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A Comparative Analysis of Quantitative Metrics of Root Architecture

作     者:Harini Rangarajan Jonathan P.Lynch 

作者机构:Department of Plant ScienceThe Pennsylvania State UniversityUniversity ParkPA 16802USA 

出 版 物:《Plant Phenomics》 (植物表型组学(英文))

年 卷 期:2021年第3卷第1期

页      面:65-85页

核心收录:

学科分类:0710[理学-生物学] 071001[理学-植物学] 07[理学] 

基  金:supported by the National Institute of Food and Agriculture the U.S.Department of Agriculture Hatch project 4732 the Foundation for Food and Agriculture Research "Crops in Silico" project 

主  题:aggregate projection estimates 

摘      要:High throughput phenotyping is important to bridge the gap between genotype and *** methods used to describe the phenotype therefore should be robust to measurement errors,relatively stable over time,and most importantly,provide a reliable estimate of elementary phenotypic *** this study,we use functional-structural modeling to evaluate quantitative phenotypic metrics used to describe root architecture to determine how they fit these *** results show that phenes such as root number,root diameter,and lateral root branching density are stable,reliable measures and are not affected by imaging method or *** aggregating multiple phenes such as total length,total volume,convex hull volume,and bushiness index estimate different subsets of the constituent phenes;they however do not provide any information regarding the underlying phene *** of phene aggregates are not unique representations of underlying constituent phenes:multiple phenotypes having phenes in different states could have similar aggregate *** growth angle is an important phene which is susceptible to measurement errors when 2D projection methods are *** that aggregate phenes which are complex functions of root growth angle and other phenes are also subject to measurement errors when 2D projection methods are *** results support the hypothesis that estimates of phenes are more useful than metrics aggregating multiple phenes for phenotyping root *** propose that these concepts are broadly applicable in phenotyping and phenomics.

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