Root system architecture in cereals: progress, challenges and perspective

文献类型: 外文期刊

第一作者: Maqbool, Saman

作者: Maqbool, Saman;Rasheed, Awais;Hassan, Muhammad Adeel;Xia, Xianchun;Rasheed, Awais;He, Zhonghu;York, Larry M.;Rasheed, Awais;He, Zhonghu

作者机构:

关键词: phenotyping; root genomics; root phenomics; root system architecture

期刊名称:PLANT JOURNAL ( 影响因子:7.091; 五年影响因子:8.028 )

ISSN: 0960-7412

年卷期: 2022 年 110 卷 1 期

页码:

收录情况: SCI

摘要: 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.

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