Improving predictive ability in sparse testing designs in soybean populations

Improving predictive ability in sparse testing designs in soybean populations

The availability of high-dimensional genomic data and advancements in genome-based prediction models (GP) have revolutionized and contributed to accelerated genetic gains in soybean breeding programs. GP-based sparse testing is a promising concept that allows increasing the testing capacity of genot...

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Bibliographic Details
Main Authors: Reyna Persa, Caio Canella Vieira, Esteban Rios, Valerio Hoyos-Villegas, Carlos D. Messina, Daniel Runcie, Diego Jarquin
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-11-01
Series:Frontiers in Genetics
Subjects:
sparse testing
genomic prediction
plant breeding
soybean
experimental design
genotype-by-environment interaction
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2023.1269255/full

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https://www.frontiersin.org/articles/10.3389/fgene.2023.1269255/full

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