Scientia Agricultura Sinica ›› 2022, Vol. 55 ›› Issue (3): 425-437.doi: 10.3864/j.issn.0578-1752.2022.03.001

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS • Previous Articles     Next Articles

Advances and Perspectives of Approaches to Phenotyping Crop Root System

LI Long(),LI ChaoNan,MAO XinGuo,WANG JingYi,JING RuiLian()   

  1. Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/National Key Facility for Crop Gene Resources and Genetic Improvement, Beijing 100081
  • Received:2021-07-21 Accepted:2021-08-09 Online:2022-02-01 Published:2022-02-11
  • Contact: RuiLian JING E-mail:lilong01@caas.cn;jingruilian@caas.cn

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Abstract: Roots are the vital organs for fixing the plant shoots and absorbing soil water and nutrients. The phenotypic characteristics of roots directly affect crop productivity and adaptability. Optimizing root phenotypes is considered to be one of the important ways to achieve the second “Green Revolution”. However, the invisibility, complexity and plasticity of root system greatly restrict the efficiency of root phenotyping, which makes the root optimization process lag far behind that of aboveground organs. With the rapid development of new technologies, i.e. spectral imaging, machine learning and three-dimensional reconstruction, the approaches to phenotyping roots gradually changed from traditional sampling observation to in-situ, nondestructive and automatic detection, and the evaluation basis expanded from two-dimensional morphological indices to three-dimensional parameters, which promoted the efficiency of root phenotyping and dramatically enriched the data of root phenotype. Meanwhile, the massive data exhibited problems, such as data redundancy and low use efficiency of information resources, which put forward new requirements, i.e. standardization and shareability, for root phenotype studies. This paper summarized the principles and technical keys of main approaches to phenotyping roots, and compared systematically in terms of precision, cost and throughput. The commonly used software for quantification of root phenotype were listed out from the aspects of license, operating platform, analysis mode and so on. The important research direction in the future was put forward, that is, to develop effective approaches to phenotyping roots in the field, to establish the evaluation system for root plasticity, to strengthen the identification and utilization of root anatomical characters, to strengthen the application of molecular detection techniques in root phenotyping, and to promote standardization of root phenotyping techniques and data sharing. The aim is to provide reference for the reasonable selection and improvement of approaches to phenotyping crop root system, so as to promote crop root improvement.


Key words: crop, root phenotype, phenotyping in the laboratory, phenotyping in the field, evaluation method

Fig. 1

Approaches for phenotyping root system architecture in the lab and the field The images of clear-pot and magnetic resonance imaging are cited from RICHARD et al.[15] and VAN DUSSCHOTEN et al.[20], respectively"

Table 1

Evaluation of approaches to phenotyping root system in the field"

方法
Method		 精确度
Accuracy		 工作量
Workload		 鉴定范畴
Scope		 动态性
Dynamic		 成本
Cost		 通量
Throughput
挖掘法 Excavation +++ +++ +++ --- --- ---
土芯法 Soil core ++ +++ + -- --- ---
网袋法 Mesh bag - ++ +++ --- -- --
小篮子法 Basket +++ +++ +++ --- - ---
剖面法 Soil profile ++ +++ ++ - --- ---
微根管法 Minirhizotron - + ++ +++ ++ +
电容法 Electrical capacitance -- --- - +++ - ++
探地雷达法 Ground-penetrating radar ? --- -- +++ +++ ++
替代性状法 Proxy trait --- --- --- +++ --- +++
+++：极高;---：极低;?：精确度与待测植物根直径有关
+++: Very high; ---: Very low; ?: The accuracy depends on the root diameter of the plant to be measured

Table 2

Commonly used software for root phenotype analysis"

软件
Software		 使用许可
License		 运行平台
Operating platform		 分析方式
Analysis mode		 批量处理
Batch		 三维成像
3D-imaging
ArchiDART[42] 免费、开源 Free, open-source Windows, Mac, Linux 自动化 Automated 能 Yes 不能 No
DART[43] 免费、闭源 Free, closed-source Windows, Mac, Linux 手动 Manual 不能 No 不能 No
DIRT[44] 免费、开源 Free, open-source Network platform 自动化 Automated 能 Yes 不能 No
DynamicRoots[45] 免费、开源 Free, open-source Windows 半自动化 Semi-automated 不能 No 能 Yes
EZ-Root-VIS[46] 免费、闭源 Free, closed-source Windows 半自动化 Semi-automated 不能 No 不能 No
GiA Roots[47] 免费、闭源 Free, closed-source Windows, Mac, Linux 自动化 Automated 能 Yes 不能 No
GT-RootS[48] 免费、开源 Free, open-source Windows, Mac, Linux 自动化 Automated 能 Yes 不能 No
iRoCS Toolbox[49] 免费、开源 Free, open-source Windows, Linux 半自动化 Semi-automated 不能 No 能 Yes
MyROOT[50] 免费、闭源 Free, closed-source Windows, Mac, Linux 半自动化 Semi-automated 能 Yes 不能 No
RhizoVision Crown[51] 免费、开源 Free, open-source Windows 自动化 Automated 能 Yes 不能 No
RootNav[52] 免费、开源 Free, open-source Windows 半自动化 Semi-automated 能 Yes 不能 No
RooTrak[53] 免费、闭源 Free, closed-source Windows 半自动化 Semi-automated 不能 No 能 Yes
RootReader2D[54] 免费、闭源 Free, closed-source Windows 半自动化 Semi-automated 能 Yes 不能 No
RootReader3D[55] 收费、闭源 Charge, closed-source Windows 自动化 Automated 不能 No 能 Yes
saRIA[56] 免费、闭源 Free, closed-source Windows, Linux 半自动化 Semi-automated 能 Yes 不能 No
SegRoot[36] 免费、开源 Free, open-source Windows, Mac, Linux 自动化 Automated 能 Yes 不能 No
SmartRoot[57] 免费、开源 Free, open-source Windows, Mac, Linux 半自动化 Semi-automated 不能 No 不能 No
WinRhizo[58] 收费、闭源 Charge, closed-source Windows 自动化 Automated 不能 No 不能 No

Fig. 2

User interface of commonly used software for root phenotype analysis"

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