d. PCA was performed using SAS procedure PROC FACTOR and clustering was done using PROC CLUSTER with Ward’s minimum-variance method. The dendrogram was constructed with PROC TREE. Acknowledgments Publication was supported by BOKU Vienna’s Open Access Publishing Fund. Supplementary Materials The following are available online at https://www.mdpi.com/2223-7747/8/11/514/s1 , Figure S1: Root length distribution over diameter for ten different cover crop species from rhizobox imaging. Click here for additional data file. Author Contributions G.B., W.L., E.E., W.H. and M.S. commonly conceptualized the manuscript. Evaluation of the data and writing of the original draft were done by G.B. Data and d
Open resource ↗MDPI · lines:311-336Unverified paper record
Characterization of Cover Crop Rooting Types from Integration of Rhizobox Imaging and Root Atlas Information
Plants · 17 Nov 2019 · 10.3390/plants8110514
Abstract
Plant root systems are essential for sustainable agriculture, conveying resource-efficient genotypes and species with benefits to soil ecosystem functions. Targeted selection of species/genotypes depends on available root system information. Currently there is no standardized approach for comprehensive root system characterization, suggesting the need for data integration across methods and sources. Here, we combine field measured root descriptors from the classical Root Atlas series with traits from controlled-environment root imaging for 10 cover crop species to (i) detect descriptors scaling between distant experimental methods, (ii) provide traits for species classification, and (iii) discuss implications for cover crop ecosystem functions. Results revealed relation of single axes measures from root imaging (convex hull, primary-lateral length ratio) to Root Atlas field descriptors (depth, branching order). Using composite root variables (principal components) for branching, morphology, and assimilate investment traits, cover crops were classified into species with (i) topsoil-allocated large diameter rooting type, (ii) low-branched primary/shoot-born axes-dominated rooting type, and (iii) highly branched dense rooting type, with classification trait-dependent distinction according to depth distribution. Data integration facilitated identification of root classification variables to derive root-related cover crop distinction, indicating their agro-ecological functions.
Plant phenotyping relevance
根系画像計測と既存Root Atlas記述子を統合し、異なる計測法間の対応を評価して根系形態形質による分類を行っており、植物表現型の取得・統合が研究の中心である。
abstractHere, we combine field measured root descriptors from the classical Root Atlas series with traits from controlled-environment root imaging for 10 cover crop species to (i) detect descriptors scaling between distant experimental methods
abstractResults revealed relation of single axes measures from root imaging (convex hull, primary-lateral length ratio) to Root Atlas field descriptors (depth, branching order).
Code and data availability
The paper's rhizobox imaging measurements and Root Atlas trait tables are presented in-text, and the authors point to a public MDPI supplementary file (Figure S1: root length distribution over diameter for the ten cover crop species from rhizobox imaging) as the only explicitly deposited paper-specific asset. No author
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