Enhancing the potential of phenomic and genomic prediction in winter wheat breeding using high-throughput phenotyping and deep learning

Integrating high-throughput phenotyping (HTP) based traits into phenomic and genomic selection (GS) can accelerate the breeding of high-yielding and climate-resilient wheat cultivars. In this study, we explored the applicability of Unmanned Aerial Vehicles (UAV)-assisted HTP combined with deep learn...

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Autori principali:	Swas Kaushal, Harsimardeep S. Gill, Mohammad Maruf Billah, Shahid Nawaz Khan, Jyotirmoy Halder, Amy Bernardo, Paul St. Amand, Guihua Bai, Karl Glover, Maitiniyazi Maimaitijiang, Sunish K. Sehgal
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Frontiers Media S.A. 2024-05-01
Serie:	Frontiers in Plant Science
Soggetti:	wheat high-throughput phenotyping (HTP) based traits deep learning phenomic prediction deep neural network multi-trait genomic selection
Accesso online:	https://www.frontiersin.org/articles/10.3389/fpls.2024.1410249/full
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