Metabolite detection via QTOF-LCMS and computational analysis on Russelia equisetiformis exploring green nanotechnology and antifungal against phytopathogens
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Le résumé fourni par la source
This study explores Russelia equisetiformis as a sustainable source for the green synthesis of antifungal nanomaterials. In response to increasing phytopathogenic fungi and environmental issues, it focuses on the fabrication of manganese nanoparticles (MnONPs), nitrogen-doped carbon dots (N-CDs), and their nanocomposite (MnO NPs@N-CDs) using R. equisetiformis extract. The synthesized nanomaterials were characterized by UV–Vis spectrophotometry, FTIR, DLS, TEM, and EDX to confirm nanoparticle formation. Their antifungal effectiveness was evaluated against Sclerotinia sclerotiorum, Fusarium equiseti, and Fusarium venenatum. Additionally, bioactive metabolites were identified via LC–QTOF-MS, and their antifungal activity, pharmacokinetic profiles, and toxicity levels were assessed through computational tools. Nanomaterials produced from R. equisetiformis extract significantly reduced fungal growth, highlighting their potential as eco-friendly solutions for plant disease control. Most metabolites exhibited favorable safety profiles with minimal predicted cardiotoxicity and mutagenicity, indicating their promise as safe fungicides. R. equisetiformis provides compounds with effective antifungal activity and low toxicity, offering a promising, environmentally friendly alternative to conventional chemical fungicides for sustainable plant disease management. Further research is essential to expand their application in agriculture.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Metabolite detection via QTOF-LCMS and computational analysis on Russelia equisetiformis exploring green nanotechnology and antifungal against phytopathogens
- Date Crossref
- 09/10/2025
- Éditeur
- Springer Science and Business Media LLC
- Type
- journal-article
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