A scanner system for high-resolution quantification of
variation in root growth dynamics of Brassica rapa genotypes

Adu, Michael Osei; Chatot, Antoine; Wiesel, Lea; Bennett, Malcolm J.; Broadley, Martin R.; White, Philip J.; Dupuy, Lionel X.

Abstract

The potential exists to breed for root system architectures that optimize resource acquisition. However, this requires the ability to screen root system development quantitatively, with high resolution, in as natural an environment as possible, with high throughput. This paper describes the construction of a low-cost, high-resolution root phenotyping platform, requiring no sophisticated equipment and adaptable to most laboratory and glasshouse environments, and its application to quantify environmental and temporal variation in root traits between genotypes of Brassica rapa L. Plants were supplied with a complete nutrient solution through the wick of a germination paper. Images of root systems were acquired without manual intervention, over extended periods, using multiple scanners controlled by customized software. Mixed-effects models were used to describe the sources of variation in root traits contributing to root system architecture estimated from digital images. It was calculated that between one and 43 replicates would be required to detect a significant difference (95% CI 50% difference between traits). Broad-sense heritability was highest for shoot biomass traits (>0.60), intermediate (0.25–0.60) for the length and diameter of primary roots and lateral root branching density on the primary root, and lower (<0.25) for other root traits. Models demonstrate that root traits show temporal variations of various types. The phenotyping platform described here can be used to quantify environmental and temporal variation in traits contributing to root system architecture in B. rapa and can be extended to screen the large populations required for breeding for efficient resource acquisition.

Citation

variation in root growth dynamics of Brassica rapa genotypes. Journal of Experimental Botany, 65(8), 2039-2048. https://doi.org/10.1093/jxb/eru048

• Journal Article Type: Article
• Acceptance Date: Jan 20, 2014
• Online Publication Date: Mar 6, 2014
• Publication Date: Jan 1, 2014
• Deposit Date: Nov 18, 2016
• Publicly Available Date: Nov 18, 2016
• Journal: Journal of Experimental Botany
• Print ISSN: 0022-0957
• Electronic ISSN: 1460-2431
• Publisher: Oxford University Press
• Peer Reviewed: Peer Reviewed
• Volume: 65
• Issue: 8
• Pages: 2039-2048
• DOI: https://doi.org/10.1093/jxb/eru048
• Keywords: Architecture, high-resolution, high throughput, model, nitrogen, phenotyping, phosphorus, root
• Public URL: https://nottingham-repository.worktribe.com/output/725534
• Publisher URL: http://jxb.oxfordjournals.org/content/65/8/2039
• Contract Date: Nov 18, 2016