Experimental system and image analysis software for high throughput phenotyping of mycorrhizal growth response in Brachypodium distachyon

Abstract

Plant growth response to Arbuscular Mycorrhizal (AM) fungi is variable and depends on genetic and environment factors that still remain largely unknown. Identification of these factors can be envisaged using high-throughput and accurate plant phenotyping. We setup experimental conditions based on a two-compartment system allowing to measure Brachypodium distachyon mycorhizal growth response (MGR) in an automated phenotyping greenhouse. We developed a new image analysis software “IPSO Phen” to estimate of B. distachyon aboveground biomass. We found a positive MGR in the B. distachyon Bd3-1 genotype inoculated with the AM fungi Rhizophagus irregularis only if nitrogen and phosphorus were added together in the compartment restricted to AM fungi. Using this condition, we found genetic diversity in B. distachyon for MGR ranging from positive to negative MGR depending on the plant genotype tested. Our result on the interaction between nitrogen and phosphorus for MGR in B. distachyon opens new perspectives about AM functioning. In addition, our open-source software allowing to test and run image analysis parameters on large amount of images generated by automated plant phenotyping facilities, will help to screen large panels of genotypes and environmental conditions to identify the factors controlling the MGR.

Code and data availability

The paper's authors developed IPSO Phen, the image-analysis software used for their Brachypodium phenotyping measurements, and explicitly state its source code is freely available on GitHub at https://github.com/tpmp-inra/ipso_phen. This is a paper-specific, public, actionable analysis-code asset. Supplementary files (