Literature DB >> 32480839

GROWSCREEN-Rhizo is a novel phenotyping robot enabling simultaneous measurements of root and shoot growth for plants grown in soil-filled rhizotrons.

Kerstin A Nagel1, Alexander Putz1, Frank Gilmer1, Kathrin Heinz1, Andreas Fischbach1, Johannes Pfeifer1, Marc Faget1, Stephan Blossfeld1, Michaela Ernst1, Chryssa Dimaki1, Bernd Kastenholz1, Ann-Katrin Kleinert1, Anna Galinski1, Hanno Scharr1, Fabio Fiorani1, Ulrich Schurr1.   

Abstract

Root systems play an essential role in ensuring plant productivity. Experiments conducted in controlled environments and simulation models suggest that root geometry and responses of root architecture to environmental factors should be studied as a priority. However, compared with aboveground plant organs, roots are not easily accessible by non-invasive analyses and field research is still based almost completely on manual, destructive methods. Contributing to reducing the gap between laboratory and field experiments, we present a novel phenotyping system (GROWSCREEN-Rhizo), which is capable of automatically imaging roots and shoots of plants grown in soil-filled rhizotrons (up to a volume of ~18L) with a throughput of 60 rhizotrons per hour. Analysis of plants grown in this setup is restricted to a certain plant size (up to a shoot height of 80cm and root-system depth of 90cm). We performed validation experiments using six different species and for barley and maize, we studied the effect of moderate soil compaction, which is a relevant factor in the field. First, we found that the portion of root systems that is visible through the rhizotrons' transparent plate is representative of the total root system. The percentage of visible roots decreases with increasing average root diameter of the plant species studied and depends, to some extent, on environmental conditions. Second, we could measure relatively minor changes in root-system architecture induced by a moderate increase in soil compaction. Taken together, these findings demonstrate the good potential of this methodology to characterise root geometry and temporal growth responses with relatively high spatial accuracy and resolution for both monocotyledonous and dicotyledonous species. Our prototype will allow the design of high-throughput screening methodologies simulating environmental scenarios that are relevant in the field and will support breeding efforts towards improved resource use efficiency and stability of crop yields.

Entities:  

Year:  2012        PMID: 32480839     DOI: 10.1071/FP12023

Source DB:  PubMed          Journal:  Funct Plant Biol        ISSN: 1445-4416            Impact factor:   3.101


  30 in total

1.  Identifying Developmental Patterns in Structured Plant Phenotyping Data.

Authors:  Yann Guédon; Yves Caraglio; Christine Granier; Pierre-Éric Lauri; Bertrand Muller
Journal:  Methods Mol Biol       Date:  2022

2.  MultipleXLab: A high-throughput portable live-imaging root phenotyping platform using deep learning and computer vision.

Authors:  Vinicius Lube; Mehmet Alican Noyan; Alexander Przybysz; Khaled Salama; Ikram Blilou
Journal:  Plant Methods       Date:  2022-03-27       Impact factor: 4.993

3.  Root angle is controlled by EGT1 in cereal crops employing an antigravitropic mechanism.

Authors:  Riccardo Fusi; Serena Rosignoli; Haoyu Lou; Giuseppe Sangiorgi; Riccardo Bovina; Jacob K Pattem; Aditi N Borkar; Marco Lombardi; Cristian Forestan; Sara G Milner; Jayne L Davis; Aneesh Lale; Gwendolyn K Kirschner; Ranjan Swarup; Alberto Tassinari; Bipin K Pandey; Larry M York; Brian S Atkinson; Craig J Sturrock; Sacha J Mooney; Frank Hochholdinger; Matthew R Tucker; Axel Himmelbach; Nils Stein; Martin Mascher; Kerstin A Nagel; Laura De Gara; James Simmonds; Cristobal Uauy; Roberto Tuberosa; Jonathan P Lynch; Gleb E Yakubov; Malcolm J Bennett; Rahul Bhosale; Silvio Salvi
Journal:  Proc Natl Acad Sci U S A       Date:  2022-07-26       Impact factor: 12.779

4.  Co-fertilization of Sulfur and Struvite-Phosphorus in a Slow-Release Fertilizer Improves Soybean Cultivation.

Authors:  Stella F Valle; Amanda S Giroto; Gelton G F Guimarães; Kerstin A Nagel; Anna Galinski; Jens Cohnen; Nicolai D Jablonowski; Caue Ribeiro
Journal:  Front Plant Sci       Date:  2022-05-10       Impact factor: 6.627

Review 5.  New approaches to improve crop tolerance to biotic and abiotic stresses.

Authors:  Miguel González Guzmán; Francesco Cellini; Vasileios Fotopoulos; Raffaella Balestrini; Vicent Arbona
Journal:  Physiol Plant       Date:  2021-09-17       Impact factor: 5.081

6.  Cohabiting Plant-Wearable Sensor In Situ Monitors Water Transport in Plant.

Authors:  Yangfan Chai; Chuyi Chen; Xuan Luo; Shijie Zhan; Jongmin Kim; Jikui Luo; Xiaozhi Wang; Zhongyuan Hu; Yibin Ying; Xiangjiang Liu
Journal:  Adv Sci (Weinh)       Date:  2021-03-09       Impact factor: 16.806

7.  DIRT/3D: 3D root phenotyping for field-grown maize (Zea mays).

Authors:  Suxing Liu; Carlos Sherard Barrow; Meredith Hanlon; Jonathan P Lynch; Alexander Bucksch
Journal:  Plant Physiol       Date:  2021-10-05       Impact factor: 8.340

Review 8.  Wheat root systems as a breeding target for climate resilience.

Authors:  Eric S Ober; Samir Alahmad; James Cockram; Cristian Forestan; Lee T Hickey; Josefine Kant; Marco Maccaferri; Emily Marr; Matthew Milner; Francisco Pinto; Charlotte Rambla; Matthew Reynolds; Silvio Salvi; Giuseppe Sciara; Rod J Snowdon; Pauline Thomelin; Roberto Tuberosa; Cristobal Uauy; Kai P Voss-Fels; Emma Wallington; Michelle Watt
Journal:  Theor Appl Genet       Date:  2021-04-26       Impact factor: 5.699

9.  Image analysis for the automatic phenotyping of Orobanche cumana tubercles on sunflower roots.

Authors:  A Le Ru; G Ibarcq; M- C Boniface; A Baussart; S Muños; M Chabaud
Journal:  Plant Methods       Date:  2021-07-21       Impact factor: 4.993

Review 10.  Next-generation phenotyping: requirements and strategies for enhancing our understanding of genotype-phenotype relationships and its relevance to crop improvement.

Authors:  Joshua N Cobb; Genevieve Declerck; Anthony Greenberg; Randy Clark; Susan McCouch
Journal:  Theor Appl Genet       Date:  2013-03-08       Impact factor: 5.699

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