Computer vision and machine learning enabled soybean root phenotyping pipeline

BACKGROUND: Root system architecture (RSA) traits are of interest for breeding selection; however, measurement of these traits is difficult, resource intensive, and results in large variability. The advent of computer vision and machine learning (ML) enabled trait extraction and measurement has rene...

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Detalles Bibliográficos
Autores principales: Falk, Kevin G., Jubery, Talukder Z., Mirnezami, Seyed V., Parmley, Kyle A., Sarkar, Soumik, Singh, Arti, Ganapathysubramanian, Baskar, Singh, Asheesh K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Methodology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6977263/
https://www.ncbi.nlm.nih.gov/pubmed/31993072
http://dx.doi.org/10.1186/s13007-019-0550-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6977263/
https://www.ncbi.nlm.nih.gov/pubmed/31993072
http://dx.doi.org/10.1186/s13007-019-0550-5

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