Literature DB >> 23706697

Cell to whole-plant phenotyping: the best is yet to come.

Stijn Dhondt1, Nathalie Wuyts, Dirk Inzé.   

Abstract

Imaging and image processing have revolutionized plant phenotyping and are now a major tool for phenotypic trait measurement. Here we review plant phenotyping systems by examining three important characteristics: throughput, dimensionality, and resolution. First, whole-plant phenotyping systems are highlighted together with advances in automation that enable significant throughput increases. Organ and cellular level phenotyping and its tools, often operating at a lower throughput, are then discussed as a means to obtain high-dimensional phenotypic data at elevated spatial and temporal resolution. The significance of recent developments in sensor technologies that give access to plant morphology and physiology-related traits is shown. Overall, attention is focused on spatial and temporal resolution because these are crucial aspects of imaging procedures in plant phenotyping systems.
Copyright © 2013 Elsevier Ltd. All rights reserved.

Keywords:  image processing; non-invasive sensor; physiology; plant growth; plant phenomics

Mesh:

Year:  2013        PMID: 23706697     DOI: 10.1016/j.tplants.2013.04.008

Source DB:  PubMed          Journal:  Trends Plant Sci        ISSN: 1360-1385            Impact factor:   18.313


  75 in total

Review 1.  Species-independent analytical tools for next-generation agriculture.

Authors:  Tedrick Thomas Salim Lew; Rajani Sarojam; In-Cheol Jang; Bong Soo Park; Naweed I Naqvi; Min Hao Wong; Gajendra P Singh; Rajeev J Ram; Oded Shoseyov; Kazuki Saito; Nam-Hai Chua; Michael S Strano
Journal:  Nat Plants       Date:  2020-11-30       Impact factor: 15.793

2.  Image-based high-throughput field phenotyping of crop roots.

Authors:  Alexander Bucksch; James Burridge; Larry M York; Abhiram Das; Eric Nord; Joshua S Weitz; Jonathan P Lynch
Journal:  Plant Physiol       Date:  2014-09-03       Impact factor: 8.340

3.  Dissecting the phenotypic components of crop plant growth and drought responses based on high-throughput image analysis.

Authors:  Dijun Chen; Kerstin Neumann; Swetlana Friedel; Benjamin Kilian; Ming Chen; Thomas Altmann; Christian Klukas
Journal:  Plant Cell       Date:  2014-12-11       Impact factor: 11.277

4.  Leaf Growth Response to Mild Drought: Natural Variation in Arabidopsis Sheds Light on Trait Architecture.

Authors:  Pieter Clauw; Frederik Coppens; Arthur Korte; Dorota Herman; Bram Slabbinck; Stijn Dhondt; Twiggy Van Daele; Liesbeth De Milde; Mattias Vermeersch; Katrien Maleux; Steven Maere; Nathalie Gonzalez; Dirk Inzé
Journal:  Plant Cell       Date:  2016-10-11       Impact factor: 11.277

5.  A New Phenotyping Pipeline Reveals Three Types of Lateral Roots and a Random Branching Pattern in Two Cereals.

Authors:  Sixtine Passot; Beatriz Moreno-Ortega; Daniel Moukouanga; Crispulo Balsera; Soazig Guyomarc'h; Mikael Lucas; Guillaume Lobet; Laurent Laplaze; Bertrand Muller; Yann Guédon
Journal:  Plant Physiol       Date:  2018-05-11       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

Review 8.  Mathematical models light up plant signaling.

Authors:  Yin Hoon Chew; Robert W Smith; Harriet J Jones; Daniel D Seaton; Ramon Grima; Karen J Halliday
Journal:  Plant Cell       Date:  2014-01-30       Impact factor: 11.277

9.  ChronoRoot: High-throughput phenotyping by deep segmentation networks reveals novel temporal parameters of plant root system architecture.

Authors:  Nicolás Gaggion; Federico Ariel; Vladimir Daric; Éric Lambert; Simon Legendre; Thomas Roulé; Alejandra Camoirano; Diego H Milone; Martin Crespi; Thomas Blein; Enzo Ferrante
Journal:  Gigascience       Date:  2021-07-20       Impact factor: 6.524

Review 10.  Biotechnological Approaches for Genetic Improvement of Lemon (Citrus limon (L.) Burm. f.) against Mal Secco Disease.

Authors:  Chiara Catalano; Mario Di Guardo; Gaetano Distefano; Marco Caruso; Elisabetta Nicolosi; Ziniu Deng; Alessandra Gentile; Stefano Giovanni La Malfa
Journal:  Plants (Basel)       Date:  2021-05-17
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