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Linear discriminant analysis reveals differences in root architecture in wheat seedlings related to nitrogen uptake efficiency.


ABSTRACT: Root architecture impacts water and nutrient uptake efficiency. Identifying exactly which root architectural properties influence these agronomic traits can prove challenging. In this paper, approximately 300 wheat (Triticum aestivum) plants were divided into four groups using two binary classifications, high versus low nitrogen uptake efficiency (NUpE), and high versus low nitrate in the growth medium. The root system architecture for each wheat plant was captured using 16 quantitative variables. The multivariate analysis tool, linear discriminant analysis, was used to construct composite variables, each a linear combination of the original variables, such that the score of the plants on the new variables showed the maximum between-group variability. The results show that the distribution of root-system architecture traits differs between low- and high-NUpE plants and, less strongly, between low-NUpE plants grown on low versus high nitrate media.

SUBMITTER: Kenobi K 

PROVIDER: S-EPMC5853436 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Linear discriminant analysis reveals differences in root architecture in wheat seedlings related to nitrogen uptake efficiency.

Kenobi Kim K   Atkinson Jonathan A JA   Wells Darren M DM   Gaju Oorbessy O   De Silva Jayalath G JG   Foulkes M John MJ   Dryden Ian L IL   Wood Andrew T A ATA   Bennett Malcolm J MJ  

Journal of experimental botany 20171001 17


Root architecture impacts water and nutrient uptake efficiency. Identifying exactly which root architectural properties influence these agronomic traits can prove challenging. In this paper, approximately 300 wheat (Triticum aestivum) plants were divided into four groups using two binary classifications, high versus low nitrogen uptake efficiency (NUpE), and high versus low nitrate in the growth medium. The root system architecture for each wheat plant was captured using 16 quantitative variable  ...[more]

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