Untargeted LC-HRMS/MS and Feature-Based Molecular Networking Reveal Distinct Metabolic Signatures in Edible Dahlia Types
Abstract Edible flowers represent chemically diverse food matrices whose characterization increasingly relies on advanced metabolomic approaches. This study employed untargeted liquid chromatography–high-resolution tandem mass spectrometry (LC-HRMS/MS) combined with feature-based molecular networking (FBMN) to characterize and differentiate the metabolic profiles of flowers and roots from five edible dahlia types cultivated under organic conditions. Biochemical composition, antioxidant properties, and enzymatic activities were evaluated and integrated with metabolomic data to investigate chemical diversity among plant organs and genotypes. Flowers exhibited high concentrations of anthocyanins, carotenoids, vitamin C, and phenolic compounds, with red pompom and yellow pompom showing particularly distinctive bioactive profiles. In contrast, red decorative roots were distinguished by their high inulin content and relatively high carotenoid concentrations. FBMN enabled the annotation and visualization of metabolite distributions, revealing clear differences among dahlia types and plant organs. Glycosylated flavonoids and anthocyanins predominated in red pompom and purple decorative flowers, whereas flavonoid aglycones were more abundant in yellow flower types. Aromatic amino acids were primarily associated with root tissues. Correlation analyses revealed associations between bioactive compounds and antioxidant responses, providing additional evidence for the functional differences observed among Dahlia types. The integrated LC-HRMS/MS and FBMN workflow successfully differentiated edible dahlia types by chemical composition and revealed distinct metabolic signatures associated with specific plant organs and genotypes. These findings highlight the applicability of metabolomic profiling and molecular networking for food characterization and provide a framework for identifying bioactive-rich edible plant materials.
Authors
- Vytória Piscitelli Cavalcanti (ORCID: https://orcid.org/0000-0003-4539-2477)
- Luciane Vilela Resende (ORCID: https://orcid.org/0000-0002-2014-4453)
- Paula Aparecida Costa (ORCID: https://orcid.org/0000-0003-4335-8814)
- Thamirys Silva da Fonseca (ORCID: https://orcid.org/0000-0002-6523-6749)
- Betsy Carolina Muñoz de Páez (ORCID: https://orcid.org/0000-0003-0081-6141)
- Marcelo Henrique Avelar Mendes (ORCID: https://orcid.org/0000-0001-5929-4371)
- Suzana Guimarães Leitão (ORCID: https://orcid.org/0000-0001-7445-074X)
- Simony Carvalho Mendonça (ORCID: https://orcid.org/0000-0001-7195-1629)
- Maria Lígia de Souza Silva (ORCID: https://orcid.org/0000-0003-1414-4219)
- Fabiana Alves Silva
- Cleyton Lourenço de Oliveira
Institutions
- Universidade Federal do Rio de Janeiro (BR)
- Universidade Federal de Lavras (BR)
- Instituto Federal Goiano (BR)
- Instituto de Ciências Farmacêuticas (BR)
Publication Details
- Journal
- Food Analytical Methods
- Published
- 2026-09-24
- DOI
- https://doi.org/10.1007/s12161-026-03280-9
- Primary Topic
- Plant Gene Expression Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00