Literature DB >> 26099924

A Versatile Phenotyping System and Analytics Platform Reveals Diverse Temporal Responses to Water Availability in Setaria.

Noah Fahlgren1, Maximilian Feldman1, Malia A Gehan1, Melinda S Wilson1, Christine Shyu1, Douglas W Bryant1, Steven T Hill1, Colton J McEntee1, Sankalpi N Warnasooriya1, Indrajit Kumar1, Tracy Ficor1, Stephanie Turnipseed1, Kerrigan B Gilbert1, Thomas P Brutnell1, James C Carrington1, Todd C Mockler1, Ivan Baxter2.   

Abstract

Phenotyping has become the rate-limiting step in using large-scale genomic data to understand and improve agricultural crops. Here, the Bellwether Phenotyping Platform for controlled-environment plant growth and automated multimodal phenotyping is described. The system has capacity for 1140 plants, which pass daily through stations to record fluorescence, near-infrared, and visible images. Plant Computer Vision (PlantCV) was developed as open-source, hardware platform-independent software for quantitative image analysis. In a 4-week experiment, wild Setaria viridis and domesticated Setaria italica had fundamentally different temporal responses to water availability. While both lines produced similar levels of biomass under limited water conditions, Setaria viridis maintained the same water-use efficiency under water replete conditions, while Setaria italica shifted to less efficient growth. Overall, the Bellwether Phenotyping Platform and PlantCV software detected significant effects of genotype and environment on height, biomass, water-use efficiency, color, plant architecture, and tissue water status traits. All ∼ 79,000 images acquired during the course of the experiment are publicly available.
Copyright © 2015 The Author. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  abiotic/environmental stress; bioinformatics; development; phenotyping; water relations

Mesh:

Substances:

Year:  2015        PMID: 26099924     DOI: 10.1016/j.molp.2015.06.005

Source DB:  PubMed          Journal:  Mol Plant        ISSN: 1674-2052            Impact factor:   13.164


  57 in total

1.  Conventional and hyperspectral time-series imaging of maize lines widely used in field trials.

Authors:  Zhikai Liang; Piyush Pandey; Vincent Stoerger; Yuhang Xu; Yumou Qiu; Yufeng Ge; James C Schnable
Journal:  Gigascience       Date:  2018-02-01       Impact factor: 6.524

2.  Components of Water Use Efficiency Have Unique Genetic Signatures in the Model C4 Grass Setaria.

Authors:  Max J Feldman; Patrick Z Ellsworth; Noah Fahlgren; Malia A Gehan; Asaph B Cousins; Ivan Baxter
Journal:  Plant Physiol       Date:  2018-08-09       Impact factor: 8.340

3.  A High-Throughput, Field-Based Phenotyping Technology for Tall Biomass Crops.

Authors:  Maria G Salas Fernandez; Yin Bao; Lie Tang; Patrick S Schnable
Journal:  Plant Physiol       Date:  2017-06-15       Impact factor: 8.340

4.  Antiviral ARGONAUTEs Against Turnip Crinkle Virus Revealed by Image-Based Trait Analysis.

Authors:  Xingguo Zheng; Noah Fahlgren; Arash Abbasi; Jeffrey C Berry; James C Carrington
Journal:  Plant Physiol       Date:  2019-05-01       Impact factor: 8.340

5.  Extensive Variations in Diurnal Growth Patterns and Metabolism Among Ulva spp. Strains.

Authors:  Antoine Fort; Morgane Lebrault; Margot Allaire; Alberto A Esteves-Ferreira; Marcus McHale; Francesca Lopez; Jose M Fariñas-Franco; Saleh Alseekh; Alisdair R Fernie; Ronan Sulpice
Journal:  Plant Physiol       Date:  2019-02-12       Impact factor: 8.340

6.  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

7.  3D Sorghum Reconstructions from Depth Images Identify QTL Regulating Shoot Architecture.

Authors:  Ryan F McCormick; Sandra K Truong; John E Mullet
Journal:  Plant Physiol       Date:  2016-08-15       Impact factor: 8.340

8.  Predicting plant biomass accumulation from image-derived parameters.

Authors:  Dijun Chen; Rongli Shi; Jean-Michel Pape; Kerstin Neumann; Daniel Arend; Andreas Graner; Ming Chen; Christian Klukas
Journal:  Gigascience       Date:  2018-02-01       Impact factor: 6.524

9.  Development of an Image Analysis Pipeline to Estimate Sphagnum Colony Density in the Field.

Authors:  Willem Q M van de Koot; Larissa J J van Vliet; Weilun Chen; John H Doonan; Candida Nibau
Journal:  Plants (Basel)       Date:  2021-04-22

Review 10.  Robotic Technologies for High-Throughput Plant Phenotyping: Contemporary Reviews and Future Perspectives.

Authors:  Abbas Atefi; Yufeng Ge; Santosh Pitla; James Schnable
Journal:  Front Plant Sci       Date:  2021-06-25       Impact factor: 5.753

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