Deep learning-based phenotyping for genome wide association studies of sudden death syndrome in soybean

Deep learning-based phenotyping for genome wide association studies of sudden death syndrome in soybean

Using a reliable and accurate method to phenotype disease incidence and severity is essential to unravel the complex genetic architecture of disease resistance in plants, and to develop disease resistant cultivars. Genome-wide association studies (GWAS) involve phenotyping large numbers of accession...

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Bibliographic Details
Main Authors: Ashlyn Rairdin, Fateme Fotouhi, Jiaoping Zhang, Daren S. Mueller, Baskar Ganapathysubramanian, Asheesh K. Singh, Somak Dutta, Soumik Sarkar, Arti Singh
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-10-01
Series:Frontiers in Plant Science
Subjects:
stress phenotyping
disease quantification
object detection
foreground detection
ROC analysis
image-based phenotyping
Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2022.966244/full

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https://www.frontiersin.org/articles/10.3389/fpls.2022.966244/full

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