Using historical phenotypic data and environmental information for genomic prediction in biomass sorghum

• Ano de defesa: 2022
• Autor(a) principal: Ribeiro, Pedro César de Oliveira
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal de Viçosa; Genética e Melhoramento
• Palavras-chave em Português: Sorghum bicolor - Melhoramento genético; Sorghum bicolor - Seleção; Genômica; Melhoramento Vegetal
• Link de acesso: https://locus.ufv.br//handle/123456789/31544; https://doi.org/10.47328/ufvbbt.2022.630

Energy sorghum is currently considered a promising alternative crop for generating bioenergy, due to its high biomass yield, has high concentrations of fermentable sugars in its stalks and desirable agro-industrial features, such as short growth cycle, high calorific value, and total crop mechanization. Therefore, the breeding programs are interested in developing new hybrids of sweet and biomass sorghum for a wide range of environmental conditions, however, the cost of the field-testing is expensive and time-consuming. The genomic selection (GS) is a powerful tool that allows breeders to predict the performance of new hybrids in yet to observe untested environments. GS models coupled with the use of environmental covariables (ECs) have the potential to enhance selection accuracy in breeding programs. Models of GS with ECs had potential to increase the accuracy of selection of breeding program. Thus, the goals of this study were to use historical data from VCU's energy sorghum tests from the Embrapa Maize and Sorghum breeding program, associated with molecular marker data and one set of environmental covariables for the prediction of untested energy sorghum hybrids and identification. of mega environments for the cultivation of energy sorghum hybrids. Keywords: Sorghum bicolor. Breeding plants. Genomic selection.