Fungi Associated with the Deterioration of Zea Mays L. (Maize) From Market Stores in Abeokuta, Ogun State, Nigeria.

This study addressed the characterization of fungi associated with fungal contamination of maize. The diversity of fungal species responsible for maize spoilage necessitates effective control measures; however, their efficacy remains uncertain. Molecular identification of fungal populations provides essential data for predicting disease incidence and assessing potential risks. Accurate characterization of fungal species is crucial for identifying pathogenic strains in maize samples. Stored maize samples were obtained from four markets in Abeokuta- Kuto, Lafenwa, Olomore, and Osiele. Samples were labeled according to their locations. Fungal isolations were performed using the serial dilution method on Potato Dextrose Agar (PDA). Microscopic identification was based on colony morphology. molecular and macroscopic analyses confirmed 100% fungal contamination in all maize samples. The predominant fungal genera identified included Aspergillus, Fusarium, Rhizopus, Penicillium, Mucor, and Cladosporium species. The prevalence of these fungi was consistent across all the sampled locations, highlighting their widespread occurrence in stored maize from Abeokuta markets. The significance of these results were discussed.

Authors

Publication Details

Journal
International Journal of Research and Innovation in Applied Science
Published
2025-01-01
DOI
https://doi.org/10.51584/ijrias.2025.10030063
Primary Topic
Food composition and properties
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fungi Associated with the Deterioration of Zea Mays L. (Maize) From Market Stores in Abeokuta, Ogun State, Nigeria.

Eguavon Mi, Segun Gbolagade Jonathan, Ade-Ogunnowo FE, Omeonu FC Omeonu FC et al.
International Journal of Research and Innovation in Applied Science
Food composition and properties
article

Fungi Associated with the Deterioration of Zea Mays L. (Maize) From Market Stores in Abeokuta, Ogun State, Nigeria.

Eguavon Mi, Segun Gbolagade Jonathan, Ade-Ogunnowo FE, Omeonu FC Omeonu FC, Olabanji IT, Oladayo IA, Salaam SM Salaam SM
article en

Abstract

This study addressed the characterization of fungi associated with fungal contamination of maize. The diversity of fungal species responsible for maize spoilage necessitates effective control measures; however, their efficacy remains uncertain. Molecular identification of fungal populations provides essential data for predicting disease incidence and assessing potential risks. Accurate characterization of fungal species is crucial for identifying pathogenic strains in maize samples. Stored maize samples were obtained from four markets in Abeokuta- Kuto, Lafenwa, Olomore, and Osiele. Samples were labeled according to their locations. Fungal isolations were performed using the serial dilution method on Potato Dextrose Agar (PDA). Microscopic identification was based on colony morphology. molecular and macroscopic analyses confirmed 100% fungal contamination in all maize samples. The predominant fungal genera identified included Aspergillus, Fusarium, Rhizopus, Penicillium, Mucor, and Cladosporium species. The prevalence of these fungi was consistent across all the sampled locations, highlighting their widespread occurrence in stored maize from Abeokuta markets. The significance of these results were discussed.

International Journal of Research and Innovation in Applied ScienceVol. X(III)
Openalex Percentile: Top 91%
Food composition and properties
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.