Coupling day length data and genomic prediction tools for predicting time-related traits under complex scenarios.

ABSTRACT: Genomic selection (GS) has proven to be an efficient tool for predicting crop-rank performance of untested genotypes; however, when the traits have intermediate optima (phenology stages), this implementation might not be the most convenient. GS might deliver high-rank correlations but incurring in serious bias. Days to heading (DTH) is a crucial development stage in rice for regional adaptability with a significant impact on yield potential. The objective of this research consisted in develop a novel method that accurately predicts time-related traits such as DTH in unobserved environments. For this, we propose an implementation that incorporates day length information (DL) in the prediction process for two relevant scenarios: CV0, predicting tested genotypes in unobserved environments (C

SUBMITTER: Jarquin D 

PROVIDER: S-EPMC7415153 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature