Author

Olivia E. Todd

Agricultural Research ServiceORCID 0000-0002-5727-1886Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Research Focus:cell type annotation· 1 Research Focus:GWAS / association mapping· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Organism:plant (other)· 1 Approach:statistical model· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Kevin DorniD· 2 shared Brian E. ScheffleriD· 1 shared Linda E. HansoniD· 1 shared Sheron SimpsoniD· 1 shared

Activity by Year

2024-2024 · peak 2/yr

Co-Author Collaboration Network

4 top collaborators · 4 mutual co-author links

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2 shared papersPlant Biology

Kevin DornORCID

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2 papers

Recent·Most cited

Plant BiologyDNA ResearchPeer-reviewedNov 25, 2024

A fully phased, chromosome-scale genome of sugar beet line FC309 enables the discovery of Fusarium Yellows resistance QTL

Olivia E. Todd, Sheron Simpson, Brian E. Scheffler, Kevin Dorn

The paper presents a chromosome-scale, haplotype-phased genome of sugar beet line FC309 and identifies a QTL for Fusarium Yellows resistance on Chromosome 3.

3 citations

plant (other)whole-genome sequencing

𝕏 PostBluesky

Plant BiologyPlant PathologyPeer-reviewedNov 4, 2024

A standard area diagram for Fusarium yellows rating in sugar beet (Beta vulgaris L.)

Olivia E. Todd, Linda E. Hanson, Kevin Dorn

This paper develops a standard area diagram (SAD) to improve the accuracy and precision of Fusarium yellows disease rating in sugar beet, showing no statistical difference between two SAD versions and demonstrating machine learning models' congruency with human estimates.

3 citations

imagingmachine learning (classical)

𝕏 PostBluesky