.1016/j.pbi.2014.02.009

Source DB:  PubMed          Journal:  Curr Opin Plant Biol        ISSN: 1369-5266            Impact factor:   7.834


  46 in total

1.  Multi-dimensional machine learning approaches for fruit shape phenotyping in strawberry.

Authors:  Mitchell J Feldmann; Michael A Hardigan; Randi A Famula; Cindy M López; Amy Tabb; Glenn S Cole; Steven J Knapp
Journal:  Gigascience       Date:  2020-05-01       Impact factor: 6.524

2.  Phenotypic integration and life history strategies among populations of Pinus halepensis: an insight through structural equation modelling.

Authors:  Filippo Santini; José M Climent; Jordi Voltas
Journal:  Ann Bot       Date:  2020-01-06       Impact factor: 4.357

3.  Leaf Segmentation and Tracking in Arabidopsis thaliana Combined to an Organ-Scale Plant Model for Genotypic Differentiation.

Authors:  Gautier Viaud; Olivier Loudet; Paul-Henry Cournède
Journal:  Front Plant Sci       Date:  2017-01-11       Impact factor: 5.753

4.  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

5.  Quantitative, Image-Based Phenotyping Methods Provide Insight into Spatial and Temporal Dimensions of Plant Disease.

Authors:  Andrew M Mutka; Sarah J Fentress; Joel W Sher; Jeffrey C Berry; Chelsea Pretz; Dmitri A Nusinow; Rebecca Bart
Journal:  Plant Physiol       Date:  2016-07-21       Impact factor: 8.340

6.  A Journey Through a Leaf: Phenomics Analysis of Leaf Growth in Arabidopsis thaliana.

Authors:  Hannes Vanhaeren; Nathalie Gonzalez; Dirk Inzé
Journal:  Arabidopsis Book       Date:  2015-07-22

7.  A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis.

Authors:  Yassin Refahi; Géraldine Brunoud; Etienne Farcot; Alain Jean-Marie; Minna Pulkkinen; Teva Vernoux; Christophe Godin
Journal:  Elife       Date:  2016-07-06       Impact factor: 8.140

8.  Natural variation in stomatal responses to environmental changes among Arabidopsis thaliana ecotypes.

Authors:  Sho Takahashi; Keina Monda; Juntaro Negi; Fumitaka Konishi; Shinobu Ishikawa; Mimi Hashimoto-Sugimoto; Nobuharu Goto; Koh Iba
Journal:  PLoS One       Date:  2015-02-23       Impact factor: 3.240

9.  Measurement of Arabidopsis thaliana Plant Traits Using the PHENOPSIS Phenotyping Platform.

Authors:  Wojciech Rymaszewski; Myriam Dauzat; Alexis Bédiée; Gaëlle Rolland; Nathalie Luchaire; Christine Granier; Jacek Hennig; Denis Vile
Journal:  Bio Protoc       Date:  2018-02-20

Review 10.  Plant Transcription Factors Involved in Drought and Associated Stresses.

Authors:  Maria Hrmova; Syed Sarfraz Hussain
Journal:  Int J Mol Sci       Date:  2021-05-26       Impact factor: 5.923

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