Bolaji Osundahunsi
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Program Associate
Also affiliated: University of Arkansas System (2024–2026); International Institute of Tropical Agriculture (2025–2026); International Institute of Tropical Agriculture (2025–2026)
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Bolaji Osundahunsi's research focuses on plant pathology and virology, with a specific emphasis on understanding and managing viral threats to agricultural crops. His work has investigated biotic constraints to food production, particularly in systems such as taro in Nigeria. Osundahunsi has contributed to the development of diagnostic techniques for plant viruses, including the use of artificial positive controls in polymerase chain reaction (PCR) assays and the characterization of endogenous pararetroviruses in yam genomes. This research has implications for improving germplasm exchange by identifying and excluding "phantom agents" that could compromise regulatory processes. He has also participated in summits aimed at establishing unified frameworks for RNA virus biology, highlighting his engagement with broader scientific communities in the field.
Metrics
- h-index: 2
- Publications: 9
- Citations: 11
Positions
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Program Associate 2023–presentDivision of agriculture, University of Arkansas Department of plant pathology ORCID
Selected Publications
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Broadening the use of virus-mimicking artificial positive controls in plant virus diagnostics (2026)
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Diversity, recombination and misclassification in the family Geminiviridae: Insight from bioinformatics analysis (2026)
Collaboration Network
Top Collaborators
- Broadening the use of virus-mimicking artificial positive controls in plant virus diagnostics
- Broadening the use of virus-mimicking artificial positive controls in plant virus diagnostics
- Broadening the use of virus-mimicking artificial positive controls in plant virus diagnostics
- Broadening the use of virus-mimicking artificial positive controls in plant virus diagnostics
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