ArticlePlant methods2021
Image analysis for the automatic phenotyping of Orobanche cumana tubercles on sunflower roots.
Article in Plant methods, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 17 citations in OpenAlex.
- Large-scale exchange of RNA between parasitic plant Orobanche cumana and its host Helianthus annuus.Pest management science · 2026Article
- Machine Learning-Based identification of resistance genes associated with sunflower broomrape.Plant methods · 2025Article
- A cluster of putative resistance genes is associated with a dominant resistance to sunflower broomrape.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Development and characterization of a new sunflower source of resistance to race G of Orobanche cumana Wallr. derived from Helianthus anomalus.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- WildFrontiers in plant science · 2022Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe parasitic plant Orobanche cumana is one of the most important threats to sunflower crops in Europe. Resistant sunflower varieties have been developed, but new O. cumana races have evolved and have overcome introgressed resistance genes, leading to the recurrent need for new resistance methods. Screening for resistance requires the phenotyping of thousands of sunflower plants to various O. cumana races. Most phenotyping experiments have been performed in fields at the later stage of the interaction, requiring time and space. A rapid phenotyping screening method under controlled conditions would need less space and would allow screening for resistance of many sunflower genotypes. Our study proposes a phenotyping tool for the sunflower/O. cumana interaction under controlled conditions through image analysis for broomrape tubercle analysis at early stages of the interaction.
resultsWe optimized the phenotyping of sunflower/O. cumana interactions by using rhizotrons (transparent Plexiglas boxes) in a growth chamber to control culture conditions and Orobanche inoculum. We used a Raspberry Pi computer with a picamera for acquiring images of inoculated sunflower roots 3 weeks post inoculation. We set up a macro using ImageJ free software for the automatic counting of the number of tubercles. This phenotyping tool was named RhizOSun. We evaluated five sunflower genotypes inoculated with two O. cumana races and showed that automatic counting of the number of tubercles using RhizOSun was highly correlated with manual time-consuming counting and could be efficiently used for screening sunflower genotypes at the tubercle stage.
conclusionThis method is rapid, accurate and low-cost. It allows rapid imaging of numerous rhizotrons over time, and it enables image tracking of all the data with time kinetics. This paves the way toward automatization of phenotyping in rhizotrons that could be used for other root phenotyping, such as symbiotic nodules on legumes.
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