Abstract

Root system architecture traits (RSAT) are crucial for crop productivity, especially under drought and low soil fertility. The "shovelomics" method of field excavation of mature root crowns followed by manual phenotyping enables a relatively high throughput as needed for breeding and quantitative genetics. We aimed to develop a new sampling protocol in combination with digital imaging and new software.Sampled rootstocks were split lengthwise, photographed under controlled illumination in an imaging tent and analysed using Root Estimator for Shovelomics Traits (REST). A set of 33 diverse maize hybrids, grown at 46 and 192 kg N ha(-1), was used to evaluate the method and software.Splitting of the crowns enhanced soil removal and enabled access to occluded traits: REST-derived median gap size correlated negatively (r = -0.62) with lateral root density based on counting. The manually measured root angle correlated with the image-derived root angle (r = 0.89) and the horizontal extension of the root system (r = 0.91). The heritabilities of RSAT ranged from 0.45 to 0.81, comparable to heritabilities of plant height and leaf biomass.The combination of the novel crown splitting method, combined with imaging under controlled illumination followed by automatic analysis with REST, allowed for higher throughput while maintaining precision. The REST Software is available as supplement.

Keywords

Root system architecture; Maize; Automated phenotyping; Image processing; Heritability

Published in

Plant and Soil
2015, Volume: 388, number: 1-2, pages: 1-20

UKÄ Subject classification

Botany


Publication identifier

DOI: https://doi.org/10.1007/s11104-015-2379-7

Permanent link to this page (URI)

https://res.slu.se/id/publ/94820