From lab to field, new approaches to phenotyping root system architecture

► Several root system architecture (RSA) traits are correlated with agronomic performance. ► Optimizing RSA may increase crop productivity. ► Historically, methods to characterize RSA have lacked resolution and throughput. ► New methods to characterize RSA in three dimensions are being developed. ►...

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Bibliographic Details
Published in:Current opinion in plant biology 2011-06, Vol.14 (3), p.310-317
Main Authors: Zhu, Jinming, Ingram, Paul A, Benfey, Philip N, Elich, Tedd
Format: Article
Language:English
Subjects:
agronomic traits
genetic techniques and protocols
image analysis
Image Processing, Computer-Assisted - methods
loci
new methods
Phenotype
Plant Cells
Plant Development
Plant Roots - cytology
Plant Roots - genetics
Plant Roots - growth & development
Plants - genetics
Quantitative Trait Loci
root systems
Software
soil resources
Tomography, X-Ray Computed - methods
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Summary:► Several root system architecture (RSA) traits are correlated with agronomic performance. ► Optimizing RSA may increase crop productivity. ► Historically, methods to characterize RSA have lacked resolution and throughput. ► New methods to characterize RSA in three dimensions are being developed. ► Future challenges include correlating lab RSA traits with crop productivity. Plant root system architecture (RSA) is plastic and dynamic, allowing plants to respond to their environment in order to optimize acquisition of important soil resources. A number of RSA traits are known to be correlated with improved crop performance. There is increasing recognition that future gains in productivity, especially under low input conditions, can be achieved through optimization of RSA. However, realization of this goal has been hampered by low resolution and low throughput approaches for characterizing RSA. To overcome these limitations, new methods are being developed to facilitate high throughput and high content RSA phenotyping. Here we summarize laboratory and field approaches for phenotyping RSA, drawing particular attention to recent advances in plant imaging and analysis. Improvements in phenotyping will facilitate the genetic analysis of RSA and aid in the identification of the genetic loci underlying useful agronomic traits.
ISSN:1369-5266
1879-0356
DOI:10.1016/j.pbi.2011.03.020