(Poly)phenol-rich extracts from six tropical fruits: antifungal and antimycotoxin activity against Fusarium verticillioides
-
Katherine Gómez-Pérez
,
Sharlyn Sánchez-Murillo
,
Cinthia Sandí-Bolaños
,
Maude Chegnimonhan
,
Víctor M. Jiménez
,
María Vinas
and
Andrea Irías-Mata
Abstract
(Poly)phenol from tropical fruits have attracted attention for their antioxidant and antimicrobial properties, offering potential solutions to food safety risks posed by microorganisms and mycotoxins. Using a validated and streamlined ultra high-performance liquid chromatography coupled to diode array and tandem mass spectrometry with electrospray ionization (UHPLC-DAD-ESI-MS/MS) protocol, targeted (poly)phenol with antimicrobial and antimycotoxin potential were analyzed in six tropical fruits (Annona muricata, Anacardium occidentale, Byrsonima crassifolia, Elaeis guineensis, Hylocereus costaricensis, and Spondias purpurea). The (poly)phenol-rich extracts of the most promising ones according to their total (poly)phenol content, namely A. occidentale, B. crassifolia, and H. costaricensis, were further evaluated for their antifungal and antimycotoxin activities. Bioassays revealed antifungal activity against Fusarium verticillioides and inhibition of fumonisin B1 (FB1) accumulation. When applied to maize and rice grains, these extracts provided protection, although efficacy decreased over time (after 45 days), likely due to (poly)phenol degradation. The antifungal and antimycotoxin effects may be attributed to the combined action of multiple (poly)phenol, which are abundant in these fruits.
Funding source: Vicerrectoría de Investigación, Universidad de Costa Rica
Award Identifier / Grant number: Project 734-C1-453
Acknowledgments
The authors thank Amancio Alvarado (ASD, Costa Rica) and Marvin Araya (pitahaya farmer) for supply the materials of Elaeis guineensis and Hylocereus costaricensis, respectively, for this research.
-
Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: Conceptualization, M.V. and A.I-M.; methodology, K.G-P, S.S-M, C. S-B, M.C, M.V. and A.I-M.; validation, K.G-P and A.I-M.; formal analysis, K.G-P, S.S-M, M.V, A.I-M.; investigation, K.G-P, S.S-M, C.S-B, M.C, M.V, A.I-M; resources, M.V.; data curation, K.G-P, S.S-M, M.V, A.I-M.; writing – original draft preparation, V.J, M.V, A.I-M.; writing – review and editing, V.J, M.V, A.I-M.; visualization, V.J, M.V, A.I-M.; supervision, V.J, M.V, A.I-M.; project administration, M.V.; funding acquisition, M.V. All authors have read and agreed to the published version of the manuscript.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors state no conflict of interest. Neither the funders nor the sample suppliers had any role in the design of the study; in the collection, analysis, or interpretation of the data; in the writing of the manuscript; or in the decision to publish the results.
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Research funding: This research was funded by the Vicerrectoría de Investigación, Universidad de Costa Rica, grant for the project 734-C1-453.
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Data availability: The datasets of the current study are available from the corresponding author on reasonable request.
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