Orobanche cumana (Orobanchaceae), commonly known as broomrape, is an obligate root holoparasitic plant that infests sunflower (Helianthus annuus), causing substantial yield losses in many regions of Europe and Asia. Its seed germination is triggered by chemical signals exuded by sunflower roots, including strigolactones (SLs) and sesquiterpene lactones (STLs) such as dehydrocostus lactone (DCL). In non-parasitic […]

Striga hermonthica is a destructive parasitic weed that threatens cereal production and food security in Sub-Saharan Africa. One promising control method is “Suicidal Germination” which forces Striga seeds to germinate in host’s absence, reducing the soil seed bank. As the efficiency of strigolactones (SLs) is often limited by seed dormancy, we tested whether the ethylene […]

I am beyond thrilled to share with you this exciting news/paper hot off the press: our efforts to propagate Rafflesia, the charismatic, critically endangered “panda of the plant world” and the largest flower on Earth, have finally paid off! Molina, J. et al. (2026) “Growing a plant you cannot see: ex situ propagation of the endoparasite […]

Plants interact ubiquitously with organisms surrounding them through chemical communication, for example through the emission of volatile organic compounds (VOCs) by flowers, to attract pollinators. To attain specificity in this relationship, plants may evolve different VOCs for different pollinators. In the present study we investigated the flower VOCs of the root parasitic butterbur broomrape (Orobanche […]

Striga hermonthica is a major constraint to cereal production in sub-Saharan Africa, particularly under low-fertility conditions. In this study, we evaluated biological and nutrient-based approaches to suppress Striga and improve sorghum growth. The arbuscular mycorrhizal fungus Glomus mosseae significantly reduced Striga emergence (up to 100%) and biomass, while greatly enhancing sorghum growth. The phosphorus-solubilizing bacterium […]

Our study demonstrates the effectiveness of hyperspectral imaging combined with machine learning for identifying and classifying parasitic Cuscuta species. The findings highlight the potential of this approach for rapid, non-destructive field diagnostics and precision agriculture applications. As imaging hardware continues to improve and become more affordable, such integrated systems could be deployed in real-world crop […]