Mega-environment analysis to assess adaptability, stability, and genomic predictions in grain sorghum hybrids

Authors: OLIVERIRA FONSECA, JALES - Texas A&M University; PERUMAL, RAMASAMAY - Kansas State University; KLEIN, PATRICIA - Texas A&M Agrilife; Klein, Robert - Bob; ROONEY, WILLIAM - Texas A&M University

Submitted to: Euphytica
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/19/2022
Publication Date: 8/17/2022
Citation: Oliverira Fonseca, J.M., Perumal, R., Klein, P.E., Klein, R.R., Rooney, W.L. 2022. Mega-environment analysis to assess adaptability, stability, and genomic predictions in grain sorghum hybrids. Euphytica. 218:128. https://doi.org/10.21203/rs.3.rs-1157295/v1.
DOI: https://doi.org/10.21203/rs.3.rs-1157295/v1

Interpretive Summary: The yield potential in grain sorghum hybrids has increased at a slower rate than other cereal crops including its close relative maize. While there are many reasons for this lag, increasing hybrid performance through mathematical modeling of genetic and environmental factors that control grain yield is commonly hypothesized as a way to boost the rate of gain. To address this issue, we developed equations that utilize genetic and environmental data to predict the performance of offspring from specific parental lines grown in a series of field locations. This study will provide the necessary knowledge to breeders who work to exploit genetic diversity and environmental data in improving grain yield of hybrid cereal crops including sorghum.

Technical Abstract: Multi-environment trials are fundamental for assessing genotype-by-environment interaction effects, adaptability and stability of genotypes and provide valuable information about target regions. As such, a multi-environments trial involving grain sorghum hybrid combinations derived from elite inbred lines adapted to diverse sorghum production regions was developed to assess agronomic performance, stability, and genomic-enabled prediction accuracies within mega-environments. Five females and five males from Texas A&M and Kansas State sorghum breeding programs were crossed following a factorial mating scheme to generate 100 hybrids. Grain yield, plant height, and days to anthesis were assessed in ten environments across Texas and Kansas over two years. A genomic prediction model including the genotype x environment effect was applied within mega-environments to assess prediction accuracy. Results suggest that grain sorghum hybrid combinations involving lines bred for geographical regions can produce superior hybrids. Mega-environments analysis identified established grain sorghum production regions in the U.S. Further, genomic predictions within mega-environments reported inconsistent results, suggesting that additional effects rather than the correlations between environments are influencing genomic prediction of grain sorghum hybrids.