Abstract
Roots are essential multifunctional plant organs involved in water and nutrient uptake, metabolite storage, anchorage, mechanical support, and interaction with the soil environment. Understanding of this ‘hidden half’ provides potential for manipulation of root system architecture (RSA) traits to optimize resource use efficiency and grain yield in cereal crops. Unfortunately, root traits are highly neglected in breeding due to the challenges of phenotyping, but could have large rewards if the variability in RSA traits can be fully exploited. Until now, a plethora of genes have been characterized in detail for their potential role in improving RSA. The use of forward genetics approaches to find sequence variations in genes underpinning desirable RSA would be highly beneficial. Advances in computer vision applications have allowed image-based approaches for high-throughput phenotyping of RSA traits that can be used by any laboratory worldwide to make progress in understanding root function and dissection of the genetics. At the same time, the frontiers of root measurement include non-invasive methods like X-ray computer tomography and magnetic resonance imaging that facilitate new types of temporal studies. Root physiology and ecology are further supported by spatiotemporal root simulation modeling. The discovery of component traits providing improved resilience and yield advantage in target environments is a key necessity for mainstreaming root-based cereal breeding. The integrated use of pan-genome resources, now available in most cereals, coupled with new in-field phenotyping platforms has the potential for precise selection of superior genotypes with improved RSA.
Original language | English |
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Pages (from-to) | 23-42 |
Number of pages | 20 |
Journal | Plant Journal |
Volume | 110 |
Issue number | 1 |
DOIs | |
State | Published - Apr 2022 |
Funding
This work was funded by the joint project of National Natural Science Foundation of China (31961143007) and Pakistan Science Foundation [PSF‐NSFC III/Agr/C‐QAU (16)]. The authors also acknowledge NSFC for Research Fund for International Young Scientists project (31950410563). Miss Saman Maqbool was supported by Indigenous Fellowship Program of Higher Education Commission (HEC), Pakistan. This work was partially funded by the Center for Bioenergy Innovation, a US Department of Energy Bioenergy Research Center supported by the Office of Biological and Environmental Research in the DOE Office of Science. This manuscript has been authored in part by UT‐Battelle, LLC, under contract DE‐AC05‐00OR22725 with the US Department of Energy (DOE). The publisher acknowledges the US government license to provide public access under the DOE Public Access Plan ( http://energy.gov/downloads/doe‐public‐access‐plan ). This work was funded by the joint project of National Natural Science Foundation of China (31961143007) and Pakistan Science Foundation [PSF-NSFC III/Agr/C-QAU (16)]. The authors also acknowledge NSFC for Research Fund for International Young Scientists project (31950410563). Miss Saman Maqbool was supported by Indigenous Fellowship Program of Higher Education Commission (HEC), Pakistan. This work was partially funded by the Center for Bioenergy Innovation, a US Department of Energy Bioenergy Research Center supported by the Office of Biological and Environmental Research in the DOE Office of Science. This manuscript has been authored in part by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The publisher acknowledges the US government license to provide public access under the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).
Keywords
- phenotyping
- root genomics
- root phenomics
- root system architecture