Author

S. A. Atanda

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Pathology· 1 Plant Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:deep learning· 1 Approach:experimental assay· 1 Assay:imaging· 1 Organism:plant (other)· 1

Frequent Co-Authors

H. Worral· 2 shared L. Piche· 2 shared M. Morales· 2 shared N. Bandillo· 2 shared P. Flores· 2 shared C. Ramos· 1 shared C. Yan· 1 shared D. Fonseka· 1 shared

Activity by Year

2022-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 39 mutual co-author links

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2 shared papersPlant Biology

H. Worral

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2 papers

Recent·Most cited

High-Throughput Phenotyping of Seed Quality Traits Using Imaging and Deep Learning in Dry Pea

M. Morales, H. Worral, L. Piche, S. A. Atanda, F. Dariva, C. Ramos, K. Hoang, C. Yan, P. Flores, N. Bandillo

This paper develops an automated seed quality assessment tool for dry peas using imaging and deep learning, achieving high accuracy and efficiency compared to traditional methods.

bioRxiv · Mar 5, 2024 · PreprintPlant Biology

A greenhouse-based high-throughput phenotyping platform for identification and genetic dissection of resistance to Aphanomyces root rot in field pea

M. A. A. Bari, D. Fonseka, J. Stenger, K. Zitnick-Anderson, S. A. Atanda, H. Worral, L. Piche, J. Kim, M. Morales, J. Johnson, R. A. Saludares, P. Flores, J. Pasche, N. Bandillo

This study develops a high-throughput phenotyping platform to assess Aphanomyces root rot resistance in field pea, identifies 260 SNPs associated with resistance, and discovers both known and novel genes involved in immunity.

bioRxiv · Aug 1, 2022 · PreprintPathology