Journal Article

FZJ-2017-01740

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Root architecture simulation improves the inference from seedling root phenotyping towards mature root systems

Zhao, J. ; Bodner, G. (Corresponding author) ; Rewald, B. ; Leitner, D. ; Nagel, K.FZJ* ; Nakhforoosh, A.

2017
Oxford Univ. Press Oxford

This record in other databases:      

Please use a persistent id in citations: http://hdl.handle.net/2128/14197  doi:10.1093/jxb/erw494

Abstract: Root phenotyping provides trait information for plant breeding. A shortcoming of high-throughput root phenotyping is the limitation to seedling plants and failure to make inferences on mature root systems. We suggest root system architecture (RSA) models to predict mature root traits and overcome the inference problem. Sixteen pea genotypes were phenotyped in (i) seedling (Petri dishes) and (ii) mature (sand-filled columns) root phenotyping platforms. The RSA model RootBox was parameterized with seedling traits to simulate the fully developed root systems. Measured and modelled root length, first-order lateral number, and root distribution were compared to determine key traits for model-based prediction. No direct relationship in root traits (tap, lateral length, interbranch distance) was evident between phenotyping systems. RootBox significantly improved the inference over phenotyping platforms. Seedling plant tap and lateral root elongation rates and interbranch distance were sufficient model parameters to predict genotype ranking in total root length with an RSpearman of 0.83. Parameterization including uneven lateral spacing via a scaling function substantially improved the prediction of architectures underlying the differently sized root systems. We conclude that RSA models can solve the inference problem of seedling root phenotyping. RSA models should be included in the phenotyping pipeline to provide reliable information on mature root systems to breeding research.

---

Contributing Institute(s):

1. Pflanzenwissenschaften (IBG-2)

Research Program(s):

1. 582 - Plant Science (POF3-582) (POF3-582)
2. EPPN - European Plant Phenotyping Network (284443) (284443)

Appears in the scientific report 2017

---

Database coverage:
; ; ; Allianz-Lizenz / DFG ; BIOSIS Previews ; Current Contents - Agriculture, Biology and Environmental Sciences ; Current Contents - Life Sciences ; Ebsco Academic Search ; IF >= 5 ; JCR ; NCBI Molecular Biology Database ; National-Konsortium ; Nationallizenz ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Thomson Reuters Master Journal List ; Web of Science Core Collection

---